fumiyau/python_no_comments_test10000 · Datasets at Hugging Face

f71874ea181c3b592a78cc7466c520b1e6d8934c

352

py

Python

code/examples/MotionTrackingAccelerometer.py

SaschaMzH/hucon

830b6c5e21c2c7316c61e8afdf708066374b9b62

[ "BSD-3-Clause" ]

2

2019-09-25T13:39:22.000Z

2019-09-26T10:06:13.000Z

code/examples/MotionTrackingAccelerometer.py

SaschaMzH/hucon

830b6c5e21c2c7316c61e8afdf708066374b9b62

[ "BSD-3-Clause" ]

44

2019-09-25T14:35:48.000Z

2021-08-20T17:26:12.000Z

code/examples/MotionTrackingAccelerometer.py

SaschaMzH/hucon

830b6c5e21c2c7316c61e8afdf708066374b9b62

[ "BSD-3-Clause" ]

8

2019-09-25T13:53:07.000Z

2022-02-24T19:23:44.000Z

""" Print the gyro sensor data. Copyright (C) 2019 Basler AG All rights reserved. This software may be modified and distributed under the terms of the BSD license. See the LICENSE file for details. """ from hucon import Mpu6050 mpu = None print('Get the data from the accelerometer.') mpu = Mpu6050() print(mpu.get_accel_data())

19.555556

65

0.713068

from hucon import Mpu6050 mpu = None print('Get the data from the accelerometer.') mpu = Mpu6050() print(mpu.get_accel_data())

true

f71874ed83499c32090bfa730a8893ccd3cb1572

4,292

py

Python

extract_feats/opensmile.py

ImmortalSdm/Speech-Emotion-Recognition-1

c5f766a0f66c77df30c6d75e86d97c27c2bbb240

[ "MIT" ]

1

2021-03-13T09:35:54.000Z

extract_feats/opensmile.py

Ulrica-ren/Speech-Emotion-Recognition-1

c5f766a0f66c77df30c6d75e86d97c27c2bbb240

[ "MIT" ]

null

extract_feats/opensmile.py

Ulrica-ren/Speech-Emotion-Recognition-1

c5f766a0f66c77df30c6d75e86d97c27c2bbb240

[ "MIT" ]

1

2021-03-17T10:52:26.000Z

import os import csv import sys import time import pandas as pd from sklearn.preprocessing import StandardScaler from typing import Tuple from sklearn.externals import joblib from sklearn.model_selection import train_test_split # 每个特征集的特征数量 FEATURE_NUM = { 'IS09_emotion': 384, 'IS10_paraling': 1582, 'IS11_speaker_state': 4368, 'IS12_speaker_trait': 6125, 'IS13_ComParE': 6373, 'ComParE_2016': 6373 } ''' get_feature_opensmile(): Opensmile 提取一个音频的特征输入: config(Class) file_path: 音频路径输出：该音频的特征向量 ''' def get_feature_opensmile(config, filepath: str): # 项目路径 BASE_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir)) # single_feature.csv 路径 single_feat_path = os.path.join(BASE_DIR, config.feature_path, 'single_feature.csv') # Opensmile 配置文件路径 opensmile_config_path = os.path.join(config.opensmile_path, 'config', config.opensmile_config + '.conf') # Opensmile 命令 cmd = 'cd ' + config.opensmile_path + ' && ./SMILExtract -C ' + opensmile_config_path + ' -I ' + filepath + ' -O ' + single_feat_path print("Opensmile cmd: ", cmd) os.system(cmd) reader = csv.reader(open(single_feat_path,'r')) rows = [row for row in reader] last_line = rows[-1] return last_line[1: FEATURE_NUM[config.opensmile_config] + 1] ''' load_feature(): 从 .csv 文件中加载特征数据输入: config(Class) feature_path: 特征文件路径 train: 是否为训练数据输出: 训练数据、测试数据和对应的标签 ''' def load_feature(config, feature_path: str, train: bool): # 加载特征数据 df = pd.read_csv(feature_path) features = [str(i) for i in range(1, FEATURE_NUM[config.opensmile_config] + 1)] X = df.loc[:,features].values Y = df.loc[:,'label'].values # 标准化模型路径 scaler_path = os.path.join(config.checkpoint_path, 'SCALER_OPENSMILE.m') if train == True: # 标准化数据 scaler = StandardScaler().fit(X) # 保存标准化模型 joblib.dump(scaler, scaler_path) X = scaler.transform(X) # 划分训练集和测试集 x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size = 0.2, random_state = 42) return x_train, x_test, y_train, y_test else: # 标准化数据 # 加载标准化模型 scaler = joblib.load(scaler_path) X = scaler.transform(X) return X ''' get_data(): 提取所有音频的特征: 遍历所有文件夹, 读取每个文件夹中的音频, 提取每个音频的特征，把所有特征保存在 feature_path 中输入: config(Class) data_path: 数据集文件夹/测试文件路径 feature_path: 保存特征的路径 train: 是否为训练数据输出: train = True: 训练数据、测试数据特征和对应的标签 train = False: 预测数据特征 ''' # Opensmile 提取特征 def get_data(config, data_path, feature_path: str, train: bool): writer = csv.writer(open(feature_path, 'w')) first_row = ['label'] for i in range(1, FEATURE_NUM[config.opensmile_config] + 1): first_row.append(str(i)) writer.writerow(first_row) writer = csv.writer(open(feature_path, 'a+')) print('Opensmile extracting...') if train == True: cur_dir = os.getcwd() sys.stderr.write('Curdir: %s\n' % cur_dir) os.chdir(data_path) # 遍历文件夹 for i, directory in enumerate(config.class_labels): sys.stderr.write("Started reading folder %s\n" % directory) os.chdir(directory) # label_name = directory label = config.class_labels.index(directory) # 读取该文件夹下的音频 for filename in os.listdir('.'): if not filename.endswith('wav'): continue filepath = os.path.join(os.getcwd(), filename) # 提取该音频的特征 feature_vector = get_feature_opensmile(config, filepath) feature_vector.insert(0, label) # 把每个音频的特征整理到一个 csv 文件中 writer.writerow(feature_vector) sys.stderr.write("Ended reading folder %s\n" % directory) os.chdir('..') os.chdir(cur_dir) else: feature_vector = get_feature_opensmile(config, data_path) feature_vector.insert(0, '-1') writer.writerow(feature_vector) print('Opensmile extract done.') # 一个玄学 bug 的暂时性解决方案 # 这里无法直接加载除了 IS10_paraling 以外的其他特征集的预测数据特征，非常玄学 if(train == True): return load_feature(config, feature_path, train = train)

27.164557

137

0.635368

import os import csv import sys import time import pandas as pd from sklearn.preprocessing import StandardScaler from typing import Tuple from sklearn.externals import joblib from sklearn.model_selection import train_test_split FEATURE_NUM = { 'IS09_emotion': 384, 'IS10_paraling': 1582, 'IS11_speaker_state': 4368, 'IS12_speaker_trait': 6125, 'IS13_ComParE': 6373, 'ComParE_2016': 6373 } def get_feature_opensmile(config, filepath: str): BASE_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir)) single_feat_path = os.path.join(BASE_DIR, config.feature_path, 'single_feature.csv') opensmile_config_path = os.path.join(config.opensmile_path, 'config', config.opensmile_config + '.conf') cmd = 'cd ' + config.opensmile_path + ' && ./SMILExtract -C ' + opensmile_config_path + ' -I ' + filepath + ' -O ' + single_feat_path print("Opensmile cmd: ", cmd) os.system(cmd) reader = csv.reader(open(single_feat_path,'r')) rows = [row for row in reader] last_line = rows[-1] return last_line[1: FEATURE_NUM[config.opensmile_config] + 1] def load_feature(config, feature_path: str, train: bool): df = pd.read_csv(feature_path) features = [str(i) for i in range(1, FEATURE_NUM[config.opensmile_config] + 1)] X = df.loc[:,features].values Y = df.loc[:,'label'].values scaler_path = os.path.join(config.checkpoint_path, 'SCALER_OPENSMILE.m') if train == True: scaler = StandardScaler().fit(X) joblib.dump(scaler, scaler_path) X = scaler.transform(X) x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size = 0.2, random_state = 42) return x_train, x_test, y_train, y_test else: scaler = joblib.load(scaler_path) X = scaler.transform(X) return X def get_data(config, data_path, feature_path: str, train: bool): writer = csv.writer(open(feature_path, 'w')) first_row = ['label'] for i in range(1, FEATURE_NUM[config.opensmile_config] + 1): first_row.append(str(i)) writer.writerow(first_row) writer = csv.writer(open(feature_path, 'a+')) print('Opensmile extracting...') if train == True: cur_dir = os.getcwd() sys.stderr.write('Curdir: %s\n' % cur_dir) os.chdir(data_path) for i, directory in enumerate(config.class_labels): sys.stderr.write("Started reading folder %s\n" % directory) os.chdir(directory) label = config.class_labels.index(directory) for filename in os.listdir('.'): if not filename.endswith('wav'): continue filepath = os.path.join(os.getcwd(), filename) feature_vector = get_feature_opensmile(config, filepath) feature_vector.insert(0, label) writer.writerow(feature_vector) sys.stderr.write("Ended reading folder %s\n" % directory) os.chdir('..') os.chdir(cur_dir) else: feature_vector = get_feature_opensmile(config, data_path) feature_vector.insert(0, '-1') writer.writerow(feature_vector) print('Opensmile extract done.') if(train == True): return load_feature(config, feature_path, train = train)

true

f7187653a74f7b01dca4f137c868aa88c9f636ab

20,547

py

Python

elasticapm/base.py

mvas/apm-agent-python

f4582e90eb5308b915ca51e2e98620fc22af09ec

[ "BSD-3-Clause" ]

null

elasticapm/base.py

mvas/apm-agent-python

f4582e90eb5308b915ca51e2e98620fc22af09ec

[ "BSD-3-Clause" ]

null

elasticapm/base.py

mvas/apm-agent-python

f4582e90eb5308b915ca51e2e98620fc22af09ec

[ "BSD-3-Clause" ]

null

""" elasticapm.base ~~~~~~~~~~ :copyright: (c) 2011-2017 Elasticsearch Large portions are :copyright: (c) 2010 by the Sentry Team, see AUTHORS for more details. :license: BSD, see LICENSE for more details. """ from __future__ import absolute_import import datetime import logging import os import platform import socket import sys import threading import time import zlib from copy import deepcopy import elasticapm from elasticapm.conf import Config, constants from elasticapm.traces import TransactionsStore, get_transaction from elasticapm.transport.base import TransportException from elasticapm.utils import compat, is_master_process from elasticapm.utils import json_encoder as json from elasticapm.utils import stacks, varmap from elasticapm.utils.encoding import keyword_field, shorten, transform from elasticapm.utils.module_import import import_string __all__ = ('Client',) class ClientState(object): ONLINE = 1 ERROR = 0 def __init__(self): self.status = self.ONLINE self.last_check = None self.retry_number = 0 def should_try(self): if self.status == self.ONLINE: return True interval = min(self.retry_number, 6) ** 2 if time.time() - self.last_check > interval: return True return False def set_fail(self): self.status = self.ERROR self.retry_number += 1 self.last_check = time.time() def set_success(self): self.status = self.ONLINE self.last_check = None self.retry_number = 0 def did_fail(self): return self.status == self.ERROR class Client(object): """ The base ElasticAPM client, which handles communication over the HTTP API to the APM Server. Will read default configuration from the environment variable ``ELASTIC_APM_APP_NAME`` and ``ELASTIC_APM_SECRET_TOKEN`` if available. :: >>> from elasticapm import Client >>> # Read configuration from environment >>> client = Client() >>> # Configure the client manually >>> client = Client( >>> include_paths=['my.package'], >>> service_name='myapp', >>> secret_token='secret_token', >>> ) >>> # Record an exception >>> try: >>> 1/0 >>> except ZeroDivisionError: >>> ident = client.capture_exception() >>> print ("Exception caught; reference is %%s" %% ident) """ logger = logging.getLogger('elasticapm') def __init__(self, config=None, **defaults): # configure loggers first cls = self.__class__ self.logger = logging.getLogger('%s.%s' % (cls.__module__, cls.__name__)) self.error_logger = logging.getLogger('elasticapm.errors') self.state = ClientState() self.instrumentation_store = None self.processors = [] self.filter_exception_types_dict = {} self._send_timer = None self._transports = {} self._service_info = None self.config = Config(config, default_dict=defaults) if self.config.errors: for msg in self.config.errors.values(): self.error_logger.error(msg) self.config.disable_send = True return self._transport_class = import_string(self.config.transport_class) for exc_to_filter in (self.config.filter_exception_types or []): exc_to_filter_type = exc_to_filter.split(".")[-1] exc_to_filter_module = ".".join(exc_to_filter.split(".")[:-1]) self.filter_exception_types_dict[exc_to_filter_type] = exc_to_filter_module self.processors = [import_string(p) for p in self.config.processors] if self.config.processors else [] if platform.python_implementation() == 'PyPy': # PyPy introduces a `_functools.partial.__call__` frame due to our use # of `partial` in AbstractInstrumentedModule skip_modules = ('elasticapm.', '_functools') else: skip_modules = ('elasticapm.',) def frames_collector_func(): return self._get_stack_info_for_trace( stacks.iter_stack_frames(skip_top_modules=skip_modules), library_frame_context_lines=self.config.source_lines_span_library_frames, in_app_frame_context_lines=self.config.source_lines_span_app_frames, with_locals=self.config.collect_local_variables in ('all', 'transactions'), locals_processor_func=lambda local_var: varmap(lambda k, v: shorten( v, list_length=self.config.local_var_list_max_length, string_length=self.config.local_var_max_length, ), local_var) ) self.instrumentation_store = TransactionsStore( frames_collector_func=frames_collector_func, collect_frequency=self.config.flush_interval, sample_rate=self.config.transaction_sample_rate, max_spans=self.config.transaction_max_spans, span_frames_min_duration=self.config.span_frames_min_duration_ms, max_queue_size=self.config.max_queue_size, ignore_patterns=self.config.transactions_ignore_patterns, ) self.include_paths_re = stacks.get_path_regex(self.config.include_paths) if self.config.include_paths else None self.exclude_paths_re = stacks.get_path_regex(self.config.exclude_paths) if self.config.exclude_paths else None compat.atexit_register(self.close) def get_handler(self, name): return import_string(name) def capture(self, event_type, date=None, context=None, custom=None, stack=None, handled=True, **kwargs): """ Captures and processes an event and pipes it off to Client.send. """ if event_type == 'Exception': # never gather log stack for exceptions stack = False data = self._build_msg_for_logging(event_type, date=date, context=context, custom=custom, stack=stack, handled=handled, **kwargs) if data: url = self.config.server_url + constants.ERROR_API_PATH self.send(url, **data) return data['errors'][0]['id'] def capture_message(self, message=None, param_message=None, **kwargs): """ Creates an event from ``message``. >>> client.capture_message('My event just happened!') """ return self.capture('Message', message=message, param_message=param_message, **kwargs) def capture_exception(self, exc_info=None, handled=True, **kwargs): """ Creates an event from an exception. >>> try: >>> exc_info = sys.exc_info() >>> client.capture_exception(exc_info) >>> finally: >>> del exc_info If exc_info is not provided, or is set to True, then this method will perform the ``exc_info = sys.exc_info()`` and the requisite clean-up for you. """ return self.capture('Exception', exc_info=exc_info, handled=handled, **kwargs) def send(self, url, **data): """ Encodes and sends data to remote URL using configured transport :param url: URL of endpoint :param data: dictionary of data to send """ if self.config.disable_send or self._filter_exception_type(data): return payload = self.encode(data) headers = { 'Content-Type': 'application/json', 'Content-Encoding': 'deflate', 'User-Agent': 'elasticapm-python/%s' % elasticapm.VERSION, } if self.config.secret_token: headers['Authorization'] = "Bearer %s" % self.config.secret_token if not self.state.should_try(): message = self._get_log_message(payload) self.error_logger.error(message) return try: self._send_remote(url=url, data=payload, headers=headers) except Exception as e: self.handle_transport_fail(exception=e) def encode(self, data): """ Serializes ``data`` into a raw string. """ return zlib.compress(json.dumps(data).encode('utf8')) def decode(self, data): """ Unserializes a string, ``data``. """ return json.loads(zlib.decompress(data).decode('utf8')) def begin_transaction(self, transaction_type): """Register the start of a transaction on the client """ return self.instrumentation_store.begin_transaction(transaction_type) def end_transaction(self, name, result=''): transaction = self.instrumentation_store.end_transaction(result, name) if self.instrumentation_store.should_collect(): self._collect_transactions() if not self._send_timer: # send first batch of data after config._wait_to_first_send self._start_send_timer(timeout=min(self.config._wait_to_first_send, self.config.flush_interval)) return transaction def close(self): self._collect_transactions() if self._send_timer: self._stop_send_timer() for url, transport in list(self._transports.items()): transport.close() self._transports.pop(url) def handle_transport_success(self, **kwargs): """ Success handler called by the transport """ if kwargs.get('url'): self.logger.info('Logged error at ' + kwargs['url']) self.state.set_success() def handle_transport_fail(self, exception=None, **kwargs): """ Failure handler called by the transport """ if isinstance(exception, TransportException): message = self._get_log_message(exception.data) self.error_logger.error(exception.args[0]) else: # stdlib exception message = str(exception) self.error_logger.error( 'Failed to submit message: %r', message, exc_info=getattr(exception, 'print_trace', True) ) self.state.set_fail() def _collect_transactions(self): self._stop_send_timer() transactions = [] if self.instrumentation_store: for transaction in self.instrumentation_store.get_all(): for processor in self.processors: transaction = processor(self, transaction) transactions.append(transaction) if not transactions: return data = self._build_msg({ 'transactions': transactions, }) api_path = constants.TRANSACTIONS_API_PATH self.send(self.config.server_url + api_path, **data) self._start_send_timer() def _start_send_timer(self, timeout=None): timeout = timeout or self.config.flush_interval self._send_timer = threading.Timer(timeout, self._collect_transactions) self._send_timer.start() def _stop_send_timer(self): if self._send_timer and self._send_timer.is_alive() and not self._send_timer == threading.current_thread(): self._send_timer.cancel() self._send_timer.join() def _send_remote(self, url, data, headers=None): if headers is None: headers = {} parsed = compat.urlparse.urlparse(url) transport = self._get_transport(parsed) if transport.async_mode: transport.send_async( data, headers, success_callback=self.handle_transport_success, fail_callback=self.handle_transport_fail ) else: url = transport.send(data, headers, timeout=self.config.server_timeout) self.handle_transport_success(url=url) def get_service_info(self): if self._service_info: return self._service_info language_version = platform.python_version() if hasattr(sys, 'pypy_version_info'): runtime_version = '.'.join(map(str, sys.pypy_version_info[:3])) else: runtime_version = language_version result = { 'name': keyword_field(self.config.service_name), 'environment': keyword_field(self.config.environment), 'version': keyword_field(self.config.service_version), 'agent': { 'name': 'python', 'version': elasticapm.VERSION, }, 'language': { 'name': 'python', 'version': keyword_field(platform.python_version()), }, 'runtime': { 'name': keyword_field(platform.python_implementation()), 'version': keyword_field(runtime_version), } } if self.config.framework_name: result['framework'] = { 'name': keyword_field(self.config.framework_name), 'version': keyword_field(self.config.framework_version), } self._service_info = result return result def get_process_info(self): return { 'pid': os.getpid(), 'ppid': os.getppid() if hasattr(os, 'getppid') else None, 'argv': sys.argv, 'title': None, # Note: if we implement this, the value needs to be wrapped with keyword_field } def get_system_info(self): return { 'hostname': keyword_field(socket.gethostname()), 'architecture': platform.machine(), 'platform': platform.system().lower(), } def _build_msg(self, data=None, **kwargs): data = data or {} data['service'] = self.get_service_info() data['process'] = self.get_process_info() data['system'] = self.get_system_info() data.update(**kwargs) return data def _build_msg_for_logging(self, event_type, date=None, context=None, custom=None, stack=None, handled=True, **kwargs): """ Captures, processes and serializes an event into a dict object """ transaction = get_transaction() if transaction: transaction_context = deepcopy(transaction.context) else: transaction_context = {} event_data = {} if custom is None: custom = {} if not date: date = datetime.datetime.utcnow() if stack is None: stack = self.config.auto_log_stacks if context: transaction_context.update(context) context = transaction_context else: context = transaction_context event_data['context'] = context if transaction and transaction.tags: context['tags'] = deepcopy(transaction.tags) # if '.' not in event_type: # Assume it's a builtin event_type = 'elasticapm.events.%s' % event_type handler = self.get_handler(event_type) result = handler.capture(self, **kwargs) if self._filter_exception_type(result): return # data (explicit) culprit takes over auto event detection culprit = result.pop('culprit', None) if custom.get('culprit'): culprit = custom.pop('culprit') for k, v in compat.iteritems(result): if k not in event_data: event_data[k] = v log = event_data.get('log', {}) if stack and 'stacktrace' not in log: if stack is True: frames = stacks.iter_stack_frames(skip=3) else: frames = stack frames = stacks.get_stack_info( frames, with_locals=self.config.collect_local_variables in ('errors', 'all'), library_frame_context_lines=self.config.source_lines_error_library_frames, in_app_frame_context_lines=self.config.source_lines_error_app_frames, include_paths_re=self.include_paths_re, exclude_paths_re=self.exclude_paths_re, locals_processor_func=lambda local_var: varmap(lambda k, v: shorten( v, list_length=self.config.local_var_list_max_length, string_length=self.config.local_var_max_length, ), local_var) ) log['stacktrace'] = frames if 'stacktrace' in log and not culprit: culprit = stacks.get_culprit( log['stacktrace'], self.config.include_paths, self.config.exclude_paths ) if 'level' in log and isinstance(log['level'], compat.integer_types): log['level'] = logging.getLevelName(log['level']).lower() if log: event_data['log'] = log if culprit: event_data['culprit'] = culprit if 'custom' in context: context['custom'].update(custom) else: context['custom'] = custom # Run the data through processors for processor in self.processors: event_data = processor(self, event_data) # Make sure all data is coerced event_data = transform(event_data) if 'exception' in event_data: event_data['exception']['handled'] = bool(handled) event_data.update({ 'timestamp': date.strftime(constants.TIMESTAMP_FORMAT), }) transaction = get_transaction() if transaction: event_data['transaction'] = {'id': transaction.id} return self._build_msg({'errors': [event_data]}) def _filter_exception_type(self, data): exception = data.get('exception') if not exception: return False exc_type = exception.get('type') exc_module = exception.get('module') if exc_module == 'None': exc_module = None if exc_type in self.filter_exception_types_dict: exc_to_filter_module = self.filter_exception_types_dict[exc_type] if not exc_to_filter_module or exc_to_filter_module == exc_module: if exc_module: exc_name = '%s.%s' % (exc_module, exc_type) else: exc_name = exc_type self.logger.info( 'Ignored %s exception due to exception type filter', exc_name ) return True return False def _get_log_message(self, data): # decode message so we can show the actual event try: data = self.decode(data) except Exception: message = '<failed decoding data>' else: message = data.pop('message', '<no message value>') return message def _get_transport(self, parsed_url): if hasattr(self._transport_class, 'sync_transport') and is_master_process(): # when in the master process, always use SYNC mode. This avoids # the danger of being forked into an inconsistent threading state self.logger.info('Sending message synchronously while in master ' 'process. PID: %s', os.getpid()) return self._transport_class.sync_transport(parsed_url) if parsed_url not in self._transports: self._transports[parsed_url] = self._transport_class( parsed_url, verify_server_cert=self.config.verify_server_cert ) return self._transports[parsed_url] def _get_stack_info_for_trace(self, frames, library_frame_context_lines=None, in_app_frame_context_lines=None, with_locals=True, locals_processor_func=None): """Overrideable in derived clients to add frames/info, e.g. templates""" return stacks.get_stack_info( frames, library_frame_context_lines=library_frame_context_lines, in_app_frame_context_lines=in_app_frame_context_lines, with_locals=with_locals, include_paths_re=self.include_paths_re, exclude_paths_re=self.exclude_paths_re, locals_processor_func=locals_processor_func, ) class DummyClient(Client): """Sends messages into an empty void""" def send(self, url, **kwargs): return None

36.174296

119

0.609627

from __future__ import absolute_import import datetime import logging import os import platform import socket import sys import threading import time import zlib from copy import deepcopy import elasticapm from elasticapm.conf import Config, constants from elasticapm.traces import TransactionsStore, get_transaction from elasticapm.transport.base import TransportException from elasticapm.utils import compat, is_master_process from elasticapm.utils import json_encoder as json from elasticapm.utils import stacks, varmap from elasticapm.utils.encoding import keyword_field, shorten, transform from elasticapm.utils.module_import import import_string __all__ = ('Client',) class ClientState(object): ONLINE = 1 ERROR = 0 def __init__(self): self.status = self.ONLINE self.last_check = None self.retry_number = 0 def should_try(self): if self.status == self.ONLINE: return True interval = min(self.retry_number, 6) ** 2 if time.time() - self.last_check > interval: return True return False def set_fail(self): self.status = self.ERROR self.retry_number += 1 self.last_check = time.time() def set_success(self): self.status = self.ONLINE self.last_check = None self.retry_number = 0 def did_fail(self): return self.status == self.ERROR class Client(object): logger = logging.getLogger('elasticapm') def __init__(self, config=None, **defaults): cls = self.__class__ self.logger = logging.getLogger('%s.%s' % (cls.__module__, cls.__name__)) self.error_logger = logging.getLogger('elasticapm.errors') self.state = ClientState() self.instrumentation_store = None self.processors = [] self.filter_exception_types_dict = {} self._send_timer = None self._transports = {} self._service_info = None self.config = Config(config, default_dict=defaults) if self.config.errors: for msg in self.config.errors.values(): self.error_logger.error(msg) self.config.disable_send = True return self._transport_class = import_string(self.config.transport_class) for exc_to_filter in (self.config.filter_exception_types or []): exc_to_filter_type = exc_to_filter.split(".")[-1] exc_to_filter_module = ".".join(exc_to_filter.split(".")[:-1]) self.filter_exception_types_dict[exc_to_filter_type] = exc_to_filter_module self.processors = [import_string(p) for p in self.config.processors] if self.config.processors else [] if platform.python_implementation() == 'PyPy': skip_modules = ('elasticapm.', '_functools') else: skip_modules = ('elasticapm.',) def frames_collector_func(): return self._get_stack_info_for_trace( stacks.iter_stack_frames(skip_top_modules=skip_modules), library_frame_context_lines=self.config.source_lines_span_library_frames, in_app_frame_context_lines=self.config.source_lines_span_app_frames, with_locals=self.config.collect_local_variables in ('all', 'transactions'), locals_processor_func=lambda local_var: varmap(lambda k, v: shorten( v, list_length=self.config.local_var_list_max_length, string_length=self.config.local_var_max_length, ), local_var) ) self.instrumentation_store = TransactionsStore( frames_collector_func=frames_collector_func, collect_frequency=self.config.flush_interval, sample_rate=self.config.transaction_sample_rate, max_spans=self.config.transaction_max_spans, span_frames_min_duration=self.config.span_frames_min_duration_ms, max_queue_size=self.config.max_queue_size, ignore_patterns=self.config.transactions_ignore_patterns, ) self.include_paths_re = stacks.get_path_regex(self.config.include_paths) if self.config.include_paths else None self.exclude_paths_re = stacks.get_path_regex(self.config.exclude_paths) if self.config.exclude_paths else None compat.atexit_register(self.close) def get_handler(self, name): return import_string(name) def capture(self, event_type, date=None, context=None, custom=None, stack=None, handled=True, **kwargs): if event_type == 'Exception': stack = False data = self._build_msg_for_logging(event_type, date=date, context=context, custom=custom, stack=stack, handled=handled, **kwargs) if data: url = self.config.server_url + constants.ERROR_API_PATH self.send(url, **data) return data['errors'][0]['id'] def capture_message(self, message=None, param_message=None, **kwargs): return self.capture('Message', message=message, param_message=param_message, **kwargs) def capture_exception(self, exc_info=None, handled=True, **kwargs): return self.capture('Exception', exc_info=exc_info, handled=handled, **kwargs) def send(self, url, **data): if self.config.disable_send or self._filter_exception_type(data): return payload = self.encode(data) headers = { 'Content-Type': 'application/json', 'Content-Encoding': 'deflate', 'User-Agent': 'elasticapm-python/%s' % elasticapm.VERSION, } if self.config.secret_token: headers['Authorization'] = "Bearer %s" % self.config.secret_token if not self.state.should_try(): message = self._get_log_message(payload) self.error_logger.error(message) return try: self._send_remote(url=url, data=payload, headers=headers) except Exception as e: self.handle_transport_fail(exception=e) def encode(self, data): return zlib.compress(json.dumps(data).encode('utf8')) def decode(self, data): return json.loads(zlib.decompress(data).decode('utf8')) def begin_transaction(self, transaction_type): return self.instrumentation_store.begin_transaction(transaction_type) def end_transaction(self, name, result=''): transaction = self.instrumentation_store.end_transaction(result, name) if self.instrumentation_store.should_collect(): self._collect_transactions() if not self._send_timer: self._start_send_timer(timeout=min(self.config._wait_to_first_send, self.config.flush_interval)) return transaction def close(self): self._collect_transactions() if self._send_timer: self._stop_send_timer() for url, transport in list(self._transports.items()): transport.close() self._transports.pop(url) def handle_transport_success(self, **kwargs): if kwargs.get('url'): self.logger.info('Logged error at ' + kwargs['url']) self.state.set_success() def handle_transport_fail(self, exception=None, **kwargs): if isinstance(exception, TransportException): message = self._get_log_message(exception.data) self.error_logger.error(exception.args[0]) else: message = str(exception) self.error_logger.error( 'Failed to submit message: %r', message, exc_info=getattr(exception, 'print_trace', True) ) self.state.set_fail() def _collect_transactions(self): self._stop_send_timer() transactions = [] if self.instrumentation_store: for transaction in self.instrumentation_store.get_all(): for processor in self.processors: transaction = processor(self, transaction) transactions.append(transaction) if not transactions: return data = self._build_msg({ 'transactions': transactions, }) api_path = constants.TRANSACTIONS_API_PATH self.send(self.config.server_url + api_path, **data) self._start_send_timer() def _start_send_timer(self, timeout=None): timeout = timeout or self.config.flush_interval self._send_timer = threading.Timer(timeout, self._collect_transactions) self._send_timer.start() def _stop_send_timer(self): if self._send_timer and self._send_timer.is_alive() and not self._send_timer == threading.current_thread(): self._send_timer.cancel() self._send_timer.join() def _send_remote(self, url, data, headers=None): if headers is None: headers = {} parsed = compat.urlparse.urlparse(url) transport = self._get_transport(parsed) if transport.async_mode: transport.send_async( data, headers, success_callback=self.handle_transport_success, fail_callback=self.handle_transport_fail ) else: url = transport.send(data, headers, timeout=self.config.server_timeout) self.handle_transport_success(url=url) def get_service_info(self): if self._service_info: return self._service_info language_version = platform.python_version() if hasattr(sys, 'pypy_version_info'): runtime_version = '.'.join(map(str, sys.pypy_version_info[:3])) else: runtime_version = language_version result = { 'name': keyword_field(self.config.service_name), 'environment': keyword_field(self.config.environment), 'version': keyword_field(self.config.service_version), 'agent': { 'name': 'python', 'version': elasticapm.VERSION, }, 'language': { 'name': 'python', 'version': keyword_field(platform.python_version()), }, 'runtime': { 'name': keyword_field(platform.python_implementation()), 'version': keyword_field(runtime_version), } } if self.config.framework_name: result['framework'] = { 'name': keyword_field(self.config.framework_name), 'version': keyword_field(self.config.framework_version), } self._service_info = result return result def get_process_info(self): return { 'pid': os.getpid(), 'ppid': os.getppid() if hasattr(os, 'getppid') else None, 'argv': sys.argv, 'title': None, } def get_system_info(self): return { 'hostname': keyword_field(socket.gethostname()), 'architecture': platform.machine(), 'platform': platform.system().lower(), } def _build_msg(self, data=None, **kwargs): data = data or {} data['service'] = self.get_service_info() data['process'] = self.get_process_info() data['system'] = self.get_system_info() data.update(**kwargs) return data def _build_msg_for_logging(self, event_type, date=None, context=None, custom=None, stack=None, handled=True, **kwargs): transaction = get_transaction() if transaction: transaction_context = deepcopy(transaction.context) else: transaction_context = {} event_data = {} if custom is None: custom = {} if not date: date = datetime.datetime.utcnow() if stack is None: stack = self.config.auto_log_stacks if context: transaction_context.update(context) context = transaction_context else: context = transaction_context event_data['context'] = context if transaction and transaction.tags: context['tags'] = deepcopy(transaction.tags) event_type = 'elasticapm.events.%s' % event_type handler = self.get_handler(event_type) result = handler.capture(self, **kwargs) if self._filter_exception_type(result): return # data (explicit) culprit takes over auto event detection culprit = result.pop('culprit', None) if custom.get('culprit'): culprit = custom.pop('culprit') for k, v in compat.iteritems(result): if k not in event_data: event_data[k] = v log = event_data.get('log', {}) if stack and 'stacktrace' not in log: if stack is True: frames = stacks.iter_stack_frames(skip=3) else: frames = stack frames = stacks.get_stack_info( frames, with_locals=self.config.collect_local_variables in ('errors', 'all'), library_frame_context_lines=self.config.source_lines_error_library_frames, in_app_frame_context_lines=self.config.source_lines_error_app_frames, include_paths_re=self.include_paths_re, exclude_paths_re=self.exclude_paths_re, locals_processor_func=lambda local_var: varmap(lambda k, v: shorten( v, list_length=self.config.local_var_list_max_length, string_length=self.config.local_var_max_length, ), local_var) ) log['stacktrace'] = frames if 'stacktrace' in log and not culprit: culprit = stacks.get_culprit( log['stacktrace'], self.config.include_paths, self.config.exclude_paths ) if 'level' in log and isinstance(log['level'], compat.integer_types): log['level'] = logging.getLevelName(log['level']).lower() if log: event_data['log'] = log if culprit: event_data['culprit'] = culprit if 'custom' in context: context['custom'].update(custom) else: context['custom'] = custom # Run the data through processors for processor in self.processors: event_data = processor(self, event_data) # Make sure all data is coerced event_data = transform(event_data) if 'exception' in event_data: event_data['exception']['handled'] = bool(handled) event_data.update({ 'timestamp': date.strftime(constants.TIMESTAMP_FORMAT), }) transaction = get_transaction() if transaction: event_data['transaction'] = {'id': transaction.id} return self._build_msg({'errors': [event_data]}) def _filter_exception_type(self, data): exception = data.get('exception') if not exception: return False exc_type = exception.get('type') exc_module = exception.get('module') if exc_module == 'None': exc_module = None if exc_type in self.filter_exception_types_dict: exc_to_filter_module = self.filter_exception_types_dict[exc_type] if not exc_to_filter_module or exc_to_filter_module == exc_module: if exc_module: exc_name = '%s.%s' % (exc_module, exc_type) else: exc_name = exc_type self.logger.info( 'Ignored %s exception due to exception type filter', exc_name ) return True return False def _get_log_message(self, data): # decode message so we can show the actual event try: data = self.decode(data) except Exception: message = '<failed decoding data>' else: message = data.pop('message', '<no message value>') return message def _get_transport(self, parsed_url): if hasattr(self._transport_class, 'sync_transport') and is_master_process(): # when in the master process, always use SYNC mode. This avoids # the danger of being forked into an inconsistent threading state self.logger.info('Sending message synchronously while in master ' 'process. PID: %s', os.getpid()) return self._transport_class.sync_transport(parsed_url) if parsed_url not in self._transports: self._transports[parsed_url] = self._transport_class( parsed_url, verify_server_cert=self.config.verify_server_cert ) return self._transports[parsed_url] def _get_stack_info_for_trace(self, frames, library_frame_context_lines=None, in_app_frame_context_lines=None, with_locals=True, locals_processor_func=None): return stacks.get_stack_info( frames, library_frame_context_lines=library_frame_context_lines, in_app_frame_context_lines=in_app_frame_context_lines, with_locals=with_locals, include_paths_re=self.include_paths_re, exclude_paths_re=self.exclude_paths_re, locals_processor_func=locals_processor_func, ) class DummyClient(Client): def send(self, url, **kwargs): return None

true

f7187739be7c1360375442537af54f3bec58e630

7,993

py

Python

YoloV3_ezhirko/detect.py

eva5covergence/EVA5_AI_Projects

7052373c52b6b9901cd0bc05a4758dd4b63f7480

[ "MIT" ]

null

YoloV3_ezhirko/detect.py

eva5covergence/EVA5_AI_Projects

7052373c52b6b9901cd0bc05a4758dd4b63f7480

[ "MIT" ]

null

YoloV3_ezhirko/detect.py

eva5covergence/EVA5_AI_Projects

7052373c52b6b9901cd0bc05a4758dd4b63f7480

[ "MIT" ]

2

2021-07-25T10:24:11.000Z

2021-08-13T09:23:30.000Z

import argparse from sys import platform from models import * # set ONNX_EXPORT in models.py from utils.datasets import * from utils.utils import * def detect(save_img=False): img_size = (320, 192) if ONNX_EXPORT else opt.img_size # (320, 192) or (416, 256) or (608, 352) for (height, width) out, source, weights, half, view_img, save_txt = opt.output, opt.source, opt.weights, opt.half, opt.view_img, opt.save_txt webcam = source == '0' or source.startswith('rtsp') or source.startswith('http') or source.endswith('.txt') # Initialize device = torch_utils.select_device(device='cpu' if ONNX_EXPORT else opt.device) if os.path.exists(out): shutil.rmtree(out) # delete output folder os.makedirs(out) # make new output folder # Initialize model model = Darknet(opt.cfg, img_size) # Load weights attempt_download(weights) if weights.endswith('.pt'): # pytorch format model.load_state_dict(torch.load(weights, map_location=device)['model']) else: # darknet format load_darknet_weights(model, weights) # Second-stage classifier classify = False if classify: modelc = torch_utils.load_classifier(name='resnet101', n=2) # initialize modelc.load_state_dict(torch.load('weights/resnet101.pt', map_location=device)['model']) # load weights modelc.to(device).eval() # Eval mode model.to(device).eval() # Fuse Conv2d + BatchNorm2d layers # model.fuse() # Export mode if ONNX_EXPORT: model.fuse() img = torch.zeros((1, 3) + img_size) # (1, 3, 320, 192) f = opt.weights.replace(opt.weights.split('.')[-1], 'onnx') # *.onnx filename torch.onnx.export(model, img, f, verbose=False, opset_version=11) # Validate exported model import onnx model = onnx.load(f) # Load the ONNX model onnx.checker.check_model(model) # Check that the IR is well formed print(onnx.helper.printable_graph(model.graph)) # Print a human readable representation of the graph return # Half precision half = half and device.type != 'cpu' # half precision only supported on CUDA if half: model.half() # Set Dataloader vid_path, vid_writer = None, None if webcam: view_img = True torch.backends.cudnn.benchmark = True # set True to speed up constant image size inference dataset = LoadStreams(source, img_size=img_size) else: save_img = True dataset = LoadImages(source, img_size=img_size) # Get names and colors names = load_classes(opt.names) colors = [[random.randint(0, 255) for _ in range(3)] for _ in range(len(names))] # Run inference t0 = time.time() _ = model(torch.zeros((1, 3, img_size, img_size), device=device)) if device.type != 'cpu' else None # run once for path, img, im0s, vid_cap in dataset: img = torch.from_numpy(img).to(device) img = img.half() if half else img.float() # uint8 to fp16/32 img /= 255.0 # 0 - 255 to 0.0 - 1.0 if img.ndimension() == 3: img = img.unsqueeze(0) # Inference t1 = torch_utils.time_synchronized() pred = model(img, augment=opt.augment)[0] t2 = torch_utils.time_synchronized() # to float if half: pred = pred.float() # Apply NMS pred = non_max_suppression(pred, opt.conf_thres, opt.iou_thres, multi_label=False, classes=opt.classes, agnostic=opt.agnostic_nms) # Apply Classifier if classify: pred = apply_classifier(pred, modelc, img, im0s) # Process detections for i, det in enumerate(pred): # detections per image if webcam: # batch_size >= 1 p, s, im0 = path[i], '%g: ' % i, im0s[i] else: p, s, im0 = path, '', im0s save_path = str(Path(out) / Path(p).name) s += '%gx%g ' % img.shape[2:] # print string if det is not None and len(det): # Rescale boxes from img_size to im0 size det[:, :4] = scale_coords(img.shape[2:], det[:, :4], im0.shape).round() # Print results for c in det[:, -1].unique(): n = (det[:, -1] == c).sum() # detections per class s += '%g %ss, ' % (n, names[int(c)]) # add to string # Write results for *xyxy, conf, cls in det: if save_txt: # Write to file with open(save_path + '.txt', 'a') as file: file.write(('%g ' * 6 + '\n') % (*xyxy, cls, conf)) if save_img or view_img: # Add bbox to image label = '%s %.2f' % (names[int(cls)], conf) plot_one_box(xyxy, im0, label=label, color=colors[int(cls)]) # Print time (inference + NMS) print('%sDone. (%.3fs)' % (s, t2 - t1)) # Stream results if view_img: cv2.imshow(p, im0) if cv2.waitKey(1) == ord('q'): # q to quit raise StopIteration # Save results (image with detections) if save_img: if dataset.mode == 'images': cv2.imwrite(save_path, im0) else: if vid_path != save_path: # new video vid_path = save_path if isinstance(vid_writer, cv2.VideoWriter): vid_writer.release() # release previous video writer fps = vid_cap.get(cv2.CAP_PROP_FPS) w = int(vid_cap.get(cv2.CAP_PROP_FRAME_WIDTH)) h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) vid_writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*opt.fourcc), fps, (w, h)) vid_writer.write(im0) if save_txt or save_img: print('Results saved to %s' % os.getcwd() + os.sep + out) if platform == 'darwin': # MacOS os.system('open ' + out + ' ' + save_path) print('Done. (%.3fs)' % (time.time() - t0)) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--cfg', type=str, default='cfg/yolov3-custom.cfg', help='*.cfg path') parser.add_argument('--names', type=str, default='data/customdata/custom.names', help='*.names path') parser.add_argument('--weights', type=str, default='weights/last.pt', help='weights path') parser.add_argument('--source', type=str, default='data/customdata/images', help='source') # input file/folder, 0 for webcam parser.add_argument('--output', type=str, default='output', help='output folder') # output folder parser.add_argument('--img-size', type=int, default=512, help='inference size (pixels)') parser.add_argument('--conf-thres', type=float, default=0.3, help='object confidence threshold') parser.add_argument('--iou-thres', type=float, default=0.6, help='IOU threshold for NMS') parser.add_argument('--fourcc', type=str, default='mp4v', help='output video codec (verify ffmpeg support)') parser.add_argument('--half', action='store_true', help='half precision FP16 inference') parser.add_argument('--device', default='', help='device id (i.e. 0 or 0,1) or cpu') parser.add_argument('--view-img', action='store_true', help='display results') parser.add_argument('--save-txt', action='store_true', help='save results to *.txt') parser.add_argument('--classes', nargs='+', type=int, help='filter by class') parser.add_argument('--agnostic-nms', action='store_true', help='class-agnostic NMS') parser.add_argument('--augment', action='store_true', help='augmented inference') opt = parser.parse_args() print(opt) with torch.no_grad(): detect()

42.743316

129

0.588515

import argparse from sys import platform from models import * from utils.datasets import * from utils.utils import * def detect(save_img=False): img_size = (320, 192) if ONNX_EXPORT else opt.img_size out, source, weights, half, view_img, save_txt = opt.output, opt.source, opt.weights, opt.half, opt.view_img, opt.save_txt webcam = source == '0' or source.startswith('rtsp') or source.startswith('http') or source.endswith('.txt') device = torch_utils.select_device(device='cpu' if ONNX_EXPORT else opt.device) if os.path.exists(out): shutil.rmtree(out) os.makedirs(out) model = Darknet(opt.cfg, img_size) attempt_download(weights) if weights.endswith('.pt'): model.load_state_dict(torch.load(weights, map_location=device)['model']) else: load_darknet_weights(model, weights) classify = False if classify: modelc = torch_utils.load_classifier(name='resnet101', n=2) modelc.load_state_dict(torch.load('weights/resnet101.pt', map_location=device)['model']) modelc.to(device).eval() model.to(device).eval() if ONNX_EXPORT: model.fuse() img = torch.zeros((1, 3) + img_size) f = opt.weights.replace(opt.weights.split('.')[-1], 'onnx') torch.onnx.export(model, img, f, verbose=False, opset_version=11) import onnx model = onnx.load(f) onnx.checker.check_model(model) print(onnx.helper.printable_graph(model.graph)) return half = half and device.type != 'cpu' if half: model.half() vid_path, vid_writer = None, None if webcam: view_img = True torch.backends.cudnn.benchmark = True dataset = LoadStreams(source, img_size=img_size) else: save_img = True dataset = LoadImages(source, img_size=img_size) names = load_classes(opt.names) colors = [[random.randint(0, 255) for _ in range(3)] for _ in range(len(names))] t0 = time.time() _ = model(torch.zeros((1, 3, img_size, img_size), device=device)) if device.type != 'cpu' else None for path, img, im0s, vid_cap in dataset: img = torch.from_numpy(img).to(device) img = img.half() if half else img.float() img /= 255.0 if img.ndimension() == 3: img = img.unsqueeze(0) t1 = torch_utils.time_synchronized() pred = model(img, augment=opt.augment)[0] t2 = torch_utils.time_synchronized() if half: pred = pred.float() pred = non_max_suppression(pred, opt.conf_thres, opt.iou_thres, multi_label=False, classes=opt.classes, agnostic=opt.agnostic_nms) if classify: pred = apply_classifier(pred, modelc, img, im0s) for i, det in enumerate(pred): if webcam: p, s, im0 = path[i], '%g: ' % i, im0s[i] else: p, s, im0 = path, '', im0s save_path = str(Path(out) / Path(p).name) s += '%gx%g ' % img.shape[2:] if det is not None and len(det): det[:, :4] = scale_coords(img.shape[2:], det[:, :4], im0.shape).round() for c in det[:, -1].unique(): n = (det[:, -1] == c).sum() s += '%g %ss, ' % (n, names[int(c)]) for *xyxy, conf, cls in det: if save_txt: with open(save_path + '.txt', 'a') as file: file.write(('%g ' * 6 + '\n') % (*xyxy, cls, conf)) if save_img or view_img: label = '%s %.2f' % (names[int(cls)], conf) plot_one_box(xyxy, im0, label=label, color=colors[int(cls)]) print('%sDone. (%.3fs)' % (s, t2 - t1)) if view_img: cv2.imshow(p, im0) if cv2.waitKey(1) == ord('q'): raise StopIteration if save_img: if dataset.mode == 'images': cv2.imwrite(save_path, im0) else: if vid_path != save_path: vid_path = save_path if isinstance(vid_writer, cv2.VideoWriter): vid_writer.release() fps = vid_cap.get(cv2.CAP_PROP_FPS) w = int(vid_cap.get(cv2.CAP_PROP_FRAME_WIDTH)) h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) vid_writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*opt.fourcc), fps, (w, h)) vid_writer.write(im0) if save_txt or save_img: print('Results saved to %s' % os.getcwd() + os.sep + out) if platform == 'darwin': os.system('open ' + out + ' ' + save_path) print('Done. (%.3fs)' % (time.time() - t0)) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--cfg', type=str, default='cfg/yolov3-custom.cfg', help='*.cfg path') parser.add_argument('--names', type=str, default='data/customdata/custom.names', help='*.names path') parser.add_argument('--weights', type=str, default='weights/last.pt', help='weights path') parser.add_argument('--source', type=str, default='data/customdata/images', help='source') parser.add_argument('--output', type=str, default='output', help='output folder') parser.add_argument('--img-size', type=int, default=512, help='inference size (pixels)') parser.add_argument('--conf-thres', type=float, default=0.3, help='object confidence threshold') parser.add_argument('--iou-thres', type=float, default=0.6, help='IOU threshold for NMS') parser.add_argument('--fourcc', type=str, default='mp4v', help='output video codec (verify ffmpeg support)') parser.add_argument('--half', action='store_true', help='half precision FP16 inference') parser.add_argument('--device', default='', help='device id (i.e. 0 or 0,1) or cpu') parser.add_argument('--view-img', action='store_true', help='display results') parser.add_argument('--save-txt', action='store_true', help='save results to *.txt') parser.add_argument('--classes', nargs='+', type=int, help='filter by class') parser.add_argument('--agnostic-nms', action='store_true', help='class-agnostic NMS') parser.add_argument('--augment', action='store_true', help='augmented inference') opt = parser.parse_args() print(opt) with torch.no_grad(): detect()

true

f71877dabf3bdc4389a088d6b5ff9767e469ea5b

11,246

py

Python

pandas/tests/series/test_replace.py

kpflugshaupt/pandas

c9e3883c630c48b17218e6bcc5593720c1402bf1

[ "BSD-3-Clause" ]

1

2019-05-19T13:44:03.000Z

pandas/tests/series/test_replace.py

sanjusci/pandas

a1fee9199eba7ebf423880243936b9f1501d3d3a

[ "BSD-3-Clause" ]

null

pandas/tests/series/test_replace.py

sanjusci/pandas

a1fee9199eba7ebf423880243936b9f1501d3d3a

[ "BSD-3-Clause" ]

3

2018-01-08T08:40:55.000Z

2019-10-07T02:02:40.000Z

# coding=utf-8 # pylint: disable-msg=E1101,W0612 import numpy as np import pytest import pandas as pd import pandas.util.testing as tm from .common import TestData class TestSeriesReplace(TestData): def test_replace(self): N = 100 ser = pd.Series(np.random.randn(N)) ser[0:4] = np.nan ser[6:10] = 0 # replace list with a single value ser.replace([np.nan], -1, inplace=True) exp = ser.fillna(-1) tm.assert_series_equal(ser, exp) rs = ser.replace(0., np.nan) ser[ser == 0.] = np.nan tm.assert_series_equal(rs, ser) ser = pd.Series(np.fabs(np.random.randn(N)), tm.makeDateIndex(N), dtype=object) ser[:5] = np.nan ser[6:10] = 'foo' ser[20:30] = 'bar' # replace list with a single value rs = ser.replace([np.nan, 'foo', 'bar'], -1) assert (rs[:5] == -1).all() assert (rs[6:10] == -1).all() assert (rs[20:30] == -1).all() assert (pd.isna(ser[:5])).all() # replace with different values rs = ser.replace({np.nan: -1, 'foo': -2, 'bar': -3}) assert (rs[:5] == -1).all() assert (rs[6:10] == -2).all() assert (rs[20:30] == -3).all() assert (pd.isna(ser[:5])).all() # replace with different values with 2 lists rs2 = ser.replace([np.nan, 'foo', 'bar'], [-1, -2, -3]) tm.assert_series_equal(rs, rs2) # replace inplace ser.replace([np.nan, 'foo', 'bar'], -1, inplace=True) assert (ser[:5] == -1).all() assert (ser[6:10] == -1).all() assert (ser[20:30] == -1).all() ser = pd.Series([np.nan, 0, np.inf]) tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) ser = pd.Series([np.nan, 0, 'foo', 'bar', np.inf, None, pd.NaT]) tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) filled = ser.copy() filled[4] = 0 tm.assert_series_equal(ser.replace(np.inf, 0), filled) ser = pd.Series(self.ts.index) tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) # malformed msg = r"Replacement lists must match in length\. Expecting 3 got 2" with pytest.raises(ValueError, match=msg): ser.replace([1, 2, 3], [np.nan, 0]) # make sure that we aren't just masking a TypeError because bools don't # implement indexing with pytest.raises(TypeError, match='Cannot compare types .+'): ser.replace([1, 2], [np.nan, 0]) ser = pd.Series([0, 1, 2, 3, 4]) result = ser.replace([0, 1, 2, 3, 4], [4, 3, 2, 1, 0]) tm.assert_series_equal(result, pd.Series([4, 3, 2, 1, 0])) def test_replace_gh5319(self): # API change from 0.12? # GH 5319 ser = pd.Series([0, np.nan, 2, 3, 4]) expected = ser.ffill() result = ser.replace([np.nan]) tm.assert_series_equal(result, expected) ser = pd.Series([0, np.nan, 2, 3, 4]) expected = ser.ffill() result = ser.replace(np.nan) tm.assert_series_equal(result, expected) # GH 5797 ser = pd.Series(pd.date_range('20130101', periods=5)) expected = ser.copy() expected.loc[2] = pd.Timestamp('20120101') result = ser.replace({pd.Timestamp('20130103'): pd.Timestamp('20120101')}) tm.assert_series_equal(result, expected) result = ser.replace(pd.Timestamp('20130103'), pd.Timestamp('20120101')) tm.assert_series_equal(result, expected) # GH 11792: Test with replacing NaT in a list with tz data ts = pd.Timestamp('2015/01/01', tz='UTC') s = pd.Series([pd.NaT, pd.Timestamp('2015/01/01', tz='UTC')]) result = s.replace([np.nan, pd.NaT], pd.Timestamp.min) expected = pd.Series([pd.Timestamp.min, ts], dtype=object) tm.assert_series_equal(expected, result) def test_replace_with_single_list(self): ser = pd.Series([0, 1, 2, 3, 4]) result = ser.replace([1, 2, 3]) tm.assert_series_equal(result, pd.Series([0, 0, 0, 0, 4])) s = ser.copy() s.replace([1, 2, 3], inplace=True) tm.assert_series_equal(s, pd.Series([0, 0, 0, 0, 4])) # make sure things don't get corrupted when fillna call fails s = ser.copy() msg = (r"Invalid fill method\. Expecting pad $ffill$ or backfill" r" $bfill$\. Got crash_cymbal") with pytest.raises(ValueError, match=msg): s.replace([1, 2, 3], inplace=True, method='crash_cymbal') tm.assert_series_equal(s, ser) def test_replace_with_empty_list(self): # GH 21977 s = pd.Series([[1], [2, 3], [], np.nan, [4]]) expected = s result = s.replace([], np.nan) tm.assert_series_equal(result, expected) # GH 19266 with pytest.raises(ValueError, match="cannot assign mismatch"): s.replace({np.nan: []}) with pytest.raises(ValueError, match="cannot assign mismatch"): s.replace({np.nan: ['dummy', 'alt']}) def test_replace_mixed_types(self): s = pd.Series(np.arange(5), dtype='int64') def check_replace(to_rep, val, expected): sc = s.copy() r = s.replace(to_rep, val) sc.replace(to_rep, val, inplace=True) tm.assert_series_equal(expected, r) tm.assert_series_equal(expected, sc) # MUST upcast to float e = pd.Series([0., 1., 2., 3., 4.]) tr, v = [3], [3.0] check_replace(tr, v, e) # MUST upcast to float e = pd.Series([0, 1, 2, 3.5, 4]) tr, v = [3], [3.5] check_replace(tr, v, e) # casts to object e = pd.Series([0, 1, 2, 3.5, 'a']) tr, v = [3, 4], [3.5, 'a'] check_replace(tr, v, e) # again casts to object e = pd.Series([0, 1, 2, 3.5, pd.Timestamp('20130101')]) tr, v = [3, 4], [3.5, pd.Timestamp('20130101')] check_replace(tr, v, e) # casts to object e = pd.Series([0, 1, 2, 3.5, True], dtype='object') tr, v = [3, 4], [3.5, True] check_replace(tr, v, e) # test an object with dates + floats + integers + strings dr = pd.date_range('1/1/2001', '1/10/2001', freq='D').to_series().reset_index(drop=True) result = dr.astype(object).replace( [dr[0], dr[1], dr[2]], [1.0, 2, 'a']) expected = pd.Series([1.0, 2, 'a'] + dr[3:].tolist(), dtype=object) tm.assert_series_equal(result, expected) def test_replace_bool_with_string_no_op(self): s = pd.Series([True, False, True]) result = s.replace('fun', 'in-the-sun') tm.assert_series_equal(s, result) def test_replace_bool_with_string(self): # nonexistent elements s = pd.Series([True, False, True]) result = s.replace(True, '2u') expected = pd.Series(['2u', False, '2u']) tm.assert_series_equal(expected, result) def test_replace_bool_with_bool(self): s = pd.Series([True, False, True]) result = s.replace(True, False) expected = pd.Series([False] * len(s)) tm.assert_series_equal(expected, result) def test_replace_with_dict_with_bool_keys(self): s = pd.Series([True, False, True]) with pytest.raises(TypeError, match='Cannot compare types .+'): s.replace({'asdf': 'asdb', True: 'yes'}) def test_replace2(self): N = 100 ser = pd.Series(np.fabs(np.random.randn(N)), tm.makeDateIndex(N), dtype=object) ser[:5] = np.nan ser[6:10] = 'foo' ser[20:30] = 'bar' # replace list with a single value rs = ser.replace([np.nan, 'foo', 'bar'], -1) assert (rs[:5] == -1).all() assert (rs[6:10] == -1).all() assert (rs[20:30] == -1).all() assert (pd.isna(ser[:5])).all() # replace with different values rs = ser.replace({np.nan: -1, 'foo': -2, 'bar': -3}) assert (rs[:5] == -1).all() assert (rs[6:10] == -2).all() assert (rs[20:30] == -3).all() assert (pd.isna(ser[:5])).all() # replace with different values with 2 lists rs2 = ser.replace([np.nan, 'foo', 'bar'], [-1, -2, -3]) tm.assert_series_equal(rs, rs2) # replace inplace ser.replace([np.nan, 'foo', 'bar'], -1, inplace=True) assert (ser[:5] == -1).all() assert (ser[6:10] == -1).all() assert (ser[20:30] == -1).all() def test_replace_with_empty_dictlike(self): # GH 15289 s = pd.Series(list('abcd')) tm.assert_series_equal(s, s.replace(dict())) tm.assert_series_equal(s, s.replace(pd.Series([]))) def test_replace_string_with_number(self): # GH 15743 s = pd.Series([1, 2, 3]) result = s.replace('2', np.nan) expected = pd.Series([1, 2, 3]) tm.assert_series_equal(expected, result) def test_replace_replacer_equals_replacement(self): # GH 20656 # make sure all replacers are matching against original values s = pd.Series(['a', 'b']) expected = pd.Series(['b', 'a']) result = s.replace({'a': 'b', 'b': 'a'}) tm.assert_series_equal(expected, result) def test_replace_unicode_with_number(self): # GH 15743 s = pd.Series([1, 2, 3]) result = s.replace('2', np.nan) expected = pd.Series([1, 2, 3]) tm.assert_series_equal(expected, result) def test_replace_mixed_types_with_string(self): # Testing mixed s = pd.Series([1, 2, 3, '4', 4, 5]) result = s.replace([2, '4'], np.nan) expected = pd.Series([1, np.nan, 3, np.nan, 4, 5]) tm.assert_series_equal(expected, result) @pytest.mark.parametrize("categorical, numeric", [ (pd.Categorical('A', categories=['A', 'B']), [1]), (pd.Categorical(('A', ), categories=['A', 'B']), [1]), (pd.Categorical(('A', 'B'), categories=['A', 'B']), [1, 2]), ]) def test_replace_categorical(self, categorical, numeric): # GH 24971 # Do not check if dtypes are equal due to a known issue that # Categorical.replace sometimes coerces to object (GH 23305) s = pd.Series(categorical) result = s.replace({'A': 1, 'B': 2}) expected = pd.Series(numeric) tm.assert_series_equal(expected, result, check_dtype=False) def test_replace_with_no_overflowerror(self): # GH 25616 # casts to object without Exception from OverflowError s = pd.Series([0, 1, 2, 3, 4]) result = s.replace([3], ['100000000000000000000']) expected = pd.Series([0, 1, 2, '100000000000000000000', 4]) tm.assert_series_equal(result, expected) s = pd.Series([0, '100000000000000000000', '100000000000000000001']) result = s.replace(['100000000000000000000'], [1]) expected = pd.Series([0, 1, '100000000000000000001']) tm.assert_series_equal(result, expected)

36.160772

79

0.55273

import numpy as np import pytest import pandas as pd import pandas.util.testing as tm from .common import TestData class TestSeriesReplace(TestData): def test_replace(self): N = 100 ser = pd.Series(np.random.randn(N)) ser[0:4] = np.nan ser[6:10] = 0 ser.replace([np.nan], -1, inplace=True) exp = ser.fillna(-1) tm.assert_series_equal(ser, exp) rs = ser.replace(0., np.nan) ser[ser == 0.] = np.nan tm.assert_series_equal(rs, ser) ser = pd.Series(np.fabs(np.random.randn(N)), tm.makeDateIndex(N), dtype=object) ser[:5] = np.nan ser[6:10] = 'foo' ser[20:30] = 'bar' rs = ser.replace([np.nan, 'foo', 'bar'], -1) assert (rs[:5] == -1).all() assert (rs[6:10] == -1).all() assert (rs[20:30] == -1).all() assert (pd.isna(ser[:5])).all() rs = ser.replace({np.nan: -1, 'foo': -2, 'bar': -3}) assert (rs[:5] == -1).all() assert (rs[6:10] == -2).all() assert (rs[20:30] == -3).all() assert (pd.isna(ser[:5])).all() rs2 = ser.replace([np.nan, 'foo', 'bar'], [-1, -2, -3]) tm.assert_series_equal(rs, rs2) ser.replace([np.nan, 'foo', 'bar'], -1, inplace=True) assert (ser[:5] == -1).all() assert (ser[6:10] == -1).all() assert (ser[20:30] == -1).all() ser = pd.Series([np.nan, 0, np.inf]) tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) ser = pd.Series([np.nan, 0, 'foo', 'bar', np.inf, None, pd.NaT]) tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) filled = ser.copy() filled[4] = 0 tm.assert_series_equal(ser.replace(np.inf, 0), filled) ser = pd.Series(self.ts.index) tm.assert_series_equal(ser.replace(np.nan, 0), ser.fillna(0)) msg = r"Replacement lists must match in length\. Expecting 3 got 2" with pytest.raises(ValueError, match=msg): ser.replace([1, 2, 3], [np.nan, 0]) with pytest.raises(TypeError, match='Cannot compare types .+'): ser.replace([1, 2], [np.nan, 0]) ser = pd.Series([0, 1, 2, 3, 4]) result = ser.replace([0, 1, 2, 3, 4], [4, 3, 2, 1, 0]) tm.assert_series_equal(result, pd.Series([4, 3, 2, 1, 0])) def test_replace_gh5319(self): ser = pd.Series([0, np.nan, 2, 3, 4]) expected = ser.ffill() result = ser.replace([np.nan]) tm.assert_series_equal(result, expected) ser = pd.Series([0, np.nan, 2, 3, 4]) expected = ser.ffill() result = ser.replace(np.nan) tm.assert_series_equal(result, expected) ser = pd.Series(pd.date_range('20130101', periods=5)) expected = ser.copy() expected.loc[2] = pd.Timestamp('20120101') result = ser.replace({pd.Timestamp('20130103'): pd.Timestamp('20120101')}) tm.assert_series_equal(result, expected) result = ser.replace(pd.Timestamp('20130103'), pd.Timestamp('20120101')) tm.assert_series_equal(result, expected) ts = pd.Timestamp('2015/01/01', tz='UTC') s = pd.Series([pd.NaT, pd.Timestamp('2015/01/01', tz='UTC')]) result = s.replace([np.nan, pd.NaT], pd.Timestamp.min) expected = pd.Series([pd.Timestamp.min, ts], dtype=object) tm.assert_series_equal(expected, result) def test_replace_with_single_list(self): ser = pd.Series([0, 1, 2, 3, 4]) result = ser.replace([1, 2, 3]) tm.assert_series_equal(result, pd.Series([0, 0, 0, 0, 4])) s = ser.copy() s.replace([1, 2, 3], inplace=True) tm.assert_series_equal(s, pd.Series([0, 0, 0, 0, 4])) s = ser.copy() msg = (r"Invalid fill method\. Expecting pad $ffill$ or backfill" r" $bfill$\. Got crash_cymbal") with pytest.raises(ValueError, match=msg): s.replace([1, 2, 3], inplace=True, method='crash_cymbal') tm.assert_series_equal(s, ser) def test_replace_with_empty_list(self): # GH 21977 s = pd.Series([[1], [2, 3], [], np.nan, [4]]) expected = s result = s.replace([], np.nan) tm.assert_series_equal(result, expected) # GH 19266 with pytest.raises(ValueError, match="cannot assign mismatch"): s.replace({np.nan: []}) with pytest.raises(ValueError, match="cannot assign mismatch"): s.replace({np.nan: ['dummy', 'alt']}) def test_replace_mixed_types(self): s = pd.Series(np.arange(5), dtype='int64') def check_replace(to_rep, val, expected): sc = s.copy() r = s.replace(to_rep, val) sc.replace(to_rep, val, inplace=True) tm.assert_series_equal(expected, r) tm.assert_series_equal(expected, sc) # MUST upcast to float e = pd.Series([0., 1., 2., 3., 4.]) tr, v = [3], [3.0] check_replace(tr, v, e) # MUST upcast to float e = pd.Series([0, 1, 2, 3.5, 4]) tr, v = [3], [3.5] check_replace(tr, v, e) # casts to object e = pd.Series([0, 1, 2, 3.5, 'a']) tr, v = [3, 4], [3.5, 'a'] check_replace(tr, v, e) # again casts to object e = pd.Series([0, 1, 2, 3.5, pd.Timestamp('20130101')]) tr, v = [3, 4], [3.5, pd.Timestamp('20130101')] check_replace(tr, v, e) # casts to object e = pd.Series([0, 1, 2, 3.5, True], dtype='object') tr, v = [3, 4], [3.5, True] check_replace(tr, v, e) # test an object with dates + floats + integers + strings dr = pd.date_range('1/1/2001', '1/10/2001', freq='D').to_series().reset_index(drop=True) result = dr.astype(object).replace( [dr[0], dr[1], dr[2]], [1.0, 2, 'a']) expected = pd.Series([1.0, 2, 'a'] + dr[3:].tolist(), dtype=object) tm.assert_series_equal(result, expected) def test_replace_bool_with_string_no_op(self): s = pd.Series([True, False, True]) result = s.replace('fun', 'in-the-sun') tm.assert_series_equal(s, result) def test_replace_bool_with_string(self): # nonexistent elements s = pd.Series([True, False, True]) result = s.replace(True, '2u') expected = pd.Series(['2u', False, '2u']) tm.assert_series_equal(expected, result) def test_replace_bool_with_bool(self): s = pd.Series([True, False, True]) result = s.replace(True, False) expected = pd.Series([False] * len(s)) tm.assert_series_equal(expected, result) def test_replace_with_dict_with_bool_keys(self): s = pd.Series([True, False, True]) with pytest.raises(TypeError, match='Cannot compare types .+'): s.replace({'asdf': 'asdb', True: 'yes'}) def test_replace2(self): N = 100 ser = pd.Series(np.fabs(np.random.randn(N)), tm.makeDateIndex(N), dtype=object) ser[:5] = np.nan ser[6:10] = 'foo' ser[20:30] = 'bar' # replace list with a single value rs = ser.replace([np.nan, 'foo', 'bar'], -1) assert (rs[:5] == -1).all() assert (rs[6:10] == -1).all() assert (rs[20:30] == -1).all() assert (pd.isna(ser[:5])).all() # replace with different values rs = ser.replace({np.nan: -1, 'foo': -2, 'bar': -3}) assert (rs[:5] == -1).all() assert (rs[6:10] == -2).all() assert (rs[20:30] == -3).all() assert (pd.isna(ser[:5])).all() # replace with different values with 2 lists rs2 = ser.replace([np.nan, 'foo', 'bar'], [-1, -2, -3]) tm.assert_series_equal(rs, rs2) # replace inplace ser.replace([np.nan, 'foo', 'bar'], -1, inplace=True) assert (ser[:5] == -1).all() assert (ser[6:10] == -1).all() assert (ser[20:30] == -1).all() def test_replace_with_empty_dictlike(self): # GH 15289 s = pd.Series(list('abcd')) tm.assert_series_equal(s, s.replace(dict())) tm.assert_series_equal(s, s.replace(pd.Series([]))) def test_replace_string_with_number(self): # GH 15743 s = pd.Series([1, 2, 3]) result = s.replace('2', np.nan) expected = pd.Series([1, 2, 3]) tm.assert_series_equal(expected, result) def test_replace_replacer_equals_replacement(self): # GH 20656 # make sure all replacers are matching against original values s = pd.Series(['a', 'b']) expected = pd.Series(['b', 'a']) result = s.replace({'a': 'b', 'b': 'a'}) tm.assert_series_equal(expected, result) def test_replace_unicode_with_number(self): # GH 15743 s = pd.Series([1, 2, 3]) result = s.replace('2', np.nan) expected = pd.Series([1, 2, 3]) tm.assert_series_equal(expected, result) def test_replace_mixed_types_with_string(self): # Testing mixed s = pd.Series([1, 2, 3, '4', 4, 5]) result = s.replace([2, '4'], np.nan) expected = pd.Series([1, np.nan, 3, np.nan, 4, 5]) tm.assert_series_equal(expected, result) @pytest.mark.parametrize("categorical, numeric", [ (pd.Categorical('A', categories=['A', 'B']), [1]), (pd.Categorical(('A', ), categories=['A', 'B']), [1]), (pd.Categorical(('A', 'B'), categories=['A', 'B']), [1, 2]), ]) def test_replace_categorical(self, categorical, numeric): # GH 24971 # Do not check if dtypes are equal due to a known issue that # Categorical.replace sometimes coerces to object (GH 23305) s = pd.Series(categorical) result = s.replace({'A': 1, 'B': 2}) expected = pd.Series(numeric) tm.assert_series_equal(expected, result, check_dtype=False) def test_replace_with_no_overflowerror(self): # GH 25616 # casts to object without Exception from OverflowError s = pd.Series([0, 1, 2, 3, 4]) result = s.replace([3], ['100000000000000000000']) expected = pd.Series([0, 1, 2, '100000000000000000000', 4]) tm.assert_series_equal(result, expected) s = pd.Series([0, '100000000000000000000', '100000000000000000001']) result = s.replace(['100000000000000000000'], [1]) expected = pd.Series([0, 1, '100000000000000000001']) tm.assert_series_equal(result, expected)

true

f71878ecaeeecc9487d63ee73a12842ed9ee5b34

73,406

py

Python

src/transformers/models/pegasus/modeling_tf_pegasus.py

Shashi456/transformers

0f43e742d908772733870730dbddd8e00e0253ef

[ "Apache-2.0" ]

17

2020-10-13T06:53:25.000Z

2022-02-22T06:12:17.000Z

src/transformers/models/pegasus/modeling_tf_pegasus.py

Shashi456/transformers

0f43e742d908772733870730dbddd8e00e0253ef

[ "Apache-2.0" ]

13

2020-10-13T11:41:11.000Z

2022-02-16T14:13:31.000Z

src/transformers/models/pegasus/modeling_tf_pegasus.py

Shashi456/transformers

0f43e742d908772733870730dbddd8e00e0253ef

[ "Apache-2.0" ]

13

2020-10-04T05:06:00.000Z

2022-02-09T01:14:59.000Z

# coding=utf-8 # Copyright 2021, Google Inc. and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ TF 2.0 Pegasus model. """ import random from typing import Dict, Optional, Tuple, Union import numpy as np import tensorflow as tf from ...activations_tf import get_tf_activation from ...file_utils import ( add_code_sample_docstrings, add_end_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings, ) from ...modeling_tf_outputs import ( TFBaseModelOutput, TFBaseModelOutputWithPastAndCrossAttentions, TFSeq2SeqLMOutput, TFSeq2SeqModelOutput, ) # Public API from ...modeling_tf_utils import ( DUMMY_INPUTS, TFCausalLanguageModelingLoss, TFPreTrainedModel, TFSharedEmbeddings, TFWrappedEmbeddings, input_processing, keras_serializable, shape_list, ) from ...utils import logging from .configuration_pegasus import PegasusConfig logger = logging.get_logger(__name__) _CHECKPOINT_FOR_DOC = "google/pegasus-large" _CONFIG_FOR_DOC = "PegasusConfig" _TOKENIZER_FOR_DOC = "PegasusTokenizer" LARGE_NEGATIVE = -1e8 # Copied from transformers.models.bart.modeling_tf_bart.shift_tokens_right def shift_tokens_right(input_ids: tf.Tensor, pad_token_id: int, decoder_start_token_id: int): start_tokens = tf.fill((shape_list(input_ids)[0], 1), decoder_start_token_id) shifted_input_ids = tf.concat([start_tokens, input_ids[:, :-1]], -1) # replace possible -100 values in labels by `pad_token_id` shifted_input_ids = tf.where( shifted_input_ids == -100, tf.fill(shape_list(shifted_input_ids), pad_token_id), shifted_input_ids ) if tf.executing_eagerly(): # "Verify that `labels` has only positive values and -100" assert_gte0 = tf.debugging.assert_greater_equal(shifted_input_ids, tf.constant(0)) # Make sure the assertion op is called by wrapping the result in an identity no-op with tf.control_dependencies([assert_gte0]): shifted_input_ids = tf.identity(shifted_input_ids) return shifted_input_ids # Copied from transformers.models.bart.modeling_tf_bart._make_causal_mask def _make_causal_mask(input_ids_shape: tf.TensorShape, past_key_values_length: int = 0): """ Make causal mask used for bi-directional self-attention. """ bsz, tgt_len = input_ids_shape mask = tf.ones((tgt_len, tgt_len)) * LARGE_NEGATIVE mask_cond = tf.range(shape_list(mask)[-1]) mask = tf.where(mask_cond < tf.reshape(mask_cond + 1, (shape_list(mask)[-1], 1)), 0.0, mask) if past_key_values_length > 0: mask = tf.concat([tf.zeros((tgt_len, past_key_values_length)), mask], axis=-1) return tf.tile(mask[None, None, :, :], (bsz, 1, 1, 1)) # Copied from transformers.models.bart.modeling_tf_bart._expand_mask def _expand_mask(mask: tf.Tensor, tgt_len: Optional[int] = None, past_key_values_length: int = 0): """ Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`. """ src_len = shape_list(mask)[1] tgt_len = tgt_len if tgt_len is not None else src_len one_cst = tf.constant(1.0) mask = tf.cast(mask, dtype=one_cst.dtype) expanded_mask = tf.tile(mask[:, None, None, :], (1, 1, tgt_len, 1)) return (one_cst - expanded_mask) * LARGE_NEGATIVE # Copied from transformers.models.marian.modeling_tf_marian.TFMarianSinusoidalPositionalEmbedding with Marian->Pegasus class TFPegasusSinusoidalPositionalEmbedding(tf.keras.layers.Layer): """This module produces sinusoidal positional embeddings of any length.""" def __init__(self, num_positions: int, embedding_dim: int, **kwargs): super().__init__(**kwargs) if embedding_dim % 2 != 0: raise NotImplementedError(f"odd embedding_dim {embedding_dim} not supported") self.embedding_dim = embedding_dim self.num_positions = num_positions def build(self, input_shape: tf.TensorShape): """ Build shared token embedding layer Shared weights logic adapted from https://github.com/tensorflow/models/blob/a009f4fb9d2fc4949e32192a944688925ef78659/official/transformer/v2/embedding_layer.py#L24 """ weight = self._init_weight(self.num_positions, self.embedding_dim) self.weight = self.add_weight( name="embeddings", shape=[self.num_positions, self.embedding_dim], ) weight = tf.cast(weight, dtype=self.weight.dtype) self.weight.assign(weight) super().build(input_shape) @staticmethod def _init_weight(n_pos: int, dim: int): """ Identical to the XLM create_sinusoidal_embeddings except features are not interleaved. The cos features are in the 2nd half of the vector. [dim // 2:] """ position_enc = np.array( [[pos / np.power(10000, 2 * (j // 2) / dim) for j in range(dim)] for pos in range(n_pos)] ) # index 0 is all zero position_enc[:, 0 : dim // 2] = np.sin(position_enc[:, 0::2]) position_enc[:, dim // 2 :] = np.cos(position_enc[:, 1::2]) # convert to tensor table = tf.convert_to_tensor(position_enc) tf.stop_gradient(table) return table def call(self, input_shape: tf.TensorShape, past_key_values_length: int = 0): """Input is expected to be of size [bsz x seqlen].""" bsz, seq_len = input_shape[:2] positions = tf.range(past_key_values_length, seq_len + past_key_values_length, delta=1, name="range") return tf.gather(self.weight, positions) # Copied from transformers.models.bart.modeling_tf_bart.TFBartAttention with Bart->Pegasus class TFPegasusAttention(tf.keras.layers.Layer): """Multi-headed attention from "Attention Is All You Need""" def __init__( self, embed_dim: int, num_heads: int, dropout: float = 0.0, is_decoder: bool = False, bias: bool = True, **kwargs, ): super().__init__(**kwargs) self.embed_dim = embed_dim self.num_heads = num_heads self.dropout = tf.keras.layers.Dropout(dropout) self.head_dim = embed_dim // num_heads assert self.head_dim * num_heads == self.embed_dim, "embed_dim must be divisible by num_heads" self.scaling = self.head_dim ** -0.5 self.is_decoder = is_decoder self.k_proj = tf.keras.layers.Dense(embed_dim, use_bias=bias, name="k_proj") self.q_proj = tf.keras.layers.Dense(embed_dim, use_bias=bias, name="q_proj") self.v_proj = tf.keras.layers.Dense(embed_dim, use_bias=bias, name="v_proj") self.out_proj = tf.keras.layers.Dense(embed_dim, use_bias=bias, name="out_proj") def _shape(self, tensor: tf.Tensor, seq_len: int, bsz: int): return tf.transpose(tf.reshape(tensor, (bsz, seq_len, self.num_heads, self.head_dim)), (0, 2, 1, 3)) def call( self, hidden_states: tf.Tensor, key_value_states: Optional[tf.Tensor] = None, past_key_value: Optional[Tuple[Tuple[tf.Tensor]]] = None, attention_mask: Optional[tf.Tensor] = None, layer_head_mask: Optional[tf.Tensor] = None, training=False, ) -> Tuple[tf.Tensor, Optional[tf.Tensor]]: """Input shape: Batch x Time x Channel""" # if key_value_states are provided this layer is used as a cross-attention layer # for the decoder is_cross_attention = key_value_states is not None bsz, tgt_len, embed_dim = shape_list(hidden_states) # get query proj query_states = self.q_proj(hidden_states) * self.scaling # get key, value proj if is_cross_attention and past_key_value is not None: # reuse k,v, cross_attentions key_states = past_key_value[0] value_states = past_key_value[1] elif is_cross_attention: # cross_attentions key_states = self._shape(self.k_proj(key_value_states), -1, bsz) value_states = self._shape(self.v_proj(key_value_states), -1, bsz) elif past_key_value is not None: # reuse k, v, self_attention key_states = self._shape(self.k_proj(hidden_states), -1, bsz) value_states = self._shape(self.v_proj(hidden_states), -1, bsz) key_states = tf.concat([past_key_value[0], key_states], axis=2) value_states = tf.concat([past_key_value[1], value_states], axis=2) else: # self_attention key_states = self._shape(self.k_proj(hidden_states), -1, bsz) value_states = self._shape(self.v_proj(hidden_states), -1, bsz) if self.is_decoder: # if cross_attention save Tuple(tf.Tensor, tf.Tensor) of all cross attention key/value_states. # Further calls to cross_attention layer can then reuse all cross-attention # key/value_states (first "if" case) # if uni-directional self-attention (decoder) save Tuple(tf.Tensor, tf.Tensor) of # all previous decoder key/value_states. Further calls to uni-directional self-attention # can concat previous decoder key/value_states to current projected key/value_states (third "elif" case) # if encoder bi-directional self-attention `past_key_value` is always `None` past_key_value = (key_states, value_states) proj_shape = (bsz * self.num_heads, -1, self.head_dim) query_states = tf.reshape(self._shape(query_states, tgt_len, bsz), proj_shape) key_states = tf.reshape(key_states, proj_shape) value_states = tf.reshape(value_states, proj_shape) src_len = shape_list(key_states)[1] attn_weights = tf.matmul(query_states, key_states, transpose_b=True) # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(attn_weights), [bsz * self.num_heads, tgt_len, src_len], message=f"Attention weights should be of size {(bsz * self.num_heads, tgt_len, src_len)}, but is {shape_list(attn_weights)}", ) if attention_mask is not None: # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(attention_mask), [bsz, 1, tgt_len, src_len], message=f"Attention mask should be of size {(bsz, 1, tgt_len, src_len)}, but is {shape_list(attention_mask)}", ) attention_mask = tf.cast(attention_mask, dtype=attn_weights.dtype) attn_weights = tf.reshape(attn_weights, (bsz, self.num_heads, tgt_len, src_len)) + attention_mask attn_weights = tf.reshape(attn_weights, (bsz * self.num_heads, tgt_len, src_len)) attn_weights = tf.nn.softmax(attn_weights, axis=-1) if layer_head_mask is not None: # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(layer_head_mask), [self.num_heads], message=f"Head mask for a single layer should be of size {(self.num_heads)}, but is {shape_list(layer_head_mask)}", ) attn_weights = tf.reshape(layer_head_mask, (1, -1, 1, 1)) * tf.reshape( attn_weights, (bsz, self.num_heads, tgt_len, src_len) ) attn_weights = tf.reshape(attn_weights, (bsz * self.num_heads, tgt_len, src_len)) attn_probs = self.dropout(attn_weights, training=training) attn_output = tf.matmul(attn_probs, value_states) # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(attn_output), [bsz * self.num_heads, tgt_len, self.head_dim], message=f"`attn_output` should be of size {(bsz, self.num_heads, tgt_len, self.head_dim)}, but is {shape_list(attn_output)}", ) attn_output = tf.transpose( tf.reshape(attn_output, (bsz, self.num_heads, tgt_len, self.head_dim)), (0, 2, 1, 3) ) attn_output = tf.reshape(attn_output, (bsz, tgt_len, embed_dim)) attn_output = self.out_proj(attn_output) attn_weights: tf.Tensor = tf.reshape(attn_weights, (bsz, self.num_heads, tgt_len, src_len)) return attn_output, attn_weights, past_key_value # Copied from transformers.models.mbart.modeling_tf_mbart.TFMBartEncoderLayer with MBart->Pegasus class TFPegasusEncoderLayer(tf.keras.layers.Layer): def __init__(self, config: PegasusConfig, **kwargs): super().__init__(**kwargs) self.embed_dim = config.d_model self.self_attn = TFPegasusAttention( self.embed_dim, config.encoder_attention_heads, dropout=config.attention_dropout, name="self_attn" ) self.self_attn_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="self_attn_layer_norm") self.dropout = tf.keras.layers.Dropout(config.dropout) self.activation_fn = get_tf_activation(config.activation_function) self.activation_dropout = tf.keras.layers.Dropout(config.activation_dropout) self.fc1 = tf.keras.layers.Dense(config.encoder_ffn_dim, name="fc1") self.fc2 = tf.keras.layers.Dense(self.embed_dim, name="fc2") self.final_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="final_layer_norm") def call(self, hidden_states: tf.Tensor, attention_mask: tf.Tensor, layer_head_mask: tf.Tensor, training=False): """ Args: hidden_states (:obj:`tf.Tensor`): input to the layer of shape `(seq_len, batch, embed_dim)` attention_mask (:obj:`tf.Tensor`): attention mask of size `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values. layer_head_mask (:obj:`tf.Tensor`): mask for attention heads in a given layer of size `(encoder_attention_heads,)` """ residual = hidden_states hidden_states = self.self_attn_layer_norm(hidden_states) hidden_states, self_attn_weights, _ = self.self_attn( hidden_states=hidden_states, attention_mask=attention_mask, layer_head_mask=layer_head_mask ) # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(hidden_states), shape_list(residual), message=f"Self attn modified the shape of query {shape_list(residual)} to {shape_list(hidden_states)}", ) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states residual = hidden_states hidden_states = self.final_layer_norm(hidden_states) hidden_states = self.activation_fn(self.fc1(hidden_states)) hidden_states = self.activation_dropout(hidden_states, training=training) hidden_states = self.fc2(hidden_states) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states return hidden_states, self_attn_weights # Copied from transformers.models.mbart.modeling_tf_mbart.TFMBartDecoderLayer with MBart->Pegasus class TFPegasusDecoderLayer(tf.keras.layers.Layer): def __init__(self, config: PegasusConfig, **kwargs): super().__init__(**kwargs) self.embed_dim = config.d_model self.self_attn = TFPegasusAttention( embed_dim=self.embed_dim, num_heads=config.decoder_attention_heads, dropout=config.attention_dropout, name="self_attn", is_decoder=True, ) self.dropout = tf.keras.layers.Dropout(config.dropout) self.activation_fn = get_tf_activation(config.activation_function) self.activation_dropout = tf.keras.layers.Dropout(config.activation_dropout) self.self_attn_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="self_attn_layer_norm") self.encoder_attn = TFPegasusAttention( self.embed_dim, config.decoder_attention_heads, dropout=config.attention_dropout, name="encoder_attn", is_decoder=True, ) self.encoder_attn_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="encoder_attn_layer_norm") self.fc1 = tf.keras.layers.Dense(config.decoder_ffn_dim, name="fc1") self.fc2 = tf.keras.layers.Dense(self.embed_dim, name="fc2") self.final_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="final_layer_norm") def call( self, hidden_states, attention_mask: Optional[tf.Tensor] = None, encoder_hidden_states: Optional[tf.Tensor] = None, encoder_attention_mask: Optional[tf.Tensor] = None, layer_head_mask: Optional[tf.Tensor] = None, cross_attn_layer_head_mask: Optional[tf.Tensor] = None, past_key_value: Optional[Tuple[tf.Tensor]] = None, training=False, ) -> Tuple[tf.Tensor, tf.Tensor, Tuple[Tuple[tf.Tensor]]]: """ Args: hidden_states (:obj:`tf.Tensor`): input to the layer of shape `(seq_len, batch, embed_dim)` attention_mask (:obj:`tf.Tensor`): attention mask of size `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values. encoder_hidden_states (:obj:`tf.Tensor`): cross attention input to the layer of shape `(seq_len, batch, embed_dim)` encoder_attention_mask (:obj:`tf.Tensor`): encoder attention mask of size `(batch, 1, tgt_len, src_len)` where padding elements are indicated by very large negative values. layer_head_mask (:obj:`tf.Tensor`): mask for attention heads in a given layer of size `(decoder_attention_heads,)` cross_attn_layer_head_mask (:obj:`tf.Tensor`): mask for heads of the cross-attention module. `(decoder_attention_heads,)` past_key_value (:obj:`Tuple(tf.Tensor)`): cached past key and value projection states """ residual = hidden_states hidden_states = self.self_attn_layer_norm(hidden_states) # Self Attention # decoder uni-directional self-attention cached key/values tuple is at positions 1,2 self_attn_past_key_value = past_key_value[:2] if past_key_value is not None else None # add present self-attn cache to positions 1,2 of present_key_value tuple hidden_states, self_attn_weights, present_key_value = self.self_attn( hidden_states=hidden_states, past_key_value=self_attn_past_key_value, attention_mask=attention_mask, layer_head_mask=layer_head_mask, ) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states # Cross-Attention Block cross_attn_present_key_value = None cross_attn_weights = None if encoder_hidden_states is not None: residual = hidden_states hidden_states = self.encoder_attn_layer_norm(hidden_states) # cross_attn cached key/values tuple is at positions 3,4 of present_key_value tuple cross_attn_past_key_value = past_key_value[-2:] if past_key_value is not None else None hidden_states, cross_attn_weights, cross_attn_present_key_value = self.encoder_attn( hidden_states=hidden_states, key_value_states=encoder_hidden_states, attention_mask=encoder_attention_mask, layer_head_mask=cross_attn_layer_head_mask, past_key_value=cross_attn_past_key_value, ) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states # add cross-attn to positions 3,4 of present_key_value tuple present_key_value = present_key_value + cross_attn_present_key_value # Fully Connected residual = hidden_states hidden_states = self.final_layer_norm(hidden_states) hidden_states = self.activation_fn(self.fc1(hidden_states)) hidden_states = self.activation_dropout(hidden_states, training=training) hidden_states = self.fc2(hidden_states) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states return ( hidden_states, self_attn_weights, cross_attn_weights, present_key_value, ) class TFPegasusPreTrainedModel(TFPreTrainedModel): config_class = PegasusConfig base_model_prefix = "model" @property def dummy_inputs(self): pad_token = 1 input_ids = tf.cast(tf.convert_to_tensor(DUMMY_INPUTS), tf.int32) decoder_input_ids = tf.cast(tf.convert_to_tensor(DUMMY_INPUTS), tf.int32) dummy_inputs = { "decoder_input_ids": decoder_input_ids, "attention_mask": tf.math.not_equal(input_ids, pad_token), "input_ids": input_ids, } return dummy_inputs @tf.function( input_signature=[ { "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"), "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"), "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"), "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"), } ] ) # Copied from transformers.models.bart.modeling_tf_bart.TFBartPretrainedModel.serving def serving(self, inputs): output = self.call(inputs) return self.serving_output(output) PEGASUS_START_DOCSTRING = r""" This model inherits from :class:`~transformers.TFPreTrainedModel`. Check the superclass documentation for the generic methods the library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads etc.) This model is also a `tf.keras.Model <https://www.tensorflow.org/api_docs/python/tf/keras/Model>`__ subclass. Use it as a regular TF 2.0 Keras Model and refer to the TF 2.0 documentation for all matter related to general usage and behavior. .. note:: TF 2.0 models accepts two formats as inputs: - having all inputs as keyword arguments (like PyTorch models), or - having all inputs as a list, tuple or dict in the first positional arguments. This second option is useful when using :meth:`tf.keras.Model.fit` method which currently requires having all the tensors in the first argument of the model call function: :obj:`model(inputs)`. If you choose this second option, there are three possibilities you can use to gather all the input Tensors in the first positional argument : - a single Tensor with :obj:`input_ids` only and nothing else: :obj:`model(input_ids)` - a list of varying length with one or several input Tensors IN THE ORDER given in the docstring: :obj:`model([input_ids, attention_mask])` or :obj:`model([input_ids, attention_mask, token_type_ids])` - a dictionary with one or several input Tensors associated to the input names given in the docstring: :obj:`model({"input_ids": input_ids, "token_type_ids": token_type_ids})` Args: config (:class:`~transformers.PegasusConfig`): Model configuration class with all the parameters of the model. Initializing with a config file does not load the weights associated with the model, only the configuration. Check out the :meth:`~transformers.TFPreTrainedModel.from_pretrained` method to load the model weights. """ PEGASUS_GENERATION_EXAMPLE = r""" Summarization example:: >>> from transformers import PegasusTokenizer, TFPegasusForConditionalGeneration >>> model = TFPegasusForConditionalGeneration.from_pretrained('google/pegasus-xsum') >>> tokenizer = PegasusTokenizer.from_pretrained('google/pegasus-xsum') >>> ARTICLE_TO_SUMMARIZE = ( ... "PG&E stated it scheduled the blackouts in response to forecasts for high winds " ... "amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were " ... "scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow." ... ) >>> inputs = tokenizer([ARTICLE_TO_SUMMARIZE], max_length=1024, return_tensors='tf') >>> # Generate Summary >>> summary_ids = model.generate(inputs['input_ids']) >>> print([tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids]) """ PEGASUS_INPUTS_DOCSTRING = r""" Args: input_ids (:obj:`tf.Tensor` of shape :obj:`({0})`): Indices of input sequence tokens in the vocabulary. Indices can be obtained using :class:`~transformers.PegasusTokenizer`. See :meth:`transformers.PreTrainedTokenizer.encode` and :meth:`transformers.PreTrainedTokenizer.__call__` for details. `What are input IDs? <../glossary.html#input-ids>`__ attention_mask (:obj:`tf.Tensor` of shape :obj:`({0})`, `optional`): Mask to avoid performing attention on padding token indices. Mask values selected in ``[0, 1]``: - 1 for tokens that are **not masked**, - 0 for tokens that are **masked**. `What are attention masks? <../glossary.html#attention-mask>`__ decoder_input_ids (:obj:`tf.Tensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`): Indices of decoder input sequence tokens in the vocabulary. Indices can be obtained using :class:`~transformers.PegasusTokenizer`. See :meth:`transformers.PreTrainedTokenizer.encode` and :meth:`transformers.PreTrainedTokenizer.__call__` for details. `What are decoder input IDs? <../glossary.html#decoder-input-ids>`__ Pegasus uses the :obj:`pad_token_id` as the starting token for :obj:`decoder_input_ids` generation. If :obj:`past_key_values` is used, optionally only the last :obj:`decoder_input_ids` have to be input (see :obj:`past_key_values`). decoder_attention_mask (:obj:`tf.Tensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`): will be made by default and ignore pad tokens. It is not recommended to set this for most use cases. head_mask (:obj:`tf.Tensor` of shape :obj:`(encoder_layers, encoder_attention_heads)`, `optional`): Mask to nullify selected heads of the attention modules in the encoder. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. decoder_head_mask (:obj:`tf.Tensor` of shape :obj:`(decoder_layers, decoder_attention_heads)`, `optional`): Mask to nullify selected heads of the attention modules in the decoder. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. cross_attn_head_mask (:obj:`tf.Tensor` of shape :obj:`(decoder_layers, decoder_attention_heads)`, `optional`): Mask to nullify selected heads of the cross-attention modules. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. encoder_outputs (:obj:`tf.FloatTensor`, `optional`): hidden states at the output of the last layer of the encoder. Used in the cross-attention of the decoder. of shape :obj:`(batch_size, sequence_length, hidden_size)` is a sequence of past_key_values (:obj:`Tuple[Tuple[tf.Tensor]]` of length :obj:`config.n_layers`) contains precomputed key and value hidden states of the attention blocks. Can be used to speed up decoding. If :obj:`past_key_values` are used, the user can optionally input only the last :obj:`decoder_input_ids` (those that don't have their past key value states given to this model) of shape :obj:`(batch_size, 1)` instead of all :obj:`decoder_input_ids` of shape :obj:`(batch_size, sequence_length)`. use_cache (:obj:`bool`, `optional`, defaults to :obj:`True`): If set to :obj:`True`, :obj:`past_key_values` key value states are returned and can be used to speed up decoding (see :obj:`past_key_values`). Set to :obj:`False` during training, :obj:`True` during generation output_attentions (:obj:`bool`, `optional`): Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. output_attentions (:obj:`bool`, `optional`): Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. output_hidden_states (:obj:`bool`, `optional`): Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. return_dict (:obj:`bool`, `optional`): Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple. This argument can be used in eager mode, in graph mode the value will always be set to True. training (:obj:`bool`, `optional`, defaults to :obj:`False`): Whether or not to use the model in training mode (some modules like dropout modules have different behaviors between training and evaluation). """ @keras_serializable class TFPegasusEncoder(tf.keras.layers.Layer): config_class = PegasusConfig """ Transformer encoder consisting of *config.encoder_layers* self attention layers. Each layer is a :class:`TFPegasusEncoderLayer`. Args: config: PegasusConfig """ def __init__(self, config: PegasusConfig, embed_tokens: Optional[TFSharedEmbeddings] = None, **kwargs): super().__init__(**kwargs) self.config = config self.dropout = tf.keras.layers.Dropout(config.dropout) self.layerdrop = config.encoder_layerdrop self.padding_idx = config.pad_token_id self.max_source_positions = config.max_position_embeddings self.embed_scale = tf.math.sqrt(float(config.d_model)) if config.scale_embedding else 1.0 self.embed_tokens = embed_tokens self.embed_positions = TFPegasusSinusoidalPositionalEmbedding( config.max_position_embeddings, config.d_model, name="embed_positions", ) self.layers = [TFPegasusEncoderLayer(config, name=f"layers.{i}") for i in range(config.encoder_layers)] self.layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="layer_norm") def get_embed_tokens(self): return self.embed_tokens def set_embed_tokens(self, embed_tokens): self.embed_tokens = embed_tokens def call( self, input_ids=None, inputs_embeds=None, attention_mask=None, head_mask=None, output_attentions=None, output_hidden_states=None, return_dict=None, training=False, **kwargs, ): """ Args: input_ids (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length)`): Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide it. Indices can be obtained using :class:`~transformers.PegasusTokenizer`. See :meth:`transformers.PreTrainedTokenizer.encode` and :meth:`transformers.PreTrainedTokenizer.__call__` for details. `What are input IDs? <../glossary.html#input-ids>`__ attention_mask (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length)`, `optional`): Mask to avoid performing attention on padding token indices. Mask values selected in ``[0, 1]``: - 1 for tokens that are **not masked**, - 0 for tokens that are **masked**. `What are attention masks? <../glossary.html#attention-mask>`__ head_mask (:obj:`tf.Tensor` of shape :obj:`(encoder_layers, encoder_attention_heads)`, `optional): Mask to nullify selected heads of the attention modules. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. inputs_embeds (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length, hidden_size)`, `optional`): Optionally, instead of passing :obj:`input_ids` you can choose to directly pass an embedded representation. This is useful if you want more control over how to convert :obj:`input_ids` indices into associated vectors than the model's internal embedding lookup matrix. output_attentions (:obj:`bool`, `optional`): Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. output_hidden_states (:obj:`bool`, `optional`): Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. return_dict (:obj:`bool`, `optional`): Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple. This argument can be used in eager mode, in graph mode the value will always be set to True. training (:obj:`bool`, `optional`, defaults to :obj:`False`): Whether or not to use the model in training mode (some modules like dropout modules have different behaviors between training and evaluation). """ inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, head_mask=head_mask, inputs_embeds=inputs_embeds, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, training=training, kwargs_call=kwargs, ) if inputs["input_ids"] is not None and inputs["inputs_embeds"] is not None: raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time") elif inputs["input_ids"] is not None: input_shape = shape_list(inputs["input_ids"]) elif inputs["inputs_embeds"] is not None: input_shape = shape_list(inputs["inputs_embeds"])[:-1] else: raise ValueError("You have to specify either input_ids or inputs_embeds") if inputs["inputs_embeds"] is None: inputs["inputs_embeds"] = self.embed_tokens(inputs["input_ids"]) * self.embed_scale embed_pos = self.embed_positions(input_shape) hidden_states = inputs["inputs_embeds"] + embed_pos hidden_states = self.dropout(hidden_states, training=inputs["training"]) # check attention mask and invert if inputs["attention_mask"] is not None: # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] attention_mask = _expand_mask(inputs["attention_mask"]) else: attention_mask = None encoder_states = () if inputs["output_hidden_states"] else None all_attentions = () if inputs["output_attentions"] else None # check if head_mask has a correct number of layers specified if desired # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. if inputs["head_mask"] is not None and tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(inputs["head_mask"])[0], len(self.layers), message=f"The head_mask should be specified for {len(self.layers)} layers, but it is for {shape_list(inputs['head_mask'])[0]}.", ) # encoder layers for idx, encoder_layer in enumerate(self.layers): if inputs["output_hidden_states"]: encoder_states = encoder_states + (hidden_states,) # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description) dropout_probability = random.uniform(0, 1) if inputs["training"] and (dropout_probability < self.layerdrop): # skip the layer continue hidden_states, attn = encoder_layer( hidden_states, attention_mask, inputs["head_mask"][idx] if inputs["head_mask"] is not None else None, ) if inputs["output_attentions"]: all_attentions += (attn,) hidden_states = self.layer_norm(hidden_states) if inputs["output_hidden_states"]: encoder_states = encoder_states + (hidden_states,) if not inputs["return_dict"]: return tuple(v for v in [hidden_states, encoder_states, all_attentions] if v is not None) return TFBaseModelOutput( last_hidden_state=hidden_states, hidden_states=encoder_states, attentions=all_attentions ) @keras_serializable class TFPegasusDecoder(tf.keras.layers.Layer): config_class = PegasusConfig """ Transformer decoder consisting of *config.decoder_layers* layers. Each layer is a :class:`TFPegasusDecoderLayer` Args: config: PegasusConfig embed_tokens: output embedding """ def __init__(self, config: PegasusConfig, embed_tokens: Optional[TFSharedEmbeddings] = None, **kwargs): super().__init__(**kwargs) self.config = config self.padding_idx = config.pad_token_id self.embed_tokens = embed_tokens self.layerdrop = config.decoder_layerdrop self.embed_positions = TFPegasusSinusoidalPositionalEmbedding( config.max_position_embeddings, config.d_model, name="embed_positions", ) self.embed_scale = tf.math.sqrt(float(config.d_model)) if config.scale_embedding else 1.0 self.layers = [TFPegasusDecoderLayer(config, name=f"layers.{i}") for i in range(config.decoder_layers)] self.layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="layer_norm") self.dropout = tf.keras.layers.Dropout(config.dropout) def get_embed_tokens(self): return self.embed_tokens def set_embed_tokens(self, embed_tokens): self.embed_tokens = embed_tokens def call( self, input_ids=None, inputs_embeds=None, attention_mask=None, encoder_hidden_states=None, encoder_attention_mask=None, head_mask=None, cross_attn_head_mask=None, past_key_values=None, use_cache=None, output_attentions=None, output_hidden_states=None, return_dict=None, training=False, **kwargs, ): r""" Args: input_ids (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length)`): Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide it. Indices can be obtained using :class:`~transformers.PegasusTokenizer`. See :meth:`transformers.PreTrainedTokenizer.encode` and :meth:`transformers.PreTrainedTokenizer.__call__` for details. `What are input IDs? <../glossary.html#input-ids>`__ attention_mask (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length)`, `optional`): Mask to avoid performing attention on padding token indices. Mask values selected in ``[0, 1]``: - 1 for tokens that are **not masked**, - 0 for tokens that are **masked**. `What are attention masks? <../glossary.html#attention-mask>`__ encoder_hidden_states (:obj:`tf.Tensor` of shape :obj:`(batch_size, encoder_sequence_length, hidden_size)`, `optional`): Sequence of hidden-states at the output of the last layer of the encoder. Used in the cross-attention of the decoder. encoder_attention_mask (:obj:`tf.Tensor` of shape :obj:`(batch_size, encoder_sequence_length)`, `optional`): Mask to avoid performing cross-attention on padding tokens indices of encoder input_ids. Mask values selected in ``[0, 1]``: - 1 for tokens that are **not masked**, - 0 for tokens that are **masked**. `What are attention masks? <../glossary.html#attention-mask>`__ head_mask (:obj:`tf.Tensor` of shape :obj:`(decoder_layers, decoder_attention_heads)`, `optional`): Mask to nullify selected heads of the attention modules. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. cross_attn_head_mask (:obj:`tf.Tensor` of shape :obj:`(decoder_layers, decoder_attention_heads)`, `optional`): Mask to nullify selected heads of the cross-attention modules. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. past_key_values (:obj:`Tuple[Tuple[tf.Tensor]]` of length :obj:`config.n_layers` with each tuple having 2 tuples each of which has 2 tensors of shape :obj:`(batch_size, num_heads, sequence_length - 1, embed_size_per_head)`): Contains precomputed key and value hidden-states of the attention blocks. Can be used to speed up decoding. If :obj:`past_key_values` are used, the user can optionally input only the last :obj:`decoder_input_ids` (those that don't have their past key value states given to this model) of shape :obj:`(batch_size, 1)` instead of all :obj:`decoder_input_ids`` of shape :obj:`(batch_size, sequence_length)`. inputs_embeds (:obj:`tf.Tensor` of shape :obj:`(batch_size, sequence_length, hidden_size)`, `optional`): Optionally, instead of passing :obj:`input_ids` you can choose to directly pass an embedded representation. This is useful if you want more control over how to convert :obj:`input_ids` indices into associated vectors than the model's internal embedding lookup matrix. output_attentions (:obj:`bool`, `optional`): Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. output_hidden_states (:obj:`bool`, `optional`): Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. return_dict (:obj:`bool`, `optional`): Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple. This argument can be used in eager mode, in graph mode the value will always be set to True. training (:obj:`bool`, `optional`, defaults to :obj:`False`): Whether or not to use the model in training mode (some modules like dropout modules have different behaviors between training and evaluation). """ inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, encoder_hidden_states=encoder_hidden_states, encoder_attention_mask=encoder_attention_mask, head_mask=head_mask, cross_attn_head_mask=cross_attn_head_mask, inputs_embeds=inputs_embeds, past_key_values=past_key_values, use_cache=use_cache, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, training=training, kwargs_call=kwargs, ) if inputs["input_ids"] is not None and inputs["inputs_embeds"] is not None: raise ValueError("You cannot specify both decoder_input_ids and decoder_inputs_embeds at the same time") elif inputs["input_ids"] is not None: input_shape = shape_list(inputs["input_ids"]) elif inputs["inputs_embeds"] is not None: input_shape = shape_list(inputs["inputs_embeds"])[:-1] else: raise ValueError("You have to specify either decoder_input_ids or decoder_inputs_embeds") past_key_values_length = ( shape_list(inputs["past_key_values"][0][0])[2] if inputs["past_key_values"] is not None else 0 ) # embed positions positions = self.embed_positions(input_shape, past_key_values_length) if inputs["inputs_embeds"] is None: inputs["inputs_embeds"] = self.embed_tokens(inputs["input_ids"]) * self.embed_scale hidden_states = inputs["inputs_embeds"] # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] if input_shape[-1] > 1: combined_attention_mask = _make_causal_mask(input_shape, past_key_values_length=past_key_values_length) else: combined_attention_mask = _expand_mask( tf.ones((input_shape[0], input_shape[1] + past_key_values_length)), tgt_len=input_shape[-1] ) if inputs["attention_mask"] is not None: combined_attention_mask = combined_attention_mask + _expand_mask( inputs["attention_mask"], tgt_len=input_shape[-1] ) if inputs["encoder_hidden_states"] is not None and inputs["encoder_attention_mask"] is not None: # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] inputs["encoder_attention_mask"] = _expand_mask(inputs["encoder_attention_mask"], tgt_len=input_shape[-1]) hidden_states = self.dropout(hidden_states + positions, training=inputs["training"]) # decoder layers all_hidden_states = () if inputs["output_hidden_states"] else None all_self_attns = () if inputs["output_attentions"] else None all_cross_attns = () if (inputs["output_attentions"] and inputs["encoder_hidden_states"] is not None) else None present_key_values = () if inputs["use_cache"] else None # check if head_mask and cross_attn_head_mask have a correct number of layers specified if desired # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. for attn_mask in ["head_mask", "cross_attn_head_mask"]: if inputs[attn_mask] is not None and tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(inputs[attn_mask])[0], len(self.layers), message=f"The {attn_mask} should be specified for {len(self.layers)} layers, but it is for {shape_list(inputs[attn_mask])[0]}.", ) for idx, decoder_layer in enumerate(self.layers): # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description) if inputs["output_hidden_states"]: all_hidden_states += (hidden_states,) dropout_probability = random.uniform(0, 1) if inputs["training"] and (dropout_probability < self.layerdrop): continue past_key_value = inputs["past_key_values"][idx] if inputs["past_key_values"] is not None else None hidden_states, layer_self_attn, layer_cross_attn, present_key_value = decoder_layer( hidden_states, attention_mask=combined_attention_mask, encoder_hidden_states=inputs["encoder_hidden_states"], encoder_attention_mask=inputs["encoder_attention_mask"], layer_head_mask=inputs["head_mask"][idx] if inputs["head_mask"] is not None else None, cross_attn_layer_head_mask=inputs["cross_attn_head_mask"][idx] if inputs["cross_attn_head_mask"] is not None else None, past_key_value=past_key_value, ) if inputs["use_cache"]: present_key_values += (present_key_value,) if inputs["output_attentions"]: all_self_attns += (layer_self_attn,) if inputs["encoder_hidden_states"] is not None: all_cross_attns += (layer_cross_attn,) hidden_states = self.layer_norm(hidden_states) if inputs["output_hidden_states"]: all_hidden_states += (hidden_states,) if inputs["output_attentions"]: all_self_attns = list(all_self_attns) if inputs["encoder_hidden_states"] is not None: all_cross_attns = list(all_cross_attns) if inputs["use_cache"]: present_key_values = (inputs["encoder_hidden_states"], present_key_values) if not inputs["return_dict"]: return hidden_states, present_key_values, all_hidden_states, all_self_attns, all_cross_attns else: return TFBaseModelOutputWithPastAndCrossAttentions( last_hidden_state=hidden_states, past_key_values=present_key_values, hidden_states=all_hidden_states, attentions=all_self_attns, cross_attentions=all_cross_attns, ) @keras_serializable class TFPegasusMainLayer(tf.keras.layers.Layer): config_class = PegasusConfig def __init__(self, config: PegasusConfig, **kwargs): super().__init__(**kwargs) self.config = config self.shared = TFSharedEmbeddings(config.vocab_size, config.d_model, config.pad_token_id, name="model.shared") with tf.compat.v1.variable_scope("model.shared") as shared_abs_scope_name: pass # Wraps layer to avoid problems with weight restoring and ensuring we're in the correct TF scope. embed_tokens = TFWrappedEmbeddings(self.shared, abs_scope_name=shared_abs_scope_name) embed_tokens.vocab_size = self.shared.vocab_size embed_tokens.hidden_size = self.shared.hidden_size self.encoder = TFPegasusEncoder(config, embed_tokens, name="encoder") self.decoder = TFPegasusDecoder(config, embed_tokens, name="decoder") def get_input_embeddings(self): return self.shared def set_input_embeddings(self, new_embeddings): self.shared.weight = new_embeddings self.shared.vocab_size = self.shared.weight.shape[0] # retrieve correct absolute scope for embed token wrapper with tf.compat.v1.variable_scope("model.shared") as shared_abs_scope_name: pass # Wraps layer to avoid problems with weight restoring and ensuring we're in the correct TF scope. embed_tokens = TFWrappedEmbeddings(self.shared, abs_scope_name=shared_abs_scope_name) self.encoder.set_embed_tokens(embed_tokens) self.decoder.set_embed_tokens(embed_tokens) def call( self, input_ids=None, attention_mask=None, decoder_input_ids=None, decoder_attention_mask=None, head_mask=None, decoder_head_mask=None, cross_attn_head_mask=None, encoder_outputs: Optional[Union[Tuple, TFBaseModelOutput]] = None, past_key_values=None, inputs_embeds=None, decoder_inputs_embeds=None, use_cache=None, output_attentions=None, output_hidden_states=None, return_dict=None, training=False, **kwargs ): inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, decoder_input_ids=decoder_input_ids, decoder_attention_mask=decoder_attention_mask, head_mask=head_mask, decoder_head_mask=decoder_head_mask, cross_attn_head_mask=cross_attn_head_mask, encoder_outputs=encoder_outputs, past_key_values=past_key_values, inputs_embeds=inputs_embeds, decoder_inputs_embeds=decoder_inputs_embeds, use_cache=use_cache, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, training=training, kwargs_call=kwargs, ) if inputs["decoder_input_ids"] is None and inputs["decoder_inputs_embeds"] is None: inputs["use_cache"] = False inputs["output_hidden_states"] = ( inputs["output_hidden_states"] if inputs["output_hidden_states"] is not None else self.config.output_hidden_states ) if inputs["encoder_outputs"] is None: inputs["encoder_outputs"] = self.encoder( input_ids=inputs["input_ids"], attention_mask=inputs["attention_mask"], head_mask=inputs["head_mask"], inputs_embeds=inputs["inputs_embeds"], output_attentions=inputs["output_attentions"], output_hidden_states=inputs["output_hidden_states"], return_dict=inputs["return_dict"], training=inputs["training"], ) # If the user passed a tuple for encoder_outputs, we wrap it in a TFBaseModelOutput when return_dict=True elif inputs["return_dict"] and not isinstance(inputs["encoder_outputs"], TFBaseModelOutput): inputs["encoder_outputs"] = TFBaseModelOutput( last_hidden_state=inputs["encoder_outputs"][0], hidden_states=inputs["encoder_outputs"][1] if len(inputs["encoder_outputs"]) > 1 else None, attentions=inputs["encoder_outputs"][2] if len(inputs["encoder_outputs"]) > 2 else None, ) # If the user passed a TFBaseModelOutput for encoder_outputs, we wrap it in a tuple when return_dict=False elif not inputs["return_dict"] and not isinstance(inputs["encoder_outputs"], tuple): inputs["encoder_outputs"] = inputs["encoder_outputs"].to_tuple() decoder_outputs = self.decoder( inputs["decoder_input_ids"], attention_mask=inputs["decoder_attention_mask"], encoder_hidden_states=inputs["encoder_outputs"][0], encoder_attention_mask=inputs["attention_mask"], head_mask=inputs["decoder_head_mask"], cross_attn_head_mask=inputs["cross_attn_head_mask"], past_key_values=inputs["past_key_values"], inputs_embeds=inputs["decoder_inputs_embeds"], use_cache=inputs["use_cache"], output_attentions=inputs["output_attentions"], output_hidden_states=inputs["output_hidden_states"], return_dict=inputs["return_dict"], training=inputs["training"], ) if not inputs["return_dict"]: return decoder_outputs + inputs["encoder_outputs"] return TFSeq2SeqModelOutput( last_hidden_state=decoder_outputs.last_hidden_state, past_key_values=decoder_outputs.past_key_values, decoder_hidden_states=decoder_outputs.hidden_states, decoder_attentions=decoder_outputs.attentions, cross_attentions=decoder_outputs.cross_attentions, encoder_last_hidden_state=inputs["encoder_outputs"].last_hidden_state, encoder_hidden_states=inputs["encoder_outputs"].hidden_states, encoder_attentions=inputs["encoder_outputs"].attentions, ) @add_start_docstrings( "The bare PEGASUS Model outputting raw hidden-states without any specific head on top.", PEGASUS_START_DOCSTRING, ) class TFPegasusModel(TFPegasusPreTrainedModel): def __init__(self, config: PegasusConfig, *inputs, **kwargs): super().__init__(config, *inputs, **kwargs) self.model = TFPegasusMainLayer(config, name="model") def get_encoder(self): return self.model.encoder def get_decoder(self): return self.model.decoder @add_start_docstrings_to_model_forward(PEGASUS_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint=_CHECKPOINT_FOR_DOC, output_type=TFSeq2SeqModelOutput, config_class=_CONFIG_FOR_DOC, ) def call( self, input_ids=None, attention_mask=None, decoder_input_ids=None, decoder_attention_mask=None, head_mask=None, decoder_head_mask=None, cross_attn_head_mask=None, encoder_outputs: Optional[Union[Tuple, TFBaseModelOutput]] = None, past_key_values=None, inputs_embeds=None, decoder_inputs_embeds=None, use_cache=None, output_attentions=None, output_hidden_states=None, return_dict=None, training=False, **kwargs ): inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, decoder_input_ids=decoder_input_ids, decoder_attention_mask=decoder_attention_mask, head_mask=head_mask, decoder_head_mask=decoder_head_mask, cross_attn_head_mask=cross_attn_head_mask, encoder_outputs=encoder_outputs, past_key_values=past_key_values, inputs_embeds=inputs_embeds, decoder_inputs_embeds=decoder_inputs_embeds, use_cache=use_cache, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, training=training, kwargs_call=kwargs, ) outputs = self.model( input_ids=inputs["input_ids"], attention_mask=inputs["attention_mask"], decoder_input_ids=inputs["decoder_input_ids"], decoder_attention_mask=inputs["decoder_attention_mask"], head_mask=inputs["head_mask"], decoder_head_mask=inputs["decoder_head_mask"], cross_attn_head_mask=inputs["cross_attn_head_mask"], encoder_outputs=inputs["encoder_outputs"], past_key_values=inputs["past_key_values"], inputs_embeds=inputs["inputs_embeds"], decoder_inputs_embeds=inputs["decoder_inputs_embeds"], use_cache=inputs["use_cache"], output_attentions=inputs["output_attentions"], output_hidden_states=inputs["output_hidden_states"], return_dict=inputs["return_dict"], training=inputs["training"], ) return outputs # Copied from transformers.models.bart.modeling_tf_bart.TFBartModel.serving_output def serving_output(self, output): pkv = tf.tuple(output.past_key_values)[1] if self.config.use_cache else None dec_hs = tf.convert_to_tensor(output.decoder_hidden_states) if self.config.output_hidden_states else None dec_attns = tf.convert_to_tensor(output.decoder_attentions) if self.config.output_attentions else None cross_attns = tf.convert_to_tensor(output.cross_attentions) if self.config.output_attentions else None enc_hs = tf.convert_to_tensor(output.encoder_hidden_states) if self.config.output_hidden_states else None enc_attns = tf.convert_to_tensor(output.encoder_attentions) if self.config.output_attentions else None return TFSeq2SeqModelOutput( last_hidden_state=output.last_hidden_state, past_key_values=pkv, decoder_hidden_states=dec_hs, decoder_attentions=dec_attns, cross_attentions=cross_attns, encoder_last_hidden_state=output.encoder_last_hidden_state, encoder_hidden_states=enc_hs, encoder_attentions=enc_attns, ) @add_start_docstrings( "The PEGASUS Model with a language modeling head. Can be used for summarization.", PEGASUS_START_DOCSTRING, ) class TFPegasusForConditionalGeneration(TFPegasusPreTrainedModel, TFCausalLanguageModelingLoss): _keys_to_ignore_on_load_unexpected = [ r"model.encoder.embed_tokens.weight", r"model.decoder.embed_tokens.weight", ] def __init__(self, config, *inputs, **kwargs): super().__init__(config, *inputs, **kwargs) self.model = TFPegasusMainLayer(config, name="model") self.use_cache = config.use_cache # final_bias_logits is registered as a buffer in pytorch, so not trainable for the the sake of consistency. self.final_logits_bias = self.add_weight( name="final_logits_bias", shape=[1, config.vocab_size], initializer="zeros", trainable=False ) def get_decoder(self): return self.model.decoder def get_encoder(self): return self.model.encoder def get_output_embeddings(self): return self.get_input_embeddings() def set_output_embeddings(self, value): self.set_input_embeddings(value) def get_bias(self): return {"final_logits_bias": self.final_logits_bias} def set_bias(self, value): self.final_logits_bias = value["final_logits_bias"] @add_start_docstrings_to_model_forward(PEGASUS_INPUTS_DOCSTRING) @replace_return_docstrings(output_type=TFSeq2SeqLMOutput, config_class=_CONFIG_FOR_DOC) @add_end_docstrings(PEGASUS_GENERATION_EXAMPLE) def call( self, input_ids=None, attention_mask=None, decoder_input_ids=None, decoder_attention_mask=None, head_mask=None, decoder_head_mask=None, cross_attn_head_mask=None, encoder_outputs: Optional[TFBaseModelOutput] = None, past_key_values=None, inputs_embeds=None, decoder_inputs_embeds=None, use_cache=None, output_attentions=None, output_hidden_states=None, return_dict=None, labels=None, training=False, **kwargs, ): """ labels (:obj:`tf.tensor` of shape :obj:`(batch_size, sequence_length)`, `optional`): Labels for computing the masked language modeling loss. Indices should either be in ``[0, ..., config.vocab_size]`` or -100 (see ``input_ids`` docstring). Tokens with indices set to ``-100`` are ignored (masked), the loss is only computed for the tokens with labels in ``[0, ..., config.vocab_size]``. Returns: """ inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, decoder_input_ids=decoder_input_ids, decoder_attention_mask=decoder_attention_mask, head_mask=head_mask, decoder_head_mask=decoder_head_mask, cross_attn_head_mask=cross_attn_head_mask, encoder_outputs=encoder_outputs, past_key_values=past_key_values, inputs_embeds=inputs_embeds, decoder_inputs_embeds=decoder_inputs_embeds, use_cache=use_cache, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, labels=labels, training=training, kwargs_call=kwargs, ) if inputs["labels"] is not None: inputs["labels"] = tf.where( inputs["labels"] == self.config.pad_token_id, tf.fill(shape_list(inputs["labels"]), -100), inputs["labels"], ) inputs["use_cache"] = False if inputs["decoder_input_ids"] is None: inputs["decoder_input_ids"] = shift_tokens_right( inputs["labels"], self.config.pad_token_id, self.config.decoder_start_token_id ) outputs = self.model( inputs["input_ids"], attention_mask=inputs["attention_mask"], decoder_input_ids=inputs["decoder_input_ids"], encoder_outputs=inputs["encoder_outputs"], decoder_attention_mask=inputs["decoder_attention_mask"], head_mask=inputs["head_mask"], decoder_head_mask=inputs["decoder_head_mask"], cross_attn_head_mask=inputs["cross_attn_head_mask"], past_key_values=inputs["past_key_values"], inputs_embeds=inputs["inputs_embeds"], decoder_inputs_embeds=inputs["decoder_inputs_embeds"], use_cache=inputs["use_cache"], output_attentions=inputs["output_attentions"], output_hidden_states=inputs["output_hidden_states"], return_dict=inputs["return_dict"], training=inputs["training"], ) lm_logits = self.model.shared(outputs[0], mode="linear") lm_logits = lm_logits + self.final_logits_bias masked_lm_loss = None if inputs["labels"] is None else self.compute_loss(inputs["labels"], lm_logits) if not inputs["return_dict"]: output = (lm_logits,) + outputs[1:] return ((masked_lm_loss,) + output) if masked_lm_loss is not None else output return TFSeq2SeqLMOutput( loss=masked_lm_loss, logits=lm_logits, past_key_values=outputs.past_key_values, # index 1 of d outputs decoder_hidden_states=outputs.decoder_hidden_states, # index 2 of d outputs decoder_attentions=outputs.decoder_attentions, # index 3 of d outputs cross_attentions=outputs.cross_attentions, # index 4 of d outputs encoder_last_hidden_state=outputs.encoder_last_hidden_state, # index 0 of encoder outputs encoder_hidden_states=outputs.encoder_hidden_states, # 1 of e out encoder_attentions=outputs.encoder_attentions, # 2 of e out ) # Copied from transformers.models.bart.modeling_tf_bart.TFBartForConditionalGeneration.serving_output def serving_output(self, output): pkv = tf.tuple(output.past_key_values)[1] if self.config.use_cache else None dec_hs = tf.convert_to_tensor(output.decoder_hidden_states) if self.config.output_hidden_states else None dec_attns = tf.convert_to_tensor(output.decoder_attentions) if self.config.output_attentions else None cross_attns = tf.convert_to_tensor(output.cross_attentions) if self.config.output_attentions else None enc_hs = tf.convert_to_tensor(output.encoder_hidden_states) if self.config.output_hidden_states else None enc_attns = tf.convert_to_tensor(output.encoder_attentions) if self.config.output_attentions else None return TFSeq2SeqLMOutput( logits=output.logits, past_key_values=pkv, decoder_hidden_states=dec_hs, decoder_attentions=dec_attns, cross_attentions=cross_attns, encoder_last_hidden_state=output.encoder_last_hidden_state, encoder_hidden_states=enc_hs, encoder_attentions=enc_attns, ) # Copied from transformers.models.bart.modeling_tf_bart.TFBartForConditionalGeneration.prepare_inputs_for_generation def prepare_inputs_for_generation( self, decoder_input_ids, past, attention_mask, head_mask=None, decoder_head_mask=None, cross_attn_head_mask=None, use_cache=None, **kwargs, ) -> Dict: assert past is not None and len(past) in {1, 2}, f"past has to be an iterable of length 1,2 got {past}" if len(past) == 1: assert isinstance(past[0], tf.Tensor), f"`past[0]` has to be of type `tf.Tensor`, but is {type(past[0])}" encoder_outputs = TFBaseModelOutput(last_hidden_state=past[0]) past_key_values = None else: assert ( len(past) == 2 ), "`past` has to be of length 2 with the encoder_outputs at the first position and past_key_values at the second position." encoder_outputs, past_key_values = past if isinstance(encoder_outputs, tuple): assert isinstance( encoder_outputs[0], tf.Tensor ), f"`encoder_outputs[0]` has to be of type `tf.Tensor`, but is {type(encoder_outputs[0])}" encoder_outputs = TFBaseModelOutput(last_hidden_state=encoder_outputs[0]) elif isinstance(encoder_outputs, tf.Tensor): encoder_outputs = TFBaseModelOutput(last_hidden_state=encoder_outputs) assert ( past_key_values ), f"decoder cached states must be truthy. got {past_key_values} from the 2nd element of past" decoder_input_ids = decoder_input_ids[:, -1:] assert isinstance( encoder_outputs, TFBaseModelOutput ), f"encoder_outputs should be a TFBaseModelOutput, Instead got {type(encoder_outputs)}." return { "input_ids": None, # encoder_outputs is defined. input_ids not needed "encoder_outputs": encoder_outputs, "past_key_values": past_key_values, "decoder_input_ids": decoder_input_ids, "attention_mask": attention_mask, "head_mask": head_mask, "decoder_head_mask": decoder_head_mask, "cross_attn_head_mask": cross_attn_head_mask, "use_cache": use_cache, # change this to avoid caching (presumably for debugging) } def prepare_decoder_input_ids_from_labels(self, labels: tf.Tensor): return shift_tokens_right(labels, self.config.pad_token_id, self.config.decoder_start_token_id) @staticmethod # Copied from transformers.models.bart.modeling_tf_bart.TFBartForConditionalGeneration._reorder_cache def _reorder_cache(past, beam_idx): if len(past) == 1: return past past_key_values = past[1] reordered_past = () for layer_past_key_values in past_key_values: reordered_past += ( tuple(tf.gather(layer_past_key_value, beam_idx) for layer_past_key_value in layer_past_key_values[:2]) + layer_past_key_values[2:], ) return (past[0], reordered_past)

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import random from typing import Dict, Optional, Tuple, Union import numpy as np import tensorflow as tf from ...activations_tf import get_tf_activation from ...file_utils import ( add_code_sample_docstrings, add_end_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings, ) from ...modeling_tf_outputs import ( TFBaseModelOutput, TFBaseModelOutputWithPastAndCrossAttentions, TFSeq2SeqLMOutput, TFSeq2SeqModelOutput, ) from ...modeling_tf_utils import ( DUMMY_INPUTS, TFCausalLanguageModelingLoss, TFPreTrainedModel, TFSharedEmbeddings, TFWrappedEmbeddings, input_processing, keras_serializable, shape_list, ) from ...utils import logging from .configuration_pegasus import PegasusConfig logger = logging.get_logger(__name__) _CHECKPOINT_FOR_DOC = "google/pegasus-large" _CONFIG_FOR_DOC = "PegasusConfig" _TOKENIZER_FOR_DOC = "PegasusTokenizer" LARGE_NEGATIVE = -1e8 def shift_tokens_right(input_ids: tf.Tensor, pad_token_id: int, decoder_start_token_id: int): start_tokens = tf.fill((shape_list(input_ids)[0], 1), decoder_start_token_id) shifted_input_ids = tf.concat([start_tokens, input_ids[:, :-1]], -1) shifted_input_ids = tf.where( shifted_input_ids == -100, tf.fill(shape_list(shifted_input_ids), pad_token_id), shifted_input_ids ) if tf.executing_eagerly(): assert_gte0 = tf.debugging.assert_greater_equal(shifted_input_ids, tf.constant(0)) with tf.control_dependencies([assert_gte0]): shifted_input_ids = tf.identity(shifted_input_ids) return shifted_input_ids def _make_causal_mask(input_ids_shape: tf.TensorShape, past_key_values_length: int = 0): bsz, tgt_len = input_ids_shape mask = tf.ones((tgt_len, tgt_len)) * LARGE_NEGATIVE mask_cond = tf.range(shape_list(mask)[-1]) mask = tf.where(mask_cond < tf.reshape(mask_cond + 1, (shape_list(mask)[-1], 1)), 0.0, mask) if past_key_values_length > 0: mask = tf.concat([tf.zeros((tgt_len, past_key_values_length)), mask], axis=-1) return tf.tile(mask[None, None, :, :], (bsz, 1, 1, 1)) def _expand_mask(mask: tf.Tensor, tgt_len: Optional[int] = None, past_key_values_length: int = 0): src_len = shape_list(mask)[1] tgt_len = tgt_len if tgt_len is not None else src_len one_cst = tf.constant(1.0) mask = tf.cast(mask, dtype=one_cst.dtype) expanded_mask = tf.tile(mask[:, None, None, :], (1, 1, tgt_len, 1)) return (one_cst - expanded_mask) * LARGE_NEGATIVE class TFPegasusSinusoidalPositionalEmbedding(tf.keras.layers.Layer): def __init__(self, num_positions: int, embedding_dim: int, **kwargs): super().__init__(**kwargs) if embedding_dim % 2 != 0: raise NotImplementedError(f"odd embedding_dim {embedding_dim} not supported") self.embedding_dim = embedding_dim self.num_positions = num_positions def build(self, input_shape: tf.TensorShape): weight = self._init_weight(self.num_positions, self.embedding_dim) self.weight = self.add_weight( name="embeddings", shape=[self.num_positions, self.embedding_dim], ) weight = tf.cast(weight, dtype=self.weight.dtype) self.weight.assign(weight) super().build(input_shape) @staticmethod def _init_weight(n_pos: int, dim: int): position_enc = np.array( [[pos / np.power(10000, 2 * (j // 2) / dim) for j in range(dim)] for pos in range(n_pos)] ) position_enc[:, 0 : dim // 2] = np.sin(position_enc[:, 0::2]) position_enc[:, dim // 2 :] = np.cos(position_enc[:, 1::2]) table = tf.convert_to_tensor(position_enc) tf.stop_gradient(table) return table def call(self, input_shape: tf.TensorShape, past_key_values_length: int = 0): bsz, seq_len = input_shape[:2] positions = tf.range(past_key_values_length, seq_len + past_key_values_length, delta=1, name="range") return tf.gather(self.weight, positions) class TFPegasusAttention(tf.keras.layers.Layer): def __init__( self, embed_dim: int, num_heads: int, dropout: float = 0.0, is_decoder: bool = False, bias: bool = True, **kwargs, ): super().__init__(**kwargs) self.embed_dim = embed_dim self.num_heads = num_heads self.dropout = tf.keras.layers.Dropout(dropout) self.head_dim = embed_dim // num_heads assert self.head_dim * num_heads == self.embed_dim, "embed_dim must be divisible by num_heads" self.scaling = self.head_dim ** -0.5 self.is_decoder = is_decoder self.k_proj = tf.keras.layers.Dense(embed_dim, use_bias=bias, name="k_proj") self.q_proj = tf.keras.layers.Dense(embed_dim, use_bias=bias, name="q_proj") self.v_proj = tf.keras.layers.Dense(embed_dim, use_bias=bias, name="v_proj") self.out_proj = tf.keras.layers.Dense(embed_dim, use_bias=bias, name="out_proj") def _shape(self, tensor: tf.Tensor, seq_len: int, bsz: int): return tf.transpose(tf.reshape(tensor, (bsz, seq_len, self.num_heads, self.head_dim)), (0, 2, 1, 3)) def call( self, hidden_states: tf.Tensor, key_value_states: Optional[tf.Tensor] = None, past_key_value: Optional[Tuple[Tuple[tf.Tensor]]] = None, attention_mask: Optional[tf.Tensor] = None, layer_head_mask: Optional[tf.Tensor] = None, training=False, ) -> Tuple[tf.Tensor, Optional[tf.Tensor]]: is_cross_attention = key_value_states is not None bsz, tgt_len, embed_dim = shape_list(hidden_states) query_states = self.q_proj(hidden_states) * self.scaling if is_cross_attention and past_key_value is not None: key_states = past_key_value[0] value_states = past_key_value[1] elif is_cross_attention: key_states = self._shape(self.k_proj(key_value_states), -1, bsz) value_states = self._shape(self.v_proj(key_value_states), -1, bsz) elif past_key_value is not None: key_states = self._shape(self.k_proj(hidden_states), -1, bsz) value_states = self._shape(self.v_proj(hidden_states), -1, bsz) key_states = tf.concat([past_key_value[0], key_states], axis=2) value_states = tf.concat([past_key_value[1], value_states], axis=2) else: key_states = self._shape(self.k_proj(hidden_states), -1, bsz) value_states = self._shape(self.v_proj(hidden_states), -1, bsz) if self.is_decoder: past_key_value = (key_states, value_states) proj_shape = (bsz * self.num_heads, -1, self.head_dim) query_states = tf.reshape(self._shape(query_states, tgt_len, bsz), proj_shape) key_states = tf.reshape(key_states, proj_shape) value_states = tf.reshape(value_states, proj_shape) src_len = shape_list(key_states)[1] attn_weights = tf.matmul(query_states, key_states, transpose_b=True) if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(attn_weights), [bsz * self.num_heads, tgt_len, src_len], message=f"Attention weights should be of size {(bsz * self.num_heads, tgt_len, src_len)}, but is {shape_list(attn_weights)}", ) if attention_mask is not None: if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(attention_mask), [bsz, 1, tgt_len, src_len], message=f"Attention mask should be of size {(bsz, 1, tgt_len, src_len)}, but is {shape_list(attention_mask)}", ) attention_mask = tf.cast(attention_mask, dtype=attn_weights.dtype) attn_weights = tf.reshape(attn_weights, (bsz, self.num_heads, tgt_len, src_len)) + attention_mask attn_weights = tf.reshape(attn_weights, (bsz * self.num_heads, tgt_len, src_len)) attn_weights = tf.nn.softmax(attn_weights, axis=-1) if layer_head_mask is not None: if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(layer_head_mask), [self.num_heads], message=f"Head mask for a single layer should be of size {(self.num_heads)}, but is {shape_list(layer_head_mask)}", ) attn_weights = tf.reshape(layer_head_mask, (1, -1, 1, 1)) * tf.reshape( attn_weights, (bsz, self.num_heads, tgt_len, src_len) ) attn_weights = tf.reshape(attn_weights, (bsz * self.num_heads, tgt_len, src_len)) attn_probs = self.dropout(attn_weights, training=training) attn_output = tf.matmul(attn_probs, value_states) if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(attn_output), [bsz * self.num_heads, tgt_len, self.head_dim], message=f"`attn_output` should be of size {(bsz, self.num_heads, tgt_len, self.head_dim)}, but is {shape_list(attn_output)}", ) attn_output = tf.transpose( tf.reshape(attn_output, (bsz, self.num_heads, tgt_len, self.head_dim)), (0, 2, 1, 3) ) attn_output = tf.reshape(attn_output, (bsz, tgt_len, embed_dim)) attn_output = self.out_proj(attn_output) attn_weights: tf.Tensor = tf.reshape(attn_weights, (bsz, self.num_heads, tgt_len, src_len)) return attn_output, attn_weights, past_key_value class TFPegasusEncoderLayer(tf.keras.layers.Layer): def __init__(self, config: PegasusConfig, **kwargs): super().__init__(**kwargs) self.embed_dim = config.d_model self.self_attn = TFPegasusAttention( self.embed_dim, config.encoder_attention_heads, dropout=config.attention_dropout, name="self_attn" ) self.self_attn_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="self_attn_layer_norm") self.dropout = tf.keras.layers.Dropout(config.dropout) self.activation_fn = get_tf_activation(config.activation_function) self.activation_dropout = tf.keras.layers.Dropout(config.activation_dropout) self.fc1 = tf.keras.layers.Dense(config.encoder_ffn_dim, name="fc1") self.fc2 = tf.keras.layers.Dense(self.embed_dim, name="fc2") self.final_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="final_layer_norm") def call(self, hidden_states: tf.Tensor, attention_mask: tf.Tensor, layer_head_mask: tf.Tensor, training=False): residual = hidden_states hidden_states = self.self_attn_layer_norm(hidden_states) hidden_states, self_attn_weights, _ = self.self_attn( hidden_states=hidden_states, attention_mask=attention_mask, layer_head_mask=layer_head_mask ) if tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(hidden_states), shape_list(residual), message=f"Self attn modified the shape of query {shape_list(residual)} to {shape_list(hidden_states)}", ) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states residual = hidden_states hidden_states = self.final_layer_norm(hidden_states) hidden_states = self.activation_fn(self.fc1(hidden_states)) hidden_states = self.activation_dropout(hidden_states, training=training) hidden_states = self.fc2(hidden_states) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states return hidden_states, self_attn_weights class TFPegasusDecoderLayer(tf.keras.layers.Layer): def __init__(self, config: PegasusConfig, **kwargs): super().__init__(**kwargs) self.embed_dim = config.d_model self.self_attn = TFPegasusAttention( embed_dim=self.embed_dim, num_heads=config.decoder_attention_heads, dropout=config.attention_dropout, name="self_attn", is_decoder=True, ) self.dropout = tf.keras.layers.Dropout(config.dropout) self.activation_fn = get_tf_activation(config.activation_function) self.activation_dropout = tf.keras.layers.Dropout(config.activation_dropout) self.self_attn_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="self_attn_layer_norm") self.encoder_attn = TFPegasusAttention( self.embed_dim, config.decoder_attention_heads, dropout=config.attention_dropout, name="encoder_attn", is_decoder=True, ) self.encoder_attn_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="encoder_attn_layer_norm") self.fc1 = tf.keras.layers.Dense(config.decoder_ffn_dim, name="fc1") self.fc2 = tf.keras.layers.Dense(self.embed_dim, name="fc2") self.final_layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="final_layer_norm") def call( self, hidden_states, attention_mask: Optional[tf.Tensor] = None, encoder_hidden_states: Optional[tf.Tensor] = None, encoder_attention_mask: Optional[tf.Tensor] = None, layer_head_mask: Optional[tf.Tensor] = None, cross_attn_layer_head_mask: Optional[tf.Tensor] = None, past_key_value: Optional[Tuple[tf.Tensor]] = None, training=False, ) -> Tuple[tf.Tensor, tf.Tensor, Tuple[Tuple[tf.Tensor]]]: residual = hidden_states hidden_states = self.self_attn_layer_norm(hidden_states) self_attn_past_key_value = past_key_value[:2] if past_key_value is not None else None hidden_states, self_attn_weights, present_key_value = self.self_attn( hidden_states=hidden_states, past_key_value=self_attn_past_key_value, attention_mask=attention_mask, layer_head_mask=layer_head_mask, ) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states cross_attn_present_key_value = None cross_attn_weights = None if encoder_hidden_states is not None: residual = hidden_states hidden_states = self.encoder_attn_layer_norm(hidden_states) cross_attn_past_key_value = past_key_value[-2:] if past_key_value is not None else None hidden_states, cross_attn_weights, cross_attn_present_key_value = self.encoder_attn( hidden_states=hidden_states, key_value_states=encoder_hidden_states, attention_mask=encoder_attention_mask, layer_head_mask=cross_attn_layer_head_mask, past_key_value=cross_attn_past_key_value, ) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states present_key_value = present_key_value + cross_attn_present_key_value residual = hidden_states hidden_states = self.final_layer_norm(hidden_states) hidden_states = self.activation_fn(self.fc1(hidden_states)) hidden_states = self.activation_dropout(hidden_states, training=training) hidden_states = self.fc2(hidden_states) hidden_states = self.dropout(hidden_states, training=training) hidden_states = residual + hidden_states return ( hidden_states, self_attn_weights, cross_attn_weights, present_key_value, ) class TFPegasusPreTrainedModel(TFPreTrainedModel): config_class = PegasusConfig base_model_prefix = "model" @property def dummy_inputs(self): pad_token = 1 input_ids = tf.cast(tf.convert_to_tensor(DUMMY_INPUTS), tf.int32) decoder_input_ids = tf.cast(tf.convert_to_tensor(DUMMY_INPUTS), tf.int32) dummy_inputs = { "decoder_input_ids": decoder_input_ids, "attention_mask": tf.math.not_equal(input_ids, pad_token), "input_ids": input_ids, } return dummy_inputs @tf.function( input_signature=[ { "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"), "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"), "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"), "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"), } ] ) def serving(self, inputs): output = self.call(inputs) return self.serving_output(output) PEGASUS_START_DOCSTRING = r""" This model inherits from :class:`~transformers.TFPreTrainedModel`. Check the superclass documentation for the generic methods the library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads etc.) This model is also a `tf.keras.Model <https://www.tensorflow.org/api_docs/python/tf/keras/Model>`__ subclass. Use it as a regular TF 2.0 Keras Model and refer to the TF 2.0 documentation for all matter related to general usage and behavior. .. note:: TF 2.0 models accepts two formats as inputs: - having all inputs as keyword arguments (like PyTorch models), or - having all inputs as a list, tuple or dict in the first positional arguments. This second option is useful when using :meth:`tf.keras.Model.fit` method which currently requires having all the tensors in the first argument of the model call function: :obj:`model(inputs)`. If you choose this second option, there are three possibilities you can use to gather all the input Tensors in the first positional argument : - a single Tensor with :obj:`input_ids` only and nothing else: :obj:`model(input_ids)` - a list of varying length with one or several input Tensors IN THE ORDER given in the docstring: :obj:`model([input_ids, attention_mask])` or :obj:`model([input_ids, attention_mask, token_type_ids])` - a dictionary with one or several input Tensors associated to the input names given in the docstring: :obj:`model({"input_ids": input_ids, "token_type_ids": token_type_ids})` Args: config (:class:`~transformers.PegasusConfig`): Model configuration class with all the parameters of the model. Initializing with a config file does not load the weights associated with the model, only the configuration. Check out the :meth:`~transformers.TFPreTrainedModel.from_pretrained` method to load the model weights. """ PEGASUS_GENERATION_EXAMPLE = r""" Summarization example:: >>> from transformers import PegasusTokenizer, TFPegasusForConditionalGeneration >>> model = TFPegasusForConditionalGeneration.from_pretrained('google/pegasus-xsum') >>> tokenizer = PegasusTokenizer.from_pretrained('google/pegasus-xsum') >>> ARTICLE_TO_SUMMARIZE = ( ... "PG&E stated it scheduled the blackouts in response to forecasts for high winds " ... "amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were " ... "scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow." ... ) >>> inputs = tokenizer([ARTICLE_TO_SUMMARIZE], max_length=1024, return_tensors='tf') >>> # Generate Summary >>> summary_ids = model.generate(inputs['input_ids']) >>> print([tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids]) """ PEGASUS_INPUTS_DOCSTRING = r""" Args: input_ids (:obj:`tf.Tensor` of shape :obj:`({0})`): Indices of input sequence tokens in the vocabulary. Indices can be obtained using :class:`~transformers.PegasusTokenizer`. See :meth:`transformers.PreTrainedTokenizer.encode` and :meth:`transformers.PreTrainedTokenizer.__call__` for details. `What are input IDs? <../glossary.html#input-ids>`__ attention_mask (:obj:`tf.Tensor` of shape :obj:`({0})`, `optional`): Mask to avoid performing attention on padding token indices. Mask values selected in ``[0, 1]``: - 1 for tokens that are **not masked**, - 0 for tokens that are **masked**. `What are attention masks? <../glossary.html#attention-mask>`__ decoder_input_ids (:obj:`tf.Tensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`): Indices of decoder input sequence tokens in the vocabulary. Indices can be obtained using :class:`~transformers.PegasusTokenizer`. See :meth:`transformers.PreTrainedTokenizer.encode` and :meth:`transformers.PreTrainedTokenizer.__call__` for details. `What are decoder input IDs? <../glossary.html#decoder-input-ids>`__ Pegasus uses the :obj:`pad_token_id` as the starting token for :obj:`decoder_input_ids` generation. If :obj:`past_key_values` is used, optionally only the last :obj:`decoder_input_ids` have to be input (see :obj:`past_key_values`). decoder_attention_mask (:obj:`tf.Tensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`): will be made by default and ignore pad tokens. It is not recommended to set this for most use cases. head_mask (:obj:`tf.Tensor` of shape :obj:`(encoder_layers, encoder_attention_heads)`, `optional`): Mask to nullify selected heads of the attention modules in the encoder. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. decoder_head_mask (:obj:`tf.Tensor` of shape :obj:`(decoder_layers, decoder_attention_heads)`, `optional`): Mask to nullify selected heads of the attention modules in the decoder. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. cross_attn_head_mask (:obj:`tf.Tensor` of shape :obj:`(decoder_layers, decoder_attention_heads)`, `optional`): Mask to nullify selected heads of the cross-attention modules. Mask values selected in ``[0, 1]``: - 1 indicates the head is **not masked**, - 0 indicates the head is **masked**. encoder_outputs (:obj:`tf.FloatTensor`, `optional`): hidden states at the output of the last layer of the encoder. Used in the cross-attention of the decoder. of shape :obj:`(batch_size, sequence_length, hidden_size)` is a sequence of past_key_values (:obj:`Tuple[Tuple[tf.Tensor]]` of length :obj:`config.n_layers`) contains precomputed key and value hidden states of the attention blocks. Can be used to speed up decoding. If :obj:`past_key_values` are used, the user can optionally input only the last :obj:`decoder_input_ids` (those that don't have their past key value states given to this model) of shape :obj:`(batch_size, 1)` instead of all :obj:`decoder_input_ids` of shape :obj:`(batch_size, sequence_length)`. use_cache (:obj:`bool`, `optional`, defaults to :obj:`True`): If set to :obj:`True`, :obj:`past_key_values` key value states are returned and can be used to speed up decoding (see :obj:`past_key_values`). Set to :obj:`False` during training, :obj:`True` during generation output_attentions (:obj:`bool`, `optional`): Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. output_attentions (:obj:`bool`, `optional`): Whether or not to return the attentions tensors of all attention layers. See ``attentions`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. output_hidden_states (:obj:`bool`, `optional`): Whether or not to return the hidden states of all layers. See ``hidden_states`` under returned tensors for more detail. This argument can be used only in eager mode, in graph mode the value in the config will be used instead. return_dict (:obj:`bool`, `optional`): Whether or not to return a :class:`~transformers.file_utils.ModelOutput` instead of a plain tuple. This argument can be used in eager mode, in graph mode the value will always be set to True. training (:obj:`bool`, `optional`, defaults to :obj:`False`): Whether or not to use the model in training mode (some modules like dropout modules have different behaviors between training and evaluation). """ @keras_serializable class TFPegasusEncoder(tf.keras.layers.Layer): config_class = PegasusConfig def __init__(self, config: PegasusConfig, embed_tokens: Optional[TFSharedEmbeddings] = None, **kwargs): super().__init__(**kwargs) self.config = config self.dropout = tf.keras.layers.Dropout(config.dropout) self.layerdrop = config.encoder_layerdrop self.padding_idx = config.pad_token_id self.max_source_positions = config.max_position_embeddings self.embed_scale = tf.math.sqrt(float(config.d_model)) if config.scale_embedding else 1.0 self.embed_tokens = embed_tokens self.embed_positions = TFPegasusSinusoidalPositionalEmbedding( config.max_position_embeddings, config.d_model, name="embed_positions", ) self.layers = [TFPegasusEncoderLayer(config, name=f"layers.{i}") for i in range(config.encoder_layers)] self.layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="layer_norm") def get_embed_tokens(self): return self.embed_tokens def set_embed_tokens(self, embed_tokens): self.embed_tokens = embed_tokens def call( self, input_ids=None, inputs_embeds=None, attention_mask=None, head_mask=None, output_attentions=None, output_hidden_states=None, return_dict=None, training=False, **kwargs, ): inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, head_mask=head_mask, inputs_embeds=inputs_embeds, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, training=training, kwargs_call=kwargs, ) if inputs["input_ids"] is not None and inputs["inputs_embeds"] is not None: raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time") elif inputs["input_ids"] is not None: input_shape = shape_list(inputs["input_ids"]) elif inputs["inputs_embeds"] is not None: input_shape = shape_list(inputs["inputs_embeds"])[:-1] else: raise ValueError("You have to specify either input_ids or inputs_embeds") if inputs["inputs_embeds"] is None: inputs["inputs_embeds"] = self.embed_tokens(inputs["input_ids"]) * self.embed_scale embed_pos = self.embed_positions(input_shape) hidden_states = inputs["inputs_embeds"] + embed_pos hidden_states = self.dropout(hidden_states, training=inputs["training"]) # check attention mask and invert if inputs["attention_mask"] is not None: # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] attention_mask = _expand_mask(inputs["attention_mask"]) else: attention_mask = None encoder_states = () if inputs["output_hidden_states"] else None all_attentions = () if inputs["output_attentions"] else None # check if head_mask has a correct number of layers specified if desired # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. if inputs["head_mask"] is not None and tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(inputs["head_mask"])[0], len(self.layers), message=f"The head_mask should be specified for {len(self.layers)} layers, but it is for {shape_list(inputs['head_mask'])[0]}.", ) # encoder layers for idx, encoder_layer in enumerate(self.layers): if inputs["output_hidden_states"]: encoder_states = encoder_states + (hidden_states,) # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description) dropout_probability = random.uniform(0, 1) if inputs["training"] and (dropout_probability < self.layerdrop): # skip the layer continue hidden_states, attn = encoder_layer( hidden_states, attention_mask, inputs["head_mask"][idx] if inputs["head_mask"] is not None else None, ) if inputs["output_attentions"]: all_attentions += (attn,) hidden_states = self.layer_norm(hidden_states) if inputs["output_hidden_states"]: encoder_states = encoder_states + (hidden_states,) if not inputs["return_dict"]: return tuple(v for v in [hidden_states, encoder_states, all_attentions] if v is not None) return TFBaseModelOutput( last_hidden_state=hidden_states, hidden_states=encoder_states, attentions=all_attentions ) @keras_serializable class TFPegasusDecoder(tf.keras.layers.Layer): config_class = PegasusConfig def __init__(self, config: PegasusConfig, embed_tokens: Optional[TFSharedEmbeddings] = None, **kwargs): super().__init__(**kwargs) self.config = config self.padding_idx = config.pad_token_id self.embed_tokens = embed_tokens self.layerdrop = config.decoder_layerdrop self.embed_positions = TFPegasusSinusoidalPositionalEmbedding( config.max_position_embeddings, config.d_model, name="embed_positions", ) self.embed_scale = tf.math.sqrt(float(config.d_model)) if config.scale_embedding else 1.0 self.layers = [TFPegasusDecoderLayer(config, name=f"layers.{i}") for i in range(config.decoder_layers)] self.layer_norm = tf.keras.layers.LayerNormalization(epsilon=1e-5, name="layer_norm") self.dropout = tf.keras.layers.Dropout(config.dropout) def get_embed_tokens(self): return self.embed_tokens def set_embed_tokens(self, embed_tokens): self.embed_tokens = embed_tokens def call( self, input_ids=None, inputs_embeds=None, attention_mask=None, encoder_hidden_states=None, encoder_attention_mask=None, head_mask=None, cross_attn_head_mask=None, past_key_values=None, use_cache=None, output_attentions=None, output_hidden_states=None, return_dict=None, training=False, **kwargs, ): inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, encoder_hidden_states=encoder_hidden_states, encoder_attention_mask=encoder_attention_mask, head_mask=head_mask, cross_attn_head_mask=cross_attn_head_mask, inputs_embeds=inputs_embeds, past_key_values=past_key_values, use_cache=use_cache, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, training=training, kwargs_call=kwargs, ) if inputs["input_ids"] is not None and inputs["inputs_embeds"] is not None: raise ValueError("You cannot specify both decoder_input_ids and decoder_inputs_embeds at the same time") elif inputs["input_ids"] is not None: input_shape = shape_list(inputs["input_ids"]) elif inputs["inputs_embeds"] is not None: input_shape = shape_list(inputs["inputs_embeds"])[:-1] else: raise ValueError("You have to specify either decoder_input_ids or decoder_inputs_embeds") past_key_values_length = ( shape_list(inputs["past_key_values"][0][0])[2] if inputs["past_key_values"] is not None else 0 ) # embed positions positions = self.embed_positions(input_shape, past_key_values_length) if inputs["inputs_embeds"] is None: inputs["inputs_embeds"] = self.embed_tokens(inputs["input_ids"]) * self.embed_scale hidden_states = inputs["inputs_embeds"] # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] if input_shape[-1] > 1: combined_attention_mask = _make_causal_mask(input_shape, past_key_values_length=past_key_values_length) else: combined_attention_mask = _expand_mask( tf.ones((input_shape[0], input_shape[1] + past_key_values_length)), tgt_len=input_shape[-1] ) if inputs["attention_mask"] is not None: combined_attention_mask = combined_attention_mask + _expand_mask( inputs["attention_mask"], tgt_len=input_shape[-1] ) if inputs["encoder_hidden_states"] is not None and inputs["encoder_attention_mask"] is not None: # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] inputs["encoder_attention_mask"] = _expand_mask(inputs["encoder_attention_mask"], tgt_len=input_shape[-1]) hidden_states = self.dropout(hidden_states + positions, training=inputs["training"]) # decoder layers all_hidden_states = () if inputs["output_hidden_states"] else None all_self_attns = () if inputs["output_attentions"] else None all_cross_attns = () if (inputs["output_attentions"] and inputs["encoder_hidden_states"] is not None) else None present_key_values = () if inputs["use_cache"] else None # check if head_mask and cross_attn_head_mask have a correct number of layers specified if desired # The tf.debugging asserts are not compliant with XLA then they # have to be disabled in other modes than eager. for attn_mask in ["head_mask", "cross_attn_head_mask"]: if inputs[attn_mask] is not None and tf.executing_eagerly(): tf.debugging.assert_equal( shape_list(inputs[attn_mask])[0], len(self.layers), message=f"The {attn_mask} should be specified for {len(self.layers)} layers, but it is for {shape_list(inputs[attn_mask])[0]}.", ) for idx, decoder_layer in enumerate(self.layers): # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description) if inputs["output_hidden_states"]: all_hidden_states += (hidden_states,) dropout_probability = random.uniform(0, 1) if inputs["training"] and (dropout_probability < self.layerdrop): continue past_key_value = inputs["past_key_values"][idx] if inputs["past_key_values"] is not None else None hidden_states, layer_self_attn, layer_cross_attn, present_key_value = decoder_layer( hidden_states, attention_mask=combined_attention_mask, encoder_hidden_states=inputs["encoder_hidden_states"], encoder_attention_mask=inputs["encoder_attention_mask"], layer_head_mask=inputs["head_mask"][idx] if inputs["head_mask"] is not None else None, cross_attn_layer_head_mask=inputs["cross_attn_head_mask"][idx] if inputs["cross_attn_head_mask"] is not None else None, past_key_value=past_key_value, ) if inputs["use_cache"]: present_key_values += (present_key_value,) if inputs["output_attentions"]: all_self_attns += (layer_self_attn,) if inputs["encoder_hidden_states"] is not None: all_cross_attns += (layer_cross_attn,) hidden_states = self.layer_norm(hidden_states) if inputs["output_hidden_states"]: all_hidden_states += (hidden_states,) if inputs["output_attentions"]: all_self_attns = list(all_self_attns) if inputs["encoder_hidden_states"] is not None: all_cross_attns = list(all_cross_attns) if inputs["use_cache"]: present_key_values = (inputs["encoder_hidden_states"], present_key_values) if not inputs["return_dict"]: return hidden_states, present_key_values, all_hidden_states, all_self_attns, all_cross_attns else: return TFBaseModelOutputWithPastAndCrossAttentions( last_hidden_state=hidden_states, past_key_values=present_key_values, hidden_states=all_hidden_states, attentions=all_self_attns, cross_attentions=all_cross_attns, ) @keras_serializable class TFPegasusMainLayer(tf.keras.layers.Layer): config_class = PegasusConfig def __init__(self, config: PegasusConfig, **kwargs): super().__init__(**kwargs) self.config = config self.shared = TFSharedEmbeddings(config.vocab_size, config.d_model, config.pad_token_id, name="model.shared") with tf.compat.v1.variable_scope("model.shared") as shared_abs_scope_name: pass # Wraps layer to avoid problems with weight restoring and ensuring we're in the correct TF scope. embed_tokens = TFWrappedEmbeddings(self.shared, abs_scope_name=shared_abs_scope_name) embed_tokens.vocab_size = self.shared.vocab_size embed_tokens.hidden_size = self.shared.hidden_size self.encoder = TFPegasusEncoder(config, embed_tokens, name="encoder") self.decoder = TFPegasusDecoder(config, embed_tokens, name="decoder") def get_input_embeddings(self): return self.shared def set_input_embeddings(self, new_embeddings): self.shared.weight = new_embeddings self.shared.vocab_size = self.shared.weight.shape[0] with tf.compat.v1.variable_scope("model.shared") as shared_abs_scope_name: pass embed_tokens = TFWrappedEmbeddings(self.shared, abs_scope_name=shared_abs_scope_name) self.encoder.set_embed_tokens(embed_tokens) self.decoder.set_embed_tokens(embed_tokens) def call( self, input_ids=None, attention_mask=None, decoder_input_ids=None, decoder_attention_mask=None, head_mask=None, decoder_head_mask=None, cross_attn_head_mask=None, encoder_outputs: Optional[Union[Tuple, TFBaseModelOutput]] = None, past_key_values=None, inputs_embeds=None, decoder_inputs_embeds=None, use_cache=None, output_attentions=None, output_hidden_states=None, return_dict=None, training=False, **kwargs ): inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, decoder_input_ids=decoder_input_ids, decoder_attention_mask=decoder_attention_mask, head_mask=head_mask, decoder_head_mask=decoder_head_mask, cross_attn_head_mask=cross_attn_head_mask, encoder_outputs=encoder_outputs, past_key_values=past_key_values, inputs_embeds=inputs_embeds, decoder_inputs_embeds=decoder_inputs_embeds, use_cache=use_cache, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, training=training, kwargs_call=kwargs, ) if inputs["decoder_input_ids"] is None and inputs["decoder_inputs_embeds"] is None: inputs["use_cache"] = False inputs["output_hidden_states"] = ( inputs["output_hidden_states"] if inputs["output_hidden_states"] is not None else self.config.output_hidden_states ) if inputs["encoder_outputs"] is None: inputs["encoder_outputs"] = self.encoder( input_ids=inputs["input_ids"], attention_mask=inputs["attention_mask"], head_mask=inputs["head_mask"], inputs_embeds=inputs["inputs_embeds"], output_attentions=inputs["output_attentions"], output_hidden_states=inputs["output_hidden_states"], return_dict=inputs["return_dict"], training=inputs["training"], ) # If the user passed a tuple for encoder_outputs, we wrap it in a TFBaseModelOutput when return_dict=True elif inputs["return_dict"] and not isinstance(inputs["encoder_outputs"], TFBaseModelOutput): inputs["encoder_outputs"] = TFBaseModelOutput( last_hidden_state=inputs["encoder_outputs"][0], hidden_states=inputs["encoder_outputs"][1] if len(inputs["encoder_outputs"]) > 1 else None, attentions=inputs["encoder_outputs"][2] if len(inputs["encoder_outputs"]) > 2 else None, ) # If the user passed a TFBaseModelOutput for encoder_outputs, we wrap it in a tuple when return_dict=False elif not inputs["return_dict"] and not isinstance(inputs["encoder_outputs"], tuple): inputs["encoder_outputs"] = inputs["encoder_outputs"].to_tuple() decoder_outputs = self.decoder( inputs["decoder_input_ids"], attention_mask=inputs["decoder_attention_mask"], encoder_hidden_states=inputs["encoder_outputs"][0], encoder_attention_mask=inputs["attention_mask"], head_mask=inputs["decoder_head_mask"], cross_attn_head_mask=inputs["cross_attn_head_mask"], past_key_values=inputs["past_key_values"], inputs_embeds=inputs["decoder_inputs_embeds"], use_cache=inputs["use_cache"], output_attentions=inputs["output_attentions"], output_hidden_states=inputs["output_hidden_states"], return_dict=inputs["return_dict"], training=inputs["training"], ) if not inputs["return_dict"]: return decoder_outputs + inputs["encoder_outputs"] return TFSeq2SeqModelOutput( last_hidden_state=decoder_outputs.last_hidden_state, past_key_values=decoder_outputs.past_key_values, decoder_hidden_states=decoder_outputs.hidden_states, decoder_attentions=decoder_outputs.attentions, cross_attentions=decoder_outputs.cross_attentions, encoder_last_hidden_state=inputs["encoder_outputs"].last_hidden_state, encoder_hidden_states=inputs["encoder_outputs"].hidden_states, encoder_attentions=inputs["encoder_outputs"].attentions, ) @add_start_docstrings( "The bare PEGASUS Model outputting raw hidden-states without any specific head on top.", PEGASUS_START_DOCSTRING, ) class TFPegasusModel(TFPegasusPreTrainedModel): def __init__(self, config: PegasusConfig, *inputs, **kwargs): super().__init__(config, *inputs, **kwargs) self.model = TFPegasusMainLayer(config, name="model") def get_encoder(self): return self.model.encoder def get_decoder(self): return self.model.decoder @add_start_docstrings_to_model_forward(PEGASUS_INPUTS_DOCSTRING.format("batch_size, sequence_length")) @add_code_sample_docstrings( tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint=_CHECKPOINT_FOR_DOC, output_type=TFSeq2SeqModelOutput, config_class=_CONFIG_FOR_DOC, ) def call( self, input_ids=None, attention_mask=None, decoder_input_ids=None, decoder_attention_mask=None, head_mask=None, decoder_head_mask=None, cross_attn_head_mask=None, encoder_outputs: Optional[Union[Tuple, TFBaseModelOutput]] = None, past_key_values=None, inputs_embeds=None, decoder_inputs_embeds=None, use_cache=None, output_attentions=None, output_hidden_states=None, return_dict=None, training=False, **kwargs ): inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, decoder_input_ids=decoder_input_ids, decoder_attention_mask=decoder_attention_mask, head_mask=head_mask, decoder_head_mask=decoder_head_mask, cross_attn_head_mask=cross_attn_head_mask, encoder_outputs=encoder_outputs, past_key_values=past_key_values, inputs_embeds=inputs_embeds, decoder_inputs_embeds=decoder_inputs_embeds, use_cache=use_cache, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, training=training, kwargs_call=kwargs, ) outputs = self.model( input_ids=inputs["input_ids"], attention_mask=inputs["attention_mask"], decoder_input_ids=inputs["decoder_input_ids"], decoder_attention_mask=inputs["decoder_attention_mask"], head_mask=inputs["head_mask"], decoder_head_mask=inputs["decoder_head_mask"], cross_attn_head_mask=inputs["cross_attn_head_mask"], encoder_outputs=inputs["encoder_outputs"], past_key_values=inputs["past_key_values"], inputs_embeds=inputs["inputs_embeds"], decoder_inputs_embeds=inputs["decoder_inputs_embeds"], use_cache=inputs["use_cache"], output_attentions=inputs["output_attentions"], output_hidden_states=inputs["output_hidden_states"], return_dict=inputs["return_dict"], training=inputs["training"], ) return outputs # Copied from transformers.models.bart.modeling_tf_bart.TFBartModel.serving_output def serving_output(self, output): pkv = tf.tuple(output.past_key_values)[1] if self.config.use_cache else None dec_hs = tf.convert_to_tensor(output.decoder_hidden_states) if self.config.output_hidden_states else None dec_attns = tf.convert_to_tensor(output.decoder_attentions) if self.config.output_attentions else None cross_attns = tf.convert_to_tensor(output.cross_attentions) if self.config.output_attentions else None enc_hs = tf.convert_to_tensor(output.encoder_hidden_states) if self.config.output_hidden_states else None enc_attns = tf.convert_to_tensor(output.encoder_attentions) if self.config.output_attentions else None return TFSeq2SeqModelOutput( last_hidden_state=output.last_hidden_state, past_key_values=pkv, decoder_hidden_states=dec_hs, decoder_attentions=dec_attns, cross_attentions=cross_attns, encoder_last_hidden_state=output.encoder_last_hidden_state, encoder_hidden_states=enc_hs, encoder_attentions=enc_attns, ) @add_start_docstrings( "The PEGASUS Model with a language modeling head. Can be used for summarization.", PEGASUS_START_DOCSTRING, ) class TFPegasusForConditionalGeneration(TFPegasusPreTrainedModel, TFCausalLanguageModelingLoss): _keys_to_ignore_on_load_unexpected = [ r"model.encoder.embed_tokens.weight", r"model.decoder.embed_tokens.weight", ] def __init__(self, config, *inputs, **kwargs): super().__init__(config, *inputs, **kwargs) self.model = TFPegasusMainLayer(config, name="model") self.use_cache = config.use_cache # final_bias_logits is registered as a buffer in pytorch, so not trainable for the the sake of consistency. self.final_logits_bias = self.add_weight( name="final_logits_bias", shape=[1, config.vocab_size], initializer="zeros", trainable=False ) def get_decoder(self): return self.model.decoder def get_encoder(self): return self.model.encoder def get_output_embeddings(self): return self.get_input_embeddings() def set_output_embeddings(self, value): self.set_input_embeddings(value) def get_bias(self): return {"final_logits_bias": self.final_logits_bias} def set_bias(self, value): self.final_logits_bias = value["final_logits_bias"] @add_start_docstrings_to_model_forward(PEGASUS_INPUTS_DOCSTRING) @replace_return_docstrings(output_type=TFSeq2SeqLMOutput, config_class=_CONFIG_FOR_DOC) @add_end_docstrings(PEGASUS_GENERATION_EXAMPLE) def call( self, input_ids=None, attention_mask=None, decoder_input_ids=None, decoder_attention_mask=None, head_mask=None, decoder_head_mask=None, cross_attn_head_mask=None, encoder_outputs: Optional[TFBaseModelOutput] = None, past_key_values=None, inputs_embeds=None, decoder_inputs_embeds=None, use_cache=None, output_attentions=None, output_hidden_states=None, return_dict=None, labels=None, training=False, **kwargs, ): inputs = input_processing( func=self.call, config=self.config, input_ids=input_ids, attention_mask=attention_mask, decoder_input_ids=decoder_input_ids, decoder_attention_mask=decoder_attention_mask, head_mask=head_mask, decoder_head_mask=decoder_head_mask, cross_attn_head_mask=cross_attn_head_mask, encoder_outputs=encoder_outputs, past_key_values=past_key_values, inputs_embeds=inputs_embeds, decoder_inputs_embeds=decoder_inputs_embeds, use_cache=use_cache, output_attentions=output_attentions, output_hidden_states=output_hidden_states, return_dict=return_dict, labels=labels, training=training, kwargs_call=kwargs, ) if inputs["labels"] is not None: inputs["labels"] = tf.where( inputs["labels"] == self.config.pad_token_id, tf.fill(shape_list(inputs["labels"]), -100), inputs["labels"], ) inputs["use_cache"] = False if inputs["decoder_input_ids"] is None: inputs["decoder_input_ids"] = shift_tokens_right( inputs["labels"], self.config.pad_token_id, self.config.decoder_start_token_id ) outputs = self.model( inputs["input_ids"], attention_mask=inputs["attention_mask"], decoder_input_ids=inputs["decoder_input_ids"], encoder_outputs=inputs["encoder_outputs"], decoder_attention_mask=inputs["decoder_attention_mask"], head_mask=inputs["head_mask"], decoder_head_mask=inputs["decoder_head_mask"], cross_attn_head_mask=inputs["cross_attn_head_mask"], past_key_values=inputs["past_key_values"], inputs_embeds=inputs["inputs_embeds"], decoder_inputs_embeds=inputs["decoder_inputs_embeds"], use_cache=inputs["use_cache"], output_attentions=inputs["output_attentions"], output_hidden_states=inputs["output_hidden_states"], return_dict=inputs["return_dict"], training=inputs["training"], ) lm_logits = self.model.shared(outputs[0], mode="linear") lm_logits = lm_logits + self.final_logits_bias masked_lm_loss = None if inputs["labels"] is None else self.compute_loss(inputs["labels"], lm_logits) if not inputs["return_dict"]: output = (lm_logits,) + outputs[1:] return ((masked_lm_loss,) + output) if masked_lm_loss is not None else output return TFSeq2SeqLMOutput( loss=masked_lm_loss, logits=lm_logits, past_key_values=outputs.past_key_values, # index 1 of d outputs decoder_hidden_states=outputs.decoder_hidden_states, # index 2 of d outputs decoder_attentions=outputs.decoder_attentions, # index 3 of d outputs cross_attentions=outputs.cross_attentions, # index 4 of d outputs encoder_last_hidden_state=outputs.encoder_last_hidden_state, # index 0 of encoder outputs encoder_hidden_states=outputs.encoder_hidden_states, # 1 of e out encoder_attentions=outputs.encoder_attentions, # 2 of e out ) # Copied from transformers.models.bart.modeling_tf_bart.TFBartForConditionalGeneration.serving_output def serving_output(self, output): pkv = tf.tuple(output.past_key_values)[1] if self.config.use_cache else None dec_hs = tf.convert_to_tensor(output.decoder_hidden_states) if self.config.output_hidden_states else None dec_attns = tf.convert_to_tensor(output.decoder_attentions) if self.config.output_attentions else None cross_attns = tf.convert_to_tensor(output.cross_attentions) if self.config.output_attentions else None enc_hs = tf.convert_to_tensor(output.encoder_hidden_states) if self.config.output_hidden_states else None enc_attns = tf.convert_to_tensor(output.encoder_attentions) if self.config.output_attentions else None return TFSeq2SeqLMOutput( logits=output.logits, past_key_values=pkv, decoder_hidden_states=dec_hs, decoder_attentions=dec_attns, cross_attentions=cross_attns, encoder_last_hidden_state=output.encoder_last_hidden_state, encoder_hidden_states=enc_hs, encoder_attentions=enc_attns, ) # Copied from transformers.models.bart.modeling_tf_bart.TFBartForConditionalGeneration.prepare_inputs_for_generation def prepare_inputs_for_generation( self, decoder_input_ids, past, attention_mask, head_mask=None, decoder_head_mask=None, cross_attn_head_mask=None, use_cache=None, **kwargs, ) -> Dict: assert past is not None and len(past) in {1, 2}, f"past has to be an iterable of length 1,2 got {past}" if len(past) == 1: assert isinstance(past[0], tf.Tensor), f"`past[0]` has to be of type `tf.Tensor`, but is {type(past[0])}" encoder_outputs = TFBaseModelOutput(last_hidden_state=past[0]) past_key_values = None else: assert ( len(past) == 2 ), "`past` has to be of length 2 with the encoder_outputs at the first position and past_key_values at the second position." encoder_outputs, past_key_values = past if isinstance(encoder_outputs, tuple): assert isinstance( encoder_outputs[0], tf.Tensor ), f"`encoder_outputs[0]` has to be of type `tf.Tensor`, but is {type(encoder_outputs[0])}" encoder_outputs = TFBaseModelOutput(last_hidden_state=encoder_outputs[0]) elif isinstance(encoder_outputs, tf.Tensor): encoder_outputs = TFBaseModelOutput(last_hidden_state=encoder_outputs) assert ( past_key_values ), f"decoder cached states must be truthy. got {past_key_values} from the 2nd element of past" decoder_input_ids = decoder_input_ids[:, -1:] assert isinstance( encoder_outputs, TFBaseModelOutput ), f"encoder_outputs should be a TFBaseModelOutput, Instead got {type(encoder_outputs)}." return { "input_ids": None, # encoder_outputs is defined. input_ids not needed "encoder_outputs": encoder_outputs, "past_key_values": past_key_values, "decoder_input_ids": decoder_input_ids, "attention_mask": attention_mask, "head_mask": head_mask, "decoder_head_mask": decoder_head_mask, "cross_attn_head_mask": cross_attn_head_mask, "use_cache": use_cache, # change this to avoid caching (presumably for debugging) } def prepare_decoder_input_ids_from_labels(self, labels: tf.Tensor): return shift_tokens_right(labels, self.config.pad_token_id, self.config.decoder_start_token_id) @staticmethod # Copied from transformers.models.bart.modeling_tf_bart.TFBartForConditionalGeneration._reorder_cache def _reorder_cache(past, beam_idx): if len(past) == 1: return past past_key_values = past[1] reordered_past = () for layer_past_key_values in past_key_values: reordered_past += ( tuple(tf.gather(layer_past_key_value, beam_idx) for layer_past_key_value in layer_past_key_values[:2]) + layer_past_key_values[2:], ) return (past[0], reordered_past)

true

f7187934ae933740a1f4b6303e02e4e7822c4691

9,491

py

Python

scripts/compile_prosivic_results.py

mrksbrg/adas-pro-sivic

fb4bbd4f39b58e42c3d47494fb4116a3e7fced0d

[ "BSD-2-Clause" ]

4

2020-04-05T01:49:24.000Z

2021-11-15T03:01:55.000Z

scripts/compile_prosivic_results.py

sukhvir-chauhan-1999/adas-pro-sivic

fb4bbd4f39b58e42c3d47494fb4116a3e7fced0d

[ "BSD-2-Clause" ]

null

scripts/compile_prosivic_results.py

sukhvir-chauhan-1999/adas-pro-sivic

fb4bbd4f39b58e42c3d47494fb4116a3e7fced0d

[ "BSD-2-Clause" ]

3

2020-04-05T01:49:26.000Z

2021-09-28T07:09:41.000Z

import os import statistics import csv from collections import Counter import pandas as pd import numpy as np class ExpSetup: def __init__(self, ped_x, ped_y, ped_orient, ped_speed, car_speed, min_dist, min_ttc, min_dist_awa, det, col): self.ped_x = ped_x self.ped_y = ped_y self.ped_orient = ped_orient self.ped_speed = ped_speed self.car_speed = car_speed self.min_dist_counter = Counter([min_dist]) self.min_dist = [min_dist] self.min_ttc = [min_ttc] self.min_ttc_counter = Counter([min_ttc]) self.min_dist_awa = [min_dist_awa] self.min_dist_awa_counter = Counter(([min_dist_awa])) self.detection = [det] self.collision = [col] self.nbr_results = 1 self.results = Counter([ExpResult(min_dist, min_ttc, min_dist_awa, det, col)]) def __str__(self): return "### Scenario (x0P=" + str(self.ped_x) + ", y0P=" + str(self.ped_y) + ", Th0P=" + str(self.ped_orient) + ", v0P=" + str(self.ped_speed) + ", v0C=" + str(self.car_speed) + ") ###" def __eq__(self, other): return self.ped_x == other.ped_x and self.ped_y == other.ped_y and self.ped_orient == other.ped_orient \ and self.ped_speed == other.ped_speed and self.car_speed == other.car_speed def __lt__(self, other): return self.ped_x < other.ped_x def add_result(self, min_dist, min_ttc, min_dist_awa, det, col): self.min_dist.append(min_dist) self.min_dist_counter.update([min_dist]) self.min_ttc.append(min_ttc) self.min_ttc_counter.update([min_ttc]) self.min_dist_awa.append(min_dist_awa) self.min_dist_awa_counter.update([min_dist_awa]) self.detection.append(det) self.collision.append(col) self.nbr_results += 1 self.results.update([ExpResult(min_dist, min_ttc, min_dist_awa, det, col)]) def get_nbr_results(self): return self.nbr_results def get_results(self): return self.results def get_nbr_unique_results(self): unique_list_of1 = [] unique_list_of2 = [] unique_list_of3 = [] for x in self.min_dist: if x not in unique_list_of1: unique_list_of1.append(x) for y in self.min_ttc: if y not in unique_list_of2: unique_list_of2.append(y) for z in self.min_dist_awa: if z not in unique_list_of3: unique_list_of3.append(z) return {'of1': unique_list_of1, 'of2': unique_list_of2, 'of3': unique_list_of3} def get_avg_min_dist(self): sum = 0 for res in self.min_dist: sum += res return sum / len(self.min_dist) def get_sd_min_dist(self): if len(self.min_dist) == 1: return 0 else: return statistics.stdev(self.min_dist) def get_avg_min_ttc(self): sum = 0 for res in self.min_ttc: sum += res return sum / len(self.min_ttc) def get_sd_min_ttc(self): if len(self.min_ttc) == 1: return 0 else: return statistics.stdev(self.min_ttc) def get_avg_min_dist_awa(self): sum = 0 for res in self.min_dist_awa: sum += res return sum / len(self.min_dist_awa) def get_sd_min_dist_awa(self): if len(self.min_dist_awa) == 1: return 0 else: return statistics.stdev(self.min_dist_awa) def get_nbr_detections(self): sum = 0 for res in self.detection: sum += res return sum def get_nbr_collisions(self): sum = 0 for res in self.collision: sum += res return sum @property def get_ped_x(self): return self.ped_x @property def get_ped_y(self): return self.ped_y @property def get_ped_orient(self): return self.ped_orient @property def get_ped_speed(self): return self.ped_speed @property def get_car_speed(self): return self.car_speed @property def get_of1_counter(self): return self.min_dist_counter class ExpResult: def __init__(self, min_dist, min_ttc, min_dist_awa, det, col): self.min_dist = min_dist self.min_ttc = min_ttc self.min_dist_awa = min_dist_awa self.detection = det self.collision = col @property def get_min_dist(self): return self.min_dist @property def get_min_ttc(self): return self.min_ttc @property def get_min_dist_awa(self): return self.min_dist_awa @property def get_detected(self): return self.detection @property def get_collision(self): return self.collision def __str__(self): return "\tOF1=" + str(self.min_dist) + ", OF2=" + str(self.min_ttc) + ", OF3=" + str(self.min_dist_awa) + ", Detection=" + str(self.detection) + ", Collision=" + str(self.collision) def __eq__(self, other): return self.min_dist == other.min_dist and self.min_ttc == other.min_ttc and self.min_dist_awa == other.min_dist_awa \ and self.detection == other.detection and self.collision == other.collision def __lt__(self, other): return self.min_dist < other.min_dist def __hash__(self): return hash((self.min_dist, self.min_ttc, self.min_dist_awa, self.detection, self.collision)) dir_name = 'prosivic_results' result_dataframes = [] scenario_results = [] for filename in os.listdir(dir_name): if filename.endswith(".csv"): df = pd.read_csv(dir_name + "\\" + filename) for index, row in df.iterrows(): exp_setup = ExpSetup(row['ped_x'], row['ped_y'], row['ped_orient'], row['ped_speed'], row['car_speed'], row['of1'], row['of2'], row['of3'], row['detection'], row['collision']) if exp_setup not in scenario_results: scenario_results.append(exp_setup) else: #print("Adding results to: " + str(conf)) i = scenario_results.index(exp_setup) scenario_results[i].add_result(row['of1'], row['of2'], row['of3'], row['detection'], row['collision']) with open('mode_prosivic_results.csv', mode='w') as merged_file: mode_writer = csv.writer(merged_file, delimiter=',') mode_writer.writerow(['x0P', 'y0P', 'Th0P', 'v0P', 'v0C', 'OF1', 'OF2', 'OF3', 'det', 'col', 'conf']) #merge_writer.writerow(['x0P', 'y0P', 'Th0P', 'v0P', 'v0C', 'nbr', 'OF1_unique', 'OF1_avg', 'OF1_sd', 'OF2_unique', 'OF2_avg', 'OF2_sd', 'OF3_unique', 'OF3_avg', 'OF3_sd', 'det_true', 'det_false', 'col_true', 'col_false']) for exp_setup in scenario_results: print("\n" + str(exp_setup)) print("\tNumber of results: " + str(exp_setup.get_nbr_results())) res = exp_setup.get_results() for result, count in res.most_common(): print("\t" + str(count) + "x:" + str(result)) unique_per_of = exp_setup.get_nbr_unique_results() print("\t\t# Result per objective function #") print("\t\tmin_dist:\t\tUnique = " + str(len(unique_per_of["of1"])) + "\tAvg = " + str(exp_setup.get_avg_min_dist()) + "\tSD = " + str(exp_setup.get_sd_min_dist())) print("\t\t\tCounter min_dist: " + str(exp_setup.min_dist_counter)) print("\t\tmin_ttc:\t\tUnique = " + str(len(unique_per_of["of2"])) + "\tAvg = " + str(exp_setup.get_avg_min_ttc()) + "\tSD = " + str(exp_setup.get_sd_min_ttc())) print("\t\t\tCounter min_ttc: " + str(exp_setup.min_ttc_counter)) print("\t\tmin_dist_awa:\tUnique = " + str(len(unique_per_of["of3"])) + "\tAvg = " + str(exp_setup.get_avg_min_dist_awa()) + "\tSD = " + str(exp_setup.get_sd_min_dist_awa())) print("\t\t\tCounter min_dist_awa: " + str(exp_setup.min_dist_awa_counter)) print("\t\tNumber detections: " + str(exp_setup.get_nbr_detections()) + " (out of " + str(exp_setup.get_nbr_results()) + " = " + str(100 * (exp_setup.get_nbr_detections()/exp_setup.get_nbr_results())) + "%)") print("\t\tNumber collisions: " + str(exp_setup.get_nbr_collisions()) + " (out of " + str(exp_setup.get_nbr_results()) + " = " + str(100 * (exp_setup.get_nbr_collisions()/exp_setup.get_nbr_results())) + "%)") mode_result = res.most_common(1)[0][0] # this is the most common ExpResult (first element in first tuple in first element in the Counter) conf = (res.most_common(1)[0][1]/exp_setup.get_nbr_results()) # this is the count of the most common results divided by the total number mode_writer.writerow([exp_setup.ped_x, exp_setup.ped_y, exp_setup.ped_orient, exp_setup.ped_speed, exp_setup.car_speed, mode_result.min_dist, mode_result.min_ttc, mode_result.min_dist_awa, mode_result.detection, mode_result.collision, conf]) #merge_writer.writerow([exp_setup.ped_x, exp_setup.ped_y, exp_setup.ped_orient, exp_setup.ped_speed, exp_setup.car_speed, exp_setup.get_nbr_results(), len(unique_per_of["of1"]), exp_setup.get_avg_min_dist(), exp_setup.get_sd_min_dist(), len(unique_per_of["of2"]), exp_setup.get_avg_min_ttc(), exp_setup.get_sd_min_ttc(), len(unique_per_of["of3"]), exp_setup.get_avg_min_dist_awa(), exp_setup.get_sd_min_dist_awa(), exp_setup.get_nbr_detections(), (exp_setup.get_nbr_results() - exp_setup.get_nbr_detections()), exp_setup.get_nbr_collisions(), (exp_setup.get_nbr_results() - exp_setup.get_nbr_collisions())])

40.909483

615

0.640185

import os import statistics import csv from collections import Counter import pandas as pd import numpy as np class ExpSetup: def __init__(self, ped_x, ped_y, ped_orient, ped_speed, car_speed, min_dist, min_ttc, min_dist_awa, det, col): self.ped_x = ped_x self.ped_y = ped_y self.ped_orient = ped_orient self.ped_speed = ped_speed self.car_speed = car_speed self.min_dist_counter = Counter([min_dist]) self.min_dist = [min_dist] self.min_ttc = [min_ttc] self.min_ttc_counter = Counter([min_ttc]) self.min_dist_awa = [min_dist_awa] self.min_dist_awa_counter = Counter(([min_dist_awa])) self.detection = [det] self.collision = [col] self.nbr_results = 1 self.results = Counter([ExpResult(min_dist, min_ttc, min_dist_awa, det, col)]) def __str__(self): return "### Scenario (x0P=" + str(self.ped_x) + ", y0P=" + str(self.ped_y) + ", Th0P=" + str(self.ped_orient) + ", v0P=" + str(self.ped_speed) + ", v0C=" + str(self.car_speed) + ") ###" def __eq__(self, other): return self.ped_x == other.ped_x and self.ped_y == other.ped_y and self.ped_orient == other.ped_orient \ and self.ped_speed == other.ped_speed and self.car_speed == other.car_speed def __lt__(self, other): return self.ped_x < other.ped_x def add_result(self, min_dist, min_ttc, min_dist_awa, det, col): self.min_dist.append(min_dist) self.min_dist_counter.update([min_dist]) self.min_ttc.append(min_ttc) self.min_ttc_counter.update([min_ttc]) self.min_dist_awa.append(min_dist_awa) self.min_dist_awa_counter.update([min_dist_awa]) self.detection.append(det) self.collision.append(col) self.nbr_results += 1 self.results.update([ExpResult(min_dist, min_ttc, min_dist_awa, det, col)]) def get_nbr_results(self): return self.nbr_results def get_results(self): return self.results def get_nbr_unique_results(self): unique_list_of1 = [] unique_list_of2 = [] unique_list_of3 = [] for x in self.min_dist: if x not in unique_list_of1: unique_list_of1.append(x) for y in self.min_ttc: if y not in unique_list_of2: unique_list_of2.append(y) for z in self.min_dist_awa: if z not in unique_list_of3: unique_list_of3.append(z) return {'of1': unique_list_of1, 'of2': unique_list_of2, 'of3': unique_list_of3} def get_avg_min_dist(self): sum = 0 for res in self.min_dist: sum += res return sum / len(self.min_dist) def get_sd_min_dist(self): if len(self.min_dist) == 1: return 0 else: return statistics.stdev(self.min_dist) def get_avg_min_ttc(self): sum = 0 for res in self.min_ttc: sum += res return sum / len(self.min_ttc) def get_sd_min_ttc(self): if len(self.min_ttc) == 1: return 0 else: return statistics.stdev(self.min_ttc) def get_avg_min_dist_awa(self): sum = 0 for res in self.min_dist_awa: sum += res return sum / len(self.min_dist_awa) def get_sd_min_dist_awa(self): if len(self.min_dist_awa) == 1: return 0 else: return statistics.stdev(self.min_dist_awa) def get_nbr_detections(self): sum = 0 for res in self.detection: sum += res return sum def get_nbr_collisions(self): sum = 0 for res in self.collision: sum += res return sum @property def get_ped_x(self): return self.ped_x @property def get_ped_y(self): return self.ped_y @property def get_ped_orient(self): return self.ped_orient @property def get_ped_speed(self): return self.ped_speed @property def get_car_speed(self): return self.car_speed @property def get_of1_counter(self): return self.min_dist_counter class ExpResult: def __init__(self, min_dist, min_ttc, min_dist_awa, det, col): self.min_dist = min_dist self.min_ttc = min_ttc self.min_dist_awa = min_dist_awa self.detection = det self.collision = col @property def get_min_dist(self): return self.min_dist @property def get_min_ttc(self): return self.min_ttc @property def get_min_dist_awa(self): return self.min_dist_awa @property def get_detected(self): return self.detection @property def get_collision(self): return self.collision def __str__(self): return "\tOF1=" + str(self.min_dist) + ", OF2=" + str(self.min_ttc) + ", OF3=" + str(self.min_dist_awa) + ", Detection=" + str(self.detection) + ", Collision=" + str(self.collision) def __eq__(self, other): return self.min_dist == other.min_dist and self.min_ttc == other.min_ttc and self.min_dist_awa == other.min_dist_awa \ and self.detection == other.detection and self.collision == other.collision def __lt__(self, other): return self.min_dist < other.min_dist def __hash__(self): return hash((self.min_dist, self.min_ttc, self.min_dist_awa, self.detection, self.collision)) dir_name = 'prosivic_results' result_dataframes = [] scenario_results = [] for filename in os.listdir(dir_name): if filename.endswith(".csv"): df = pd.read_csv(dir_name + "\\" + filename) for index, row in df.iterrows(): exp_setup = ExpSetup(row['ped_x'], row['ped_y'], row['ped_orient'], row['ped_speed'], row['car_speed'], row['of1'], row['of2'], row['of3'], row['detection'], row['collision']) if exp_setup not in scenario_results: scenario_results.append(exp_setup) else: i = scenario_results.index(exp_setup) scenario_results[i].add_result(row['of1'], row['of2'], row['of3'], row['detection'], row['collision']) with open('mode_prosivic_results.csv', mode='w') as merged_file: mode_writer = csv.writer(merged_file, delimiter=',') mode_writer.writerow(['x0P', 'y0P', 'Th0P', 'v0P', 'v0C', 'OF1', 'OF2', 'OF3', 'det', 'col', 'conf']) for exp_setup in scenario_results: print("\n" + str(exp_setup)) print("\tNumber of results: " + str(exp_setup.get_nbr_results())) res = exp_setup.get_results() for result, count in res.most_common(): print("\t" + str(count) + "x:" + str(result)) unique_per_of = exp_setup.get_nbr_unique_results() print("\t\t# Result per objective function #") print("\t\tmin_dist:\t\tUnique = " + str(len(unique_per_of["of1"])) + "\tAvg = " + str(exp_setup.get_avg_min_dist()) + "\tSD = " + str(exp_setup.get_sd_min_dist())) print("\t\t\tCounter min_dist: " + str(exp_setup.min_dist_counter)) print("\t\tmin_ttc:\t\tUnique = " + str(len(unique_per_of["of2"])) + "\tAvg = " + str(exp_setup.get_avg_min_ttc()) + "\tSD = " + str(exp_setup.get_sd_min_ttc())) print("\t\t\tCounter min_ttc: " + str(exp_setup.min_ttc_counter)) print("\t\tmin_dist_awa:\tUnique = " + str(len(unique_per_of["of3"])) + "\tAvg = " + str(exp_setup.get_avg_min_dist_awa()) + "\tSD = " + str(exp_setup.get_sd_min_dist_awa())) print("\t\t\tCounter min_dist_awa: " + str(exp_setup.min_dist_awa_counter)) print("\t\tNumber detections: " + str(exp_setup.get_nbr_detections()) + " (out of " + str(exp_setup.get_nbr_results()) + " = " + str(100 * (exp_setup.get_nbr_detections()/exp_setup.get_nbr_results())) + "%)") print("\t\tNumber collisions: " + str(exp_setup.get_nbr_collisions()) + " (out of " + str(exp_setup.get_nbr_results()) + " = " + str(100 * (exp_setup.get_nbr_collisions()/exp_setup.get_nbr_results())) + "%)") mode_result = res.most_common(1)[0][0] conf = (res.most_common(1)[0][1]/exp_setup.get_nbr_results()) mode_writer.writerow([exp_setup.ped_x, exp_setup.ped_y, exp_setup.ped_orient, exp_setup.ped_speed, exp_setup.car_speed, mode_result.min_dist, mode_result.min_ttc, mode_result.min_dist_awa, mode_result.detection, mode_result.collision, conf])

true

f7187a6e99e39c6f2ebf4e337d526183e1dbb006

521

py

Python

alveo/neptune/service.py

asirasa-xilinx/Vitis-AI

2ea756d2946d66266c111b09b85f4bcf7fc60764

[ "Apache-2.0" ]

null

alveo/neptune/service.py

asirasa-xilinx/Vitis-AI

2ea756d2946d66266c111b09b85f4bcf7fc60764

[ "Apache-2.0" ]

null

alveo/neptune/service.py

asirasa-xilinx/Vitis-AI

2ea756d2946d66266c111b09b85f4bcf7fc60764

[ "Apache-2.0" ]

null

import os class Service(object): """ The base class for all services. All services inherit from this class """ def __init__(self, prefix, artifacts, graph): self._artifacts = artifacts self._prefix = prefix self._proc = None self._graph = graph def start(self, args): # os.environ["XDNN_VERBOSE"] = "1" # os.environ["XBLAS_EMIT_PROFILING_INFO"] = "1" self._graph.serve(args, background=True) def stop(self): self._graph.stop()

22.652174

73

0.608445

import os class Service(object): def __init__(self, prefix, artifacts, graph): self._artifacts = artifacts self._prefix = prefix self._proc = None self._graph = graph def start(self, args): self._graph.serve(args, background=True) def stop(self): self._graph.stop()

true

f7187a7d00539bb05c8029543eca7c0694b8593d

1,063

py

Python

ExecutingEntryCallingScriptHash/contractB_compiler2.0.py

ONT-Avocados/python-template

0acb5032adf8f4968c5d46cf53681f31ac917650

[ "Apache-2.0" ]

17

2018-09-26T07:09:16.000Z

2020-05-28T06:16:47.000Z

ExecutingEntryCallingScriptHash/contractB_compiler2.0.py

zhangxiaocong/python-template

0acb5032adf8f4968c5d46cf53681f31ac917650

[ "Apache-2.0" ]

8

2018-09-26T02:08:04.000Z

2021-12-14T02:53:26.000Z

ExecutingEntryCallingScriptHash/contractB_compiler2.0.py

zhangxiaocong/python-template

0acb5032adf8f4968c5d46cf53681f31ac917650

[ "Apache-2.0" ]

30

2018-09-25T08:27:42.000Z

2020-12-08T09:02:33.000Z

OntCversion = '2.0.0' from ontology.interop.System.ExecutionEngine import GetExecutingScriptHash, GetCallingScriptHash, GetEntryScriptHash from ontology.interop.System.Runtime import CheckWitness, GetTime, Notify, Serialize, Deserialize ContractAddress = GetExecutingScriptHash() def Main(opration, args): if opration == "invokeB": return invokeB(args[0]) if opration == "avoidToBeInvokedByContract": return avoidToBeInvokedByContract() return False def invokeB(param): Notify(["111_invokeB", param]) # to prevent hack from other contract callerHash = GetCallingScriptHash() entryHash = GetEntryScriptHash() Notify([callerHash, entryHash, ContractAddress]) return True def avoidToBeInvokedByContract(): callerHash = GetCallingScriptHash() entryHash = GetEntryScriptHash() if callerHash != entryHash: Notify(["You are not allowed to invoke this method through contract"]) return False else: Notify(["You can implement what you need to do here!"]) return True

33.21875

116

0.728128

OntCversion = '2.0.0' from ontology.interop.System.ExecutionEngine import GetExecutingScriptHash, GetCallingScriptHash, GetEntryScriptHash from ontology.interop.System.Runtime import CheckWitness, GetTime, Notify, Serialize, Deserialize ContractAddress = GetExecutingScriptHash() def Main(opration, args): if opration == "invokeB": return invokeB(args[0]) if opration == "avoidToBeInvokedByContract": return avoidToBeInvokedByContract() return False def invokeB(param): Notify(["111_invokeB", param]) callerHash = GetCallingScriptHash() entryHash = GetEntryScriptHash() Notify([callerHash, entryHash, ContractAddress]) return True def avoidToBeInvokedByContract(): callerHash = GetCallingScriptHash() entryHash = GetEntryScriptHash() if callerHash != entryHash: Notify(["You are not allowed to invoke this method through contract"]) return False else: Notify(["You can implement what you need to do here!"]) return True

true

f7187bb4fead8b89d8048f1b523ec3b567c0a9ea

25,260

py

Python

src/rosdep2/sources_list.py

tianbot/rosdep

24c8c76a8cb99b08285192013a165f30af0f5232

[ "BSD-3-Clause" ]

2

2021-11-16T10:49:18.000Z

2021-11-16T23:38:11.000Z

src/rosdep2/sources_list.py

tianbot/rosdep

24c8c76a8cb99b08285192013a165f30af0f5232

[ "BSD-3-Clause" ]

null

src/rosdep2/sources_list.py

tianbot/rosdep

24c8c76a8cb99b08285192013a165f30af0f5232

[ "BSD-3-Clause" ]

null

# Copyright (c) 2012, Willow Garage, Inc. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # * Neither the name of the Willow Garage, Inc. nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF # SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. # Author Ken Conley/kwc@willowgarage.com from __future__ import print_function import os import sys import yaml from rosdep2.shell_utils import FakeURLOpener as urlopen try: from urllib.error import URLError import urllib.request as request except ImportError: from urllib2 import URLError import urllib2 as request try: import cPickle as pickle except ImportError: import pickle from .cache_tools import compute_filename_hash, PICKLE_CACHE_EXT, write_atomic, write_cache_file from .core import InvalidData, DownloadFailure, CachePermissionError from .gbpdistro_support import get_gbprepo_as_rosdep_data, download_gbpdistro_as_rosdep_data from .meta import MetaDatabase from ._version import __version__ try: import urlparse except ImportError: import urllib.parse as urlparse # py3k try: import httplib except ImportError: import http.client as httplib # py3k import rospkg import rospkg.distro from .loader import RosdepLoader from .rosdistrohelper import get_index, get_index_url # default file to download with 'init' command in order to bootstrap # rosdep DEFAULT_SOURCES_LIST_URL = 'https://raw.githubusercontent.com/ros/rosdistro/master/rosdep/sources.list.d/20-default.list' # seconds to wait before aborting download of rosdep data DOWNLOAD_TIMEOUT = 15.0 SOURCES_LIST_DIR = 'sources.list.d' SOURCES_CACHE_DIR = 'sources.cache' # name of index file for sources cache CACHE_INDEX = 'index' # extension for binary cache SOURCE_PATH_ENV = 'ROSDEP_SOURCE_PATH' def get_sources_list_dirs(source_list_dir): if SOURCE_PATH_ENV in os.environ: sdirs = os.environ[SOURCE_PATH_ENV].split(os.pathsep) else: sdirs = [source_list_dir] for p in list(sdirs): if not os.path.exists(p): sdirs.remove(p) return sdirs def get_sources_list_dir(): # base of where we read config files from # TODO: windows if 0: # we can't use etc/ros because environment config does not carry over under sudo etc_ros = rospkg.get_etc_ros_dir() else: etc_ros = '/etc/ros' # compute default system wide sources directory sys_sources_list_dir = os.path.join(etc_ros, 'rosdep', SOURCES_LIST_DIR) sources_list_dirs = get_sources_list_dirs(sys_sources_list_dir) if sources_list_dirs: return sources_list_dirs[0] else: return sys_sources_list_dir def get_default_sources_list_file(): return os.path.join(get_sources_list_dir(), '20-default.list') def get_sources_cache_dir(): ros_home = rospkg.get_ros_home() return os.path.join(ros_home, 'rosdep', SOURCES_CACHE_DIR) # Default rosdep.yaml format. For now this is the only valid type and # is specified for future compatibility. TYPE_YAML = 'yaml' # git-buildpackage repo list TYPE_GBPDISTRO = 'gbpdistro' VALID_TYPES = [TYPE_YAML, TYPE_GBPDISTRO] class DataSource(object): def __init__(self, type_, url, tags, origin=None): """ :param type_: data source type, e.g. TYPE_YAML, TYPE_GBPDISTRO :param url: URL of data location. For file resources, must start with the file:// scheme. For remote resources, URL must include a path. :param tags: tags for matching data source to configurations :param origin: filename or other indicator of where data came from for debugging. :raises: :exc:`ValueError` if parameters do not validate """ # validate inputs if type_ not in VALID_TYPES: raise ValueError('type must be one of [%s]' % (','.join(VALID_TYPES))) parsed = urlparse.urlparse(url) if not parsed.scheme or (parsed.scheme != 'file' and not parsed.netloc) or parsed.path in ('', '/'): raise ValueError('url must be a fully-specified URL with scheme, hostname, and path: %s' % (str(url))) if not type(tags) == list: raise ValueError('tags must be a list: %s' % (str(tags))) self.type = type_ self.tags = tags self.url = url self.origin = origin def __eq__(self, other): return isinstance(other, DataSource) and \ self.type == other.type and \ self.tags == other.tags and \ self.url == other.url and \ self.origin == other.origin def __str__(self): if self.origin: return '[%s]:\n%s %s %s' % (self.origin, self.type, self.url, ' '.join(self.tags)) else: return '%s %s %s' % (self.type, self.url, ' '.join(self.tags)) def __repr__(self): return repr((self.type, self.url, self.tags, self.origin)) class RosDistroSource(DataSource): def __init__(self, distro): self.type = TYPE_GBPDISTRO self.tags = [distro] # In this case self.url is a list if REP-143 is being used self.url = get_index().distributions[distro]['distribution'] self.origin = None # create function we can pass in as model to parse_source_data. The # function emulates the CachedDataSource constructor but does the # necessary full filepath calculation and loading of data. def cache_data_source_loader(sources_cache_dir, verbose=False): def create_model(type_, uri, tags, origin=None): # compute the filename has from the URL filename = compute_filename_hash(uri) filepath = os.path.join(sources_cache_dir, filename) pickle_filepath = filepath + PICKLE_CACHE_EXT if os.path.exists(pickle_filepath): if verbose: print('loading cached data source:\n\t%s\n\t%s' % (uri, pickle_filepath), file=sys.stderr) with open(pickle_filepath, 'rb') as f: rosdep_data = pickle.loads(f.read()) elif os.path.exists(filepath): if verbose: print('loading cached data source:\n\t%s\n\t%s' % (uri, filepath), file=sys.stderr) with open(filepath) as f: rosdep_data = yaml.safe_load(f.read()) else: rosdep_data = {} return CachedDataSource(type_, uri, tags, rosdep_data, origin=filepath) return create_model class CachedDataSource(object): def __init__(self, type_, url, tags, rosdep_data, origin=None): """ Stores data source and loaded rosdep data for that source. NOTE: this is not a subclass of DataSource, though it's API is duck-type compatible with the DataSource API. """ self.source = DataSource(type_, url, tags, origin=origin) self.rosdep_data = rosdep_data def __eq__(self, other): try: return self.source == other.source and \ self.rosdep_data == other.rosdep_data except AttributeError: return False def __str__(self): return '%s\n%s' % (self.source, self.rosdep_data) def __repr__(self): return repr((self.type, self.url, self.tags, self.rosdep_data, self.origin)) @property def type(self): """ :returns: data source type """ return self.source.type @property def url(self): """ :returns: data source URL """ return self.source.url @property def tags(self): """ :returns: data source tags """ return self.source.tags @property def origin(self): """ :returns: data source origin, if set, or ``None`` """ return self.source.origin class DataSourceMatcher(object): def __init__(self, tags): self.tags = tags def matches(self, rosdep_data_source): """ Check if the datasource matches this configuration. :param rosdep_data_source: :class:`DataSource` """ # all of the rosdep_data_source tags must be in our matcher tags return not any(set(rosdep_data_source.tags) - set(self.tags)) @staticmethod def create_default(os_override=None): """ Create a :class:`DataSourceMatcher` to match the current configuration. :param os_override: (os_name, os_codename) tuple to override OS detection :returns: :class:`DataSourceMatcher` """ distro_name = rospkg.distro.current_distro_codename() if os_override is None: os_detect = rospkg.os_detect.OsDetect() os_name, os_version, os_codename = os_detect.detect_os() else: os_name, os_codename = os_override tags = [t for t in (distro_name, os_name, os_codename) if t] return DataSourceMatcher(tags) def download_rosdep_data(url): """ :raises: :exc:`DownloadFailure` If data cannot be retrieved (e.g. 404, bad YAML format, server down). """ try: # http/https URLs need custom requests to specify the user-agent, since some repositories reject # requests from the default user-agent. if url.startswith("http://") or url.startswith("https://"): url_request = request.Request(url, headers={'User-Agent': 'rosdep/{version}'.format(version=__version__)}) else: url_request = url f = urlopen(url_request, timeout=DOWNLOAD_TIMEOUT) text = f.read() f.close() data = yaml.safe_load(text) if type(data) != dict: raise DownloadFailure('rosdep data from [%s] is not a YAML dictionary' % (url)) return data except (URLError, httplib.HTTPException) as e: raise DownloadFailure(str(e) + ' (%s)' % url) except yaml.YAMLError as e: raise DownloadFailure(str(e)) def download_default_sources_list(url=DEFAULT_SOURCES_LIST_URL): """ Download (and validate) contents of default sources list. :param url: override URL of default sources list file :return: raw sources list data, ``str`` :raises: :exc:`DownloadFailure` If data cannot be retrieved (e.g. 404, bad YAML format, server down). :raises: :exc:`urllib2.URLError` If data cannot be retrieved (e.g. 404, server down). """ try: f = urlopen(url, timeout=DOWNLOAD_TIMEOUT) except (URLError, httplib.HTTPException) as e: raise URLError(str(e) + ' (%s)' % url) data = f.read().decode() f.close() if not data: raise DownloadFailure('cannot download defaults file from %s : empty contents' % url) # parse just for validation try: parse_sources_data(data) except InvalidData as e: raise DownloadFailure( 'The content downloaded from %s failed to pass validation.' ' It is likely that the source is invalid unless the data was corrupted during the download.' ' The contents were:{{{%s}}} The error raised was: %s' % (url, data, e)) return data def parse_sources_data(data, origin='<string>', model=None): """ Parse sources file format (tags optional):: # comments and empty lines allowed <type> <uri> [tags] e.g.:: yaml http://foo/rosdep.yaml fuerte lucid ubuntu If tags are specified, *all* tags must match the current configuration for the sources data to be used. :param data: data in sources file format :param model: model to load data into. Defaults to :class:`DataSource` :returns: List of data sources, [:class:`DataSource`] :raises: :exc:`InvalidData` """ if model is None: model = DataSource sources = [] for line in data.split('\n'): line = line.strip() # ignore empty lines or comments if not line or line.startswith('#'): continue splits = line.split(' ') if len(splits) < 2: raise InvalidData('invalid line:\n%s' % (line), origin=origin) type_ = splits[0] url = splits[1] tags = splits[2:] try: sources.append(model(type_, url, tags, origin=origin)) except ValueError as e: raise InvalidData('line:\n\t%s\n%s' % (line, e), origin=origin) return sources def parse_sources_file(filepath): """ Parse file on disk :returns: List of data sources, [:class:`DataSource`] :raises: :exc:`InvalidData` If any error occurs reading file, so an I/O error, non-existent file, or invalid format. """ try: with open(filepath, 'r') as f: return parse_sources_data(f.read(), origin=filepath) except IOError as e: raise InvalidData('I/O error reading sources file: %s' % (str(e)), origin=filepath) def parse_sources_list(sources_list_dir=None): """ Parse data stored in on-disk sources list directory into a list of :class:`DataSource` for processing. :returns: List of data sources, [:class:`DataSource`]. If there is no sources list dir, this returns an empty list. :raises: :exc:`InvalidData` :raises: :exc:`OSError` if *sources_list_dir* cannot be read. :raises: :exc:`IOError` if *sources_list_dir* cannot be read. """ if sources_list_dir is None: sources_list_dir = get_sources_list_dir() sources_list_dirs = get_sources_list_dirs(sources_list_dir) filelist = [] for sdir in sources_list_dirs: filelist += sorted([os.path.join(sdir, f) for f in os.listdir(sdir) if f.endswith('.list')]) sources_list = [] for f in filelist: sources_list.extend(parse_sources_file(f)) return sources_list def _generate_key_from_urls(urls): # urls may be a list of urls or a single string try: assert isinstance(urls, (list, basestring)) except NameError: assert isinstance(urls, (list, str)) # We join the urls by the '^' character because it is not allowed in urls return '^'.join(urls if isinstance(urls, list) else [urls]) def update_sources_list(sources_list_dir=None, sources_cache_dir=None, success_handler=None, error_handler=None, skip_eol_distros=False, ros_distro=None): """ Re-downloaded data from remote sources and store in cache. Also update the cache index based on current sources. :param sources_list_dir: override source list directory :param sources_cache_dir: override sources cache directory :param success_handler: fn(DataSource) to call if a particular source loads successfully. This hook is mainly for printing errors to console. :param error_handler: fn(DataSource, DownloadFailure) to call if a particular source fails. This hook is mainly for printing errors to console. :param skip_eol_distros: skip downloading sources for EOL distros :returns: list of (`DataSource`, cache_file_path) pairs for cache files that were updated, ``[str]`` :raises: :exc:`InvalidData` If any of the sources list files is invalid :raises: :exc:`OSError` if *sources_list_dir* cannot be read. :raises: :exc:`IOError` If *sources_list_dir* cannot be read or cache data cannot be written """ if sources_cache_dir is None: sources_cache_dir = get_sources_cache_dir() sources = parse_sources_list(sources_list_dir=sources_list_dir) retval = [] for source in list(sources): try: if source.type == TYPE_YAML: rosdep_data = download_rosdep_data(source.url) elif source.type == TYPE_GBPDISTRO: # DEPRECATED, do not use this file. See REP137 if not source.tags[0] in ['electric', 'fuerte']: print('Ignore legacy gbpdistro "%s"' % source.tags[0]) sources.remove(source) continue # do not store this entry in the cache rosdep_data = download_gbpdistro_as_rosdep_data(source.url) retval.append((source, write_cache_file(sources_cache_dir, source.url, rosdep_data))) if success_handler is not None: success_handler(source) except DownloadFailure as e: if error_handler is not None: error_handler(source, e) # Additional sources for ros distros # In compliance with REP137 and REP143 python_versions = {} print('Query rosdistro index %s' % get_index_url()) distribution_names = get_index().distributions.keys() if ros_distro is not None and ros_distro not in distribution_names: raise ValueError( 'Requested distribution "%s" is not in the index.' % ros_distro) for dist_name in sorted(distribution_names): distribution = get_index().distributions[dist_name] if dist_name != ros_distro: if ros_distro is not None: print('Skip distro "%s" different from requested "%s"' % (dist_name, ros_distro)) continue if skip_eol_distros: if distribution.get('distribution_status') == 'end-of-life': print('Skip end-of-life distro "%s"' % dist_name) continue print('Add distro "%s"' % dist_name) # import pdb; pdb.set_trace() rds = RosDistroSource(dist_name) rosdep_data = get_gbprepo_as_rosdep_data(dist_name) # Store Python version from REP153 if distribution.get('python_version'): python_versions[dist_name] = distribution.get('python_version') # dist_files can either be a string (single filename) or a list (list of filenames) dist_files = distribution['distribution'] key = _generate_key_from_urls(dist_files) retval.append((rds, write_cache_file(sources_cache_dir, key, rosdep_data))) sources.append(rds) # cache metadata that isn't a source list MetaDatabase().set('ROS_PYTHON_VERSION', python_versions) # Create a combined index of *all* the sources. We do all the # sources regardless of failures because a cache from a previous # attempt may still exist. We have to do this cache index so that # loads() see consistent data. if not os.path.exists(sources_cache_dir): os.makedirs(sources_cache_dir) cache_index = os.path.join(sources_cache_dir, CACHE_INDEX) data = "#autogenerated by rosdep, do not edit. use 'rosdep update' instead\n" for source in sources: url = _generate_key_from_urls(source.url) data += 'yaml %s %s\n' % (url, ' '.join(source.tags)) write_atomic(cache_index, data) # mainly for debugging and testing return retval def load_cached_sources_list(sources_cache_dir=None, verbose=False): """ Load cached data based on the sources list. :returns: list of :class:`CachedDataSource` instance with raw rosdep data loaded. :raises: :exc:`OSError` if cache cannot be read :raises: :exc:`IOError` if cache cannot be read """ if sources_cache_dir is None: sources_cache_dir = get_sources_cache_dir() cache_index = os.path.join(sources_cache_dir, 'index') if not os.path.exists(cache_index): if verbose: print('no cache index present, not loading cached sources', file=sys.stderr) return [] try: with open(cache_index, 'r') as f: cache_data = f.read() except IOError as e: if e.strerror == 'Permission denied': raise CachePermissionError('Failed to write cache file: ' + str(e)) else: raise # the loader does all the work model = cache_data_source_loader(sources_cache_dir, verbose=verbose) return parse_sources_data(cache_data, origin=cache_index, model=model) class SourcesListLoader(RosdepLoader): """ SourcesList loader implements the general RosdepLoader API. This implementation is fairly simple as there is only one view the source list loader can create. It is also a bit degenerate as it is not capable of mapping resource names to views, thus any resource-name-based API fails or returns nothing interesting. This loader should not be used directly; instead, it is more useful composed with other higher-level implementations, like the :class:`rosdep2.rospkg_loader.RospkgLoader`. The general intent is to compose it with another loader by making all of the other loader's views depends on all the views in this loader. """ ALL_VIEW_KEY = 'sources.list' def __init__(self, sources): """ :param sources: cached sources list entries, [:class:`CachedDataSource`] """ self.sources = sources @staticmethod def create_default(matcher=None, sources_cache_dir=None, os_override=None, verbose=False): """ :param matcher: override DataSourceMatcher. Defaults to DataSourceMatcher.create_default(). :param sources_cache_dir: override location of sources cache """ if matcher is None: matcher = DataSourceMatcher.create_default(os_override=os_override) if verbose: print('using matcher with tags [%s]' % (', '.join(matcher.tags)), file=sys.stderr) sources = load_cached_sources_list(sources_cache_dir=sources_cache_dir, verbose=verbose) if verbose: print('loaded %s sources' % (len(sources)), file=sys.stderr) sources = [x for x in sources if matcher.matches(x)] if verbose: print('%s sources match current tags' % (len(sources)), file=sys.stderr) return SourcesListLoader(sources) def load_view(self, view_name, rosdep_db, verbose=False): """ Load view data into rosdep_db. If the view has already been loaded into rosdep_db, this method does nothing. :param view_name: name of ROS stack to load, ``str`` :param rosdep_db: database to load stack data into, :class:`RosdepDatabase` :raises: :exc:`InvalidData` """ if rosdep_db.is_loaded(view_name): return source = self.get_source(view_name) if verbose: print('loading view [%s] with sources.list loader' % (view_name), file=sys.stderr) view_dependencies = self.get_view_dependencies(view_name) rosdep_db.set_view_data(view_name, source.rosdep_data, view_dependencies, view_name) def get_loadable_resources(self): return [] def get_loadable_views(self): return [x.url for x in self.sources] def get_view_dependencies(self, view_name): # use dependencies to implement precedence if view_name != SourcesListLoader.ALL_VIEW_KEY: # if the view_name matches one of our sources, return # empty list as none of our sources has deps. if any([x for x in self.sources if view_name == x.url]): return [] # not one of our views, so it depends on everything we provide return [x.url for x in self.sources] def get_source(self, view_name): matches = [x for x in self.sources if x.url == view_name] if matches: return matches[0] else: raise rospkg.ResourceNotFound(view_name) def get_rosdeps(self, resource_name, implicit=True): """ Always raises as SourceListLoader defines no concrete resources with rosdeps. :raises: :exc:`rospkg.ResourceNotFound` """ raise rospkg.ResourceNotFound(resource_name) def get_view_key(self, resource_name): """ Always raises as SourceListLoader defines no concrete resources with rosdeps. :returns: Name of view that *resource_name* is in, ``None`` if no associated view. :raises: :exc:`rospkg.ResourceNotFound` if *resource_name* cannot be found. """ raise rospkg.ResourceNotFound(resource_name)

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from __future__ import print_function import os import sys import yaml from rosdep2.shell_utils import FakeURLOpener as urlopen try: from urllib.error import URLError import urllib.request as request except ImportError: from urllib2 import URLError import urllib2 as request try: import cPickle as pickle except ImportError: import pickle from .cache_tools import compute_filename_hash, PICKLE_CACHE_EXT, write_atomic, write_cache_file from .core import InvalidData, DownloadFailure, CachePermissionError from .gbpdistro_support import get_gbprepo_as_rosdep_data, download_gbpdistro_as_rosdep_data from .meta import MetaDatabase from ._version import __version__ try: import urlparse except ImportError: import urllib.parse as urlparse try: import httplib except ImportError: import http.client as httplib import rospkg import rospkg.distro from .loader import RosdepLoader from .rosdistrohelper import get_index, get_index_url DEFAULT_SOURCES_LIST_URL = 'https://raw.githubusercontent.com/ros/rosdistro/master/rosdep/sources.list.d/20-default.list' DOWNLOAD_TIMEOUT = 15.0 SOURCES_LIST_DIR = 'sources.list.d' SOURCES_CACHE_DIR = 'sources.cache' CACHE_INDEX = 'index' SOURCE_PATH_ENV = 'ROSDEP_SOURCE_PATH' def get_sources_list_dirs(source_list_dir): if SOURCE_PATH_ENV in os.environ: sdirs = os.environ[SOURCE_PATH_ENV].split(os.pathsep) else: sdirs = [source_list_dir] for p in list(sdirs): if not os.path.exists(p): sdirs.remove(p) return sdirs def get_sources_list_dir(): if 0: etc_ros = rospkg.get_etc_ros_dir() else: etc_ros = '/etc/ros' # compute default system wide sources directory sys_sources_list_dir = os.path.join(etc_ros, 'rosdep', SOURCES_LIST_DIR) sources_list_dirs = get_sources_list_dirs(sys_sources_list_dir) if sources_list_dirs: return sources_list_dirs[0] else: return sys_sources_list_dir def get_default_sources_list_file(): return os.path.join(get_sources_list_dir(), '20-default.list') def get_sources_cache_dir(): ros_home = rospkg.get_ros_home() return os.path.join(ros_home, 'rosdep', SOURCES_CACHE_DIR) # Default rosdep.yaml format. For now this is the only valid type and # is specified for future compatibility. TYPE_YAML = 'yaml' # git-buildpackage repo list TYPE_GBPDISTRO = 'gbpdistro' VALID_TYPES = [TYPE_YAML, TYPE_GBPDISTRO] class DataSource(object): def __init__(self, type_, url, tags, origin=None): # validate inputs if type_ not in VALID_TYPES: raise ValueError('type must be one of [%s]' % (','.join(VALID_TYPES))) parsed = urlparse.urlparse(url) if not parsed.scheme or (parsed.scheme != 'file' and not parsed.netloc) or parsed.path in ('', '/'): raise ValueError('url must be a fully-specified URL with scheme, hostname, and path: %s' % (str(url))) if not type(tags) == list: raise ValueError('tags must be a list: %s' % (str(tags))) self.type = type_ self.tags = tags self.url = url self.origin = origin def __eq__(self, other): return isinstance(other, DataSource) and \ self.type == other.type and \ self.tags == other.tags and \ self.url == other.url and \ self.origin == other.origin def __str__(self): if self.origin: return '[%s]:\n%s %s %s' % (self.origin, self.type, self.url, ' '.join(self.tags)) else: return '%s %s %s' % (self.type, self.url, ' '.join(self.tags)) def __repr__(self): return repr((self.type, self.url, self.tags, self.origin)) class RosDistroSource(DataSource): def __init__(self, distro): self.type = TYPE_GBPDISTRO self.tags = [distro] # In this case self.url is a list if REP-143 is being used self.url = get_index().distributions[distro]['distribution'] self.origin = None # create function we can pass in as model to parse_source_data. The # function emulates the CachedDataSource constructor but does the # necessary full filepath calculation and loading of data. def cache_data_source_loader(sources_cache_dir, verbose=False): def create_model(type_, uri, tags, origin=None): # compute the filename has from the URL filename = compute_filename_hash(uri) filepath = os.path.join(sources_cache_dir, filename) pickle_filepath = filepath + PICKLE_CACHE_EXT if os.path.exists(pickle_filepath): if verbose: print('loading cached data source:\n\t%s\n\t%s' % (uri, pickle_filepath), file=sys.stderr) with open(pickle_filepath, 'rb') as f: rosdep_data = pickle.loads(f.read()) elif os.path.exists(filepath): if verbose: print('loading cached data source:\n\t%s\n\t%s' % (uri, filepath), file=sys.stderr) with open(filepath) as f: rosdep_data = yaml.safe_load(f.read()) else: rosdep_data = {} return CachedDataSource(type_, uri, tags, rosdep_data, origin=filepath) return create_model class CachedDataSource(object): def __init__(self, type_, url, tags, rosdep_data, origin=None): self.source = DataSource(type_, url, tags, origin=origin) self.rosdep_data = rosdep_data def __eq__(self, other): try: return self.source == other.source and \ self.rosdep_data == other.rosdep_data except AttributeError: return False def __str__(self): return '%s\n%s' % (self.source, self.rosdep_data) def __repr__(self): return repr((self.type, self.url, self.tags, self.rosdep_data, self.origin)) @property def type(self): return self.source.type @property def url(self): return self.source.url @property def tags(self): return self.source.tags @property def origin(self): return self.source.origin class DataSourceMatcher(object): def __init__(self, tags): self.tags = tags def matches(self, rosdep_data_source): # all of the rosdep_data_source tags must be in our matcher tags return not any(set(rosdep_data_source.tags) - set(self.tags)) @staticmethod def create_default(os_override=None): distro_name = rospkg.distro.current_distro_codename() if os_override is None: os_detect = rospkg.os_detect.OsDetect() os_name, os_version, os_codename = os_detect.detect_os() else: os_name, os_codename = os_override tags = [t for t in (distro_name, os_name, os_codename) if t] return DataSourceMatcher(tags) def download_rosdep_data(url): try: # http/https URLs need custom requests to specify the user-agent, since some repositories reject # requests from the default user-agent. if url.startswith("http://") or url.startswith("https://"): url_request = request.Request(url, headers={'User-Agent': 'rosdep/{version}'.format(version=__version__)}) else: url_request = url f = urlopen(url_request, timeout=DOWNLOAD_TIMEOUT) text = f.read() f.close() data = yaml.safe_load(text) if type(data) != dict: raise DownloadFailure('rosdep data from [%s] is not a YAML dictionary' % (url)) return data except (URLError, httplib.HTTPException) as e: raise DownloadFailure(str(e) + ' (%s)' % url) except yaml.YAMLError as e: raise DownloadFailure(str(e)) def download_default_sources_list(url=DEFAULT_SOURCES_LIST_URL): try: f = urlopen(url, timeout=DOWNLOAD_TIMEOUT) except (URLError, httplib.HTTPException) as e: raise URLError(str(e) + ' (%s)' % url) data = f.read().decode() f.close() if not data: raise DownloadFailure('cannot download defaults file from %s : empty contents' % url) # parse just for validation try: parse_sources_data(data) except InvalidData as e: raise DownloadFailure( 'The content downloaded from %s failed to pass validation.' ' It is likely that the source is invalid unless the data was corrupted during the download.' ' The contents were:{{{%s}}} The error raised was: %s' % (url, data, e)) return data def parse_sources_data(data, origin='<string>', model=None): if model is None: model = DataSource sources = [] for line in data.split('\n'): line = line.strip() # ignore empty lines or comments if not line or line.startswith(' continue splits = line.split(' ') if len(splits) < 2: raise InvalidData('invalid line:\n%s' % (line), origin=origin) type_ = splits[0] url = splits[1] tags = splits[2:] try: sources.append(model(type_, url, tags, origin=origin)) except ValueError as e: raise InvalidData('line:\n\t%s\n%s' % (line, e), origin=origin) return sources def parse_sources_file(filepath): try: with open(filepath, 'r') as f: return parse_sources_data(f.read(), origin=filepath) except IOError as e: raise InvalidData('I/O error reading sources file: %s' % (str(e)), origin=filepath) def parse_sources_list(sources_list_dir=None): if sources_list_dir is None: sources_list_dir = get_sources_list_dir() sources_list_dirs = get_sources_list_dirs(sources_list_dir) filelist = [] for sdir in sources_list_dirs: filelist += sorted([os.path.join(sdir, f) for f in os.listdir(sdir) if f.endswith('.list')]) sources_list = [] for f in filelist: sources_list.extend(parse_sources_file(f)) return sources_list def _generate_key_from_urls(urls): # urls may be a list of urls or a single string try: assert isinstance(urls, (list, basestring)) except NameError: assert isinstance(urls, (list, str)) # We join the urls by the '^' character because it is not allowed in urls return '^'.join(urls if isinstance(urls, list) else [urls]) def update_sources_list(sources_list_dir=None, sources_cache_dir=None, success_handler=None, error_handler=None, skip_eol_distros=False, ros_distro=None): if sources_cache_dir is None: sources_cache_dir = get_sources_cache_dir() sources = parse_sources_list(sources_list_dir=sources_list_dir) retval = [] for source in list(sources): try: if source.type == TYPE_YAML: rosdep_data = download_rosdep_data(source.url) elif source.type == TYPE_GBPDISTRO: # DEPRECATED, do not use this file. See REP137 if not source.tags[0] in ['electric', 'fuerte']: print('Ignore legacy gbpdistro "%s"' % source.tags[0]) sources.remove(source) continue # do not store this entry in the cache rosdep_data = download_gbpdistro_as_rosdep_data(source.url) retval.append((source, write_cache_file(sources_cache_dir, source.url, rosdep_data))) if success_handler is not None: success_handler(source) except DownloadFailure as e: if error_handler is not None: error_handler(source, e) # Additional sources for ros distros # In compliance with REP137 and REP143 python_versions = {} print('Query rosdistro index %s' % get_index_url()) distribution_names = get_index().distributions.keys() if ros_distro is not None and ros_distro not in distribution_names: raise ValueError( 'Requested distribution "%s" is not in the index.' % ros_distro) for dist_name in sorted(distribution_names): distribution = get_index().distributions[dist_name] if dist_name != ros_distro: if ros_distro is not None: print('Skip distro "%s" different from requested "%s"' % (dist_name, ros_distro)) continue if skip_eol_distros: if distribution.get('distribution_status') == 'end-of-life': print('Skip end-of-life distro "%s"' % dist_name) continue print('Add distro "%s"' % dist_name) # import pdb; pdb.set_trace() rds = RosDistroSource(dist_name) rosdep_data = get_gbprepo_as_rosdep_data(dist_name) # Store Python version from REP153 if distribution.get('python_version'): python_versions[dist_name] = distribution.get('python_version') # dist_files can either be a string (single filename) or a list (list of filenames) dist_files = distribution['distribution'] key = _generate_key_from_urls(dist_files) retval.append((rds, write_cache_file(sources_cache_dir, key, rosdep_data))) sources.append(rds) # cache metadata that isn't a source list MetaDatabase().set('ROS_PYTHON_VERSION', python_versions) if not os.path.exists(sources_cache_dir): os.makedirs(sources_cache_dir) cache_index = os.path.join(sources_cache_dir, CACHE_INDEX) data = "#autogenerated by rosdep, do not edit. use 'rosdep update' instead\n" for source in sources: url = _generate_key_from_urls(source.url) data += 'yaml %s %s\n' % (url, ' '.join(source.tags)) write_atomic(cache_index, data) return retval def load_cached_sources_list(sources_cache_dir=None, verbose=False): if sources_cache_dir is None: sources_cache_dir = get_sources_cache_dir() cache_index = os.path.join(sources_cache_dir, 'index') if not os.path.exists(cache_index): if verbose: print('no cache index present, not loading cached sources', file=sys.stderr) return [] try: with open(cache_index, 'r') as f: cache_data = f.read() except IOError as e: if e.strerror == 'Permission denied': raise CachePermissionError('Failed to write cache file: ' + str(e)) else: raise model = cache_data_source_loader(sources_cache_dir, verbose=verbose) return parse_sources_data(cache_data, origin=cache_index, model=model) class SourcesListLoader(RosdepLoader): ALL_VIEW_KEY = 'sources.list' def __init__(self, sources): self.sources = sources @staticmethod def create_default(matcher=None, sources_cache_dir=None, os_override=None, verbose=False): if matcher is None: matcher = DataSourceMatcher.create_default(os_override=os_override) if verbose: print('using matcher with tags [%s]' % (', '.join(matcher.tags)), file=sys.stderr) sources = load_cached_sources_list(sources_cache_dir=sources_cache_dir, verbose=verbose) if verbose: print('loaded %s sources' % (len(sources)), file=sys.stderr) sources = [x for x in sources if matcher.matches(x)] if verbose: print('%s sources match current tags' % (len(sources)), file=sys.stderr) return SourcesListLoader(sources) def load_view(self, view_name, rosdep_db, verbose=False): if rosdep_db.is_loaded(view_name): return source = self.get_source(view_name) if verbose: print('loading view [%s] with sources.list loader' % (view_name), file=sys.stderr) view_dependencies = self.get_view_dependencies(view_name) rosdep_db.set_view_data(view_name, source.rosdep_data, view_dependencies, view_name) def get_loadable_resources(self): return [] def get_loadable_views(self): return [x.url for x in self.sources] def get_view_dependencies(self, view_name): if view_name != SourcesListLoader.ALL_VIEW_KEY: if any([x for x in self.sources if view_name == x.url]): return [] return [x.url for x in self.sources] def get_source(self, view_name): matches = [x for x in self.sources if x.url == view_name] if matches: return matches[0] else: raise rospkg.ResourceNotFound(view_name) def get_rosdeps(self, resource_name, implicit=True): raise rospkg.ResourceNotFound(resource_name) def get_view_key(self, resource_name): raise rospkg.ResourceNotFound(resource_name)

true

f7187bd033077653af8175fd412b56d5fba443ce

30

py

Python

snakeai/gui/__init__.py

thankthemaker/snake-ai-reinforcement

e74964faf7eb893e35dc85ede10f5d794b740fff

[ "MIT" ]

145

2017-04-08T17:48:50.000Z

2022-03-21T15:14:12.000Z

snakeai/gui/__init__.py

thankthemaker/snake-ai-reinforcement

e74964faf7eb893e35dc85ede10f5d794b740fff

[ "MIT" ]

7

2017-08-10T04:43:30.000Z

2020-11-18T07:21:16.000Z

snakeai/gui/__init__.py

thankthemaker/snake-ai-reinforcement

e74964faf7eb893e35dc85ede10f5d794b740fff

[ "MIT" ]

48

2017-06-01T07:29:01.000Z

2021-09-18T09:05:16.000Z

from .pygame import PyGameGUI

15

29

0.833333

from .pygame import PyGameGUI

true

f7187c1a413767abebf5c8ea371b99345ec2aceb

1,532

py

Python

web/forms.py

tusharbohara/simple-user-registration-and-functionality-webapp-using-django

f3ad7aef110f4f637955f39b93c066f54ebab231

[ "MIT" ]

null

web/forms.py

tusharbohara/simple-user-registration-and-functionality-webapp-using-django

f3ad7aef110f4f637955f39b93c066f54ebab231

[ "MIT" ]

null

web/forms.py

tusharbohara/simple-user-registration-and-functionality-webapp-using-django

f3ad7aef110f4f637955f39b93c066f54ebab231

[ "MIT" ]

null

from django import forms from tempus_dominus.widgets import DatePicker class ConsumerRegistrationForm(forms.Form): GENDER = [ ('Male', 'Male'), ('Female', 'Female'), ('Transgender', 'Transgender'), ('Not to Specify', 'Not to Specify'), ] BLOOD_TYPE = [ ('A+', 'A+'), ('B+', 'B+'), ('AB+', 'AB+'), ('O+', 'O+'), ('A-', 'A-'), ('B-', 'B-'), ('AB-', 'AB-'), ('O-', 'O-'), ] MARITAL_STATUS_TYPE = [ ('Single', 'Single'), ('Married', 'Married'), ('Widowed', 'Widowed'), ('Divorced', 'Divorced'), ] first_name = forms.CharField(label='Enter First Name', required=True) last_name = forms.CharField(label='Enter Last Name', required=True) gender = forms.ChoiceField(choices=GENDER) date_of_birth = forms.DateField( widget=DatePicker( options={ 'ignoreReadonly': True, }, attrs={ 'append': 'fa fa-calendar', } ) ) blood_group = forms.ChoiceField(choices=BLOOD_TYPE) marital_status = forms.ChoiceField(choices=MARITAL_STATUS_TYPE) country = forms.CharField(label='Country', required=True) state = forms.CharField(label='State', required=False) district = forms.CharField(label='District', required=False) city = forms.CharField(label='City', required=True) phone = forms.IntegerField(required=True) email = forms.EmailField(required=True)

30.64

73

0.555483

from django import forms from tempus_dominus.widgets import DatePicker class ConsumerRegistrationForm(forms.Form): GENDER = [ ('Male', 'Male'), ('Female', 'Female'), ('Transgender', 'Transgender'), ('Not to Specify', 'Not to Specify'), ] BLOOD_TYPE = [ ('A+', 'A+'), ('B+', 'B+'), ('AB+', 'AB+'), ('O+', 'O+'), ('A-', 'A-'), ('B-', 'B-'), ('AB-', 'AB-'), ('O-', 'O-'), ] MARITAL_STATUS_TYPE = [ ('Single', 'Single'), ('Married', 'Married'), ('Widowed', 'Widowed'), ('Divorced', 'Divorced'), ] first_name = forms.CharField(label='Enter First Name', required=True) last_name = forms.CharField(label='Enter Last Name', required=True) gender = forms.ChoiceField(choices=GENDER) date_of_birth = forms.DateField( widget=DatePicker( options={ 'ignoreReadonly': True, }, attrs={ 'append': 'fa fa-calendar', } ) ) blood_group = forms.ChoiceField(choices=BLOOD_TYPE) marital_status = forms.ChoiceField(choices=MARITAL_STATUS_TYPE) country = forms.CharField(label='Country', required=True) state = forms.CharField(label='State', required=False) district = forms.CharField(label='District', required=False) city = forms.CharField(label='City', required=True) phone = forms.IntegerField(required=True) email = forms.EmailField(required=True)

true

f7187cef3a6d64b15e1d52f337b3a219d8d5f4ed

7,702

py

Python

tests/cli/commands/test_celery_command.py

gtossou/airflow

0314a3a218f864f78ec260cc66134e7acae34bc5

[ "Apache-2.0" ]

2

2020-10-23T18:55:03.000Z

2021-07-13T04:45:49.000Z

tests/cli/commands/test_celery_command.py

gtossou/airflow

0314a3a218f864f78ec260cc66134e7acae34bc5

[ "Apache-2.0" ]

10

2021-09-08T21:27:07.000Z

2022-03-30T17:54:45.000Z

tests/cli/commands/test_celery_command.py

gtossou/airflow

0314a3a218f864f78ec260cc66134e7acae34bc5

[ "Apache-2.0" ]

2

2020-10-23T18:55:05.000Z

2022-02-16T21:53:10.000Z

# # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import unittest from argparse import Namespace from tempfile import NamedTemporaryFile from unittest import mock import pytest import sqlalchemy import airflow from airflow.cli import cli_parser from airflow.cli.commands import celery_command from airflow.configuration import conf from tests.test_utils.config import conf_vars class TestWorkerPrecheck(unittest.TestCase): @mock.patch('airflow.settings.validate_session') def test_error(self, mock_validate_session): """ Test to verify the exit mechanism of airflow-worker cli by mocking validate_session method """ mock_validate_session.return_value = False with self.assertRaises(SystemExit) as cm: celery_command.worker(Namespace(queues=1, concurrency=1)) self.assertEqual(cm.exception.code, 1) @conf_vars({('core', 'worker_precheck'): 'False'}) def test_worker_precheck_exception(self): """ Test to check the behaviour of validate_session method when worker_precheck is absent in airflow configuration """ self.assertTrue(airflow.settings.validate_session()) @mock.patch('sqlalchemy.orm.session.Session.execute') @conf_vars({('core', 'worker_precheck'): 'True'}) def test_validate_session_dbapi_exception(self, mock_session): """ Test to validate connection failure scenario on SELECT 1 query """ mock_session.side_effect = sqlalchemy.exc.OperationalError("m1", "m2", "m3", "m4") self.assertEqual(airflow.settings.validate_session(), False) @pytest.mark.integration("redis") @pytest.mark.integration("rabbitmq") @pytest.mark.backend("mysql", "postgres") class TestWorkerServeLogs(unittest.TestCase): @classmethod def setUpClass(cls): cls.parser = cli_parser.get_parser() @mock.patch('airflow.cli.commands.celery_command.worker_bin') @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_serve_logs_on_worker_start(self, mock_worker): with mock.patch('airflow.cli.commands.celery_command.Process') as mock_process: args = self.parser.parse_args(['celery', 'worker', '--concurrency', '1']) with mock.patch('celery.platforms.check_privileges') as mock_privil: mock_privil.return_value = 0 celery_command.worker(args) mock_process.assert_called() @mock.patch('airflow.cli.commands.celery_command.worker_bin') @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_skip_serve_logs_on_worker_start(self, mock_worker): with mock.patch('airflow.cli.commands.celery_command.Process') as mock_popen: args = self.parser.parse_args(['celery', 'worker', '--concurrency', '1', '--skip-serve-logs']) with mock.patch('celery.platforms.check_privileges') as mock_privil: mock_privil.return_value = 0 celery_command.worker(args) mock_popen.assert_not_called() @pytest.mark.backend("mysql", "postgres") class TestCeleryStopCommand(unittest.TestCase): @classmethod def setUpClass(cls): cls.parser = cli_parser.get_parser() @mock.patch("airflow.cli.commands.celery_command.setup_locations") @mock.patch("airflow.cli.commands.celery_command.psutil.Process") @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_if_right_pid_is_read(self, mock_process, mock_setup_locations): args = self.parser.parse_args(['celery', 'stop']) pid = "123" # Calling stop_worker should delete the temporary pid file with self.assertRaises(FileNotFoundError): with NamedTemporaryFile("w+") as f: # Create pid file f.write(pid) f.flush() # Setup mock mock_setup_locations.return_value = (f.name, None, None, None) # Check if works as expected celery_command.stop_worker(args) mock_process.assert_called_once_with(int(pid)) mock_process.return_value.terminate.assert_called_once_with() @mock.patch("airflow.cli.commands.celery_command.read_pid_from_pidfile") @mock.patch("airflow.cli.commands.celery_command.worker_bin.worker") @mock.patch("airflow.cli.commands.celery_command.setup_locations") @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_same_pid_file_is_used_in_start_and_stop( self, mock_setup_locations, mock_celery_worker, mock_read_pid_from_pidfile ): pid_file = "test_pid_file" mock_setup_locations.return_value = (pid_file, None, None, None) mock_read_pid_from_pidfile.return_value = None # Call worker worker_args = self.parser.parse_args(['celery', 'worker', '--skip-serve-logs']) celery_command.worker(worker_args) run_mock = mock_celery_worker.return_value.run assert run_mock.call_args _, kwargs = run_mock.call_args assert 'pidfile' in kwargs assert kwargs['pidfile'] == pid_file # Call stop stop_args = self.parser.parse_args(['celery', 'stop']) celery_command.stop_worker(stop_args) mock_read_pid_from_pidfile.assert_called_once_with(pid_file) @pytest.mark.backend("mysql", "postgres") class TestWorkerStart(unittest.TestCase): @classmethod def setUpClass(cls): cls.parser = cli_parser.get_parser() @mock.patch("airflow.cli.commands.celery_command.setup_locations") @mock.patch('airflow.cli.commands.celery_command.Process') @mock.patch('airflow.cli.commands.celery_command.worker_bin') @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_worker_started_with_required_arguments(self, mock_worker, mock_popen, mock_locations): pid_file = "pid_file" mock_locations.return_value = (pid_file, None, None, None) concurrency = '1' celery_hostname = "celery_hostname" queues = "queue" autoscale = "2,5" args = self.parser.parse_args([ 'celery', 'worker', '--autoscale', autoscale, '--concurrency', concurrency, '--celery-hostname', celery_hostname, '--queues', queues ]) with mock.patch('celery.platforms.check_privileges') as mock_privil: mock_privil.return_value = 0 celery_command.worker(args) mock_worker.worker.return_value.run.assert_called_once_with( pool='prefork', optimization='fair', O='fair', # noqa queues=queues, pidfile=pid_file, concurrency=int(concurrency), autoscale=autoscale, hostname=celery_hostname, loglevel=conf.get('logging', 'LOGGING_LEVEL'), )

39.497436

106

0.675019

import unittest from argparse import Namespace from tempfile import NamedTemporaryFile from unittest import mock import pytest import sqlalchemy import airflow from airflow.cli import cli_parser from airflow.cli.commands import celery_command from airflow.configuration import conf from tests.test_utils.config import conf_vars class TestWorkerPrecheck(unittest.TestCase): @mock.patch('airflow.settings.validate_session') def test_error(self, mock_validate_session): mock_validate_session.return_value = False with self.assertRaises(SystemExit) as cm: celery_command.worker(Namespace(queues=1, concurrency=1)) self.assertEqual(cm.exception.code, 1) @conf_vars({('core', 'worker_precheck'): 'False'}) def test_worker_precheck_exception(self): self.assertTrue(airflow.settings.validate_session()) @mock.patch('sqlalchemy.orm.session.Session.execute') @conf_vars({('core', 'worker_precheck'): 'True'}) def test_validate_session_dbapi_exception(self, mock_session): mock_session.side_effect = sqlalchemy.exc.OperationalError("m1", "m2", "m3", "m4") self.assertEqual(airflow.settings.validate_session(), False) @pytest.mark.integration("redis") @pytest.mark.integration("rabbitmq") @pytest.mark.backend("mysql", "postgres") class TestWorkerServeLogs(unittest.TestCase): @classmethod def setUpClass(cls): cls.parser = cli_parser.get_parser() @mock.patch('airflow.cli.commands.celery_command.worker_bin') @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_serve_logs_on_worker_start(self, mock_worker): with mock.patch('airflow.cli.commands.celery_command.Process') as mock_process: args = self.parser.parse_args(['celery', 'worker', '--concurrency', '1']) with mock.patch('celery.platforms.check_privileges') as mock_privil: mock_privil.return_value = 0 celery_command.worker(args) mock_process.assert_called() @mock.patch('airflow.cli.commands.celery_command.worker_bin') @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_skip_serve_logs_on_worker_start(self, mock_worker): with mock.patch('airflow.cli.commands.celery_command.Process') as mock_popen: args = self.parser.parse_args(['celery', 'worker', '--concurrency', '1', '--skip-serve-logs']) with mock.patch('celery.platforms.check_privileges') as mock_privil: mock_privil.return_value = 0 celery_command.worker(args) mock_popen.assert_not_called() @pytest.mark.backend("mysql", "postgres") class TestCeleryStopCommand(unittest.TestCase): @classmethod def setUpClass(cls): cls.parser = cli_parser.get_parser() @mock.patch("airflow.cli.commands.celery_command.setup_locations") @mock.patch("airflow.cli.commands.celery_command.psutil.Process") @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_if_right_pid_is_read(self, mock_process, mock_setup_locations): args = self.parser.parse_args(['celery', 'stop']) pid = "123" with self.assertRaises(FileNotFoundError): with NamedTemporaryFile("w+") as f: f.write(pid) f.flush() mock_setup_locations.return_value = (f.name, None, None, None) celery_command.stop_worker(args) mock_process.assert_called_once_with(int(pid)) mock_process.return_value.terminate.assert_called_once_with() @mock.patch("airflow.cli.commands.celery_command.read_pid_from_pidfile") @mock.patch("airflow.cli.commands.celery_command.worker_bin.worker") @mock.patch("airflow.cli.commands.celery_command.setup_locations") @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_same_pid_file_is_used_in_start_and_stop( self, mock_setup_locations, mock_celery_worker, mock_read_pid_from_pidfile ): pid_file = "test_pid_file" mock_setup_locations.return_value = (pid_file, None, None, None) mock_read_pid_from_pidfile.return_value = None worker_args = self.parser.parse_args(['celery', 'worker', '--skip-serve-logs']) celery_command.worker(worker_args) run_mock = mock_celery_worker.return_value.run assert run_mock.call_args _, kwargs = run_mock.call_args assert 'pidfile' in kwargs assert kwargs['pidfile'] == pid_file stop_args = self.parser.parse_args(['celery', 'stop']) celery_command.stop_worker(stop_args) mock_read_pid_from_pidfile.assert_called_once_with(pid_file) @pytest.mark.backend("mysql", "postgres") class TestWorkerStart(unittest.TestCase): @classmethod def setUpClass(cls): cls.parser = cli_parser.get_parser() @mock.patch("airflow.cli.commands.celery_command.setup_locations") @mock.patch('airflow.cli.commands.celery_command.Process') @mock.patch('airflow.cli.commands.celery_command.worker_bin') @conf_vars({("core", "executor"): "CeleryExecutor"}) def test_worker_started_with_required_arguments(self, mock_worker, mock_popen, mock_locations): pid_file = "pid_file" mock_locations.return_value = (pid_file, None, None, None) concurrency = '1' celery_hostname = "celery_hostname" queues = "queue" autoscale = "2,5" args = self.parser.parse_args([ 'celery', 'worker', '--autoscale', autoscale, '--concurrency', concurrency, '--celery-hostname', celery_hostname, '--queues', queues ]) with mock.patch('celery.platforms.check_privileges') as mock_privil: mock_privil.return_value = 0 celery_command.worker(args) mock_worker.worker.return_value.run.assert_called_once_with( pool='prefork', optimization='fair', O='fair', queues=queues, pidfile=pid_file, concurrency=int(concurrency), autoscale=autoscale, hostname=celery_hostname, loglevel=conf.get('logging', 'LOGGING_LEVEL'), )

true

f7187e1c7404425320737222caf5e588e2f3c608

2,883

py

Python

subgroups/gamma_zero.py

kalinkinisaac/modular

301d26ad222a5ef3278aaf251908e0a8537bb58f

[ "MIT" ]

null

subgroups/gamma_zero.py

kalinkinisaac/modular

301d26ad222a5ef3278aaf251908e0a8537bb58f

[ "MIT" ]

null

subgroups/gamma_zero.py

kalinkinisaac/modular

301d26ad222a5ef3278aaf251908e0a8537bb58f

[ "MIT" ]

null

from .base_gamma import BaseGamma from .isomorphism import (one2many, many2one) from .algo import (factor, get_xy, gcd, inv_element) from math import log from fimath import Matrix import itertools class GammaZero(BaseGamma): def __init__(self, *args, **kwargs): super(__class__, self).__init__(*args, **kwargs) self.pair_reprs = [] self.fact = factor(self.N) self.gen_pair_reprs() def gen_pair_reprs(self): tmp_pair_reprs = [] for (p_i, m_i) in self.fact: tmp_pair_reprs += [self._gen_pair_reprs_prime(p_i, m_i)] for combination in list(itertools.product(*tmp_pair_reprs)): self.pair_reprs.append(many2one(list(combination))) def _gen_pair_reprs_prime(self, p, m): reprs = [] reprs.append([0, 1, [p, m]]) reprs.extend([[1, i, [p, m]] for i in range(p ** m)]) for i in range(1, m): bs = list(filter(lambda x: x % p != 0, range(1, p ** (m - i)))) reprs.extend([[p ** i, b, [p, m]] for b in bs]) return reprs def pair_reduced(self, a, b): many = one2many([a, b, self.N], fact=self.fact) reduced = [] for one in many: reduced.append(self._pair_reduced(one)) return many2one(reduced) def _pair_reduced(self, one): a, b, [p, m] = one N = p ** m if a % N == 0: return [0, 1, [p, m]] _gcd = gcd(a, N) c = a // _gcd i = int(log(_gcd, p)) bc = (b * inv_element(c, N)) % N if i == 0: return [1, bc % N, [p, m]] else: return [p ** i, (bc % p ** (m - i)) % N, [p, m]] class GammaBotZero(GammaZero): def __init__(self, *args, **kwargs): super(__class__, self).__init__(*args, **kwargs) self.gen_reprs() def gen_reprs(self): self.reprs = [] for a, b, N in self.pair_reprs: self.reprs.append(self.reduced(Matrix(0, 0, a, b))) def not_cached_reduced(self, mat): a, b = mat.c, mat.d a, b = self.pair_reduced(a, b)[0:2] d, c = list(map(lambda x: x % self.N, get_xy(a, b, self.N))) return Matrix(c, -d, a, b) % self.N @staticmethod def sort_key(m): return [m.c, m.d, m.a, m.b] class GammaTopZero(GammaZero): def __init__(self, *args, **kwargs): super(__class__, self).__init__(*args, **kwargs) self.gen_reprs() def gen_reprs(self): for a, b, N in self.pair_reprs: self.reprs.append(self.reduced(Matrix(a, b, 0, 0))) def not_cached_reduced(self, mat): a, b = mat.a, mat.b a, b = self.pair_reduced(a, b)[0:2] d, c = list(map(lambda x : x % self.N, get_xy(a, b, self.N))) return Matrix(a, b, -c, d) % self.N @staticmethod def sort_key(m): return [m.a, m.b, m.c, m.d]

28.83

75

0.541797

from .base_gamma import BaseGamma from .isomorphism import (one2many, many2one) from .algo import (factor, get_xy, gcd, inv_element) from math import log from fimath import Matrix import itertools class GammaZero(BaseGamma): def __init__(self, *args, **kwargs): super(__class__, self).__init__(*args, **kwargs) self.pair_reprs = [] self.fact = factor(self.N) self.gen_pair_reprs() def gen_pair_reprs(self): tmp_pair_reprs = [] for (p_i, m_i) in self.fact: tmp_pair_reprs += [self._gen_pair_reprs_prime(p_i, m_i)] for combination in list(itertools.product(*tmp_pair_reprs)): self.pair_reprs.append(many2one(list(combination))) def _gen_pair_reprs_prime(self, p, m): reprs = [] reprs.append([0, 1, [p, m]]) reprs.extend([[1, i, [p, m]] for i in range(p ** m)]) for i in range(1, m): bs = list(filter(lambda x: x % p != 0, range(1, p ** (m - i)))) reprs.extend([[p ** i, b, [p, m]] for b in bs]) return reprs def pair_reduced(self, a, b): many = one2many([a, b, self.N], fact=self.fact) reduced = [] for one in many: reduced.append(self._pair_reduced(one)) return many2one(reduced) def _pair_reduced(self, one): a, b, [p, m] = one N = p ** m if a % N == 0: return [0, 1, [p, m]] _gcd = gcd(a, N) c = a // _gcd i = int(log(_gcd, p)) bc = (b * inv_element(c, N)) % N if i == 0: return [1, bc % N, [p, m]] else: return [p ** i, (bc % p ** (m - i)) % N, [p, m]] class GammaBotZero(GammaZero): def __init__(self, *args, **kwargs): super(__class__, self).__init__(*args, **kwargs) self.gen_reprs() def gen_reprs(self): self.reprs = [] for a, b, N in self.pair_reprs: self.reprs.append(self.reduced(Matrix(0, 0, a, b))) def not_cached_reduced(self, mat): a, b = mat.c, mat.d a, b = self.pair_reduced(a, b)[0:2] d, c = list(map(lambda x: x % self.N, get_xy(a, b, self.N))) return Matrix(c, -d, a, b) % self.N @staticmethod def sort_key(m): return [m.c, m.d, m.a, m.b] class GammaTopZero(GammaZero): def __init__(self, *args, **kwargs): super(__class__, self).__init__(*args, **kwargs) self.gen_reprs() def gen_reprs(self): for a, b, N in self.pair_reprs: self.reprs.append(self.reduced(Matrix(a, b, 0, 0))) def not_cached_reduced(self, mat): a, b = mat.a, mat.b a, b = self.pair_reduced(a, b)[0:2] d, c = list(map(lambda x : x % self.N, get_xy(a, b, self.N))) return Matrix(a, b, -c, d) % self.N @staticmethod def sort_key(m): return [m.a, m.b, m.c, m.d]

true

f7187e6897bff9206930e55c479aeb8c17fd6cb9

11,160

py

Python

KGEAttack/ConvE/l2_del.py

PeruBhardwaj/AttributionAttack

0d5ca334c611c5e067029a3f8907f2d91255ddde

[ "MIT" ]

5

2021-11-08T07:18:10.000Z

2022-03-10T09:06:11.000Z

KGEAttack/ConvE/l2_del.py

PeruBhardwaj/AttributionAttack

0d5ca334c611c5e067029a3f8907f2d91255ddde

[ "MIT" ]

null

KGEAttack/ConvE/l2_del.py

PeruBhardwaj/AttributionAttack

0d5ca334c611c5e067029a3f8907f2d91255ddde

[ "MIT" ]

null

#!/usr/bin/env python # coding: utf-8 # In this notebook, I delete a triple from the neighbourhood of the target triple based on the **L2 metric = euclidean distance** between the candidate triple's embedding and the target triple's embedding # # - 'triple' embedding is computed by applying the model's scoring function to embeddings # - neighbourhood refers to the triples that share the entities with target's entities # # # In[1]: import pickle from typing import Dict, Tuple, List import os import numpy as np import pandas as pd from collections import defaultdict import operator import json import logging import argparse import math from pprint import pprint import errno import time import torch from torch.utils.data import DataLoader import torch.backends.cudnn as cudnn from torch import nn from torch.nn import CrossEntropyLoss from torch.nn import functional as F import torch.autograd as autograd from evaluation import evaluation from model import Distmult, Complex, Conve, Transe import utils def generate_nghbrs(test_set, train_set): ''' For every triple in test set, return the index of neighbouring triple in training set, i.e. indices in training set are returned ''' n_dict = {} for t, triple in enumerate(test_set): sub = triple[0] obj = triple[2] mask = (np.isin(train_set[:,0], [sub, obj]) | np.isin(train_set[:,2], [sub, obj])) #nghbrs_dict[t] = pro_train[mask] mask_idx = np.where(mask)[0] n_dict[t] = mask_idx return n_dict def get_deletions(train_data, test_data, neighbours, model, attack_batch_size): logger.info('------ Generating edits per target triple ------') start_time = time.time() logger.info('Start time: {0}'.format(str(start_time))) triples_to_delete = [] for test_idx, test_trip in enumerate(test_data): test_nghbrs = neighbours[test_idx] nghbr_trip = train_data[test_nghbrs] test_trip = test_trip[None, :] # add a batch dimension test_trip = torch.from_numpy(test_trip).to(device) test_s, test_r, test_o = test_trip[:,0], test_trip[:,1], test_trip[:,2] test_vec = model.score_triples_vec(test_s, test_r, test_o) b_begin = 0 nghbr_dist = [] if attack_batch_size == -1: nghbr_batch = nghbr_trip.shape[0] else: nghbr_batch = args.attack_batch_size while b_begin < nghbr_trip.shape[0]: b_nghbr_trip = nghbr_trip[b_begin : b_begin+nghbr_batch] b_nghbr_trip = torch.from_numpy(b_nghbr_trip).to(device) b_nghbr_s, b_nghbr_r, b_nghbr_o = b_nghbr_trip[:,0], b_nghbr_trip[:,1], b_nghbr_trip[:,2] b_nghbr_vec = model.score_triples_vec(b_nghbr_s, b_nghbr_r, b_nghbr_o) # shape of nghbr_vec is (num_nghbrs x emb_dim) e.g. (459 x 100) # shape of test vec is (1 x emb_dim) #b_dist = -torch.cdist(test_vec, b_nghbr_vec).squeeze() b_dist = -torch.norm((b_nghbr_vec-test_vec), p=2, dim=-1) b_dist = b_dist.detach().cpu().numpy().tolist() nghbr_dist += b_dist b_begin += nghbr_batch nghbr_dist = np.array(nghbr_dist) nghbr_dist = torch.from_numpy(nghbr_dist).to(device) # we want to remove the neighbour with maximum norm similarity max_values, argsort = torch.sort(nghbr_dist, -1, descending=True) del_idx = argsort[0] triple_to_delete = nghbr_trip[del_idx] triples_to_delete.append(triple_to_delete) if test_idx%100 == 0 or test_idx == test_data.shape[0]-1: logger.info('Processed test triple {0}'.format(str(test_idx))) logger.info('Time taken: {0}'.format(str(time.time() - start_time))) logger.info('Time taken to generate edits: {0}'.format(str(time.time() - start_time))) return triples_to_delete if __name__ == '__main__': parser = utils.get_argument_parser() parser.add_argument('--target-split', type=str, default='0_100_1', help='Ranks to use for target set. Values are 0 for ranks==1; 1 for ranks <=10; 2 for ranks>10 and ranks<=100. Default: 1') parser.add_argument('--budget', type=int, default=1, help='Budget for each target triple for each corruption side') parser.add_argument('--rand-run', type=int, default=1, help='A number assigned to the random run of experiment') parser.add_argument('--attack-batch-size', type=int, default=-1, help='Batch size for processing neighbours of target') args = parser.parse_args() device = torch.device("cuda" if torch.cuda.is_available() else "cpu") args.device = device # args.target_split = '0_100_1' # which target split to use #Values are 1 for ranks <=10; 2 for ranks>10 and ranks<=100. # args.budget = 1 #indicates the num of adversarial edits for each target triple for each corruption side # args.rand_run = 1 # a number assigned to the random run of the experiment args.seed = args.seed + (args.rand_run - 1) # default seed is 17 # args.model = 'distmult' # args.data = 'WN18RR' if args.reproduce_results: args = utils.set_hyperparams(args) # Fixing random seeds for reproducibility -https://pytorch.org/docs/stable/notes/randomness.html torch.manual_seed(args.seed) cudnn.deterministic = True cudnn.benchmark = False np.random.seed(args.seed) rng = np.random.default_rng(seed=args.seed) args.epochs = -1 #no training here model_name = '{0}_{1}_{2}_{3}_{4}'.format(args.model, args.embedding_dim, args.input_drop, args.hidden_drop, args.feat_drop) model_path = 'saved_models/{0}_{1}.model'.format(args.data, model_name) log_path = 'logs/attack_logs/l2_del_{0}_{1}_{2}_{3}_{4}'.format( args.model, args.data, args.target_split, args.budget, args.rand_run) logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt = '%m/%d/%Y %H:%M:%S', level = logging.INFO, filename = log_path ) logger = logging.getLogger(__name__) data_path = 'data/target_{0}_{1}_{2}'.format(args.model, args.data, args.target_split) n_ent, n_rel, ent_to_id, rel_to_id = utils.generate_dicts(data_path) ##### load data#### data = utils.load_data(data_path) train_data, valid_data, test_data = data['train'], data['valid'], data['test'] inp_f = open(os.path.join(data_path, 'to_skip_eval.pickle'), 'rb') to_skip_eval: Dict[str, Dict[Tuple[int, int], List[int]]] = pickle.load(inp_f) inp_f.close() to_skip_eval['lhs'] = {(int(k[0]), int(k[1])): v for k,v in to_skip_eval['lhs'].items()} to_skip_eval['rhs'] = {(int(k[0]), int(k[1])): v for k,v in to_skip_eval['rhs'].items()} model = utils.load_model(model_path, args, n_ent, n_rel, device) neighbours = generate_nghbrs(test_data, train_data) # test set is the target set because we loaded data from target_... triples_to_delete = get_deletions(train_data, test_data, neighbours, model, args.attack_batch_size) df = pd.DataFrame(data=triples_to_delete) df = df.drop_duplicates() # print(df.shape) trips_to_delete = df.values # print(trips_to_delete.shape) num_duplicates = len(triples_to_delete) - trips_to_delete.shape[0] # print(num_duplicates) per_tr_1, n_ignored_edits = utils.perturb_data(train_data, trips_to_delete) # Perturbed dataset logger.info('Shape of perturbed training set: {0}'.format(per_tr_1.shape)) logger.info('Number of adversarial deletions ignored (because of singleton nodes): {0}'.format(n_ignored_edits)) logger.info('Number of duplicate adversarial deletions : {0}'.format(num_duplicates)) logger.info ('Length of original training set: ' + str(train_data.shape[0])) logger.info ('Length of new poisoned training set: ' + str(per_tr_1.shape[0])) save_path = 'data/l2_del_{0}_{1}_{2}_{3}_{4}'.format( args.model, args.data, args.target_split, args.budget, args.rand_run) try : os.makedirs(save_path) except OSError as e: if e.errno == errno.EEXIST: logger.info(e) logger.info('Using the existing folder {0} for processed data'.format(save_path)) else: raise new_train = per_tr_1 num_en_or = np.unique(np.concatenate((train_data[:,0], train_data[:,2]))).shape[0] num_en_pos = np.unique(np.concatenate((new_train[:,0], new_train[:,2]))).shape[0] with open(os.path.join(save_path, 'train.txt'), 'w') as out: for item in new_train: out.write("%s\n" % "\t".join(map(str, item))) out = open(os.path.join(save_path, 'train.pickle'), 'wb') pickle.dump(new_train.astype('uint64'), out) out.close() with open(os.path.join(save_path, 'entities_dict.json'), 'w') as f: f.write(json.dumps(ent_to_id) + '\n') with open(os.path.join(save_path, 'relations_dict.json'), 'w') as f: f.write(json.dumps(rel_to_id) + '\n') with open(os.path.join(save_path, 'valid.txt'), 'w') as out: for item in valid_data: out.write("%s\n" % "\t".join(map(str, item))) out = open(os.path.join(save_path, 'valid.pickle'), 'wb') pickle.dump(valid_data.astype('uint64'), out) out.close() with open(os.path.join(save_path, 'test.txt'), 'w') as out: for item in test_data: out.write("%s\n" % "\t".join(map(str, item))) out = open(os.path.join(save_path, 'test.pickle'), 'wb') pickle.dump(test_data.astype('uint64'), out) out.close() with open(os.path.join(save_path, 'stats.txt'), 'w') as f: f.write('Model: {0} \n'.format(args.model)) f.write('Data: {0} \n'.format(args.data)) f.write('Length of original training set: {0} \n'. format(train_data.shape[0])) f.write('Length of new poisoned training set: {0} \n'. format(new_train.shape[0])) f.write('Number of duplicate deletions: {0} \n'. format(num_duplicates)) f.write('Number of deletions ignored due to singleton nodes: {0} \n'. format(n_ignored_edits)) f.write('Number of entities in original training set: {0} \n'. format(num_en_or)) f.write('Number of entities in poisoned training set: {0} \n'. format(num_en_pos)) f.write('Length of original test set: {0} \n'. format(test_data.shape[0])) f.write('---------------------------------------------------------------------- \n') with open(os.path.join(save_path, 'influential_triples.txt'), 'w') as out: for item in triples_to_delete: out.write("%s\n" % "\t".join(map(str, item))) with open(os.path.join(save_path, 'deletions.txt'), 'w') as out: for item in trips_to_delete: out.write("%s\n" % "\t".join(map(str, item))) # In[ ]: # In[ ]:

37.2

204

0.63629

# - neighbourhood refers to the triples that share the entities with target's entities import pickle from typing import Dict, Tuple, List import os import numpy as np import pandas as pd from collections import defaultdict import operator import json import logging import argparse import math from pprint import pprint import errno import time import torch from torch.utils.data import DataLoader import torch.backends.cudnn as cudnn from torch import nn from torch.nn import CrossEntropyLoss from torch.nn import functional as F import torch.autograd as autograd from evaluation import evaluation from model import Distmult, Complex, Conve, Transe import utils def generate_nghbrs(test_set, train_set): n_dict = {} for t, triple in enumerate(test_set): sub = triple[0] obj = triple[2] mask = (np.isin(train_set[:,0], [sub, obj]) | np.isin(train_set[:,2], [sub, obj])) mask_idx = np.where(mask)[0] n_dict[t] = mask_idx return n_dict def get_deletions(train_data, test_data, neighbours, model, attack_batch_size): logger.info('------ Generating edits per target triple ------') start_time = time.time() logger.info('Start time: {0}'.format(str(start_time))) triples_to_delete = [] for test_idx, test_trip in enumerate(test_data): test_nghbrs = neighbours[test_idx] nghbr_trip = train_data[test_nghbrs] test_trip = test_trip[None, :] test_trip = torch.from_numpy(test_trip).to(device) test_s, test_r, test_o = test_trip[:,0], test_trip[:,1], test_trip[:,2] test_vec = model.score_triples_vec(test_s, test_r, test_o) b_begin = 0 nghbr_dist = [] if attack_batch_size == -1: nghbr_batch = nghbr_trip.shape[0] else: nghbr_batch = args.attack_batch_size while b_begin < nghbr_trip.shape[0]: b_nghbr_trip = nghbr_trip[b_begin : b_begin+nghbr_batch] b_nghbr_trip = torch.from_numpy(b_nghbr_trip).to(device) b_nghbr_s, b_nghbr_r, b_nghbr_o = b_nghbr_trip[:,0], b_nghbr_trip[:,1], b_nghbr_trip[:,2] b_nghbr_vec = model.score_triples_vec(b_nghbr_s, b_nghbr_r, b_nghbr_o) b_dist = -torch.norm((b_nghbr_vec-test_vec), p=2, dim=-1) b_dist = b_dist.detach().cpu().numpy().tolist() nghbr_dist += b_dist b_begin += nghbr_batch nghbr_dist = np.array(nghbr_dist) nghbr_dist = torch.from_numpy(nghbr_dist).to(device) max_values, argsort = torch.sort(nghbr_dist, -1, descending=True) del_idx = argsort[0] triple_to_delete = nghbr_trip[del_idx] triples_to_delete.append(triple_to_delete) if test_idx%100 == 0 or test_idx == test_data.shape[0]-1: logger.info('Processed test triple {0}'.format(str(test_idx))) logger.info('Time taken: {0}'.format(str(time.time() - start_time))) logger.info('Time taken to generate edits: {0}'.format(str(time.time() - start_time))) return triples_to_delete if __name__ == '__main__': parser = utils.get_argument_parser() parser.add_argument('--target-split', type=str, default='0_100_1', help='Ranks to use for target set. Values are 0 for ranks==1; 1 for ranks <=10; 2 for ranks>10 and ranks<=100. Default: 1') parser.add_argument('--budget', type=int, default=1, help='Budget for each target triple for each corruption side') parser.add_argument('--rand-run', type=int, default=1, help='A number assigned to the random run of experiment') parser.add_argument('--attack-batch-size', type=int, default=-1, help='Batch size for processing neighbours of target') args = parser.parse_args() device = torch.device("cuda" if torch.cuda.is_available() else "cpu") args.device = device manual_seed(args.seed) cudnn.deterministic = True cudnn.benchmark = False np.random.seed(args.seed) rng = np.random.default_rng(seed=args.seed) args.epochs = -1 model_name = '{0}_{1}_{2}_{3}_{4}'.format(args.model, args.embedding_dim, args.input_drop, args.hidden_drop, args.feat_drop) model_path = 'saved_models/{0}_{1}.model'.format(args.data, model_name) log_path = 'logs/attack_logs/l2_del_{0}_{1}_{2}_{3}_{4}'.format( args.model, args.data, args.target_split, args.budget, args.rand_run) logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt = '%m/%d/%Y %H:%M:%S', level = logging.INFO, filename = log_path ) logger = logging.getLogger(__name__) data_path = 'data/target_{0}_{1}_{2}'.format(args.model, args.data, args.target_split) n_ent, n_rel, ent_to_id, rel_to_id = utils.generate_dicts(data_path) a = data['train'], data['valid'], data['test'] inp_f = open(os.path.join(data_path, 'to_skip_eval.pickle'), 'rb') to_skip_eval: Dict[str, Dict[Tuple[int, int], List[int]]] = pickle.load(inp_f) inp_f.close() to_skip_eval['lhs'] = {(int(k[0]), int(k[1])): v for k,v in to_skip_eval['lhs'].items()} to_skip_eval['rhs'] = {(int(k[0]), int(k[1])): v for k,v in to_skip_eval['rhs'].items()} model = utils.load_model(model_path, args, n_ent, n_rel, device) neighbours = generate_nghbrs(test_data, train_data) triples_to_delete = get_deletions(train_data, test_data, neighbours, model, args.attack_batch_size) df = pd.DataFrame(data=triples_to_delete) df = df.drop_duplicates() trips_to_delete = df.values num_duplicates = len(triples_to_delete) - trips_to_delete.shape[0] per_tr_1, n_ignored_edits = utils.perturb_data(train_data, trips_to_delete) logger.info('Shape of perturbed training set: {0}'.format(per_tr_1.shape)) logger.info('Number of adversarial deletions ignored (because of singleton nodes): {0}'.format(n_ignored_edits)) logger.info('Number of duplicate adversarial deletions : {0}'.format(num_duplicates)) logger.info ('Length of original training set: ' + str(train_data.shape[0])) logger.info ('Length of new poisoned training set: ' + str(per_tr_1.shape[0])) save_path = 'data/l2_del_{0}_{1}_{2}_{3}_{4}'.format( args.model, args.data, args.target_split, args.budget, args.rand_run) try : os.makedirs(save_path) except OSError as e: if e.errno == errno.EEXIST: logger.info(e) logger.info('Using the existing folder {0} for processed data'.format(save_path)) else: raise new_train = per_tr_1 num_en_or = np.unique(np.concatenate((train_data[:,0], train_data[:,2]))).shape[0] num_en_pos = np.unique(np.concatenate((new_train[:,0], new_train[:,2]))).shape[0] with open(os.path.join(save_path, 'train.txt'), 'w') as out: for item in new_train: out.write("%s\n" % "\t".join(map(str, item))) out = open(os.path.join(save_path, 'train.pickle'), 'wb') pickle.dump(new_train.astype('uint64'), out) out.close() with open(os.path.join(save_path, 'entities_dict.json'), 'w') as f: f.write(json.dumps(ent_to_id) + '\n') with open(os.path.join(save_path, 'relations_dict.json'), 'w') as f: f.write(json.dumps(rel_to_id) + '\n') with open(os.path.join(save_path, 'valid.txt'), 'w') as out: for item in valid_data: out.write("%s\n" % "\t".join(map(str, item))) out = open(os.path.join(save_path, 'valid.pickle'), 'wb') pickle.dump(valid_data.astype('uint64'), out) out.close() with open(os.path.join(save_path, 'test.txt'), 'w') as out: for item in test_data: out.write("%s\n" % "\t".join(map(str, item))) out = open(os.path.join(save_path, 'test.pickle'), 'wb') pickle.dump(test_data.astype('uint64'), out) out.close() with open(os.path.join(save_path, 'stats.txt'), 'w') as f: f.write('Model: {0} \n'.format(args.model)) f.write('Data: {0} \n'.format(args.data)) f.write('Length of original training set: {0} \n'. format(train_data.shape[0])) f.write('Length of new poisoned training set: {0} \n'. format(new_train.shape[0])) f.write('Number of duplicate deletions: {0} \n'. format(num_duplicates)) f.write('Number of deletions ignored due to singleton nodes: {0} \n'. format(n_ignored_edits)) f.write('Number of entities in original training set: {0} \n'. format(num_en_or)) f.write('Number of entities in poisoned training set: {0} \n'. format(num_en_pos)) f.write('Length of original test set: {0} \n'. format(test_data.shape[0])) f.write('---------------------------------------------------------------------- \n') with open(os.path.join(save_path, 'influential_triples.txt'), 'w') as out: for item in triples_to_delete: out.write("%s\n" % "\t".join(map(str, item))) with open(os.path.join(save_path, 'deletions.txt'), 'w') as out: for item in trips_to_delete: out.write("%s\n" % "\t".join(map(str, item)))

true

f7187f1fc12ea1ed1b0c5a0ce33d00d4b8ac79c3

7,229

py

Python

blocklogic.py

rroctavian/blockchain_wdss

2d25cb83fac91404da8b7e2404b5668a5877318f

[ "MIT" ]

null

blocklogic.py

rroctavian/blockchain_wdss

2d25cb83fac91404da8b7e2404b5668a5877318f

[ "MIT" ]

null

blocklogic.py

rroctavian/blockchain_wdss

2d25cb83fac91404da8b7e2404b5668a5877318f

[ "MIT" ]

null

from hashlib import sha256 import json import time import multiprocessing import time import numpy as np class Block: def __init__( self, depth, transactions, timestamp, previous_hash, nonce=0 ): self.depth = depth self.transactions = transactions self.timestamp = timestamp self.previous_hash = previous_hash self.nonce = nonce def compute_hash(self): ''' A function that return the hash of the block contents. ''' block_str = json.dumps(self.__dict__, sort_keys=True) return sha256(block_str.encode()).hexdigest() def __eq__(self, other): ''' Overloading the equality operator ''' return self.__dict__ == other.__dict__ class Blockchain: ''' Blockchain class; Inspired from IBM version at the moment. ''' difficulty = 4 block_capacity = 3 def __init__(self): ''' Choose initial difficulty and create the genesis block [1] They are the orphans and stale blocks It's a list of lists where we also store the block leading to the orphan. That block is stored multiple time (also in the longest chain) ''' # Transactions to be mined self.outstanding_transactions = [] # Consensus chain and extensions, see [1] self.chain = [] self.extensions = [] # Create genesis block self.create_genesis_block() def create_genesis_block(self): """ A function to generate genesis block and appends it to the chain. The block has index 0, previous_hash as 0, and a valid hash. """ genesis_block = Block(0, [], 0, "0") genesis_block.hash = genesis_block.compute_hash() self.chain.append(genesis_block) @property def last_block(self): return self.chain[-1] def add_block_longest(self, block, proof): """ Attempt to add a block after checking the validity of the provided proof. Append to longest chain. """ # Reject if previous hash not accurate if self.last_block.hash != block.previous_hash: return False # Reject if proof is not valid hash if not Blockchain.is_valid_proof(block, proof): return False block.hash = proof self.chain.append(block) return True def add_block( self, block, proof, base_block ): """ Attempt to add a block after checking the validity of the provided proof. Append to longest chain. :param base_block: the base block receiving the potential new block [1] If base_block is not last block in longest chain, check all extensions for their last block. If again, none of the extensions have the base_block as their last, create another extension. You could have nested extensions because of this, but shouldn't care. """ # If the base block is the last block # in longest chain, just use regular add if base_block == self.last_block: return self.add_block_longest(block, proof) # Previous hash should be accurate, reject otherwise if base_block.hash != block.previous_hash: return False # Reject if proof is not valid hash of block if not Blockchain.is_valid_proof(block, proof): return False # If checks passed, update the block's hash block.hash = proof # Check all extensions for the base block # See add_block.[1] for ext_idx in range(self.extensions): # Check each last block in extensions if base_block == self.extensions[ext_idx][-1]: # If found, proceed there self.extensions[ext_idx].append(block) return True # If not found there, create extension self.extensions.append([base_block, block]) return True def internal_consensus(self): ''' Method to update to longest chain using possibly larger extensions. So it checks if any extension is longer than current chain. In case of a change, the tail of the current chain becomes a new extension. [1] If any update happens, return True and stop since another one is impossible. This is because we are calling this at each mine, so changes are continuously updated. ''' for ext in self.extensions: if ext[-1].depth > self.last_block.depth: fork_depth = ext[0].depth # Create new extension with chain to be # dumped self.extensions.append( self.chain[fork_depth:] ) # Remove and store chain tail until # depth of fork node, then add extension # tail to now have longest chain while self.last_block.depth >= fork_depth: self.chain.pop() self.chain = self.chain + ext # See internal_consensus.[1] return True # If no internal consensus update, return False return False @staticmethod def proof_of_work(block, work_time = None): """ Do proof of work and stop after a work_time seconds. :param starting_nonce: can store progress :param work_time: storing progress requires early stopping and we're using a potentially pre-set time """ # Parse work_time None to inf if work_time is None: work_time = float('inf') start = time.time() # Start from 0, flexibility here to be debated block.nonce = 0 # Do computational work computed_hash = block.compute_hash() while not computed_hash.startswith('0' * Blockchain.difficulty): block.nonce += 1 computed_hash = block.compute_hash() # Return if out of time if (time.time() - start) > work_time: return # Return good hash return computed_hash def add_new_transaction(self, transaction): self.outstanding_transactions.append(transaction) def remove_front_transactions(self): self.outstanding_transactions = self.outstanding_transactions[Blockchain.block_capacity:] def get_outstanding_transactions(self): return self.outstanding_transactions @classmethod def is_valid_proof(cls, block, block_hash): """ Check if block_hash is valid hash of block and satisfies the difficulty criteria. """ return (block_hash.startswith('0' * Blockchain.difficulty) and block_hash == block.compute_hash())

35.787129

98

0.580302

from hashlib import sha256 import json import time import multiprocessing import time import numpy as np class Block: def __init__( self, depth, transactions, timestamp, previous_hash, nonce=0 ): self.depth = depth self.transactions = transactions self.timestamp = timestamp self.previous_hash = previous_hash self.nonce = nonce def compute_hash(self): block_str = json.dumps(self.__dict__, sort_keys=True) return sha256(block_str.encode()).hexdigest() def __eq__(self, other): return self.__dict__ == other.__dict__ class Blockchain: difficulty = 4 block_capacity = 3 def __init__(self): self.outstanding_transactions = [] self.chain = [] self.extensions = [] self.create_genesis_block() def create_genesis_block(self): genesis_block = Block(0, [], 0, "0") genesis_block.hash = genesis_block.compute_hash() self.chain.append(genesis_block) @property def last_block(self): return self.chain[-1] def add_block_longest(self, block, proof): if self.last_block.hash != block.previous_hash: return False if not Blockchain.is_valid_proof(block, proof): return False block.hash = proof self.chain.append(block) return True def add_block( self, block, proof, base_block ): if base_block == self.last_block: return self.add_block_longest(block, proof) if base_block.hash != block.previous_hash: return False if not Blockchain.is_valid_proof(block, proof): return False block.hash = proof # Check all extensions for the base block # See add_block.[1] for ext_idx in range(self.extensions): # Check each last block in extensions if base_block == self.extensions[ext_idx][-1]: # If found, proceed there self.extensions[ext_idx].append(block) return True # If not found there, create extension self.extensions.append([base_block, block]) return True def internal_consensus(self): for ext in self.extensions: if ext[-1].depth > self.last_block.depth: fork_depth = ext[0].depth # Create new extension with chain to be # dumped self.extensions.append( self.chain[fork_depth:] ) # Remove and store chain tail until # depth of fork node, then add extension # tail to now have longest chain while self.last_block.depth >= fork_depth: self.chain.pop() self.chain = self.chain + ext # See internal_consensus.[1] return True # If no internal consensus update, return False return False @staticmethod def proof_of_work(block, work_time = None): # Parse work_time None to inf if work_time is None: work_time = float('inf') start = time.time() # Start from 0, flexibility here to be debated block.nonce = 0 # Do computational work computed_hash = block.compute_hash() while not computed_hash.startswith('0' * Blockchain.difficulty): block.nonce += 1 computed_hash = block.compute_hash() # Return if out of time if (time.time() - start) > work_time: return # Return good hash return computed_hash def add_new_transaction(self, transaction): self.outstanding_transactions.append(transaction) def remove_front_transactions(self): self.outstanding_transactions = self.outstanding_transactions[Blockchain.block_capacity:] def get_outstanding_transactions(self): return self.outstanding_transactions @classmethod def is_valid_proof(cls, block, block_hash): return (block_hash.startswith('0' * Blockchain.difficulty) and block_hash == block.compute_hash())

true

f7187f5b5ab4da7e46565bfd415acf79f33f3db2

25,583

py

Python

test/with_dummyserver/test_poolmanager.py

pquentin/hip

89c766d0782f016baeda236149f29477f7237eed

[ "MIT" ]

null

test/with_dummyserver/test_poolmanager.py

pquentin/hip

89c766d0782f016baeda236149f29477f7237eed

[ "MIT" ]

1

2020-01-21T06:48:37.000Z

test/with_dummyserver/test_poolmanager.py

pquentin/hip

89c766d0782f016baeda236149f29477f7237eed

[ "MIT" ]

null

import io import json import time import pytest from dummyserver.server import HAS_IPV6 from dummyserver.testcase import HTTPDummyServerTestCase, IPv6HTTPDummyServerTestCase from hip.base import DEFAULT_PORTS from hip.poolmanager import PoolManager from hip.exceptions import MaxRetryError, NewConnectionError, UnrewindableBodyError from hip.util.retry import Retry, RequestHistory from test import LONG_TIMEOUT # Retry failed tests pytestmark = pytest.mark.flaky class TestPoolManager(HTTPDummyServerTestCase): @classmethod def setup_class(cls): super(TestPoolManager, cls).setup_class() cls.base_url = "http://%s:%d" % (cls.host, cls.port) cls.base_url_alt = "http://%s:%d" % (cls.host_alt, cls.port) def test_redirect(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/" % self.base_url}, redirect=False, ) assert r.status == 303 r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/" % self.base_url}, ) assert r.status == 200 assert r.data == b"Dummy server!" def test_redirect_twice(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/redirect" % self.base_url}, redirect=False, ) assert r.status == 303 r = http.request( "GET", "%s/redirect" % self.base_url, fields={ "target": "%s/redirect?target=%s/" % (self.base_url, self.base_url) }, ) assert r.status == 200 assert r.data == b"Dummy server!" def test_redirect_to_relative_url(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/redirect"}, redirect=False, ) assert r.status == 303 r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/redirect"} ) assert r.status == 200 assert r.data == b"Dummy server!" def test_cross_host_redirect(self): with PoolManager() as http: cross_host_location = "%s/echo?a=b" % self.base_url_alt with pytest.raises(MaxRetryError): http.request( "GET", "%s/redirect" % self.base_url, fields={"target": cross_host_location}, timeout=LONG_TIMEOUT, retries=0, ) r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/echo?a=b" % self.base_url_alt}, timeout=LONG_TIMEOUT, retries=1, ) assert r._pool.host == self.host_alt def test_too_many_redirects(self): with PoolManager() as http: with pytest.raises(MaxRetryError): http.request( "GET", "%s/redirect" % self.base_url, fields={ "target": "%s/redirect?target=%s/" % (self.base_url, self.base_url) }, retries=1, ) with pytest.raises(MaxRetryError): http.request( "GET", "%s/redirect" % self.base_url, fields={ "target": "%s/redirect?target=%s/" % (self.base_url, self.base_url) }, retries=Retry(total=None, redirect=1), ) def test_redirect_cross_host_remove_headers(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"Authorization": "foo"}, ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert "Authorization" not in data r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"authorization": "foo"}, ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert "authorization" not in data assert "Authorization" not in data def test_redirect_cross_host_no_remove_headers(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"Authorization": "foo"}, retries=Retry(remove_headers_on_redirect=[]), ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert data["Authorization"] == "foo" def test_redirect_cross_host_set_removed_headers(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"X-API-Secret": "foo", "Authorization": "bar"}, retries=Retry(remove_headers_on_redirect=["X-API-Secret"]), ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert "X-API-Secret" not in data assert data["Authorization"] == "bar" r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"x-api-secret": "foo", "authorization": "bar"}, retries=Retry(remove_headers_on_redirect=["X-API-Secret"]), ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert "x-api-secret" not in data assert "X-API-Secret" not in data assert data["Authorization"] == "bar" def test_raise_on_redirect(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={ "target": "%s/redirect?target=%s/" % (self.base_url, self.base_url) }, retries=Retry(total=None, redirect=1, raise_on_redirect=False), ) assert r.status == 303 def test_raise_on_status(self): with PoolManager() as http: with pytest.raises(MaxRetryError): # the default is to raise r = http.request( "GET", "%s/status" % self.base_url, fields={"status": "500 Internal Server Error"}, retries=Retry(total=1, status_forcelist=range(500, 600)), ) with pytest.raises(MaxRetryError): # raise explicitly r = http.request( "GET", "%s/status" % self.base_url, fields={"status": "500 Internal Server Error"}, retries=Retry( total=1, status_forcelist=range(500, 600), raise_on_status=True ), ) # don't raise r = http.request( "GET", "%s/status" % self.base_url, fields={"status": "500 Internal Server Error"}, retries=Retry( total=1, status_forcelist=range(500, 600), raise_on_status=False ), ) assert r.status == 500 def test_missing_port(self): # Can a URL that lacks an explicit port like ':80' succeed, or # will all such URLs fail with an error? with PoolManager() as http: # By globally adjusting `DEFAULT_PORTS` we pretend for a moment # that HTTP's default port is not 80, but is the port at which # our test server happens to be listening. DEFAULT_PORTS["http"] = self.port try: r = http.request("GET", "http://%s/" % self.host, retries=0) finally: DEFAULT_PORTS["http"] = 80 assert r.status == 200 assert r.data == b"Dummy server!" def test_headers(self): with PoolManager(headers={"Foo": "bar"}) as http: r = http.request("GET", "%s/headers" % self.base_url) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") == "bar" r = http.request("POST", "%s/headers" % self.base_url) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") == "bar" r = http.request_encode_url("GET", "%s/headers" % self.base_url) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") == "bar" r = http.request_encode_body("POST", "%s/headers" % self.base_url) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") == "bar" r = http.request_encode_url( "GET", "%s/headers" % self.base_url, headers={"Baz": "quux"} ) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") is None assert returned_headers.get("Baz") == "quux" r = http.request_encode_body( "GET", "%s/headers" % self.base_url, headers={"Baz": "quux"} ) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") is None assert returned_headers.get("Baz") == "quux" def test_http_with_ssl_keywords(self): with PoolManager(ca_certs="REQUIRED") as http: r = http.request("GET", "http://%s:%s/" % (self.host, self.port)) assert r.status == 200 def test_http_with_ca_cert_dir(self): with PoolManager(ca_certs="REQUIRED", ca_cert_dir="/nosuchdir") as http: r = http.request("GET", "http://%s:%s/" % (self.host, self.port)) assert r.status == 200 def test_cleanup_on_connection_error(self): """ Test that connections are recycled to the pool on connection errors where no http response is received. """ poolsize = 3 with PoolManager(maxsize=poolsize, block=True) as http: pool = http.connection_from_host(self.host, self.port) assert pool.pool.qsize() == poolsize # force a connection error by supplying a non-existent # url. We won't get a response for this and so the # conn won't be implicitly returned to the pool. url = "%s/redirect" % self.base_url with pytest.raises(MaxRetryError): http.request("GET", url, fields={"target": "/"}, retries=0) r = http.request("GET", url, fields={"target": "/"}, retries=1) r.release_conn() # the pool should still contain poolsize elements assert pool.pool.qsize() == poolsize class TestRetry(HTTPDummyServerTestCase): @classmethod def setup_class(self): super(TestRetry, self).setup_class() self.base_url = "http://%s:%d" % (self.host, self.port) self.base_url_alt = "http://%s:%d" % (self.host_alt, self.port) def test_max_retry(self): with PoolManager() as http: with pytest.raises(MaxRetryError): http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/"}, retries=0, ) def test_disabled_retry(self): """ Disabled retries should disable redirect handling. """ with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/"}, retries=False, ) assert r.status == 303 r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/"}, retries=Retry(redirect=False), ) assert r.status == 303 with pytest.raises(NewConnectionError): http.request( "GET", "http://thishostdoesnotexist.invalid/", timeout=0.001, retries=False, ) def test_read_retries(self): """ Should retry for status codes in the whitelist """ retry = Retry(read=1, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers={"test-name": "test_read_retries"}, retries=retry, ) assert resp.status == 200 def test_read_total_retries(self): """ HTTP response w/ status code in the whitelist should be retried """ headers = {"test-name": "test_read_total_retries"} retry = Retry(total=1, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 200 def test_retries_wrong_whitelist(self): """HTTP response w/ status code not in whitelist shouldn't be retried""" retry = Retry(total=1, status_forcelist=[202]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers={"test-name": "test_wrong_whitelist"}, retries=retry, ) assert resp.status == 418 def test_default_method_whitelist_retried(self): """Hip should retry methods in the default method whitelist""" retry = Retry(total=1, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "OPTIONS", "%s/successful_retry" % self.base_url, headers={"test-name": "test_default_whitelist"}, retries=retry, ) assert resp.status == 200 def test_retries_wrong_method_list(self): """Method not in our whitelist should not be retried, even if code matches""" headers = {"test-name": "test_wrong_method_whitelist"} retry = Retry(total=1, status_forcelist=[418], method_whitelist=["POST"]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 418 def test_read_retries_unsuccessful(self): headers = {"test-name": "test_read_retries_unsuccessful"} with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=1 ) assert resp.status == 418 def test_retry_reuse_safe(self): """ It should be possible to reuse a Retry object across requests """ headers = {"test-name": "test_retry_safe"} retry = Retry(total=1, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 200 resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 200 def test_retry_return_in_response(self): headers = {"test-name": "test_retry_return_in_response"} retry = Retry(total=2, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 200 assert resp.retries.total == 1 assert resp.retries.history == ( RequestHistory("GET", "/successful_retry", None, 418, None), ) def test_retry_redirect_history(self): with PoolManager() as http: resp = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/"} ) assert resp.status == 200 assert resp.retries.history == ( RequestHistory( "GET", self.base_url + "/redirect?target=%2F", None, 303, "/" ), ) def test_multi_redirect_history(self): with PoolManager() as http: r = http.request( "GET", "%s/multi_redirect" % self.base_url, fields={"redirect_codes": "303,302,200"}, redirect=False, ) assert r.status == 303 assert r.retries.history == tuple() r = http.request( "GET", "%s/multi_redirect" % self.base_url, retries=10, fields={"redirect_codes": "303,302,301,307,302,200"}, ) assert r.status == 200 assert r.data == b"Done redirecting" expected = [ (303, "/multi_redirect?redirect_codes=302,301,307,302,200"), (302, "/multi_redirect?redirect_codes=301,307,302,200"), (301, "/multi_redirect?redirect_codes=307,302,200"), (307, "/multi_redirect?redirect_codes=302,200"), (302, "/multi_redirect?redirect_codes=200"), ] actual = [ (history.status, history.redirect_location) for history in r.retries.history ] assert actual == expected def test_redirect_put_file(self): """PUT with file object should work with a redirection response""" retry = Retry(total=3, status_forcelist=[418]) # httplib reads in 8k chunks; use a larger content length content_length = 65535 data = b"A" * content_length uploaded_file = io.BytesIO(data) headers = { "test-name": "test_redirect_put_file", "Content-Length": str(content_length), } url = "%s/redirect?target=/echo&status=307" % self.base_url with PoolManager() as http: resp = http.urlopen( "PUT", url, headers=headers, retries=retry, body=uploaded_file ) assert resp.status == 200 assert resp.data == data class TestRetryAfter(HTTPDummyServerTestCase): @classmethod def setup_class(self): super(TestRetryAfter, self).setup_class() self.base_url = "http://%s:%d" % (self.host, self.port) self.base_url_alt = "http://%s:%d" % (self.host_alt, self.port) def test_retry_after(self): url = "%s/retry_after" % self.base_url with PoolManager() as http: # Request twice in a second to get a 429 response. r = http.request( "GET", url, fields={"status": "429 Too Many Requests"}, retries=False ) r = http.request( "GET", url, fields={"status": "429 Too Many Requests"}, retries=False ) assert r.status == 429 r = http.request( "GET", url, fields={"status": "429 Too Many Requests"}, retries=True ) assert r.status == 200 # Request twice in a second to get a 503 response. r = http.request( "GET", url, fields={"status": "503 Service Unavailable"}, retries=False ) r = http.request( "GET", url, fields={"status": "503 Service Unavailable"}, retries=False ) assert r.status == 503 r = http.request( "GET", url, fields={"status": "503 Service Unavailable"}, retries=True ) assert r.status == 200 # Ignore Retry-After header on status which is not defined in # Retry.RETRY_AFTER_STATUS_CODES. r = http.request( "GET", url, fields={"status": "418 I'm a teapot"}, retries=True ) assert r.status == 418 def test_redirect_after(self): with PoolManager() as http: r = http.request("GET", "%s/redirect_after" % self.base_url, retries=False) assert r.status == 303 t = time.time() r = http.request("GET", "%s/redirect_after" % self.base_url) assert r.status == 200 delta = time.time() - t assert delta >= 1 t = time.time() timestamp = t + 2 r = http.request( "GET", self.base_url + "/redirect_after?date=" + str(timestamp) ) assert r.status == 200 delta = time.time() - t assert delta >= 1 # Retry-After is past t = time.time() timestamp = t - 1 r = http.request( "GET", self.base_url + "/redirect_after?date=" + str(timestamp) ) delta = time.time() - t assert r.status == 200 assert delta < 1 class TestFileBodiesOnRetryOrRedirect(HTTPDummyServerTestCase): def setup_class(self): super(TestFileBodiesOnRetryOrRedirect, self).setup_class() self.base_url = "http://%s:%d" % (self.host, self.port) self.base_url_alt = "http://%s:%d" % (self.host_alt, self.port) def test_retries_put_filehandle(self): """HTTP PUT retry with a file-like object should not timeout""" retry = Retry(total=3, status_forcelist=[418]) # httplib reads in 8k chunks; use a larger content length content_length = 65535 data = b"A" * content_length uploaded_file = io.BytesIO(data) headers = { "test-name": "test_retries_put_filehandle", "Content-Length": str(content_length), } with PoolManager() as http: resp = http.urlopen( "PUT", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, body=uploaded_file, redirect=False, ) assert resp.status == 200 def test_redirect_with_failed_tell(self): """Abort request if failed to get a position from tell()""" class BadTellObject(io.BytesIO): def tell(self): raise IOError body = BadTellObject(b"the data") url = "%s/redirect?target=/successful_retry" % self.base_url # httplib uses fileno if Content-Length isn't supplied, # which is unsupported by BytesIO. headers = {"Content-Length": "8"} with PoolManager() as http: with pytest.raises(UnrewindableBodyError) as e: http.urlopen("PUT", url, headers=headers, body=body) assert "Unable to record file position for" in str(e.value) @pytest.mark.parametrize( ["target", "expected_target"], [ ("/echo_uri?q=1#fragment", b"/echo_uri?q=1"), ("/echo_uri?#", b"/echo_uri?"), ("/echo_uri#?", b"/echo_uri"), ("/echo_uri#?#", b"/echo_uri"), ("/echo_uri??#", b"/echo_uri??"), ("/echo_uri?%3f#", b"/echo_uri?%3F"), ("/echo_uri?%3F#", b"/echo_uri?%3F"), ("/echo_uri?[]", b"/echo_uri?%5B%5D"), ], ) def test_encode_http_target(self, target, expected_target): with PoolManager() as http: url = "http://%s:%d%s" % (self.host, self.port, target) r = http.request("GET", url) assert r.data == expected_target @pytest.mark.skipif(not HAS_IPV6, reason="IPv6 is not supported on this system") class TestIPv6PoolManager(IPv6HTTPDummyServerTestCase): @classmethod def setup_class(cls): super(TestIPv6PoolManager, cls).setup_class() cls.base_url = "http://[%s]:%d" % (cls.host, cls.port) def test_ipv6(self): with PoolManager() as http: http.request("GET", self.base_url)

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import io import json import time import pytest from dummyserver.server import HAS_IPV6 from dummyserver.testcase import HTTPDummyServerTestCase, IPv6HTTPDummyServerTestCase from hip.base import DEFAULT_PORTS from hip.poolmanager import PoolManager from hip.exceptions import MaxRetryError, NewConnectionError, UnrewindableBodyError from hip.util.retry import Retry, RequestHistory from test import LONG_TIMEOUT pytestmark = pytest.mark.flaky class TestPoolManager(HTTPDummyServerTestCase): @classmethod def setup_class(cls): super(TestPoolManager, cls).setup_class() cls.base_url = "http://%s:%d" % (cls.host, cls.port) cls.base_url_alt = "http://%s:%d" % (cls.host_alt, cls.port) def test_redirect(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/" % self.base_url}, redirect=False, ) assert r.status == 303 r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/" % self.base_url}, ) assert r.status == 200 assert r.data == b"Dummy server!" def test_redirect_twice(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/redirect" % self.base_url}, redirect=False, ) assert r.status == 303 r = http.request( "GET", "%s/redirect" % self.base_url, fields={ "target": "%s/redirect?target=%s/" % (self.base_url, self.base_url) }, ) assert r.status == 200 assert r.data == b"Dummy server!" def test_redirect_to_relative_url(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/redirect"}, redirect=False, ) assert r.status == 303 r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/redirect"} ) assert r.status == 200 assert r.data == b"Dummy server!" def test_cross_host_redirect(self): with PoolManager() as http: cross_host_location = "%s/echo?a=b" % self.base_url_alt with pytest.raises(MaxRetryError): http.request( "GET", "%s/redirect" % self.base_url, fields={"target": cross_host_location}, timeout=LONG_TIMEOUT, retries=0, ) r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/echo?a=b" % self.base_url_alt}, timeout=LONG_TIMEOUT, retries=1, ) assert r._pool.host == self.host_alt def test_too_many_redirects(self): with PoolManager() as http: with pytest.raises(MaxRetryError): http.request( "GET", "%s/redirect" % self.base_url, fields={ "target": "%s/redirect?target=%s/" % (self.base_url, self.base_url) }, retries=1, ) with pytest.raises(MaxRetryError): http.request( "GET", "%s/redirect" % self.base_url, fields={ "target": "%s/redirect?target=%s/" % (self.base_url, self.base_url) }, retries=Retry(total=None, redirect=1), ) def test_redirect_cross_host_remove_headers(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"Authorization": "foo"}, ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert "Authorization" not in data r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"authorization": "foo"}, ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert "authorization" not in data assert "Authorization" not in data def test_redirect_cross_host_no_remove_headers(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"Authorization": "foo"}, retries=Retry(remove_headers_on_redirect=[]), ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert data["Authorization"] == "foo" def test_redirect_cross_host_set_removed_headers(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"X-API-Secret": "foo", "Authorization": "bar"}, retries=Retry(remove_headers_on_redirect=["X-API-Secret"]), ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert "X-API-Secret" not in data assert data["Authorization"] == "bar" r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "%s/headers" % self.base_url_alt}, headers={"x-api-secret": "foo", "authorization": "bar"}, retries=Retry(remove_headers_on_redirect=["X-API-Secret"]), ) assert r.status == 200 data = json.loads(r.data.decode("utf-8")) assert "x-api-secret" not in data assert "X-API-Secret" not in data assert data["Authorization"] == "bar" def test_raise_on_redirect(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={ "target": "%s/redirect?target=%s/" % (self.base_url, self.base_url) }, retries=Retry(total=None, redirect=1, raise_on_redirect=False), ) assert r.status == 303 def test_raise_on_status(self): with PoolManager() as http: with pytest.raises(MaxRetryError): r = http.request( "GET", "%s/status" % self.base_url, fields={"status": "500 Internal Server Error"}, retries=Retry(total=1, status_forcelist=range(500, 600)), ) with pytest.raises(MaxRetryError): r = http.request( "GET", "%s/status" % self.base_url, fields={"status": "500 Internal Server Error"}, retries=Retry( total=1, status_forcelist=range(500, 600), raise_on_status=True ), ) r = http.request( "GET", "%s/status" % self.base_url, fields={"status": "500 Internal Server Error"}, retries=Retry( total=1, status_forcelist=range(500, 600), raise_on_status=False ), ) assert r.status == 500 def test_missing_port(self): # Can a URL that lacks an explicit port like ':80' succeed, or # will all such URLs fail with an error? with PoolManager() as http: # By globally adjusting `DEFAULT_PORTS` we pretend for a moment # that HTTP's default port is not 80, but is the port at which DEFAULT_PORTS["http"] = self.port try: r = http.request("GET", "http://%s/" % self.host, retries=0) finally: DEFAULT_PORTS["http"] = 80 assert r.status == 200 assert r.data == b"Dummy server!" def test_headers(self): with PoolManager(headers={"Foo": "bar"}) as http: r = http.request("GET", "%s/headers" % self.base_url) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") == "bar" r = http.request("POST", "%s/headers" % self.base_url) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") == "bar" r = http.request_encode_url("GET", "%s/headers" % self.base_url) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") == "bar" r = http.request_encode_body("POST", "%s/headers" % self.base_url) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") == "bar" r = http.request_encode_url( "GET", "%s/headers" % self.base_url, headers={"Baz": "quux"} ) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") is None assert returned_headers.get("Baz") == "quux" r = http.request_encode_body( "GET", "%s/headers" % self.base_url, headers={"Baz": "quux"} ) returned_headers = json.loads(r.data.decode()) assert returned_headers.get("Foo") is None assert returned_headers.get("Baz") == "quux" def test_http_with_ssl_keywords(self): with PoolManager(ca_certs="REQUIRED") as http: r = http.request("GET", "http://%s:%s/" % (self.host, self.port)) assert r.status == 200 def test_http_with_ca_cert_dir(self): with PoolManager(ca_certs="REQUIRED", ca_cert_dir="/nosuchdir") as http: r = http.request("GET", "http://%s:%s/" % (self.host, self.port)) assert r.status == 200 def test_cleanup_on_connection_error(self): poolsize = 3 with PoolManager(maxsize=poolsize, block=True) as http: pool = http.connection_from_host(self.host, self.port) assert pool.pool.qsize() == poolsize # conn won't be implicitly returned to the pool. url = "%s/redirect" % self.base_url with pytest.raises(MaxRetryError): http.request("GET", url, fields={"target": "/"}, retries=0) r = http.request("GET", url, fields={"target": "/"}, retries=1) r.release_conn() assert pool.pool.qsize() == poolsize class TestRetry(HTTPDummyServerTestCase): @classmethod def setup_class(self): super(TestRetry, self).setup_class() self.base_url = "http://%s:%d" % (self.host, self.port) self.base_url_alt = "http://%s:%d" % (self.host_alt, self.port) def test_max_retry(self): with PoolManager() as http: with pytest.raises(MaxRetryError): http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/"}, retries=0, ) def test_disabled_retry(self): with PoolManager() as http: r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/"}, retries=False, ) assert r.status == 303 r = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/"}, retries=Retry(redirect=False), ) assert r.status == 303 with pytest.raises(NewConnectionError): http.request( "GET", "http://thishostdoesnotexist.invalid/", timeout=0.001, retries=False, ) def test_read_retries(self): retry = Retry(read=1, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers={"test-name": "test_read_retries"}, retries=retry, ) assert resp.status == 200 def test_read_total_retries(self): headers = {"test-name": "test_read_total_retries"} retry = Retry(total=1, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 200 def test_retries_wrong_whitelist(self): retry = Retry(total=1, status_forcelist=[202]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers={"test-name": "test_wrong_whitelist"}, retries=retry, ) assert resp.status == 418 def test_default_method_whitelist_retried(self): retry = Retry(total=1, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "OPTIONS", "%s/successful_retry" % self.base_url, headers={"test-name": "test_default_whitelist"}, retries=retry, ) assert resp.status == 200 def test_retries_wrong_method_list(self): headers = {"test-name": "test_wrong_method_whitelist"} retry = Retry(total=1, status_forcelist=[418], method_whitelist=["POST"]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 418 def test_read_retries_unsuccessful(self): headers = {"test-name": "test_read_retries_unsuccessful"} with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=1 ) assert resp.status == 418 def test_retry_reuse_safe(self): headers = {"test-name": "test_retry_safe"} retry = Retry(total=1, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 200 resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 200 def test_retry_return_in_response(self): headers = {"test-name": "test_retry_return_in_response"} retry = Retry(total=2, status_forcelist=[418]) with PoolManager() as http: resp = http.request( "GET", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, ) assert resp.status == 200 assert resp.retries.total == 1 assert resp.retries.history == ( RequestHistory("GET", "/successful_retry", None, 418, None), ) def test_retry_redirect_history(self): with PoolManager() as http: resp = http.request( "GET", "%s/redirect" % self.base_url, fields={"target": "/"} ) assert resp.status == 200 assert resp.retries.history == ( RequestHistory( "GET", self.base_url + "/redirect?target=%2F", None, 303, "/" ), ) def test_multi_redirect_history(self): with PoolManager() as http: r = http.request( "GET", "%s/multi_redirect" % self.base_url, fields={"redirect_codes": "303,302,200"}, redirect=False, ) assert r.status == 303 assert r.retries.history == tuple() r = http.request( "GET", "%s/multi_redirect" % self.base_url, retries=10, fields={"redirect_codes": "303,302,301,307,302,200"}, ) assert r.status == 200 assert r.data == b"Done redirecting" expected = [ (303, "/multi_redirect?redirect_codes=302,301,307,302,200"), (302, "/multi_redirect?redirect_codes=301,307,302,200"), (301, "/multi_redirect?redirect_codes=307,302,200"), (307, "/multi_redirect?redirect_codes=302,200"), (302, "/multi_redirect?redirect_codes=200"), ] actual = [ (history.status, history.redirect_location) for history in r.retries.history ] assert actual == expected def test_redirect_put_file(self): retry = Retry(total=3, status_forcelist=[418]) content_length = 65535 data = b"A" * content_length uploaded_file = io.BytesIO(data) headers = { "test-name": "test_redirect_put_file", "Content-Length": str(content_length), } url = "%s/redirect?target=/echo&status=307" % self.base_url with PoolManager() as http: resp = http.urlopen( "PUT", url, headers=headers, retries=retry, body=uploaded_file ) assert resp.status == 200 assert resp.data == data class TestRetryAfter(HTTPDummyServerTestCase): @classmethod def setup_class(self): super(TestRetryAfter, self).setup_class() self.base_url = "http://%s:%d" % (self.host, self.port) self.base_url_alt = "http://%s:%d" % (self.host_alt, self.port) def test_retry_after(self): url = "%s/retry_after" % self.base_url with PoolManager() as http: r = http.request( "GET", url, fields={"status": "429 Too Many Requests"}, retries=False ) r = http.request( "GET", url, fields={"status": "429 Too Many Requests"}, retries=False ) assert r.status == 429 r = http.request( "GET", url, fields={"status": "429 Too Many Requests"}, retries=True ) assert r.status == 200 r = http.request( "GET", url, fields={"status": "503 Service Unavailable"}, retries=False ) r = http.request( "GET", url, fields={"status": "503 Service Unavailable"}, retries=False ) assert r.status == 503 r = http.request( "GET", url, fields={"status": "503 Service Unavailable"}, retries=True ) assert r.status == 200 r = http.request( "GET", url, fields={"status": "418 I'm a teapot"}, retries=True ) assert r.status == 418 def test_redirect_after(self): with PoolManager() as http: r = http.request("GET", "%s/redirect_after" % self.base_url, retries=False) assert r.status == 303 t = time.time() r = http.request("GET", "%s/redirect_after" % self.base_url) assert r.status == 200 delta = time.time() - t assert delta >= 1 t = time.time() timestamp = t + 2 r = http.request( "GET", self.base_url + "/redirect_after?date=" + str(timestamp) ) assert r.status == 200 delta = time.time() - t assert delta >= 1 # Retry-After is past t = time.time() timestamp = t - 1 r = http.request( "GET", self.base_url + "/redirect_after?date=" + str(timestamp) ) delta = time.time() - t assert r.status == 200 assert delta < 1 class TestFileBodiesOnRetryOrRedirect(HTTPDummyServerTestCase): def setup_class(self): super(TestFileBodiesOnRetryOrRedirect, self).setup_class() self.base_url = "http://%s:%d" % (self.host, self.port) self.base_url_alt = "http://%s:%d" % (self.host_alt, self.port) def test_retries_put_filehandle(self): retry = Retry(total=3, status_forcelist=[418]) # httplib reads in 8k chunks; use a larger content length content_length = 65535 data = b"A" * content_length uploaded_file = io.BytesIO(data) headers = { "test-name": "test_retries_put_filehandle", "Content-Length": str(content_length), } with PoolManager() as http: resp = http.urlopen( "PUT", "%s/successful_retry" % self.base_url, headers=headers, retries=retry, body=uploaded_file, redirect=False, ) assert resp.status == 200 def test_redirect_with_failed_tell(self): class BadTellObject(io.BytesIO): def tell(self): raise IOError body = BadTellObject(b"the data") url = "%s/redirect?target=/successful_retry" % self.base_url # httplib uses fileno if Content-Length isn't supplied, headers = {"Content-Length": "8"} with PoolManager() as http: with pytest.raises(UnrewindableBodyError) as e: http.urlopen("PUT", url, headers=headers, body=body) assert "Unable to record file position for" in str(e.value) @pytest.mark.parametrize( ["target", "expected_target"], [ ("/echo_uri?q=1#fragment", b"/echo_uri?q=1"), ("/echo_uri?#", b"/echo_uri?"), ("/echo_uri#?", b"/echo_uri"), ("/echo_uri#?#", b"/echo_uri"), ("/echo_uri??#", b"/echo_uri??"), ("/echo_uri?%3f#", b"/echo_uri?%3F"), ("/echo_uri?%3F#", b"/echo_uri?%3F"), ("/echo_uri?[]", b"/echo_uri?%5B%5D"), ], ) def test_encode_http_target(self, target, expected_target): with PoolManager() as http: url = "http://%s:%d%s" % (self.host, self.port, target) r = http.request("GET", url) assert r.data == expected_target @pytest.mark.skipif(not HAS_IPV6, reason="IPv6 is not supported on this system") class TestIPv6PoolManager(IPv6HTTPDummyServerTestCase): @classmethod def setup_class(cls): super(TestIPv6PoolManager, cls).setup_class() cls.base_url = "http://[%s]:%d" % (cls.host, cls.port) def test_ipv6(self): with PoolManager() as http: http.request("GET", self.base_url)

true

f7187fe8f56ad4cf2d4f4dd6df4dd33406b5cf84

13,872

py

Python

tools/my_runner.py

ydiller/NoMoreNMS

1c1557357e5312c287f0971c840060deb1bcd039

[ "Apache-2.0" ]

null

tools/my_runner.py

ydiller/NoMoreNMS

1c1557357e5312c287f0971c840060deb1bcd039

[ "Apache-2.0" ]

null

tools/my_runner.py

ydiller/NoMoreNMS

1c1557357e5312c287f0971c840060deb1bcd039

[ "Apache-2.0" ]

null

# Copyright (c) OpenMMLab. All rights reserved. import os.path as osp import platform import shutil import time import warnings import torch import mmcv import wandb from mmcv.runner.hooks import HOOKS, Hook from mmcv.runner.base_runner import BaseRunner from mmcv.runner.builder import RUNNERS from mmcv.runner.checkpoint import save_checkpoint from mmcv.runner.utils import get_host_info import copy import logging import os.path as osp import warnings from abc import ABCMeta, abstractmethod import torch from torch.optim import Optimizer import mmcv from mmcv.parallel import is_module_wrapper from mmcv.runner.checkpoint import load_checkpoint from mmcv.runner.dist_utils import get_dist_info from mmcv.runner.hooks import HOOKS, Hook from mmcv.runner.log_buffer import LogBuffer from mmcv.runner.priority import Priority, get_priority from mmcv.runner.utils import get_time_str @RUNNERS.register_module() class MyRunner(BaseRunner): """Epoch-based Runner. This runner train models epoch by epoch. """ def __init__(self, model, batch_processor=None, optimizer=None, work_dir=None, logger=None, meta=None, max_iters=None, max_epochs=None, with_wandb=None): if batch_processor is not None: if not callable(batch_processor): raise TypeError('batch_processor must be callable, ' f'but got {type(batch_processor)}') warnings.warn( 'batch_processor is deprecated, please implement ' 'train_step() and val_step() in the model instead.', DeprecationWarning) # raise an error is `batch_processor` is not None and # `model.train_step()` exists. if is_module_wrapper(model): _model = model.module else: _model = model if hasattr(_model, 'train_step') or hasattr(_model, 'val_step'): raise RuntimeError( 'batch_processor and model.train_step()/model.val_step() ' 'cannot be both available.') else: assert hasattr(model, 'train_step') # check the type of `optimizer` if isinstance(optimizer, dict): for name, optim in optimizer.items(): if not isinstance(optim, Optimizer): raise TypeError( f'optimizer must be a dict of torch.optim.Optimizers, ' f'but optimizer["{name}"] is a {type(optim)}') elif not isinstance(optimizer, Optimizer) and optimizer is not None: raise TypeError( f'optimizer must be a torch.optim.Optimizer object ' f'or dict or None, but got {type(optimizer)}') # check the type of `logger` if not isinstance(logger, logging.Logger): raise TypeError(f'logger must be a logging.Logger object, ' f'but got {type(logger)}') # check the type of `meta` if meta is not None and not isinstance(meta, dict): raise TypeError( f'meta must be a dict or None, but got {type(meta)}') self.model = model self.batch_processor = batch_processor self.optimizer = optimizer self.logger = logger self.meta = meta self.with_wandb = with_wandb # create work_dir if mmcv.is_str(work_dir): self.work_dir = osp.abspath(work_dir) mmcv.mkdir_or_exist(self.work_dir) elif work_dir is None: self.work_dir = None else: raise TypeError('"work_dir" must be a str or None') # get model name from the model class if hasattr(self.model, 'module'): self._model_name = self.model.module.__class__.__name__ else: self._model_name = self.model.__class__.__name__ self._rank, self._world_size = get_dist_info() self.timestamp = get_time_str() self.mode = None self._hooks = [] self._epoch = 0 self._iter = 0 self._inner_iter = 0 if max_epochs is not None and max_iters is not None: raise ValueError( 'Only one of `max_epochs` or `max_iters` can be set.') self._max_epochs = max_epochs self._max_iters = max_iters # TODO: Redesign LogBuffer, it is not flexible and elegant enough self.log_buffer = LogBuffer() def register_optimizer_hook(self, optimizer_config): if optimizer_config is None: return if isinstance(optimizer_config, dict): optimizer_config.setdefault('type', 'MyHook') hook = mmcv.build_from_cfg(optimizer_config, HOOKS) else: hook = optimizer_config self.register_hook(hook, priority='ABOVE_NORMAL') def run_iter(self, data_batch, train_mode, **kwargs): if self.batch_processor is not None: outputs = self.batch_processor( self.model, data_batch, train_mode=train_mode, **kwargs) elif train_mode: outputs = self.model.train_step(data_batch, self.optimizer, **kwargs) else: outputs = self.model.val_step(data_batch, self.optimizer, **kwargs) if not isinstance(outputs, dict): raise TypeError('"batch_processor()" or "model.train_step()"' 'and "model.val_step()" must return a dict') if 'log_vars' in outputs: self.log_buffer.update(outputs['log_vars'], outputs['num_samples']) self.outputs = outputs def train(self, data_loader, **kwargs): self.model.train() self.mode = 'train' self.data_loader = data_loader self._max_iters = self._max_epochs * len(self.data_loader) self.call_hook('before_train_epoch') time.sleep(2) # Prevent possible deadlock during epoch transition for i, data_batch in enumerate(self.data_loader): self._inner_iter = i self.call_hook('before_train_iter') self.run_iter(data_batch, train_mode=True, **kwargs) self.call_hook('after_train_iter') self._iter += 1 self.call_hook('after_train_epoch') self._epoch += 1 @torch.no_grad() def val(self, data_loader, **kwargs): self.model.eval() self.mode = 'val' self.data_loader = data_loader self.call_hook('before_val_epoch') time.sleep(2) # Prevent possible deadlock during epoch transition for i, data_batch in enumerate(self.data_loader): self._inner_iter = i self.call_hook('before_val_iter') self.run_iter(data_batch, train_mode=False) self.call_hook('after_val_iter') self.call_hook('after_val_epoch') if torch.distributed.is_initialized(): if torch.distributed.get_rank() == 0: if self.with_wandb: wandb.log({"CE val loss": sum(self.log_buffer.val_history['loss_deepsets_ce'])/ len(self.log_buffer.val_history['loss_deepsets_ce']), "val ds_acc": sum(self.log_buffer.val_history['ds_acc'])/ len(self.log_buffer.val_history['ds_acc']), "val iou_error": sum(self.log_buffer.val_history['iou_error'])/len(self.log_buffer.val_history['iou_error']), "val max score predictions": sum(self.log_buffer.val_history['ds_pred_on_max'])/ len(self.log_buffer.val_history['ds_pred_on_max']) }) else: # single gpu if self.with_wandb: wandb.log({"CE val loss": sum(self.log_buffer.val_history['loss_deepsets_ce']) / len(self.log_buffer.val_history['loss_deepsets_ce']), "val ds_acc": sum(self.log_buffer.val_history['ds_acc']) / len(self.log_buffer.val_history['ds_acc']), "val iou_error": sum(self.log_buffer.val_history['iou_error']) / len( self.log_buffer.val_history['iou_error']), "val max score predictions": sum(self.log_buffer.val_history['ds_pred_on_max']) / len(self.log_buffer.val_history['ds_pred_on_max'])}) def run(self, data_loaders, workflow, max_epochs=None, **kwargs): """Start running. Args: data_loaders (list[:obj:`DataLoader`]): Dataloaders for training and validation. workflow (list[tuple]): A list of (phase, epochs) to specify the running order and epochs. E.g, [('train', 2), ('val', 1)] means running 2 epochs for training and 1 epoch for validation, iteratively. """ assert isinstance(data_loaders, list) assert mmcv.is_list_of(workflow, tuple) assert len(data_loaders) == len(workflow) if max_epochs is not None: warnings.warn( 'setting max_epochs in run is deprecated, ' 'please set max_epochs in runner_config', DeprecationWarning) self._max_epochs = max_epochs assert self._max_epochs is not None, ( 'max_epochs must be specified during instantiation') for i, flow in enumerate(workflow): mode, epochs = flow if mode == 'train': self._max_iters = self._max_epochs * len(data_loaders[i]) break work_dir = self.work_dir if self.work_dir is not None else 'NONE' self.logger.info('Start running, host: %s, work_dir: %s', get_host_info(), work_dir) self.logger.info('Hooks will be executed in the following order:\n%s', self.get_hook_info()) self.logger.info('workflow: %s, max: %d epochs', workflow, self._max_epochs) self.call_hook('before_run') while self.epoch < self._max_epochs: for i, flow in enumerate(workflow): mode, epochs = flow if isinstance(mode, str): # self.train() if not hasattr(self, mode): raise ValueError( f'runner has no method named "{mode}" to run an ' 'epoch') epoch_runner = getattr(self, mode) else: raise TypeError( 'mode in workflow must be a str, but got {}'.format( type(mode))) for _ in range(epochs): if mode == 'train' and self.epoch >= self._max_epochs: break epoch_runner(data_loaders[i], **kwargs) time.sleep(1) # wait for some hooks like loggers to finish self.call_hook('after_run') def save_checkpoint(self, out_dir, filename_tmpl='end2end_epoch_{}.pth', save_optimizer=True, meta=None, create_symlink=True): """Save the checkpoint. Args: out_dir (str): The directory that checkpoints are saved. filename_tmpl (str, optional): The checkpoint filename template, which contains a placeholder for the epoch number. Defaults to 'epoch_{}.pth'. save_optimizer (bool, optional): Whether to save the optimizer to the checkpoint. Defaults to True. meta (dict, optional): The meta information to be saved in the checkpoint. Defaults to None. create_symlink (bool, optional): Whether to create a symlink "latest.pth" to point to the latest checkpoint. Defaults to True. """ if meta is None: meta = {} elif not isinstance(meta, dict): raise TypeError( f'meta should be a dict or None, but got {type(meta)}') if self.meta is not None: meta.update(self.meta) # Note: meta.update(self.meta) should be done before # meta.update(epoch=self.epoch + 1, iter=self.iter) otherwise # there will be problems with resumed checkpoints. # More details in https://github.com/open-mmlab/mmcv/pull/1108 meta.update(epoch=self.epoch + 1, iter=self.iter) filename = filename_tmpl.format(self.epoch + 1) filepath = osp.join(out_dir, filename) optimizer = self.optimizer if save_optimizer else None save_checkpoint(self.model, filepath, optimizer=optimizer, meta=meta) # in some environments, `os.symlink` is not supported, you may need to # set `create_symlink` to False if create_symlink: dst_file = osp.join(out_dir, 'latest.pth') if platform.system() != 'Windows': mmcv.symlink(filename, dst_file) else: shutil.copy(filepath, dst_file) # @RUNNERS.register_module() # class Runner(MyRunner): # """Deprecated name of EpochBasedRunner.""" # # def __init__(self, *args, **kwargs): # warnings.warn( # 'Runner was deprecated, please use EpochBasedRunner instead', # DeprecationWarning) # super().__init__(*args, **kwargs)

42.292683

140

0.575115

import os.path as osp import platform import shutil import time import warnings import torch import mmcv import wandb from mmcv.runner.hooks import HOOKS, Hook from mmcv.runner.base_runner import BaseRunner from mmcv.runner.builder import RUNNERS from mmcv.runner.checkpoint import save_checkpoint from mmcv.runner.utils import get_host_info import copy import logging import os.path as osp import warnings from abc import ABCMeta, abstractmethod import torch from torch.optim import Optimizer import mmcv from mmcv.parallel import is_module_wrapper from mmcv.runner.checkpoint import load_checkpoint from mmcv.runner.dist_utils import get_dist_info from mmcv.runner.hooks import HOOKS, Hook from mmcv.runner.log_buffer import LogBuffer from mmcv.runner.priority import Priority, get_priority from mmcv.runner.utils import get_time_str @RUNNERS.register_module() class MyRunner(BaseRunner): def __init__(self, model, batch_processor=None, optimizer=None, work_dir=None, logger=None, meta=None, max_iters=None, max_epochs=None, with_wandb=None): if batch_processor is not None: if not callable(batch_processor): raise TypeError('batch_processor must be callable, ' f'but got {type(batch_processor)}') warnings.warn( 'batch_processor is deprecated, please implement ' 'train_step() and val_step() in the model instead.', DeprecationWarning) if is_module_wrapper(model): _model = model.module else: _model = model if hasattr(_model, 'train_step') or hasattr(_model, 'val_step'): raise RuntimeError( 'batch_processor and model.train_step()/model.val_step() ' 'cannot be both available.') else: assert hasattr(model, 'train_step') if isinstance(optimizer, dict): for name, optim in optimizer.items(): if not isinstance(optim, Optimizer): raise TypeError( f'optimizer must be a dict of torch.optim.Optimizers, ' f'but optimizer["{name}"] is a {type(optim)}') elif not isinstance(optimizer, Optimizer) and optimizer is not None: raise TypeError( f'optimizer must be a torch.optim.Optimizer object ' f'or dict or None, but got {type(optimizer)}') if not isinstance(logger, logging.Logger): raise TypeError(f'logger must be a logging.Logger object, ' f'but got {type(logger)}') if meta is not None and not isinstance(meta, dict): raise TypeError( f'meta must be a dict or None, but got {type(meta)}') self.model = model self.batch_processor = batch_processor self.optimizer = optimizer self.logger = logger self.meta = meta self.with_wandb = with_wandb if mmcv.is_str(work_dir): self.work_dir = osp.abspath(work_dir) mmcv.mkdir_or_exist(self.work_dir) elif work_dir is None: self.work_dir = None else: raise TypeError('"work_dir" must be a str or None') if hasattr(self.model, 'module'): self._model_name = self.model.module.__class__.__name__ else: self._model_name = self.model.__class__.__name__ self._rank, self._world_size = get_dist_info() self.timestamp = get_time_str() self.mode = None self._hooks = [] self._epoch = 0 self._iter = 0 self._inner_iter = 0 if max_epochs is not None and max_iters is not None: raise ValueError( 'Only one of `max_epochs` or `max_iters` can be set.') self._max_epochs = max_epochs self._max_iters = max_iters self.log_buffer = LogBuffer() def register_optimizer_hook(self, optimizer_config): if optimizer_config is None: return if isinstance(optimizer_config, dict): optimizer_config.setdefault('type', 'MyHook') hook = mmcv.build_from_cfg(optimizer_config, HOOKS) else: hook = optimizer_config self.register_hook(hook, priority='ABOVE_NORMAL') def run_iter(self, data_batch, train_mode, **kwargs): if self.batch_processor is not None: outputs = self.batch_processor( self.model, data_batch, train_mode=train_mode, **kwargs) elif train_mode: outputs = self.model.train_step(data_batch, self.optimizer, **kwargs) else: outputs = self.model.val_step(data_batch, self.optimizer, **kwargs) if not isinstance(outputs, dict): raise TypeError('"batch_processor()" or "model.train_step()"' 'and "model.val_step()" must return a dict') if 'log_vars' in outputs: self.log_buffer.update(outputs['log_vars'], outputs['num_samples']) self.outputs = outputs def train(self, data_loader, **kwargs): self.model.train() self.mode = 'train' self.data_loader = data_loader self._max_iters = self._max_epochs * len(self.data_loader) self.call_hook('before_train_epoch') time.sleep(2) for i, data_batch in enumerate(self.data_loader): self._inner_iter = i self.call_hook('before_train_iter') self.run_iter(data_batch, train_mode=True, **kwargs) self.call_hook('after_train_iter') self._iter += 1 self.call_hook('after_train_epoch') self._epoch += 1 @torch.no_grad() def val(self, data_loader, **kwargs): self.model.eval() self.mode = 'val' self.data_loader = data_loader self.call_hook('before_val_epoch') time.sleep(2) for i, data_batch in enumerate(self.data_loader): self._inner_iter = i self.call_hook('before_val_iter') self.run_iter(data_batch, train_mode=False) self.call_hook('after_val_iter') self.call_hook('after_val_epoch') if torch.distributed.is_initialized(): if torch.distributed.get_rank() == 0: if self.with_wandb: wandb.log({"CE val loss": sum(self.log_buffer.val_history['loss_deepsets_ce'])/ len(self.log_buffer.val_history['loss_deepsets_ce']), "val ds_acc": sum(self.log_buffer.val_history['ds_acc'])/ len(self.log_buffer.val_history['ds_acc']), "val iou_error": sum(self.log_buffer.val_history['iou_error'])/len(self.log_buffer.val_history['iou_error']), "val max score predictions": sum(self.log_buffer.val_history['ds_pred_on_max'])/ len(self.log_buffer.val_history['ds_pred_on_max']) }) else: if self.with_wandb: wandb.log({"CE val loss": sum(self.log_buffer.val_history['loss_deepsets_ce']) / len(self.log_buffer.val_history['loss_deepsets_ce']), "val ds_acc": sum(self.log_buffer.val_history['ds_acc']) / len(self.log_buffer.val_history['ds_acc']), "val iou_error": sum(self.log_buffer.val_history['iou_error']) / len( self.log_buffer.val_history['iou_error']), "val max score predictions": sum(self.log_buffer.val_history['ds_pred_on_max']) / len(self.log_buffer.val_history['ds_pred_on_max'])}) def run(self, data_loaders, workflow, max_epochs=None, **kwargs): assert isinstance(data_loaders, list) assert mmcv.is_list_of(workflow, tuple) assert len(data_loaders) == len(workflow) if max_epochs is not None: warnings.warn( 'setting max_epochs in run is deprecated, ' 'please set max_epochs in runner_config', DeprecationWarning) self._max_epochs = max_epochs assert self._max_epochs is not None, ( 'max_epochs must be specified during instantiation') for i, flow in enumerate(workflow): mode, epochs = flow if mode == 'train': self._max_iters = self._max_epochs * len(data_loaders[i]) break work_dir = self.work_dir if self.work_dir is not None else 'NONE' self.logger.info('Start running, host: %s, work_dir: %s', get_host_info(), work_dir) self.logger.info('Hooks will be executed in the following order:\n%s', self.get_hook_info()) self.logger.info('workflow: %s, max: %d epochs', workflow, self._max_epochs) self.call_hook('before_run') while self.epoch < self._max_epochs: for i, flow in enumerate(workflow): mode, epochs = flow if isinstance(mode, str): if not hasattr(self, mode): raise ValueError( f'runner has no method named "{mode}" to run an ' 'epoch') epoch_runner = getattr(self, mode) else: raise TypeError( 'mode in workflow must be a str, but got {}'.format( type(mode))) for _ in range(epochs): if mode == 'train' and self.epoch >= self._max_epochs: break epoch_runner(data_loaders[i], **kwargs) time.sleep(1) self.call_hook('after_run') def save_checkpoint(self, out_dir, filename_tmpl='end2end_epoch_{}.pth', save_optimizer=True, meta=None, create_symlink=True): if meta is None: meta = {} elif not isinstance(meta, dict): raise TypeError( f'meta should be a dict or None, but got {type(meta)}') if self.meta is not None: meta.update(self.meta) meta.update(epoch=self.epoch + 1, iter=self.iter) filename = filename_tmpl.format(self.epoch + 1) filepath = osp.join(out_dir, filename) optimizer = self.optimizer if save_optimizer else None save_checkpoint(self.model, filepath, optimizer=optimizer, meta=meta) if create_symlink: dst_file = osp.join(out_dir, 'latest.pth') if platform.system() != 'Windows': mmcv.symlink(filename, dst_file) else: shutil.copy(filepath, dst_file)

true

f7187ff435949165d6ffa9b6741462e446524819

6,374

py

Python

data_process/kdtree.py

MortonWang/geo_IF

4e27aeb9e005cdfb151777bc730de6d8372d1b7f

[ "MIT" ]

5

2020-06-19T13:39:59.000Z

2022-03-04T13:05:58.000Z

data_process/kdtree.py

MortonWang/geo_IF

4e27aeb9e005cdfb151777bc730de6d8372d1b7f

[ "MIT" ]

null

data_process/kdtree.py

MortonWang/geo_IF

4e27aeb9e005cdfb151777bc730de6d8372d1b7f

[ "MIT" ]

null

# -*- coding:utf-8 -*- import copy import numpy as np from scipy._lib.six import xrange class KDTree: def __init__(self, bucket_size, dimensions, parent=None): self.bucket_size = bucket_size self.parent = None self.left = None self.right = None self.split_dimension = None self.split_value = None self.index_locations = [] self.location_count = 0 self.min_limit = [np.Inf] * dimensions self.max_limit = [-np.Inf] * dimensions self.dimensions = dimensions def get_leaf(self, location): if not self.left and not self.right: return self elif location[self.split_dimension] <= self.split_value: return self.left.get_leaf(location) else: return self.right.get_leaf(location) def add_point(self, index_location_tuple): self.index_locations.append(index_location_tuple) self.location_count += 1 self.extendBounds(index_location_tuple[1]) self.min_boundary = copy.deepcopy(self.min_limit) self.max_boundary = copy.deepcopy(self.max_limit) def extendBounds(self, location): # empty if self.min_limit == None: self.min_limit = copy.deepcopy(location) self.max_limit = copy.deepcopy(location) return for i in xrange(self.dimensions): self.min_limit[i] = min(self.min_limit[i], location[i]) self.max_limit[i] = max(self.max_limit[i], location[i]) def findWidestAxis(self): widths = [self.max_limit[i] - self.min_limit[i] for i in range(self.dimensions)] widest_axis = np.argmax(widths) return widest_axis def getNodes(self): nodes = [] self.getNodesHelper(nodes) return nodes def getNodesHelper(self, nodes): nodes.append(self) if self.left: self.left.getNodesHelper(nodes) if self.right: self.right.getNodesHelper(nodes) def getLeaves(self): leaves = [] self.getLeavesHelper(leaves) return leaves def getLeavesHelper(self, leaves): if not self.right and not self.left: leaves.append(self) else: if self.left: self.left.getLeavesHelper(leaves) if self.right: self.right.getLeavesHelper(leaves) def balance(self): self.nodeSplit(self) def nodeSplit(self, cursor, empty_non_leaf=True): if cursor.location_count > cursor.bucket_size: cursor.split_dimension = cursor.findWidestAxis() # the partition method is the median of all values in the widest dimension cursor.split_value = np.median([cursor.index_locations[i][1][cursor.split_dimension] for i in range(cursor.location_count)]) # if width is 0 (all the values are the same) don't partition if cursor.min_limit[cursor.split_dimension] == cursor.max_limit[cursor.split_dimension]: return # Don't let the split value be the same as the upper value as # can happen due to rounding errors! if cursor.split_value == cursor.max_limit[cursor.split_dimension]: cursor.split_value = cursor.min_limit[cursor.split_dimension] cursor.left = KDTree(bucket_size=cursor.bucket_size, dimensions=cursor.dimensions, parent=cursor) cursor.right = KDTree(bucket_size=cursor.bucket_size, dimensions=cursor.dimensions, parent=cursor) cursor.left.min_boundary = copy.deepcopy(cursor.min_boundary) cursor.left.max_boundary = copy.deepcopy(cursor.max_boundary) cursor.right.min_boundary = copy.deepcopy(cursor.min_boundary) cursor.right.max_boundary = copy.deepcopy(cursor.max_boundary) cursor.left.max_boundary[cursor.split_dimension] = cursor.split_value cursor.right.min_boundary[cursor.split_dimension] = cursor.split_value for index_loc in cursor.index_locations: if index_loc[1][cursor.split_dimension] > cursor.split_value: cursor.right.index_locations.append(index_loc) cursor.right.location_count += 1 cursor.right.extendBounds(index_loc[1]) else: cursor.left.index_locations.append(index_loc) cursor.left.location_count += 1 cursor.left.extendBounds(index_loc[1]) if empty_non_leaf: cursor.index_locations = [] cursor.nodeSplit(cursor.left) cursor.nodeSplit(cursor.right) class KDTreeClustering: def __init__(self, bucket_size=10): self.bucket_size = bucket_size self.is_fitted = False def fit(self, X): # X is an array if hasattr(X, 'shape'): n_samples = X.shape[0] dimensions = X.shape[1] else: n_samples = len(X) dimensions = len(X[0]) self.kdtree = KDTree(bucket_size=self.bucket_size, dimensions=dimensions, parent=None) for i in xrange(n_samples): self.kdtree.add_point((i, X[i])) self.kdtree.nodeSplit(cursor=self.kdtree, empty_non_leaf=True) self.clusters = [leave.index_locations for leave in self.kdtree.getLeaves()] clusters = [cluster.index_locations for cluster in self.kdtree.getLeaves()] results = np.zeros((n_samples,), dtype=int) for i, id_locs in enumerate(clusters): for id, l in id_locs: results[id] = i self.clusters = results self.num_clusters = len(clusters) self.is_fitted = True def get_clusters(self): if self.is_fitted: return self.clusters if __name__ == '__main__': # tree = KDTree(300, 2) import params import geolocate geolocate.initialize(granularity=params.BUCKET_SIZE, write=False, readText=True, reload_init=False, regression=False) locations = [geolocate.locationStr2Float(loc) for loc in params.trainUsers.values()] clusterer = KDTreeClustering(bucket_size=params.BUCKET_SIZE) clusterer.fit(locations) clusters = clusterer.get_clusters()

39.8375

136

0.623784

import copy import numpy as np from scipy._lib.six import xrange class KDTree: def __init__(self, bucket_size, dimensions, parent=None): self.bucket_size = bucket_size self.parent = None self.left = None self.right = None self.split_dimension = None self.split_value = None self.index_locations = [] self.location_count = 0 self.min_limit = [np.Inf] * dimensions self.max_limit = [-np.Inf] * dimensions self.dimensions = dimensions def get_leaf(self, location): if not self.left and not self.right: return self elif location[self.split_dimension] <= self.split_value: return self.left.get_leaf(location) else: return self.right.get_leaf(location) def add_point(self, index_location_tuple): self.index_locations.append(index_location_tuple) self.location_count += 1 self.extendBounds(index_location_tuple[1]) self.min_boundary = copy.deepcopy(self.min_limit) self.max_boundary = copy.deepcopy(self.max_limit) def extendBounds(self, location): if self.min_limit == None: self.min_limit = copy.deepcopy(location) self.max_limit = copy.deepcopy(location) return for i in xrange(self.dimensions): self.min_limit[i] = min(self.min_limit[i], location[i]) self.max_limit[i] = max(self.max_limit[i], location[i]) def findWidestAxis(self): widths = [self.max_limit[i] - self.min_limit[i] for i in range(self.dimensions)] widest_axis = np.argmax(widths) return widest_axis def getNodes(self): nodes = [] self.getNodesHelper(nodes) return nodes def getNodesHelper(self, nodes): nodes.append(self) if self.left: self.left.getNodesHelper(nodes) if self.right: self.right.getNodesHelper(nodes) def getLeaves(self): leaves = [] self.getLeavesHelper(leaves) return leaves def getLeavesHelper(self, leaves): if not self.right and not self.left: leaves.append(self) else: if self.left: self.left.getLeavesHelper(leaves) if self.right: self.right.getLeavesHelper(leaves) def balance(self): self.nodeSplit(self) def nodeSplit(self, cursor, empty_non_leaf=True): if cursor.location_count > cursor.bucket_size: cursor.split_dimension = cursor.findWidestAxis() cursor.split_value = np.median([cursor.index_locations[i][1][cursor.split_dimension] for i in range(cursor.location_count)]) if cursor.min_limit[cursor.split_dimension] == cursor.max_limit[cursor.split_dimension]: return # Don't let the split value be the same as the upper value as if cursor.split_value == cursor.max_limit[cursor.split_dimension]: cursor.split_value = cursor.min_limit[cursor.split_dimension] cursor.left = KDTree(bucket_size=cursor.bucket_size, dimensions=cursor.dimensions, parent=cursor) cursor.right = KDTree(bucket_size=cursor.bucket_size, dimensions=cursor.dimensions, parent=cursor) cursor.left.min_boundary = copy.deepcopy(cursor.min_boundary) cursor.left.max_boundary = copy.deepcopy(cursor.max_boundary) cursor.right.min_boundary = copy.deepcopy(cursor.min_boundary) cursor.right.max_boundary = copy.deepcopy(cursor.max_boundary) cursor.left.max_boundary[cursor.split_dimension] = cursor.split_value cursor.right.min_boundary[cursor.split_dimension] = cursor.split_value for index_loc in cursor.index_locations: if index_loc[1][cursor.split_dimension] > cursor.split_value: cursor.right.index_locations.append(index_loc) cursor.right.location_count += 1 cursor.right.extendBounds(index_loc[1]) else: cursor.left.index_locations.append(index_loc) cursor.left.location_count += 1 cursor.left.extendBounds(index_loc[1]) if empty_non_leaf: cursor.index_locations = [] cursor.nodeSplit(cursor.left) cursor.nodeSplit(cursor.right) class KDTreeClustering: def __init__(self, bucket_size=10): self.bucket_size = bucket_size self.is_fitted = False def fit(self, X): if hasattr(X, 'shape'): n_samples = X.shape[0] dimensions = X.shape[1] else: n_samples = len(X) dimensions = len(X[0]) self.kdtree = KDTree(bucket_size=self.bucket_size, dimensions=dimensions, parent=None) for i in xrange(n_samples): self.kdtree.add_point((i, X[i])) self.kdtree.nodeSplit(cursor=self.kdtree, empty_non_leaf=True) self.clusters = [leave.index_locations for leave in self.kdtree.getLeaves()] clusters = [cluster.index_locations for cluster in self.kdtree.getLeaves()] results = np.zeros((n_samples,), dtype=int) for i, id_locs in enumerate(clusters): for id, l in id_locs: results[id] = i self.clusters = results self.num_clusters = len(clusters) self.is_fitted = True def get_clusters(self): if self.is_fitted: return self.clusters if __name__ == '__main__': import params import geolocate geolocate.initialize(granularity=params.BUCKET_SIZE, write=False, readText=True, reload_init=False, regression=False) locations = [geolocate.locationStr2Float(loc) for loc in params.trainUsers.values()] clusterer = KDTreeClustering(bucket_size=params.BUCKET_SIZE) clusterer.fit(locations) clusters = clusterer.get_clusters()

true

f7188051fe659ac1411c3c3c3d773672836caf24

13,881

py

Python

tensorflow_probability/python/distributions/student_t_process_regression_model_test.py

jakee417/probability-1

ae7117f37ac441bc7a888167ea23e5e620c5bcde

[ "Apache-2.0" ]

3,670

2018-02-14T03:29:40.000Z

2022-03-30T01:19:52.000Z

tensorflow_probability/python/distributions/student_t_process_regression_model_test.py

jakee417/probability-1

ae7117f37ac441bc7a888167ea23e5e620c5bcde

[ "Apache-2.0" ]

1,395

2018-02-24T02:28:49.000Z

2022-03-31T16:12:06.000Z

tensorflow_probability/python/distributions/student_t_process_regression_model_test.py

jakee417/probability-1

ae7117f37ac441bc7a888167ea23e5e620c5bcde

[ "Apache-2.0" ]

1,135

2018-02-14T01:51:10.000Z

2022-03-28T02:24:11.000Z

# Copyright 2021 The TensorFlow Probability Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ # Dependency imports import numpy as np import tensorflow.compat.v2 as tf from tensorflow_probability.python import distributions as tfd from tensorflow_probability.python.internal import test_util from tensorflow_probability.python.math import psd_kernels @test_util.test_all_tf_execution_regimes class StudentTProcessRegressionModelTest(test_util.TestCase): def testInstantiate(self): df = np.float64(1.) # 5x5 grid of index points in R^2 and flatten to 25x2 index_points = np.linspace(-4., 4., 5, dtype=np.float64) index_points = np.stack(np.meshgrid(index_points, index_points), axis=-1) index_points = np.reshape(index_points, [-1, 2]) # ==> shape = [25, 2] # Kernel with batch_shape [2, 4, 1, 3] amplitude = np.array([1., 2.], np.float64).reshape([2, 1, 1, 1]) length_scale = np.array([.1, .2, .3, .4], np.float64).reshape( [1, 4, 1, 1]) observation_noise_variance = np.array( [1e-5, 1e-6, 1e-9], np.float64).reshape([1, 1, 1, 3]) observation_index_points = ( np.random.uniform(-1., 1., (3, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (3, 7)).astype(np.float64) def cholesky_fn(x): return tf.linalg.cholesky( tf.linalg.set_diag(x, tf.linalg.diag_part(x) + 1.)) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) stprm = tfd.StudentTProcessRegressionModel( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance, cholesky_fn=cholesky_fn) batch_shape = [2, 4, 1, 3] event_shape = [25] sample_shape = [7, 2] print(stprm.batch_shape) print(stprm.kernel.batch_shape) print(stprm.kernel.schur_complement.batch_shape) print(stprm.kernel.schur_complement.base_kernel.batch_shape) self.assertIs(cholesky_fn, stprm.cholesky_fn) samples = stprm.sample(sample_shape, seed=test_util.test_seed()) self.assertAllEqual(stprm.batch_shape_tensor(), batch_shape) self.assertAllEqual(stprm.event_shape_tensor(), event_shape) self.assertAllEqual(self.evaluate(samples).shape, sample_shape + batch_shape + event_shape) def testMeanSameAsGPRM(self): df = np.float64(3.) index_points = np.linspace(-4., 4., 5, dtype=np.float64) index_points = np.stack(np.meshgrid(index_points, index_points), axis=-1) index_points = np.reshape(index_points, [-1, 2]) # Kernel with batch_shape [5, 3] amplitude = np.array([1., 2., 3., 4., 5.], np.float64).reshape([5, 1]) length_scale = np.array([.1, .2, .3], np.float64).reshape( [1, 3]) observation_noise_variance = np.array( [1e-5, 1e-6, 1e-9], np.float64).reshape([1, 3]) observation_index_points = ( np.random.uniform(-1., 1., (3, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (3, 7)).astype(np.float64) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) stprm = tfd.StudentTProcessRegressionModel( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance) gprm = tfd.GaussianProcessRegressionModel( kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance) self.assertAllClose(self.evaluate(stprm.mean()), self.evaluate(gprm.mean())) def testLogProbNearGPRM(self): # For large df, the log_prob calculations should be the same. df = np.float64(1e6) index_points = np.linspace(-4., 4., 5, dtype=np.float64) index_points = np.stack(np.meshgrid(index_points, index_points), axis=-1) index_points = np.reshape(index_points, [-1, 2]) # Kernel with batch_shape [5, 3] amplitude = np.array([1., 2., 3., 4., 5.], np.float64).reshape([5, 1]) length_scale = np.array([.1, .2, .3], np.float64).reshape( [1, 3]) observation_noise_variance = np.array( [1e-5, 1e-6, 1e-9], np.float64).reshape([1, 3]) observation_index_points = ( np.random.uniform(-1., 1., (3, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (3, 7)).astype(np.float64) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) stprm = tfd.StudentTProcessRegressionModel( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance) gprm = tfd.GaussianProcessRegressionModel( kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance) x = np.linspace(-3., 3., 25) self.assertAllClose( self.evaluate(stprm.log_prob(x)), self.evaluate(gprm.log_prob(x)), rtol=2e-5) def testMeanVarianceAndCovariancePrecomputed(self): amplitude = np.array([1., 2.], np.float64).reshape([2, 1]) length_scale = np.array([.1, .2, .3], np.float64).reshape([1, 3]) observation_noise_variance = np.array([1e-9], np.float64) df = np.float64(3.) observation_index_points = ( np.random.uniform(-1., 1., (1, 1, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (1, 1, 7)).astype(np.float64) index_points = np.random.uniform(-1., 1., (6, 2)).astype(np.float64) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) stprm = tfd.StudentTProcessRegressionModel( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance, validate_args=True) precomputed_stprm = tfd.StudentTProcessRegressionModel.precompute_regression_model( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance, validate_args=True) self.assertAllClose(self.evaluate(precomputed_stprm.covariance()), self.evaluate(stprm.covariance())) self.assertAllClose(self.evaluate(precomputed_stprm.variance()), self.evaluate(stprm.variance())) self.assertAllClose(self.evaluate(precomputed_stprm.mean()), self.evaluate(stprm.mean())) @test_util.disable_test_for_backend( disable_numpy=True, disable_jax=True, reason='Numpy and JAX have no notion of CompositeTensor/saved_model') def testPrecomputedCompositeTensor(self): amplitude = np.array([1., 2.], np.float64).reshape([2, 1]) length_scale = np.array([.1, .2, .3], np.float64).reshape([1, 3]) observation_noise_variance = np.array([1e-9], np.float64) observation_index_points = ( np.random.uniform(-1., 1., (1, 1, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (1, 1, 7)).astype(np.float64) index_points = np.random.uniform(-1., 1., (6, 2)).astype(np.float64) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) precomputed_stprm = tfd.StudentTProcessRegressionModel.precompute_regression_model( df=3., kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance, validate_args=True) flat = tf.nest.flatten(precomputed_stprm, expand_composites=True) unflat = tf.nest.pack_sequence_as( precomputed_stprm, flat, expand_composites=True) self.assertIsInstance(unflat, tfd.StudentTProcessRegressionModel) # Check that we don't recompute the divisor matrix on flattening / # unflattening. self.assertIs( precomputed_stprm.kernel.schur_complement._precomputed_divisor_matrix_cholesky, # pylint:disable=line-too-long unflat.kernel.schur_complement._precomputed_divisor_matrix_cholesky) # TODO(b/196219597): Enable this test once STPRM works across TF function # boundaries. # index_observations = np.random.uniform(-1., 1., (6,)).astype(np.float64) # @tf.function # def log_prob(d): # return d.log_prob(index_observations) # lp = self.evaluate(precomputed_stprm.log_prob(index_observations)) # self.assertAllClose(lp, self.evaluate(log_prob(precomputed_stprm))) # self.assertAllClose(lp, self.evaluate(log_prob(unflat))) def testEmptyDataMatchesStPPrior(self): df = np.float64(3.5) amp = np.float64(.5) len_scale = np.float64(.2) index_points = np.random.uniform(-1., 1., (10, 1)).astype(np.float64) # k_xx - k_xn @ (k_nn + sigma^2) @ k_nx + sigma^2 mean_fn = lambda x: x[:, 0]**2 kernel = psd_kernels.ExponentiatedQuadratic(amp, len_scale) stp = tfd.StudentTProcess( df, kernel, index_points, mean_fn=mean_fn, validate_args=True) stprm_nones = tfd.StudentTProcessRegressionModel( df, kernel=kernel, index_points=index_points, mean_fn=mean_fn, validate_args=True) stprm_zero_shapes = tfd.StudentTProcessRegressionModel( df, kernel=kernel, index_points=index_points, observation_index_points=tf.ones([0, 1], tf.float64), observations=tf.ones([0], tf.float64), mean_fn=mean_fn, validate_args=True) for stprm in [stprm_nones, stprm_zero_shapes]: self.assertAllClose( self.evaluate(stp.mean()), self.evaluate(stprm.mean())) self.assertAllClose(self.evaluate(stp.covariance()), self.evaluate(stprm.covariance())) self.assertAllClose(self.evaluate(stp.variance()), self.evaluate(stprm.variance())) observations = np.random.uniform(-1., 1., 10).astype(np.float64) self.assertAllClose(self.evaluate(stp.log_prob(observations)), self.evaluate(stprm.log_prob(observations))) def testCopy(self): # 5 random index points in R^2 index_points_1 = np.random.uniform(-4., 4., (5, 2)).astype(np.float32) # 10 random index points in R^2 index_points_2 = np.random.uniform(-4., 4., (10, 2)).astype(np.float32) observation_index_points_1 = ( np.random.uniform(-4., 4., (7, 2)).astype(np.float32)) observation_index_points_2 = ( np.random.uniform(-4., 4., (9, 2)).astype(np.float32)) observations_1 = np.random.uniform(-1., 1., 7).astype(np.float32) observations_2 = np.random.uniform(-1., 1., 9).astype(np.float32) # ==> shape = [6, 25, 2] mean_fn = lambda x: np.array([0.], np.float32) kernel_1 = psd_kernels.ExponentiatedQuadratic() kernel_2 = psd_kernels.ExpSinSquared() stprm1 = tfd.StudentTProcessRegressionModel( df=5., kernel=kernel_1, index_points=index_points_1, observation_index_points=observation_index_points_1, observations=observations_1, mean_fn=mean_fn, validate_args=True) stprm2 = stprm1.copy( kernel=kernel_2, index_points=index_points_2, observation_index_points=observation_index_points_2, observations=observations_2) precomputed_stprm1 = ( tfd.StudentTProcessRegressionModel.precompute_regression_model( df=5., kernel=kernel_1, index_points=index_points_1, observation_index_points=observation_index_points_1, observations=observations_1, mean_fn=mean_fn, validate_args=True)) precomputed_stprm2 = precomputed_stprm1.copy(index_points=index_points_2) self.assertIs(precomputed_stprm1.mean_fn, precomputed_stprm2.mean_fn) self.assertIs(precomputed_stprm1.kernel, precomputed_stprm2.kernel) event_shape_1 = [5] event_shape_2 = [10] self.assertIsInstance(stprm1.kernel.schur_complement.base_kernel, psd_kernels.ExponentiatedQuadratic) self.assertIsInstance(stprm2.kernel.schur_complement.base_kernel, psd_kernels.ExpSinSquared) self.assertAllEqual(self.evaluate(stprm1.batch_shape_tensor()), self.evaluate(stprm2.batch_shape_tensor())) self.assertAllEqual(self.evaluate(stprm1.event_shape_tensor()), event_shape_1) self.assertAllEqual(self.evaluate(stprm2.event_shape_tensor()), event_shape_2) self.assertAllEqual(self.evaluate(stprm1.index_points), index_points_1) self.assertAllEqual(self.evaluate(stprm2.index_points), index_points_2) if __name__ == '__main__': test_util.main()

40.469388

119

0.680931

import numpy as np import tensorflow.compat.v2 as tf from tensorflow_probability.python import distributions as tfd from tensorflow_probability.python.internal import test_util from tensorflow_probability.python.math import psd_kernels @test_util.test_all_tf_execution_regimes class StudentTProcessRegressionModelTest(test_util.TestCase): def testInstantiate(self): df = np.float64(1.) index_points = np.linspace(-4., 4., 5, dtype=np.float64) index_points = np.stack(np.meshgrid(index_points, index_points), axis=-1) index_points = np.reshape(index_points, [-1, 2]) amplitude = np.array([1., 2.], np.float64).reshape([2, 1, 1, 1]) length_scale = np.array([.1, .2, .3, .4], np.float64).reshape( [1, 4, 1, 1]) observation_noise_variance = np.array( [1e-5, 1e-6, 1e-9], np.float64).reshape([1, 1, 1, 3]) observation_index_points = ( np.random.uniform(-1., 1., (3, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (3, 7)).astype(np.float64) def cholesky_fn(x): return tf.linalg.cholesky( tf.linalg.set_diag(x, tf.linalg.diag_part(x) + 1.)) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) stprm = tfd.StudentTProcessRegressionModel( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance, cholesky_fn=cholesky_fn) batch_shape = [2, 4, 1, 3] event_shape = [25] sample_shape = [7, 2] print(stprm.batch_shape) print(stprm.kernel.batch_shape) print(stprm.kernel.schur_complement.batch_shape) print(stprm.kernel.schur_complement.base_kernel.batch_shape) self.assertIs(cholesky_fn, stprm.cholesky_fn) samples = stprm.sample(sample_shape, seed=test_util.test_seed()) self.assertAllEqual(stprm.batch_shape_tensor(), batch_shape) self.assertAllEqual(stprm.event_shape_tensor(), event_shape) self.assertAllEqual(self.evaluate(samples).shape, sample_shape + batch_shape + event_shape) def testMeanSameAsGPRM(self): df = np.float64(3.) index_points = np.linspace(-4., 4., 5, dtype=np.float64) index_points = np.stack(np.meshgrid(index_points, index_points), axis=-1) index_points = np.reshape(index_points, [-1, 2]) amplitude = np.array([1., 2., 3., 4., 5.], np.float64).reshape([5, 1]) length_scale = np.array([.1, .2, .3], np.float64).reshape( [1, 3]) observation_noise_variance = np.array( [1e-5, 1e-6, 1e-9], np.float64).reshape([1, 3]) observation_index_points = ( np.random.uniform(-1., 1., (3, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (3, 7)).astype(np.float64) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) stprm = tfd.StudentTProcessRegressionModel( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance) gprm = tfd.GaussianProcessRegressionModel( kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance) self.assertAllClose(self.evaluate(stprm.mean()), self.evaluate(gprm.mean())) def testLogProbNearGPRM(self): df = np.float64(1e6) index_points = np.linspace(-4., 4., 5, dtype=np.float64) index_points = np.stack(np.meshgrid(index_points, index_points), axis=-1) index_points = np.reshape(index_points, [-1, 2]) amplitude = np.array([1., 2., 3., 4., 5.], np.float64).reshape([5, 1]) length_scale = np.array([.1, .2, .3], np.float64).reshape( [1, 3]) observation_noise_variance = np.array( [1e-5, 1e-6, 1e-9], np.float64).reshape([1, 3]) observation_index_points = ( np.random.uniform(-1., 1., (3, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (3, 7)).astype(np.float64) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) stprm = tfd.StudentTProcessRegressionModel( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance) gprm = tfd.GaussianProcessRegressionModel( kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance) x = np.linspace(-3., 3., 25) self.assertAllClose( self.evaluate(stprm.log_prob(x)), self.evaluate(gprm.log_prob(x)), rtol=2e-5) def testMeanVarianceAndCovariancePrecomputed(self): amplitude = np.array([1., 2.], np.float64).reshape([2, 1]) length_scale = np.array([.1, .2, .3], np.float64).reshape([1, 3]) observation_noise_variance = np.array([1e-9], np.float64) df = np.float64(3.) observation_index_points = ( np.random.uniform(-1., 1., (1, 1, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (1, 1, 7)).astype(np.float64) index_points = np.random.uniform(-1., 1., (6, 2)).astype(np.float64) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) stprm = tfd.StudentTProcessRegressionModel( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance, validate_args=True) precomputed_stprm = tfd.StudentTProcessRegressionModel.precompute_regression_model( df=df, kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance, validate_args=True) self.assertAllClose(self.evaluate(precomputed_stprm.covariance()), self.evaluate(stprm.covariance())) self.assertAllClose(self.evaluate(precomputed_stprm.variance()), self.evaluate(stprm.variance())) self.assertAllClose(self.evaluate(precomputed_stprm.mean()), self.evaluate(stprm.mean())) @test_util.disable_test_for_backend( disable_numpy=True, disable_jax=True, reason='Numpy and JAX have no notion of CompositeTensor/saved_model') def testPrecomputedCompositeTensor(self): amplitude = np.array([1., 2.], np.float64).reshape([2, 1]) length_scale = np.array([.1, .2, .3], np.float64).reshape([1, 3]) observation_noise_variance = np.array([1e-9], np.float64) observation_index_points = ( np.random.uniform(-1., 1., (1, 1, 7, 2)).astype(np.float64)) observations = np.random.uniform(-1., 1., (1, 1, 7)).astype(np.float64) index_points = np.random.uniform(-1., 1., (6, 2)).astype(np.float64) kernel = psd_kernels.ExponentiatedQuadratic(amplitude, length_scale) precomputed_stprm = tfd.StudentTProcessRegressionModel.precompute_regression_model( df=3., kernel=kernel, index_points=index_points, observation_index_points=observation_index_points, observations=observations, observation_noise_variance=observation_noise_variance, validate_args=True) flat = tf.nest.flatten(precomputed_stprm, expand_composites=True) unflat = tf.nest.pack_sequence_as( precomputed_stprm, flat, expand_composites=True) self.assertIsInstance(unflat, tfd.StudentTProcessRegressionModel) # unflattening. self.assertIs( precomputed_stprm.kernel.schur_complement._precomputed_divisor_matrix_cholesky, # pylint:disable=line-too-long unflat.kernel.schur_complement._precomputed_divisor_matrix_cholesky) # TODO(b/196219597): Enable this test once STPRM works across TF function # boundaries. # index_observations = np.random.uniform(-1., 1., (6,)).astype(np.float64) # @tf.function # def log_prob(d): # return d.log_prob(index_observations) # lp = self.evaluate(precomputed_stprm.log_prob(index_observations)) # self.assertAllClose(lp, self.evaluate(log_prob(precomputed_stprm))) # self.assertAllClose(lp, self.evaluate(log_prob(unflat))) def testEmptyDataMatchesStPPrior(self): df = np.float64(3.5) amp = np.float64(.5) len_scale = np.float64(.2) index_points = np.random.uniform(-1., 1., (10, 1)).astype(np.float64) # k_xx - k_xn @ (k_nn + sigma^2) @ k_nx + sigma^2 mean_fn = lambda x: x[:, 0]**2 kernel = psd_kernels.ExponentiatedQuadratic(amp, len_scale) stp = tfd.StudentTProcess( df, kernel, index_points, mean_fn=mean_fn, validate_args=True) stprm_nones = tfd.StudentTProcessRegressionModel( df, kernel=kernel, index_points=index_points, mean_fn=mean_fn, validate_args=True) stprm_zero_shapes = tfd.StudentTProcessRegressionModel( df, kernel=kernel, index_points=index_points, observation_index_points=tf.ones([0, 1], tf.float64), observations=tf.ones([0], tf.float64), mean_fn=mean_fn, validate_args=True) for stprm in [stprm_nones, stprm_zero_shapes]: self.assertAllClose( self.evaluate(stp.mean()), self.evaluate(stprm.mean())) self.assertAllClose(self.evaluate(stp.covariance()), self.evaluate(stprm.covariance())) self.assertAllClose(self.evaluate(stp.variance()), self.evaluate(stprm.variance())) observations = np.random.uniform(-1., 1., 10).astype(np.float64) self.assertAllClose(self.evaluate(stp.log_prob(observations)), self.evaluate(stprm.log_prob(observations))) def testCopy(self): # 5 random index points in R^2 index_points_1 = np.random.uniform(-4., 4., (5, 2)).astype(np.float32) # 10 random index points in R^2 index_points_2 = np.random.uniform(-4., 4., (10, 2)).astype(np.float32) observation_index_points_1 = ( np.random.uniform(-4., 4., (7, 2)).astype(np.float32)) observation_index_points_2 = ( np.random.uniform(-4., 4., (9, 2)).astype(np.float32)) observations_1 = np.random.uniform(-1., 1., 7).astype(np.float32) observations_2 = np.random.uniform(-1., 1., 9).astype(np.float32) # ==> shape = [6, 25, 2] mean_fn = lambda x: np.array([0.], np.float32) kernel_1 = psd_kernels.ExponentiatedQuadratic() kernel_2 = psd_kernels.ExpSinSquared() stprm1 = tfd.StudentTProcessRegressionModel( df=5., kernel=kernel_1, index_points=index_points_1, observation_index_points=observation_index_points_1, observations=observations_1, mean_fn=mean_fn, validate_args=True) stprm2 = stprm1.copy( kernel=kernel_2, index_points=index_points_2, observation_index_points=observation_index_points_2, observations=observations_2) precomputed_stprm1 = ( tfd.StudentTProcessRegressionModel.precompute_regression_model( df=5., kernel=kernel_1, index_points=index_points_1, observation_index_points=observation_index_points_1, observations=observations_1, mean_fn=mean_fn, validate_args=True)) precomputed_stprm2 = precomputed_stprm1.copy(index_points=index_points_2) self.assertIs(precomputed_stprm1.mean_fn, precomputed_stprm2.mean_fn) self.assertIs(precomputed_stprm1.kernel, precomputed_stprm2.kernel) event_shape_1 = [5] event_shape_2 = [10] self.assertIsInstance(stprm1.kernel.schur_complement.base_kernel, psd_kernels.ExponentiatedQuadratic) self.assertIsInstance(stprm2.kernel.schur_complement.base_kernel, psd_kernels.ExpSinSquared) self.assertAllEqual(self.evaluate(stprm1.batch_shape_tensor()), self.evaluate(stprm2.batch_shape_tensor())) self.assertAllEqual(self.evaluate(stprm1.event_shape_tensor()), event_shape_1) self.assertAllEqual(self.evaluate(stprm2.event_shape_tensor()), event_shape_2) self.assertAllEqual(self.evaluate(stprm1.index_points), index_points_1) self.assertAllEqual(self.evaluate(stprm2.index_points), index_points_2) if __name__ == '__main__': test_util.main()

true

f718815b2922106732719f8c9367ef276f71008f

24,159

py

Python

contents/tts/content/TensorflowTTS/tensorflow_tts/utils/group_conv.py

PIN-devel/inside-kids

554e4a0a5654c9a0f5237b904bb2ca6db88a55cb

[ "MIT" ]

2

2020-07-03T05:47:47.000Z

2020-07-03T19:59:09.000Z

contents/tts/content/TensorflowTTS/tensorflow_tts/utils/group_conv.py

PIN-devel/inside-kids

554e4a0a5654c9a0f5237b904bb2ca6db88a55cb

[ "MIT" ]

1

2021-02-26T04:10:19.000Z

contents/tts/content/TensorflowTTS/tensorflow_tts/utils/group_conv.py

PIN-devel/inside-kids

554e4a0a5654c9a0f5237b904bb2ca6db88a55cb

[ "MIT" ]

4

2021-02-23T13:05:59.000Z

2021-04-23T05:15:32.000Z

# -*- coding: utf-8 -*- # This code is copy from https://github.com/tensorflow/tensorflow/pull/36773. """Group Convolution Modules.""" from tensorflow.python.framework import tensor_shape from tensorflow.python.keras import activations from tensorflow.python.keras import constraints from tensorflow.python.keras import initializers from tensorflow.python.keras import regularizers from tensorflow.python.keras.engine.base_layer import Layer from tensorflow.python.keras.engine.input_spec import InputSpec from tensorflow.python.keras.utils import conv_utils from tensorflow.python.ops import array_ops from tensorflow.python.ops import nn from tensorflow.python.ops import nn_ops from tensorflow.python.keras.layers import Conv1D from tensorflow.python.keras.layers import SeparableConv1D class Convolution(object): """Helper class for convolution. Note that this class assumes that shapes of input and filter passed to __call__ are compatible with input_shape and filter_shape passed to the constructor. Arguments input_shape: static shape of input. i.e. input.get_shape(). filter_shape: static shape of the filter. i.e. filter.get_shape(). padding: see convolution. strides: see convolution. dilation_rate: see convolution. name: see convolution. data_format: see convolution. """ def __init__( self, input_shape, filter_shape, padding, strides=None, dilation_rate=None, name=None, data_format=None, ): """Helper function for convolution.""" num_total_dims = filter_shape.ndims if num_total_dims is None: num_total_dims = input_shape.ndims if num_total_dims is None: raise ValueError("rank of input or filter must be known") num_spatial_dims = num_total_dims - 2 try: input_shape.with_rank(num_spatial_dims + 2) except ValueError: raise ValueError("input tensor must have rank %d" % (num_spatial_dims + 2)) try: filter_shape.with_rank(num_spatial_dims + 2) except ValueError: raise ValueError("filter tensor must have rank %d" % (num_spatial_dims + 2)) if data_format is None or not data_format.startswith("NC"): input_channels_dim = tensor_shape.dimension_at_index( input_shape, num_spatial_dims + 1 ) spatial_dims = range(1, num_spatial_dims + 1) else: input_channels_dim = tensor_shape.dimension_at_index(input_shape, 1) spatial_dims = range(2, num_spatial_dims + 2) filter_dim = tensor_shape.dimension_at_index(filter_shape, num_spatial_dims) if not (input_channels_dim % filter_dim).is_compatible_with(0): raise ValueError( "number of input channels is not divisible by corresponding " "dimension of filter, {} % {} != 0".format( input_channels_dim, filter_dim ) ) strides, dilation_rate = nn_ops._get_strides_and_dilation_rate( num_spatial_dims, strides, dilation_rate ) self.input_shape = input_shape self.filter_shape = filter_shape self.data_format = data_format self.strides = strides self.padding = padding self.name = name self.dilation_rate = dilation_rate self.conv_op = nn_ops._WithSpaceToBatch( input_shape, dilation_rate=dilation_rate, padding=padding, build_op=self._build_op, filter_shape=filter_shape, spatial_dims=spatial_dims, data_format=data_format, ) def _build_op(self, _, padding): return nn_ops._NonAtrousConvolution( self.input_shape, filter_shape=self.filter_shape, padding=padding, data_format=self.data_format, strides=self.strides, name=self.name, ) def __call__(self, inp, filter): return self.conv_op(inp, filter) class Conv(Layer): """Abstract N-D convolution layer (private, used as implementation base). This layer creates a convolution kernel that is convolved (actually cross-correlated) with the layer input to produce a tensor of outputs. If `use_bias` is True (and a `bias_initializer` is provided), a bias vector is created and added to the outputs. Finally, if `activation` is not `None`, it is applied to the outputs as well. Note: layer attributes cannot be modified after the layer has been called once (except the `trainable` attribute). Arguments: rank: An integer, the rank of the convolution, e.g. "2" for 2D convolution. filters: Integer, the dimensionality of the output space (i.e. the number of filters in the convolution). kernel_size: An integer or tuple/list of n integers, specifying the length of the convolution window. strides: An integer or tuple/list of n integers, specifying the stride length of the convolution. Specifying any stride value != 1 is incompatible with specifying any `dilation_rate` value != 1. padding: One of `"valid"`, `"same"`, or `"causal"` (case-insensitive). data_format: A string, one of `channels_last` (default) or `channels_first`. The ordering of the dimensions in the inputs. `channels_last` corresponds to inputs with shape `(batch_size, ..., channels)` while `channels_first` corresponds to inputs with shape `(batch_size, channels, ...)`. dilation_rate: An integer or tuple/list of n integers, specifying the dilation rate to use for dilated convolution. Currently, specifying any `dilation_rate` value != 1 is incompatible with specifying any `strides` value != 1. groups: Integer, the number of channel groups controlling the connections between inputs and outputs. Input channels and `filters` must both be divisible by `groups`. For example, - At `groups=1`, all inputs are convolved to all outputs. - At `groups=2`, the operation becomes equivalent to having two convolutional layers side by side, each seeing half the input channels, and producing half the output channels, and both subsequently concatenated. - At `groups=input_channels`, each input channel is convolved with its own set of filters, of size `input_channels / filters` activation: Activation function to use. If you don't specify anything, no activation is applied. use_bias: Boolean, whether the layer uses a bias. kernel_initializer: An initializer for the convolution kernel. bias_initializer: An initializer for the bias vector. If None, the default initializer will be used. kernel_regularizer: Optional regularizer for the convolution kernel. bias_regularizer: Optional regularizer for the bias vector. activity_regularizer: Optional regularizer function for the output. kernel_constraint: Optional projection function to be applied to the kernel after being updated by an `Optimizer` (e.g. used to implement norm constraints or value constraints for layer weights). The function must take as input the unprojected variable and must return the projected variable (which must have the same shape). Constraints are not safe to use when doing asynchronous distributed training. bias_constraint: Optional projection function to be applied to the bias after being updated by an `Optimizer`. trainable: Boolean, if `True` the weights of this layer will be marked as trainable (and listed in `layer.trainable_weights`). name: A string, the name of the layer. """ def __init__( self, rank, filters, kernel_size, strides=1, padding="valid", data_format=None, dilation_rate=1, groups=1, activation=None, use_bias=True, kernel_initializer="glorot_uniform", bias_initializer="zeros", kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, trainable=True, name=None, **kwargs ): super(Conv, self).__init__( trainable=trainable, name=name, activity_regularizer=regularizers.get(activity_regularizer), **kwargs ) self.rank = rank if filters is not None and not isinstance(filters, int): filters = int(filters) self.filters = filters self.groups = groups or 1 if filters is not None and filters % self.groups != 0: raise ValueError( "The number of filters must be evenly divisible by the number of " "groups. Received: groups={}, filters={}".format(groups, filters) ) self.kernel_size = conv_utils.normalize_tuple(kernel_size, rank, "kernel_size") if not all(self.kernel_size): raise ValueError( "The argument `kernel_size` cannot contain 0(s). " "Received: %s" % (kernel_size,) ) self.strides = conv_utils.normalize_tuple(strides, rank, "strides") self.padding = conv_utils.normalize_padding(padding) if self.padding == "causal" and not isinstance(self, (Conv1D, SeparableConv1D)): raise ValueError( "Causal padding is only supported for `Conv1D`" "and ``SeparableConv1D`." ) self.data_format = conv_utils.normalize_data_format(data_format) self.dilation_rate = conv_utils.normalize_tuple( dilation_rate, rank, "dilation_rate" ) self.activation = activations.get(activation) self.use_bias = use_bias self.kernel_initializer = initializers.get(kernel_initializer) self.bias_initializer = initializers.get(bias_initializer) self.kernel_regularizer = regularizers.get(kernel_regularizer) self.bias_regularizer = regularizers.get(bias_regularizer) self.kernel_constraint = constraints.get(kernel_constraint) self.bias_constraint = constraints.get(bias_constraint) self.input_spec = InputSpec(ndim=self.rank + 2) def build(self, input_shape): input_shape = tensor_shape.TensorShape(input_shape) input_channel = self._get_input_channel(input_shape) if input_channel % self.groups != 0: raise ValueError( "The number of input channels must be evenly divisible by the number " "of groups. Received groups={}, but the input has {} channels " "(full input shape is {}).".format( self.groups, input_channel, input_shape ) ) kernel_shape = self.kernel_size + (input_channel // self.groups, self.filters) self.kernel = self.add_weight( name="kernel", shape=kernel_shape, initializer=self.kernel_initializer, regularizer=self.kernel_regularizer, constraint=self.kernel_constraint, trainable=True, dtype=self.dtype, ) if self.use_bias: self.bias = self.add_weight( name="bias", shape=(self.filters,), initializer=self.bias_initializer, regularizer=self.bias_regularizer, constraint=self.bias_constraint, trainable=True, dtype=self.dtype, ) else: self.bias = None channel_axis = self._get_channel_axis() self.input_spec = InputSpec( ndim=self.rank + 2, axes={channel_axis: input_channel} ) self._build_conv_op_input_shape = input_shape self._build_input_channel = input_channel self._padding_op = self._get_padding_op() self._conv_op_data_format = conv_utils.convert_data_format( self.data_format, self.rank + 2 ) self._convolution_op = Convolution( input_shape, filter_shape=self.kernel.shape, dilation_rate=self.dilation_rate, strides=self.strides, padding=self._padding_op, data_format=self._conv_op_data_format, ) self.built = True def call(self, inputs): if self._recreate_conv_op(inputs): self._convolution_op = Convolution( inputs.get_shape(), filter_shape=self.kernel.shape, dilation_rate=self.dilation_rate, strides=self.strides, padding=self._padding_op, data_format=self._conv_op_data_format, ) self._build_conv_op_input_shape = inputs.get_shape() # Apply causal padding to inputs for Conv1D. if self.padding == "causal" and self.__class__.__name__ == "Conv1D": inputs = array_ops.pad(inputs, self._compute_causal_padding()) outputs = self._convolution_op(inputs, self.kernel) if self.use_bias: if self.data_format == "channels_first": if self.rank == 1: # nn.bias_add does not accept a 1D input tensor. bias = array_ops.reshape(self.bias, (1, self.filters, 1)) outputs += bias else: outputs = nn.bias_add(outputs, self.bias, data_format="NCHW") else: outputs = nn.bias_add(outputs, self.bias, data_format="NHWC") if self.activation is not None: return self.activation(outputs) return outputs def compute_output_shape(self, input_shape): input_shape = tensor_shape.TensorShape(input_shape).as_list() if self.data_format == "channels_last": space = input_shape[1:-1] new_space = [] for i in range(len(space)): new_dim = conv_utils.conv_output_length( space[i], self.kernel_size[i], padding=self.padding, stride=self.strides[i], dilation=self.dilation_rate[i], ) new_space.append(new_dim) return tensor_shape.TensorShape( [input_shape[0]] + new_space + [self.filters] ) else: space = input_shape[2:] new_space = [] for i in range(len(space)): new_dim = conv_utils.conv_output_length( space[i], self.kernel_size[i], padding=self.padding, stride=self.strides[i], dilation=self.dilation_rate[i], ) new_space.append(new_dim) return tensor_shape.TensorShape([input_shape[0], self.filters] + new_space) def get_config(self): config = { "filters": self.filters, "kernel_size": self.kernel_size, "strides": self.strides, "padding": self.padding, "data_format": self.data_format, "dilation_rate": self.dilation_rate, "groups": self.groups, "activation": activations.serialize(self.activation), "use_bias": self.use_bias, "kernel_initializer": initializers.serialize(self.kernel_initializer), "bias_initializer": initializers.serialize(self.bias_initializer), "kernel_regularizer": regularizers.serialize(self.kernel_regularizer), "bias_regularizer": regularizers.serialize(self.bias_regularizer), "activity_regularizer": regularizers.serialize(self.activity_regularizer), "kernel_constraint": constraints.serialize(self.kernel_constraint), "bias_constraint": constraints.serialize(self.bias_constraint), } base_config = super(Conv, self).get_config() return dict(list(base_config.items()) + list(config.items())) def _compute_causal_padding(self): """Calculates padding for 'causal' option for 1-d conv layers.""" left_pad = self.dilation_rate[0] * (self.kernel_size[0] - 1) if self.data_format == "channels_last": causal_padding = [[0, 0], [left_pad, 0], [0, 0]] else: causal_padding = [[0, 0], [0, 0], [left_pad, 0]] return causal_padding def _get_channel_axis(self): if self.data_format == "channels_first": return 1 else: return -1 def _get_input_channel(self, input_shape): channel_axis = self._get_channel_axis() if input_shape.dims[channel_axis].value is None: raise ValueError( "The channel dimension of the inputs " "should be defined. Found `None`." ) return int(input_shape[channel_axis]) def _get_padding_op(self): if self.padding == "causal": op_padding = "valid" else: op_padding = self.padding if not isinstance(op_padding, (list, tuple)): op_padding = op_padding.upper() return op_padding def _recreate_conv_op(self, inputs): """Recreate conv_op if necessary. Check if the input_shape in call() is different from that in build(). For the values that are not None, if they are different, recreate the _convolution_op to avoid the stateful behavior. Args: inputs: The input data to call() method. Returns: `True` or `False` to indicate whether to recreate the conv_op. """ call_input_shape = inputs.get_shape() for axis in range(1, len(call_input_shape)): if ( call_input_shape[axis] is not None and self._build_conv_op_input_shape[axis] is not None and call_input_shape[axis] != self._build_conv_op_input_shape[axis] ): return True return False class GroupConv1D(Conv): """1D convolution layer (e.g. temporal convolution). This layer creates a convolution kernel that is convolved with the layer input over a single spatial (or temporal) dimension to produce a tensor of outputs. If `use_bias` is True, a bias vector is created and added to the outputs. Finally, if `activation` is not `None`, it is applied to the outputs as well. When using this layer as the first layer in a model, provide an `input_shape` argument (tuple of integers or `None`, e.g. `(10, 128)` for sequences of 10 vectors of 128-dimensional vectors, or `(None, 128)` for variable-length sequences of 128-dimensional vectors. Examples: >>> # The inputs are 128-length vectors with 10 timesteps, and the batch size >>> # is 4. >>> input_shape = (4, 10, 128) >>> x = tf.random.normal(input_shape) >>> y = tf.keras.layers.Conv1D( ... 32, 3, activation='relu',input_shape=input_shape)(x) >>> print(y.shape) (4, 8, 32) Arguments: filters: Integer, the dimensionality of the output space (i.e. the number of output filters in the convolution). kernel_size: An integer or tuple/list of a single integer, specifying the length of the 1D convolution window. strides: An integer or tuple/list of a single integer, specifying the stride length of the convolution. Specifying any stride value != 1 is incompatible with specifying any `dilation_rate` value != 1. padding: One of `"valid"`, `"causal"` or `"same"` (case-insensitive). `"causal"` results in causal (dilated) convolutions, e.g. `output[t]` does not depend on `input[t+1:]`. Useful when modeling temporal data where the model should not violate the temporal order. See [WaveNet: A Generative Model for Raw Audio, section 2.1](https://arxiv.org/abs/1609.03499). data_format: A string, one of `channels_last` (default) or `channels_first`. groups: Integer, the number of channel groups controlling the connections between inputs and outputs. Input channels and `filters` must both be divisible by `groups`. For example, - At `groups=1`, all inputs are convolved to all outputs. - At `groups=2`, the operation becomes equivalent to having two convolutional layers side by side, each seeing half the input channels, and producing half the output channels, and both subsequently concatenated. - At `groups=input_channels`, each input channel is convolved with its own set of filters, of size `input_channels / filters` dilation_rate: an integer or tuple/list of a single integer, specifying the dilation rate to use for dilated convolution. Currently, specifying any `dilation_rate` value != 1 is incompatible with specifying any `strides` value != 1. activation: Activation function to use. If you don't specify anything, no activation is applied ( see `keras.activations`). use_bias: Boolean, whether the layer uses a bias vector. kernel_initializer: Initializer for the `kernel` weights matrix ( see `keras.initializers`). bias_initializer: Initializer for the bias vector ( see `keras.initializers`). kernel_regularizer: Regularizer function applied to the `kernel` weights matrix (see `keras.regularizers`). bias_regularizer: Regularizer function applied to the bias vector ( see `keras.regularizers`). activity_regularizer: Regularizer function applied to the output of the layer (its "activation") ( see `keras.regularizers`). kernel_constraint: Constraint function applied to the kernel matrix ( see `keras.constraints`). bias_constraint: Constraint function applied to the bias vector ( see `keras.constraints`). Input shape: 3D tensor with shape: `(batch_size, steps, input_dim)` Output shape: 3D tensor with shape: `(batch_size, new_steps, filters)` `steps` value might have changed due to padding or strides. Returns: A tensor of rank 3 representing `activation(conv1d(inputs, kernel) + bias)`. Raises: ValueError: when both `strides` > 1 and `dilation_rate` > 1. """ def __init__( self, filters, kernel_size, strides=1, padding="valid", data_format="channels_last", dilation_rate=1, groups=1, activation=None, use_bias=True, kernel_initializer="glorot_uniform", bias_initializer="zeros", kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, **kwargs ): super().__init__( rank=1, filters=filters, kernel_size=kernel_size, strides=strides, padding=padding, data_format=data_format, dilation_rate=dilation_rate, groups=groups, activation=activations.get(activation), use_bias=use_bias, kernel_initializer=initializers.get(kernel_initializer), bias_initializer=initializers.get(bias_initializer), kernel_regularizer=regularizers.get(kernel_regularizer), bias_regularizer=regularizers.get(bias_regularizer), activity_regularizer=regularizers.get(activity_regularizer), kernel_constraint=constraints.get(kernel_constraint), bias_constraint=constraints.get(bias_constraint), **kwargs )

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from tensorflow.python.framework import tensor_shape from tensorflow.python.keras import activations from tensorflow.python.keras import constraints from tensorflow.python.keras import initializers from tensorflow.python.keras import regularizers from tensorflow.python.keras.engine.base_layer import Layer from tensorflow.python.keras.engine.input_spec import InputSpec from tensorflow.python.keras.utils import conv_utils from tensorflow.python.ops import array_ops from tensorflow.python.ops import nn from tensorflow.python.ops import nn_ops from tensorflow.python.keras.layers import Conv1D from tensorflow.python.keras.layers import SeparableConv1D class Convolution(object): def __init__( self, input_shape, filter_shape, padding, strides=None, dilation_rate=None, name=None, data_format=None, ): num_total_dims = filter_shape.ndims if num_total_dims is None: num_total_dims = input_shape.ndims if num_total_dims is None: raise ValueError("rank of input or filter must be known") num_spatial_dims = num_total_dims - 2 try: input_shape.with_rank(num_spatial_dims + 2) except ValueError: raise ValueError("input tensor must have rank %d" % (num_spatial_dims + 2)) try: filter_shape.with_rank(num_spatial_dims + 2) except ValueError: raise ValueError("filter tensor must have rank %d" % (num_spatial_dims + 2)) if data_format is None or not data_format.startswith("NC"): input_channels_dim = tensor_shape.dimension_at_index( input_shape, num_spatial_dims + 1 ) spatial_dims = range(1, num_spatial_dims + 1) else: input_channels_dim = tensor_shape.dimension_at_index(input_shape, 1) spatial_dims = range(2, num_spatial_dims + 2) filter_dim = tensor_shape.dimension_at_index(filter_shape, num_spatial_dims) if not (input_channels_dim % filter_dim).is_compatible_with(0): raise ValueError( "number of input channels is not divisible by corresponding " "dimension of filter, {} % {} != 0".format( input_channels_dim, filter_dim ) ) strides, dilation_rate = nn_ops._get_strides_and_dilation_rate( num_spatial_dims, strides, dilation_rate ) self.input_shape = input_shape self.filter_shape = filter_shape self.data_format = data_format self.strides = strides self.padding = padding self.name = name self.dilation_rate = dilation_rate self.conv_op = nn_ops._WithSpaceToBatch( input_shape, dilation_rate=dilation_rate, padding=padding, build_op=self._build_op, filter_shape=filter_shape, spatial_dims=spatial_dims, data_format=data_format, ) def _build_op(self, _, padding): return nn_ops._NonAtrousConvolution( self.input_shape, filter_shape=self.filter_shape, padding=padding, data_format=self.data_format, strides=self.strides, name=self.name, ) def __call__(self, inp, filter): return self.conv_op(inp, filter) class Conv(Layer): def __init__( self, rank, filters, kernel_size, strides=1, padding="valid", data_format=None, dilation_rate=1, groups=1, activation=None, use_bias=True, kernel_initializer="glorot_uniform", bias_initializer="zeros", kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, trainable=True, name=None, **kwargs ): super(Conv, self).__init__( trainable=trainable, name=name, activity_regularizer=regularizers.get(activity_regularizer), **kwargs ) self.rank = rank if filters is not None and not isinstance(filters, int): filters = int(filters) self.filters = filters self.groups = groups or 1 if filters is not None and filters % self.groups != 0: raise ValueError( "The number of filters must be evenly divisible by the number of " "groups. Received: groups={}, filters={}".format(groups, filters) ) self.kernel_size = conv_utils.normalize_tuple(kernel_size, rank, "kernel_size") if not all(self.kernel_size): raise ValueError( "The argument `kernel_size` cannot contain 0(s). " "Received: %s" % (kernel_size,) ) self.strides = conv_utils.normalize_tuple(strides, rank, "strides") self.padding = conv_utils.normalize_padding(padding) if self.padding == "causal" and not isinstance(self, (Conv1D, SeparableConv1D)): raise ValueError( "Causal padding is only supported for `Conv1D`" "and ``SeparableConv1D`." ) self.data_format = conv_utils.normalize_data_format(data_format) self.dilation_rate = conv_utils.normalize_tuple( dilation_rate, rank, "dilation_rate" ) self.activation = activations.get(activation) self.use_bias = use_bias self.kernel_initializer = initializers.get(kernel_initializer) self.bias_initializer = initializers.get(bias_initializer) self.kernel_regularizer = regularizers.get(kernel_regularizer) self.bias_regularizer = regularizers.get(bias_regularizer) self.kernel_constraint = constraints.get(kernel_constraint) self.bias_constraint = constraints.get(bias_constraint) self.input_spec = InputSpec(ndim=self.rank + 2) def build(self, input_shape): input_shape = tensor_shape.TensorShape(input_shape) input_channel = self._get_input_channel(input_shape) if input_channel % self.groups != 0: raise ValueError( "The number of input channels must be evenly divisible by the number " "of groups. Received groups={}, but the input has {} channels " "(full input shape is {}).".format( self.groups, input_channel, input_shape ) ) kernel_shape = self.kernel_size + (input_channel // self.groups, self.filters) self.kernel = self.add_weight( name="kernel", shape=kernel_shape, initializer=self.kernel_initializer, regularizer=self.kernel_regularizer, constraint=self.kernel_constraint, trainable=True, dtype=self.dtype, ) if self.use_bias: self.bias = self.add_weight( name="bias", shape=(self.filters,), initializer=self.bias_initializer, regularizer=self.bias_regularizer, constraint=self.bias_constraint, trainable=True, dtype=self.dtype, ) else: self.bias = None channel_axis = self._get_channel_axis() self.input_spec = InputSpec( ndim=self.rank + 2, axes={channel_axis: input_channel} ) self._build_conv_op_input_shape = input_shape self._build_input_channel = input_channel self._padding_op = self._get_padding_op() self._conv_op_data_format = conv_utils.convert_data_format( self.data_format, self.rank + 2 ) self._convolution_op = Convolution( input_shape, filter_shape=self.kernel.shape, dilation_rate=self.dilation_rate, strides=self.strides, padding=self._padding_op, data_format=self._conv_op_data_format, ) self.built = True def call(self, inputs): if self._recreate_conv_op(inputs): self._convolution_op = Convolution( inputs.get_shape(), filter_shape=self.kernel.shape, dilation_rate=self.dilation_rate, strides=self.strides, padding=self._padding_op, data_format=self._conv_op_data_format, ) self._build_conv_op_input_shape = inputs.get_shape() if self.padding == "causal" and self.__class__.__name__ == "Conv1D": inputs = array_ops.pad(inputs, self._compute_causal_padding()) outputs = self._convolution_op(inputs, self.kernel) if self.use_bias: if self.data_format == "channels_first": if self.rank == 1: bias = array_ops.reshape(self.bias, (1, self.filters, 1)) outputs += bias else: outputs = nn.bias_add(outputs, self.bias, data_format="NCHW") else: outputs = nn.bias_add(outputs, self.bias, data_format="NHWC") if self.activation is not None: return self.activation(outputs) return outputs def compute_output_shape(self, input_shape): input_shape = tensor_shape.TensorShape(input_shape).as_list() if self.data_format == "channels_last": space = input_shape[1:-1] new_space = [] for i in range(len(space)): new_dim = conv_utils.conv_output_length( space[i], self.kernel_size[i], padding=self.padding, stride=self.strides[i], dilation=self.dilation_rate[i], ) new_space.append(new_dim) return tensor_shape.TensorShape( [input_shape[0]] + new_space + [self.filters] ) else: space = input_shape[2:] new_space = [] for i in range(len(space)): new_dim = conv_utils.conv_output_length( space[i], self.kernel_size[i], padding=self.padding, stride=self.strides[i], dilation=self.dilation_rate[i], ) new_space.append(new_dim) return tensor_shape.TensorShape([input_shape[0], self.filters] + new_space) def get_config(self): config = { "filters": self.filters, "kernel_size": self.kernel_size, "strides": self.strides, "padding": self.padding, "data_format": self.data_format, "dilation_rate": self.dilation_rate, "groups": self.groups, "activation": activations.serialize(self.activation), "use_bias": self.use_bias, "kernel_initializer": initializers.serialize(self.kernel_initializer), "bias_initializer": initializers.serialize(self.bias_initializer), "kernel_regularizer": regularizers.serialize(self.kernel_regularizer), "bias_regularizer": regularizers.serialize(self.bias_regularizer), "activity_regularizer": regularizers.serialize(self.activity_regularizer), "kernel_constraint": constraints.serialize(self.kernel_constraint), "bias_constraint": constraints.serialize(self.bias_constraint), } base_config = super(Conv, self).get_config() return dict(list(base_config.items()) + list(config.items())) def _compute_causal_padding(self): left_pad = self.dilation_rate[0] * (self.kernel_size[0] - 1) if self.data_format == "channels_last": causal_padding = [[0, 0], [left_pad, 0], [0, 0]] else: causal_padding = [[0, 0], [0, 0], [left_pad, 0]] return causal_padding def _get_channel_axis(self): if self.data_format == "channels_first": return 1 else: return -1 def _get_input_channel(self, input_shape): channel_axis = self._get_channel_axis() if input_shape.dims[channel_axis].value is None: raise ValueError( "The channel dimension of the inputs " "should be defined. Found `None`." ) return int(input_shape[channel_axis]) def _get_padding_op(self): if self.padding == "causal": op_padding = "valid" else: op_padding = self.padding if not isinstance(op_padding, (list, tuple)): op_padding = op_padding.upper() return op_padding def _recreate_conv_op(self, inputs): call_input_shape = inputs.get_shape() for axis in range(1, len(call_input_shape)): if ( call_input_shape[axis] is not None and self._build_conv_op_input_shape[axis] is not None and call_input_shape[axis] != self._build_conv_op_input_shape[axis] ): return True return False class GroupConv1D(Conv): def __init__( self, filters, kernel_size, strides=1, padding="valid", data_format="channels_last", dilation_rate=1, groups=1, activation=None, use_bias=True, kernel_initializer="glorot_uniform", bias_initializer="zeros", kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, **kwargs ): super().__init__( rank=1, filters=filters, kernel_size=kernel_size, strides=strides, padding=padding, data_format=data_format, dilation_rate=dilation_rate, groups=groups, activation=activations.get(activation), use_bias=use_bias, kernel_initializer=initializers.get(kernel_initializer), bias_initializer=initializers.get(bias_initializer), kernel_regularizer=regularizers.get(kernel_regularizer), bias_regularizer=regularizers.get(bias_regularizer), activity_regularizer=regularizers.get(activity_regularizer), kernel_constraint=constraints.get(kernel_constraint), bias_constraint=constraints.get(bias_constraint), **kwargs )

true

f71882478dfe74c0a4592f297f1ac49bf7457bb9

531

py

Python

tests/test_stuff.py

alexanderrichards/ProductionSystem

ea9b80f13d76be293c8e2a3387d4cb3abc56e314

[ "MIT" ]

null

tests/test_stuff.py

alexanderrichards/ProductionSystem

ea9b80f13d76be293c8e2a3387d4cb3abc56e314

[ "MIT" ]

43

2018-04-23T08:39:17.000Z

2019-11-26T12:17:14.000Z

tests/test_stuff.py

alexanderrichards/ProductionSystem

ea9b80f13d76be293c8e2a3387d4cb3abc56e314

[ "MIT" ]

1

2019-02-05T04:17:07.000Z

"""Test Stuff.""" from unittest import TestCase import pkg_resources from productionsystem.config import ConfigSystem # def setup_module(module): # """ setup any state specific to the execution of the given module.""" # config_instance = ConfigSystem.setup(None) # pylint: disable=no-member # config_instance.entry_point_map = pkg_resources.get_entry_map('productionsystem') # return config_instance class TestStuff(TestCase): """Test case.""" def test_bob(self): """test bob.""" pass

26.55

87

0.708098

from unittest import TestCase import pkg_resources from productionsystem.config import ConfigSystem se): def test_bob(self): pass

true

f718825de43905bfc5be6bacd294d07ee49fda2d

10,286

py

Python

src/python/zquantum/core/utils.py

FredericSauv/z-quantum-core

f285b292159fe272d7401ba05baac7bab28475d7

[ "Apache-2.0" ]

null

src/python/zquantum/core/utils.py

FredericSauv/z-quantum-core

f285b292159fe272d7401ba05baac7bab28475d7

[ "Apache-2.0" ]

null

src/python/zquantum/core/utils.py

FredericSauv/z-quantum-core

f285b292159fe272d7401ba05baac7bab28475d7

[ "Apache-2.0" ]

null

"""General-purpose utilities.""" import numpy as np from scipy.linalg import expm import random import math import operator import sys import json import openfermion from openfermion import hermitian_conjugated from openfermion.ops import SymbolicOperator from networkx.readwrite import json_graph import lea import collections import scipy from typing import List import importlib SCHEMA_VERSION = 'zapata-v1' RNDSEED = 12345 def convert_dict_to_array(dictionary: dict) -> np.ndarray: """Convert a dictionary to a numpy array. Args: dictionary (dict): the dict containing the data Returns: array (numpy.array): a numpy array """ array = np.array(dictionary['real']) if dictionary.get('imag'): array = array + 1j*np.array(dictionary['imag']) return array def convert_array_to_dict(array: np.ndarray) -> dict: """Convert a numpy array to a dictionary. Args: array (numpy.array): a numpy array Returns: dictionary (dict): the dict containing the data """ dictionary = {} if np.iscomplexobj(array): dictionary['real'] = array.real.tolist() dictionary['imag'] = array.imag.tolist() else: dictionary['real'] = array.tolist() return dictionary def dec2bin(number: int, length: int) -> List[int]: """Converts a decimal number into a binary representation of fixed number of bits. Args: number: (int) the input decimal number length: (int) number of bits in the output string Returns: A list of binary numbers """ if pow(2,length) < number: sys.exit('Insufficient number of bits for representing the number {}'.format(number)) bit_str = bin(number) bit_str = bit_str[2:len(bit_str)] # chop off the first two chars bit_string = [int(x) for x in list(bit_str)] if len(bit_string) < length: len_zeros = length - len(bit_string) bit_string = [int(x) for x in list(np.zeros(len_zeros))] + bit_string return bit_string def bin2dec(x: List[int]) -> int: """Converts a binary vector to an integer, with the 0-th element being the most significant digit. Args: x: (list) a binary vector Returns: An integer """ dec = 0 coeff = 1 for i in range(len(x)): dec = dec + coeff * x[len(x)-1-i] coeff = coeff * 2 return dec """ The functions PAULI_X, PAULI_Y, PAULI_Z and IDENTITY below are used for generating the generators of the Pauli group, which include Pauli X, Y, Z operators as well as identity operator """ pauli_x = np.array([[0.0,1.0],[1.0,0.0]]) pauli_y = np.array([[0.0,-1.0j],[1.0j,0.0]]) pauli_z = np.array([[1.0,0.0],[0.0,-1.0]]) identity = np.array([[1.0,0.0],[0.0,1.0]]) def is_identity(u, tol=1e-15): """Test if a matrix is identity. Args: u: np.ndarray Matrix to be checked. tol: float Threshold below which two matrix elements are considered equal. """ dims = np.array(u).shape if dims[0] != dims[1]: raise Exception('Input matrix is not square.') return np.allclose(u, np.eye(u.shape[0]), atol=tol) def is_unitary(u, tol = 1e-15): """Test if a matrix is unitary. Args: u: array Matrix to be checked. tol: float Threshold below which two matrix elements are considered equal. """ dims = np.array(u).shape if dims[0] != dims[1]: raise Exception('Input matrix is not square.') test_matrix = np.dot(hermitian_conjugated(np.array(u)), u) return is_identity(test_matrix, tol) def compare_unitary(u1: np.ndarray, u2: np.ndarray, tol: float = 1e-15) -> bool: """Compares two unitary operators to see if they are equal to within a phase. Args: u1 (numpy.ndarray): First unitary operator. u2 (numpy.ndarray): Second unitary operator. tol (float): Threshold below which two matrix elements are considered equal. Returns: bool: True if the unitaries are equal to within the tolerance, ignoring differences in global phase. """ if is_unitary(u1, tol) == False: raise Exception('The first input matrix is not unitary.') if is_unitary(u2, tol) == False: raise Exception('The second input matrix is not unitary.') test_matrix = np.dot(u1.conj().T, u2) phase = test_matrix.item((0,0))**-1 return is_identity(phase*test_matrix, tol) def sample_from_probability_distribution(probability_distribution: dict, n_samples: int) -> collections.Counter: ''' Samples events from a discrete probability distribution Args: probabilty_distribution: The discrete probability distribution to be used for sampling. This should be a dictionary n_samples (int): The number of samples desired Returns: A dictionary of the outcomes sampled. The key values are the things be sampled and values are how many times those things appeared in the sampling ''' if isinstance(probability_distribution, dict): prob_pmf = lea.pmf(probability_distribution) sampled_dict = collections.Counter(prob_pmf.random(n_samples)) return sampled_dict else: raise RuntimeError("Probability distribution should be a dictionary with key value \ being the thing being sampled and the value being probability of getting \ sampled ") def convert_bitstrings_to_tuples(bitstrings): '''Given the measured bitstrings, convert each bitstring to tuple format Args: bitstrings (list of strings): the measured bitstrings Returns: A list of tuples ''' # Convert from bitstrings to tuple format measurements = [] for bitstring in bitstrings: measurement = () for char in bitstring: measurement = measurement + (int(char),) measurements.append(measurement) return measurements def convert_tuples_to_bitstrings(tuples): '''Given a set of measurement tuples, convert each to bitstring format Args: tuples (list of tuples): the measurement tuples Returns: A list of bitstrings ''' # Convert from tuples to bitstrings bitstrings = [] for tuple_item in tuples: bitstring = "" for bit in tuple_item: bitstring = bitstring + str(bit) bitstrings.append(bitstring) return bitstrings class ValueEstimate: """A class representing a numerical value and its precision corresponding to an observable or an objective function Args: value (np.float): the numerical value precision (np.float): its precision Attributes: value (np.float): the numerical value precision (np.float): its precision """ def __init__(self, value, precision=None): self.value = value self.precision = precision def to_dict(self): """Convert to a dictionary""" data = {'schema' : SCHEMA_VERSION + '-value_estimate'} if type(self.value).__module__ == np.__name__: data['value'] = self.value.item() else: data['value'] = self.value if type(self.precision).__module__ == np.__name__: data['precision'] = self.precision.item() else: data['precision'] = self.precision return data @classmethod def from_dict(cls, dictionary): """Create an ExpectationValues object from a dictionary.""" value = dictionary['value'] if 'precision' in dictionary: precision = dictionary['precision'] return cls(value, precision) else: return cls(value) def load_value_estimate(file): """Loads value estimate from a faile. Args: file (str or file-like object): the name of the file, or a file-like object. Returns: array (numpy.array): the array """ if isinstance(file, str): with open(file, 'r') as f: data = json.load(f) else: data = json.load(file) return ValueEstimate.from_dict(data) def save_value_estimate(value_estimate, filename): """Saves value estimate to a file. Args: value_estimate (core.utils.ValueEstimate): the value estimate file (str or file-like object): the name of the file, or a file-like object """ dictionary = value_estimate.to_dict() dictionary['schema'] = SCHEMA_VERSION + '-value_estimate' with open(filename, 'w') as f: f.write(json.dumps(dictionary, indent=2)) def load_list(file): """Load an array from a file. Args: file (str or file-like object): the name of the file, or a file-like object. Returns: array (list): the list """ if isinstance(file, str): with open(file, 'r') as f: data = json.load(f) else: data = json.load(file) return data['list'] def save_list(array, filename): """Save expectation values to a file. Args: array (list): the list to be saved file (str or file-like object): the name of the file, or a file-like object """ dictionary = {} dictionary['schema'] = SCHEMA_VERSION + '-list' dictionary['list'] = array with open(filename, 'w') as f: f.write(json.dumps(dictionary, indent=2)) def create_object(specs, **kwargs): """ Creates an object based on given specs. Specs include information about module and function necessary to create the object, as well as any additional input parameters for it. Args: specs (dict): dictionary containing the following keys: module_name: specifies from which module an object comes. function_name: specifies the name of the function used to create object. Returns: object: object of any type """ module_name = specs.pop("module_name") module = importlib.import_module(module_name) creator_name = specs.pop("function_name") creator = getattr(module, creator_name) created_object = creator(**specs, **kwargs) return created_object

28.258242

112

0.637857

import numpy as np from scipy.linalg import expm import random import math import operator import sys import json import openfermion from openfermion import hermitian_conjugated from openfermion.ops import SymbolicOperator from networkx.readwrite import json_graph import lea import collections import scipy from typing import List import importlib SCHEMA_VERSION = 'zapata-v1' RNDSEED = 12345 def convert_dict_to_array(dictionary: dict) -> np.ndarray: array = np.array(dictionary['real']) if dictionary.get('imag'): array = array + 1j*np.array(dictionary['imag']) return array def convert_array_to_dict(array: np.ndarray) -> dict: dictionary = {} if np.iscomplexobj(array): dictionary['real'] = array.real.tolist() dictionary['imag'] = array.imag.tolist() else: dictionary['real'] = array.tolist() return dictionary def dec2bin(number: int, length: int) -> List[int]: if pow(2,length) < number: sys.exit('Insufficient number of bits for representing the number {}'.format(number)) bit_str = bin(number) bit_str = bit_str[2:len(bit_str)] bit_string = [int(x) for x in list(bit_str)] if len(bit_string) < length: len_zeros = length - len(bit_string) bit_string = [int(x) for x in list(np.zeros(len_zeros))] + bit_string return bit_string def bin2dec(x: List[int]) -> int: dec = 0 coeff = 1 for i in range(len(x)): dec = dec + coeff * x[len(x)-1-i] coeff = coeff * 2 return dec pauli_x = np.array([[0.0,1.0],[1.0,0.0]]) pauli_y = np.array([[0.0,-1.0j],[1.0j,0.0]]) pauli_z = np.array([[1.0,0.0],[0.0,-1.0]]) identity = np.array([[1.0,0.0],[0.0,1.0]]) def is_identity(u, tol=1e-15): dims = np.array(u).shape if dims[0] != dims[1]: raise Exception('Input matrix is not square.') return np.allclose(u, np.eye(u.shape[0]), atol=tol) def is_unitary(u, tol = 1e-15): dims = np.array(u).shape if dims[0] != dims[1]: raise Exception('Input matrix is not square.') test_matrix = np.dot(hermitian_conjugated(np.array(u)), u) return is_identity(test_matrix, tol) def compare_unitary(u1: np.ndarray, u2: np.ndarray, tol: float = 1e-15) -> bool: if is_unitary(u1, tol) == False: raise Exception('The first input matrix is not unitary.') if is_unitary(u2, tol) == False: raise Exception('The second input matrix is not unitary.') test_matrix = np.dot(u1.conj().T, u2) phase = test_matrix.item((0,0))**-1 return is_identity(phase*test_matrix, tol) def sample_from_probability_distribution(probability_distribution: dict, n_samples: int) -> collections.Counter: if isinstance(probability_distribution, dict): prob_pmf = lea.pmf(probability_distribution) sampled_dict = collections.Counter(prob_pmf.random(n_samples)) return sampled_dict else: raise RuntimeError("Probability distribution should be a dictionary with key value \ being the thing being sampled and the value being probability of getting \ sampled ") def convert_bitstrings_to_tuples(bitstrings): measurements = [] for bitstring in bitstrings: measurement = () for char in bitstring: measurement = measurement + (int(char),) measurements.append(measurement) return measurements def convert_tuples_to_bitstrings(tuples): bitstrings = [] for tuple_item in tuples: bitstring = "" for bit in tuple_item: bitstring = bitstring + str(bit) bitstrings.append(bitstring) return bitstrings class ValueEstimate: def __init__(self, value, precision=None): self.value = value self.precision = precision def to_dict(self): data = {'schema' : SCHEMA_VERSION + '-value_estimate'} if type(self.value).__module__ == np.__name__: data['value'] = self.value.item() else: data['value'] = self.value if type(self.precision).__module__ == np.__name__: data['precision'] = self.precision.item() else: data['precision'] = self.precision return data @classmethod def from_dict(cls, dictionary): value = dictionary['value'] if 'precision' in dictionary: precision = dictionary['precision'] return cls(value, precision) else: return cls(value) def load_value_estimate(file): if isinstance(file, str): with open(file, 'r') as f: data = json.load(f) else: data = json.load(file) return ValueEstimate.from_dict(data) def save_value_estimate(value_estimate, filename): dictionary = value_estimate.to_dict() dictionary['schema'] = SCHEMA_VERSION + '-value_estimate' with open(filename, 'w') as f: f.write(json.dumps(dictionary, indent=2)) def load_list(file): if isinstance(file, str): with open(file, 'r') as f: data = json.load(f) else: data = json.load(file) return data['list'] def save_list(array, filename): dictionary = {} dictionary['schema'] = SCHEMA_VERSION + '-list' dictionary['list'] = array with open(filename, 'w') as f: f.write(json.dumps(dictionary, indent=2)) def create_object(specs, **kwargs): module_name = specs.pop("module_name") module = importlib.import_module(module_name) creator_name = specs.pop("function_name") creator = getattr(module, creator_name) created_object = creator(**specs, **kwargs) return created_object

true

f71882825d3f22da41da2d51951295858305f25f

128

py

Python

cactus/types/coin_solution.py

grayfallstown/cactus-blockchain

680d68d0bb7694bd4b99e4906b356e014bca7734

[ "Apache-2.0" ]

11,902

2019-12-05T00:14:29.000Z

2022-03-31T23:25:37.000Z

chia/types/coin_solution.py

jcteng/ext9-blockchain

46506bc5778e14cbc373de39438b0c6f794a49c5

[ "Apache-2.0" ]

5,246

2019-12-05T04:00:03.000Z

2022-03-31T21:33:30.000Z

chia/types/coin_solution.py

jcteng/ext9-blockchain

46506bc5778e14cbc373de39438b0c6f794a49c5

[ "Apache-2.0" ]

2,149

2019-12-05T11:12:53.000Z

2022-03-31T06:08:34.000Z

import warnings from .coin_spend import CoinSpend as CoinSolution # noqa warnings.warn("`CoinSolution` is now `CoinSpend`")

18.285714

57

0.773438

import warnings from .coin_spend import CoinSpend as CoinSolution warnings.warn("`CoinSolution` is now `CoinSpend`")

true

f71882b27108d3771cc3ddae3f362ee0e8b76a4b

6,457

py

Python

examples/ale/train_nsq_ale.py

yuishihara/chainerrl

74901712a8ed8207b9d526d3f45b04bf22996b8d

[ "MIT" ]

18

2018-08-07T07:27:41.000Z

2018-08-20T01:51:21.000Z

examples/ale/train_nsq_ale.py

yuishihara/chainerrl

74901712a8ed8207b9d526d3f45b04bf22996b8d

[ "MIT" ]

null

examples/ale/train_nsq_ale.py

yuishihara/chainerrl

74901712a8ed8207b9d526d3f45b04bf22996b8d

[ "MIT" ]

2

2018-08-16T06:47:26.000Z

2018-08-20T01:51:22.000Z

from __future__ import print_function from __future__ import division from __future__ import unicode_literals from __future__ import absolute_import from builtins import * # NOQA from future import standard_library standard_library.install_aliases() # NOQA import argparse import os import random # This prevents numpy from using multiple threads os.environ['OMP_NUM_THREADS'] = '1' # NOQA import gym gym.undo_logger_setup() # NOQA from chainer import links as L import numpy as np from chainerrl.action_value import DiscreteActionValue from chainerrl.agents import nsq from chainerrl import experiments from chainerrl import explorers from chainerrl import links from chainerrl import misc from chainerrl.optimizers import rmsprop_async from chainerrl import spaces import atari_wrappers def main(): parser = argparse.ArgumentParser() parser.add_argument('processes', type=int) parser.add_argument('--env', type=str, default='BreakoutNoFrameskip-v4') parser.add_argument('--seed', type=int, default=0, help='Random seed [0, 2 ** 31)') parser.add_argument('--lr', type=float, default=7e-4) parser.add_argument('--steps', type=int, default=8 * 10 ** 7) parser.add_argument('--max-episode-len', type=int, default=5 * 60 * 60 // 4, # 5 minutes with 60/4 fps help='Maximum number of steps for each episode.') parser.add_argument('--final-exploration-frames', type=int, default=4 * 10 ** 6) parser.add_argument('--outdir', type=str, default='results', help='Directory path to save output files.' ' If it does not exist, it will be created.') parser.add_argument('--profile', action='store_true') parser.add_argument('--eval-interval', type=int, default=10 ** 6) parser.add_argument('--eval-n-runs', type=int, default=10) parser.add_argument('--demo', action='store_true', default=False) parser.add_argument('--load', type=str, default=None) parser.add_argument('--logging-level', type=int, default=20, help='Logging level. 10:DEBUG, 20:INFO etc.') parser.add_argument('--render', action='store_true', default=False, help='Render env states in a GUI window.') parser.add_argument('--monitor', action='store_true', default=False, help='Monitor env. Videos and additional information' ' are saved as output files.') args = parser.parse_args() import logging logging.basicConfig(level=args.logging_level) # Set a random seed used in ChainerRL. # If you use more than one processes, the results will be no longer # deterministic even with the same random seed. misc.set_random_seed(args.seed) # Set different random seeds for different subprocesses. # If seed=0 and processes=4, subprocess seeds are [0, 1, 2, 3]. # If seed=1 and processes=4, subprocess seeds are [4, 5, 6, 7]. process_seeds = np.arange(args.processes) + args.seed * args.processes assert process_seeds.max() < 2 ** 31 args.outdir = experiments.prepare_output_dir(args, args.outdir) print('Output files are saved in {}'.format(args.outdir)) def make_env(process_idx, test): # Use different random seeds for train and test envs process_seed = process_seeds[process_idx] env_seed = 2 ** 31 - 1 - process_seed if test else process_seed env = atari_wrappers.wrap_deepmind( atari_wrappers.make_atari(args.env), episode_life=not test, clip_rewards=not test) env.seed(int(env_seed)) if args.monitor: env = gym.wrappers.Monitor( env, args.outdir, mode='evaluation' if test else 'training') if args.render: misc.env_modifiers.make_rendered(env) return env sample_env = make_env(0, test=False) action_space = sample_env.action_space assert isinstance(action_space, spaces.Discrete) # Define a model and its optimizer q_func = links.Sequence( links.NIPSDQNHead(), L.Linear(256, action_space.n), DiscreteActionValue) opt = rmsprop_async.RMSpropAsync(lr=args.lr, eps=1e-1, alpha=0.99) opt.setup(q_func) def phi(x): # Feature extractor return np.asarray(x, dtype=np.float32) / 255 # Make process-specific agents to diversify exploration def make_agent(process_idx): # Random epsilon assignment described in the original paper rand = random.random() if rand < 0.4: epsilon_target = 0.1 elif rand < 0.7: epsilon_target = 0.01 else: epsilon_target = 0.5 explorer = explorers.LinearDecayEpsilonGreedy( 1, epsilon_target, args.final_exploration_frames, action_space.sample) # Suppress the explorer logger explorer.logger.setLevel(logging.INFO) return nsq.NSQ(q_func, opt, t_max=5, gamma=0.99, i_target=40000, explorer=explorer, phi=phi) if args.demo: env = make_env(0, True) agent = make_agent(0) eval_stats = experiments.eval_performance( env=env, agent=agent, n_runs=args.eval_n_runs) print('n_runs: {} mean: {} median: {} stdev {}'.format( args.eval_n_runs, eval_stats['mean'], eval_stats['median'], eval_stats['stdev'])) else: explorer = explorers.ConstantEpsilonGreedy(0.05, action_space.sample) # Linearly decay the learning rate to zero def lr_setter(env, agent, value): agent.optimizer.lr = value lr_decay_hook = experiments.LinearInterpolationHook( args.steps, args.lr, 0, lr_setter) experiments.train_agent_async( outdir=args.outdir, processes=args.processes, make_env=make_env, make_agent=make_agent, profile=args.profile, steps=args.steps, eval_n_runs=args.eval_n_runs, eval_interval=args.eval_interval, eval_explorer=explorer, max_episode_len=args.max_episode_len, global_step_hooks=[lr_decay_hook], save_best_so_far_agent=False, ) if __name__ == '__main__': main()

37.760234

77

0.641474

from __future__ import print_function from __future__ import division from __future__ import unicode_literals from __future__ import absolute_import from builtins import * from future import standard_library standard_library.install_aliases() import argparse import os import random os.environ['OMP_NUM_THREADS'] = '1' import gym gym.undo_logger_setup() from chainer import links as L import numpy as np from chainerrl.action_value import DiscreteActionValue from chainerrl.agents import nsq from chainerrl import experiments from chainerrl import explorers from chainerrl import links from chainerrl import misc from chainerrl.optimizers import rmsprop_async from chainerrl import spaces import atari_wrappers def main(): parser = argparse.ArgumentParser() parser.add_argument('processes', type=int) parser.add_argument('--env', type=str, default='BreakoutNoFrameskip-v4') parser.add_argument('--seed', type=int, default=0, help='Random seed [0, 2 ** 31)') parser.add_argument('--lr', type=float, default=7e-4) parser.add_argument('--steps', type=int, default=8 * 10 ** 7) parser.add_argument('--max-episode-len', type=int, default=5 * 60 * 60 // 4, help='Maximum number of steps for each episode.') parser.add_argument('--final-exploration-frames', type=int, default=4 * 10 ** 6) parser.add_argument('--outdir', type=str, default='results', help='Directory path to save output files.' ' If it does not exist, it will be created.') parser.add_argument('--profile', action='store_true') parser.add_argument('--eval-interval', type=int, default=10 ** 6) parser.add_argument('--eval-n-runs', type=int, default=10) parser.add_argument('--demo', action='store_true', default=False) parser.add_argument('--load', type=str, default=None) parser.add_argument('--logging-level', type=int, default=20, help='Logging level. 10:DEBUG, 20:INFO etc.') parser.add_argument('--render', action='store_true', default=False, help='Render env states in a GUI window.') parser.add_argument('--monitor', action='store_true', default=False, help='Monitor env. Videos and additional information' ' are saved as output files.') args = parser.parse_args() import logging logging.basicConfig(level=args.logging_level) misc.set_random_seed(args.seed) process_seeds = np.arange(args.processes) + args.seed * args.processes assert process_seeds.max() < 2 ** 31 args.outdir = experiments.prepare_output_dir(args, args.outdir) print('Output files are saved in {}'.format(args.outdir)) def make_env(process_idx, test): process_seed = process_seeds[process_idx] env_seed = 2 ** 31 - 1 - process_seed if test else process_seed env = atari_wrappers.wrap_deepmind( atari_wrappers.make_atari(args.env), episode_life=not test, clip_rewards=not test) env.seed(int(env_seed)) if args.monitor: env = gym.wrappers.Monitor( env, args.outdir, mode='evaluation' if test else 'training') if args.render: misc.env_modifiers.make_rendered(env) return env sample_env = make_env(0, test=False) action_space = sample_env.action_space assert isinstance(action_space, spaces.Discrete) q_func = links.Sequence( links.NIPSDQNHead(), L.Linear(256, action_space.n), DiscreteActionValue) opt = rmsprop_async.RMSpropAsync(lr=args.lr, eps=1e-1, alpha=0.99) opt.setup(q_func) def phi(x): return np.asarray(x, dtype=np.float32) / 255 def make_agent(process_idx): rand = random.random() if rand < 0.4: epsilon_target = 0.1 elif rand < 0.7: epsilon_target = 0.01 else: epsilon_target = 0.5 explorer = explorers.LinearDecayEpsilonGreedy( 1, epsilon_target, args.final_exploration_frames, action_space.sample) explorer.logger.setLevel(logging.INFO) return nsq.NSQ(q_func, opt, t_max=5, gamma=0.99, i_target=40000, explorer=explorer, phi=phi) if args.demo: env = make_env(0, True) agent = make_agent(0) eval_stats = experiments.eval_performance( env=env, agent=agent, n_runs=args.eval_n_runs) print('n_runs: {} mean: {} median: {} stdev {}'.format( args.eval_n_runs, eval_stats['mean'], eval_stats['median'], eval_stats['stdev'])) else: explorer = explorers.ConstantEpsilonGreedy(0.05, action_space.sample) def lr_setter(env, agent, value): agent.optimizer.lr = value lr_decay_hook = experiments.LinearInterpolationHook( args.steps, args.lr, 0, lr_setter) experiments.train_agent_async( outdir=args.outdir, processes=args.processes, make_env=make_env, make_agent=make_agent, profile=args.profile, steps=args.steps, eval_n_runs=args.eval_n_runs, eval_interval=args.eval_interval, eval_explorer=explorer, max_episode_len=args.max_episode_len, global_step_hooks=[lr_decay_hook], save_best_so_far_agent=False, ) if __name__ == '__main__': main()

true

f71882cab39cf5d57a226bf9a24b1aec3387c49a

1,466

py

Python

aliyun-python-sdk-ons/aliyunsdkons/request/v20190214/OnsTopicListRequest.py

liumihust/aliyun-openapi-python-sdk

c7b5dd4befae4b9c59181654289f9272531207ef

[ "Apache-2.0" ]

null

aliyun-python-sdk-ons/aliyunsdkons/request/v20190214/OnsTopicListRequest.py

liumihust/aliyun-openapi-python-sdk

c7b5dd4befae4b9c59181654289f9272531207ef

[ "Apache-2.0" ]

null

aliyun-python-sdk-ons/aliyunsdkons/request/v20190214/OnsTopicListRequest.py

liumihust/aliyun-openapi-python-sdk

c7b5dd4befae4b9c59181654289f9272531207ef

[ "Apache-2.0" ]

null

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. from aliyunsdkcore.request import RpcRequest class OnsTopicListRequest(RpcRequest): def __init__(self): RpcRequest.__init__(self, 'Ons', '2019-02-14', 'OnsTopicList','ons') def get_PreventCache(self): return self.get_query_params().get('PreventCache') def set_PreventCache(self,PreventCache): self.add_query_param('PreventCache',PreventCache) def get_InstanceId(self): return self.get_query_params().get('InstanceId') def set_InstanceId(self,InstanceId): self.add_query_param('InstanceId',InstanceId) def get_Topic(self): return self.get_query_params().get('Topic') def set_Topic(self,Topic): self.add_query_param('Topic',Topic)

34.904762

71

0.761255

from aliyunsdkcore.request import RpcRequest class OnsTopicListRequest(RpcRequest): def __init__(self): RpcRequest.__init__(self, 'Ons', '2019-02-14', 'OnsTopicList','ons') def get_PreventCache(self): return self.get_query_params().get('PreventCache') def set_PreventCache(self,PreventCache): self.add_query_param('PreventCache',PreventCache) def get_InstanceId(self): return self.get_query_params().get('InstanceId') def set_InstanceId(self,InstanceId): self.add_query_param('InstanceId',InstanceId) def get_Topic(self): return self.get_query_params().get('Topic') def set_Topic(self,Topic): self.add_query_param('Topic',Topic)

true

f7188338fbe6feb8c2970ca81bf60c30b86db76c

1,709

py

Python

landmark.py

gavincangan/alvin

4e1945a3f5bb061842f0e35633f254863f8923c8

[ "MIT" ]

null

landmark.py

gavincangan/alvin

4e1945a3f5bb061842f0e35633f254863f8923c8

[ "MIT" ]

null

landmark.py

gavincangan/alvin

4e1945a3f5bb061842f0e35633f254863f8923c8

[ "MIT" ]

null

import sys from pymunk import Body, Circle, ShapeFilter from configsingleton import ConfigSingleton from common import * from common.drawing import draw_circle class Landmark(object): def __init__(self, mask, radius): self.body = Body(0, 0, Body.STATIC) self.body.position = 0, 0 self.body.angle = 0 self.body.velocity = 0, 0 self.body.angular_velocity = 0 self.shape = Circle(self.body, radius) self.mask = mask self.shape.filter = ShapeFilter(categories = mask) if mask == ARC_LANDMARK_MASK: self.shape.color = 0, 255, 0 elif mask == POLE_LANDMARK_MASK: self.shape.color = 0, 0, 255 elif mask == BLAST_LANDMARK_MASK: self.shape.color = 255, 0, 0 else: sys.exit("Unknown landmark mask: " + str(mask)) # The following is just to set the appropriate params to visualize below config = ConfigSingleton.get_instance() self.vis_range_max = \ config.getfloat("RangeScan:landmarks", "range_max") \ + radius self.vis_inside_radius = \ config.getfloat("LandmarkCircleController", "inside_radius") \ + radius self.vis_outside_radius = \ config.getfloat("LandmarkCircleController", "outside_radius") \ + radius def visualize_params(self): centre = (self.body.position.x, self.body.position.y) draw_circle(centre, self.vis_range_max, (255, 255, 255)) if self.mask == ARC_LANDMARK_MASK: draw_circle(centre, self.vis_inside_radius, (0, 255, 0)) draw_circle(centre, self.vis_outside_radius, (255, 0, 0))

37.152174

80

0.622586

import sys from pymunk import Body, Circle, ShapeFilter from configsingleton import ConfigSingleton from common import * from common.drawing import draw_circle class Landmark(object): def __init__(self, mask, radius): self.body = Body(0, 0, Body.STATIC) self.body.position = 0, 0 self.body.angle = 0 self.body.velocity = 0, 0 self.body.angular_velocity = 0 self.shape = Circle(self.body, radius) self.mask = mask self.shape.filter = ShapeFilter(categories = mask) if mask == ARC_LANDMARK_MASK: self.shape.color = 0, 255, 0 elif mask == POLE_LANDMARK_MASK: self.shape.color = 0, 0, 255 elif mask == BLAST_LANDMARK_MASK: self.shape.color = 255, 0, 0 else: sys.exit("Unknown landmark mask: " + str(mask)) config = ConfigSingleton.get_instance() self.vis_range_max = \ config.getfloat("RangeScan:landmarks", "range_max") \ + radius self.vis_inside_radius = \ config.getfloat("LandmarkCircleController", "inside_radius") \ + radius self.vis_outside_radius = \ config.getfloat("LandmarkCircleController", "outside_radius") \ + radius def visualize_params(self): centre = (self.body.position.x, self.body.position.y) draw_circle(centre, self.vis_range_max, (255, 255, 255)) if self.mask == ARC_LANDMARK_MASK: draw_circle(centre, self.vis_inside_radius, (0, 255, 0)) draw_circle(centre, self.vis_outside_radius, (255, 0, 0))

true

f71883436f0b25e5b91c4b47d39b55ee34c3a2ba

353

py

Python

Chapter 02/scape_v1.py

mujib2953/Python_Practice

39da23190196f050ea5834358907db723053da27

[ "MIT" ]

null

Chapter 02/scape_v1.py

mujib2953/Python_Practice

39da23190196f050ea5834358907db723053da27

[ "MIT" ]

null

Chapter 02/scape_v1.py

mujib2953/Python_Practice

39da23190196f050ea5834358907db723053da27

[ "MIT" ]

null

import urllib.request # http://beans-r-us.appspot.com/prices.html # http://www.beans-r-us.biz/prices.html # http://www.moneycontrol.com/india/stockpricequote/computers-software/tataconsultancyservices/TCS baseUrl = 'http://beans-r-us.appspot.com/prices.html' page = urllib.request.urlopen( baseUrl ) text = page.read().decode( 'utf8' ) print( text )

29.416667

98

0.750708

import urllib.request baseUrl = 'http://beans-r-us.appspot.com/prices.html' page = urllib.request.urlopen( baseUrl ) text = page.read().decode( 'utf8' ) print( text )

true

f71883577f39ef70d1dc2c52c00b5ff024d4497c

1,400

py

Python

likes/urls.py

CMPUT404-stev-sand-pant-ashw-mehr/CMPUT404-stev-sand-pant-ashw-mehr-repo

0f96d938e9e3ec51103f2b20cb9673bd0b145343

[ "MIT" ]

null

likes/urls.py

CMPUT404-stev-sand-pant-ashw-mehr/CMPUT404-stev-sand-pant-ashw-mehr-repo

0f96d938e9e3ec51103f2b20cb9673bd0b145343

[ "MIT" ]

50

2021-10-08T00:01:43.000Z

2021-12-06T06:34:29.000Z

likes/urls.py

CMPUT404-stev-sand-pant-ashw-mehr/CMPUT404-stev-sand-pant-ashw-mehr-repo

0f96d938e9e3ec51103f2b20cb9673bd0b145343

[ "MIT" ]

null

from django.urls import re_path from .api import PostLikeViewSet, CommentLikeViewSet, AuthorLikeViewSet urlpatterns = [ re_path(r'^author/(?P<author_id>[a-z0-9-\.-]+)/post/(?P<post_id>[a-z0-9-:\.-]+)/likes/?$', PostLikeViewSet.as_view({ "get": "get_post_likes", "post": "add_post_like", })), re_path(r'^author/(?P<author_id>[a-z0-9-/:\.-]+)/post/(?P<post_id>[a-z0-9-:\.-]+)/comments/(?P<comment_id>[a-z0-9-:\.-]+)/likes/?$', CommentLikeViewSet.as_view({ "get": "get_comment_likes", "post": "add_comment_like", })), re_path(r'^author/(?P<author_id>[a-z0-9-\.-]+)/posts/(?P<post_id>[a-z0-9-:\.-]+)/likes/?$', PostLikeViewSet.as_view({ "get": "get_post_likes", "post": "add_post_like", })), re_path(r'^author/(?P<author_id>[a-z0-9-/:\.-]+)/posts/(?P<post_id>[a-z0-9-:\.-]+)/comments/(?P<comment_id>[a-z0-9-:\.-]+)/likes/?$', CommentLikeViewSet.as_view({ "get": "get_comment_likes", "post": "add_comment_like", })), re_path(r'^author/(?P<author_id>[a-z0-9-\.-]+)/likes/?$', AuthorLikeViewSet.as_view({ "get": "get_likes", })), re_path(r'^author/(?P<author_id>(http://|https://)[a-z0-9\.-:]+(/author/)[a-z0-9\.-]+)/likes/?$', AuthorLikeViewSet.as_view({ "get": "get_likes", })) ]

46.666667

166

0.531429

from django.urls import re_path from .api import PostLikeViewSet, CommentLikeViewSet, AuthorLikeViewSet urlpatterns = [ re_path(r'^author/(?P<author_id>[a-z0-9-\.-]+)/post/(?P<post_id>[a-z0-9-:\.-]+)/likes/?$', PostLikeViewSet.as_view({ "get": "get_post_likes", "post": "add_post_like", })), re_path(r'^author/(?P<author_id>[a-z0-9-/:\.-]+)/post/(?P<post_id>[a-z0-9-:\.-]+)/comments/(?P<comment_id>[a-z0-9-:\.-]+)/likes/?$', CommentLikeViewSet.as_view({ "get": "get_comment_likes", "post": "add_comment_like", })), re_path(r'^author/(?P<author_id>[a-z0-9-\.-]+)/posts/(?P<post_id>[a-z0-9-:\.-]+)/likes/?$', PostLikeViewSet.as_view({ "get": "get_post_likes", "post": "add_post_like", })), re_path(r'^author/(?P<author_id>[a-z0-9-/:\.-]+)/posts/(?P<post_id>[a-z0-9-:\.-]+)/comments/(?P<comment_id>[a-z0-9-:\.-]+)/likes/?$', CommentLikeViewSet.as_view({ "get": "get_comment_likes", "post": "add_comment_like", })), re_path(r'^author/(?P<author_id>[a-z0-9-\.-]+)/likes/?$', AuthorLikeViewSet.as_view({ "get": "get_likes", })), re_path(r'^author/(?P<author_id>(http://|https://)[a-z0-9\.-:]+(/author/)[a-z0-9\.-]+)/likes/?$', AuthorLikeViewSet.as_view({ "get": "get_likes", })) ]

true

f7188362b6c3cf336bbf4135433d127a1a5e5491

469

py

Python

search/selectionsort.py

jsz1/algorithms-and-data-structures

fbf71f290d55c4f3f7b2123c4bd6df6396e3ede4

[ "MIT" ]

null

search/selectionsort.py

jsz1/algorithms-and-data-structures

fbf71f290d55c4f3f7b2123c4bd6df6396e3ede4

[ "MIT" ]

null

search/selectionsort.py

jsz1/algorithms-and-data-structures

fbf71f290d55c4f3f7b2123c4bd6df6396e3ede4

[ "MIT" ]

null

def selection_sort(alist): for fill_slot in range(len(alist) - 1,0,-1): position_of_max = 0 for location in range(1, fill_slot + 1): if alist[location] > alist[position_of_max]: position_of_max = location temp = alist[fill_slot] alist[fill_slot] = alist[position_of_max] alist[position_of_max] = temp alist = [54,23,65,87,43,32,5,7,3423,44,6,23,35,6,68,76,53,3] selection_sort(alist) print alist

33.5

60

0.635394

def selection_sort(alist): for fill_slot in range(len(alist) - 1,0,-1): position_of_max = 0 for location in range(1, fill_slot + 1): if alist[location] > alist[position_of_max]: position_of_max = location temp = alist[fill_slot] alist[fill_slot] = alist[position_of_max] alist[position_of_max] = temp alist = [54,23,65,87,43,32,5,7,3423,44,6,23,35,6,68,76,53,3] selection_sort(alist) print alist

false

true

f718836b8c0b46908cdf57f0144d22ccc800514c

363,980

py

Python

pynos/versions/ver_6/ver_6_0_1/yang/brocade_interface_ext.py

bdeetz/pynos

bd8a34e98f322de3fc06750827d8bbc3a0c00380

[ "Apache-2.0" ]

12

2015-09-21T23:56:09.000Z

2018-03-30T04:35:32.000Z

pynos/versions/ver_6/ver_6_0_1/yang/brocade_interface_ext.py

bdeetz/pynos

bd8a34e98f322de3fc06750827d8bbc3a0c00380

[ "Apache-2.0" ]

10

2016-09-15T19:03:27.000Z

2017-07-17T23:38:01.000Z

pynos/versions/ver_6/ver_6_0_1/yang/brocade_interface_ext.py

bdeetz/pynos

bd8a34e98f322de3fc06750827d8bbc3a0c00380

[ "Apache-2.0" ]

6

2015-08-14T08:05:23.000Z

2022-02-03T15:33:54.000Z

#!/usr/bin/env python import xml.etree.ElementTree as ET class brocade_interface_ext(object): """Auto generated class. """ def __init__(self, **kwargs): self._callback = kwargs.pop('callback') def get_vlan_brief_input_request_type_get_request_vlan_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief input = ET.SubElement(get_vlan_brief, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") vlan_id = ET.SubElement(get_request, "vlan-id") vlan_id.text = kwargs.pop('vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_input_request_type_get_next_request_last_rcvd_vlan_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief input = ET.SubElement(get_vlan_brief, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_vlan_id = ET.SubElement(get_next_request, "last-rcvd-vlan-id") last_rcvd_vlan_id.text = kwargs.pop('last_rcvd_vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_configured_vlans_count(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") configured_vlans_count = ET.SubElement(output, "configured-vlans-count") configured_vlans_count.text = kwargs.pop('configured_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_provisioned_vlans_count(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") provisioned_vlans_count = ET.SubElement(output, "provisioned-vlans-count") provisioned_vlans_count.text = kwargs.pop('provisioned_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_unprovisioned_vlans_count(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") unprovisioned_vlans_count = ET.SubElement(output, "unprovisioned-vlans-count") unprovisioned_vlans_count.text = kwargs.pop('unprovisioned_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id = ET.SubElement(vlan, "vlan-id") vlan_id.text = kwargs.pop('vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_type = ET.SubElement(vlan, "vlan-type") vlan_type.text = kwargs.pop('vlan_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_name = ET.SubElement(vlan, "vlan-name") vlan_name.text = kwargs.pop('vlan_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_state = ET.SubElement(vlan, "vlan-state") vlan_state.text = kwargs.pop('vlan_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_tag(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') tag = ET.SubElement(interface, "tag") tag.text = kwargs.pop('tag') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_classification_classification_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') classification = ET.SubElement(interface, "classification") classification_value_key = ET.SubElement(classification, "classification-value") classification_value_key.text = kwargs.pop('classification_value') classification_type = ET.SubElement(classification, "classification-type") classification_type.text = kwargs.pop('classification_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_classification_classification_value(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') classification = ET.SubElement(interface, "classification") classification_type_key = ET.SubElement(classification, "classification-type") classification_type_key.text = kwargs.pop('classification_type') classification_value = ET.SubElement(classification, "classification-value") classification_value.text = kwargs.pop('classification_value') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_last_vlan_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") last_vlan_id = ET.SubElement(output, "last-vlan-id") last_vlan_id.text = kwargs.pop('last_vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_has_more(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(switchport, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(switchport, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_mode(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') mode = ET.SubElement(switchport, "mode") mode.text = kwargs.pop('mode') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_fcoe_port_enabled(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') fcoe_port_enabled = ET.SubElement(switchport, "fcoe-port-enabled") fcoe_port_enabled.text = kwargs.pop('fcoe_port_enabled') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_ingress_filter_enabled(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ingress_filter_enabled = ET.SubElement(switchport, "ingress-filter-enabled") ingress_filter_enabled.text = kwargs.pop('ingress_filter_enabled') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_acceptable_frame_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') acceptable_frame_type = ET.SubElement(switchport, "acceptable-frame-type") acceptable_frame_type.text = kwargs.pop('acceptable_frame_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_default_vlan(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') default_vlan = ET.SubElement(switchport, "default-vlan") default_vlan.text = kwargs.pop('default_vlan') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_type = ET.SubElement(get_request, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_name = ET.SubElement(get_request, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") rbridge_id = ET.SubElement(get_request, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_if_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_name = ET.SubElement(interface, "if-name") if_name.text = kwargs.pop('if_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ipv4(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4 = ET.SubElement(ip_address, "ipv4") ipv4.text = kwargs.pop('ipv4') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ipv4_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') ipv4_type = ET.SubElement(ip_address, "ipv4-type") ipv4_type.text = kwargs.pop('ipv4_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_broadcast(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') broadcast = ET.SubElement(ip_address, "broadcast") broadcast.text = kwargs.pop('broadcast') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ip_mtu(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') ip_mtu = ET.SubElement(ip_address, "ip-mtu") ip_mtu.text = kwargs.pop('ip_mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_if_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_state = ET.SubElement(interface, "if-state") if_state.text = kwargs.pop('if_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_line_protocol_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state = ET.SubElement(interface, "line-protocol-state") line_protocol_state.text = kwargs.pop('line_protocol_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_proxy_arp(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') proxy_arp = ET.SubElement(interface, "proxy-arp") proxy_arp.text = kwargs.pop('proxy_arp') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_vrf(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') vrf = ET.SubElement(interface, "vrf") vrf.text = kwargs.pop('vrf') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_has_more(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_request_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_type = ET.SubElement(get_request, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_request_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_name = ET.SubElement(get_request, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_next_request_last_rcvd_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_interface = ET.SubElement(get_next_request, "last-rcvd-interface") interface_type = ET.SubElement(last_rcvd_interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_next_request_last_rcvd_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_interface = ET.SubElement(get_next_request, "last-rcvd-interface") interface_name = ET.SubElement(last_rcvd_interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifindex(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifindex = ET.SubElement(interface, "ifindex") ifindex.text = kwargs.pop('ifindex') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_mtu(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') mtu = ET.SubElement(interface, "mtu") mtu.text = kwargs.pop('mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ip_mtu(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_mtu = ET.SubElement(interface, "ip-mtu") ip_mtu.text = kwargs.pop('ip_mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_name = ET.SubElement(interface, "if-name") if_name.text = kwargs.pop('if_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_state = ET.SubElement(interface, "if-state") if_state.text = kwargs.pop('if_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state = ET.SubElement(interface, "line-protocol-state") line_protocol_state.text = kwargs.pop('line_protocol_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_state_info(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state_info = ET.SubElement(interface, "line-protocol-state-info") line_protocol_state_info.text = kwargs.pop('line_protocol_state_info') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_exception_info(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_exception_info = ET.SubElement(interface, "line-protocol-exception-info") line_protocol_exception_info.text = kwargs.pop('line_protocol_exception_info') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_hardware_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') hardware_type = ET.SubElement(interface, "hardware-type") hardware_type.text = kwargs.pop('hardware_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_logical_hardware_address(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') logical_hardware_address = ET.SubElement(interface, "logical-hardware-address") logical_hardware_address.text = kwargs.pop('logical_hardware_address') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_current_hardware_address(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') current_hardware_address = ET.SubElement(interface, "current-hardware-address") current_hardware_address.text = kwargs.pop('current_hardware_address') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_media_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') media_type = ET.SubElement(interface, "media-type") media_type.text = kwargs.pop('media_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') wavelength = ET.SubElement(interface, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_description(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_description = ET.SubElement(interface, "if-description") if_description.text = kwargs.pop('if_description') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_actual_line_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') actual_line_speed = ET.SubElement(interface, "actual-line-speed") actual_line_speed.text = kwargs.pop('actual_line_speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_configured_line_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') configured_line_speed = ET.SubElement(interface, "configured-line-speed") configured_line_speed.text = kwargs.pop('configured_line_speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_duplex_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_duplex_state = ET.SubElement(interface, "line-duplex-state") line_duplex_state.text = kwargs.pop('line_duplex_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_flow_control(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') flow_control = ET.SubElement(interface, "flow-control") flow_control.text = kwargs.pop('flow_control') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_queuing_strategy(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') queuing_strategy = ET.SubElement(interface, "queuing-strategy") queuing_strategy.text = kwargs.pop('queuing_strategy') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_port_role(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') port_role = ET.SubElement(interface, "port-role") port_role.text = kwargs.pop('port_role') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_port_mode(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') port_mode = ET.SubElement(interface, "port-mode") port_mode.text = kwargs.pop('port_mode') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInOctets(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInOctets = ET.SubElement(interface, "ifHCInOctets") ifHCInOctets.text = kwargs.pop('ifHCInOctets') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInUcastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInUcastPkts = ET.SubElement(interface, "ifHCInUcastPkts") ifHCInUcastPkts.text = kwargs.pop('ifHCInUcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInMulticastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInMulticastPkts = ET.SubElement(interface, "ifHCInMulticastPkts") ifHCInMulticastPkts.text = kwargs.pop('ifHCInMulticastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInBroadcastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInBroadcastPkts = ET.SubElement(interface, "ifHCInBroadcastPkts") ifHCInBroadcastPkts.text = kwargs.pop('ifHCInBroadcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInErrors(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInErrors = ET.SubElement(interface, "ifHCInErrors") ifHCInErrors.text = kwargs.pop('ifHCInErrors') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutOctets(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutOctets = ET.SubElement(interface, "ifHCOutOctets") ifHCOutOctets.text = kwargs.pop('ifHCOutOctets') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutUcastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutUcastPkts = ET.SubElement(interface, "ifHCOutUcastPkts") ifHCOutUcastPkts.text = kwargs.pop('ifHCOutUcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutMulticastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutMulticastPkts = ET.SubElement(interface, "ifHCOutMulticastPkts") ifHCOutMulticastPkts.text = kwargs.pop('ifHCOutMulticastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutBroadcastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutBroadcastPkts = ET.SubElement(interface, "ifHCOutBroadcastPkts") ifHCOutBroadcastPkts.text = kwargs.pop('ifHCOutBroadcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutErrors(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutErrors = ET.SubElement(interface, "ifHCOutErrors") ifHCOutErrors.text = kwargs.pop('ifHCOutErrors') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_has_more(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") interface_type = ET.SubElement(input, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") interface_name = ET.SubElement(input, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") speed = ET.SubElement(sfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") connector = ET.SubElement(sfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") encoding = ET.SubElement(sfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_name = ET.SubElement(sfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_oui = ET.SubElement(sfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_pn = ET.SubElement(sfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_rev = ET.SubElement(sfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") distance = ET.SubElement(sfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") media_form_factor = ET.SubElement(sfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") wavelength = ET.SubElement(sfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") serial_no = ET.SubElement(sfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") date_code = ET.SubElement(sfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") temperature = ET.SubElement(sfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") voltage = ET.SubElement(sfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") current = ET.SubElement(sfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") tx_power = ET.SubElement(sfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") rx_power = ET.SubElement(sfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") speed = ET.SubElement(on_board, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") connector = ET.SubElement(on_board, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") encoding = ET.SubElement(on_board, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_name = ET.SubElement(on_board, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_oui = ET.SubElement(on_board, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_pn = ET.SubElement(on_board, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_rev = ET.SubElement(on_board, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_name = ET.SubElement(gbc, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_oui = ET.SubElement(gbc, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_pn = ET.SubElement(gbc, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_rev = ET.SubElement(gbc, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_name = ET.SubElement(xfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_oui = ET.SubElement(xfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_pn = ET.SubElement(xfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_rev = ET.SubElement(xfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_name = ET.SubElement(xff, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_oui = ET.SubElement(xff, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_pn = ET.SubElement(xff, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_rev = ET.SubElement(xff, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_name = ET.SubElement(xfpe, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_oui = ET.SubElement(xfpe, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_pn = ET.SubElement(xfpe, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_rev = ET.SubElement(xfpe, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_name = ET.SubElement(unknown, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_oui = ET.SubElement(unknown, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_pn = ET.SubElement(unknown, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_rev = ET.SubElement(unknown, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") speed = ET.SubElement(qsfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") connector = ET.SubElement(qsfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") encoding = ET.SubElement(qsfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_name = ET.SubElement(qsfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_oui = ET.SubElement(qsfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_pn = ET.SubElement(qsfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_rev = ET.SubElement(qsfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") distance = ET.SubElement(qsfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") media_form_factor = ET.SubElement(qsfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") wavelength = ET.SubElement(qsfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") serial_no = ET.SubElement(qsfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") date_code = ET.SubElement(qsfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") temperature = ET.SubElement(qsfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") voltage = ET.SubElement(qsfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") current = ET.SubElement(qsfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") tx_power = ET.SubElement(qsfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") rx_power = ET.SubElement(qsfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") speed = ET.SubElement(qsfpp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") connector = ET.SubElement(qsfpp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") encoding = ET.SubElement(qsfpp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_name = ET.SubElement(qsfpp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_oui = ET.SubElement(qsfpp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_pn = ET.SubElement(qsfpp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_rev = ET.SubElement(qsfpp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") distance = ET.SubElement(qsfpp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") media_form_factor = ET.SubElement(qsfpp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") wavelength = ET.SubElement(qsfpp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") serial_no = ET.SubElement(qsfpp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") date_code = ET.SubElement(qsfpp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") temperature = ET.SubElement(qsfpp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") voltage = ET.SubElement(qsfpp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") current = ET.SubElement(qsfpp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") tx_power = ET.SubElement(qsfpp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") rx_power = ET.SubElement(qsfpp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") speed = ET.SubElement(cfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") connector = ET.SubElement(cfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") encoding = ET.SubElement(cfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_name = ET.SubElement(cfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_oui = ET.SubElement(cfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_pn = ET.SubElement(cfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_rev = ET.SubElement(cfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") distance = ET.SubElement(cfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") media_form_factor = ET.SubElement(cfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") wavelength = ET.SubElement(cfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") serial_no = ET.SubElement(cfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") date_code = ET.SubElement(cfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") temperature = ET.SubElement(cfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") voltage = ET.SubElement(cfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") current = ET.SubElement(cfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") tx_power = ET.SubElement(cfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") rx_power = ET.SubElement(cfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") speed = ET.SubElement(cfp2, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") connector = ET.SubElement(cfp2, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") encoding = ET.SubElement(cfp2, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_name = ET.SubElement(cfp2, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_oui = ET.SubElement(cfp2, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_pn = ET.SubElement(cfp2, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_rev = ET.SubElement(cfp2, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") distance = ET.SubElement(cfp2, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") media_form_factor = ET.SubElement(cfp2, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") wavelength = ET.SubElement(cfp2, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") serial_no = ET.SubElement(cfp2, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") date_code = ET.SubElement(cfp2, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") temperature = ET.SubElement(cfp2, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") voltage = ET.SubElement(cfp2, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") current = ET.SubElement(cfp2, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") tx_power = ET.SubElement(cfp2, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") rx_power = ET.SubElement(cfp2, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_input_request_type_get_request_vlan_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief input = ET.SubElement(get_vlan_brief, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") vlan_id = ET.SubElement(get_request, "vlan-id") vlan_id.text = kwargs.pop('vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_input_request_type_get_next_request_last_rcvd_vlan_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief input = ET.SubElement(get_vlan_brief, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_vlan_id = ET.SubElement(get_next_request, "last-rcvd-vlan-id") last_rcvd_vlan_id.text = kwargs.pop('last_rcvd_vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_configured_vlans_count(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") configured_vlans_count = ET.SubElement(output, "configured-vlans-count") configured_vlans_count.text = kwargs.pop('configured_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_provisioned_vlans_count(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") provisioned_vlans_count = ET.SubElement(output, "provisioned-vlans-count") provisioned_vlans_count.text = kwargs.pop('provisioned_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_unprovisioned_vlans_count(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") unprovisioned_vlans_count = ET.SubElement(output, "unprovisioned-vlans-count") unprovisioned_vlans_count.text = kwargs.pop('unprovisioned_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id = ET.SubElement(vlan, "vlan-id") vlan_id.text = kwargs.pop('vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_type = ET.SubElement(vlan, "vlan-type") vlan_type.text = kwargs.pop('vlan_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_name = ET.SubElement(vlan, "vlan-name") vlan_name.text = kwargs.pop('vlan_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_state = ET.SubElement(vlan, "vlan-state") vlan_state.text = kwargs.pop('vlan_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_tag(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') tag = ET.SubElement(interface, "tag") tag.text = kwargs.pop('tag') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_classification_classification_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') classification = ET.SubElement(interface, "classification") classification_value_key = ET.SubElement(classification, "classification-value") classification_value_key.text = kwargs.pop('classification_value') classification_type = ET.SubElement(classification, "classification-type") classification_type.text = kwargs.pop('classification_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_classification_classification_value(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') classification = ET.SubElement(interface, "classification") classification_type_key = ET.SubElement(classification, "classification-type") classification_type_key.text = kwargs.pop('classification_type') classification_value = ET.SubElement(classification, "classification-value") classification_value.text = kwargs.pop('classification_value') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_last_vlan_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") last_vlan_id = ET.SubElement(output, "last-vlan-id") last_vlan_id.text = kwargs.pop('last_vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_has_more(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(switchport, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(switchport, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_mode(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') mode = ET.SubElement(switchport, "mode") mode.text = kwargs.pop('mode') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_fcoe_port_enabled(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') fcoe_port_enabled = ET.SubElement(switchport, "fcoe-port-enabled") fcoe_port_enabled.text = kwargs.pop('fcoe_port_enabled') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_ingress_filter_enabled(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ingress_filter_enabled = ET.SubElement(switchport, "ingress-filter-enabled") ingress_filter_enabled.text = kwargs.pop('ingress_filter_enabled') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_acceptable_frame_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') acceptable_frame_type = ET.SubElement(switchport, "acceptable-frame-type") acceptable_frame_type.text = kwargs.pop('acceptable_frame_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_default_vlan(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') default_vlan = ET.SubElement(switchport, "default-vlan") default_vlan.text = kwargs.pop('default_vlan') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_type = ET.SubElement(get_request, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_name = ET.SubElement(get_request, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") rbridge_id = ET.SubElement(get_request, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_if_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_name = ET.SubElement(interface, "if-name") if_name.text = kwargs.pop('if_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ipv4(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4 = ET.SubElement(ip_address, "ipv4") ipv4.text = kwargs.pop('ipv4') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ipv4_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') ipv4_type = ET.SubElement(ip_address, "ipv4-type") ipv4_type.text = kwargs.pop('ipv4_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_broadcast(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') broadcast = ET.SubElement(ip_address, "broadcast") broadcast.text = kwargs.pop('broadcast') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ip_mtu(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') ip_mtu = ET.SubElement(ip_address, "ip-mtu") ip_mtu.text = kwargs.pop('ip_mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_if_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_state = ET.SubElement(interface, "if-state") if_state.text = kwargs.pop('if_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_line_protocol_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state = ET.SubElement(interface, "line-protocol-state") line_protocol_state.text = kwargs.pop('line_protocol_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_proxy_arp(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') proxy_arp = ET.SubElement(interface, "proxy-arp") proxy_arp.text = kwargs.pop('proxy_arp') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_vrf(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') vrf = ET.SubElement(interface, "vrf") vrf.text = kwargs.pop('vrf') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_has_more(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_request_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_type = ET.SubElement(get_request, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_request_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_name = ET.SubElement(get_request, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_next_request_last_rcvd_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_interface = ET.SubElement(get_next_request, "last-rcvd-interface") interface_type = ET.SubElement(last_rcvd_interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_next_request_last_rcvd_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_interface = ET.SubElement(get_next_request, "last-rcvd-interface") interface_name = ET.SubElement(last_rcvd_interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifindex(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifindex = ET.SubElement(interface, "ifindex") ifindex.text = kwargs.pop('ifindex') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_mtu(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') mtu = ET.SubElement(interface, "mtu") mtu.text = kwargs.pop('mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ip_mtu(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_mtu = ET.SubElement(interface, "ip-mtu") ip_mtu.text = kwargs.pop('ip_mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_name = ET.SubElement(interface, "if-name") if_name.text = kwargs.pop('if_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_state = ET.SubElement(interface, "if-state") if_state.text = kwargs.pop('if_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state = ET.SubElement(interface, "line-protocol-state") line_protocol_state.text = kwargs.pop('line_protocol_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_state_info(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state_info = ET.SubElement(interface, "line-protocol-state-info") line_protocol_state_info.text = kwargs.pop('line_protocol_state_info') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_exception_info(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_exception_info = ET.SubElement(interface, "line-protocol-exception-info") line_protocol_exception_info.text = kwargs.pop('line_protocol_exception_info') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_hardware_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') hardware_type = ET.SubElement(interface, "hardware-type") hardware_type.text = kwargs.pop('hardware_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_logical_hardware_address(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') logical_hardware_address = ET.SubElement(interface, "logical-hardware-address") logical_hardware_address.text = kwargs.pop('logical_hardware_address') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_current_hardware_address(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') current_hardware_address = ET.SubElement(interface, "current-hardware-address") current_hardware_address.text = kwargs.pop('current_hardware_address') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_media_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') media_type = ET.SubElement(interface, "media-type") media_type.text = kwargs.pop('media_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') wavelength = ET.SubElement(interface, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_description(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_description = ET.SubElement(interface, "if-description") if_description.text = kwargs.pop('if_description') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_actual_line_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') actual_line_speed = ET.SubElement(interface, "actual-line-speed") actual_line_speed.text = kwargs.pop('actual_line_speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_configured_line_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') configured_line_speed = ET.SubElement(interface, "configured-line-speed") configured_line_speed.text = kwargs.pop('configured_line_speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_duplex_state(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_duplex_state = ET.SubElement(interface, "line-duplex-state") line_duplex_state.text = kwargs.pop('line_duplex_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_flow_control(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') flow_control = ET.SubElement(interface, "flow-control") flow_control.text = kwargs.pop('flow_control') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_queuing_strategy(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') queuing_strategy = ET.SubElement(interface, "queuing-strategy") queuing_strategy.text = kwargs.pop('queuing_strategy') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_port_role(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') port_role = ET.SubElement(interface, "port-role") port_role.text = kwargs.pop('port_role') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_port_mode(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') port_mode = ET.SubElement(interface, "port-mode") port_mode.text = kwargs.pop('port_mode') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInOctets(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInOctets = ET.SubElement(interface, "ifHCInOctets") ifHCInOctets.text = kwargs.pop('ifHCInOctets') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInUcastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInUcastPkts = ET.SubElement(interface, "ifHCInUcastPkts") ifHCInUcastPkts.text = kwargs.pop('ifHCInUcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInMulticastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInMulticastPkts = ET.SubElement(interface, "ifHCInMulticastPkts") ifHCInMulticastPkts.text = kwargs.pop('ifHCInMulticastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInBroadcastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInBroadcastPkts = ET.SubElement(interface, "ifHCInBroadcastPkts") ifHCInBroadcastPkts.text = kwargs.pop('ifHCInBroadcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInErrors(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInErrors = ET.SubElement(interface, "ifHCInErrors") ifHCInErrors.text = kwargs.pop('ifHCInErrors') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutOctets(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutOctets = ET.SubElement(interface, "ifHCOutOctets") ifHCOutOctets.text = kwargs.pop('ifHCOutOctets') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutUcastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutUcastPkts = ET.SubElement(interface, "ifHCOutUcastPkts") ifHCOutUcastPkts.text = kwargs.pop('ifHCOutUcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutMulticastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutMulticastPkts = ET.SubElement(interface, "ifHCOutMulticastPkts") ifHCOutMulticastPkts.text = kwargs.pop('ifHCOutMulticastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutBroadcastPkts(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutBroadcastPkts = ET.SubElement(interface, "ifHCOutBroadcastPkts") ifHCOutBroadcastPkts.text = kwargs.pop('ifHCOutBroadcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutErrors(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutErrors = ET.SubElement(interface, "ifHCOutErrors") ifHCOutErrors.text = kwargs.pop('ifHCOutErrors') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_has_more(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") interface_type = ET.SubElement(input, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") interface_name = ET.SubElement(input, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_rbridge_id(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") speed = ET.SubElement(sfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") connector = ET.SubElement(sfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") encoding = ET.SubElement(sfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_name = ET.SubElement(sfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_oui = ET.SubElement(sfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_pn = ET.SubElement(sfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_rev = ET.SubElement(sfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") distance = ET.SubElement(sfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") media_form_factor = ET.SubElement(sfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") wavelength = ET.SubElement(sfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") serial_no = ET.SubElement(sfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") date_code = ET.SubElement(sfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") temperature = ET.SubElement(sfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") voltage = ET.SubElement(sfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") current = ET.SubElement(sfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") tx_power = ET.SubElement(sfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") rx_power = ET.SubElement(sfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") speed = ET.SubElement(on_board, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") connector = ET.SubElement(on_board, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") encoding = ET.SubElement(on_board, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_name = ET.SubElement(on_board, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_oui = ET.SubElement(on_board, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_pn = ET.SubElement(on_board, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_rev = ET.SubElement(on_board, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_name = ET.SubElement(gbc, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_oui = ET.SubElement(gbc, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_pn = ET.SubElement(gbc, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_rev = ET.SubElement(gbc, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_name = ET.SubElement(xfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_oui = ET.SubElement(xfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_pn = ET.SubElement(xfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_rev = ET.SubElement(xfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_name = ET.SubElement(xff, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_oui = ET.SubElement(xff, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_pn = ET.SubElement(xff, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_rev = ET.SubElement(xff, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_name = ET.SubElement(xfpe, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_oui = ET.SubElement(xfpe, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_pn = ET.SubElement(xfpe, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_rev = ET.SubElement(xfpe, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_name = ET.SubElement(unknown, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_oui = ET.SubElement(unknown, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_pn = ET.SubElement(unknown, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_rev = ET.SubElement(unknown, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") speed = ET.SubElement(qsfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") connector = ET.SubElement(qsfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") encoding = ET.SubElement(qsfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_name = ET.SubElement(qsfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_oui = ET.SubElement(qsfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_pn = ET.SubElement(qsfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_rev = ET.SubElement(qsfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") distance = ET.SubElement(qsfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") media_form_factor = ET.SubElement(qsfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") wavelength = ET.SubElement(qsfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") serial_no = ET.SubElement(qsfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") date_code = ET.SubElement(qsfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") temperature = ET.SubElement(qsfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") voltage = ET.SubElement(qsfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") current = ET.SubElement(qsfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") tx_power = ET.SubElement(qsfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") rx_power = ET.SubElement(qsfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") speed = ET.SubElement(qsfpp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") connector = ET.SubElement(qsfpp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") encoding = ET.SubElement(qsfpp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_name = ET.SubElement(qsfpp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_oui = ET.SubElement(qsfpp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_pn = ET.SubElement(qsfpp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_rev = ET.SubElement(qsfpp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") distance = ET.SubElement(qsfpp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") media_form_factor = ET.SubElement(qsfpp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") wavelength = ET.SubElement(qsfpp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") serial_no = ET.SubElement(qsfpp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") date_code = ET.SubElement(qsfpp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") temperature = ET.SubElement(qsfpp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") voltage = ET.SubElement(qsfpp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") current = ET.SubElement(qsfpp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") tx_power = ET.SubElement(qsfpp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") rx_power = ET.SubElement(qsfpp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") speed = ET.SubElement(cfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") connector = ET.SubElement(cfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") encoding = ET.SubElement(cfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_name = ET.SubElement(cfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_oui = ET.SubElement(cfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_pn = ET.SubElement(cfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_rev = ET.SubElement(cfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") distance = ET.SubElement(cfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") media_form_factor = ET.SubElement(cfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") wavelength = ET.SubElement(cfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") serial_no = ET.SubElement(cfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") date_code = ET.SubElement(cfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") temperature = ET.SubElement(cfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") voltage = ET.SubElement(cfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") current = ET.SubElement(cfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") tx_power = ET.SubElement(cfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") rx_power = ET.SubElement(cfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_speed(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") speed = ET.SubElement(cfp2, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_connector(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") connector = ET.SubElement(cfp2, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_encoding(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") encoding = ET.SubElement(cfp2, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_name(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_name = ET.SubElement(cfp2, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_oui(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_oui = ET.SubElement(cfp2, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_pn(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_pn = ET.SubElement(cfp2, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_rev(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_rev = ET.SubElement(cfp2, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_distance(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") distance = ET.SubElement(cfp2, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_media_form_factor(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") media_form_factor = ET.SubElement(cfp2, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_wavelength(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") wavelength = ET.SubElement(cfp2, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_serial_no(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") serial_no = ET.SubElement(cfp2, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_date_code(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") date_code = ET.SubElement(cfp2, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_temperature(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") temperature = ET.SubElement(cfp2, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_voltage(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") voltage = ET.SubElement(cfp2, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_current(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") current = ET.SubElement(cfp2, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_tx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") tx_power = ET.SubElement(cfp2, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_rx_power(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") rx_power = ET.SubElement(cfp2, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config)

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import xml.etree.ElementTree as ET class brocade_interface_ext(object): def __init__(self, **kwargs): self._callback = kwargs.pop('callback') def get_vlan_brief_input_request_type_get_request_vlan_id(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief input = ET.SubElement(get_vlan_brief, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") vlan_id = ET.SubElement(get_request, "vlan-id") vlan_id.text = kwargs.pop('vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_input_request_type_get_next_request_last_rcvd_vlan_id(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief input = ET.SubElement(get_vlan_brief, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_vlan_id = ET.SubElement(get_next_request, "last-rcvd-vlan-id") last_rcvd_vlan_id.text = kwargs.pop('last_rcvd_vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_configured_vlans_count(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") configured_vlans_count = ET.SubElement(output, "configured-vlans-count") configured_vlans_count.text = kwargs.pop('configured_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_provisioned_vlans_count(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") provisioned_vlans_count = ET.SubElement(output, "provisioned-vlans-count") provisioned_vlans_count.text = kwargs.pop('provisioned_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_unprovisioned_vlans_count(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") unprovisioned_vlans_count = ET.SubElement(output, "unprovisioned-vlans-count") unprovisioned_vlans_count.text = kwargs.pop('unprovisioned_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_id(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id = ET.SubElement(vlan, "vlan-id") vlan_id.text = kwargs.pop('vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_type(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_type = ET.SubElement(vlan, "vlan-type") vlan_type.text = kwargs.pop('vlan_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_name(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_name = ET.SubElement(vlan, "vlan-name") vlan_name.text = kwargs.pop('vlan_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_state(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_state = ET.SubElement(vlan, "vlan-state") vlan_state.text = kwargs.pop('vlan_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_interface_type(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_interface_name(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_tag(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') tag = ET.SubElement(interface, "tag") tag.text = kwargs.pop('tag') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_classification_classification_type(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') classification = ET.SubElement(interface, "classification") classification_value_key = ET.SubElement(classification, "classification-value") classification_value_key.text = kwargs.pop('classification_value') classification_type = ET.SubElement(classification, "classification-type") classification_type.text = kwargs.pop('classification_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_classification_classification_value(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') classification = ET.SubElement(interface, "classification") classification_type_key = ET.SubElement(classification, "classification-type") classification_type_key.text = kwargs.pop('classification_type') classification_value = ET.SubElement(classification, "classification-value") classification_value.text = kwargs.pop('classification_value') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_last_vlan_id(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") last_vlan_id = ET.SubElement(output, "last-vlan-id") last_vlan_id.text = kwargs.pop('last_vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_has_more(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_interface_type(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(switchport, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_interface_name(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(switchport, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_mode(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') mode = ET.SubElement(switchport, "mode") mode.text = kwargs.pop('mode') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_fcoe_port_enabled(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') fcoe_port_enabled = ET.SubElement(switchport, "fcoe-port-enabled") fcoe_port_enabled.text = kwargs.pop('fcoe_port_enabled') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_ingress_filter_enabled(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ingress_filter_enabled = ET.SubElement(switchport, "ingress-filter-enabled") ingress_filter_enabled.text = kwargs.pop('ingress_filter_enabled') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_acceptable_frame_type(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') acceptable_frame_type = ET.SubElement(switchport, "acceptable-frame-type") acceptable_frame_type.text = kwargs.pop('acceptable_frame_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_default_vlan(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') default_vlan = ET.SubElement(switchport, "default-vlan") default_vlan.text = kwargs.pop('default_vlan') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_interface_type(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_type = ET.SubElement(get_request, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_interface_name(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_name = ET.SubElement(get_request, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_rbridge_id(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") rbridge_id = ET.SubElement(get_request, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_interface_type(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_interface_name(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_if_name(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_name = ET.SubElement(interface, "if-name") if_name.text = kwargs.pop('if_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ipv4(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4 = ET.SubElement(ip_address, "ipv4") ipv4.text = kwargs.pop('ipv4') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ipv4_type(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') ipv4_type = ET.SubElement(ip_address, "ipv4-type") ipv4_type.text = kwargs.pop('ipv4_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_broadcast(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') broadcast = ET.SubElement(ip_address, "broadcast") broadcast.text = kwargs.pop('broadcast') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ip_mtu(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') ip_mtu = ET.SubElement(ip_address, "ip-mtu") ip_mtu.text = kwargs.pop('ip_mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_if_state(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_state = ET.SubElement(interface, "if-state") if_state.text = kwargs.pop('if_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_line_protocol_state(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state = ET.SubElement(interface, "line-protocol-state") line_protocol_state.text = kwargs.pop('line_protocol_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_proxy_arp(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') proxy_arp = ET.SubElement(interface, "proxy-arp") proxy_arp.text = kwargs.pop('proxy_arp') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_vrf(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') vrf = ET.SubElement(interface, "vrf") vrf.text = kwargs.pop('vrf') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_has_more(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_request_interface_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_type = ET.SubElement(get_request, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_request_interface_name(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_name = ET.SubElement(get_request, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_next_request_last_rcvd_interface_interface_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_interface = ET.SubElement(get_next_request, "last-rcvd-interface") interface_type = ET.SubElement(last_rcvd_interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_next_request_last_rcvd_interface_interface_name(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_interface = ET.SubElement(get_next_request, "last-rcvd-interface") interface_name = ET.SubElement(last_rcvd_interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_interface_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_interface_name(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifindex(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifindex = ET.SubElement(interface, "ifindex") ifindex.text = kwargs.pop('ifindex') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_mtu(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') mtu = ET.SubElement(interface, "mtu") mtu.text = kwargs.pop('mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ip_mtu(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_mtu = ET.SubElement(interface, "ip-mtu") ip_mtu.text = kwargs.pop('ip_mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_name(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_name = ET.SubElement(interface, "if-name") if_name.text = kwargs.pop('if_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_state(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_state = ET.SubElement(interface, "if-state") if_state.text = kwargs.pop('if_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_state(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state = ET.SubElement(interface, "line-protocol-state") line_protocol_state.text = kwargs.pop('line_protocol_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_state_info(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state_info = ET.SubElement(interface, "line-protocol-state-info") line_protocol_state_info.text = kwargs.pop('line_protocol_state_info') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_exception_info(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_exception_info = ET.SubElement(interface, "line-protocol-exception-info") line_protocol_exception_info.text = kwargs.pop('line_protocol_exception_info') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_hardware_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') hardware_type = ET.SubElement(interface, "hardware-type") hardware_type.text = kwargs.pop('hardware_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_logical_hardware_address(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') logical_hardware_address = ET.SubElement(interface, "logical-hardware-address") logical_hardware_address.text = kwargs.pop('logical_hardware_address') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_current_hardware_address(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') current_hardware_address = ET.SubElement(interface, "current-hardware-address") current_hardware_address.text = kwargs.pop('current_hardware_address') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_media_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') media_type = ET.SubElement(interface, "media-type") media_type.text = kwargs.pop('media_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_wavelength(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') wavelength = ET.SubElement(interface, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_description(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_description = ET.SubElement(interface, "if-description") if_description.text = kwargs.pop('if_description') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_actual_line_speed(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') actual_line_speed = ET.SubElement(interface, "actual-line-speed") actual_line_speed.text = kwargs.pop('actual_line_speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_configured_line_speed(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') configured_line_speed = ET.SubElement(interface, "configured-line-speed") configured_line_speed.text = kwargs.pop('configured_line_speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_duplex_state(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_duplex_state = ET.SubElement(interface, "line-duplex-state") line_duplex_state.text = kwargs.pop('line_duplex_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_flow_control(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') flow_control = ET.SubElement(interface, "flow-control") flow_control.text = kwargs.pop('flow_control') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_queuing_strategy(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') queuing_strategy = ET.SubElement(interface, "queuing-strategy") queuing_strategy.text = kwargs.pop('queuing_strategy') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_port_role(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') port_role = ET.SubElement(interface, "port-role") port_role.text = kwargs.pop('port_role') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_port_mode(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') port_mode = ET.SubElement(interface, "port-mode") port_mode.text = kwargs.pop('port_mode') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInOctets(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInOctets = ET.SubElement(interface, "ifHCInOctets") ifHCInOctets.text = kwargs.pop('ifHCInOctets') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInUcastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInUcastPkts = ET.SubElement(interface, "ifHCInUcastPkts") ifHCInUcastPkts.text = kwargs.pop('ifHCInUcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInMulticastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInMulticastPkts = ET.SubElement(interface, "ifHCInMulticastPkts") ifHCInMulticastPkts.text = kwargs.pop('ifHCInMulticastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInBroadcastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInBroadcastPkts = ET.SubElement(interface, "ifHCInBroadcastPkts") ifHCInBroadcastPkts.text = kwargs.pop('ifHCInBroadcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInErrors(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInErrors = ET.SubElement(interface, "ifHCInErrors") ifHCInErrors.text = kwargs.pop('ifHCInErrors') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutOctets(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutOctets = ET.SubElement(interface, "ifHCOutOctets") ifHCOutOctets.text = kwargs.pop('ifHCOutOctets') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutUcastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutUcastPkts = ET.SubElement(interface, "ifHCOutUcastPkts") ifHCOutUcastPkts.text = kwargs.pop('ifHCOutUcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutMulticastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutMulticastPkts = ET.SubElement(interface, "ifHCOutMulticastPkts") ifHCOutMulticastPkts.text = kwargs.pop('ifHCOutMulticastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutBroadcastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutBroadcastPkts = ET.SubElement(interface, "ifHCOutBroadcastPkts") ifHCOutBroadcastPkts.text = kwargs.pop('ifHCOutBroadcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutErrors(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutErrors = ET.SubElement(interface, "ifHCOutErrors") ifHCOutErrors.text = kwargs.pop('ifHCOutErrors') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_has_more(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_interface_type(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") interface_type = ET.SubElement(input, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_interface_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") interface_name = ET.SubElement(input, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_rbridge_id(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_type(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") speed = ET.SubElement(sfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") connector = ET.SubElement(sfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") encoding = ET.SubElement(sfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_name = ET.SubElement(sfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_oui = ET.SubElement(sfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_pn = ET.SubElement(sfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_rev = ET.SubElement(sfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") distance = ET.SubElement(sfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") media_form_factor = ET.SubElement(sfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") wavelength = ET.SubElement(sfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") serial_no = ET.SubElement(sfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") date_code = ET.SubElement(sfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") temperature = ET.SubElement(sfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") voltage = ET.SubElement(sfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") current = ET.SubElement(sfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") tx_power = ET.SubElement(sfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") rx_power = ET.SubElement(sfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") speed = ET.SubElement(on_board, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") connector = ET.SubElement(on_board, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") encoding = ET.SubElement(on_board, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_name = ET.SubElement(on_board, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_oui = ET.SubElement(on_board, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_pn = ET.SubElement(on_board, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_rev = ET.SubElement(on_board, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_name = ET.SubElement(gbc, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_oui = ET.SubElement(gbc, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_pn = ET.SubElement(gbc, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_rev = ET.SubElement(gbc, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_name = ET.SubElement(xfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_oui = ET.SubElement(xfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_pn = ET.SubElement(xfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_rev = ET.SubElement(xfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_name = ET.SubElement(xff, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_oui = ET.SubElement(xff, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_pn = ET.SubElement(xff, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_rev = ET.SubElement(xff, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_name = ET.SubElement(xfpe, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_oui = ET.SubElement(xfpe, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_pn = ET.SubElement(xfpe, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_rev = ET.SubElement(xfpe, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_name = ET.SubElement(unknown, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_oui = ET.SubElement(unknown, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_pn = ET.SubElement(unknown, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_rev = ET.SubElement(unknown, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") speed = ET.SubElement(qsfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") connector = ET.SubElement(qsfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") encoding = ET.SubElement(qsfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_name = ET.SubElement(qsfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_oui = ET.SubElement(qsfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_pn = ET.SubElement(qsfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_rev = ET.SubElement(qsfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") distance = ET.SubElement(qsfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") media_form_factor = ET.SubElement(qsfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") wavelength = ET.SubElement(qsfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") serial_no = ET.SubElement(qsfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") date_code = ET.SubElement(qsfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") temperature = ET.SubElement(qsfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") voltage = ET.SubElement(qsfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") current = ET.SubElement(qsfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") tx_power = ET.SubElement(qsfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") rx_power = ET.SubElement(qsfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") speed = ET.SubElement(qsfpp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") connector = ET.SubElement(qsfpp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") encoding = ET.SubElement(qsfpp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_name = ET.SubElement(qsfpp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_oui = ET.SubElement(qsfpp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_pn = ET.SubElement(qsfpp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_rev = ET.SubElement(qsfpp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") distance = ET.SubElement(qsfpp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") media_form_factor = ET.SubElement(qsfpp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") wavelength = ET.SubElement(qsfpp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") serial_no = ET.SubElement(qsfpp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") date_code = ET.SubElement(qsfpp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") temperature = ET.SubElement(qsfpp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") voltage = ET.SubElement(qsfpp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") current = ET.SubElement(qsfpp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") tx_power = ET.SubElement(qsfpp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") rx_power = ET.SubElement(qsfpp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") speed = ET.SubElement(cfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") connector = ET.SubElement(cfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") encoding = ET.SubElement(cfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_name = ET.SubElement(cfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_oui = ET.SubElement(cfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_pn = ET.SubElement(cfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_rev = ET.SubElement(cfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") distance = ET.SubElement(cfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") media_form_factor = ET.SubElement(cfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") wavelength = ET.SubElement(cfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") serial_no = ET.SubElement(cfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") date_code = ET.SubElement(cfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") temperature = ET.SubElement(cfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") voltage = ET.SubElement(cfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") current = ET.SubElement(cfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") tx_power = ET.SubElement(cfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") rx_power = ET.SubElement(cfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") speed = ET.SubElement(cfp2, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") connector = ET.SubElement(cfp2, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") encoding = ET.SubElement(cfp2, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_name = ET.SubElement(cfp2, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_oui = ET.SubElement(cfp2, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_pn = ET.SubElement(cfp2, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_rev = ET.SubElement(cfp2, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") distance = ET.SubElement(cfp2, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") media_form_factor = ET.SubElement(cfp2, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") wavelength = ET.SubElement(cfp2, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") serial_no = ET.SubElement(cfp2, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") date_code = ET.SubElement(cfp2, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") temperature = ET.SubElement(cfp2, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") voltage = ET.SubElement(cfp2, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") current = ET.SubElement(cfp2, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") tx_power = ET.SubElement(cfp2, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") rx_power = ET.SubElement(cfp2, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_input_request_type_get_request_vlan_id(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief input = ET.SubElement(get_vlan_brief, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") vlan_id = ET.SubElement(get_request, "vlan-id") vlan_id.text = kwargs.pop('vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_input_request_type_get_next_request_last_rcvd_vlan_id(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief input = ET.SubElement(get_vlan_brief, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_vlan_id = ET.SubElement(get_next_request, "last-rcvd-vlan-id") last_rcvd_vlan_id.text = kwargs.pop('last_rcvd_vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_configured_vlans_count(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") configured_vlans_count = ET.SubElement(output, "configured-vlans-count") configured_vlans_count.text = kwargs.pop('configured_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_provisioned_vlans_count(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") provisioned_vlans_count = ET.SubElement(output, "provisioned-vlans-count") provisioned_vlans_count.text = kwargs.pop('provisioned_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_unprovisioned_vlans_count(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") unprovisioned_vlans_count = ET.SubElement(output, "unprovisioned-vlans-count") unprovisioned_vlans_count.text = kwargs.pop('unprovisioned_vlans_count') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_id(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id = ET.SubElement(vlan, "vlan-id") vlan_id.text = kwargs.pop('vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_type(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_type = ET.SubElement(vlan, "vlan-type") vlan_type.text = kwargs.pop('vlan_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_name(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_name = ET.SubElement(vlan, "vlan-name") vlan_name.text = kwargs.pop('vlan_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_vlan_state(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') vlan_state = ET.SubElement(vlan, "vlan-state") vlan_state.text = kwargs.pop('vlan_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_interface_type(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_interface_name(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_tag(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') tag = ET.SubElement(interface, "tag") tag.text = kwargs.pop('tag') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_classification_classification_type(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') classification = ET.SubElement(interface, "classification") classification_value_key = ET.SubElement(classification, "classification-value") classification_value_key.text = kwargs.pop('classification_value') classification_type = ET.SubElement(classification, "classification-type") classification_type.text = kwargs.pop('classification_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_vlan_interface_classification_classification_value(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") vlan = ET.SubElement(output, "vlan") vlan_id_key = ET.SubElement(vlan, "vlan-id") vlan_id_key.text = kwargs.pop('vlan_id') interface = ET.SubElement(vlan, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') classification = ET.SubElement(interface, "classification") classification_type_key = ET.SubElement(classification, "classification-type") classification_type_key.text = kwargs.pop('classification_type') classification_value = ET.SubElement(classification, "classification-value") classification_value.text = kwargs.pop('classification_value') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_last_vlan_id(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") last_vlan_id = ET.SubElement(output, "last-vlan-id") last_vlan_id.text = kwargs.pop('last_vlan_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_vlan_brief_output_has_more(self, **kwargs): config = ET.Element("config") get_vlan_brief = ET.Element("get_vlan_brief") config = get_vlan_brief output = ET.SubElement(get_vlan_brief, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_interface_type(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(switchport, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_interface_name(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(switchport, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_mode(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') mode = ET.SubElement(switchport, "mode") mode.text = kwargs.pop('mode') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_fcoe_port_enabled(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') fcoe_port_enabled = ET.SubElement(switchport, "fcoe-port-enabled") fcoe_port_enabled.text = kwargs.pop('fcoe_port_enabled') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_ingress_filter_enabled(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ingress_filter_enabled = ET.SubElement(switchport, "ingress-filter-enabled") ingress_filter_enabled.text = kwargs.pop('ingress_filter_enabled') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_acceptable_frame_type(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') acceptable_frame_type = ET.SubElement(switchport, "acceptable-frame-type") acceptable_frame_type.text = kwargs.pop('acceptable_frame_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_switchport_output_switchport_default_vlan(self, **kwargs): config = ET.Element("config") get_interface_switchport = ET.Element("get_interface_switchport") config = get_interface_switchport output = ET.SubElement(get_interface_switchport, "output") switchport = ET.SubElement(output, "switchport") interface_type_key = ET.SubElement(switchport, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(switchport, "interface-name") interface_name_key.text = kwargs.pop('interface_name') default_vlan = ET.SubElement(switchport, "default-vlan") default_vlan.text = kwargs.pop('default_vlan') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_interface_type(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_type = ET.SubElement(get_request, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_interface_name(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_name = ET.SubElement(get_request, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_input_request_type_get_request_rbridge_id(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface input = ET.SubElement(get_ip_interface, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") rbridge_id = ET.SubElement(get_request, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_interface_type(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_interface_name(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_if_name(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_name = ET.SubElement(interface, "if-name") if_name.text = kwargs.pop('if_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ipv4(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4 = ET.SubElement(ip_address, "ipv4") ipv4.text = kwargs.pop('ipv4') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ipv4_type(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') ipv4_type = ET.SubElement(ip_address, "ipv4-type") ipv4_type.text = kwargs.pop('ipv4_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_broadcast(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') broadcast = ET.SubElement(ip_address, "broadcast") broadcast.text = kwargs.pop('broadcast') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_ip_address_ip_mtu(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_address = ET.SubElement(interface, "ip-address") ipv4_key = ET.SubElement(ip_address, "ipv4") ipv4_key.text = kwargs.pop('ipv4') ip_mtu = ET.SubElement(ip_address, "ip-mtu") ip_mtu.text = kwargs.pop('ip_mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_if_state(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_state = ET.SubElement(interface, "if-state") if_state.text = kwargs.pop('if_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_line_protocol_state(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state = ET.SubElement(interface, "line-protocol-state") line_protocol_state.text = kwargs.pop('line_protocol_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_proxy_arp(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') proxy_arp = ET.SubElement(interface, "proxy-arp") proxy_arp.text = kwargs.pop('proxy_arp') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_interface_vrf(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') vrf = ET.SubElement(interface, "vrf") vrf.text = kwargs.pop('vrf') callback = kwargs.pop('callback', self._callback) return callback(config) def get_ip_interface_output_has_more(self, **kwargs): config = ET.Element("config") get_ip_interface = ET.Element("get_ip_interface") config = get_ip_interface output = ET.SubElement(get_ip_interface, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_request_interface_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_type = ET.SubElement(get_request, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_request_interface_name(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_request = ET.SubElement(request_type, "get-request") interface_name = ET.SubElement(get_request, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_next_request_last_rcvd_interface_interface_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_interface = ET.SubElement(get_next_request, "last-rcvd-interface") interface_type = ET.SubElement(last_rcvd_interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_input_request_type_get_next_request_last_rcvd_interface_interface_name(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail input = ET.SubElement(get_interface_detail, "input") request_type = ET.SubElement(input, "request-type") get_next_request = ET.SubElement(request_type, "get-next-request") last_rcvd_interface = ET.SubElement(get_next_request, "last-rcvd-interface") interface_name = ET.SubElement(last_rcvd_interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_interface_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_interface_name(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifindex(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifindex = ET.SubElement(interface, "ifindex") ifindex.text = kwargs.pop('ifindex') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_mtu(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') mtu = ET.SubElement(interface, "mtu") mtu.text = kwargs.pop('mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ip_mtu(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ip_mtu = ET.SubElement(interface, "ip-mtu") ip_mtu.text = kwargs.pop('ip_mtu') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_name(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_name = ET.SubElement(interface, "if-name") if_name.text = kwargs.pop('if_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_state(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_state = ET.SubElement(interface, "if-state") if_state.text = kwargs.pop('if_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_state(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state = ET.SubElement(interface, "line-protocol-state") line_protocol_state.text = kwargs.pop('line_protocol_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_state_info(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_state_info = ET.SubElement(interface, "line-protocol-state-info") line_protocol_state_info.text = kwargs.pop('line_protocol_state_info') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_protocol_exception_info(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_protocol_exception_info = ET.SubElement(interface, "line-protocol-exception-info") line_protocol_exception_info.text = kwargs.pop('line_protocol_exception_info') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_hardware_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') hardware_type = ET.SubElement(interface, "hardware-type") hardware_type.text = kwargs.pop('hardware_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_logical_hardware_address(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') logical_hardware_address = ET.SubElement(interface, "logical-hardware-address") logical_hardware_address.text = kwargs.pop('logical_hardware_address') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_current_hardware_address(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') current_hardware_address = ET.SubElement(interface, "current-hardware-address") current_hardware_address.text = kwargs.pop('current_hardware_address') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_media_type(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') media_type = ET.SubElement(interface, "media-type") media_type.text = kwargs.pop('media_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_wavelength(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') wavelength = ET.SubElement(interface, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_if_description(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') if_description = ET.SubElement(interface, "if-description") if_description.text = kwargs.pop('if_description') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_actual_line_speed(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') actual_line_speed = ET.SubElement(interface, "actual-line-speed") actual_line_speed.text = kwargs.pop('actual_line_speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_configured_line_speed(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') configured_line_speed = ET.SubElement(interface, "configured-line-speed") configured_line_speed.text = kwargs.pop('configured_line_speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_line_duplex_state(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') line_duplex_state = ET.SubElement(interface, "line-duplex-state") line_duplex_state.text = kwargs.pop('line_duplex_state') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_flow_control(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') flow_control = ET.SubElement(interface, "flow-control") flow_control.text = kwargs.pop('flow_control') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_queuing_strategy(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') queuing_strategy = ET.SubElement(interface, "queuing-strategy") queuing_strategy.text = kwargs.pop('queuing_strategy') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_port_role(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') port_role = ET.SubElement(interface, "port-role") port_role.text = kwargs.pop('port_role') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_port_mode(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') port_mode = ET.SubElement(interface, "port-mode") port_mode.text = kwargs.pop('port_mode') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInOctets(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInOctets = ET.SubElement(interface, "ifHCInOctets") ifHCInOctets.text = kwargs.pop('ifHCInOctets') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInUcastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInUcastPkts = ET.SubElement(interface, "ifHCInUcastPkts") ifHCInUcastPkts.text = kwargs.pop('ifHCInUcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInMulticastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInMulticastPkts = ET.SubElement(interface, "ifHCInMulticastPkts") ifHCInMulticastPkts.text = kwargs.pop('ifHCInMulticastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInBroadcastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInBroadcastPkts = ET.SubElement(interface, "ifHCInBroadcastPkts") ifHCInBroadcastPkts.text = kwargs.pop('ifHCInBroadcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCInErrors(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCInErrors = ET.SubElement(interface, "ifHCInErrors") ifHCInErrors.text = kwargs.pop('ifHCInErrors') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutOctets(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutOctets = ET.SubElement(interface, "ifHCOutOctets") ifHCOutOctets.text = kwargs.pop('ifHCOutOctets') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutUcastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutUcastPkts = ET.SubElement(interface, "ifHCOutUcastPkts") ifHCOutUcastPkts.text = kwargs.pop('ifHCOutUcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutMulticastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutMulticastPkts = ET.SubElement(interface, "ifHCOutMulticastPkts") ifHCOutMulticastPkts.text = kwargs.pop('ifHCOutMulticastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutBroadcastPkts(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutBroadcastPkts = ET.SubElement(interface, "ifHCOutBroadcastPkts") ifHCOutBroadcastPkts.text = kwargs.pop('ifHCOutBroadcastPkts') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_interface_ifHCOutErrors(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') ifHCOutErrors = ET.SubElement(interface, "ifHCOutErrors") ifHCOutErrors.text = kwargs.pop('ifHCOutErrors') callback = kwargs.pop('callback', self._callback) return callback(config) def get_interface_detail_output_has_more(self, **kwargs): config = ET.Element("config") get_interface_detail = ET.Element("get_interface_detail") config = get_interface_detail output = ET.SubElement(get_interface_detail, "output") has_more = ET.SubElement(output, "has-more") has_more.text = kwargs.pop('has_more') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_interface_type(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") interface_type = ET.SubElement(input, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_interface_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") interface_name = ET.SubElement(input, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_input_rbridge_id(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail input = ET.SubElement(get_media_detail, "input") rbridge_id = ET.SubElement(input, "rbridge-id") rbridge_id.text = kwargs.pop('rbridge_id') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_type(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_type = ET.SubElement(interface, "interface-type") interface_type.text = kwargs.pop('interface_type') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name = ET.SubElement(interface, "interface-name") interface_name.text = kwargs.pop('interface_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") speed = ET.SubElement(sfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") connector = ET.SubElement(sfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") encoding = ET.SubElement(sfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_name = ET.SubElement(sfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_oui = ET.SubElement(sfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_pn = ET.SubElement(sfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") vendor_rev = ET.SubElement(sfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") distance = ET.SubElement(sfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") media_form_factor = ET.SubElement(sfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") wavelength = ET.SubElement(sfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") serial_no = ET.SubElement(sfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") date_code = ET.SubElement(sfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") temperature = ET.SubElement(sfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") voltage = ET.SubElement(sfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") current = ET.SubElement(sfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") tx_power = ET.SubElement(sfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_sfp_sfp_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") sfp = ET.SubElement(interface_identifier, "sfp") sfp = ET.SubElement(sfp, "sfp") rx_power = ET.SubElement(sfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") speed = ET.SubElement(on_board, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") connector = ET.SubElement(on_board, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") encoding = ET.SubElement(on_board, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_name = ET.SubElement(on_board, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_oui = ET.SubElement(on_board, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_pn = ET.SubElement(on_board, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_on_board_on_board_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") on_board = ET.SubElement(interface_identifier, "on-board") on_board = ET.SubElement(on_board, "on-board") vendor_rev = ET.SubElement(on_board, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_name = ET.SubElement(gbc, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_oui = ET.SubElement(gbc, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_pn = ET.SubElement(gbc, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_gbic_gbc_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") gbic = ET.SubElement(interface_identifier, "gbic") gbc = ET.SubElement(gbic, "gbc") vendor_rev = ET.SubElement(gbc, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_name = ET.SubElement(xfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_oui = ET.SubElement(xfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_pn = ET.SubElement(xfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfp_xfp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfp = ET.SubElement(interface_identifier, "xfp") xfp = ET.SubElement(xfp, "xfp") vendor_rev = ET.SubElement(xfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_name = ET.SubElement(xff, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_oui = ET.SubElement(xff, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_pn = ET.SubElement(xff, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xff_xff_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xff = ET.SubElement(interface_identifier, "xff") xff = ET.SubElement(xff, "xff") vendor_rev = ET.SubElement(xff, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_name = ET.SubElement(xfpe, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_oui = ET.SubElement(xfpe, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_pn = ET.SubElement(xfpe, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_xfpe_xfpe_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") xfpe = ET.SubElement(interface_identifier, "xfpe") xfpe = ET.SubElement(xfpe, "xfpe") vendor_rev = ET.SubElement(xfpe, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_name = ET.SubElement(unknown, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_oui = ET.SubElement(unknown, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_pn = ET.SubElement(unknown, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_unknown_unknown_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") unknown = ET.SubElement(interface_identifier, "unknown") unknown = ET.SubElement(unknown, "unknown") vendor_rev = ET.SubElement(unknown, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") speed = ET.SubElement(qsfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") connector = ET.SubElement(qsfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") encoding = ET.SubElement(qsfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_name = ET.SubElement(qsfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_oui = ET.SubElement(qsfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_pn = ET.SubElement(qsfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") vendor_rev = ET.SubElement(qsfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") distance = ET.SubElement(qsfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") media_form_factor = ET.SubElement(qsfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") wavelength = ET.SubElement(qsfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") serial_no = ET.SubElement(qsfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") date_code = ET.SubElement(qsfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") temperature = ET.SubElement(qsfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") voltage = ET.SubElement(qsfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") current = ET.SubElement(qsfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") tx_power = ET.SubElement(qsfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfp_qsfp_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfp = ET.SubElement(interface_identifier, "qsfp") qsfp = ET.SubElement(qsfp, "qsfp") rx_power = ET.SubElement(qsfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") speed = ET.SubElement(qsfpp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") connector = ET.SubElement(qsfpp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") encoding = ET.SubElement(qsfpp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_name = ET.SubElement(qsfpp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_oui = ET.SubElement(qsfpp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_pn = ET.SubElement(qsfpp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") vendor_rev = ET.SubElement(qsfpp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") distance = ET.SubElement(qsfpp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") media_form_factor = ET.SubElement(qsfpp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") wavelength = ET.SubElement(qsfpp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") serial_no = ET.SubElement(qsfpp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") date_code = ET.SubElement(qsfpp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") temperature = ET.SubElement(qsfpp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") voltage = ET.SubElement(qsfpp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") current = ET.SubElement(qsfpp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") tx_power = ET.SubElement(qsfpp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_qsfpp_qsfpp_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") qsfpp = ET.SubElement(interface_identifier, "qsfpp") qsfpp = ET.SubElement(qsfpp, "qsfpp") rx_power = ET.SubElement(qsfpp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") speed = ET.SubElement(cfp, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") connector = ET.SubElement(cfp, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") encoding = ET.SubElement(cfp, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_name = ET.SubElement(cfp, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_oui = ET.SubElement(cfp, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_pn = ET.SubElement(cfp, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") vendor_rev = ET.SubElement(cfp, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") distance = ET.SubElement(cfp, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") media_form_factor = ET.SubElement(cfp, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") wavelength = ET.SubElement(cfp, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") serial_no = ET.SubElement(cfp, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") date_code = ET.SubElement(cfp, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") temperature = ET.SubElement(cfp, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") voltage = ET.SubElement(cfp, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") current = ET.SubElement(cfp, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") tx_power = ET.SubElement(cfp, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp_cfp_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp = ET.SubElement(interface_identifier, "cfp") cfp = ET.SubElement(cfp, "cfp") rx_power = ET.SubElement(cfp, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_speed(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") speed = ET.SubElement(cfp2, "speed") speed.text = kwargs.pop('speed') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_connector(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") connector = ET.SubElement(cfp2, "connector") connector.text = kwargs.pop('connector') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_encoding(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") encoding = ET.SubElement(cfp2, "encoding") encoding.text = kwargs.pop('encoding') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_name(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_name = ET.SubElement(cfp2, "vendor-name") vendor_name.text = kwargs.pop('vendor_name') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_oui(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_oui = ET.SubElement(cfp2, "vendor-oui") vendor_oui.text = kwargs.pop('vendor_oui') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_pn(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_pn = ET.SubElement(cfp2, "vendor-pn") vendor_pn.text = kwargs.pop('vendor_pn') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_vendor_rev(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") vendor_rev = ET.SubElement(cfp2, "vendor-rev") vendor_rev.text = kwargs.pop('vendor_rev') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_distance(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") distance = ET.SubElement(cfp2, "distance") distance.text = kwargs.pop('distance') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_media_form_factor(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") media_form_factor = ET.SubElement(cfp2, "media-form-factor") media_form_factor.text = kwargs.pop('media_form_factor') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_wavelength(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") wavelength = ET.SubElement(cfp2, "wavelength") wavelength.text = kwargs.pop('wavelength') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_serial_no(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") serial_no = ET.SubElement(cfp2, "serial-no") serial_no.text = kwargs.pop('serial_no') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_date_code(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") date_code = ET.SubElement(cfp2, "date-code") date_code.text = kwargs.pop('date_code') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_temperature(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") temperature = ET.SubElement(cfp2, "temperature") temperature.text = kwargs.pop('temperature') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_voltage(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") voltage = ET.SubElement(cfp2, "voltage") voltage.text = kwargs.pop('voltage') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_current(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") current = ET.SubElement(cfp2, "current") current.text = kwargs.pop('current') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_tx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") tx_power = ET.SubElement(cfp2, "tx-power") tx_power.text = kwargs.pop('tx_power') callback = kwargs.pop('callback', self._callback) return callback(config) def get_media_detail_output_interface_interface_identifier_cfp2_cfp2_rx_power(self, **kwargs): config = ET.Element("config") get_media_detail = ET.Element("get_media_detail") config = get_media_detail output = ET.SubElement(get_media_detail, "output") interface = ET.SubElement(output, "interface") interface_type_key = ET.SubElement(interface, "interface-type") interface_type_key.text = kwargs.pop('interface_type') interface_name_key = ET.SubElement(interface, "interface-name") interface_name_key.text = kwargs.pop('interface_name') interface_identifier = ET.SubElement(interface, "interface-identifier") cfp2 = ET.SubElement(interface_identifier, "cfp2") cfp2 = ET.SubElement(cfp2, "cfp2") rx_power = ET.SubElement(cfp2, "rx-power") rx_power.text = kwargs.pop('rx_power') callback = kwargs.pop('callback', self._callback) return callback(config)

true

f71884bbf144038a727debbf7cccc7fa2cfb1499

720

py

Python

qa/rpc-tests/create_cache.py

jtoomim/BitcoinUnlimited

b7b9b59a8440f720c5e0c3d5aeb1bcc4e48f1b9c

[ "MIT" ]

535

2015-09-04T15:10:08.000Z

2022-03-17T20:51:05.000Z

qa/rpc-tests/create_cache.py

jtoomim/BitcoinUnlimited

b7b9b59a8440f720c5e0c3d5aeb1bcc4e48f1b9c

[ "MIT" ]

1,269

2016-01-31T20:21:24.000Z

2022-03-16T01:20:08.000Z

qa/rpc-tests/create_cache.py

jtoomim/BitcoinUnlimited

b7b9b59a8440f720c5e0c3d5aeb1bcc4e48f1b9c

[ "MIT" ]

295

2015-10-19T16:12:29.000Z

2021-08-02T20:05:17.000Z

#!/usr/bin/env python3 # Copyright (c) 2016 The Bitcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. import test_framework.loginit # # Helper script to create the cache # (see BitcoinTestFramework.setup_chain) # from test_framework.test_framework import BitcoinTestFramework class CreateCache(BitcoinTestFramework): def __init__(self): super().__init__() # Test network and test nodes are not required: self.num_nodes = 0 self.nodes = [] def setup_network(self): pass def run_test(self): pass if __name__ == '__main__': CreateCache().main()

24

69

0.708333

import test_framework.loginit from test_framework.test_framework import BitcoinTestFramework class CreateCache(BitcoinTestFramework): def __init__(self): super().__init__() self.num_nodes = 0 self.nodes = [] def setup_network(self): pass def run_test(self): pass if __name__ == '__main__': CreateCache().main()

true

f71885021d239ae2002c7b0633f54ec994ea9bdc

255

py

Python

app/validators/answers/answer_validator.py

ajmaddaford/eq-questionnaire-validator

f1f2540533e01e476ffc0a558f36f8f822a7362c

[ "MIT" ]

1

2021-09-10T12:03:02.000Z

app/validators/answers/answer_validator.py

ajmaddaford/eq-questionnaire-validator

f1f2540533e01e476ffc0a558f36f8f822a7362c

[ "MIT" ]

67

2020-02-05T11:54:27.000Z

2022-03-03T12:55:25.000Z

app/validators/answers/answer_validator.py

ajmaddaford/eq-questionnaire-validator

f1f2540533e01e476ffc0a558f36f8f822a7362c

[ "MIT" ]

2

2021-04-11T07:45:45.000Z

2021-04-19T14:52:07.000Z

from app.validators.validator import Validator class AnswerValidator(Validator): def __init__(self, schema_element): super().__init__(schema_element) self.answer = schema_element self.context["answer_id"] = self.answer["id"]

28.333333

53

0.713725

from app.validators.validator import Validator class AnswerValidator(Validator): def __init__(self, schema_element): super().__init__(schema_element) self.answer = schema_element self.context["answer_id"] = self.answer["id"]

true

f718868cd1db2d24c9fc9a8d1fbfa74f3af35d37

22,294

py

Python

airtest/core/api.py

Aracoix/Airtest

d41737944738e651dd29564c29b88cc4c2e71e2e

[ "Apache-2.0" ]

6,140

2018-01-24T03:27:48.000Z

2022-03-31T14:37:54.000Z

airtest/core/api.py

Aracoix/Airtest

d41737944738e651dd29564c29b88cc4c2e71e2e

[ "Apache-2.0" ]

993

2018-02-02T11:21:40.000Z

2022-03-31T20:41:41.000Z

airtest/core/api.py

Aracoix/Airtest

d41737944738e651dd29564c29b88cc4c2e71e2e

[ "Apache-2.0" ]

1,022

2018-03-05T07:45:22.000Z

2022-03-31T04:29:57.000Z

# -*- coding: utf-8 -*- """ This module contains the Airtest Core APIs. """ import os import time from six.moves.urllib.parse import parse_qsl, urlparse from airtest.core.cv import Template, loop_find, try_log_screen from airtest.core.error import TargetNotFoundError from airtest.core.settings import Settings as ST from airtest.utils.compat import script_log_dir from airtest.core.helper import (G, delay_after_operation, import_device_cls, logwrap, set_logdir, using, log) """ Device Setup APIs """ def init_device(platform="Android", uuid=None, **kwargs): """ Initialize device if not yet, and set as current device. :param platform: Android, IOS or Windows :param uuid: uuid for target device, e.g. serialno for Android, handle for Windows, uuid for iOS :param kwargs: Optional platform specific keyword args, e.g. `cap_method=JAVACAP` for Android :return: device instance :Example: >>> init_device(platform="Android",uuid="SJE5T17B17", cap_method="JAVACAP") >>> init_device(platform="Windows",uuid="123456") """ cls = import_device_cls(platform) dev = cls(uuid, **kwargs) # Add device instance in G and set as current device. G.add_device(dev) return dev def connect_device(uri): """ Initialize device with uri, and set as current device. :param uri: an URI where to connect to device, e.g. `android://adbhost:adbport/serialno?param=value&param2=value2` :return: device instance :Example: >>> connect_device("Android:///") # local adb device using default params >>> # local device with serial number SJE5T17B17 and custom params >>> connect_device("Android:///SJE5T17B17?cap_method=javacap&touch_method=adb") >>> # remote device using custom params Android://adbhost:adbport/serialno >>> connect_device("Android://127.0.0.1:5037/10.254.60.1:5555") >>> connect_device("Windows:///") # connect to the desktop >>> connect_device("Windows:///123456") # Connect to the window with handle 123456 >>> connect_device("iOS:///127.0.0.1:8100") # iOS device """ d = urlparse(uri) platform = d.scheme host = d.netloc uuid = d.path.lstrip("/") params = dict(parse_qsl(d.query)) if host: params["host"] = host.split(":") dev = init_device(platform, uuid, **params) return dev def device(): """ Return the current active device. :return: current device instance :Example: >>> dev = device() >>> dev.touch((100, 100)) """ return G.DEVICE def set_current(idx): """ Set current active device. :param idx: uuid or index of initialized device instance :raise IndexError: raised when device idx is not found :return: None :platforms: Android, iOS, Windows :Example: >>> # switch to the first phone currently connected >>> set_current(0) >>> # switch to the phone with serial number serialno1 >>> set_current("serialno1") """ dev_dict = {dev.uuid: dev for dev in G.DEVICE_LIST} if idx in dev_dict: current_dev = dev_dict[idx] elif isinstance(idx, int) and idx < len(G.DEVICE_LIST): current_dev = G.DEVICE_LIST[idx] else: raise IndexError("device idx not found in: %s or %s" % ( list(dev_dict.keys()), list(range(len(G.DEVICE_LIST))))) G.DEVICE = current_dev def auto_setup(basedir=None, devices=None, logdir=None, project_root=None, compress=None): """ Auto setup running env and try connect android device if not device connected. :param basedir: basedir of script, __file__ is also acceptable. :param devices: connect_device uri in list. :param logdir: log dir for script report, default is None for no log, set to ``True`` for ``<basedir>/log``. :param project_root: project root dir for `using` api. :param compress: The compression rate of the screenshot image, integer in range [1, 99], default is 10 :Example: >>> auto_setup(__file__) >>> auto_setup(__file__, devices=["Android://127.0.0.1:5037/SJE5T17B17"], ... logdir=True, project_root=r"D:\\test\\logs", compress=90) """ if basedir: if os.path.isfile(basedir): basedir = os.path.dirname(basedir) if basedir not in G.BASEDIR: G.BASEDIR.append(basedir) if devices: for dev in devices: connect_device(dev) if logdir: logdir = script_log_dir(basedir, logdir) set_logdir(logdir) if project_root: ST.PROJECT_ROOT = project_root if compress: ST.SNAPSHOT_QUALITY = compress """ Device Operations """ @logwrap def shell(cmd): """ Start remote shell in the target device and execute the command :param cmd: command to be run on device, e.g. "ls /data/local/tmp" :return: the output of the shell cmd :platforms: Android :Example: >>> # Execute commands on the current device adb shell ls >>> print(shell("ls")) >>> # Execute adb instructions for specific devices >>> dev = connect_device("Android:///device1") >>> dev.shell("ls") >>> # Switch to a device and execute the adb command >>> set_current(0) >>> shell("ls") """ return G.DEVICE.shell(cmd) @logwrap def start_app(package, activity=None): """ Start the target application on device :param package: name of the package to be started, e.g. "com.netease.my" :param activity: the activity to start, default is None which means the main activity :return: None :platforms: Android, iOS :Example: >>> start_app("com.netease.cloudmusic") >>> start_app("com.apple.mobilesafari") # on iOS """ G.DEVICE.start_app(package, activity) @logwrap def stop_app(package): """ Stop the target application on device :param package: name of the package to stop, see also `start_app` :return: None :platforms: Android, iOS :Example: >>> stop_app("com.netease.cloudmusic") """ G.DEVICE.stop_app(package) @logwrap def clear_app(package): """ Clear data of the target application on device :param package: name of the package, see also `start_app` :return: None :platforms: Android :Example: >>> clear_app("com.netease.cloudmusic") """ G.DEVICE.clear_app(package) @logwrap def install(filepath, **kwargs): """ Install application on device :param filepath: the path to file to be installed on target device :param kwargs: platform specific `kwargs`, please refer to corresponding docs :return: None :platforms: Android :Example: >>> install(r"D:\\demo\\test.apk") >>> # adb install -r -t D:\\demo\\test.apk >>> install(r"D:\\demo\\test.apk", install_options=["-r", "-t"]) """ return G.DEVICE.install_app(filepath, **kwargs) @logwrap def uninstall(package): """ Uninstall application on device :param package: name of the package, see also `start_app` :return: None :platforms: Android :Example: >>> uninstall("com.netease.cloudmusic") """ return G.DEVICE.uninstall_app(package) @logwrap def snapshot(filename=None, msg="", quality=None, max_size=None): """ Take the screenshot of the target device and save it to the file. :param filename: name of the file where to save the screenshot. If the relative path is provided, the default location is ``ST.LOG_DIR`` :param msg: short description for screenshot, it will be recorded in the report :param quality: The image quality, integer in range [1, 99], default is 10 :param max_size: the maximum size of the picture, e.g 1200 :return: {"screen": filename, "resolution": resolution of the screen} or None :platforms: Android, iOS, Windows :Example: >>> snapshot(msg="index") >>> # save the screenshot to test.jpg >>> snapshot(filename="test.png", msg="test") The quality and size of the screenshot can be set:: >>> # Set the screenshot quality to 30 >>> ST.SNAPSHOT_QUALITY = 30 >>> # Set the screenshot size not to exceed 600*600 >>> # if not set, the default size is the original image size >>> ST.IMAGE_MAXSIZE = 600 >>> # The quality of the screenshot is 30, and the size does not exceed 600*600 >>> touch((100, 100)) >>> # The quality of the screenshot of this sentence is 90 >>> snapshot(filename="test.png", msg="test", quality=90) >>> # The quality of the screenshot is 90, and the size does not exceed 1200*1200 >>> snapshot(filename="test2.png", msg="test", quality=90, max_size=1200) """ if not quality: quality = ST.SNAPSHOT_QUALITY if not max_size and ST.IMAGE_MAXSIZE: max_size = ST.IMAGE_MAXSIZE if filename: if not os.path.isabs(filename): logdir = ST.LOG_DIR or "." filename = os.path.join(logdir, filename) screen = G.DEVICE.snapshot(filename, quality=quality, max_size=max_size) return try_log_screen(screen, quality=quality, max_size=max_size) else: return try_log_screen(quality=quality, max_size=max_size) @logwrap def wake(): """ Wake up and unlock the target device :return: None :platforms: Android :Example: >>> wake() .. note:: Might not work on some models """ G.DEVICE.wake() @logwrap def home(): """ Return to the home screen of the target device. :return: None :platforms: Android, iOS :Example: >>> home() """ G.DEVICE.home() @logwrap def touch(v, times=1, **kwargs): """ Perform the touch action on the device screen :param v: target to touch, either a ``Template`` instance or absolute coordinates (x, y) :param times: how many touches to be performed :param kwargs: platform specific `kwargs`, please refer to corresponding docs :return: finial position to be clicked, e.g. (100, 100) :platforms: Android, Windows, iOS :Example: Click absolute coordinates:: >>> touch((100, 100)) Click the center of the picture(Template object):: >>> touch(Template(r"tpl1606730579419.png", target_pos=5)) Click 2 times:: >>> touch((100, 100), times=2) Under Android and Windows platforms, you can set the click duration:: >>> touch((100, 100), duration=2) Right click(Windows):: >>> touch((100, 100), right_click=True) """ if isinstance(v, Template): pos = loop_find(v, timeout=ST.FIND_TIMEOUT) else: try_log_screen() pos = v for _ in range(times): G.DEVICE.touch(pos, **kwargs) time.sleep(0.05) delay_after_operation() return pos click = touch # click is alias of touch @logwrap def double_click(v): """ Perform double click :param v: target to touch, either a ``Template`` instance or absolute coordinates (x, y) :return: finial position to be clicked :Example: >>> double_click((100, 100)) >>> double_click(Template(r"tpl1606730579419.png")) """ if isinstance(v, Template): pos = loop_find(v, timeout=ST.FIND_TIMEOUT) else: try_log_screen() pos = v G.DEVICE.double_click(pos) delay_after_operation() return pos @logwrap def swipe(v1, v2=None, vector=None, **kwargs): """ Perform the swipe action on the device screen. There are two ways of assigning the parameters * ``swipe(v1, v2=Template(...))`` # swipe from v1 to v2 * ``swipe(v1, vector=(x, y))`` # swipe starts at v1 and moves along the vector. :param v1: the start point of swipe, either a Template instance or absolute coordinates (x, y) :param v2: the end point of swipe, either a Template instance or absolute coordinates (x, y) :param vector: a vector coordinates of swipe action, either absolute coordinates (x, y) or percentage of screen e.g.(0.5, 0.5) :param **kwargs: platform specific `kwargs`, please refer to corresponding docs :raise Exception: general exception when not enough parameters to perform swap action have been provided :return: Origin position and target position :platforms: Android, Windows, iOS :Example: >>> swipe(Template(r"tpl1606814865574.png"), vector=[-0.0316, -0.3311]) >>> swipe((100, 100), (200, 200)) Custom swiping duration and number of steps(Android and iOS):: >>> # swiping lasts for 1 second, divided into 6 steps >>> swipe((100, 100), (200, 200), duration=1, steps=6) """ if isinstance(v1, Template): pos1 = loop_find(v1, timeout=ST.FIND_TIMEOUT) else: try_log_screen() pos1 = v1 if v2: if isinstance(v2, Template): pos2 = loop_find(v2, timeout=ST.FIND_TIMEOUT_TMP) else: pos2 = v2 elif vector: if vector[0] <= 1 and vector[1] <= 1: w, h = G.DEVICE.get_current_resolution() vector = (int(vector[0] * w), int(vector[1] * h)) pos2 = (pos1[0] + vector[0], pos1[1] + vector[1]) else: raise Exception("no enough params for swipe") G.DEVICE.swipe(pos1, pos2, **kwargs) delay_after_operation() return pos1, pos2 @logwrap def pinch(in_or_out='in', center=None, percent=0.5): """ Perform the pinch action on the device screen :param in_or_out: pinch in or pinch out, enum in ["in", "out"] :param center: center of pinch action, default as None which is the center of the screen :param percent: percentage of the screen of pinch action, default is 0.5 :return: None :platforms: Android :Example: Pinch in the center of the screen with two fingers:: >>> pinch() Take (100,100) as the center and slide out with two fingers:: >>> pinch('out', center=(100, 100)) """ try_log_screen() G.DEVICE.pinch(in_or_out=in_or_out, center=center, percent=percent) delay_after_operation() @logwrap def keyevent(keyname, **kwargs): """ Perform key event on the device :param keyname: platform specific key name :param **kwargs: platform specific `kwargs`, please refer to corresponding docs :return: None :platforms: Android, Windows, iOS :Example: * ``Android``: it is equivalent to executing ``adb shell input keyevent KEYNAME`` :: >>> keyevent("HOME") >>> # The constant corresponding to the home key is 3 >>> keyevent("3") # same as keyevent("HOME") >>> keyevent("BACK") >>> keyevent("KEYCODE_DEL") .. seealso:: Module :py:mod:`airtest.core.android.adb.ADB.keyevent` Equivalent to calling the ``android.adb.keyevent()`` `Android Keyevent <https://developer.android.com/reference/android/view/KeyEvent#constants_1>`_ Documentation for more ``Android.KeyEvent`` * ``Windows``: Use ``pywinauto.keyboard`` module for key input:: >>> keyevent("{DEL}") >>> keyevent("%{F4}") # close an active window with Alt+F4 .. seealso:: Module :py:mod:`airtest.core.win.win.Windows.keyevent` `pywinauto.keyboard <https://pywinauto.readthedocs.io/en/latest/code/pywinauto.keyboard.html>`_ Documentation for ``pywinauto.keyboard`` * ``iOS``: Only supports home/volumeUp/volumeDown:: >>> keyevent("HOME") >>> keyevent("volumeUp") """ G.DEVICE.keyevent(keyname, **kwargs) delay_after_operation() @logwrap def text(text, enter=True, **kwargs): """ Input text on the target device. Text input widget must be active first. :param text: text to input, unicode is supported :param enter: input `Enter` keyevent after text input, default is True :return: None :platforms: Android, Windows, iOS :Example: >>> text("test") >>> text("test", enter=False) On Android, sometimes you need to click the search button after typing:: >>> text("test", search=True) .. seealso:: Module :py:mod:`airtest.core.android.ime.YosemiteIme.code` If you want to enter other keys on the keyboard, you can use the interface:: >>> text("test") >>> device().yosemite_ime.code("3") # 3 = IME_ACTION_SEARCH Ref: `Editor Action Code <http://developer.android.com/reference/android/view/inputmethod/EditorInfo.html>`_ """ G.DEVICE.text(text, enter=enter, **kwargs) delay_after_operation() @logwrap def sleep(secs=1.0): """ Set the sleep interval. It will be recorded in the report :param secs: seconds to sleep :return: None :platforms: Android, Windows, iOS :Example: >>> sleep(1) """ time.sleep(secs) @logwrap def wait(v, timeout=None, interval=0.5, intervalfunc=None): """ Wait to match the Template on the device screen :param v: target object to wait for, Template instance :param timeout: time interval to wait for the match, default is None which is ``ST.FIND_TIMEOUT`` :param interval: time interval in seconds to attempt to find a match :param intervalfunc: called after each unsuccessful attempt to find the corresponding match :raise TargetNotFoundError: raised if target is not found after the time limit expired :return: coordinates of the matched target :platforms: Android, Windows, iOS :Example: >>> wait(Template(r"tpl1606821804906.png")) # timeout after ST.FIND_TIMEOUT >>> # find Template every 3 seconds, timeout after 120 seconds >>> wait(Template(r"tpl1606821804906.png"), timeout=120, interval=3) You can specify a callback function every time the search target fails:: >>> def notfound(): >>> print("No target found") >>> wait(Template(r"tpl1607510661400.png"), intervalfunc=notfound) """ timeout = timeout or ST.FIND_TIMEOUT pos = loop_find(v, timeout=timeout, interval=interval, intervalfunc=intervalfunc) return pos @logwrap def exists(v): """ Check whether given target exists on device screen :param v: target to be checked :return: False if target is not found, otherwise returns the coordinates of the target :platforms: Android, Windows, iOS :Example: >>> if exists(Template(r"tpl1606822430589.png")): >>> touch(Template(r"tpl1606822430589.png")) Since ``exists()`` will return the coordinates, we can directly click on this return value to reduce one image search:: >>> pos = exists(Template(r"tpl1606822430589.png")) >>> if pos: >>> touch(pos) """ try: pos = loop_find(v, timeout=ST.FIND_TIMEOUT_TMP) except TargetNotFoundError: return False else: return pos @logwrap def find_all(v): """ Find all occurrences of the target on the device screen and return their coordinates :param v: target to find :return: list of results, [{'result': (x, y), 'rectangle': ( (left_top, left_bottom, right_bottom, right_top) ), 'confidence': 0.9}, ...] :platforms: Android, Windows, iOS :Example: >>> find_all(Template(r"tpl1607511235111.png")) [{'result': (218, 468), 'rectangle': ((149, 440), (149, 496), (288, 496), (288, 440)), 'confidence': 0.9999996423721313}] """ screen = G.DEVICE.snapshot(quality=ST.SNAPSHOT_QUALITY) return v.match_all_in(screen) """ Assertions """ @logwrap def assert_exists(v, msg=""): """ Assert target exists on device screen :param v: target to be checked :param msg: short description of assertion, it will be recorded in the report :raise AssertionError: if assertion fails :return: coordinates of the target :platforms: Android, Windows, iOS :Example: >>> assert_exists(Template(r"tpl1607324047907.png"), "assert exists") """ try: pos = loop_find(v, timeout=ST.FIND_TIMEOUT, threshold=ST.THRESHOLD_STRICT or v.threshold) return pos except TargetNotFoundError: raise AssertionError("%s does not exist in screen, message: %s" % (v, msg)) @logwrap def assert_not_exists(v, msg=""): """ Assert target does not exist on device screen :param v: target to be checked :param msg: short description of assertion, it will be recorded in the report :raise AssertionError: if assertion fails :return: None. :platforms: Android, Windows, iOS :Example: >>> assert_not_exists(Template(r"tpl1607324047907.png"), "assert not exists") """ try: pos = loop_find(v, timeout=ST.FIND_TIMEOUT_TMP) raise AssertionError("%s exists unexpectedly at pos: %s, message: %s" % (v, pos, msg)) except TargetNotFoundError: pass @logwrap def assert_equal(first, second, msg=""): """ Assert two values are equal :param first: first value :param second: second value :param msg: short description of assertion, it will be recorded in the report :raise AssertionError: if assertion fails :return: None :platforms: Android, Windows, iOS :Example: >>> assert_equal(1, 1, msg="assert 1==1") """ if first != second: raise AssertionError("%s and %s are not equal, message: %s" % (first, second, msg)) @logwrap def assert_not_equal(first, second, msg=""): """ Assert two values are not equal :param first: first value :param second: second value :param msg: short description of assertion, it will be recorded in the report :raise AssertionError: if assertion :return: None :platforms: Android, Windows, iOS :Example: >>> assert_not_equal(1, 2, msg="assert 1!=2") """ if first == second: raise AssertionError("%s and %s are equal, message: %s" % (first, second, msg))

30.581619

127

0.632906

import os import time from six.moves.urllib.parse import parse_qsl, urlparse from airtest.core.cv import Template, loop_find, try_log_screen from airtest.core.error import TargetNotFoundError from airtest.core.settings import Settings as ST from airtest.utils.compat import script_log_dir from airtest.core.helper import (G, delay_after_operation, import_device_cls, logwrap, set_logdir, using, log) def init_device(platform="Android", uuid=None, **kwargs): cls = import_device_cls(platform) dev = cls(uuid, **kwargs) G.add_device(dev) return dev def connect_device(uri): d = urlparse(uri) platform = d.scheme host = d.netloc uuid = d.path.lstrip("/") params = dict(parse_qsl(d.query)) if host: params["host"] = host.split(":") dev = init_device(platform, uuid, **params) return dev def device(): return G.DEVICE def set_current(idx): dev_dict = {dev.uuid: dev for dev in G.DEVICE_LIST} if idx in dev_dict: current_dev = dev_dict[idx] elif isinstance(idx, int) and idx < len(G.DEVICE_LIST): current_dev = G.DEVICE_LIST[idx] else: raise IndexError("device idx not found in: %s or %s" % ( list(dev_dict.keys()), list(range(len(G.DEVICE_LIST))))) G.DEVICE = current_dev def auto_setup(basedir=None, devices=None, logdir=None, project_root=None, compress=None): if basedir: if os.path.isfile(basedir): basedir = os.path.dirname(basedir) if basedir not in G.BASEDIR: G.BASEDIR.append(basedir) if devices: for dev in devices: connect_device(dev) if logdir: logdir = script_log_dir(basedir, logdir) set_logdir(logdir) if project_root: ST.PROJECT_ROOT = project_root if compress: ST.SNAPSHOT_QUALITY = compress @logwrap def shell(cmd): return G.DEVICE.shell(cmd) @logwrap def start_app(package, activity=None): G.DEVICE.start_app(package, activity) @logwrap def stop_app(package): G.DEVICE.stop_app(package) @logwrap def clear_app(package): G.DEVICE.clear_app(package) @logwrap def install(filepath, **kwargs): return G.DEVICE.install_app(filepath, **kwargs) @logwrap def uninstall(package): return G.DEVICE.uninstall_app(package) @logwrap def snapshot(filename=None, msg="", quality=None, max_size=None): if not quality: quality = ST.SNAPSHOT_QUALITY if not max_size and ST.IMAGE_MAXSIZE: max_size = ST.IMAGE_MAXSIZE if filename: if not os.path.isabs(filename): logdir = ST.LOG_DIR or "." filename = os.path.join(logdir, filename) screen = G.DEVICE.snapshot(filename, quality=quality, max_size=max_size) return try_log_screen(screen, quality=quality, max_size=max_size) else: return try_log_screen(quality=quality, max_size=max_size) @logwrap def wake(): G.DEVICE.wake() @logwrap def home(): G.DEVICE.home() @logwrap def touch(v, times=1, **kwargs): if isinstance(v, Template): pos = loop_find(v, timeout=ST.FIND_TIMEOUT) else: try_log_screen() pos = v for _ in range(times): G.DEVICE.touch(pos, **kwargs) time.sleep(0.05) delay_after_operation() return pos click = touch @logwrap def double_click(v): if isinstance(v, Template): pos = loop_find(v, timeout=ST.FIND_TIMEOUT) else: try_log_screen() pos = v G.DEVICE.double_click(pos) delay_after_operation() return pos @logwrap def swipe(v1, v2=None, vector=None, **kwargs): if isinstance(v1, Template): pos1 = loop_find(v1, timeout=ST.FIND_TIMEOUT) else: try_log_screen() pos1 = v1 if v2: if isinstance(v2, Template): pos2 = loop_find(v2, timeout=ST.FIND_TIMEOUT_TMP) else: pos2 = v2 elif vector: if vector[0] <= 1 and vector[1] <= 1: w, h = G.DEVICE.get_current_resolution() vector = (int(vector[0] * w), int(vector[1] * h)) pos2 = (pos1[0] + vector[0], pos1[1] + vector[1]) else: raise Exception("no enough params for swipe") G.DEVICE.swipe(pos1, pos2, **kwargs) delay_after_operation() return pos1, pos2 @logwrap def pinch(in_or_out='in', center=None, percent=0.5): try_log_screen() G.DEVICE.pinch(in_or_out=in_or_out, center=center, percent=percent) delay_after_operation() @logwrap def keyevent(keyname, **kwargs): G.DEVICE.keyevent(keyname, **kwargs) delay_after_operation() @logwrap def text(text, enter=True, **kwargs): G.DEVICE.text(text, enter=enter, **kwargs) delay_after_operation() @logwrap def sleep(secs=1.0): time.sleep(secs) @logwrap def wait(v, timeout=None, interval=0.5, intervalfunc=None): timeout = timeout or ST.FIND_TIMEOUT pos = loop_find(v, timeout=timeout, interval=interval, intervalfunc=intervalfunc) return pos @logwrap def exists(v): try: pos = loop_find(v, timeout=ST.FIND_TIMEOUT_TMP) except TargetNotFoundError: return False else: return pos @logwrap def find_all(v): screen = G.DEVICE.snapshot(quality=ST.SNAPSHOT_QUALITY) return v.match_all_in(screen) @logwrap def assert_exists(v, msg=""): try: pos = loop_find(v, timeout=ST.FIND_TIMEOUT, threshold=ST.THRESHOLD_STRICT or v.threshold) return pos except TargetNotFoundError: raise AssertionError("%s does not exist in screen, message: %s" % (v, msg)) @logwrap def assert_not_exists(v, msg=""): try: pos = loop_find(v, timeout=ST.FIND_TIMEOUT_TMP) raise AssertionError("%s exists unexpectedly at pos: %s, message: %s" % (v, pos, msg)) except TargetNotFoundError: pass @logwrap def assert_equal(first, second, msg=""): if first != second: raise AssertionError("%s and %s are not equal, message: %s" % (first, second, msg)) @logwrap def assert_not_equal(first, second, msg=""): if first == second: raise AssertionError("%s and %s are equal, message: %s" % (first, second, msg))

true

f71886a55daf56e9ad908610ff29c7fc570805ef

3,988

py

Python

model_zoo/official/recommend/wide_and_deep_multitable/train_and_eval.py

huxian123/mindspore

ec5ba10c82bbd6eccafe32d3a1149add90105bc8

[ "Apache-2.0" ]

1

2021-04-23T06:35:18.000Z

model_zoo/official/recommend/wide_and_deep_multitable/train_and_eval.py

nudt-eddie/mindspore

55372b41fdfae6d2b88d7078971e06d537f6c558

[ "Apache-2.0" ]

null

model_zoo/official/recommend/wide_and_deep_multitable/train_and_eval.py

nudt-eddie/mindspore

55372b41fdfae6d2b88d7078971e06d537f6c558

[ "Apache-2.0" ]

null

# Copyright 2020 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """ training_and_evaluating """ import os import sys from mindspore import Model, context from mindspore.train.callback import ModelCheckpoint, CheckpointConfig from mindspore.train.callback import TimeMonitor from src.wide_and_deep import PredictWithSigmoid, TrainStepWrap, NetWithLossClass, WideDeepModel from src.callbacks import LossCallBack, EvalCallBack from src.datasets import create_dataset, compute_emb_dim from src.metrics import AUCMetric from src.config import WideDeepConfig sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) def get_WideDeep_net(config): """ Get network of wide&deep model. """ WideDeep_net = WideDeepModel(config) loss_net = NetWithLossClass(WideDeep_net, config) train_net = TrainStepWrap(loss_net, config) eval_net = PredictWithSigmoid(WideDeep_net) return train_net, eval_net class ModelBuilder(): """ ModelBuilder. """ def __init__(self): pass def get_hook(self): pass def get_train_hook(self): hooks = [] callback = LossCallBack() hooks.append(callback) if int(os.getenv('DEVICE_ID')) == 0: pass return hooks def get_net(self, config): return get_WideDeep_net(config) def train_and_eval(config): """ train_and_eval. """ data_path = config.data_path epochs = config.epochs print("epochs is {}".format(epochs)) ds_train = create_dataset(data_path, train_mode=True, epochs=1, batch_size=config.batch_size, is_tf_dataset=config.is_tf_dataset) ds_eval = create_dataset(data_path, train_mode=False, epochs=1, batch_size=config.batch_size, is_tf_dataset=config.is_tf_dataset) print("ds_train.size: {}".format(ds_train.get_dataset_size())) print("ds_eval.size: {}".format(ds_eval.get_dataset_size())) net_builder = ModelBuilder() train_net, eval_net = net_builder.get_net(config) train_net.set_train() auc_metric = AUCMetric() model = Model(train_net, eval_network=eval_net, metrics={"auc": auc_metric}) eval_callback = EvalCallBack(model, ds_eval, auc_metric, config) callback = LossCallBack(config) # Only save the last checkpoint at the last epoch. For saving epochs at each epoch, please # set save_checkpoint_steps=ds_train.get_dataset_size() ckptconfig = CheckpointConfig(save_checkpoint_steps=ds_train.get_dataset_size()*config.epochs, keep_checkpoint_max=10) ckpoint_cb = ModelCheckpoint(prefix='widedeep_train', directory=config.ckpt_path, config=ckptconfig) model.train(epochs, ds_train, callbacks=[TimeMonitor(ds_train.get_dataset_size()), eval_callback, callback, ckpoint_cb], sink_size=ds_train.get_dataset_size()) if __name__ == "__main__": wide_and_deep_config = WideDeepConfig() wide_and_deep_config.argparse_init() compute_emb_dim(wide_and_deep_config) context.set_context(mode=context.GRAPH_MODE, device_target="Davinci", save_graphs=True) train_and_eval(wide_and_deep_config)

36.254545

107

0.675527

import os import sys from mindspore import Model, context from mindspore.train.callback import ModelCheckpoint, CheckpointConfig from mindspore.train.callback import TimeMonitor from src.wide_and_deep import PredictWithSigmoid, TrainStepWrap, NetWithLossClass, WideDeepModel from src.callbacks import LossCallBack, EvalCallBack from src.datasets import create_dataset, compute_emb_dim from src.metrics import AUCMetric from src.config import WideDeepConfig sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) def get_WideDeep_net(config): WideDeep_net = WideDeepModel(config) loss_net = NetWithLossClass(WideDeep_net, config) train_net = TrainStepWrap(loss_net, config) eval_net = PredictWithSigmoid(WideDeep_net) return train_net, eval_net class ModelBuilder(): def __init__(self): pass def get_hook(self): pass def get_train_hook(self): hooks = [] callback = LossCallBack() hooks.append(callback) if int(os.getenv('DEVICE_ID')) == 0: pass return hooks def get_net(self, config): return get_WideDeep_net(config) def train_and_eval(config): data_path = config.data_path epochs = config.epochs print("epochs is {}".format(epochs)) ds_train = create_dataset(data_path, train_mode=True, epochs=1, batch_size=config.batch_size, is_tf_dataset=config.is_tf_dataset) ds_eval = create_dataset(data_path, train_mode=False, epochs=1, batch_size=config.batch_size, is_tf_dataset=config.is_tf_dataset) print("ds_train.size: {}".format(ds_train.get_dataset_size())) print("ds_eval.size: {}".format(ds_eval.get_dataset_size())) net_builder = ModelBuilder() train_net, eval_net = net_builder.get_net(config) train_net.set_train() auc_metric = AUCMetric() model = Model(train_net, eval_network=eval_net, metrics={"auc": auc_metric}) eval_callback = EvalCallBack(model, ds_eval, auc_metric, config) callback = LossCallBack(config) ckptconfig = CheckpointConfig(save_checkpoint_steps=ds_train.get_dataset_size()*config.epochs, keep_checkpoint_max=10) ckpoint_cb = ModelCheckpoint(prefix='widedeep_train', directory=config.ckpt_path, config=ckptconfig) model.train(epochs, ds_train, callbacks=[TimeMonitor(ds_train.get_dataset_size()), eval_callback, callback, ckpoint_cb], sink_size=ds_train.get_dataset_size()) if __name__ == "__main__": wide_and_deep_config = WideDeepConfig() wide_and_deep_config.argparse_init() compute_emb_dim(wide_and_deep_config) context.set_context(mode=context.GRAPH_MODE, device_target="Davinci", save_graphs=True) train_and_eval(wide_and_deep_config)

true

f71887a83f72a2a2fe70f9569cd374a4db495fcc

242

py

Python

easilyb/file_ops/_file_ops.py

xaled/easilyb

cdb5f738205f700b37e03c50d04061a2d1e730cc

[ "MIT" ]

null

easilyb/file_ops/_file_ops.py

xaled/easilyb

cdb5f738205f700b37e03c50d04061a2d1e730cc

[ "MIT" ]

null

easilyb/file_ops/_file_ops.py

xaled/easilyb

cdb5f738205f700b37e03c50d04061a2d1e730cc

[ "MIT" ]

null

import logging logger = logging.getLogger(__name__) def read_all(sock): sock.settimeout(5.0) data = "" while True: part = sock.recv(4096) data += part if len(part) < 4096: break return data

20.166667

36

0.57438

import logging logger = logging.getLogger(__name__) def read_all(sock): sock.settimeout(5.0) data = "" while True: part = sock.recv(4096) data += part if len(part) < 4096: break return data

true

f71887d368f45f3ec2e13e47d2be1ae91cb6c737

4,803

py

Python

python_anon/PlotLetterROC.py

MaviccPRP/Anonymizer

3d75ed3e97e260b6ded7e188eb3d58d749844e36

[ "MIT" ]

null

python_anon/PlotLetterROC.py

MaviccPRP/Anonymizer

3d75ed3e97e260b6ded7e188eb3d58d749844e36

[ "MIT" ]

2

2019-06-14T19:55:39.000Z

2019-06-14T20:16:11.000Z

python_anon/PlotLetterROC.py

MaviccPRP/Anonymizer

3d75ed3e97e260b6ded7e188eb3d58d749844e36

[ "MIT" ]

1

2020-03-13T14:32:31.000Z

#!/usr/env/python """ Author: Ralf Hauenschild E-Mail: ralf_hauenschild@gmx.de """ import sys import os import numpy import matplotlib import matplotlib as mpl import matplotlib.pyplot as plt import pylab as py import matplotlib.cm as cm import math c = [] sens = [] # sens (recall) senserror = [] specloss = [] # 1-spec specerror = [] p = [] # ppv (precision) perror = [] for i in range(1, len(sys.argv)): if sys.argv[i] != "distinct": c.append([]) sens.append([]) # sens (recall) senserror.append([]) specloss.append([]) # 1-spec specerror.append([]) p.append([]) # ppv (precision) perror.append([]) infile = open(sys.argv[i], "r") line = infile.readline() while len(line) > 4: splitlist = line[:-1].split("\t") if "distinct" in sys.argv[i]: c[i-1].append(float(splitlist[1])) sens[i-1].append(float(splitlist[21])) senserror[i-1].append(float(splitlist[23])) specloss[i-1].append(1-float(splitlist[33])) specerror[i-1].append(float(splitlist[35])) p[i-1].append(float(splitlist[27])) perror[i-1].append(float(splitlist[29])) else: c[i-1].append(float(splitlist[1])) sens[i-1].append(float(splitlist[3])) senserror[i-1].append(float(splitlist[5])) specloss[i-1].append(1-float(splitlist[15])) specerror[i-1].append(float(splitlist[17])) p[i-1].append(float(splitlist[9])) perror[i-1].append(float(splitlist[11])) line = infile.readline() infile.close() fig = py.figure(1, figsize=(12, 6)) py.subplots_adjust(top=0.8) linestyles = ["-", "--"] #colors=[cb.to_rgba(value) for value in c] norm=mpl.colors.Normalize(vmin=min(c[0]), vmax=max(c[0])) fig.suptitle("Anonymization performance assessment under sliding PPV threshold\nfor words leading X-ed out training content") #labels = ["-1 leader only", "-1 & -2 leader indep."] labels = ["X-out events", "word-distinct X-out events"] handles = [] m = cm.ScalarMappable(norm=norm, cmap=cm.jet) ax = fig.add_subplot(121) for column in range(0, len(specloss)): for i in range(1, len(specloss[column])): aplot, = ax.plot(specloss[column][i-1:i+1], sens[column][i-1:i+1], linestyles[column], color=m.to_rgba(numpy.mean(c[column][i-1:i+1])), linewidth=3) for i in range(0, len(specloss[column])): ax.errorbar(specloss[column][i:i+1], sens[column][i:i+1], xerr=specerror[column][i:i+1], yerr=senserror[column][i:i+1], marker='o', fmt='-o', linewidth=3, color=m.to_rgba(c[column][i])) group1 = ax.scatter(specloss[column], sens[column], c=c[column], cmap=cm.jet, norm=norm, alpha=0) import matplotlib.ticker as ticker #, format=ticker.FormatStrFormatter('%.0f') cb = py.colorbar(group1) cb.set_alpha(1) cb.draw_all() cb.ax.set_ylabel("PPV threshold for feature to be considered in model") py.xlim(xmin=0) py.ylim(ymin=0) py.xlabel("FPR (1-specificity)") py.ylabel("TPR (sensitivity)") py.title("ROC") a, = ax.plot([-1, -1], [-1, -1], linestyles[0], color=m.to_rgba(c[column][0]), linewidth=3) b, = ax.plot([-1, -1], [-1, -1], linestyles[1], color=m.to_rgba(c[column][0]), linewidth=3) #plt.legend([a, b], labels, loc='lower right') #plt.legend(handles=handles, labels=labels) ax = fig.add_subplot(122) for column in range(0, len(specloss)): print sens[column] for i in range(1, len(specloss[column])): ax.plot(sens[column][i-1:i+1], p[column][i-1:i+1], linestyles[column], color=m.to_rgba(numpy.mean(c[column][i-1:i+1])), linewidth=3) for i in range(0, len(specloss[column])): ax.errorbar(sens[column][i:i+1], p[column][i:i+1], xerr=senserror[column][i:i+1], yerr=perror[column][i:i+1], marker='o', fmt='-o', linewidth=3, color=m.to_rgba(c[column][i])) cb = py.colorbar(group1) cb.set_alpha(1) cb.draw_all() cb.ax.set_ylabel("PPV threshold for feature to be considered in model") py.xlim(xmin=0, xmax=1) py.ylim(ymin=0, ymax=1) py.xlabel("sensitivity (recall)") py.ylabel("PPV (precision)") py.title("P/R (precision by recall)") a, = ax.plot([-1, -1], [-1, -1], linestyles[0], color=m.to_rgba(c[column][0]), linewidth=3) b, = ax.plot([-1, -1], [-1, -1], linestyles[1], color=m.to_rgba(c[column][0]), linewidth=3) #plt.legend([a, b], labels, loc='lower left') auc = round(numpy.trapz(y=[item for item in sens[0][::-1]], x=[item for item in specloss[0][::-1]]) / numpy.trapz(y=[1.0 for item in sens[0][::-1]], x=[item for item in specloss[0][::-1]]), 4) print "AUC:", auc plt.savefig(sys.argv[1] + ".roc" + "_auc_" + str(auc) + ".svg") plt.show() plt.close()

32.452703

193

0.609827

""" Author: Ralf Hauenschild E-Mail: ralf_hauenschild@gmx.de """ import sys import os import numpy import matplotlib import matplotlib as mpl import matplotlib.pyplot as plt import pylab as py import matplotlib.cm as cm import math c = [] sens = [] senserror = [] specloss = [] specerror = [] p = [] perror = [] for i in range(1, len(sys.argv)): if sys.argv[i] != "distinct": c.append([]) sens.append([]) senserror.append([]) specloss.append([]) specerror.append([]) p.append([]) perror.append([]) infile = open(sys.argv[i], "r") line = infile.readline() while len(line) > 4: splitlist = line[:-1].split("\t") if "distinct" in sys.argv[i]: c[i-1].append(float(splitlist[1])) sens[i-1].append(float(splitlist[21])) senserror[i-1].append(float(splitlist[23])) specloss[i-1].append(1-float(splitlist[33])) specerror[i-1].append(float(splitlist[35])) p[i-1].append(float(splitlist[27])) perror[i-1].append(float(splitlist[29])) else: c[i-1].append(float(splitlist[1])) sens[i-1].append(float(splitlist[3])) senserror[i-1].append(float(splitlist[5])) specloss[i-1].append(1-float(splitlist[15])) specerror[i-1].append(float(splitlist[17])) p[i-1].append(float(splitlist[9])) perror[i-1].append(float(splitlist[11])) line = infile.readline() infile.close() fig = py.figure(1, figsize=(12, 6)) py.subplots_adjust(top=0.8) linestyles = ["-", "--"] norm=mpl.colors.Normalize(vmin=min(c[0]), vmax=max(c[0])) fig.suptitle("Anonymization performance assessment under sliding PPV threshold\nfor words leading X-ed out training content") labels = ["X-out events", "word-distinct X-out events"] handles = [] m = cm.ScalarMappable(norm=norm, cmap=cm.jet) ax = fig.add_subplot(121) for column in range(0, len(specloss)): for i in range(1, len(specloss[column])): aplot, = ax.plot(specloss[column][i-1:i+1], sens[column][i-1:i+1], linestyles[column], color=m.to_rgba(numpy.mean(c[column][i-1:i+1])), linewidth=3) for i in range(0, len(specloss[column])): ax.errorbar(specloss[column][i:i+1], sens[column][i:i+1], xerr=specerror[column][i:i+1], yerr=senserror[column][i:i+1], marker='o', fmt='-o', linewidth=3, color=m.to_rgba(c[column][i])) group1 = ax.scatter(specloss[column], sens[column], c=c[column], cmap=cm.jet, norm=norm, alpha=0) import matplotlib.ticker as ticker cb = py.colorbar(group1) cb.set_alpha(1) cb.draw_all() cb.ax.set_ylabel("PPV threshold for feature to be considered in model") py.xlim(xmin=0) py.ylim(ymin=0) py.xlabel("FPR (1-specificity)") py.ylabel("TPR (sensitivity)") py.title("ROC") a, = ax.plot([-1, -1], [-1, -1], linestyles[0], color=m.to_rgba(c[column][0]), linewidth=3) b, = ax.plot([-1, -1], [-1, -1], linestyles[1], color=m.to_rgba(c[column][0]), linewidth=3) ax = fig.add_subplot(122) for column in range(0, len(specloss)): print sens[column] for i in range(1, len(specloss[column])): ax.plot(sens[column][i-1:i+1], p[column][i-1:i+1], linestyles[column], color=m.to_rgba(numpy.mean(c[column][i-1:i+1])), linewidth=3) for i in range(0, len(specloss[column])): ax.errorbar(sens[column][i:i+1], p[column][i:i+1], xerr=senserror[column][i:i+1], yerr=perror[column][i:i+1], marker='o', fmt='-o', linewidth=3, color=m.to_rgba(c[column][i])) cb = py.colorbar(group1) cb.set_alpha(1) cb.draw_all() cb.ax.set_ylabel("PPV threshold for feature to be considered in model") py.xlim(xmin=0, xmax=1) py.ylim(ymin=0, ymax=1) py.xlabel("sensitivity (recall)") py.ylabel("PPV (precision)") py.title("P/R (precision by recall)") a, = ax.plot([-1, -1], [-1, -1], linestyles[0], color=m.to_rgba(c[column][0]), linewidth=3) b, = ax.plot([-1, -1], [-1, -1], linestyles[1], color=m.to_rgba(c[column][0]), linewidth=3) auc = round(numpy.trapz(y=[item for item in sens[0][::-1]], x=[item for item in specloss[0][::-1]]) / numpy.trapz(y=[1.0 for item in sens[0][::-1]], x=[item for item in specloss[0][::-1]]), 4) print "AUC:", auc plt.savefig(sys.argv[1] + ".roc" + "_auc_" + str(auc) + ".svg") plt.show() plt.close()

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true

f718889a61bd413f4f9ce078cd48cee4a7b368ac

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Python

tests/keras/test_callbacks.py

mdand2000/keras-team-keras

5eecd55a6f1d6d149b42f9b76aa53d4c5ab8d3eb

[ "MIT" ]

2

2019-09-17T22:01:41.000Z

2020-05-30T05:48:14.000Z

tests/keras/test_callbacks.py

mdand2000/keras-team-keras

5eecd55a6f1d6d149b42f9b76aa53d4c5ab8d3eb

[ "MIT" ]

null

tests/keras/test_callbacks.py

mdand2000/keras-team-keras

5eecd55a6f1d6d149b42f9b76aa53d4c5ab8d3eb

[ "MIT" ]

3

2019-08-12T18:15:17.000Z

2021-06-20T19:40:13.000Z

import os import multiprocessing import numpy as np import pytest from csv import reader from csv import Sniffer import shutil from keras import optimizers from keras import initializers from keras import callbacks from keras.models import Sequential, Model from keras.layers import Input, Dense, Dropout, add, dot, Lambda from keras.layers.convolutional import Conv2D from keras.layers.pooling import MaxPooling2D, GlobalAveragePooling1D, GlobalAveragePooling2D from keras.utils.test_utils import get_test_data from keras.utils.test_utils import keras_test from keras import backend as K from keras.utils import np_utils try: from unittest.mock import patch except: from mock import patch input_dim = 2 num_hidden = 4 num_classes = 2 batch_size = 5 train_samples = 20 test_samples = 20 @keras_test def test_TerminateOnNaN(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) cbks = [callbacks.TerminateOnNaN()] model = Sequential() initializer = initializers.Constant(value=1e5) for _ in range(5): model.add(Dense(num_hidden, input_dim=input_dim, activation='relu', kernel_initializer=initializer)) model.add(Dense(num_classes, activation='linear')) model.compile(loss='mean_squared_error', optimizer='rmsprop') # case 1 fit history = model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=20) loss = history.history['loss'] assert len(loss) == 1 assert loss[0] == np.inf # case 2 fit_generator def data_generator(): max_batch_index = len(X_train) // batch_size i = 0 while 1: yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) i += 1 i = i % max_batch_index history = model.fit_generator(data_generator(), len(X_train), validation_data=(X_test, y_test), callbacks=cbks, epochs=20) loss = history.history['loss'] assert len(loss) == 1 assert loss[0] == np.inf or np.isnan(loss[0]) @keras_test def test_stop_training_csv(tmpdir): np.random.seed(1337) fp = str(tmpdir / 'test.csv') (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) cbks = [callbacks.TerminateOnNaN(), callbacks.CSVLogger(fp)] model = Sequential() for _ in range(5): model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='linear')) model.compile(loss='mean_squared_error', optimizer='rmsprop') def data_generator(): i = 0 max_batch_index = len(X_train) // batch_size tot = 0 while 1: if tot > 3 * len(X_train): yield np.ones([batch_size, input_dim]) * np.nan, np.ones([batch_size, num_classes]) * np.nan else: yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) i += 1 tot += 1 i = i % max_batch_index history = model.fit_generator(data_generator(), len(X_train) // batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=20) loss = history.history['loss'] assert len(loss) > 1 assert loss[-1] == np.inf or np.isnan(loss[-1]) values = [] with open(fp) as f: for x in reader(f): values.append(x) assert 'nan' in values[-1], 'The last epoch was not logged.' os.remove(fp) @keras_test def test_ModelCheckpoint(tmpdir): np.random.seed(1337) filepath = str(tmpdir / 'checkpoint.h5') (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) # case 1 monitor = 'val_loss' save_best_only = False mode = 'auto' model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) os.remove(filepath) # case 2 mode = 'min' cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) os.remove(filepath) # case 3 mode = 'max' monitor = 'val_acc' cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) os.remove(filepath) # case 4 save_best_only = True cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) os.remove(filepath) # case 5 save_best_only = False period = 2 mode = 'auto' filepath = 'checkpoint.{epoch:02d}.h5' cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode, period=period)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=4) assert os.path.isfile(filepath.format(epoch=2)) assert os.path.isfile(filepath.format(epoch=4)) assert not os.path.exists(filepath.format(epoch=1)) assert not os.path.exists(filepath.format(epoch=3)) os.remove(filepath.format(epoch=2)) os.remove(filepath.format(epoch=4)) assert not tmpdir.listdir() @keras_test def test_EarlyStopping(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) mode = 'max' monitor = 'val_acc' patience = 0 cbks = [callbacks.EarlyStopping(patience=patience, monitor=monitor, mode=mode)] history = model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=20) mode = 'auto' monitor = 'val_acc' patience = 2 cbks = [callbacks.EarlyStopping(patience=patience, monitor=monitor, mode=mode)] history = model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=20) @keras_test def test_EarlyStopping_reuse(): np.random.seed(1337) patience = 3 data = np.random.random((100, 1)) labels = np.where(data > 0.5, 1, 0) model = Sequential(( Dense(1, input_dim=1, activation='relu'), Dense(1, activation='sigmoid'), )) model.compile(optimizer='sgd', loss='binary_crossentropy', metrics=['accuracy']) stopper = callbacks.EarlyStopping(monitor='acc', patience=patience) weights = model.get_weights() hist = model.fit(data, labels, callbacks=[stopper], epochs=20) assert len(hist.epoch) >= patience # This should allow training to go for at least `patience` epochs model.set_weights(weights) hist = model.fit(data, labels, callbacks=[stopper], epochs=20) assert len(hist.epoch) >= patience @keras_test def test_EarlyStopping_patience(): class DummyModel(object): def __init__(self): self.stop_training = False early_stop = callbacks.EarlyStopping(monitor='val_loss', patience=2) early_stop.model = DummyModel() losses = [0.0860, 0.1096, 0.1040, 0.1019] # Should stop after epoch 3, as the loss has not improved after patience=2 epochs. epochs_trained = 0 early_stop.on_train_begin() for epoch in range(len(losses)): epochs_trained += 1 early_stop.on_epoch_end(epoch, logs={'val_loss': losses[epoch]}) if early_stop.model.stop_training: break assert epochs_trained == 3 @keras_test def test_EarlyStopping_baseline(): class DummyModel(object): def __init__(self): self.stop_training = False def baseline_tester(acc_levels): early_stop = callbacks.EarlyStopping(monitor='val_acc', baseline=0.75, patience=2) early_stop.model = DummyModel() epochs_trained = 0 early_stop.on_train_begin() for epoch in range(len(acc_levels)): epochs_trained += 1 early_stop.on_epoch_end(epoch, logs={'val_acc': acc_levels[epoch]}) if early_stop.model.stop_training: break return epochs_trained acc_levels = [0.55, 0.76, 0.81, 0.81] baseline_met = baseline_tester(acc_levels) acc_levels = [0.55, 0.74, 0.81, 0.81] baseline_not_met = baseline_tester(acc_levels) # All epochs should run because baseline was met in second epoch assert baseline_met == 4 # Baseline was not met by second epoch and should stop assert baseline_not_met == 2 @keras_test def test_LearningRateScheduler(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) cbks = [callbacks.LearningRateScheduler(lambda x: 1. / (1. + x))] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=5) assert (float(K.get_value(model.optimizer.lr)) - 0.2) < K.epsilon() @keras_test def test_ReduceLROnPlateau(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def make_model(): np.random.seed(1337) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer=optimizers.SGD(lr=0.1), metrics=['accuracy']) return model model = make_model() # This should reduce the LR after the first epoch (due to high epsilon). cbks = [callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.1, min_delta=10, patience=1, cooldown=5)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=5, verbose=2) assert np.allclose(float(K.get_value(model.optimizer.lr)), 0.01, atol=K.epsilon()) model = make_model() cbks = [callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.1, min_delta=0, patience=1, cooldown=5)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=5, verbose=2) assert np.allclose(float(K.get_value(model.optimizer.lr)), 0.1, atol=K.epsilon()) @keras_test def test_ReduceLROnPlateau_patience(): class DummyOptimizer(object): def __init__(self): self.lr = K.variable(1.0) class DummyModel(object): def __init__(self): self.optimizer = DummyOptimizer() reduce_on_plateau = callbacks.ReduceLROnPlateau(monitor='val_loss', patience=2) reduce_on_plateau.model = DummyModel() losses = [0.0860, 0.1096, 0.1040] lrs = [] for epoch in range(len(losses)): reduce_on_plateau.on_epoch_end(epoch, logs={'val_loss': losses[epoch]}) lrs.append(K.get_value(reduce_on_plateau.model.optimizer.lr)) # The learning rates should be 1.0 except the last one assert all([lr == 1.0 for lr in lrs[:-1]]) and lrs[-1] < 1.0 @keras_test def test_ReduceLROnPlateau_backwards_compatibility(): import warnings with warnings.catch_warnings(record=True) as ws: reduce_on_plateau = callbacks.ReduceLROnPlateau(epsilon=1e-13) # Check if warnings are disabled if os.environ.get("PYTHONWARNINGS") != "ignore": assert "`epsilon` argument is deprecated" in str(ws[0].message) assert not hasattr(reduce_on_plateau, 'epsilon') assert hasattr(reduce_on_plateau, 'min_delta') assert reduce_on_plateau.min_delta == 1e-13 @keras_test def test_CSVLogger(tmpdir): np.random.seed(1337) filepath = str(tmpdir / 'log.tsv') sep = '\t' (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def make_model(): np.random.seed(1337) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer=optimizers.SGD(lr=0.1), metrics=['accuracy']) return model # case 1, create new file with defined separator model = make_model() cbks = [callbacks.CSVLogger(filepath, separator=sep)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) with open(filepath) as csvfile: dialect = Sniffer().sniff(csvfile.read()) assert dialect.delimiter == sep del model del cbks # case 2, append data to existing file, skip header model = make_model() cbks = [callbacks.CSVLogger(filepath, separator=sep, append=True)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) # case 3, reuse of CSVLogger object model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) import re with open(filepath) as csvfile: output = " ".join(csvfile.readlines()) assert len(re.findall('epoch', output)) == 1 os.remove(filepath) assert not tmpdir.listdir() @keras_test def test_TensorBoard(tmpdir): np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') (X_train, y_train), (X_test, y_test) = get_test_data( num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def data_generator(train): if train: max_batch_index = len(X_train) // batch_size else: max_batch_index = len(X_test) // batch_size i = 0 while 1: if train: # simulate multi-input/output models yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) else: yield (X_test[i * batch_size: (i + 1) * batch_size], y_test[i * batch_size: (i + 1) * batch_size]) i += 1 i = i % max_batch_index inp = Input((input_dim,)) hidden = Dense(num_hidden, activation='relu')(inp) hidden = Dropout(0.1)(hidden) output = Dense(num_classes, activation='softmax')(hidden) model = Model(inputs=inp, outputs=output) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) # we must generate new callbacks for each test, as they aren't stateless def callbacks_factory(histogram_freq): return [callbacks.TensorBoard(log_dir=filepath, histogram_freq=histogram_freq, write_images=True, write_grads=True, embeddings_freq=1, embeddings_layer_names=['dense_1'], batch_size=5)] # fit without validation data model.fit(X_train, y_train, batch_size=batch_size, callbacks=callbacks_factory(histogram_freq=0), epochs=3) # fit with validation data and accuracy model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=callbacks_factory(histogram_freq=0), epochs=2) # fit generator without validation data model.fit_generator(data_generator(True), len(X_train), epochs=2, callbacks=callbacks_factory(histogram_freq=0)) # fit generator with validation data and accuracy model.fit_generator(data_generator(True), len(X_train), epochs=2, validation_data=(X_test, y_test), callbacks=callbacks_factory(histogram_freq=1)) assert os.path.isdir(filepath) shutil.rmtree(filepath) assert not tmpdir.listdir() @keras_test @pytest.mark.skipif((K.backend() != 'tensorflow'), reason='Requires TensorFlow backend') def test_TensorBoard_histogram_freq_must_have_validation_data(tmpdir): np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') (X_train, y_train), (X_test, y_test) = get_test_data( num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def data_generator(train): if train: max_batch_index = len(X_train) // batch_size else: max_batch_index = len(X_test) // batch_size i = 0 while 1: if train: # simulate multi-input/output models yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) else: yield (X_test[i * batch_size: (i + 1) * batch_size], y_test[i * batch_size: (i + 1) * batch_size]) i += 1 i = i % max_batch_index inp = Input((input_dim,)) hidden = Dense(num_hidden, activation='relu')(inp) hidden = Dropout(0.1)(hidden) output = Dense(num_classes, activation='softmax')(hidden) model = Model(inputs=inp, outputs=output) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) # we must generate new callbacks for each test, as they aren't stateless def callbacks_factory(histogram_freq): return [callbacks.TensorBoard(log_dir=filepath, histogram_freq=histogram_freq, write_images=True, write_grads=True, embeddings_freq=1, embeddings_layer_names=['dense_1'], batch_size=5)] # fit without validation data should raise ValueError if histogram_freq > 0 with pytest.raises(ValueError) as raised_exception: model.fit(X_train, y_train, batch_size=batch_size, callbacks=callbacks_factory(histogram_freq=1), epochs=3) assert 'validation_data must be provided' in str(raised_exception.value) # fit generator without validation data should raise ValueError if # histogram_freq > 0 with pytest.raises(ValueError) as raised_exception: model.fit_generator(data_generator(True), len(X_train), epochs=2, callbacks=callbacks_factory(histogram_freq=1)) assert 'validation_data must be provided' in str(raised_exception.value) # fit generator with validation data generator should raise ValueError if # histogram_freq > 0 with pytest.raises(ValueError) as raised_exception: model.fit_generator(data_generator(True), len(X_train), epochs=2, validation_data=data_generator(False), validation_steps=1, callbacks=callbacks_factory(histogram_freq=1)) assert 'validation_data must be provided' in str(raised_exception.value) @keras_test def test_TensorBoard_multi_input_output(tmpdir): np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') (X_train, y_train), (X_test, y_test) = get_test_data( num_train=train_samples, num_test=test_samples, input_shape=(input_dim, input_dim), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def data_generator(train): if train: max_batch_index = len(X_train) // batch_size else: max_batch_index = len(X_test) // batch_size i = 0 while 1: if train: # simulate multi-input/output models yield ([X_train[i * batch_size: (i + 1) * batch_size]] * 2, [y_train[i * batch_size: (i + 1) * batch_size]] * 2) else: yield ([X_test[i * batch_size: (i + 1) * batch_size]] * 2, [y_test[i * batch_size: (i + 1) * batch_size]] * 2) i += 1 i = i % max_batch_index inp1 = Input((input_dim, input_dim)) inp2 = Input((input_dim, input_dim)) inp_3d = add([inp1, inp2]) inp_2d = GlobalAveragePooling1D()(inp_3d) inp_pair = Lambda(lambda x: x)([inp_3d, inp_2d]) # test a layer with a list of output tensors hidden = dot(inp_pair, axes=-1) hidden = Dense(num_hidden, activation='relu')(hidden) hidden = Dropout(0.1)(hidden) output1 = Dense(num_classes, activation='softmax')(hidden) output2 = Dense(num_classes, activation='softmax')(hidden) model = Model(inputs=[inp1, inp2], outputs=[output1, output2]) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) # we must generate new callbacks for each test, as they aren't stateless def callbacks_factory(histogram_freq): return [callbacks.TensorBoard(log_dir=filepath, histogram_freq=histogram_freq, write_images=True, write_grads=True, embeddings_freq=1, embeddings_layer_names=['dense_1'], batch_size=5)] # fit without validation data model.fit([X_train] * 2, [y_train] * 2, batch_size=batch_size, callbacks=callbacks_factory(histogram_freq=0), epochs=3) # fit with validation data and accuracy model.fit([X_train] * 2, [y_train] * 2, batch_size=batch_size, validation_data=([X_test] * 2, [y_test] * 2), callbacks=callbacks_factory(histogram_freq=1), epochs=2) # fit generator without validation data model.fit_generator(data_generator(True), len(X_train), epochs=2, callbacks=callbacks_factory(histogram_freq=0)) # fit generator with validation data and accuracy model.fit_generator(data_generator(True), len(X_train), epochs=2, validation_data=([X_test] * 2, [y_test] * 2), callbacks=callbacks_factory(histogram_freq=1)) assert os.path.isdir(filepath) shutil.rmtree(filepath) assert not tmpdir.listdir() @keras_test def test_TensorBoard_convnet(tmpdir): np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') input_shape = (16, 16, 3) (x_train, y_train), (x_test, y_test) = get_test_data(num_train=500, num_test=200, input_shape=input_shape, classification=True, num_classes=num_classes) y_train = np_utils.to_categorical(y_train) y_test = np_utils.to_categorical(y_test) model = Sequential([ Conv2D(filters=8, kernel_size=3, activation='relu', input_shape=input_shape), MaxPooling2D(pool_size=2), Conv2D(filters=4, kernel_size=(3, 3), activation='relu', padding='same'), GlobalAveragePooling2D(), Dense(num_classes, activation='softmax') ]) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) tsb = callbacks.TensorBoard(log_dir=filepath, histogram_freq=1, write_images=True, write_grads=True, batch_size=16) cbks = [tsb] model.summary() history = model.fit(x_train, y_train, epochs=2, batch_size=16, validation_data=(x_test, y_test), callbacks=cbks, verbose=0) assert os.path.isdir(filepath) shutil.rmtree(filepath) assert not tmpdir.listdir() @keras_test def test_CallbackValData(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) cbk = callbacks.LambdaCallback(on_train_end=lambda x: 1) model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=[cbk], epochs=1) def data_generator(train): if train: max_batch_index = len(X_train) // batch_size else: max_batch_index = len(X_test) // batch_size i = 0 while 1: if train: yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) else: yield (X_test[i * batch_size: (i + 1) * batch_size], y_test[i * batch_size: (i + 1) * batch_size]) i += 1 i = i % max_batch_index cbk2 = callbacks.LambdaCallback(on_train_end=lambda x: 1) model.fit_generator(data_generator(True), len(X_train), epochs=1, validation_data=(X_test, y_test), callbacks=[cbk2]) # callback validation data should always have x, y, and sample weights assert len(cbk.validation_data) == len(cbk2.validation_data) == 3 assert cbk.validation_data[0] is cbk2.validation_data[0] assert cbk.validation_data[1] is cbk2.validation_data[1] assert cbk.validation_data[2].shape == cbk2.validation_data[2].shape @keras_test def test_LambdaCallback(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) # Start an arbitrary process that should run during model training and be terminated after training has completed. def f(): while True: pass p = multiprocessing.Process(target=f) p.start() cleanup_callback = callbacks.LambdaCallback(on_train_end=lambda logs: p.terminate()) cbks = [cleanup_callback] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=5) p.join() assert not p.is_alive() @keras_test def test_TensorBoard_with_ReduceLROnPlateau(tmpdir): import shutil np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='binary_crossentropy', optimizer='sgd', metrics=['accuracy']) cbks = [ callbacks.ReduceLROnPlateau( monitor='val_loss', factor=0.5, patience=4, verbose=1), callbacks.TensorBoard( log_dir=filepath)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=2) assert os.path.isdir(filepath) shutil.rmtree(filepath) assert not tmpdir.listdir() @keras_test def tests_RemoteMonitor(): (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) cbks = [callbacks.RemoteMonitor()] with patch('requests.post'): model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) @keras_test def tests_RemoteMonitorWithJsonPayload(): (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) cbks = [callbacks.RemoteMonitor(send_as_json=True)] with patch('requests.post'): model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) if __name__ == '__main__': pytest.main([__file__])

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import os import multiprocessing import numpy as np import pytest from csv import reader from csv import Sniffer import shutil from keras import optimizers from keras import initializers from keras import callbacks from keras.models import Sequential, Model from keras.layers import Input, Dense, Dropout, add, dot, Lambda from keras.layers.convolutional import Conv2D from keras.layers.pooling import MaxPooling2D, GlobalAveragePooling1D, GlobalAveragePooling2D from keras.utils.test_utils import get_test_data from keras.utils.test_utils import keras_test from keras import backend as K from keras.utils import np_utils try: from unittest.mock import patch except: from mock import patch input_dim = 2 num_hidden = 4 num_classes = 2 batch_size = 5 train_samples = 20 test_samples = 20 @keras_test def test_TerminateOnNaN(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) cbks = [callbacks.TerminateOnNaN()] model = Sequential() initializer = initializers.Constant(value=1e5) for _ in range(5): model.add(Dense(num_hidden, input_dim=input_dim, activation='relu', kernel_initializer=initializer)) model.add(Dense(num_classes, activation='linear')) model.compile(loss='mean_squared_error', optimizer='rmsprop') history = model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=20) loss = history.history['loss'] assert len(loss) == 1 assert loss[0] == np.inf def data_generator(): max_batch_index = len(X_train) // batch_size i = 0 while 1: yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) i += 1 i = i % max_batch_index history = model.fit_generator(data_generator(), len(X_train), validation_data=(X_test, y_test), callbacks=cbks, epochs=20) loss = history.history['loss'] assert len(loss) == 1 assert loss[0] == np.inf or np.isnan(loss[0]) @keras_test def test_stop_training_csv(tmpdir): np.random.seed(1337) fp = str(tmpdir / 'test.csv') (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) cbks = [callbacks.TerminateOnNaN(), callbacks.CSVLogger(fp)] model = Sequential() for _ in range(5): model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='linear')) model.compile(loss='mean_squared_error', optimizer='rmsprop') def data_generator(): i = 0 max_batch_index = len(X_train) // batch_size tot = 0 while 1: if tot > 3 * len(X_train): yield np.ones([batch_size, input_dim]) * np.nan, np.ones([batch_size, num_classes]) * np.nan else: yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) i += 1 tot += 1 i = i % max_batch_index history = model.fit_generator(data_generator(), len(X_train) // batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=20) loss = history.history['loss'] assert len(loss) > 1 assert loss[-1] == np.inf or np.isnan(loss[-1]) values = [] with open(fp) as f: for x in reader(f): values.append(x) assert 'nan' in values[-1], 'The last epoch was not logged.' os.remove(fp) @keras_test def test_ModelCheckpoint(tmpdir): np.random.seed(1337) filepath = str(tmpdir / 'checkpoint.h5') (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) monitor = 'val_loss' save_best_only = False mode = 'auto' model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) os.remove(filepath) mode = 'min' cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) os.remove(filepath) mode = 'max' monitor = 'val_acc' cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) os.remove(filepath) save_best_only = True cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) os.remove(filepath) save_best_only = False period = 2 mode = 'auto' filepath = 'checkpoint.{epoch:02d}.h5' cbks = [callbacks.ModelCheckpoint(filepath, monitor=monitor, save_best_only=save_best_only, mode=mode, period=period)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=4) assert os.path.isfile(filepath.format(epoch=2)) assert os.path.isfile(filepath.format(epoch=4)) assert not os.path.exists(filepath.format(epoch=1)) assert not os.path.exists(filepath.format(epoch=3)) os.remove(filepath.format(epoch=2)) os.remove(filepath.format(epoch=4)) assert not tmpdir.listdir() @keras_test def test_EarlyStopping(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) mode = 'max' monitor = 'val_acc' patience = 0 cbks = [callbacks.EarlyStopping(patience=patience, monitor=monitor, mode=mode)] history = model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=20) mode = 'auto' monitor = 'val_acc' patience = 2 cbks = [callbacks.EarlyStopping(patience=patience, monitor=monitor, mode=mode)] history = model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=20) @keras_test def test_EarlyStopping_reuse(): np.random.seed(1337) patience = 3 data = np.random.random((100, 1)) labels = np.where(data > 0.5, 1, 0) model = Sequential(( Dense(1, input_dim=1, activation='relu'), Dense(1, activation='sigmoid'), )) model.compile(optimizer='sgd', loss='binary_crossentropy', metrics=['accuracy']) stopper = callbacks.EarlyStopping(monitor='acc', patience=patience) weights = model.get_weights() hist = model.fit(data, labels, callbacks=[stopper], epochs=20) assert len(hist.epoch) >= patience model.set_weights(weights) hist = model.fit(data, labels, callbacks=[stopper], epochs=20) assert len(hist.epoch) >= patience @keras_test def test_EarlyStopping_patience(): class DummyModel(object): def __init__(self): self.stop_training = False early_stop = callbacks.EarlyStopping(monitor='val_loss', patience=2) early_stop.model = DummyModel() losses = [0.0860, 0.1096, 0.1040, 0.1019] epochs_trained = 0 early_stop.on_train_begin() for epoch in range(len(losses)): epochs_trained += 1 early_stop.on_epoch_end(epoch, logs={'val_loss': losses[epoch]}) if early_stop.model.stop_training: break assert epochs_trained == 3 @keras_test def test_EarlyStopping_baseline(): class DummyModel(object): def __init__(self): self.stop_training = False def baseline_tester(acc_levels): early_stop = callbacks.EarlyStopping(monitor='val_acc', baseline=0.75, patience=2) early_stop.model = DummyModel() epochs_trained = 0 early_stop.on_train_begin() for epoch in range(len(acc_levels)): epochs_trained += 1 early_stop.on_epoch_end(epoch, logs={'val_acc': acc_levels[epoch]}) if early_stop.model.stop_training: break return epochs_trained acc_levels = [0.55, 0.76, 0.81, 0.81] baseline_met = baseline_tester(acc_levels) acc_levels = [0.55, 0.74, 0.81, 0.81] baseline_not_met = baseline_tester(acc_levels) assert baseline_met == 4 assert baseline_not_met == 2 @keras_test def test_LearningRateScheduler(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) cbks = [callbacks.LearningRateScheduler(lambda x: 1. / (1. + x))] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=5) assert (float(K.get_value(model.optimizer.lr)) - 0.2) < K.epsilon() @keras_test def test_ReduceLROnPlateau(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def make_model(): np.random.seed(1337) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer=optimizers.SGD(lr=0.1), metrics=['accuracy']) return model model = make_model() cbks = [callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.1, min_delta=10, patience=1, cooldown=5)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=5, verbose=2) assert np.allclose(float(K.get_value(model.optimizer.lr)), 0.01, atol=K.epsilon()) model = make_model() cbks = [callbacks.ReduceLROnPlateau(monitor='val_loss', factor=0.1, min_delta=0, patience=1, cooldown=5)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=5, verbose=2) assert np.allclose(float(K.get_value(model.optimizer.lr)), 0.1, atol=K.epsilon()) @keras_test def test_ReduceLROnPlateau_patience(): class DummyOptimizer(object): def __init__(self): self.lr = K.variable(1.0) class DummyModel(object): def __init__(self): self.optimizer = DummyOptimizer() reduce_on_plateau = callbacks.ReduceLROnPlateau(monitor='val_loss', patience=2) reduce_on_plateau.model = DummyModel() losses = [0.0860, 0.1096, 0.1040] lrs = [] for epoch in range(len(losses)): reduce_on_plateau.on_epoch_end(epoch, logs={'val_loss': losses[epoch]}) lrs.append(K.get_value(reduce_on_plateau.model.optimizer.lr)) assert all([lr == 1.0 for lr in lrs[:-1]]) and lrs[-1] < 1.0 @keras_test def test_ReduceLROnPlateau_backwards_compatibility(): import warnings with warnings.catch_warnings(record=True) as ws: reduce_on_plateau = callbacks.ReduceLROnPlateau(epsilon=1e-13) if os.environ.get("PYTHONWARNINGS") != "ignore": assert "`epsilon` argument is deprecated" in str(ws[0].message) assert not hasattr(reduce_on_plateau, 'epsilon') assert hasattr(reduce_on_plateau, 'min_delta') assert reduce_on_plateau.min_delta == 1e-13 @keras_test def test_CSVLogger(tmpdir): np.random.seed(1337) filepath = str(tmpdir / 'log.tsv') sep = '\t' (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def make_model(): np.random.seed(1337) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer=optimizers.SGD(lr=0.1), metrics=['accuracy']) return model model = make_model() cbks = [callbacks.CSVLogger(filepath, separator=sep)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) assert os.path.isfile(filepath) with open(filepath) as csvfile: dialect = Sniffer().sniff(csvfile.read()) assert dialect.delimiter == sep del model del cbks model = make_model() cbks = [callbacks.CSVLogger(filepath, separator=sep, append=True)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) import re with open(filepath) as csvfile: output = " ".join(csvfile.readlines()) assert len(re.findall('epoch', output)) == 1 os.remove(filepath) assert not tmpdir.listdir() @keras_test def test_TensorBoard(tmpdir): np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') (X_train, y_train), (X_test, y_test) = get_test_data( num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def data_generator(train): if train: max_batch_index = len(X_train) // batch_size else: max_batch_index = len(X_test) // batch_size i = 0 while 1: if train: yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) else: yield (X_test[i * batch_size: (i + 1) * batch_size], y_test[i * batch_size: (i + 1) * batch_size]) i += 1 i = i % max_batch_index inp = Input((input_dim,)) hidden = Dense(num_hidden, activation='relu')(inp) hidden = Dropout(0.1)(hidden) output = Dense(num_classes, activation='softmax')(hidden) model = Model(inputs=inp, outputs=output) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) def callbacks_factory(histogram_freq): return [callbacks.TensorBoard(log_dir=filepath, histogram_freq=histogram_freq, write_images=True, write_grads=True, embeddings_freq=1, embeddings_layer_names=['dense_1'], batch_size=5)] # fit without validation data model.fit(X_train, y_train, batch_size=batch_size, callbacks=callbacks_factory(histogram_freq=0), epochs=3) # fit with validation data and accuracy model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=callbacks_factory(histogram_freq=0), epochs=2) # fit generator without validation data model.fit_generator(data_generator(True), len(X_train), epochs=2, callbacks=callbacks_factory(histogram_freq=0)) # fit generator with validation data and accuracy model.fit_generator(data_generator(True), len(X_train), epochs=2, validation_data=(X_test, y_test), callbacks=callbacks_factory(histogram_freq=1)) assert os.path.isdir(filepath) shutil.rmtree(filepath) assert not tmpdir.listdir() @keras_test @pytest.mark.skipif((K.backend() != 'tensorflow'), reason='Requires TensorFlow backend') def test_TensorBoard_histogram_freq_must_have_validation_data(tmpdir): np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') (X_train, y_train), (X_test, y_test) = get_test_data( num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def data_generator(train): if train: max_batch_index = len(X_train) // batch_size else: max_batch_index = len(X_test) // batch_size i = 0 while 1: if train: # simulate multi-input/output models yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) else: yield (X_test[i * batch_size: (i + 1) * batch_size], y_test[i * batch_size: (i + 1) * batch_size]) i += 1 i = i % max_batch_index inp = Input((input_dim,)) hidden = Dense(num_hidden, activation='relu')(inp) hidden = Dropout(0.1)(hidden) output = Dense(num_classes, activation='softmax')(hidden) model = Model(inputs=inp, outputs=output) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) # we must generate new callbacks for each test, as they aren't stateless def callbacks_factory(histogram_freq): return [callbacks.TensorBoard(log_dir=filepath, histogram_freq=histogram_freq, write_images=True, write_grads=True, embeddings_freq=1, embeddings_layer_names=['dense_1'], batch_size=5)] with pytest.raises(ValueError) as raised_exception: model.fit(X_train, y_train, batch_size=batch_size, callbacks=callbacks_factory(histogram_freq=1), epochs=3) assert 'validation_data must be provided' in str(raised_exception.value) with pytest.raises(ValueError) as raised_exception: model.fit_generator(data_generator(True), len(X_train), epochs=2, callbacks=callbacks_factory(histogram_freq=1)) assert 'validation_data must be provided' in str(raised_exception.value) with pytest.raises(ValueError) as raised_exception: model.fit_generator(data_generator(True), len(X_train), epochs=2, validation_data=data_generator(False), validation_steps=1, callbacks=callbacks_factory(histogram_freq=1)) assert 'validation_data must be provided' in str(raised_exception.value) @keras_test def test_TensorBoard_multi_input_output(tmpdir): np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') (X_train, y_train), (X_test, y_test) = get_test_data( num_train=train_samples, num_test=test_samples, input_shape=(input_dim, input_dim), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) def data_generator(train): if train: max_batch_index = len(X_train) // batch_size else: max_batch_index = len(X_test) // batch_size i = 0 while 1: if train: yield ([X_train[i * batch_size: (i + 1) * batch_size]] * 2, [y_train[i * batch_size: (i + 1) * batch_size]] * 2) else: yield ([X_test[i * batch_size: (i + 1) * batch_size]] * 2, [y_test[i * batch_size: (i + 1) * batch_size]] * 2) i += 1 i = i % max_batch_index inp1 = Input((input_dim, input_dim)) inp2 = Input((input_dim, input_dim)) inp_3d = add([inp1, inp2]) inp_2d = GlobalAveragePooling1D()(inp_3d) inp_pair = Lambda(lambda x: x)([inp_3d, inp_2d]) hidden = dot(inp_pair, axes=-1) hidden = Dense(num_hidden, activation='relu')(hidden) hidden = Dropout(0.1)(hidden) output1 = Dense(num_classes, activation='softmax')(hidden) output2 = Dense(num_classes, activation='softmax')(hidden) model = Model(inputs=[inp1, inp2], outputs=[output1, output2]) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) def callbacks_factory(histogram_freq): return [callbacks.TensorBoard(log_dir=filepath, histogram_freq=histogram_freq, write_images=True, write_grads=True, embeddings_freq=1, embeddings_layer_names=['dense_1'], batch_size=5)] # fit without validation data model.fit([X_train] * 2, [y_train] * 2, batch_size=batch_size, callbacks=callbacks_factory(histogram_freq=0), epochs=3) # fit with validation data and accuracy model.fit([X_train] * 2, [y_train] * 2, batch_size=batch_size, validation_data=([X_test] * 2, [y_test] * 2), callbacks=callbacks_factory(histogram_freq=1), epochs=2) # fit generator without validation data model.fit_generator(data_generator(True), len(X_train), epochs=2, callbacks=callbacks_factory(histogram_freq=0)) # fit generator with validation data and accuracy model.fit_generator(data_generator(True), len(X_train), epochs=2, validation_data=([X_test] * 2, [y_test] * 2), callbacks=callbacks_factory(histogram_freq=1)) assert os.path.isdir(filepath) shutil.rmtree(filepath) assert not tmpdir.listdir() @keras_test def test_TensorBoard_convnet(tmpdir): np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') input_shape = (16, 16, 3) (x_train, y_train), (x_test, y_test) = get_test_data(num_train=500, num_test=200, input_shape=input_shape, classification=True, num_classes=num_classes) y_train = np_utils.to_categorical(y_train) y_test = np_utils.to_categorical(y_test) model = Sequential([ Conv2D(filters=8, kernel_size=3, activation='relu', input_shape=input_shape), MaxPooling2D(pool_size=2), Conv2D(filters=4, kernel_size=(3, 3), activation='relu', padding='same'), GlobalAveragePooling2D(), Dense(num_classes, activation='softmax') ]) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) tsb = callbacks.TensorBoard(log_dir=filepath, histogram_freq=1, write_images=True, write_grads=True, batch_size=16) cbks = [tsb] model.summary() history = model.fit(x_train, y_train, epochs=2, batch_size=16, validation_data=(x_test, y_test), callbacks=cbks, verbose=0) assert os.path.isdir(filepath) shutil.rmtree(filepath) assert not tmpdir.listdir() @keras_test def test_CallbackValData(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) cbk = callbacks.LambdaCallback(on_train_end=lambda x: 1) model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=[cbk], epochs=1) def data_generator(train): if train: max_batch_index = len(X_train) // batch_size else: max_batch_index = len(X_test) // batch_size i = 0 while 1: if train: yield (X_train[i * batch_size: (i + 1) * batch_size], y_train[i * batch_size: (i + 1) * batch_size]) else: yield (X_test[i * batch_size: (i + 1) * batch_size], y_test[i * batch_size: (i + 1) * batch_size]) i += 1 i = i % max_batch_index cbk2 = callbacks.LambdaCallback(on_train_end=lambda x: 1) model.fit_generator(data_generator(True), len(X_train), epochs=1, validation_data=(X_test, y_test), callbacks=[cbk2]) # callback validation data should always have x, y, and sample weights assert len(cbk.validation_data) == len(cbk2.validation_data) == 3 assert cbk.validation_data[0] is cbk2.validation_data[0] assert cbk.validation_data[1] is cbk2.validation_data[1] assert cbk.validation_data[2].shape == cbk2.validation_data[2].shape @keras_test def test_LambdaCallback(): np.random.seed(1337) (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy']) # Start an arbitrary process that should run during model training and be terminated after training has completed. def f(): while True: pass p = multiprocessing.Process(target=f) p.start() cleanup_callback = callbacks.LambdaCallback(on_train_end=lambda logs: p.terminate()) cbks = [cleanup_callback] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=5) p.join() assert not p.is_alive() @keras_test def test_TensorBoard_with_ReduceLROnPlateau(tmpdir): import shutil np.random.seed(np.random.randint(1, 1e7)) filepath = str(tmpdir / 'logs') (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='binary_crossentropy', optimizer='sgd', metrics=['accuracy']) cbks = [ callbacks.ReduceLROnPlateau( monitor='val_loss', factor=0.5, patience=4, verbose=1), callbacks.TensorBoard( log_dir=filepath)] model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=2) assert os.path.isdir(filepath) shutil.rmtree(filepath) assert not tmpdir.listdir() @keras_test def tests_RemoteMonitor(): (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) cbks = [callbacks.RemoteMonitor()] with patch('requests.post'): model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) @keras_test def tests_RemoteMonitorWithJsonPayload(): (X_train, y_train), (X_test, y_test) = get_test_data(num_train=train_samples, num_test=test_samples, input_shape=(input_dim,), classification=True, num_classes=num_classes) y_test = np_utils.to_categorical(y_test) y_train = np_utils.to_categorical(y_train) model = Sequential() model.add(Dense(num_hidden, input_dim=input_dim, activation='relu')) model.add(Dense(num_classes, activation='softmax')) model.compile(loss='categorical_crossentropy', optimizer='rmsprop', metrics=['accuracy']) cbks = [callbacks.RemoteMonitor(send_as_json=True)] with patch('requests.post'): model.fit(X_train, y_train, batch_size=batch_size, validation_data=(X_test, y_test), callbacks=cbks, epochs=1) if __name__ == '__main__': pytest.main([__file__])

true

f718891f5d70f5bc34c238ce47c933a0dbeff2c0

27,465

py

Python

twisted/conch/scripts/cftp.py

twonds/twisted

d6e270a465d371c3bed01bf369af497b77eb9f1e

[ "Unlicense", "MIT" ]

1

2021-01-27T19:11:21.000Z

twisted/conch/scripts/cftp.py

twonds/twisted

d6e270a465d371c3bed01bf369af497b77eb9f1e

[ "Unlicense", "MIT" ]

null

twisted/conch/scripts/cftp.py

twonds/twisted

d6e270a465d371c3bed01bf369af497b77eb9f1e

[ "Unlicense", "MIT" ]

3

2017-01-04T01:24:15.000Z

2020-06-18T16:14:56.000Z

# -*- test-case-name: twisted.conch.test.test_cftp -*- # Copyright (c) 2001-2009 Twisted Matrix Laboratories. # See LICENSE for details. """ Implementation module for the I{cftp} command. """ import os, sys, getpass, struct, tty, fcntl, stat import fnmatch, pwd, time, glob from twisted.conch.client import connect, default, options from twisted.conch.ssh import connection, common from twisted.conch.ssh import channel, filetransfer from twisted.protocols import basic from twisted.internet import reactor, stdio, defer, utils from twisted.python import log, usage, failure class ClientOptions(options.ConchOptions): synopsis = """Usage: cftp [options] [user@]host cftp [options] [user@]host[:dir[/]] cftp [options] [user@]host[:file [localfile]] """ optParameters = [ ['buffersize', 'B', 32768, 'Size of the buffer to use for sending/receiving.'], ['batchfile', 'b', None, 'File to read commands from, or \'-\' for stdin.'], ['requests', 'R', 5, 'Number of requests to make before waiting for a reply.'], ['subsystem', 's', 'sftp', 'Subsystem/server program to connect to.']] zsh_altArgDescr = {"buffersize":"Size of send/receive buffer (default: 32768)"} #zsh_multiUse = ["foo", "bar"] #zsh_mutuallyExclusive = [("foo", "bar"), ("bar", "baz")] #zsh_actions = {"foo":'_files -g "*.foo"', "bar":"(one two three)"} #zsh_actionDescr = {"logfile":"log file name", "random":"random seed"} zsh_extras = ['2::localfile:{if [[ $words[1] == *:* ]]; then; _files; fi}'] def parseArgs(self, host, localPath=None): self['remotePath'] = '' if ':' in host: host, self['remotePath'] = host.split(':', 1) self['remotePath'].rstrip('/') self['host'] = host self['localPath'] = localPath def run(): # import hotshot # prof = hotshot.Profile('cftp.prof') # prof.start() args = sys.argv[1:] if '-l' in args: # cvs is an idiot i = args.index('-l') args = args[i:i+2]+args del args[i+2:i+4] options = ClientOptions() try: options.parseOptions(args) except usage.UsageError, u: print 'ERROR: %s' % u sys.exit(1) if options['log']: realout = sys.stdout log.startLogging(sys.stderr) sys.stdout = realout else: log.discardLogs() doConnect(options) reactor.run() # prof.stop() # prof.close() def handleError(): global exitStatus exitStatus = 2 try: reactor.stop() except: pass log.err(failure.Failure()) raise def doConnect(options): # log.deferr = handleError # HACK if '@' in options['host']: options['user'], options['host'] = options['host'].split('@',1) host = options['host'] if not options['user']: options['user'] = getpass.getuser() if not options['port']: options['port'] = 22 else: options['port'] = int(options['port']) host = options['host'] port = options['port'] conn = SSHConnection() conn.options = options vhk = default.verifyHostKey uao = default.SSHUserAuthClient(options['user'], options, conn) connect.connect(host, port, options, vhk, uao).addErrback(_ebExit) def _ebExit(f): #global exitStatus if hasattr(f.value, 'value'): s = f.value.value else: s = str(f) print s #exitStatus = "conch: exiting with error %s" % f try: reactor.stop() except: pass def _ignore(*args): pass class FileWrapper: def __init__(self, f): self.f = f self.total = 0.0 f.seek(0, 2) # seek to the end self.size = f.tell() def __getattr__(self, attr): return getattr(self.f, attr) class StdioClient(basic.LineReceiver): _pwd = pwd ps = 'cftp> ' delimiter = '\n' def __init__(self, client, f = None): self.client = client self.currentDirectory = '' self.file = f self.useProgressBar = (not f and 1) or 0 def connectionMade(self): self.client.realPath('').addCallback(self._cbSetCurDir) def _cbSetCurDir(self, path): self.currentDirectory = path self._newLine() def lineReceived(self, line): if self.client.transport.localClosed: return log.msg('got line %s' % repr(line)) line = line.lstrip() if not line: self._newLine() return if self.file and line.startswith('-'): self.ignoreErrors = 1 line = line[1:] else: self.ignoreErrors = 0 d = self._dispatchCommand(line) if d is not None: d.addCallback(self._cbCommand) d.addErrback(self._ebCommand) def _dispatchCommand(self, line): if ' ' in line: command, rest = line.split(' ', 1) rest = rest.lstrip() else: command, rest = line, '' if command.startswith('!'): # command f = self.cmd_EXEC rest = (command[1:] + ' ' + rest).strip() else: command = command.upper() log.msg('looking up cmd %s' % command) f = getattr(self, 'cmd_%s' % command, None) if f is not None: return defer.maybeDeferred(f, rest) else: self._ebCommand(failure.Failure(NotImplementedError( "No command called `%s'" % command))) self._newLine() def _printFailure(self, f): log.msg(f) e = f.trap(NotImplementedError, filetransfer.SFTPError, OSError, IOError) if e == NotImplementedError: self.transport.write(self.cmd_HELP('')) elif e == filetransfer.SFTPError: self.transport.write("remote error %i: %s\n" % (f.value.code, f.value.message)) elif e in (OSError, IOError): self.transport.write("local error %i: %s\n" % (f.value.errno, f.value.strerror)) def _newLine(self): if self.client.transport.localClosed: return self.transport.write(self.ps) self.ignoreErrors = 0 if self.file: l = self.file.readline() if not l: self.client.transport.loseConnection() else: self.transport.write(l) self.lineReceived(l.strip()) def _cbCommand(self, result): if result is not None: self.transport.write(result) if not result.endswith('\n'): self.transport.write('\n') self._newLine() def _ebCommand(self, f): self._printFailure(f) if self.file and not self.ignoreErrors: self.client.transport.loseConnection() self._newLine() def cmd_CD(self, path): path, rest = self._getFilename(path) if not path.endswith('/'): path += '/' newPath = path and os.path.join(self.currentDirectory, path) or '' d = self.client.openDirectory(newPath) d.addCallback(self._cbCd) d.addErrback(self._ebCommand) return d def _cbCd(self, directory): directory.close() d = self.client.realPath(directory.name) d.addCallback(self._cbCurDir) return d def _cbCurDir(self, path): self.currentDirectory = path def cmd_CHGRP(self, rest): grp, rest = rest.split(None, 1) path, rest = self._getFilename(rest) grp = int(grp) d = self.client.getAttrs(path) d.addCallback(self._cbSetUsrGrp, path, grp=grp) return d def cmd_CHMOD(self, rest): mod, rest = rest.split(None, 1) path, rest = self._getFilename(rest) mod = int(mod, 8) d = self.client.setAttrs(path, {'permissions':mod}) d.addCallback(_ignore) return d def cmd_CHOWN(self, rest): usr, rest = rest.split(None, 1) path, rest = self._getFilename(rest) usr = int(usr) d = self.client.getAttrs(path) d.addCallback(self._cbSetUsrGrp, path, usr=usr) return d def _cbSetUsrGrp(self, attrs, path, usr=None, grp=None): new = {} new['uid'] = (usr is not None) and usr or attrs['uid'] new['gid'] = (grp is not None) and grp or attrs['gid'] d = self.client.setAttrs(path, new) d.addCallback(_ignore) return d def cmd_GET(self, rest): remote, rest = self._getFilename(rest) if '*' in remote or '?' in remote: # wildcard if rest: local, rest = self._getFilename(rest) if not os.path.isdir(local): return "Wildcard get with non-directory target." else: local = '' d = self._remoteGlob(remote) d.addCallback(self._cbGetMultiple, local) return d if rest: local, rest = self._getFilename(rest) else: local = os.path.split(remote)[1] log.msg((remote, local)) lf = file(local, 'w', 0) path = os.path.join(self.currentDirectory, remote) d = self.client.openFile(path, filetransfer.FXF_READ, {}) d.addCallback(self._cbGetOpenFile, lf) d.addErrback(self._ebCloseLf, lf) return d def _cbGetMultiple(self, files, local): #if self._useProgressBar: # one at a time # XXX this can be optimized for times w/o progress bar return self._cbGetMultipleNext(None, files, local) def _cbGetMultipleNext(self, res, files, local): if isinstance(res, failure.Failure): self._printFailure(res) elif res: self.transport.write(res) if not res.endswith('\n'): self.transport.write('\n') if not files: return f = files.pop(0)[0] lf = file(os.path.join(local, os.path.split(f)[1]), 'w', 0) path = os.path.join(self.currentDirectory, f) d = self.client.openFile(path, filetransfer.FXF_READ, {}) d.addCallback(self._cbGetOpenFile, lf) d.addErrback(self._ebCloseLf, lf) d.addBoth(self._cbGetMultipleNext, files, local) return d def _ebCloseLf(self, f, lf): lf.close() return f def _cbGetOpenFile(self, rf, lf): return rf.getAttrs().addCallback(self._cbGetFileSize, rf, lf) def _cbGetFileSize(self, attrs, rf, lf): if not stat.S_ISREG(attrs['permissions']): rf.close() lf.close() return "Can't get non-regular file: %s" % rf.name rf.size = attrs['size'] bufferSize = self.client.transport.conn.options['buffersize'] numRequests = self.client.transport.conn.options['requests'] rf.total = 0.0 dList = [] chunks = [] startTime = time.time() for i in range(numRequests): d = self._cbGetRead('', rf, lf, chunks, 0, bufferSize, startTime) dList.append(d) dl = defer.DeferredList(dList, fireOnOneErrback=1) dl.addCallback(self._cbGetDone, rf, lf) return dl def _getNextChunk(self, chunks): end = 0 for chunk in chunks: if end == 'eof': return # nothing more to get if end != chunk[0]: i = chunks.index(chunk) chunks.insert(i, (end, chunk[0])) return (end, chunk[0] - end) end = chunk[1] bufSize = int(self.client.transport.conn.options['buffersize']) chunks.append((end, end + bufSize)) return (end, bufSize) def _cbGetRead(self, data, rf, lf, chunks, start, size, startTime): if data and isinstance(data, failure.Failure): log.msg('get read err: %s' % data) reason = data reason.trap(EOFError) i = chunks.index((start, start + size)) del chunks[i] chunks.insert(i, (start, 'eof')) elif data: log.msg('get read data: %i' % len(data)) lf.seek(start) lf.write(data) if len(data) != size: log.msg('got less than we asked for: %i < %i' % (len(data), size)) i = chunks.index((start, start + size)) del chunks[i] chunks.insert(i, (start, start + len(data))) rf.total += len(data) if self.useProgressBar: self._printProgessBar(rf, startTime) chunk = self._getNextChunk(chunks) if not chunk: return else: start, length = chunk log.msg('asking for %i -> %i' % (start, start+length)) d = rf.readChunk(start, length) d.addBoth(self._cbGetRead, rf, lf, chunks, start, length, startTime) return d def _cbGetDone(self, ignored, rf, lf): log.msg('get done') rf.close() lf.close() if self.useProgressBar: self.transport.write('\n') return "Transferred %s to %s" % (rf.name, lf.name) def cmd_PUT(self, rest): local, rest = self._getFilename(rest) if '*' in local or '?' in local: # wildcard if rest: remote, rest = self._getFilename(rest) path = os.path.join(self.currentDirectory, remote) d = self.client.getAttrs(path) d.addCallback(self._cbPutTargetAttrs, remote, local) return d else: remote = '' files = glob.glob(local) return self._cbPutMultipleNext(None, files, remote) if rest: remote, rest = self._getFilename(rest) else: remote = os.path.split(local)[1] lf = file(local, 'r') path = os.path.join(self.currentDirectory, remote) flags = filetransfer.FXF_WRITE|filetransfer.FXF_CREAT|filetransfer.FXF_TRUNC d = self.client.openFile(path, flags, {}) d.addCallback(self._cbPutOpenFile, lf) d.addErrback(self._ebCloseLf, lf) return d def _cbPutTargetAttrs(self, attrs, path, local): if not stat.S_ISDIR(attrs['permissions']): return "Wildcard put with non-directory target." return self._cbPutMultipleNext(None, files, path) def _cbPutMultipleNext(self, res, files, path): if isinstance(res, failure.Failure): self._printFailure(res) elif res: self.transport.write(res) if not res.endswith('\n'): self.transport.write('\n') f = None while files and not f: try: f = files.pop(0) lf = file(f, 'r') except: self._printFailure(failure.Failure()) f = None if not f: return name = os.path.split(f)[1] remote = os.path.join(self.currentDirectory, path, name) log.msg((name, remote, path)) flags = filetransfer.FXF_WRITE|filetransfer.FXF_CREAT|filetransfer.FXF_TRUNC d = self.client.openFile(remote, flags, {}) d.addCallback(self._cbPutOpenFile, lf) d.addErrback(self._ebCloseLf, lf) d.addBoth(self._cbPutMultipleNext, files, path) return d def _cbPutOpenFile(self, rf, lf): numRequests = self.client.transport.conn.options['requests'] if self.useProgressBar: lf = FileWrapper(lf) dList = [] chunks = [] startTime = time.time() for i in range(numRequests): d = self._cbPutWrite(None, rf, lf, chunks, startTime) if d: dList.append(d) dl = defer.DeferredList(dList, fireOnOneErrback=1) dl.addCallback(self._cbPutDone, rf, lf) return dl def _cbPutWrite(self, ignored, rf, lf, chunks, startTime): chunk = self._getNextChunk(chunks) start, size = chunk lf.seek(start) data = lf.read(size) if self.useProgressBar: lf.total += len(data) self._printProgessBar(lf, startTime) if data: d = rf.writeChunk(start, data) d.addCallback(self._cbPutWrite, rf, lf, chunks, startTime) return d else: return def _cbPutDone(self, ignored, rf, lf): lf.close() rf.close() if self.useProgressBar: self.transport.write('\n') return 'Transferred %s to %s' % (lf.name, rf.name) def cmd_LCD(self, path): os.chdir(path) def cmd_LN(self, rest): linkpath, rest = self._getFilename(rest) targetpath, rest = self._getFilename(rest) linkpath, targetpath = map( lambda x: os.path.join(self.currentDirectory, x), (linkpath, targetpath)) return self.client.makeLink(linkpath, targetpath).addCallback(_ignore) def cmd_LS(self, rest): # possible lines: # ls current directory # ls name_of_file that file # ls name_of_directory that directory # ls some_glob_string current directory, globbed for that string options = [] rest = rest.split() while rest and rest[0] and rest[0][0] == '-': opts = rest.pop(0)[1:] for o in opts: if o == 'l': options.append('verbose') elif o == 'a': options.append('all') rest = ' '.join(rest) path, rest = self._getFilename(rest) if not path: fullPath = self.currentDirectory + '/' else: fullPath = os.path.join(self.currentDirectory, path) d = self._remoteGlob(fullPath) d.addCallback(self._cbDisplayFiles, options) return d def _cbDisplayFiles(self, files, options): files.sort() if 'all' not in options: files = [f for f in files if not f[0].startswith('.')] if 'verbose' in options: lines = [f[1] for f in files] else: lines = [f[0] for f in files] if not lines: return None else: return '\n'.join(lines) def cmd_MKDIR(self, path): path, rest = self._getFilename(path) path = os.path.join(self.currentDirectory, path) return self.client.makeDirectory(path, {}).addCallback(_ignore) def cmd_RMDIR(self, path): path, rest = self._getFilename(path) path = os.path.join(self.currentDirectory, path) return self.client.removeDirectory(path).addCallback(_ignore) def cmd_LMKDIR(self, path): os.system("mkdir %s" % path) def cmd_RM(self, path): path, rest = self._getFilename(path) path = os.path.join(self.currentDirectory, path) return self.client.removeFile(path).addCallback(_ignore) def cmd_LLS(self, rest): os.system("ls %s" % rest) def cmd_RENAME(self, rest): oldpath, rest = self._getFilename(rest) newpath, rest = self._getFilename(rest) oldpath, newpath = map ( lambda x: os.path.join(self.currentDirectory, x), (oldpath, newpath)) return self.client.renameFile(oldpath, newpath).addCallback(_ignore) def cmd_EXIT(self, ignored): self.client.transport.loseConnection() cmd_QUIT = cmd_EXIT def cmd_VERSION(self, ignored): return "SFTP version %i" % self.client.version def cmd_HELP(self, ignored): return """Available commands: cd path Change remote directory to 'path'. chgrp gid path Change gid of 'path' to 'gid'. chmod mode path Change mode of 'path' to 'mode'. chown uid path Change uid of 'path' to 'uid'. exit Disconnect from the server. get remote-path [local-path] Get remote file. help Get a list of available commands. lcd path Change local directory to 'path'. lls [ls-options] [path] Display local directory listing. lmkdir path Create local directory. ln linkpath targetpath Symlink remote file. lpwd Print the local working directory. ls [-l] [path] Display remote directory listing. mkdir path Create remote directory. progress Toggle progress bar. put local-path [remote-path] Put local file. pwd Print the remote working directory. quit Disconnect from the server. rename oldpath newpath Rename remote file. rmdir path Remove remote directory. rm path Remove remote file. version Print the SFTP version. ? Synonym for 'help'. """ def cmd_PWD(self, ignored): return self.currentDirectory def cmd_LPWD(self, ignored): return os.getcwd() def cmd_PROGRESS(self, ignored): self.useProgressBar = not self.useProgressBar return "%ssing progess bar." % (self.useProgressBar and "U" or "Not u") def cmd_EXEC(self, rest): """ Run C{rest} using the user's shell (or /bin/sh if they do not have one). """ shell = self._pwd.getpwnam(getpass.getuser())[6] if not shell: shell = '/bin/sh' if rest: cmds = ['-c', rest] return utils.getProcessOutput(shell, cmds, errortoo=1) else: os.system(shell) # accessory functions def _remoteGlob(self, fullPath): log.msg('looking up %s' % fullPath) head, tail = os.path.split(fullPath) if '*' in tail or '?' in tail: glob = 1 else: glob = 0 if tail and not glob: # could be file or directory # try directory first d = self.client.openDirectory(fullPath) d.addCallback(self._cbOpenList, '') d.addErrback(self._ebNotADirectory, head, tail) else: d = self.client.openDirectory(head) d.addCallback(self._cbOpenList, tail) return d def _cbOpenList(self, directory, glob): files = [] d = directory.read() d.addBoth(self._cbReadFile, files, directory, glob) return d def _ebNotADirectory(self, reason, path, glob): d = self.client.openDirectory(path) d.addCallback(self._cbOpenList, glob) return d def _cbReadFile(self, files, l, directory, glob): if not isinstance(files, failure.Failure): if glob: l.extend([f for f in files if fnmatch.fnmatch(f[0], glob)]) else: l.extend(files) d = directory.read() d.addBoth(self._cbReadFile, l, directory, glob) return d else: reason = files reason.trap(EOFError) directory.close() return l def _abbrevSize(self, size): # from http://mail.python.org/pipermail/python-list/1999-December/018395.html _abbrevs = [ (1<<50L, 'PB'), (1<<40L, 'TB'), (1<<30L, 'GB'), (1<<20L, 'MB'), (1<<10L, 'kb'), (1, '') ] for factor, suffix in _abbrevs: if size > factor: break return '%.1f' % (size/factor) + suffix def _abbrevTime(self, t): if t > 3600: # 1 hour hours = int(t / 3600) t -= (3600 * hours) mins = int(t / 60) t -= (60 * mins) return "%i:%02i:%02i" % (hours, mins, t) else: mins = int(t/60) t -= (60 * mins) return "%02i:%02i" % (mins, t) def _printProgessBar(self, f, startTime): diff = time.time() - startTime total = f.total try: winSize = struct.unpack('4H', fcntl.ioctl(0, tty.TIOCGWINSZ, '12345679')) except IOError: winSize = [None, 80] speed = total/diff if speed: timeLeft = (f.size - total) / speed else: timeLeft = 0 front = f.name back = '%3i%% %s %sps %s ' % ((total/f.size)*100, self._abbrevSize(total), self._abbrevSize(total/diff), self._abbrevTime(timeLeft)) spaces = (winSize[1] - (len(front) + len(back) + 1)) * ' ' self.transport.write('\r%s%s%s' % (front, spaces, back)) def _getFilename(self, line): line.lstrip() if not line: return None, '' if line[0] in '\'"': ret = [] line = list(line) try: for i in range(1,len(line)): c = line[i] if c == line[0]: return ''.join(ret), ''.join(line[i+1:]).lstrip() elif c == '\\': # quoted character del line[i] if line[i] not in '\'"\\': raise IndexError, "bad quote: \\%s" % line[i] ret.append(line[i]) else: ret.append(line[i]) except IndexError: raise IndexError, "unterminated quote" ret = line.split(None, 1) if len(ret) == 1: return ret[0], '' else: return ret StdioClient.__dict__['cmd_?'] = StdioClient.cmd_HELP class SSHConnection(connection.SSHConnection): def serviceStarted(self): self.openChannel(SSHSession()) class SSHSession(channel.SSHChannel): name = 'session' def channelOpen(self, foo): log.msg('session %s open' % self.id) if self.conn.options['subsystem'].startswith('/'): request = 'exec' else: request = 'subsystem' d = self.conn.sendRequest(self, request, \ common.NS(self.conn.options['subsystem']), wantReply=1) d.addCallback(self._cbSubsystem) d.addErrback(_ebExit) def _cbSubsystem(self, result): self.client = filetransfer.FileTransferClient() self.client.makeConnection(self) self.dataReceived = self.client.dataReceived f = None if self.conn.options['batchfile']: fn = self.conn.options['batchfile'] if fn != '-': f = file(fn) self.stdio = stdio.StandardIO(StdioClient(self.client, f)) def extReceived(self, t, data): if t==connection.EXTENDED_DATA_STDERR: log.msg('got %s stderr data' % len(data)) sys.stderr.write(data) sys.stderr.flush() def eofReceived(self): log.msg('got eof') self.stdio.closeStdin() def closeReceived(self): log.msg('remote side closed %s' % self) self.conn.sendClose(self) def closed(self): try: reactor.stop() except: pass def stopWriting(self): self.stdio.pauseProducing() def startWriting(self): self.stdio.resumeProducing() if __name__ == '__main__': run()

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""" Implementation module for the I{cftp} command. """ import os, sys, getpass, struct, tty, fcntl, stat import fnmatch, pwd, time, glob from twisted.conch.client import connect, default, options from twisted.conch.ssh import connection, common from twisted.conch.ssh import channel, filetransfer from twisted.protocols import basic from twisted.internet import reactor, stdio, defer, utils from twisted.python import log, usage, failure class ClientOptions(options.ConchOptions): synopsis = """Usage: cftp [options] [user@]host cftp [options] [user@]host[:dir[/]] cftp [options] [user@]host[:file [localfile]] """ optParameters = [ ['buffersize', 'B', 32768, 'Size of the buffer to use for sending/receiving.'], ['batchfile', 'b', None, 'File to read commands from, or \'-\' for stdin.'], ['requests', 'R', 5, 'Number of requests to make before waiting for a reply.'], ['subsystem', 's', 'sftp', 'Subsystem/server program to connect to.']] zsh_altArgDescr = {"buffersize":"Size of send/receive buffer (default: 32768)"} zsh_extras = ['2::localfile:{if [[ $words[1] == *:* ]]; then; _files; fi}'] def parseArgs(self, host, localPath=None): self['remotePath'] = '' if ':' in host: host, self['remotePath'] = host.split(':', 1) self['remotePath'].rstrip('/') self['host'] = host self['localPath'] = localPath def run(): args = sys.argv[1:] if '-l' in args: i = args.index('-l') args = args[i:i+2]+args del args[i+2:i+4] options = ClientOptions() try: options.parseOptions(args) except usage.UsageError, u: print 'ERROR: %s' % u sys.exit(1) if options['log']: realout = sys.stdout log.startLogging(sys.stderr) sys.stdout = realout else: log.discardLogs() doConnect(options) reactor.run() def handleError(): global exitStatus exitStatus = 2 try: reactor.stop() except: pass log.err(failure.Failure()) raise def doConnect(options): f '@' in options['host']: options['user'], options['host'] = options['host'].split('@',1) host = options['host'] if not options['user']: options['user'] = getpass.getuser() if not options['port']: options['port'] = 22 else: options['port'] = int(options['port']) host = options['host'] port = options['port'] conn = SSHConnection() conn.options = options vhk = default.verifyHostKey uao = default.SSHUserAuthClient(options['user'], options, conn) connect.connect(host, port, options, vhk, uao).addErrback(_ebExit) def _ebExit(f): if hasattr(f.value, 'value'): s = f.value.value else: s = str(f) print s try: reactor.stop() except: pass def _ignore(*args): pass class FileWrapper: def __init__(self, f): self.f = f self.total = 0.0 f.seek(0, 2) self.size = f.tell() def __getattr__(self, attr): return getattr(self.f, attr) class StdioClient(basic.LineReceiver): _pwd = pwd ps = 'cftp> ' delimiter = '\n' def __init__(self, client, f = None): self.client = client self.currentDirectory = '' self.file = f self.useProgressBar = (not f and 1) or 0 def connectionMade(self): self.client.realPath('').addCallback(self._cbSetCurDir) def _cbSetCurDir(self, path): self.currentDirectory = path self._newLine() def lineReceived(self, line): if self.client.transport.localClosed: return log.msg('got line %s' % repr(line)) line = line.lstrip() if not line: self._newLine() return if self.file and line.startswith('-'): self.ignoreErrors = 1 line = line[1:] else: self.ignoreErrors = 0 d = self._dispatchCommand(line) if d is not None: d.addCallback(self._cbCommand) d.addErrback(self._ebCommand) def _dispatchCommand(self, line): if ' ' in line: command, rest = line.split(' ', 1) rest = rest.lstrip() else: command, rest = line, '' if command.startswith('!'): f = self.cmd_EXEC rest = (command[1:] + ' ' + rest).strip() else: command = command.upper() log.msg('looking up cmd %s' % command) f = getattr(self, 'cmd_%s' % command, None) if f is not None: return defer.maybeDeferred(f, rest) else: self._ebCommand(failure.Failure(NotImplementedError( "No command called `%s'" % command))) self._newLine() def _printFailure(self, f): log.msg(f) e = f.trap(NotImplementedError, filetransfer.SFTPError, OSError, IOError) if e == NotImplementedError: self.transport.write(self.cmd_HELP('')) elif e == filetransfer.SFTPError: self.transport.write("remote error %i: %s\n" % (f.value.code, f.value.message)) elif e in (OSError, IOError): self.transport.write("local error %i: %s\n" % (f.value.errno, f.value.strerror)) def _newLine(self): if self.client.transport.localClosed: return self.transport.write(self.ps) self.ignoreErrors = 0 if self.file: l = self.file.readline() if not l: self.client.transport.loseConnection() else: self.transport.write(l) self.lineReceived(l.strip()) def _cbCommand(self, result): if result is not None: self.transport.write(result) if not result.endswith('\n'): self.transport.write('\n') self._newLine() def _ebCommand(self, f): self._printFailure(f) if self.file and not self.ignoreErrors: self.client.transport.loseConnection() self._newLine() def cmd_CD(self, path): path, rest = self._getFilename(path) if not path.endswith('/'): path += '/' newPath = path and os.path.join(self.currentDirectory, path) or '' d = self.client.openDirectory(newPath) d.addCallback(self._cbCd) d.addErrback(self._ebCommand) return d def _cbCd(self, directory): directory.close() d = self.client.realPath(directory.name) d.addCallback(self._cbCurDir) return d def _cbCurDir(self, path): self.currentDirectory = path def cmd_CHGRP(self, rest): grp, rest = rest.split(None, 1) path, rest = self._getFilename(rest) grp = int(grp) d = self.client.getAttrs(path) d.addCallback(self._cbSetUsrGrp, path, grp=grp) return d def cmd_CHMOD(self, rest): mod, rest = rest.split(None, 1) path, rest = self._getFilename(rest) mod = int(mod, 8) d = self.client.setAttrs(path, {'permissions':mod}) d.addCallback(_ignore) return d def cmd_CHOWN(self, rest): usr, rest = rest.split(None, 1) path, rest = self._getFilename(rest) usr = int(usr) d = self.client.getAttrs(path) d.addCallback(self._cbSetUsrGrp, path, usr=usr) return d def _cbSetUsrGrp(self, attrs, path, usr=None, grp=None): new = {} new['uid'] = (usr is not None) and usr or attrs['uid'] new['gid'] = (grp is not None) and grp or attrs['gid'] d = self.client.setAttrs(path, new) d.addCallback(_ignore) return d def cmd_GET(self, rest): remote, rest = self._getFilename(rest) if '*' in remote or '?' in remote: # wildcard if rest: local, rest = self._getFilename(rest) if not os.path.isdir(local): return "Wildcard get with non-directory target." else: local = '' d = self._remoteGlob(remote) d.addCallback(self._cbGetMultiple, local) return d if rest: local, rest = self._getFilename(rest) else: local = os.path.split(remote)[1] log.msg((remote, local)) lf = file(local, 'w', 0) path = os.path.join(self.currentDirectory, remote) d = self.client.openFile(path, filetransfer.FXF_READ, {}) d.addCallback(self._cbGetOpenFile, lf) d.addErrback(self._ebCloseLf, lf) return d def _cbGetMultiple(self, files, local): #if self._useProgressBar: # one at a time # XXX this can be optimized for times w/o progress bar return self._cbGetMultipleNext(None, files, local) def _cbGetMultipleNext(self, res, files, local): if isinstance(res, failure.Failure): self._printFailure(res) elif res: self.transport.write(res) if not res.endswith('\n'): self.transport.write('\n') if not files: return f = files.pop(0)[0] lf = file(os.path.join(local, os.path.split(f)[1]), 'w', 0) path = os.path.join(self.currentDirectory, f) d = self.client.openFile(path, filetransfer.FXF_READ, {}) d.addCallback(self._cbGetOpenFile, lf) d.addErrback(self._ebCloseLf, lf) d.addBoth(self._cbGetMultipleNext, files, local) return d def _ebCloseLf(self, f, lf): lf.close() return f def _cbGetOpenFile(self, rf, lf): return rf.getAttrs().addCallback(self._cbGetFileSize, rf, lf) def _cbGetFileSize(self, attrs, rf, lf): if not stat.S_ISREG(attrs['permissions']): rf.close() lf.close() return "Can't get non-regular file: %s" % rf.name rf.size = attrs['size'] bufferSize = self.client.transport.conn.options['buffersize'] numRequests = self.client.transport.conn.options['requests'] rf.total = 0.0 dList = [] chunks = [] startTime = time.time() for i in range(numRequests): d = self._cbGetRead('', rf, lf, chunks, 0, bufferSize, startTime) dList.append(d) dl = defer.DeferredList(dList, fireOnOneErrback=1) dl.addCallback(self._cbGetDone, rf, lf) return dl def _getNextChunk(self, chunks): end = 0 for chunk in chunks: if end == 'eof': return if end != chunk[0]: i = chunks.index(chunk) chunks.insert(i, (end, chunk[0])) return (end, chunk[0] - end) end = chunk[1] bufSize = int(self.client.transport.conn.options['buffersize']) chunks.append((end, end + bufSize)) return (end, bufSize) def _cbGetRead(self, data, rf, lf, chunks, start, size, startTime): if data and isinstance(data, failure.Failure): log.msg('get read err: %s' % data) reason = data reason.trap(EOFError) i = chunks.index((start, start + size)) del chunks[i] chunks.insert(i, (start, 'eof')) elif data: log.msg('get read data: %i' % len(data)) lf.seek(start) lf.write(data) if len(data) != size: log.msg('got less than we asked for: %i < %i' % (len(data), size)) i = chunks.index((start, start + size)) del chunks[i] chunks.insert(i, (start, start + len(data))) rf.total += len(data) if self.useProgressBar: self._printProgessBar(rf, startTime) chunk = self._getNextChunk(chunks) if not chunk: return else: start, length = chunk log.msg('asking for %i -> %i' % (start, start+length)) d = rf.readChunk(start, length) d.addBoth(self._cbGetRead, rf, lf, chunks, start, length, startTime) return d def _cbGetDone(self, ignored, rf, lf): log.msg('get done') rf.close() lf.close() if self.useProgressBar: self.transport.write('\n') return "Transferred %s to %s" % (rf.name, lf.name) def cmd_PUT(self, rest): local, rest = self._getFilename(rest) if '*' in local or '?' in local: if rest: remote, rest = self._getFilename(rest) path = os.path.join(self.currentDirectory, remote) d = self.client.getAttrs(path) d.addCallback(self._cbPutTargetAttrs, remote, local) return d else: remote = '' files = glob.glob(local) return self._cbPutMultipleNext(None, files, remote) if rest: remote, rest = self._getFilename(rest) else: remote = os.path.split(local)[1] lf = file(local, 'r') path = os.path.join(self.currentDirectory, remote) flags = filetransfer.FXF_WRITE|filetransfer.FXF_CREAT|filetransfer.FXF_TRUNC d = self.client.openFile(path, flags, {}) d.addCallback(self._cbPutOpenFile, lf) d.addErrback(self._ebCloseLf, lf) return d def _cbPutTargetAttrs(self, attrs, path, local): if not stat.S_ISDIR(attrs['permissions']): return "Wildcard put with non-directory target." return self._cbPutMultipleNext(None, files, path) def _cbPutMultipleNext(self, res, files, path): if isinstance(res, failure.Failure): self._printFailure(res) elif res: self.transport.write(res) if not res.endswith('\n'): self.transport.write('\n') f = None while files and not f: try: f = files.pop(0) lf = file(f, 'r') except: self._printFailure(failure.Failure()) f = None if not f: return name = os.path.split(f)[1] remote = os.path.join(self.currentDirectory, path, name) log.msg((name, remote, path)) flags = filetransfer.FXF_WRITE|filetransfer.FXF_CREAT|filetransfer.FXF_TRUNC d = self.client.openFile(remote, flags, {}) d.addCallback(self._cbPutOpenFile, lf) d.addErrback(self._ebCloseLf, lf) d.addBoth(self._cbPutMultipleNext, files, path) return d def _cbPutOpenFile(self, rf, lf): numRequests = self.client.transport.conn.options['requests'] if self.useProgressBar: lf = FileWrapper(lf) dList = [] chunks = [] startTime = time.time() for i in range(numRequests): d = self._cbPutWrite(None, rf, lf, chunks, startTime) if d: dList.append(d) dl = defer.DeferredList(dList, fireOnOneErrback=1) dl.addCallback(self._cbPutDone, rf, lf) return dl def _cbPutWrite(self, ignored, rf, lf, chunks, startTime): chunk = self._getNextChunk(chunks) start, size = chunk lf.seek(start) data = lf.read(size) if self.useProgressBar: lf.total += len(data) self._printProgessBar(lf, startTime) if data: d = rf.writeChunk(start, data) d.addCallback(self._cbPutWrite, rf, lf, chunks, startTime) return d else: return def _cbPutDone(self, ignored, rf, lf): lf.close() rf.close() if self.useProgressBar: self.transport.write('\n') return 'Transferred %s to %s' % (lf.name, rf.name) def cmd_LCD(self, path): os.chdir(path) def cmd_LN(self, rest): linkpath, rest = self._getFilename(rest) targetpath, rest = self._getFilename(rest) linkpath, targetpath = map( lambda x: os.path.join(self.currentDirectory, x), (linkpath, targetpath)) return self.client.makeLink(linkpath, targetpath).addCallback(_ignore) def cmd_LS(self, rest): options = [] rest = rest.split() while rest and rest[0] and rest[0][0] == '-': opts = rest.pop(0)[1:] for o in opts: if o == 'l': options.append('verbose') elif o == 'a': options.append('all') rest = ' '.join(rest) path, rest = self._getFilename(rest) if not path: fullPath = self.currentDirectory + '/' else: fullPath = os.path.join(self.currentDirectory, path) d = self._remoteGlob(fullPath) d.addCallback(self._cbDisplayFiles, options) return d def _cbDisplayFiles(self, files, options): files.sort() if 'all' not in options: files = [f for f in files if not f[0].startswith('.')] if 'verbose' in options: lines = [f[1] for f in files] else: lines = [f[0] for f in files] if not lines: return None else: return '\n'.join(lines) def cmd_MKDIR(self, path): path, rest = self._getFilename(path) path = os.path.join(self.currentDirectory, path) return self.client.makeDirectory(path, {}).addCallback(_ignore) def cmd_RMDIR(self, path): path, rest = self._getFilename(path) path = os.path.join(self.currentDirectory, path) return self.client.removeDirectory(path).addCallback(_ignore) def cmd_LMKDIR(self, path): os.system("mkdir %s" % path) def cmd_RM(self, path): path, rest = self._getFilename(path) path = os.path.join(self.currentDirectory, path) return self.client.removeFile(path).addCallback(_ignore) def cmd_LLS(self, rest): os.system("ls %s" % rest) def cmd_RENAME(self, rest): oldpath, rest = self._getFilename(rest) newpath, rest = self._getFilename(rest) oldpath, newpath = map ( lambda x: os.path.join(self.currentDirectory, x), (oldpath, newpath)) return self.client.renameFile(oldpath, newpath).addCallback(_ignore) def cmd_EXIT(self, ignored): self.client.transport.loseConnection() cmd_QUIT = cmd_EXIT def cmd_VERSION(self, ignored): return "SFTP version %i" % self.client.version def cmd_HELP(self, ignored): return """Available commands: cd path Change remote directory to 'path'. chgrp gid path Change gid of 'path' to 'gid'. chmod mode path Change mode of 'path' to 'mode'. chown uid path Change uid of 'path' to 'uid'. exit Disconnect from the server. get remote-path [local-path] Get remote file. help Get a list of available commands. lcd path Change local directory to 'path'. lls [ls-options] [path] Display local directory listing. lmkdir path Create local directory. ln linkpath targetpath Symlink remote file. lpwd Print the local working directory. ls [-l] [path] Display remote directory listing. mkdir path Create remote directory. progress Toggle progress bar. put local-path [remote-path] Put local file. pwd Print the remote working directory. quit Disconnect from the server. rename oldpath newpath Rename remote file. rmdir path Remove remote directory. rm path Remove remote file. version Print the SFTP version. ? Synonym for 'help'. """ def cmd_PWD(self, ignored): return self.currentDirectory def cmd_LPWD(self, ignored): return os.getcwd() def cmd_PROGRESS(self, ignored): self.useProgressBar = not self.useProgressBar return "%ssing progess bar." % (self.useProgressBar and "U" or "Not u") def cmd_EXEC(self, rest): """ Run C{rest} using the user's shell (or /bin/sh if they do not have one). """ shell = self._pwd.getpwnam(getpass.getuser())[6] if not shell: shell = '/bin/sh' if rest: cmds = ['-c', rest] return utils.getProcessOutput(shell, cmds, errortoo=1) else: os.system(shell) # accessory functions def _remoteGlob(self, fullPath): log.msg('looking up %s' % fullPath) head, tail = os.path.split(fullPath) if '*' in tail or '?' in tail: glob = 1 else: glob = 0 if tail and not glob: # could be file or directory # try directory first d = self.client.openDirectory(fullPath) d.addCallback(self._cbOpenList, '') d.addErrback(self._ebNotADirectory, head, tail) else: d = self.client.openDirectory(head) d.addCallback(self._cbOpenList, tail) return d def _cbOpenList(self, directory, glob): files = [] d = directory.read() d.addBoth(self._cbReadFile, files, directory, glob) return d def _ebNotADirectory(self, reason, path, glob): d = self.client.openDirectory(path) d.addCallback(self._cbOpenList, glob) return d def _cbReadFile(self, files, l, directory, glob): if not isinstance(files, failure.Failure): if glob: l.extend([f for f in files if fnmatch.fnmatch(f[0], glob)]) else: l.extend(files) d = directory.read() d.addBoth(self._cbReadFile, l, directory, glob) return d else: reason = files reason.trap(EOFError) directory.close() return l def _abbrevSize(self, size): # from http://mail.python.org/pipermail/python-list/1999-December/018395.html _abbrevs = [ (1<<50L, 'PB'), (1<<40L, 'TB'), (1<<30L, 'GB'), (1<<20L, 'MB'), (1<<10L, 'kb'), (1, '') ] for factor, suffix in _abbrevs: if size > factor: break return '%.1f' % (size/factor) + suffix def _abbrevTime(self, t): if t > 3600: # 1 hour hours = int(t / 3600) t -= (3600 * hours) mins = int(t / 60) t -= (60 * mins) return "%i:%02i:%02i" % (hours, mins, t) else: mins = int(t/60) t -= (60 * mins) return "%02i:%02i" % (mins, t) def _printProgessBar(self, f, startTime): diff = time.time() - startTime total = f.total try: winSize = struct.unpack('4H', fcntl.ioctl(0, tty.TIOCGWINSZ, '12345679')) except IOError: winSize = [None, 80] speed = total/diff if speed: timeLeft = (f.size - total) / speed else: timeLeft = 0 front = f.name back = '%3i%% %s %sps %s ' % ((total/f.size)*100, self._abbrevSize(total), self._abbrevSize(total/diff), self._abbrevTime(timeLeft)) spaces = (winSize[1] - (len(front) + len(back) + 1)) * ' ' self.transport.write('\r%s%s%s' % (front, spaces, back)) def _getFilename(self, line): line.lstrip() if not line: return None, '' if line[0] in '\'"': ret = [] line = list(line) try: for i in range(1,len(line)): c = line[i] if c == line[0]: return ''.join(ret), ''.join(line[i+1:]).lstrip() elif c == '\\': # quoted character del line[i] if line[i] not in '\'"\\': raise IndexError, "bad quote: \\%s" % line[i] ret.append(line[i]) else: ret.append(line[i]) except IndexError: raise IndexError, "unterminated quote" ret = line.split(None, 1) if len(ret) == 1: return ret[0], '' else: return ret StdioClient.__dict__['cmd_?'] = StdioClient.cmd_HELP class SSHConnection(connection.SSHConnection): def serviceStarted(self): self.openChannel(SSHSession()) class SSHSession(channel.SSHChannel): name = 'session' def channelOpen(self, foo): log.msg('session %s open' % self.id) if self.conn.options['subsystem'].startswith('/'): request = 'exec' else: request = 'subsystem' d = self.conn.sendRequest(self, request, \ common.NS(self.conn.options['subsystem']), wantReply=1) d.addCallback(self._cbSubsystem) d.addErrback(_ebExit) def _cbSubsystem(self, result): self.client = filetransfer.FileTransferClient() self.client.makeConnection(self) self.dataReceived = self.client.dataReceived f = None if self.conn.options['batchfile']: fn = self.conn.options['batchfile'] if fn != '-': f = file(fn) self.stdio = stdio.StandardIO(StdioClient(self.client, f)) def extReceived(self, t, data): if t==connection.EXTENDED_DATA_STDERR: log.msg('got %s stderr data' % len(data)) sys.stderr.write(data) sys.stderr.flush() def eofReceived(self): log.msg('got eof') self.stdio.closeStdin() def closeReceived(self): log.msg('remote side closed %s' % self) self.conn.sendClose(self) def closed(self): try: reactor.stop() except: pass def stopWriting(self): self.stdio.pauseProducing() def startWriting(self): self.stdio.resumeProducing() if __name__ == '__main__': run()

false

true

f7188a38996cf7c598da7499b124f3d25c63ff64

24

py

Python

trimesh/version.py

hroncok/trimesh

85c6af12f8bfdf7d3e6c0b8fa553142a9d4219fe

[ "MIT" ]

null

trimesh/version.py

hroncok/trimesh

85c6af12f8bfdf7d3e6c0b8fa553142a9d4219fe

[ "MIT" ]

null

trimesh/version.py

hroncok/trimesh

85c6af12f8bfdf7d3e6c0b8fa553142a9d4219fe

[ "MIT" ]

null

__version__ = '2.35.24'

12

23

0.666667

__version__ = '2.35.24'

true

f7188a5d6697e456a89894a7330aa0af3fad00a2

146

py

Python

tests/filetwo.py

alexandrevicenzi/lazyconfig

a03aa0b92cf8f810a8652728d80dd0d792dd66ed

[ "MIT" ]

null

tests/filetwo.py

alexandrevicenzi/lazyconfig

a03aa0b92cf8f810a8652728d80dd0d792dd66ed

[ "MIT" ]

null

tests/filetwo.py

alexandrevicenzi/lazyconfig

a03aa0b92cf8f810a8652728d80dd0d792dd66ed

[ "MIT" ]

null

# -*- coding: utf-8 -*- import sys sys.path.append('./') from lazyconfig import lazyconfig def get_name(): return lazyconfig.config.name

12.166667

33

0.678082

import sys sys.path.append('./') from lazyconfig import lazyconfig def get_name(): return lazyconfig.config.name

true

f7188bfb1008501bd297684979855b6ad8cfff58

2,432

py

Python

Framework/Sketch/Helpers/Metrices.py

Gruschwick/ECG_PLATFORM

4a1ee568e8593938a3b51c595d4834f861a6db6e

[ "MIT" ]

5

2021-01-28T00:04:35.000Z

2022-03-05T05:35:10.000Z

Framework/Sketch/Helpers/Metrices.py

Gruschwick/ECG_PLATFORM

4a1ee568e8593938a3b51c595d4834f861a6db6e

[ "MIT" ]

null

Framework/Sketch/Helpers/Metrices.py

Gruschwick/ECG_PLATFORM

4a1ee568e8593938a3b51c595d4834f861a6db6e

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Mon Mar 11 16:56:51 2019 @author: x """ import numpy as np from collections import Counter class MetricesConstants(object): #qrs_cutoff_distance = 0.2 qrs_cutoff_distance = 0.120 #https://www.sciencedirect.com/science/article/abs/pii/S1746809417300216 def sample_to_time(samples, freq): return samples/freq def match_peaks( ref_peaks, pred_peaks, cutoff_distance = None): ''' calc best matching between ref_peaks and pred_peaks with cutoff (error time distance no longer than cutoff_distance) [(ref_peaks[r], pred_peaks[c]) for r, c in zip(row_ind, col_ind) ''' from scipy.optimize import linear_sum_assignment assert np.all(ref_peaks >= 0), "positive time" assert np.all(pred_peaks >= 0), "positive time" if cutoff_distance is None: cutoff_distance = MetricesConstants.qrs_cutoff_distance max_ref_peaks = np.max(ref_peaks) len_ref_peaks = len(ref_peaks) max_pred_peaks = np.max(pred_peaks) len_pred_peaks = len(pred_peaks) max_len = max(len_ref_peaks, len_pred_peaks) max_peaks = max(max_ref_peaks, max_pred_peaks) max_distance = max_peaks*10000 ref_peaks = np.pad(ref_peaks, ((0,max_len - len_ref_peaks),), 'constant', constant_values=(0, max_distance)) pred_peaks = np.pad(pred_peaks, ((0,max_len - len_pred_peaks),), 'constant', constant_values=(0, max_distance)) distance_matrix = np.abs(ref_peaks[:,np.newaxis] - pred_peaks[np.newaxis,:]) distance_matrix[distance_matrix > cutoff_distance] = max_distance row_ind, col_ind= linear_sum_assignment(distance_matrix) matching_filtered = [(r,c) for r, c in zip(row_ind, col_ind) if distance_matrix[r,c] <= cutoff_distance] #ref_peaks[r], pred_peaks[c] return matching_filtered def qrs_detection_scores( ref_peaks, pred_peaks, peaks_matching): deltas = [(ref_peaks[r] - pred_peaks[c]) for r, c in peaks_matching] tpr = len(peaks_matching)/len(ref_peaks) ppv = len(peaks_matching)/len(pred_peaks) return np.mean(deltas), np.std(deltas), tpr, ppv def qrs_detection_by_class(ref_peaks_class, peaks_matching): ref_counts = Counter(ref_peaks_class) detected_counts = Counter(ref_peaks_class[r] for r, c in peaks_matching) return {(k, detected_counts.get(k,0)/ref_counts[k]) for k in ref_counts.keys()}, ref_counts, detected_counts

37.415385

123

0.713816

import numpy as np from collections import Counter class MetricesConstants(object): qrs_cutoff_distance = 0.120 def sample_to_time(samples, freq): return samples/freq def match_peaks( ref_peaks, pred_peaks, cutoff_distance = None): from scipy.optimize import linear_sum_assignment assert np.all(ref_peaks >= 0), "positive time" assert np.all(pred_peaks >= 0), "positive time" if cutoff_distance is None: cutoff_distance = MetricesConstants.qrs_cutoff_distance max_ref_peaks = np.max(ref_peaks) len_ref_peaks = len(ref_peaks) max_pred_peaks = np.max(pred_peaks) len_pred_peaks = len(pred_peaks) max_len = max(len_ref_peaks, len_pred_peaks) max_peaks = max(max_ref_peaks, max_pred_peaks) max_distance = max_peaks*10000 ref_peaks = np.pad(ref_peaks, ((0,max_len - len_ref_peaks),), 'constant', constant_values=(0, max_distance)) pred_peaks = np.pad(pred_peaks, ((0,max_len - len_pred_peaks),), 'constant', constant_values=(0, max_distance)) distance_matrix = np.abs(ref_peaks[:,np.newaxis] - pred_peaks[np.newaxis,:]) distance_matrix[distance_matrix > cutoff_distance] = max_distance row_ind, col_ind= linear_sum_assignment(distance_matrix) matching_filtered = [(r,c) for r, c in zip(row_ind, col_ind) if distance_matrix[r,c] <= cutoff_distance] return matching_filtered def qrs_detection_scores( ref_peaks, pred_peaks, peaks_matching): deltas = [(ref_peaks[r] - pred_peaks[c]) for r, c in peaks_matching] tpr = len(peaks_matching)/len(ref_peaks) ppv = len(peaks_matching)/len(pred_peaks) return np.mean(deltas), np.std(deltas), tpr, ppv def qrs_detection_by_class(ref_peaks_class, peaks_matching): ref_counts = Counter(ref_peaks_class) detected_counts = Counter(ref_peaks_class[r] for r, c in peaks_matching) return {(k, detected_counts.get(k,0)/ref_counts[k]) for k in ref_counts.keys()}, ref_counts, detected_counts

true

f7188c282ded875e0b10619595c7c3e809117a5a

222

py

Python

old_code/keras_main.py

pgruening/dlbio

0c4e468bcd5d7e298fbecba13003bcae36889486

[ "MIT" ]

1

2020-10-08T11:14:48.000Z

old_code/keras_main.py

pgruening/dlbio

0c4e468bcd5d7e298fbecba13003bcae36889486

[ "MIT" ]

5

2020-03-24T18:01:02.000Z

2022-03-12T00:17:24.000Z

old_code/keras_main.py

pgruening/dlbio

0c4e468bcd5d7e298fbecba13003bcae36889486

[ "MIT" ]

1

2021-11-29T10:31:28.000Z

from keras.utils.generic_utils import get_custom_objects from main import IMain class KerasMain(IMain): def init_costum_objects(self, costum_objects): get_custom_objects().update( costum_objects)

24.666667

56

0.752252

from keras.utils.generic_utils import get_custom_objects from main import IMain class KerasMain(IMain): def init_costum_objects(self, costum_objects): get_custom_objects().update( costum_objects)

true

f7188d171f94cd5bbe951736476fdbef7da4879a

7,038

py

Python

source/conf.py

edgarriba/tutorials

781378818dde4b1e055e9b2d3cb8ea02d66a863e

[ "Apache-2.0" ]

1

2021-05-03T06:42:35.000Z

source/conf.py

edgarriba/tutorials

781378818dde4b1e055e9b2d3cb8ea02d66a863e

[ "Apache-2.0" ]

null

source/conf.py

edgarriba/tutorials

781378818dde4b1e055e9b2d3cb8ea02d66a863e

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # # Configuration file for the Sphinx documentation builder. # # This file does only contain a selection of the most common options. For a # full list see the documentation: # http://www.sphinx-doc.org/en/master/config # -- Path setup -------------------------------------------------------------- # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # # import os # import sys # sys.path.insert(0, os.path.abspath('.')) # -- Project information ----------------------------------------------------- project = 'Kornia Tutorials' copyright = '2021, Kornia Authors' author = 'Kornia Authors' # The short X.Y version version = '' # The full version, including alpha/beta/rc tags release = '' # -- General configuration --------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. # # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ 'nbsphinx', 'sphinx.ext.mathjax', 'sphinx.ext.githubpages', ] exclude_patterns = ['_build', '**.ipynb_checkpoints'] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # # source_suffix = ['.rst', '.md'] source_suffix = ['.rst', '.ipynb'] # The master toctree document. master_doc = 'index' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path. exclude_patterns = [] # The name of the Pygments (syntax highlighting) style to use. pygments_style = None autosummary_generate = True napolean_use_rtype = False # -- Options for nbsphinx ----------------------------------------------------- # Execute notebooks before conversion: 'always', 'never', 'auto' (default) # We execute all notebooks, exclude the slow ones using 'exclude_patterns' nbsphinx_execute = 'never' # Use this kernel instead of the one stored in the notebook metadata: #nbsphinx_kernel_name = 'python3' # List of arguments to be passed to the kernel that executes the notebooks: # nbsphinx_execute_arguments = [] # If True, the build process is continued even if an exception occurs: #nbsphinx_allow_errors = True # Controls when a cell will time out (defaults to 30; use -1 for no timeout): #nbsphinx_timeout = 180 # Default Pygments lexer for syntax highlighting in code cells: #nbsphinx_codecell_lexer = 'ipython3' # Width of input/output prompts used in CSS: #nbsphinx_prompt_width = '8ex' # If window is narrower than this, input/output prompts are on separate lines: #nbsphinx_responsive_width = '700px' # This is processed by Jinja2 and inserted before each notebook nbsphinx_prolog = r""" {% set docname = 'source/' + env.doc2path(env.docname, base=None) %} .. only:: html .. role:: raw-html(raw) :format: html .. nbinfo:: Interactive online version: :raw-html:`<a href="https://colab.research.google.com/github/kornia/tutorials/blob/master/{{ docname }}" target="_blank" rel="noopener noreferrer><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg" style="vertical-align:text-bottom"></a>` __ https://github.com/kornia/tutorials/blob/ {{ env.config.release }}/{{ docname }} """ # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # html_theme = 'sphinx_rtd_theme' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # # html_theme_options = {} # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # The default sidebars (for documents that don't match any pattern) are # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # # html_sidebars = {} # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = 'KorniaTutorialsdoc' # -- Options for LaTeX output ------------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'KorniaTutorials.tex', 'Kornia Tutorials Documentation', 'Kornia Authors', 'manual'), ] # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'korniatutorials', 'Kornia Tutorials Documentation', [author], 1) ] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'KorniaTutorials', 'Kornia Tutorials Documentation', author, 'KorniaTutorials', 'One line description of project.', 'Miscellaneous'), ] # -- Options for Epub output ------------------------------------------------- # Bibliographic Dublin Core info. epub_title = project # The unique identifier of the text. This can be a ISBN number # or the project homepage. # # epub_identifier = '' # A unique identification for the text. # # epub_uid = '' # A list of files that should not be packed into the epub file. epub_exclude_files = ['search.html']

31.004405

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project = 'Kornia Tutorials' copyright = '2021, Kornia Authors' author = 'Kornia Authors' version = '' release = '' extensions = [ 'nbsphinx', 'sphinx.ext.mathjax', 'sphinx.ext.githubpages', ] exclude_patterns = ['_build', '**.ipynb_checkpoints'] templates_path = ['_templates'] source_suffix = ['.rst', '.ipynb'] master_doc = 'index' language = None exclude_patterns = [] pygments_style = None autosummary_generate = True napolean_use_rtype = False nbsphinx_execute = 'never' nbsphinx_prolog = r""" {% set docname = 'source/' + env.doc2path(env.docname, base=None) %} .. only:: html .. role:: raw-html(raw) :format: html .. nbinfo:: Interactive online version: :raw-html:`<a href="https://colab.research.google.com/github/kornia/tutorials/blob/master/{{ docname }}" target="_blank" rel="noopener noreferrer><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg" style="vertical-align:text-bottom"></a>` __ https://github.com/kornia/tutorials/blob/ {{ env.config.release }}/{{ docname }} """ # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # html_theme = 'sphinx_rtd_theme' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # # html_theme_options = {} # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # The default sidebars (for documents that don't match any pattern) are # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # # html_sidebars = {} # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = 'KorniaTutorialsdoc' # -- Options for LaTeX output ------------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'KorniaTutorials.tex', 'Kornia Tutorials Documentation', 'Kornia Authors', 'manual'), ] # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'korniatutorials', 'Kornia Tutorials Documentation', [author], 1) ] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'KorniaTutorials', 'Kornia Tutorials Documentation', author, 'KorniaTutorials', 'One line description of project.', 'Miscellaneous'), ] # -- Options for Epub output ------------------------------------------------- # Bibliographic Dublin Core info. epub_title = project # The unique identifier of the text. This can be a ISBN number # or the project homepage. # # epub_identifier = '' # A unique identification for the text. # # epub_uid = '' # A list of files that should not be packed into the epub file. epub_exclude_files = ['search.html']

true

f7188d70a660f168ca65fa4e5633d1e3038f23fa

6,067

py

Python

venv/Lib/site-packages/IPython/lib/latextools.py

Kiiwi/Syssel

83705e3fd0edf40f09df950d5ce91c95586573f5

[ "BSD-3-Clause" ]

1

2017-12-30T20:43:28.000Z

venv/Lib/site-packages/IPython/lib/latextools.py

Kiiwi/Syssel

83705e3fd0edf40f09df950d5ce91c95586573f5

[ "BSD-3-Clause" ]

7

2021-02-08T20:22:15.000Z

2022-03-11T23:19:41.000Z

venv/Lib/site-packages/IPython/lib/latextools.py

Kiiwi/Syssel

83705e3fd0edf40f09df950d5ce91c95586573f5

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """Tools for handling LaTeX.""" # Copyright (c) IPython Development Team. # Distributed under the terms of the Modified BSD License. from io import BytesIO, open from base64 import encodestring import os import tempfile import shutil import subprocess from IPython.utils.process import find_cmd, FindCmdError from IPython.config import get_config from IPython.config.configurable import SingletonConfigurable from IPython.utils.traitlets import List, Bool, Unicode from IPython.utils.py3compat import cast_unicode, cast_unicode_py2 as u class LaTeXTool(SingletonConfigurable): """An object to store configuration of the LaTeX tool.""" def _config_default(self): return get_config() backends = List( Unicode, ["matplotlib", "dvipng"], help="Preferred backend to draw LaTeX math equations. " "Backends in the list are checked one by one and the first " "usable one is used. Note that `matplotlib` backend " "is usable only for inline style equations. To draw " "display style equations, `dvipng` backend must be specified. ", # It is a List instead of Enum, to make configuration more # flexible. For example, to use matplotlib mainly but dvipng # for display style, the default ["matplotlib", "dvipng"] can # be used. To NOT use dvipng so that other repr such as # unicode pretty printing is used, you can use ["matplotlib"]. config=True) use_breqn = Bool( True, help="Use breqn.sty to automatically break long equations. " "This configuration takes effect only for dvipng backend.", config=True) packages = List( ['amsmath', 'amsthm', 'amssymb', 'bm'], help="A list of packages to use for dvipng backend. " "'breqn' will be automatically appended when use_breqn=True.", config=True) preamble = Unicode( help="Additional preamble to use when generating LaTeX source " "for dvipng backend.", config=True) def latex_to_png(s, encode=False, backend=None, wrap=False): """Render a LaTeX string to PNG. Parameters ---------- s : text The raw string containing valid inline LaTeX. encode : bool, optional Should the PNG data base64 encoded to make it JSON'able. backend : {matplotlib, dvipng} Backend for producing PNG data. wrap : bool If true, Automatically wrap `s` as a LaTeX equation. None is returned when the backend cannot be used. """ s = cast_unicode(s) allowed_backends = LaTeXTool.instance().backends if backend is None: backend = allowed_backends[0] if backend not in allowed_backends: return None if backend == 'matplotlib': f = latex_to_png_mpl elif backend == 'dvipng': f = latex_to_png_dvipng else: raise ValueError('No such backend {0}'.format(backend)) bin_data = f(s, wrap) if encode and bin_data: bin_data = encodestring(bin_data) return bin_data def latex_to_png_mpl(s, wrap): try: from matplotlib import mathtext except ImportError: return None # mpl mathtext doesn't support display math, force inline s = s.replace('$$', '$') if wrap: s = u'${0}$'.format(s) mt = mathtext.MathTextParser('bitmap') f = BytesIO() mt.to_png(f, s, fontsize=12) return f.getvalue() def latex_to_png_dvipng(s, wrap): try: find_cmd('latex') find_cmd('dvipng') except FindCmdError: return None try: workdir = tempfile.mkdtemp() tmpfile = os.path.join(workdir, "tmp.tex") dvifile = os.path.join(workdir, "tmp.dvi") outfile = os.path.join(workdir, "tmp.png") with open(tmpfile, "w", encoding='utf8') as f: f.writelines(genelatex(s, wrap)) with open(os.devnull, 'wb') as devnull: subprocess.check_call( ["latex", "-halt-on-error", "-interaction", "batchmode", tmpfile], cwd=workdir, stdout=devnull, stderr=devnull) subprocess.check_call( ["dvipng", "-T", "tight", "-x", "1500", "-z", "9", "-bg", "transparent", "-o", outfile, dvifile], cwd=workdir, stdout=devnull, stderr=devnull) with open(outfile, "rb") as f: return f.read() finally: shutil.rmtree(workdir) def kpsewhich(filename): """Invoke kpsewhich command with an argument `filename`.""" try: find_cmd("kpsewhich") proc = subprocess.Popen( ["kpsewhich", filename], stdout=subprocess.PIPE, stderr=subprocess.PIPE) (stdout, stderr) = proc.communicate() return stdout.strip().decode('utf8', 'replace') except FindCmdError: pass def genelatex(body, wrap): """Generate LaTeX document for dvipng backend.""" lt = LaTeXTool.instance() breqn = wrap and lt.use_breqn and kpsewhich("breqn.sty") yield u(r'\documentclass{article}') packages = lt.packages if breqn: packages = packages + ['breqn'] for pack in packages: yield u(r'\usepackage{{{0}}}'.format(pack)) yield u(r'\pagestyle{empty}') if lt.preamble: yield lt.preamble yield u(r'\begin{document}') if breqn: yield u(r'\begin{dmath*}') yield body yield u(r'\end{dmath*}') elif wrap: yield u'$${0}$$'.format(body) else: yield body yield u'\end{document}' _data_uri_template_png = u"""<img src="data:image/png;base64,%s" alt=%s />""" def latex_to_html(s, alt='image'): """Render LaTeX to HTML with embedded PNG data using data URIs. Parameters ---------- s : str The raw string containing valid inline LateX. alt : str The alt text to use for the HTML. """ base64_data = latex_to_png(s, encode=True).decode('ascii') if base64_data: return _data_uri_template_png % (base64_data, alt)

30.954082

82

0.624691

from io import BytesIO, open from base64 import encodestring import os import tempfile import shutil import subprocess from IPython.utils.process import find_cmd, FindCmdError from IPython.config import get_config from IPython.config.configurable import SingletonConfigurable from IPython.utils.traitlets import List, Bool, Unicode from IPython.utils.py3compat import cast_unicode, cast_unicode_py2 as u class LaTeXTool(SingletonConfigurable): def _config_default(self): return get_config() backends = List( Unicode, ["matplotlib", "dvipng"], help="Preferred backend to draw LaTeX math equations. " "Backends in the list are checked one by one and the first " "usable one is used. Note that `matplotlib` backend " "is usable only for inline style equations. To draw " "display style equations, `dvipng` backend must be specified. ", config=True) use_breqn = Bool( True, help="Use breqn.sty to automatically break long equations. " "This configuration takes effect only for dvipng backend.", config=True) packages = List( ['amsmath', 'amsthm', 'amssymb', 'bm'], help="A list of packages to use for dvipng backend. " "'breqn' will be automatically appended when use_breqn=True.", config=True) preamble = Unicode( help="Additional preamble to use when generating LaTeX source " "for dvipng backend.", config=True) def latex_to_png(s, encode=False, backend=None, wrap=False): s = cast_unicode(s) allowed_backends = LaTeXTool.instance().backends if backend is None: backend = allowed_backends[0] if backend not in allowed_backends: return None if backend == 'matplotlib': f = latex_to_png_mpl elif backend == 'dvipng': f = latex_to_png_dvipng else: raise ValueError('No such backend {0}'.format(backend)) bin_data = f(s, wrap) if encode and bin_data: bin_data = encodestring(bin_data) return bin_data def latex_to_png_mpl(s, wrap): try: from matplotlib import mathtext except ImportError: return None s = s.replace('$$', '$') if wrap: s = u'${0}$'.format(s) mt = mathtext.MathTextParser('bitmap') f = BytesIO() mt.to_png(f, s, fontsize=12) return f.getvalue() def latex_to_png_dvipng(s, wrap): try: find_cmd('latex') find_cmd('dvipng') except FindCmdError: return None try: workdir = tempfile.mkdtemp() tmpfile = os.path.join(workdir, "tmp.tex") dvifile = os.path.join(workdir, "tmp.dvi") outfile = os.path.join(workdir, "tmp.png") with open(tmpfile, "w", encoding='utf8') as f: f.writelines(genelatex(s, wrap)) with open(os.devnull, 'wb') as devnull: subprocess.check_call( ["latex", "-halt-on-error", "-interaction", "batchmode", tmpfile], cwd=workdir, stdout=devnull, stderr=devnull) subprocess.check_call( ["dvipng", "-T", "tight", "-x", "1500", "-z", "9", "-bg", "transparent", "-o", outfile, dvifile], cwd=workdir, stdout=devnull, stderr=devnull) with open(outfile, "rb") as f: return f.read() finally: shutil.rmtree(workdir) def kpsewhich(filename): try: find_cmd("kpsewhich") proc = subprocess.Popen( ["kpsewhich", filename], stdout=subprocess.PIPE, stderr=subprocess.PIPE) (stdout, stderr) = proc.communicate() return stdout.strip().decode('utf8', 'replace') except FindCmdError: pass def genelatex(body, wrap): lt = LaTeXTool.instance() breqn = wrap and lt.use_breqn and kpsewhich("breqn.sty") yield u(r'\documentclass{article}') packages = lt.packages if breqn: packages = packages + ['breqn'] for pack in packages: yield u(r'\usepackage{{{0}}}'.format(pack)) yield u(r'\pagestyle{empty}') if lt.preamble: yield lt.preamble yield u(r'\begin{document}') if breqn: yield u(r'\begin{dmath*}') yield body yield u(r'\end{dmath*}') elif wrap: yield u'$${0}$$'.format(body) else: yield body yield u'\end{document}' _data_uri_template_png = u"""<img src="data:image/png;base64,%s" alt=%s />""" def latex_to_html(s, alt='image'): base64_data = latex_to_png(s, encode=True).decode('ascii') if base64_data: return _data_uri_template_png % (base64_data, alt)

true

f7188e86396b3eca935897136cb622f3195ec895

2,702

py

Python

eval/eval_OTB.py

Existever/PyCFTrackers

3221e47aecca40de21ad9be875b2f8d960b4e09c

[ "MIT" ]

null

eval/eval_OTB.py

Existever/PyCFTrackers

3221e47aecca40de21ad9be875b2f8d960b4e09c

[ "MIT" ]

null

eval/eval_OTB.py

Existever/PyCFTrackers

3221e47aecca40de21ad9be875b2f8d960b4e09c

[ "MIT" ]

null

import argparse import glob from os.path import join, realpath, dirname from tqdm import tqdm from multiprocessing import Pool from lib.pysot.datasets import OTBDataset from lib.pysot.evaluation import OPEBenchmark from lib.pysot.visualization import draw_success_precision if __name__ == '__main__': parser = argparse.ArgumentParser(description='VOT Evaluation') parser.add_argument('--dataset', type=str, default='OTB50',help='dataset name') parser.add_argument('--result_dir', type=str, default='test/OTB100',help='tracker result root') parser.add_argument('--tracker_prefix', type=str,default='test', help='tracker prefix') parser.add_argument('--show_video_level', action='store_true') parser.add_argument('--num', type=int, help='number of processes to eval', default=8) parser.add_argument('--vis',type=bool,default=True) args = parser.parse_args() root = join(realpath(dirname(__file__)), '../dataset/OTB100') tracker_dir = args.result_dir trackers = glob.glob(join(tracker_dir, args.tracker_prefix+'*')) trackers = [t.split('/')[-1] for t in trackers] trackers=['MCCTH-Staple','MKCFup-LP','MKCFup','CSRDCF-LP','DSST-LP','LDES','SAMF','Staple-CA','OPENCV-CSRDCF','DCF','MOSSE','KCF','CSK','Staple','DSST','CN','DAT','ECO-HC','ECO','BACF','CSRDCF'] trackers = ['STRCF', 'KCF', 'ECO'] print(trackers) assert len(trackers) > 0 args.num = min(args.num, len(trackers)) if 'OTB' in args.dataset: dataset = OTBDataset(args.dataset, root) dataset.set_tracker(tracker_dir, trackers) benchmark = OPEBenchmark(dataset) success_ret = {} with Pool(processes=args.num) as pool: for ret in tqdm(pool.imap_unordered(benchmark.eval_success, trackers), desc='eval success', total=len(trackers), ncols=100): success_ret.update(ret) precision_ret = {} with Pool(processes=args.num) as pool: for ret in tqdm(pool.imap_unordered(benchmark.eval_precision, trackers), desc='eval precision', total=len(trackers), ncols=2): precision_ret.update(ret) benchmark.show_result(success_ret, precision_ret, show_video_level=args.show_video_level) if args.vis: for attr, videos in dataset.attr.items(): draw_success_precision(success_ret, name=dataset.name, videos=videos, attr=attr, precision_ret=precision_ret)

49.127273

198

0.620651

import argparse import glob from os.path import join, realpath, dirname from tqdm import tqdm from multiprocessing import Pool from lib.pysot.datasets import OTBDataset from lib.pysot.evaluation import OPEBenchmark from lib.pysot.visualization import draw_success_precision if __name__ == '__main__': parser = argparse.ArgumentParser(description='VOT Evaluation') parser.add_argument('--dataset', type=str, default='OTB50',help='dataset name') parser.add_argument('--result_dir', type=str, default='test/OTB100',help='tracker result root') parser.add_argument('--tracker_prefix', type=str,default='test', help='tracker prefix') parser.add_argument('--show_video_level', action='store_true') parser.add_argument('--num', type=int, help='number of processes to eval', default=8) parser.add_argument('--vis',type=bool,default=True) args = parser.parse_args() root = join(realpath(dirname(__file__)), '../dataset/OTB100') tracker_dir = args.result_dir trackers = glob.glob(join(tracker_dir, args.tracker_prefix+'*')) trackers = [t.split('/')[-1] for t in trackers] trackers=['MCCTH-Staple','MKCFup-LP','MKCFup','CSRDCF-LP','DSST-LP','LDES','SAMF','Staple-CA','OPENCV-CSRDCF','DCF','MOSSE','KCF','CSK','Staple','DSST','CN','DAT','ECO-HC','ECO','BACF','CSRDCF'] trackers = ['STRCF', 'KCF', 'ECO'] print(trackers) assert len(trackers) > 0 args.num = min(args.num, len(trackers)) if 'OTB' in args.dataset: dataset = OTBDataset(args.dataset, root) dataset.set_tracker(tracker_dir, trackers) benchmark = OPEBenchmark(dataset) success_ret = {} with Pool(processes=args.num) as pool: for ret in tqdm(pool.imap_unordered(benchmark.eval_success, trackers), desc='eval success', total=len(trackers), ncols=100): success_ret.update(ret) precision_ret = {} with Pool(processes=args.num) as pool: for ret in tqdm(pool.imap_unordered(benchmark.eval_precision, trackers), desc='eval precision', total=len(trackers), ncols=2): precision_ret.update(ret) benchmark.show_result(success_ret, precision_ret, show_video_level=args.show_video_level) if args.vis: for attr, videos in dataset.attr.items(): draw_success_precision(success_ret, name=dataset.name, videos=videos, attr=attr, precision_ret=precision_ret)

true

f7188f40cc5531a2407a8ee908641bbb4f109aeb

6,566

py

Python

starthinker/task/cm_to_dv/run.py

arbrown/starthinker

1a14664fb1a8f2a757b100363ea8958833b7754c

[ "Apache-2.0" ]

138

2018-11-28T21:42:44.000Z

2022-03-30T17:26:35.000Z

starthinker/task/cm_to_dv/run.py

arbrown/starthinker

1a14664fb1a8f2a757b100363ea8958833b7754c

[ "Apache-2.0" ]

36

2019-02-19T18:33:20.000Z

2022-01-24T18:02:44.000Z

starthinker/task/cm_to_dv/run.py

arbrown/starthinker

1a14664fb1a8f2a757b100363ea8958833b7754c

[ "Apache-2.0" ]

54

2018-12-06T05:47:32.000Z

2022-02-21T22:01:01.000Z

########################################################################### # # Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ########################################################################### from starthinker.util import has_values from starthinker.util.data import get_rows from starthinker.task.cm_to_dv.cm_account import cm_account_clear from starthinker.task.cm_to_dv.cm_account import cm_account_load from starthinker.task.cm_to_dv.cm_advertiser import cm_advertiser_clear from starthinker.task.cm_to_dv.cm_advertiser import cm_advertiser_load from starthinker.task.cm_to_dv.cm_campaign import cm_campaign_clear from starthinker.task.cm_to_dv.cm_campaign import cm_campaign_load from starthinker.task.cm_to_dv.cm_placement import cm_placement_clear from starthinker.task.cm_to_dv.cm_placement import cm_placement_load from starthinker.task.cm_to_dv.cm_placement_group import cm_placement_group_clear from starthinker.task.cm_to_dv.cm_placement_group import cm_placement_group_load from starthinker.task.cm_to_dv.cm_profile import cm_profile_clear from starthinker.task.cm_to_dv.cm_profile import cm_profile_load from starthinker.task.cm_to_dv.cm_site import cm_site_clear from starthinker.task.cm_to_dv.cm_site import cm_site_load from starthinker.task.cm_to_dv.dv_advertiser import dv_advertiser_clear from starthinker.task.cm_to_dv.dv_advertiser import dv_advertiser_load from starthinker.task.cm_to_dv.dv_algorithm import dv_algorithm_clear from starthinker.task.cm_to_dv.dv_algorithm import dv_algorithm_load from starthinker.task.cm_to_dv.dv_campaign import dv_campaign_clear from starthinker.task.cm_to_dv.dv_campaign import dv_campaign_load from starthinker.task.cm_to_dv.dv_insertion_order import dv_insertion_order_clear from starthinker.task.cm_to_dv.dv_insertion_order import dv_insertion_order_load from starthinker.task.cm_to_dv.dv_line_item import dv_line_item_clear from starthinker.task.cm_to_dv.dv_line_item import dv_line_item_load from starthinker.task.cm_to_dv.dv_partner import dv_partner_clear from starthinker.task.cm_to_dv.dv_partner import dv_partner_load from starthinker.task.cm_to_dv.preview_io import preview_io_clear from starthinker.task.cm_to_dv.preview_io import preview_io_load from starthinker.task.cm_to_dv.preview_io import preview_io_insert from starthinker.task.cm_to_dv.preview_li import preview_li_clear from starthinker.task.cm_to_dv.preview_li import preview_li_load from starthinker.task.cm_to_dv.preview_li import preview_li_insert from starthinker.task.cm_to_dv.log import log_clear from starthinker.task.cm_to_dv.log import log_clear def cm_to_dv(config, task): print('COMMAND:', task['command']) if task['command'] == 'Clear': dv_line_item_clear(config, task) dv_insertion_order_clear(config, task) dv_campaign_clear(config, task) dv_advertiser_clear(config, task) dv_algorithm_clear(config, task) dv_partner_clear(config, task) cm_profile_clear(config, task) cm_account_clear(config, task) cm_advertiser_clear(config, task) cm_campaign_clear(config, task) cm_placement_clear(config, task) cm_placement_group_clear(config, task) cm_site_clear(config, task) preview_io_clear(config, task) preview_li_clear(config, task) log_clear(config, task) elif task['command'] == 'Load': # load if profile filters are missing if not has_values(get_rows( config, task['auth_sheets'], { 'sheets': { 'sheet': task['sheet'], 'tab': 'CM Profiles', 'header':False, 'range': 'A2:A' }} )): print('CM Profile Load') cm_profile_load(config, task) # load if account filters are missing elif not has_values(get_rows( config, task['auth_sheets'], { 'sheets': { 'sheet': task['sheet'], 'tab': 'CM Accounts', 'header':False, 'range': 'A2:A' }} )): cm_account_load(config, task) # load if advertiser filters are missing elif not has_values(get_rows( config, task['auth_sheets'], { 'sheets': { 'sheet': task['sheet'], 'tab': 'CM Advertisers', 'header':False, 'range': 'A2:A' }} )): print('CM Advertiser Load') cm_advertiser_load(config, task) # load if advertiser filters are missing elif not has_values(get_rows( config, task['auth_sheets'], { 'sheets': { 'sheet': task['sheet'], 'tab': 'CM Campaigns', 'header':False, 'range': 'A2:A' }} )): print('CM Campaigns Load') cm_campaign_load(config, task) else: print('CM Placement Load') cm_placement_load(config, task) cm_placement_group_load(config, task) cm_site_load(config, task) # load if partner filters are missing if not has_values(get_rows( config, task['auth_sheets'], { 'sheets': { 'sheet': task['sheet'], 'tab': 'DV Partners', 'header':False, 'range': 'A2:A' }} )): print('DV Partner Load') dv_partner_load(config, task) # load if advertiser filters are missing elif not has_values(get_rows( config, task['auth_sheets'], { 'sheets': { 'sheet': task['sheet'], 'tab': 'DV Advertisers', 'header':False, 'range': 'A2:A' }} )): print('DV Advertiser Load') dv_advertiser_load(config, task) # load if advertiser filters are present else: print('DV Campaign / IO / LI Load') dv_algorithm_load(config, task) dv_campaign_load(config, task) dv_insertion_order_load(config, task) dv_line_item_load(config, task) elif task['command'] == 'Preview': log_clear(config, task) preview_io_load(config, task) preview_li_load(config, task) elif task['command'] == 'Insert': log_clear(config, task) preview_io_insert(config, task) preview_li_insert(config, task)

32.029268

81

0.700579

insert(config, task)

true

f7188fdf67798b6b524e83b8873542b335c4a5b4

8,649

py

Python

acq4/devices/PatchStar/patchstar.py

tropp/ACQ4

792e05e99cedfc175593d200aeabecd6fa6304ce

[ "MIT" ]

null

acq4/devices/PatchStar/patchstar.py

tropp/ACQ4

792e05e99cedfc175593d200aeabecd6fa6304ce

[ "MIT" ]

null

acq4/devices/PatchStar/patchstar.py

tropp/ACQ4

792e05e99cedfc175593d200aeabecd6fa6304ce

[ "MIT" ]

null

# -*- coding: utf-8 -*- import time import numpy as np from PyQt4 import QtGui, QtCore from ..Stage import Stage, MoveFuture, StageInterface from acq4.drivers.PatchStar import PatchStar as PatchStarDriver from acq4.util.Mutex import Mutex from acq4.util.Thread import Thread from acq4.pyqtgraph import debug, ptime, SpinBox class PatchStar(Stage): """ A Scientifica PatchStar manipulator. port: <serial port> # eg. 'COM1' or '/dev/ttyACM0' """ def __init__(self, man, config, name): self.port = config.pop('port') self.scale = config.pop('scale', (1e-7, 1e-7, 1e-7)) self.dev = PatchStarDriver(self.port) self._lastMove = None man.sigAbortAll.connect(self.stop) Stage.__init__(self, man, config, name) # clear cached position for this device and re-read to generate an initial position update self._lastPos = None self.getPosition(refresh=True) self.setUserSpeed(3e-3) # Set scaling for each axis self.dev.send('UUX 6.4') self.dev.send('UUY 6.4') self.dev.send('UUZ 6.4') # makes 1 roe turn == 1 second movement for any speed self.dev.send('JS 200') # Set approach angle self.dev.send('ANGLE %f' % self.pitch) self.dev.send('APPROACH 0') # thread for polling position changes self.monitor = MonitorThread(self) self.monitor.start() def capabilities(self): """Return a structure describing the capabilities of this device""" if 'capabilities' in self.config: return self.config['capabilities'] else: return { 'getPos': (True, True, True), 'setPos': (True, True, True), 'limits': (False, False, False), } def stop(self): """Stop the manipulator immediately. """ with self.lock: self.dev.stop() if self._lastMove is not None: self._lastMove._stopped() self._lastMove = None def setUserSpeed(self, v): """Set the speed of the rotary controller (m/turn). """ self.userSpeed = v self.dev.setSpeed(v / self.scale[0]) def _getPosition(self): # Called by superclass when user requests position refresh with self.lock: pos = self.dev.getPos() pos = [pos[i] * self.scale[i] for i in (0, 1, 2)] if pos != self._lastPos: self._lastPos = pos emit = True else: emit = False if emit: # don't emit signal while locked self.posChanged(pos) return pos def targetPosition(self): with self.lock: if self._lastMove is None or self._lastMove.isDone(): return self.getPosition() else: return self._lastMove.targetPos def quit(self): self.monitor.stop() Stage.quit(self) def _move(self, abs, rel, speed, linear): with self.lock: if self._lastMove is not None and not self._lastMove.isDone(): self.stop() pos = self._toAbsolutePosition(abs, rel) self._lastMove = PatchStarMoveFuture(self, pos, speed, self.userSpeed) return self._lastMove def deviceInterface(self, win): return PatchStarGUI(self, win) class MonitorThread(Thread): """Thread to poll for manipulator position changes. """ def __init__(self, dev): self.dev = dev self.lock = Mutex(recursive=True) self.stopped = False self.interval = 0.3 Thread.__init__(self) def start(self): self.stopped = False Thread.start(self) def stop(self): with self.lock: self.stopped = True def setInterval(self, i): with self.lock: self.interval = i def run(self): minInterval = 100e-3 interval = minInterval lastPos = None while True: try: with self.lock: if self.stopped: break maxInterval = self.interval pos = self.dev._getPosition() # this causes sigPositionChanged to be emitted if pos != lastPos: # if there was a change, then loop more rapidly for a short time. interval = minInterval lastPos = pos else: interval = min(maxInterval, interval*2) time.sleep(interval) except: debug.printExc('Error in PatchStar monitor thread:') time.sleep(maxInterval) class PatchStarMoveFuture(MoveFuture): """Provides access to a move-in-progress on a PatchStar manipulator. """ def __init__(self, dev, pos, speed, userSpeed): MoveFuture.__init__(self, dev, pos, speed) self._interrupted = False self._errorMSg = None self._finished = False pos = (np.array(pos) / np.array(self.dev.scale)).astype(int) if speed == 'fast': speed = 1e-3 elif speed == 'slow': speed = 1e-6 with self.dev.dev.lock: self.dev.dev.moveTo(pos, speed / self.dev.scale[0]) # reset to user speed immediately after starting move # (the move itself will run with the previous speed) self.dev.dev.setSpeed(userSpeed / self.dev.scale[0]) def wasInterrupted(self): """Return True if the move was interrupted before completing. """ return self._interrupted def isDone(self): """Return True if the move is complete. """ return self._getStatus() != 0 def _getStatus(self): # check status of move unless we already know it is complete. # 0: still moving; 1: finished successfully; -1: finished unsuccessfully if self._finished: if self._interrupted: return -1 else: return 1 if self.dev.dev.isMoving(): # Still moving return 0 # did we reach target? pos = self.dev._getPosition() if ((np.array(pos) - np.array(self.targetPos))**2).sum()**0.5 < 1e-6: # reached target self._finished = True return 1 else: # missed self._finished = True self._interrupted = True self._errorMsg = "Move did not complete." return -1 def _stopped(self): # Called when the manipulator is stopped, possibly interrupting this move. status = self._getStatus() if status == 1: # finished; ignore stop return elif status == -1: self._errorMsg = "Move was interrupted before completion." elif status == 0: # not actually stopped! This should not happen. raise RuntimeError("Interrupted move but manipulator is still running!") else: raise Exception("Unknown status: %s" % status) def errorMessage(self): return self._errorMsg class PatchStarGUI(StageInterface): def __init__(self, dev, win): StageInterface.__init__(self, dev, win) # Insert patchstar-specific controls into GUI self.psGroup = QtGui.QGroupBox('PatchStar Rotary Controller') self.layout.addWidget(self.psGroup, self.nextRow, 0, 1, 2) self.nextRow += 1 self.psLayout = QtGui.QGridLayout() self.psGroup.setLayout(self.psLayout) self.speedLabel = QtGui.QLabel('Speed') self.speedSpin = SpinBox(value=self.dev.userSpeed, suffix='m/turn', siPrefix=True, dec=True, limits=[1e-6, 10e-3]) self.revXBtn = QtGui.QPushButton('Reverse X') self.revYBtn = QtGui.QPushButton('Reverse Y') self.revZBtn = QtGui.QPushButton('Reverse Z') self.psLayout.addWidget(self.speedLabel, 0, 0) self.psLayout.addWidget(self.speedSpin, 0, 1) self.psLayout.addWidget(self.revXBtn, 1, 1) self.psLayout.addWidget(self.revYBtn, 2, 1) self.psLayout.addWidget(self.revZBtn, 3, 1) self.revXBtn.clicked.connect(lambda: self.dev.dev.send('JDX')) self.revYBtn.clicked.connect(lambda: self.dev.dev.send('JDY')) self.revZBtn.clicked.connect(lambda: self.dev.dev.send('JDZ')) self.speedSpin.valueChanged.connect(lambda v: self.dev.setDefaultSpeed(v))

33.01145

122

0.575327

import time import numpy as np from PyQt4 import QtGui, QtCore from ..Stage import Stage, MoveFuture, StageInterface from acq4.drivers.PatchStar import PatchStar as PatchStarDriver from acq4.util.Mutex import Mutex from acq4.util.Thread import Thread from acq4.pyqtgraph import debug, ptime, SpinBox class PatchStar(Stage): def __init__(self, man, config, name): self.port = config.pop('port') self.scale = config.pop('scale', (1e-7, 1e-7, 1e-7)) self.dev = PatchStarDriver(self.port) self._lastMove = None man.sigAbortAll.connect(self.stop) Stage.__init__(self, man, config, name) self._lastPos = None self.getPosition(refresh=True) self.setUserSpeed(3e-3) self.dev.send('UUX 6.4') self.dev.send('UUY 6.4') self.dev.send('UUZ 6.4') self.dev.send('JS 200') self.dev.send('ANGLE %f' % self.pitch) self.dev.send('APPROACH 0') self.monitor = MonitorThread(self) self.monitor.start() def capabilities(self): if 'capabilities' in self.config: return self.config['capabilities'] else: return { 'getPos': (True, True, True), 'setPos': (True, True, True), 'limits': (False, False, False), } def stop(self): with self.lock: self.dev.stop() if self._lastMove is not None: self._lastMove._stopped() self._lastMove = None def setUserSpeed(self, v): self.userSpeed = v self.dev.setSpeed(v / self.scale[0]) def _getPosition(self): with self.lock: pos = self.dev.getPos() pos = [pos[i] * self.scale[i] for i in (0, 1, 2)] if pos != self._lastPos: self._lastPos = pos emit = True else: emit = False if emit: self.posChanged(pos) return pos def targetPosition(self): with self.lock: if self._lastMove is None or self._lastMove.isDone(): return self.getPosition() else: return self._lastMove.targetPos def quit(self): self.monitor.stop() Stage.quit(self) def _move(self, abs, rel, speed, linear): with self.lock: if self._lastMove is not None and not self._lastMove.isDone(): self.stop() pos = self._toAbsolutePosition(abs, rel) self._lastMove = PatchStarMoveFuture(self, pos, speed, self.userSpeed) return self._lastMove def deviceInterface(self, win): return PatchStarGUI(self, win) class MonitorThread(Thread): def __init__(self, dev): self.dev = dev self.lock = Mutex(recursive=True) self.stopped = False self.interval = 0.3 Thread.__init__(self) def start(self): self.stopped = False Thread.start(self) def stop(self): with self.lock: self.stopped = True def setInterval(self, i): with self.lock: self.interval = i def run(self): minInterval = 100e-3 interval = minInterval lastPos = None while True: try: with self.lock: if self.stopped: break maxInterval = self.interval pos = self.dev._getPosition() # this causes sigPositionChanged to be emitted if pos != lastPos: # if there was a change, then loop more rapidly for a short time. interval = minInterval lastPos = pos else: interval = min(maxInterval, interval*2) time.sleep(interval) except: debug.printExc('Error in PatchStar monitor thread:') time.sleep(maxInterval) class PatchStarMoveFuture(MoveFuture): def __init__(self, dev, pos, speed, userSpeed): MoveFuture.__init__(self, dev, pos, speed) self._interrupted = False self._errorMSg = None self._finished = False pos = (np.array(pos) / np.array(self.dev.scale)).astype(int) if speed == 'fast': speed = 1e-3 elif speed == 'slow': speed = 1e-6 with self.dev.dev.lock: self.dev.dev.moveTo(pos, speed / self.dev.scale[0]) # reset to user speed immediately after starting move # (the move itself will run with the previous speed) self.dev.dev.setSpeed(userSpeed / self.dev.scale[0]) def wasInterrupted(self): return self._interrupted def isDone(self): return self._getStatus() != 0 def _getStatus(self): # check status of move unless we already know it is complete. # 0: still moving; 1: finished successfully; -1: finished unsuccessfully if self._finished: if self._interrupted: return -1 else: return 1 if self.dev.dev.isMoving(): # Still moving return 0 # did we reach target? pos = self.dev._getPosition() if ((np.array(pos) - np.array(self.targetPos))**2).sum()**0.5 < 1e-6: # reached target self._finished = True return 1 else: # missed self._finished = True self._interrupted = True self._errorMsg = "Move did not complete." return -1 def _stopped(self): # Called when the manipulator is stopped, possibly interrupting this move. status = self._getStatus() if status == 1: # finished; ignore stop return elif status == -1: self._errorMsg = "Move was interrupted before completion." elif status == 0: # not actually stopped! This should not happen. raise RuntimeError("Interrupted move but manipulator is still running!") else: raise Exception("Unknown status: %s" % status) def errorMessage(self): return self._errorMsg class PatchStarGUI(StageInterface): def __init__(self, dev, win): StageInterface.__init__(self, dev, win) # Insert patchstar-specific controls into GUI self.psGroup = QtGui.QGroupBox('PatchStar Rotary Controller') self.layout.addWidget(self.psGroup, self.nextRow, 0, 1, 2) self.nextRow += 1 self.psLayout = QtGui.QGridLayout() self.psGroup.setLayout(self.psLayout) self.speedLabel = QtGui.QLabel('Speed') self.speedSpin = SpinBox(value=self.dev.userSpeed, suffix='m/turn', siPrefix=True, dec=True, limits=[1e-6, 10e-3]) self.revXBtn = QtGui.QPushButton('Reverse X') self.revYBtn = QtGui.QPushButton('Reverse Y') self.revZBtn = QtGui.QPushButton('Reverse Z') self.psLayout.addWidget(self.speedLabel, 0, 0) self.psLayout.addWidget(self.speedSpin, 0, 1) self.psLayout.addWidget(self.revXBtn, 1, 1) self.psLayout.addWidget(self.revYBtn, 2, 1) self.psLayout.addWidget(self.revZBtn, 3, 1) self.revXBtn.clicked.connect(lambda: self.dev.dev.send('JDX')) self.revYBtn.clicked.connect(lambda: self.dev.dev.send('JDY')) self.revZBtn.clicked.connect(lambda: self.dev.dev.send('JDZ')) self.speedSpin.valueChanged.connect(lambda v: self.dev.setDefaultSpeed(v))

true

f7188fe85522ebf6c7d8d5ad84760673a34d5f14

3,440

py

Python

plusportals/client.py

DhruvBisla/PlusPortalsAPI

606d145f1a61c474907db5b034af5c887783882a

[ "MIT" ]

4

2021-02-16T23:25:08.000Z

2022-01-04T01:11:39.000Z

plusportals/client.py

DhruvBisla/PlusPortalsAPI

606d145f1a61c474907db5b034af5c887783882a

[ "MIT" ]

2

2021-12-17T15:27:46.000Z

2021-12-18T04:21:48.000Z

plusportals/client.py

DhruvBisla/PlusPortalsAPI

606d145f1a61c474907db5b034af5c887783882a

[ "MIT" ]

2

2021-08-01T01:39:45.000Z

2021-12-17T15:22:51.000Z

import os import json import requests from typing import Optional from . import credentials from . import info from . import session class Client(session.Session): _SCHOOL_NAME : str = None _EMAIL : str = None _ID : int = None _PASSWORD : str = None markingPeriods : list = [] hasCachedCredentials : bool = (os.path.isfile(os.path.join((os.path.dirname(__file__)), 'credentials.json'))) def __init__(self, cacheCredentials : Optional[bool] = False, schoolName : Optional[str] = None, email : Optional[str] = None, ID : Optional[int] = None, password : Optional[str] = None): if cacheCredentials: Client.setCredentials(schoolName, email, ID, password) else: Client._SCHOOL_NAME = schoolName Client._EMAIL = email Client._ID = ID Client._PASSWORD = password if Client.hasCachedCredentials: Client._SCHOOL_NAME = credentials.getCredential('schoolName') Client._EMAIL = credentials.getCredential('email') Client._ID = credentials.getCredential('ID') Client._PASSWORD = credentials.getCredential('password') super().__init__(Client._SCHOOL_NAME, Client._EMAIL, Client._PASSWORD) Client.markingPeriods = self.getMarkingPeriods() self.hasGetGrades : bool = False self.grades : list[dict] = [] def reset(self) -> None: self.session.cookies.clear() self.getDetails() @classmethod def setCredentials(cls, schoolName: str, email: str, ID: int, password: str) -> None: credentials.setCredentials(schoolName, email, ID, password) Client.hasCachedCredentials = True def getGrades(self) -> requests.Response: None if (Client.markingPeriods is not None) else self.getMarkingPeriods() specHeaders = { '__requestverificationtoken': '{}'.format(self.requestVerificationToken), 'cookie': '__cfduid={}; ppschoollink={}; __RequestVerificationToken={}; _pps=-480; ASP.NET_SessionId={}; emailoption={}; UGUID={}; ppusername={}; .ASPXAUTH={}'.format(self.session.cookies.get_dict().get('__cfduid'), Client._SCHOOL_NAME, self.session.cookies.get_dict().get('__RequestVerificationToken'), self.session.cookies.get_dict().get('ASP.NET_SessionId'), self.session.cookies.get_dict().get('emailoption'), self.session.cookies.get_dict().get('UGUID'), self.session.cookies.get_dict().get('ppusername'), self.session.cookies.get_dict().get('.ASPXAUTH')) } try: agrades : list[dict] = [] responses : list[requests.Response.status_code] = [] for i in range(len(Client.markingPeriods)): response = (self.session.post(info.GRADES(self.markingPeriods[i]), headers=dict(info.BASE_HEADERS, **specHeaders))) agrades.append(json.loads(response.content.decode('utf-8'))) responses.append(response.status_code) except: print("Information provided was incorrect; Login was not successful.") self.grades = agrades self.hasGetGrades = True return responses def printGrades(self, markingPeriod : int) -> None: None if (self.hasGetGrades) else self.getGrades() mgrades = self.grades[markingPeriod-1] for i in mgrades["Data"]: print("{}'s grade is {}".format(i.get("CourseName")[:(len(i.get("CourseName")))-12],i.get("Average")))

51.343284

572

0.659593

import os import json import requests from typing import Optional from . import credentials from . import info from . import session class Client(session.Session): _SCHOOL_NAME : str = None _EMAIL : str = None _ID : int = None _PASSWORD : str = None markingPeriods : list = [] hasCachedCredentials : bool = (os.path.isfile(os.path.join((os.path.dirname(__file__)), 'credentials.json'))) def __init__(self, cacheCredentials : Optional[bool] = False, schoolName : Optional[str] = None, email : Optional[str] = None, ID : Optional[int] = None, password : Optional[str] = None): if cacheCredentials: Client.setCredentials(schoolName, email, ID, password) else: Client._SCHOOL_NAME = schoolName Client._EMAIL = email Client._ID = ID Client._PASSWORD = password if Client.hasCachedCredentials: Client._SCHOOL_NAME = credentials.getCredential('schoolName') Client._EMAIL = credentials.getCredential('email') Client._ID = credentials.getCredential('ID') Client._PASSWORD = credentials.getCredential('password') super().__init__(Client._SCHOOL_NAME, Client._EMAIL, Client._PASSWORD) Client.markingPeriods = self.getMarkingPeriods() self.hasGetGrades : bool = False self.grades : list[dict] = [] def reset(self) -> None: self.session.cookies.clear() self.getDetails() @classmethod def setCredentials(cls, schoolName: str, email: str, ID: int, password: str) -> None: credentials.setCredentials(schoolName, email, ID, password) Client.hasCachedCredentials = True def getGrades(self) -> requests.Response: None if (Client.markingPeriods is not None) else self.getMarkingPeriods() specHeaders = { '__requestverificationtoken': '{}'.format(self.requestVerificationToken), 'cookie': '__cfduid={}; ppschoollink={}; __RequestVerificationToken={}; _pps=-480; ASP.NET_SessionId={}; emailoption={}; UGUID={}; ppusername={}; .ASPXAUTH={}'.format(self.session.cookies.get_dict().get('__cfduid'), Client._SCHOOL_NAME, self.session.cookies.get_dict().get('__RequestVerificationToken'), self.session.cookies.get_dict().get('ASP.NET_SessionId'), self.session.cookies.get_dict().get('emailoption'), self.session.cookies.get_dict().get('UGUID'), self.session.cookies.get_dict().get('ppusername'), self.session.cookies.get_dict().get('.ASPXAUTH')) } try: agrades : list[dict] = [] responses : list[requests.Response.status_code] = [] for i in range(len(Client.markingPeriods)): response = (self.session.post(info.GRADES(self.markingPeriods[i]), headers=dict(info.BASE_HEADERS, **specHeaders))) agrades.append(json.loads(response.content.decode('utf-8'))) responses.append(response.status_code) except: print("Information provided was incorrect; Login was not successful.") self.grades = agrades self.hasGetGrades = True return responses def printGrades(self, markingPeriod : int) -> None: None if (self.hasGetGrades) else self.getGrades() mgrades = self.grades[markingPeriod-1] for i in mgrades["Data"]: print("{}'s grade is {}".format(i.get("CourseName")[:(len(i.get("CourseName")))-12],i.get("Average")))

true

f71890129fc28aa45ba1867efbaf6e4c01b12e1b

5,309

py

Python

agent/DQN_agent.py

JiaXingBinggan/MSRL

fcc8b06eb1938a78549868b27f2962cb47b3d866

[ "Apache-2.0" ]

null

agent/DQN_agent.py

JiaXingBinggan/MSRL

fcc8b06eb1938a78549868b27f2962cb47b3d866

[ "Apache-2.0" ]

null

agent/DQN_agent.py

JiaXingBinggan/MSRL

fcc8b06eb1938a78549868b27f2962cb47b3d866

[ "Apache-2.0" ]

null

import numpy as np import mindspore from mindspore import context, ops, Tensor, nn from mindspore.common.parameter import Parameter, ParameterTuple import copy context.set_context(mode=context.PYNATIVE_MODE, device_target="CPU") _update_op = ops.MultitypeFuncGraph("update_op") @_update_op.register("Tensor", "Tensor") def _parameter_update(policy_param, target_param): assign = ops.Assign() output = assign(target_param, policy_param) return output class DQN(nn.Cell): neuron_nums = 16 def __init__(self, n_features, n_actions): super(DQN, self).__init__() self.net = nn.SequentialCell( nn.Dense(n_features, self.neuron_nums), nn.ReLU(), nn.Dense(self.neuron_nums, n_actions), ) def construct(self, s): return self.net(s) class PolicyNetWithLossCell(nn.Cell): """DQN policy network with loss cell""" def __init__(self, backbone, loss_fn): super(PolicyNetWithLossCell, self).__init__(auto_prefix=False) self._backbone = backbone self._loss_fn = loss_fn self.gather = ops.GatherD() def construct(self, x, a0, label): """constructor for Loss Cell""" out = self._backbone(x) out = self.gather(out, 1, a0) loss = self._loss_fn(out, label) return loss # Deep Q Network off-policy class DeepQNetwork: def __init__( self, n_actions, n_features, learning_rate=0.01, reward_decay=0.9, e_greedy=0.9, replace_target_iter=300, memory_size=500, batch_size=3, e_greedy_increment=None, ): self.n_actions = n_actions self.n_features = n_features self.lr = learning_rate self.gamma = reward_decay self.epsilon_max = e_greedy self.replace_target_iter = replace_target_iter self.memory_size = memory_size self.batch_size = batch_size self.epsilon_increment = e_greedy_increment self.epsilon = 0 if e_greedy_increment is not None else self.epsilon_max # total learning step self.learn_step_counter = 0 # initialize zero memory [s, a, r, s_] self.memory = np.zeros((self.memory_size, n_features * 2 + 2)) self.eval_net = DQN(self.n_features, self.n_actions) self.target_net = copy.deepcopy(self.eval_net) self.policy_param = ParameterTuple( self.eval_net.get_parameters()) self.target_param = ParameterTuple( self.target_net.get_parameters()) if not hasattr(self, 'memory_counter'): self.memory_counter = 0 loss_func = nn.MSELoss() opt = nn.Adam(self.eval_net.trainable_params(), learning_rate=self.lr) loss_q_net = PolicyNetWithLossCell(self.eval_net, loss_func) self.policy_network_train = nn.TrainOneStepCell(loss_q_net, opt) self.policy_network_train.set_train(mode=True) self.hyper_map = ops.HyperMap() self.cost_his = [] def store_transition(self, transition): index = self.memory_counter % self.memory_size self.memory[index, :] = transition self.memory_counter += 1 def reset_epsilon(self, epsilon): self.epsilon = epsilon def choose_action(self, observation): observation = Tensor(observation[np.newaxis, :], mindspore.float32) if np.random.uniform() < self.epsilon: self.eval_net.set_train(mode=False) action_v = self.eval_net(observation) action = np.argmax(action_v) else: action = np.random.randint(0, self.n_actions) return action def update_param(self): assign_result = self.hyper_map( _update_op, self.policy_param, self.target_param ) return assign_result def learn(self): if self.learn_step_counter % self.replace_target_iter == 0: self.update_param() if self.memory_counter > self.memory_size: sample_index = np.random.choice(self.memory_size, size=self.batch_size, replace=False) else: sample_index = np.random.choice(self.memory_counter, size=self.batch_size, replace=False) batch_memory = Tensor(self.memory[sample_index, :], mindspore.float32) b_s = batch_memory[:, :self.n_features] b_a = ops.ExpandDims()(batch_memory[:, self.n_features], 1).astype(mindspore.int32) b_r = ops.ExpandDims()(batch_memory[:, self.n_features + 1], 1) b_s_ = batch_memory[:, -self.n_features:] q_next = self.target_net(b_s_).max(axis=1) q_target = b_r + self.gamma * q_next loss = self.policy_network_train(b_s, b_a, q_target) self.cost_his.append(round(float(np.mean(loss.asnumpy())), 3)) # increasing epsilon self.epsilon = self.epsilon + self.epsilon_increment if self.epsilon < self.epsilon_max else self.epsilon_max self.learn_step_counter += 1 return loss def plot_cost(self): import matplotlib.pyplot as plt plt.plot(np.arange(len(self.cost_his)), self.cost_his) plt.ylabel('Cost') plt.xlabel('training steps') plt.show()

32.175758

117

0.638727

import numpy as np import mindspore from mindspore import context, ops, Tensor, nn from mindspore.common.parameter import Parameter, ParameterTuple import copy context.set_context(mode=context.PYNATIVE_MODE, device_target="CPU") _update_op = ops.MultitypeFuncGraph("update_op") @_update_op.register("Tensor", "Tensor") def _parameter_update(policy_param, target_param): assign = ops.Assign() output = assign(target_param, policy_param) return output class DQN(nn.Cell): neuron_nums = 16 def __init__(self, n_features, n_actions): super(DQN, self).__init__() self.net = nn.SequentialCell( nn.Dense(n_features, self.neuron_nums), nn.ReLU(), nn.Dense(self.neuron_nums, n_actions), ) def construct(self, s): return self.net(s) class PolicyNetWithLossCell(nn.Cell): def __init__(self, backbone, loss_fn): super(PolicyNetWithLossCell, self).__init__(auto_prefix=False) self._backbone = backbone self._loss_fn = loss_fn self.gather = ops.GatherD() def construct(self, x, a0, label): out = self._backbone(x) out = self.gather(out, 1, a0) loss = self._loss_fn(out, label) return loss class DeepQNetwork: def __init__( self, n_actions, n_features, learning_rate=0.01, reward_decay=0.9, e_greedy=0.9, replace_target_iter=300, memory_size=500, batch_size=3, e_greedy_increment=None, ): self.n_actions = n_actions self.n_features = n_features self.lr = learning_rate self.gamma = reward_decay self.epsilon_max = e_greedy self.replace_target_iter = replace_target_iter self.memory_size = memory_size self.batch_size = batch_size self.epsilon_increment = e_greedy_increment self.epsilon = 0 if e_greedy_increment is not None else self.epsilon_max self.learn_step_counter = 0 self.memory = np.zeros((self.memory_size, n_features * 2 + 2)) self.eval_net = DQN(self.n_features, self.n_actions) self.target_net = copy.deepcopy(self.eval_net) self.policy_param = ParameterTuple( self.eval_net.get_parameters()) self.target_param = ParameterTuple( self.target_net.get_parameters()) if not hasattr(self, 'memory_counter'): self.memory_counter = 0 loss_func = nn.MSELoss() opt = nn.Adam(self.eval_net.trainable_params(), learning_rate=self.lr) loss_q_net = PolicyNetWithLossCell(self.eval_net, loss_func) self.policy_network_train = nn.TrainOneStepCell(loss_q_net, opt) self.policy_network_train.set_train(mode=True) self.hyper_map = ops.HyperMap() self.cost_his = [] def store_transition(self, transition): index = self.memory_counter % self.memory_size self.memory[index, :] = transition self.memory_counter += 1 def reset_epsilon(self, epsilon): self.epsilon = epsilon def choose_action(self, observation): observation = Tensor(observation[np.newaxis, :], mindspore.float32) if np.random.uniform() < self.epsilon: self.eval_net.set_train(mode=False) action_v = self.eval_net(observation) action = np.argmax(action_v) else: action = np.random.randint(0, self.n_actions) return action def update_param(self): assign_result = self.hyper_map( _update_op, self.policy_param, self.target_param ) return assign_result def learn(self): if self.learn_step_counter % self.replace_target_iter == 0: self.update_param() if self.memory_counter > self.memory_size: sample_index = np.random.choice(self.memory_size, size=self.batch_size, replace=False) else: sample_index = np.random.choice(self.memory_counter, size=self.batch_size, replace=False) batch_memory = Tensor(self.memory[sample_index, :], mindspore.float32) b_s = batch_memory[:, :self.n_features] b_a = ops.ExpandDims()(batch_memory[:, self.n_features], 1).astype(mindspore.int32) b_r = ops.ExpandDims()(batch_memory[:, self.n_features + 1], 1) b_s_ = batch_memory[:, -self.n_features:] q_next = self.target_net(b_s_).max(axis=1) q_target = b_r + self.gamma * q_next loss = self.policy_network_train(b_s, b_a, q_target) self.cost_his.append(round(float(np.mean(loss.asnumpy())), 3)) self.epsilon = self.epsilon + self.epsilon_increment if self.epsilon < self.epsilon_max else self.epsilon_max self.learn_step_counter += 1 return loss def plot_cost(self): import matplotlib.pyplot as plt plt.plot(np.arange(len(self.cost_his)), self.cost_his) plt.ylabel('Cost') plt.xlabel('training steps') plt.show()

true

f718913f5c1602a006b860d8a1473f9c5e8ad63a

1,114

py

Python

base/base_train.py

AndersDHenriksen/Tensorflow-Project-Template

32dfeaaf1243587af4ceb7b378c135092ddb9258

[ "Apache-2.0" ]

null

base/base_train.py

AndersDHenriksen/Tensorflow-Project-Template

32dfeaaf1243587af4ceb7b378c135092ddb9258

[ "Apache-2.0" ]

null

base/base_train.py

AndersDHenriksen/Tensorflow-Project-Template

32dfeaaf1243587af4ceb7b378c135092ddb9258

[ "Apache-2.0" ]

1

2018-07-09T03:01:18.000Z

import tensorflow as tf class BaseTrain: def __init__(self, sess, model, data, config, logger): self.model = model self.logger = logger self.config = config self.sess = sess self.data = data self.init = tf.group(tf.global_variables_initializer(), tf.local_variables_initializer()) if not self.model.is_loaded: self.sess.run(self.init) def train(self): for cur_epoch in range(self.model.cur_epoch_tensor.eval(self.sess), self.config.num_epochs + 1, 1): self.train_epoch() self.sess.run(self.model.increment_cur_epoch_tensor) def train_epoch(self): """ implement the logic of epoch: -loop over the number of iterations in the config and call the train step -add any summaries you want using the summary """ raise NotImplementedError def train_step(self): """ implement the logic of the train step - run the tensorflow session - return any metrics you need to summarize """ raise NotImplementedError

31.828571

107

0.630162

import tensorflow as tf class BaseTrain: def __init__(self, sess, model, data, config, logger): self.model = model self.logger = logger self.config = config self.sess = sess self.data = data self.init = tf.group(tf.global_variables_initializer(), tf.local_variables_initializer()) if not self.model.is_loaded: self.sess.run(self.init) def train(self): for cur_epoch in range(self.model.cur_epoch_tensor.eval(self.sess), self.config.num_epochs + 1, 1): self.train_epoch() self.sess.run(self.model.increment_cur_epoch_tensor) def train_epoch(self): raise NotImplementedError def train_step(self): raise NotImplementedError

true

f71891d9166196c7b6043b3a9276fa1418b86155

10,866

py

Python

modules/nmt.py

tjuwlz/MachineTranslation

6e6fc757060ccd076e0ab4313562b1c34892fc60

[ "Apache-2.0" ]

1

2019-09-26T08:23:20.000Z

modules/nmt.py

LindgeW/MachineTranslation

7335c7e95d2ca23ca7e26c45d4b8b13e2ce96704

[ "Apache-2.0" ]

null

modules/nmt.py

LindgeW/MachineTranslation

7335c7e95d2ca23ca7e26c45d4b8b13e2ce96704

[ "Apache-2.0" ]

null

from datautil.dataloader import batch_iter import torch.nn.functional as F import torch.optim as optim import torch.nn.utils as nn_utils import time import torch import numpy as np from config.Const import * class NMT(object): def __init__(self, encoder, decoder): super(NMT, self).__init__() self.encoder = encoder self.decoder = decoder def summary(self): print('encoder:', self.encoder) print('decoder:', self.decoder) # 训练一轮 def train(self, train_pairs, enc_optimizer, dec_optimizer, args, src_vocab, tgt_vocab): train_loss = 0 for src_batch, tgt_batch in batch_iter(train_pairs, args, src_vocab, tgt_vocab): loss = 0 # enc_out: (batch_size, seq_len, hidden_size * nb_directions) # enc_hidden: (num_layers * nb_directions, batch_size, hidden_size) enc_out, enc_hidden = self.encoder(src_batch.src_idxs, mask=src_batch.non_pad_mask) self.encoder.zero_grad() self.decoder.zero_grad() dec_hidden = enc_hidden dec_input = tgt_batch.src_idxs[0].unsqueeze(1) if np.random.uniform(0, 1) <= args.teacher_force: # print('以目标作为下一个输入') for i in range(1, tgt_batch.src_idxs.size(0)): dec_out, dec_hidden = self.decoder(dec_input, dec_hidden, enc_out) dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) loss += self.calc_loss(dec_out, tgt_batch.src_idxs[i]) train_loss += loss.data.item() dec_input = tgt_batch.src_idxs[i].unsqueeze(1) else: # print('以网络的预测输出作为下一个输入') for i in range(1, tgt_batch.src_idxs.size(0)): dec_out, dec_hidden = self.decoder(dec_input, dec_hidden, enc_out) dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) loss += self.calc_loss(dec_out, tgt_batch.src_idxs[i]) train_loss += loss.data.item() _, top_i = dec_out.data.topk(1) dec_input = top_i # (batch_size, 1) loss.backward() nn_utils.clip_grad_norm_(filter(lambda p: p.requires_grad, self.encoder.parameters()), max_norm=5.0) nn_utils.clip_grad_norm_(filter(lambda p: p.requires_grad, self.decoder.parameters()), max_norm=5.0) enc_optimizer.step() dec_optimizer.step() return train_loss / len(train_pairs) # 训练多轮 def train_iter(self, train_pairs, args, src_vocab, tgt_vocab): self.encoder.train() self.decoder.train() enc_optimizer = optim.Adam(filter(lambda p: p.requires_grad, self.encoder.parameters()), lr=args.lr) dec_optimizer = optim.Adam(filter(lambda p: p.requires_grad, self.decoder.parameters()), lr=args.lr) enc_lr_scheduler = optim.lr_scheduler.LambdaLR(enc_optimizer, lambda ep: max(0.95**ep, 1e-4)) dec_lr_scheduler = optim.lr_scheduler.LambdaLR(dec_optimizer, lambda ep: max(0.95**ep, 1e-4)) # enc_lr_scheduler = optim.lr_scheduler.LambdaLR(enc_optimizer, lambda ep: max(1 - 0.75 * ep / args.epoch, 1e-4)) # dec_lr_scheduler = optim.lr_scheduler.LambdaLR(dec_optimizer, lambda ep: max(1 - 0.75 * ep / args.epoch, 1e-4)) for i in range(args.epoch): enc_lr_scheduler.step() dec_lr_scheduler.step() t1 = time.time() train_loss = self.train(train_pairs, enc_optimizer, dec_optimizer, args, src_vocab, tgt_vocab) t2 = time.time() print('[Epoch %d] train loss: %.3f' % (i+1, train_loss)) print('encoder lr:', enc_lr_scheduler.get_lr()) print('decoder lr:', dec_lr_scheduler.get_lr()) print('time cost: %.2fs' % (t2 - t1)) def calc_loss(self, pred, tgt): return F.nll_loss(pred, tgt, ignore_index=0) # def evaluate(self, test_pairs, args, src_vocab, tgt_vocab): # self.encoder.eval() # self.decoder.eval() # pred_wds, tgt_wds = [], [] # for src_batch, tgt_batch in batch_iter(test_pairs, args, src_vocab, tgt_vocab): # batch_pred_wds, batch_tgt_wds = [], [] # enc_out, enc_hidden = self.encoder(src_batch.src_idxs, mask=src_batch.non_pad_mask) # # dec_hidden = enc_hidden # dec_input = tgt_batch.src_idxs[0] # for i in range(1, tgt_batch.src_idxs.size(0)): # dec_out, dec_hidden = self.decoder(dec_input, dec_hidden, enc_out) # # dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) # tgt_idxs = tgt_batch.src_idxs[i] # # greedy search # pred_idxs = dec_out.data.argmax(dim=1) # batch_pred_wds.append(tgt_vocab.index2word(pred_idxs.tolist())) # batch_tgt_wds.append(tgt_vocab.index2word(tgt_idxs.tolist())) # dec_input = pred_idxs # # pred_wds.extend(self.extract_valid(np.asarray(batch_pred_wds).T.tolist())) # tgt_wds.extend(self.extract_valid(np.asarray(batch_tgt_wds).T.tolist())) # # print('BLEU:', self.corpus_bleu(pred_wds, tgt_wds)) # beam search ''' 执行过程：设beam size = 3 1、选择t1时刻输出的概率分数最大的3个词 2、分别将t-1时刻选择的3个词作为当前时刻的输入 3、求t时刻累积的（序列）概率分数(历史所选择词的对数似然和)，选择分数值最大的3个词 4、重复2-3过程，直到到达最大长度（或遇到<eos>） ''' def evaluate(self, test_pairs, args, src_vocab, tgt_vocab): self.encoder.eval() self.decoder.eval() # pred_wds, tgt_wds = [], [] for src_batch, tgt_batch in batch_iter(test_pairs, args, src_vocab, tgt_vocab): # batch_pred_wds, batch_tgt_wds = [], [] enc_out, enc_hidden = self.encoder(src_batch.src_idxs, mask=src_batch.non_pad_mask) # 保存历史分数 seq_len, batch_size = tgt_batch.src_idxs.size() # (bz, beam_size) hist_score = torch.zeros((batch_size, args.beam_size), device=args.device) # (beam_size, bz, vocab_size) beam_score = torch.zeros((args.beam_size, batch_size, tgt_vocab.vocab_size), device=args.device) # (bz, beam_size, max_len) best_paths = torch.zeros((MAX_LEN, batch_size, args.beam_size), device=args.device) dec_hidden = enc_hidden dec_input = tgt_batch.src_idxs[0].unsqueeze(1) for i in range(1, min(MAX_LEN, seq_len)): if i == 1: # dec_input: (bz, 1) # dec_out: (bz, vocab_size) dec_out, dec_hidden = self.decoder(dec_input, dec_hidden, enc_out) dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) # (bz, beam_size) top_prob, top_idxs = dec_out.data.topk(args.beam_size, dim=1) hist_score = top_prob best_paths[i] = top_idxs # (bz, beam_size) dec_input = top_idxs else: # dec_input: (bz, beam_size) -> (beam_size, bz) dec_input = dec_input.transpose(0, 1) for j in range(args.beam_size): # dec_out: (bz, vocab_size) dec_out, dec_hidden = self.decoder(dec_input[j].unsqueeze(1), dec_hidden, enc_out) dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) beam_score[j] = dec_out # (bz, beam_size, 1) -> (bz, beam_size, vocab_size) hist_score = hist_score.unsqueeze(-1).expand((-1, -1, tgt_vocab.vocab_size)) hist_score += beam_score.transpose(0, 1) # (bz, beam_size, vocab_size) # (bz, beam_size * vocab_size) hist_score = hist_score.reshape((batch_size, -1)) # (bz, beam_size) top_prob, top_idxs = hist_score.topk(args.beam_size, dim=1) hist_score = top_prob top_idxs %= tgt_vocab.vocab_size best_paths[i] = top_idxs dec_input = top_idxs # pred_wds.extend(self.extract_valid(np.asarray(batch_pred_wds).T.tolist())) # tgt_wds.extend(self.extract_valid(np.asarray(batch_tgt_wds).T.tolist())) # 提取序列的非填充部分 def extract_valid(self, seqs: list): return list(map(lambda x: x[:x.index(EOS)] if EOS in x else x, seqs)) # 统计ngram数目 def count_ngram(self, cand: list, ref: list, n=1) -> int: assert len(cand) != 0 and len(ref) != 0 total_count = 0 for i in range(len(cand) - n + 1): cand_count, ref_count = 1, 0 ngram = cand[i: i + n] # 统计ngram在机器翻译译文中出现的次数 for j in range(i + n, len(cand) - n + 1): if ngram == cand[j: j + n]: cand_count += 1 # 统计ngram在人工译文中出现的次数 for k in range(len(ref) - n + 1): if ngram == ref[k: k + n]: ref_count += 1 total_count += min(cand_count, ref_count) return total_count # 计算单句话的BLEU值，取值在[0, 1]之间，越大越好 def sentence_bleu(self, cand: list, ref: list, N=4) -> float: ''' :param cand: sentence_tokens :param ref: sentence_tokens :return: ''' assert len(cand) != 0 and len(ref) != 0 # n-gram中n的取值在[1, 4]之间 res = 0 cand_len, ref_len = len(cand), len(ref) for n in range(1, N+1): cand_gram = max(0, cand_len - n + 1) res += 0.25 * np.log(self.count_ngram(cand, ref, n) / cand_gram) # 短译句惩罚因子 # bp = np.exp(1 - max(1., len(ref) / len(cand))) return np.exp(res + min(0., 1 - ref_len / cand_len)) # 计算多句话的BLEU值(注:不是直接对sentence bleu求和求平均) def corpus_bleu(self, cands: list, refs: list, N=4) -> float: ''' :param cands: [sentence_tokens1, sentence_tokens2] :param refs: [sentence_tokens1, sentence_tokens2] :return: ''' assert len(cands) != 0 and len(cands) == len(refs) ref_len, cand_len = 0, 0 for cand, ref in zip(cands, refs): ref_len += len(ref) cand_len += len(cand) res = 0 for n in range(1, N+1): n_match, n_grams = 0, 0 for cand, ref in zip(cands, refs): n_match += self.count_ngram(cand, ref, n) n_grams += max(0, len(cand) - n + 1) res += 0.25 * np.log(n_match / n_grams + 1e-8) return np.exp(res + min(0., 1 - ref_len / cand_len))

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from datautil.dataloader import batch_iter import torch.nn.functional as F import torch.optim as optim import torch.nn.utils as nn_utils import time import torch import numpy as np from config.Const import * class NMT(object): def __init__(self, encoder, decoder): super(NMT, self).__init__() self.encoder = encoder self.decoder = decoder def summary(self): print('encoder:', self.encoder) print('decoder:', self.decoder) def train(self, train_pairs, enc_optimizer, dec_optimizer, args, src_vocab, tgt_vocab): train_loss = 0 for src_batch, tgt_batch in batch_iter(train_pairs, args, src_vocab, tgt_vocab): loss = 0 enc_out, enc_hidden = self.encoder(src_batch.src_idxs, mask=src_batch.non_pad_mask) self.encoder.zero_grad() self.decoder.zero_grad() dec_hidden = enc_hidden dec_input = tgt_batch.src_idxs[0].unsqueeze(1) if np.random.uniform(0, 1) <= args.teacher_force: for i in range(1, tgt_batch.src_idxs.size(0)): dec_out, dec_hidden = self.decoder(dec_input, dec_hidden, enc_out) dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) loss += self.calc_loss(dec_out, tgt_batch.src_idxs[i]) train_loss += loss.data.item() dec_input = tgt_batch.src_idxs[i].unsqueeze(1) else: for i in range(1, tgt_batch.src_idxs.size(0)): dec_out, dec_hidden = self.decoder(dec_input, dec_hidden, enc_out) dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) loss += self.calc_loss(dec_out, tgt_batch.src_idxs[i]) train_loss += loss.data.item() _, top_i = dec_out.data.topk(1) dec_input = top_i loss.backward() nn_utils.clip_grad_norm_(filter(lambda p: p.requires_grad, self.encoder.parameters()), max_norm=5.0) nn_utils.clip_grad_norm_(filter(lambda p: p.requires_grad, self.decoder.parameters()), max_norm=5.0) enc_optimizer.step() dec_optimizer.step() return train_loss / len(train_pairs) def train_iter(self, train_pairs, args, src_vocab, tgt_vocab): self.encoder.train() self.decoder.train() enc_optimizer = optim.Adam(filter(lambda p: p.requires_grad, self.encoder.parameters()), lr=args.lr) dec_optimizer = optim.Adam(filter(lambda p: p.requires_grad, self.decoder.parameters()), lr=args.lr) enc_lr_scheduler = optim.lr_scheduler.LambdaLR(enc_optimizer, lambda ep: max(0.95**ep, 1e-4)) dec_lr_scheduler = optim.lr_scheduler.LambdaLR(dec_optimizer, lambda ep: max(0.95**ep, 1e-4)) for i in range(args.epoch): enc_lr_scheduler.step() dec_lr_scheduler.step() t1 = time.time() train_loss = self.train(train_pairs, enc_optimizer, dec_optimizer, args, src_vocab, tgt_vocab) t2 = time.time() print('[Epoch %d] train loss: %.3f' % (i+1, train_loss)) print('encoder lr:', enc_lr_scheduler.get_lr()) print('decoder lr:', dec_lr_scheduler.get_lr()) print('time cost: %.2fs' % (t2 - t1)) def calc_loss(self, pred, tgt): return F.nll_loss(pred, tgt, ignore_index=0) def evaluate(self, test_pairs, args, src_vocab, tgt_vocab): self.encoder.eval() self.decoder.eval() for src_batch, tgt_batch in batch_iter(test_pairs, args, src_vocab, tgt_vocab): enc_out, enc_hidden = self.encoder(src_batch.src_idxs, mask=src_batch.non_pad_mask) seq_len, batch_size = tgt_batch.src_idxs.size() hist_score = torch.zeros((batch_size, args.beam_size), device=args.device) beam_score = torch.zeros((args.beam_size, batch_size, tgt_vocab.vocab_size), device=args.device) best_paths = torch.zeros((MAX_LEN, batch_size, args.beam_size), device=args.device) dec_hidden = enc_hidden dec_input = tgt_batch.src_idxs[0].unsqueeze(1) for i in range(1, min(MAX_LEN, seq_len)): if i == 1: dec_out, dec_hidden = self.decoder(dec_input, dec_hidden, enc_out) dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) top_prob, top_idxs = dec_out.data.topk(args.beam_size, dim=1) hist_score = top_prob best_paths[i] = top_idxs dec_input = top_idxs else: dec_input = dec_input.transpose(0, 1) for j in range(args.beam_size): dec_out, dec_hidden = self.decoder(dec_input[j].unsqueeze(1), dec_hidden, enc_out) dec_hidden *= tgt_batch.non_pad_mask[i].unsqueeze(1).repeat(1, dec_hidden.size(-1)) beam_score[j] = dec_out hist_score = hist_score.unsqueeze(-1).expand((-1, -1, tgt_vocab.vocab_size)) hist_score += beam_score.transpose(0, 1) hist_score = hist_score.reshape((batch_size, -1)) top_prob, top_idxs = hist_score.topk(args.beam_size, dim=1) hist_score = top_prob top_idxs %= tgt_vocab.vocab_size best_paths[i] = top_idxs dec_input = top_idxs def extract_valid(self, seqs: list): return list(map(lambda x: x[:x.index(EOS)] if EOS in x else x, seqs)) def count_ngram(self, cand: list, ref: list, n=1) -> int: assert len(cand) != 0 and len(ref) != 0 total_count = 0 for i in range(len(cand) - n + 1): cand_count, ref_count = 1, 0 ngram = cand[i: i + n] for j in range(i + n, len(cand) - n + 1): if ngram == cand[j: j + n]: cand_count += 1 for k in range(len(ref) - n + 1): if ngram == ref[k: k + n]: ref_count += 1 total_count += min(cand_count, ref_count) return total_count def sentence_bleu(self, cand: list, ref: list, N=4) -> float: assert len(cand) != 0 and len(ref) != 0 res = 0 cand_len, ref_len = len(cand), len(ref) for n in range(1, N+1): cand_gram = max(0, cand_len - n + 1) res += 0.25 * np.log(self.count_ngram(cand, ref, n) / cand_gram) return np.exp(res + min(0., 1 - ref_len / cand_len)) def corpus_bleu(self, cands: list, refs: list, N=4) -> float: assert len(cands) != 0 and len(cands) == len(refs) ref_len, cand_len = 0, 0 for cand, ref in zip(cands, refs): ref_len += len(ref) cand_len += len(cand) res = 0 for n in range(1, N+1): n_match, n_grams = 0, 0 for cand, ref in zip(cands, refs): n_match += self.count_ngram(cand, ref, n) n_grams += max(0, len(cand) - n + 1) res += 0.25 * np.log(n_match / n_grams + 1e-8) return np.exp(res + min(0., 1 - ref_len / cand_len))

true

f71892180c36d626c06032d591d63adab692cc84

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py

Python

indigo-web/cdmi/models.py

pericles-project/ERMR

99e19c476c813632d0508cdef65b4683e36f8e43

[ "Apache-2.0" ]

null

indigo-web/cdmi/models.py

pericles-project/ERMR

99e19c476c813632d0508cdef65b4683e36f8e43

[ "Apache-2.0" ]

null

indigo-web/cdmi/models.py

pericles-project/ERMR

99e19c476c813632d0508cdef65b4683e36f8e43

[ "Apache-2.0" ]

null

""""CDMI Models Copyright 2015 Archive Analytics Solutions - University of Liverpool Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import mimetypes from collections import OrderedDict from indigo.models.collection import Collection class CDMIContainer(object): """Wrapper to return CDMI fields fro an Indigo Collection""" def __init__(self, indigo_container, api_root): self.collection = indigo_container self.api_root = api_root def get_capabilitiesURI(self): """Mandatory URI to the capabilities for the object""" return (u'{0}/cdmi_capabilities/container{1}' ''.format(self.api_root, self.collection.path) ) def get_children(self, range=None): """Mandatory - Names of the children objects in the container object.""" child_c , child_r = self.collection.get_child() child_c = [ u"{}/".format(c) for c in child_c ] res = child_c + child_r if range: start, stop = ( int(el) for el in range.split("-", 1)) # map CDMI range value to python index stop += 1 else: start = 0 stop = len(res) return res[start:stop] def get_childrenrange(self): """Mandatory - The children of the container expressed as a range""" child_container , child_dataobject = self.collection.get_child() nb_child = len(child_container) + len(child_dataobject) if nb_child != 0: return "{}-{}".format(0, nb_child-1) else: return "0-0" def get_completionStatus(self): """Mandatory - A string indicating if the object is still in the process of being created or updated by another operation,""" val = self.collection.get_metadata_key("cdmi_completionStatus") if not val: val = "Complete" return val def get_domainURI(self): """Mandatory URI of the owning domain""" return ('{0}/cdmi_domains/indigo/'.format(self.api_root)) def get_metadata(self): md = self.collection.get_cdmi_metadata() md.update(self.collection.get_acl_metadata()) return md def get_objectID(self): """Mandatory object ID of the object""" return self.collection.uuid def get_objectName(self): """Conditional name of the object We don't support objects only accessible by ID so this is mandatory""" return self.collection.name def get_objectType(self): """Mandatory Object type""" return "application/cdmi-container" def get_parentID(self): """Conditional Object ID of the parent container object We don't support objects only accessible by ID so this is mandatory""" parent_path = self.collection.container if self.collection.is_root: parent_path = u"/" parent = Collection.find(parent_path) return parent.uuid def get_parentURI(self): """Conditional URI for the parent object We don't support objects only accessible by ID so this is mandatory""" # A container in CDMI has a '/' at the end but we don't (except for the # root) parent_path = self.collection.container if parent_path != '/' and parent_path != "null": parent_path = u"{}/".format(parent_path) return u"{}".format(parent_path) def get_path(self): return self.collection.path def get_percentComplete(self): """Optional - Indicate the percentage of completion as a numeric integer value from 0 through 100. 100 if the completionStatus is 'Complete'""" val = self.collection.get_metadata_key("cdmi_percentComplete") if not val: val = "100" return val class CDMIResource(object): """Wrapper to return CDMI fields fro an Indigo Resource""" def __init__(self, indigo_resource, api_root): self.resource = indigo_resource self.api_root = api_root def chunk_content(self): return self.resource.chunk_content() def get_capabilitiesURI(self): """Mandatory URI to the capabilities for the object""" return (u'{0}/cdmi_capabilities/dataobject{1}' ''.format(self.api_root, self.resource.path) ) def get_completionStatus(self): """Mandatory - A string indicating if the object is still in the process of being created or updated by another operation,""" val = self.resource.get_metadata_key("cdmi_completionStatus") if not val: val = "Complete" return val def get_domainURI(self): """Mandatory URI of the owning domain""" return ('{0}/cdmi_domains/indigo/'.format(self.api_root)) def get_length(self): return self.resource.size def get_metadata(self): md = self.resource.get_cdmi_metadata() md.update(self.resource.get_acl_metadata()) return md def get_mimetype(self): if self.resource.get_mimetype(): return self.resource.get_mimetype() # Give best guess at mimetype mimetype = mimetypes.guess_type(self.resource.name) if mimetype[0]: return mimetype[0] else: # Interpret as binary data return 'application/octet-stream' def get_objectID(self): """Mandatory object ID of the object""" return self.resource.uuid def get_objectName(self): """Conditional name of the object We don't support objects only accessible by ID so this is mandatory""" return self.resource.get_name() def get_objectType(self): """Mandatory Object type""" return "application/cdmi-object" def get_parentID(self): """Conditional Object ID of the parent container object We don't support objects only accessible by ID so this is mandatory""" parent = Collection.find(self.resource.container) return parent.uuid def get_parentURI(self): """Conditional URI for the parent object We don't support objects only accessible by ID so this is mandatory""" # A container in CDMI has a '/' at the end but we don't (except for the # root) parent_path = self.resource.container if parent_path != '/': parent_path = u"{}/".format(parent_path) return u"{}".format(parent_path) def get_path(self): return self.resource.path def get_percentComplete(self): """Optional - Indicate the percentage of completion as a numeric integer value from 0 through 100. 100 if the completionStatus is 'Complete'""" val = self.resource.get_metadata_key("cdmi_percentComplete") if not val: val = "100" return val def get_reference(self): return self.resource.url def get_url(self): return self.resource.url def get_value(self, range=None): driver = get_driver(self.resource.url) # TODO: Improve that for large files. Check what CDMI recommends # for stream access data = [] for chk in driver.chunk_content(): data.append(chk) res = ''.join([s for s in data]) if range: start, stop = (int(el) for el in range.split("-", 1)) # map CDMI range value to python index stop += 1 else: start = 0 stop = len(res) return res[start:stop] def get_valuerange(self): """Mandatory - The range of bytes of the data object to be returned in the value field""" return "0-{}".format(self.resource.size-1) def get_valuetransferencoding(self): """Mandatory - The value transfer encoding used for the data object value""" return "utf-8" def is_reference(self): """Check if the resource is a reference""" return self.resource.is_reference

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80

0.633909

import mimetypes from collections import OrderedDict from indigo.models.collection import Collection class CDMIContainer(object): def __init__(self, indigo_container, api_root): self.collection = indigo_container self.api_root = api_root def get_capabilitiesURI(self): return (u'{0}/cdmi_capabilities/container{1}' ''.format(self.api_root, self.collection.path) ) def get_children(self, range=None): child_c , child_r = self.collection.get_child() child_c = [ u"{}/".format(c) for c in child_c ] res = child_c + child_r if range: start, stop = ( int(el) for el in range.split("-", 1)) stop += 1 else: start = 0 stop = len(res) return res[start:stop] def get_childrenrange(self): child_container , child_dataobject = self.collection.get_child() nb_child = len(child_container) + len(child_dataobject) if nb_child != 0: return "{}-{}".format(0, nb_child-1) else: return "0-0" def get_completionStatus(self): val = self.collection.get_metadata_key("cdmi_completionStatus") if not val: val = "Complete" return val def get_domainURI(self): return ('{0}/cdmi_domains/indigo/'.format(self.api_root)) def get_metadata(self): md = self.collection.get_cdmi_metadata() md.update(self.collection.get_acl_metadata()) return md def get_objectID(self): return self.collection.uuid def get_objectName(self): return self.collection.name def get_objectType(self): return "application/cdmi-container" def get_parentID(self): parent_path = self.collection.container if self.collection.is_root: parent_path = u"/" parent = Collection.find(parent_path) return parent.uuid def get_parentURI(self): # root) parent_path = self.collection.container if parent_path != '/' and parent_path != "null": parent_path = u"{}/".format(parent_path) return u"{}".format(parent_path) def get_path(self): return self.collection.path def get_percentComplete(self): val = self.collection.get_metadata_key("cdmi_percentComplete") if not val: val = "100" return val class CDMIResource(object): def __init__(self, indigo_resource, api_root): self.resource = indigo_resource self.api_root = api_root def chunk_content(self): return self.resource.chunk_content() def get_capabilitiesURI(self): return (u'{0}/cdmi_capabilities/dataobject{1}' ''.format(self.api_root, self.resource.path) ) def get_completionStatus(self): val = self.resource.get_metadata_key("cdmi_completionStatus") if not val: val = "Complete" return val def get_domainURI(self): return ('{0}/cdmi_domains/indigo/'.format(self.api_root)) def get_length(self): return self.resource.size def get_metadata(self): md = self.resource.get_cdmi_metadata() md.update(self.resource.get_acl_metadata()) return md def get_mimetype(self): if self.resource.get_mimetype(): return self.resource.get_mimetype() # Give best guess at mimetype mimetype = mimetypes.guess_type(self.resource.name) if mimetype[0]: return mimetype[0] else: # Interpret as binary data return 'application/octet-stream' def get_objectID(self): return self.resource.uuid def get_objectName(self): return self.resource.get_name() def get_objectType(self): return "application/cdmi-object" def get_parentID(self): parent = Collection.find(self.resource.container) return parent.uuid def get_parentURI(self): # A container in CDMI has a '/' at the end but we don't (except for the parent_path = self.resource.container if parent_path != '/': parent_path = u"{}/".format(parent_path) return u"{}".format(parent_path) def get_path(self): return self.resource.path def get_percentComplete(self): val = self.resource.get_metadata_key("cdmi_percentComplete") if not val: val = "100" return val def get_reference(self): return self.resource.url def get_url(self): return self.resource.url def get_value(self, range=None): driver = get_driver(self.resource.url) data = [] for chk in driver.chunk_content(): data.append(chk) res = ''.join([s for s in data]) if range: start, stop = (int(el) for el in range.split("-", 1)) stop += 1 else: start = 0 stop = len(res) return res[start:stop] def get_valuerange(self): return "0-{}".format(self.resource.size-1) def get_valuetransferencoding(self): return "utf-8" def is_reference(self): return self.resource.is_reference

true

f7189242314d212cfcbc3ba03b7ee8ad651c0080

6,401

py

Python

tests/test_slot.py

glichtner/fhir.resources

94896d8f8a0b7dd69253762aab968f4fd6eb69a0

[ "BSD-3-Clause" ]

null

tests/test_slot.py

glichtner/fhir.resources

94896d8f8a0b7dd69253762aab968f4fd6eb69a0

[ "BSD-3-Clause" ]

null

tests/test_slot.py

glichtner/fhir.resources

94896d8f8a0b7dd69253762aab968f4fd6eb69a0

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """ Profile: http://hl7.org/fhir/StructureDefinition/Slot Release: R5 Version: 4.5.0 Build ID: 0d95498 Last updated: 2021-04-03T00:34:11.075+00:00 """ from pydantic.validators import bytes_validator # noqa: F401 from fhir.resources import fhirtypes # noqa: F401 from fhir.resources import slot def impl_slot_1(inst): assert inst.appointmentType.coding[0].code == "WALKIN" assert ( inst.appointmentType.coding[0].display == "A previously unscheduled walk-in visit" ) assert ( inst.appointmentType.coding[0].system == "http://terminology.hl7.org/CodeSystem/v2-0276" ) assert inst.comment == ( "Assessments should be performed before requesting " "appointments in this slot." ) assert inst.end == fhirtypes.Instant.validate("2013-12-25T09:30:00Z") assert inst.id == "example" assert inst.meta.tag[0].code == "HTEST" assert inst.meta.tag[0].display == "test health data" assert ( inst.meta.tag[0].system == "http://terminology.hl7.org/CodeSystem/v3-ActReason" ) assert inst.schedule.reference == "Schedule/example" assert inst.serviceCategory[0].coding[0].code == "17" assert inst.serviceCategory[0].coding[0].display == "General Practice" assert inst.serviceType[0].coding[0].code == "57" assert inst.serviceType[0].coding[0].display == "Immunization" assert inst.specialty[0].coding[0].code == "408480009" assert inst.specialty[0].coding[0].display == "Clinical immunology" assert inst.start == fhirtypes.Instant.validate("2013-12-25T09:15:00Z") assert inst.status == "free" assert inst.text.status == "generated" def test_slot_1(base_settings): """No. 1 tests collection for Slot. Test File: slot-example.json """ filename = base_settings["unittest_data_dir"] / "slot-example.json" inst = slot.Slot.parse_file( filename, content_type="application/json", encoding="utf-8" ) assert "Slot" == inst.resource_type impl_slot_1(inst) # testing reverse by generating data from itself and create again. data = inst.dict() assert "Slot" == data["resourceType"] inst2 = slot.Slot(**data) impl_slot_1(inst2) def impl_slot_2(inst): assert inst.comment == "Dr Careful is out of the office" assert inst.end == fhirtypes.Instant.validate("2013-12-25T10:00:00Z") assert inst.id == "2" assert inst.meta.tag[0].code == "HTEST" assert inst.meta.tag[0].display == "test health data" assert ( inst.meta.tag[0].system == "http://terminology.hl7.org/CodeSystem/v3-ActReason" ) assert inst.schedule.reference == "Schedule/example" assert inst.serviceCategory[0].coding[0].code == "17" assert inst.serviceCategory[0].coding[0].display == "General Practice" assert inst.start == fhirtypes.Instant.validate("2013-12-25T09:45:00Z") assert inst.status == "busy-tentative" assert inst.text.status == "generated" def test_slot_2(base_settings): """No. 2 tests collection for Slot. Test File: slot-example-tentative.json """ filename = base_settings["unittest_data_dir"] / "slot-example-tentative.json" inst = slot.Slot.parse_file( filename, content_type="application/json", encoding="utf-8" ) assert "Slot" == inst.resource_type impl_slot_2(inst) # testing reverse by generating data from itself and create again. data = inst.dict() assert "Slot" == data["resourceType"] inst2 = slot.Slot(**data) impl_slot_2(inst2) def impl_slot_3(inst): assert inst.comment == "Dr Careful is out of the office" assert inst.end == fhirtypes.Instant.validate("2013-12-25T09:45:00Z") assert inst.id == "3" assert inst.meta.tag[0].code == "HTEST" assert inst.meta.tag[0].display == "test health data" assert ( inst.meta.tag[0].system == "http://terminology.hl7.org/CodeSystem/v3-ActReason" ) assert inst.schedule.reference == "Schedule/example" assert inst.serviceCategory[0].coding[0].code == "17" assert inst.serviceCategory[0].coding[0].display == "General Practice" assert inst.start == fhirtypes.Instant.validate("2013-12-25T09:30:00Z") assert inst.status == "busy-unavailable" assert inst.text.status == "generated" def test_slot_3(base_settings): """No. 3 tests collection for Slot. Test File: slot-example-unavailable.json """ filename = base_settings["unittest_data_dir"] / "slot-example-unavailable.json" inst = slot.Slot.parse_file( filename, content_type="application/json", encoding="utf-8" ) assert "Slot" == inst.resource_type impl_slot_3(inst) # testing reverse by generating data from itself and create again. data = inst.dict() assert "Slot" == data["resourceType"] inst2 = slot.Slot(**data) impl_slot_3(inst2) def impl_slot_4(inst): assert inst.comment == ( "Assessments should be performed before requesting " "appointments in this slot." ) assert inst.end == fhirtypes.Instant.validate("2013-12-25T09:15:00Z") assert inst.id == "1" assert inst.identifier[0].system == "http://example.org/identifiers/slots" assert inst.identifier[0].value == "123132" assert inst.meta.tag[0].code == "HTEST" assert inst.meta.tag[0].display == "test health data" assert ( inst.meta.tag[0].system == "http://terminology.hl7.org/CodeSystem/v3-ActReason" ) assert inst.overbooked is True assert inst.schedule.reference == "Schedule/example" assert inst.serviceCategory[0].coding[0].code == "17" assert inst.serviceCategory[0].coding[0].display == "General Practice" assert inst.start == fhirtypes.Instant.validate("2013-12-25T09:00:00Z") assert inst.status == "busy" assert inst.text.status == "generated" def test_slot_4(base_settings): """No. 4 tests collection for Slot. Test File: slot-example-busy.json """ filename = base_settings["unittest_data_dir"] / "slot-example-busy.json" inst = slot.Slot.parse_file( filename, content_type="application/json", encoding="utf-8" ) assert "Slot" == inst.resource_type impl_slot_4(inst) # testing reverse by generating data from itself and create again. data = inst.dict() assert "Slot" == data["resourceType"] inst2 = slot.Slot(**data) impl_slot_4(inst2)

35.17033

87

0.675051

from pydantic.validators import bytes_validator from fhir.resources import fhirtypes from fhir.resources import slot def impl_slot_1(inst): assert inst.appointmentType.coding[0].code == "WALKIN" assert ( inst.appointmentType.coding[0].display == "A previously unscheduled walk-in visit" ) assert ( inst.appointmentType.coding[0].system == "http://terminology.hl7.org/CodeSystem/v2-0276" ) assert inst.comment == ( "Assessments should be performed before requesting " "appointments in this slot." ) assert inst.end == fhirtypes.Instant.validate("2013-12-25T09:30:00Z") assert inst.id == "example" assert inst.meta.tag[0].code == "HTEST" assert inst.meta.tag[0].display == "test health data" assert ( inst.meta.tag[0].system == "http://terminology.hl7.org/CodeSystem/v3-ActReason" ) assert inst.schedule.reference == "Schedule/example" assert inst.serviceCategory[0].coding[0].code == "17" assert inst.serviceCategory[0].coding[0].display == "General Practice" assert inst.serviceType[0].coding[0].code == "57" assert inst.serviceType[0].coding[0].display == "Immunization" assert inst.specialty[0].coding[0].code == "408480009" assert inst.specialty[0].coding[0].display == "Clinical immunology" assert inst.start == fhirtypes.Instant.validate("2013-12-25T09:15:00Z") assert inst.status == "free" assert inst.text.status == "generated" def test_slot_1(base_settings): filename = base_settings["unittest_data_dir"] / "slot-example.json" inst = slot.Slot.parse_file( filename, content_type="application/json", encoding="utf-8" ) assert "Slot" == inst.resource_type impl_slot_1(inst) data = inst.dict() assert "Slot" == data["resourceType"] inst2 = slot.Slot(**data) impl_slot_1(inst2) def impl_slot_2(inst): assert inst.comment == "Dr Careful is out of the office" assert inst.end == fhirtypes.Instant.validate("2013-12-25T10:00:00Z") assert inst.id == "2" assert inst.meta.tag[0].code == "HTEST" assert inst.meta.tag[0].display == "test health data" assert ( inst.meta.tag[0].system == "http://terminology.hl7.org/CodeSystem/v3-ActReason" ) assert inst.schedule.reference == "Schedule/example" assert inst.serviceCategory[0].coding[0].code == "17" assert inst.serviceCategory[0].coding[0].display == "General Practice" assert inst.start == fhirtypes.Instant.validate("2013-12-25T09:45:00Z") assert inst.status == "busy-tentative" assert inst.text.status == "generated" def test_slot_2(base_settings): filename = base_settings["unittest_data_dir"] / "slot-example-tentative.json" inst = slot.Slot.parse_file( filename, content_type="application/json", encoding="utf-8" ) assert "Slot" == inst.resource_type impl_slot_2(inst) data = inst.dict() assert "Slot" == data["resourceType"] inst2 = slot.Slot(**data) impl_slot_2(inst2) def impl_slot_3(inst): assert inst.comment == "Dr Careful is out of the office" assert inst.end == fhirtypes.Instant.validate("2013-12-25T09:45:00Z") assert inst.id == "3" assert inst.meta.tag[0].code == "HTEST" assert inst.meta.tag[0].display == "test health data" assert ( inst.meta.tag[0].system == "http://terminology.hl7.org/CodeSystem/v3-ActReason" ) assert inst.schedule.reference == "Schedule/example" assert inst.serviceCategory[0].coding[0].code == "17" assert inst.serviceCategory[0].coding[0].display == "General Practice" assert inst.start == fhirtypes.Instant.validate("2013-12-25T09:30:00Z") assert inst.status == "busy-unavailable" assert inst.text.status == "generated" def test_slot_3(base_settings): filename = base_settings["unittest_data_dir"] / "slot-example-unavailable.json" inst = slot.Slot.parse_file( filename, content_type="application/json", encoding="utf-8" ) assert "Slot" == inst.resource_type impl_slot_3(inst) data = inst.dict() assert "Slot" == data["resourceType"] inst2 = slot.Slot(**data) impl_slot_3(inst2) def impl_slot_4(inst): assert inst.comment == ( "Assessments should be performed before requesting " "appointments in this slot." ) assert inst.end == fhirtypes.Instant.validate("2013-12-25T09:15:00Z") assert inst.id == "1" assert inst.identifier[0].system == "http://example.org/identifiers/slots" assert inst.identifier[0].value == "123132" assert inst.meta.tag[0].code == "HTEST" assert inst.meta.tag[0].display == "test health data" assert ( inst.meta.tag[0].system == "http://terminology.hl7.org/CodeSystem/v3-ActReason" ) assert inst.overbooked is True assert inst.schedule.reference == "Schedule/example" assert inst.serviceCategory[0].coding[0].code == "17" assert inst.serviceCategory[0].coding[0].display == "General Practice" assert inst.start == fhirtypes.Instant.validate("2013-12-25T09:00:00Z") assert inst.status == "busy" assert inst.text.status == "generated" def test_slot_4(base_settings): filename = base_settings["unittest_data_dir"] / "slot-example-busy.json" inst = slot.Slot.parse_file( filename, content_type="application/json", encoding="utf-8" ) assert "Slot" == inst.resource_type impl_slot_4(inst) data = inst.dict() assert "Slot" == data["resourceType"] inst2 = slot.Slot(**data) impl_slot_4(inst2)

true

f71892bb0c58c579cec15c6e116e3bf81ee58e49

1,959

py

Python

celestial/client/rootfs/__init__.py

ams-tech/celestial

0c4c264563fe79d6838a1c40a1d114c1d6fcf23f

[ "MIT" ]

null

celestial/client/rootfs/__init__.py

ams-tech/celestial

0c4c264563fe79d6838a1c40a1d114c1d6fcf23f

[ "MIT" ]

null

celestial/client/rootfs/__init__.py

ams-tech/celestial

0c4c264563fe79d6838a1c40a1d114c1d6fcf23f

[ "MIT" ]

null

import os import subprocess from celestial.strings import Filesystems from celestial.client.system import cmdline def get_fs_types(path): """ Fetch a list of possible filesystem types :param path: :return: a list of strings with the possible filesystem type, else None """ if not os.path.exists(path): return None output = subprocess.check_output( ['''(eval $(blkid {} | awk ' {{ print $3 }} '); echo $TYPE)'''.format(path)], shell=True, executable='/bin/bash').decode().rstrip() if output == "": retval = [] elif output == Filesystems.EXT2: # ext3 filesystems misidentify as ext2. Consider both as possible outputs retval = [Filesystems.EXT2, Filesystems.EXT3] else: retval = [output] return retval def install(rootfs_file, device_node, block_size_kb=10, expected_fs=Filesystems.NONE): """ Install rootfs_file into device_node """ if expected_fs is not None: fs_types = get_fs_types(rootfs_file) if expected_fs not in fs_types: raise ValueError("rootfs_file is type {}, expected {}".format(rootfs_file, expected_fs)) result = subprocess.run([ 'dd', 'if={}'.format(rootfs_file), 'of={}'.format(device_node), 'bs={}K'.format(block_size_kb) ]) return result def get_boot_device(cmdline_file="/proc/cmdline"): """ Retrieve the "root" parameter of "/proc/cmdline" :param cmdline_file: The location of the cmdline file (that we booted with) :return: """ return cmdline.get_parameter("root", cmdline_file) def set_boot_device(boot_device, cmdline_file="/boot/cmdline"): """ Update the "root" parameter of the "cmdline_file" to "boot_device" :param boot_device: :param cmdline_file: The location of the boot partition's commandline file :return: """ cmdline.set_parameter("root", boot_device, cmdline_file)

30.609375

100

0.654926

import os import subprocess from celestial.strings import Filesystems from celestial.client.system import cmdline def get_fs_types(path): if not os.path.exists(path): return None output = subprocess.check_output( ['''(eval $(blkid {} | awk ' {{ print $3 }} '); echo $TYPE)'''.format(path)], shell=True, executable='/bin/bash').decode().rstrip() if output == "": retval = [] elif output == Filesystems.EXT2: retval = [Filesystems.EXT2, Filesystems.EXT3] else: retval = [output] return retval def install(rootfs_file, device_node, block_size_kb=10, expected_fs=Filesystems.NONE): if expected_fs is not None: fs_types = get_fs_types(rootfs_file) if expected_fs not in fs_types: raise ValueError("rootfs_file is type {}, expected {}".format(rootfs_file, expected_fs)) result = subprocess.run([ 'dd', 'if={}'.format(rootfs_file), 'of={}'.format(device_node), 'bs={}K'.format(block_size_kb) ]) return result def get_boot_device(cmdline_file="/proc/cmdline"): return cmdline.get_parameter("root", cmdline_file) def set_boot_device(boot_device, cmdline_file="/boot/cmdline"): cmdline.set_parameter("root", boot_device, cmdline_file)

true

f71892da316822a589e48a3fac5a0c42deab2e4e

22

py

Python

raster/tester.py

xiaoyingpu/gis

44c2ef2e604f6547e5bd29aa991e5930342adaba

[ "MIT" ]

1

2019-08-20T13:29:42.000Z

raster/tester.py

xiaoyingpu/gis

44c2ef2e604f6547e5bd29aa991e5930342adaba

[ "MIT" ]

null

raster/tester.py

xiaoyingpu/gis

44c2ef2e604f6547e5bd29aa991e5930342adaba

[ "MIT" ]

null

def test(): print(ds)

11

0.636364

def test(): print(ds)

true

f718935aaa88e73d7b6202df20fac852419becfe

759

py

Python

scripts/prepare_syllable_counts.py

voberoi/pysyllables

e1950ac306975f5d197bca7ad5ed9b0c680b0fb2

[ "MIT" ]

null

scripts/prepare_syllable_counts.py

voberoi/pysyllables

e1950ac306975f5d197bca7ad5ed9b0c680b0fb2

[ "MIT" ]

3

2020-03-24T17:17:49.000Z

2021-02-02T22:15:36.000Z

scripts/prepare_syllable_counts.py

voberoi/pysyllables

e1950ac306975f5d197bca7ad5ed9b0c680b0fb2

[ "MIT" ]

null

#!/usr/bin/env python3 import sys import codecs def main(): syllable_counts = {} filepath = sys.argv[1] lines = codecs.open(filepath, encoding="iso-8859-1").read().split("\n") for line in lines: if line.startswith(";;;") or len(line) == 0 or line.isspace(): continue word, phonemes = line.split(maxsplit=1) word = word.lower() syllable_count = 0 for phoneme in phonemes.split(): if phoneme[-1].isdigit(): syllable_count += 1 syllable_counts[word] = syllable_count for word in sorted(syllable_counts.keys()): syllable_count = syllable_counts[word] print(word + " " + str(syllable_count)) if __name__ == "__main__": main()

26.172414

75

0.59025

import sys import codecs def main(): syllable_counts = {} filepath = sys.argv[1] lines = codecs.open(filepath, encoding="iso-8859-1").read().split("\n") for line in lines: if line.startswith(";;;") or len(line) == 0 or line.isspace(): continue word, phonemes = line.split(maxsplit=1) word = word.lower() syllable_count = 0 for phoneme in phonemes.split(): if phoneme[-1].isdigit(): syllable_count += 1 syllable_counts[word] = syllable_count for word in sorted(syllable_counts.keys()): syllable_count = syllable_counts[word] print(word + " " + str(syllable_count)) if __name__ == "__main__": main()

true

f7189442bf63f4b7c1154480aea820c9a1a2688c

13,745

py

Python

startrek/script_mixins.py

drinkfalconpunch/star-trek

33c8155f94f11832d925a733b1f3ed6eecdcb31e

[ "MIT" ]

1

2019-08-21T18:56:42.000Z

startrek/script_mixins.py

drinkfalconpunch/star-trek

33c8155f94f11832d925a733b1f3ed6eecdcb31e

[ "MIT" ]

2

2021-03-31T19:22:55.000Z

2021-06-02T00:17:04.000Z

startrek/script_mixins.py

drinkfalconpunch/star-trek

33c8155f94f11832d925a733b1f3ed6eecdcb31e

[ "MIT" ]

null

import itertools import re from abc import ABCMeta, abstractmethod from collections import deque from pathlib import Path from typing import List from startrek.exceptions import ScriptException from startrek.utils import pairwise OMITTED = 'OMITTED' class ScriptBase(metaclass=ABCMeta): def __init__(self, script_text=None, script_path=None, series_name=None, season_number=0, episode_number=0): if script_text: self.script = script_text self.script_path = None elif script_path: self.script = self._get_script_path_contents(script_path) self.script_path = script_path else: raise ScriptException('No valid script.') self.series_name = series_name self.season_number = season_number self.episode_number = episode_number self.dialogue = None self.characters = None @abstractmethod def extract_dialogue_from_script(self, remove_blank_lines=False): pass @abstractmethod def section_headers(self): pass @abstractmethod def sectioned_script(self): pass @staticmethod def _get_script_path_contents(script_path): if isinstance(script_path, str): script_path = Path(script_path) if not script_path.exists(): raise ScriptException(f'Invalid script path: {script_path}') return open(script_path, 'r').read() @staticmethod def separate_dialogue(block): pass def _script_to_lines(self): return [line for line in self.script] class ScriptBlocks(ScriptBase): # TODO: Rename functions/attributes. SECTION_HEADER = '' ACT = ['ACT'] END = ['END OF'] NUMBERS = ['ONE', 'TWO', 'THREE', 'FOUR', 'FIVE', 'SIX', 'SEVEN', 'EIGHT', 'NINE', 'TEN'] SKIPS = ['THE END', 'END OF TEASER', 'FADE OUT', 'FADE OUT.'] for combo in itertools.product(END, ACT, NUMBERS): SKIPS.append(' '.join(combo)) for combo in itertools.product(ACT, NUMBERS): SKIPS.append(' '.join(combo)) _regex_section_number = r'^\d+[a-zA-Z]?' regex_section_number = re.compile(_regex_section_number) # regex to get everything between two brackets if it is the only thing in the line. _regex_header = r'^\d+[a-zA-Z]?\s*(.+)$' regex_header = re.compile(_regex_header) # regex to match line starting with capitalized words with a colon, signifying character dialogue. _regex_character = r"^\s*([A-Z-.'\"() ]+)\s*$" regex_character = re.compile(_regex_character) # # regex to match everything after the character name, colon, and space # _regex_dialogue_line = r'^[A-Z]{1,}.+:\s*(.+)' # regex_dialogue_line = re.compile(_regex_dialogue_line) def get_characters(self): if not self.dialogue: self.extract_dialogue_from_script() characters = set() for line in self.dialogue: matches = re.findall(self.regex_character, line.strip()) if matches: for match in matches: # Yay random corner cases! if match in self.SKIPS: continue parens = match.find('(') quote = match.find('\'') if parens != -1: match = match[:parens - 1] if quote != -1: match = match[:quote] if match.endswith('.'): while match.endswith('.'): match = match[:-1] if match.startswith('('): continue if match.endswith(')'): continue characters.add(match.replace('"', '')) self.characters = characters return characters def _iterate_lines_words(self, string, remove_blank_lines=True): if isinstance(string, list): string_list = string else: string_list = string.splitlines() for line in string_list: line = line.strip() words = line.split() if remove_blank_lines: if line: yield line, words else: yield line, words @staticmethod def _separate_dialogue_block(block): if not block: return # dict(name='None', text='') block = deque(block) temp = '' # Check if any initial lines are text and save them. while True: if not block: break line = block.popleft() if not line.isupper(): # First line is dialogue/text temp = f"{temp} {line}" else: block.appendleft(line) break dialogue = {} dialogue[0] = dict(name='None', text=temp.strip()) name = '' text = '' index = 1 for line in block: if line.isupper(): if name == line: continue else: if name: dialogue[index] = dict(name=name, text=text.strip()) name = line text = '' index += 1 else: name = line continue else: text = f"{text} {line}" return dialogue def combine_lines_by_character(self): sectioned = self.sectioned_script() for number, section in sectioned.items(): section['part'] = self._separate_dialogue_block(section['part']) return sectioned def _iterate_dialogue_dict(self): pass @staticmethod def replace_character_names(dialogue, characters): # Dict[str, Dict[str, Dict[int, Dict[str, str]]]]. characters.add('None') for section, content in dialogue.items(): parts = content['part'] for section, stuff in parts.items(): name = stuff['name'] for check in characters: if check in name: stuff['name'] = check break return dialogue def extract_dialogue_from_script(self, remove_blank_lines=True): script = deque(self.script.splitlines()) # Iterate through the lines until a number is found as the first character. while True: line = script.popleft() words = line.split() # Skip blank lines or a corner case where 2ND REV. FINAL DRAFT is in the script. if not words or any(x in words for x in ('REV', 'REV.', 'FINAL', 'OMITTED')): continue if words[0][0].isdigit(): # Put it back and break. Runs in O(1) time. script.appendleft(line) break if remove_blank_lines: script = list(filter(None, script)) # Strip out the white space in lines with text script = [s.lstrip() for s in script] # Remove page header lines and lines with OMITTED in between section numbers dialogue = list(filter(lambda line: line[:len(self.SECTION_HEADER)] != self.SECTION_HEADER, script)) # dialogue = list(filter(lambda line: 'OMITTED' not in line or line[0][0].isdigit(), dialogue)) self.dialogue = dialogue def _number_header_from_line(self, line): line = line.split() return line[0], ' '.join(line[1:]) def get_between_indices(self, s, begin, end): return s[begin:end] def section_headers(self): '''Returns the section headers from a block of dialogue and their respective line numbers in said block.''' if not self.dialogue: self.extract_dialogue_from_script() sections = {} indices = [] _regex_number = r'^\d{1,3}?[a-zA-Z]{0,1}' regex_number = re.compile(_regex_number) for index, line in enumerate(self.dialogue): words = line.split() if not words: continue try: int(words[0][0]) number = words[0] name = " ".join(words[1:]).replace(':', '') if not name: name = 'OMITTED' # Corner case check if year is in section number # if not re.findall(regex_number, number): # print(number, re.findall(regex_number, number)) if len(number) > 3 and number[3].isdigit(): continue # Check for same section number if number in sections.keys(): sections[number].append(name) else: sections[number] = [name] indices.append(index) except: continue setattr(self, 'section_names', sections) setattr(self, 'header_indices', indices) def sectioned_script(self): if not self.dialogue: self.extract_dialogue_from_script() if not hasattr(self, 'header_indices'): self.section_headers() sections = {} index_pairs = pairwise(self.header_indices) for pair in index_pairs: part = self.get_between_indices(self.dialogue, *pair) head = part.pop(0) number, header = self._number_header_from_line(head) sections[number] = dict(header=header, part=part) return sections class ScriptLines(ScriptBase): # regex to get everything between two brackets if it is the only thing in the line. _regex_header = r'^\[([^\]]+?)\]$' regex_header = re.compile(_regex_header) # regex to match line starting with capitalized words with a colon, signifying character dialogue. _regex_character = r'^([A-Z]{1,}.+):' regex_character = re.compile(_regex_character) # regex to match everything after the character name, colon, and space _regex_dialogue_line = r'^[A-Z]{1,}.+:\s*(.+)' regex_dialogue_line = re.compile(_regex_dialogue_line) def extract_dialogue_from_script(self, remove_blank_lines=False): script = deque(self.script.split('\n')) # Iterate through the lines until a number is found as the first character. while True: line = script.popleft() words = line.split() # Skip blank lines if not words: continue if words[0][0].isdigit(): # Put it back and break. Runs in O(1) time. script.appendleft(line) break if remove_blank_lines: script = list(filter(None, script)) # Strip out the white space in lines with text script = [s.lstrip() for s in script] # Remove page header lines and lines with OMITTED in between section numbers dialogue = list(filter(lambda line: line[:len(self.SECTION_HEADER)] != self.SECTION_HEADER, script)) dialogue = list(filter(lambda line: 'OMITTED' not in line or line[0][0].isdigit(), dialogue)) self.dialogue = dialogue return dialogue def section_headers(self): '''Returns the section headers from a block of dialogue and their respective line numbers in said block.''' if not self.script: raise AttributeError('') # 'Dialogue not found. Script.extract_entire_dialogue()') sections = {} indices = [] for index, line in enumerate(self.script): words = line.split() if not words: continue try: int(words[0][0]) number = words[0] name = " ".join(words[1:]) if not name: name = 'OMITTED' # Check for same section number if number in sections.keys(): sections[number].append(name) else: sections[number] = [name] indices.append(index) except: continue return sections, indices def sectioned_script(self): script = deque(self.script) sections = {} section_number = 0 while len(script) > 0: line = script.popleft().split() if line[0][0].isdigit(): # Check for duplicate section number if line[0] == section_number: continue else: section_number = line[0] sections[section_number] = {} sections[section_number]['section_header'] = ' '.join(line[1:]) sections[section_number]['text'] = [] else: sections[section_number]['text'].append(' '.join(line)) return sections def _check_header(self, line: str, starts_with='(', ends_with=')'): if line.strip().startswith(starts_with) and line.strip().endswith(ends_with): return True return False class ScriptTNG(ScriptBlocks): """Script class for The Next Generation.""" SECTION_HEADER = 'STAR TREK' pass class ScriptDeepSpaceNine(ScriptBlocks): """Script class for Deep Space Nine.""" SECTION_HEADER = 'DEEP SPACE' pass class ScriptEnterprise(ScriptLines): """Script class for Enterprise.""" pass class ScriptTOS(ScriptLines): """Script class for The Original Series.""" pass class ScriptVoyager(ScriptLines): """Script class for Voyager.""" pass

34.276808

108

0.555838

import itertools import re from abc import ABCMeta, abstractmethod from collections import deque from pathlib import Path from typing import List from startrek.exceptions import ScriptException from startrek.utils import pairwise OMITTED = 'OMITTED' class ScriptBase(metaclass=ABCMeta): def __init__(self, script_text=None, script_path=None, series_name=None, season_number=0, episode_number=0): if script_text: self.script = script_text self.script_path = None elif script_path: self.script = self._get_script_path_contents(script_path) self.script_path = script_path else: raise ScriptException('No valid script.') self.series_name = series_name self.season_number = season_number self.episode_number = episode_number self.dialogue = None self.characters = None @abstractmethod def extract_dialogue_from_script(self, remove_blank_lines=False): pass @abstractmethod def section_headers(self): pass @abstractmethod def sectioned_script(self): pass @staticmethod def _get_script_path_contents(script_path): if isinstance(script_path, str): script_path = Path(script_path) if not script_path.exists(): raise ScriptException(f'Invalid script path: {script_path}') return open(script_path, 'r').read() @staticmethod def separate_dialogue(block): pass def _script_to_lines(self): return [line for line in self.script] class ScriptBlocks(ScriptBase): SECTION_HEADER = '' ACT = ['ACT'] END = ['END OF'] NUMBERS = ['ONE', 'TWO', 'THREE', 'FOUR', 'FIVE', 'SIX', 'SEVEN', 'EIGHT', 'NINE', 'TEN'] SKIPS = ['THE END', 'END OF TEASER', 'FADE OUT', 'FADE OUT.'] for combo in itertools.product(END, ACT, NUMBERS): SKIPS.append(' '.join(combo)) for combo in itertools.product(ACT, NUMBERS): SKIPS.append(' '.join(combo)) _regex_section_number = r'^\d+[a-zA-Z]?' regex_section_number = re.compile(_regex_section_number) _regex_header = r'^\d+[a-zA-Z]?\s*(.+)$' regex_header = re.compile(_regex_header) _regex_character = r"^\s*([A-Z-.'\"() ]+)\s*$" regex_character = re.compile(_regex_character) # # regex to match everything after the character name, colon, and space # _regex_dialogue_line = r'^[A-Z]{1,}.+:\s*(.+)' # regex_dialogue_line = re.compile(_regex_dialogue_line) def get_characters(self): if not self.dialogue: self.extract_dialogue_from_script() characters = set() for line in self.dialogue: matches = re.findall(self.regex_character, line.strip()) if matches: for match in matches: # Yay random corner cases! if match in self.SKIPS: continue parens = match.find('(') quote = match.find('\'') if parens != -1: match = match[:parens - 1] if quote != -1: match = match[:quote] if match.endswith('.'): while match.endswith('.'): match = match[:-1] if match.startswith('('): continue if match.endswith(')'): continue characters.add(match.replace('"', '')) self.characters = characters return characters def _iterate_lines_words(self, string, remove_blank_lines=True): if isinstance(string, list): string_list = string else: string_list = string.splitlines() for line in string_list: line = line.strip() words = line.split() if remove_blank_lines: if line: yield line, words else: yield line, words @staticmethod def _separate_dialogue_block(block): if not block: return block = deque(block) temp = '' while True: if not block: break line = block.popleft() if not line.isupper(): temp = f"{temp} {line}" else: block.appendleft(line) break dialogue = {} dialogue[0] = dict(name='None', text=temp.strip()) name = '' text = '' index = 1 for line in block: if line.isupper(): if name == line: continue else: if name: dialogue[index] = dict(name=name, text=text.strip()) name = line text = '' index += 1 else: name = line continue else: text = f"{text} {line}" return dialogue def combine_lines_by_character(self): sectioned = self.sectioned_script() for number, section in sectioned.items(): section['part'] = self._separate_dialogue_block(section['part']) return sectioned def _iterate_dialogue_dict(self): pass @staticmethod def replace_character_names(dialogue, characters): characters.add('None') for section, content in dialogue.items(): parts = content['part'] for section, stuff in parts.items(): name = stuff['name'] for check in characters: if check in name: stuff['name'] = check break return dialogue def extract_dialogue_from_script(self, remove_blank_lines=True): script = deque(self.script.splitlines()) while True: line = script.popleft() words = line.split() if not words or any(x in words for x in ('REV', 'REV.', 'FINAL', 'OMITTED')): continue if words[0][0].isdigit(): script.appendleft(line) break if remove_blank_lines: script = list(filter(None, script)) script = [s.lstrip() for s in script] dialogue = list(filter(lambda line: line[:len(self.SECTION_HEADER)] != self.SECTION_HEADER, script)) self.dialogue = dialogue def _number_header_from_line(self, line): line = line.split() return line[0], ' '.join(line[1:]) def get_between_indices(self, s, begin, end): return s[begin:end] def section_headers(self): if not self.dialogue: self.extract_dialogue_from_script() sections = {} indices = [] _regex_number = r'^\d{1,3}?[a-zA-Z]{0,1}' regex_number = re.compile(_regex_number) for index, line in enumerate(self.dialogue): words = line.split() if not words: continue try: int(words[0][0]) number = words[0] name = " ".join(words[1:]).replace(':', '') if not name: name = 'OMITTED' if len(number) > 3 and number[3].isdigit(): continue if number in sections.keys(): sections[number].append(name) else: sections[number] = [name] indices.append(index) except: continue setattr(self, 'section_names', sections) setattr(self, 'header_indices', indices) def sectioned_script(self): if not self.dialogue: self.extract_dialogue_from_script() if not hasattr(self, 'header_indices'): self.section_headers() sections = {} index_pairs = pairwise(self.header_indices) for pair in index_pairs: part = self.get_between_indices(self.dialogue, *pair) head = part.pop(0) number, header = self._number_header_from_line(head) sections[number] = dict(header=header, part=part) return sections class ScriptLines(ScriptBase): _regex_header = r'^\[([^\]]+?)\]$' regex_header = re.compile(_regex_header) _regex_character = r'^([A-Z]{1,}.+):' regex_character = re.compile(_regex_character) _regex_dialogue_line = r'^[A-Z]{1,}.+:\s*(.+)' regex_dialogue_line = re.compile(_regex_dialogue_line) def extract_dialogue_from_script(self, remove_blank_lines=False): script = deque(self.script.split('\n')) while True: line = script.popleft() words = line.split() if not words: continue if words[0][0].isdigit(): script.appendleft(line) break if remove_blank_lines: script = list(filter(None, script)) script = [s.lstrip() for s in script] dialogue = list(filter(lambda line: line[:len(self.SECTION_HEADER)] != self.SECTION_HEADER, script)) dialogue = list(filter(lambda line: 'OMITTED' not in line or line[0][0].isdigit(), dialogue)) self.dialogue = dialogue return dialogue def section_headers(self): if not self.script: raise AttributeError('') sections = {} indices = [] for index, line in enumerate(self.script): words = line.split() if not words: continue try: int(words[0][0]) number = words[0] name = " ".join(words[1:]) if not name: name = 'OMITTED' if number in sections.keys(): sections[number].append(name) else: sections[number] = [name] indices.append(index) except: continue return sections, indices def sectioned_script(self): script = deque(self.script) sections = {} section_number = 0 while len(script) > 0: line = script.popleft().split() if line[0][0].isdigit(): if line[0] == section_number: continue else: section_number = line[0] sections[section_number] = {} sections[section_number]['section_header'] = ' '.join(line[1:]) sections[section_number]['text'] = [] else: sections[section_number]['text'].append(' '.join(line)) return sections def _check_header(self, line: str, starts_with='(', ends_with=')'): if line.strip().startswith(starts_with) and line.strip().endswith(ends_with): return True return False class ScriptTNG(ScriptBlocks): SECTION_HEADER = 'STAR TREK' pass class ScriptDeepSpaceNine(ScriptBlocks): SECTION_HEADER = 'DEEP SPACE' pass class ScriptEnterprise(ScriptLines): pass class ScriptTOS(ScriptLines): pass class ScriptVoyager(ScriptLines): pass

true

f7189717d2883a50d191f134c319e5e2e641ca0c

71

py

Python

ddtools/_version.py

Jyyin333/DMTools

42fed226ffc6291bc8c8438eea49b8488fb692d6

[ "MIT" ]

null

ddtools/_version.py

Jyyin333/DMTools

42fed226ffc6291bc8c8438eea49b8488fb692d6

[ "MIT" ]

null

ddtools/_version.py

Jyyin333/DMTools

42fed226ffc6291bc8c8438eea49b8488fb692d6

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- __version__ = '1.0.0'

17.75

24

0.549296

__version__ = '1.0.0'

true

f71897df774811c2c7e969c6d67c5191a419a861

2,722

py

Python

experimentmanager/utils.py

sciexpem/sciexpem

6de9a8039356588a5e817f0fa6bafd948220fc8f

[ "MIT" ]

null

experimentmanager/utils.py

sciexpem/sciexpem

6de9a8039356588a5e817f0fa6bafd948220fc8f

[ "MIT" ]

3

2019-05-10T14:57:30.000Z

2021-06-10T21:14:21.000Z

experimentmanager/utils.py

sciexpem/sciexpem

6de9a8039356588a5e817f0fa6bafd948220fc8f

[ "MIT" ]

1

2020-09-11T09:16:15.000Z

from . import models import pandas as pd import zipfile import os import re # def curve_io_formatter(x_column, y_columns, y_names, x_axis, y_axis, log=False): # curves = [] # for index, output in enumerate(y_columns): # curve = {round(float(k), 3): round(float(v), 3) for k, v in zip(x_column, output)} # curves.append({"name": y_names[index], "data": curve}) # return {"curves": curves, "x_axis": x_axis, "y_axis": y_axis, "log": log} excel_colunn_pattern = re.compile("(?P<name>[A-Za-z0-9_/]*)[ \t]+\[(?P<units>[(A-Za-z0-9_/)]*)\]") def curve_io_formatter(curves, x_axis, y_axis, logY=False): return {"curves": curves, "x_axis": x_axis, "y_axis": y_axis, "logY": logY} def extract_experiment_table(exp_id, units_row=False, units_brackets=True, reorder=True): dc = models.DataColumn.objects.filter(experiment_id=exp_id) # dict: name -> (units, data) column_names_units_data = {d.name if d.species is None else ",".join(d.species): (d.units, d.data) for d in dc} column_names = list(column_names_units_data.keys()) # we can freely reorder names if reorder: e = models.Experiment.objects.get(pk=exp_id) if ( e.reactor == "shock tube" and e.experiment_type == "ignition delay measurement") or e.reactor == "stirred reactor": column_names.remove("temperature") column_names.insert(0, "temperature") # units and data are taken as a consequence of the reordered names column_units = [column_names_units_data[cn][0] for cn in column_names] column_data = [[float(i) for i in column_names_units_data[cn][1]] for cn in column_names] # decimal to float (for excel seeing it as a number) if units_row: column_data = [[i] + j for i, j in zip(column_units, column_data)] if units_brackets: column_names = ["{} [{}]".format(i, j) for i, j in zip(column_names, column_units)] r = pd.DataFrame(dict(zip(column_names, column_data))) return r def zip_folders(f, folders, zipname, remove_trailing=""): with zipfile.ZipFile(f, 'w') as myzip: for fp in folders: for root, dirs, files in os.walk(fp): for f in files: new_name = os.path.relpath(os.path.join(root,f), remove_trailing) myzip.write(os.path.join(root, f), arcname=new_name) def check_data_excel(df): # check if the dataframe contain nan has_nan = df.isnull().values.any() if has_nan: return False columns = df.columns columns_extracted = [] for column in columns: p = excel_colunn_pattern.match(column) if not p: return False return True

34.025

131

0.640705

from . import models import pandas as pd import zipfile import os import re excel_colunn_pattern = re.compile("(?P<name>[A-Za-z0-9_/]*)[ \t]+\[(?P<units>[(A-Za-z0-9_/)]*)\]") def curve_io_formatter(curves, x_axis, y_axis, logY=False): return {"curves": curves, "x_axis": x_axis, "y_axis": y_axis, "logY": logY} def extract_experiment_table(exp_id, units_row=False, units_brackets=True, reorder=True): dc = models.DataColumn.objects.filter(experiment_id=exp_id) column_names_units_data = {d.name if d.species is None else ",".join(d.species): (d.units, d.data) for d in dc} column_names = list(column_names_units_data.keys()) if reorder: e = models.Experiment.objects.get(pk=exp_id) if ( e.reactor == "shock tube" and e.experiment_type == "ignition delay measurement") or e.reactor == "stirred reactor": column_names.remove("temperature") column_names.insert(0, "temperature") column_units = [column_names_units_data[cn][0] for cn in column_names] column_data = [[float(i) for i in column_names_units_data[cn][1]] for cn in column_names] if units_row: column_data = [[i] + j for i, j in zip(column_units, column_data)] if units_brackets: column_names = ["{} [{}]".format(i, j) for i, j in zip(column_names, column_units)] r = pd.DataFrame(dict(zip(column_names, column_data))) return r def zip_folders(f, folders, zipname, remove_trailing=""): with zipfile.ZipFile(f, 'w') as myzip: for fp in folders: for root, dirs, files in os.walk(fp): for f in files: new_name = os.path.relpath(os.path.join(root,f), remove_trailing) myzip.write(os.path.join(root, f), arcname=new_name) def check_data_excel(df): has_nan = df.isnull().values.any() if has_nan: return False columns = df.columns columns_extracted = [] for column in columns: p = excel_colunn_pattern.match(column) if not p: return False return True

true

f71898c3ed083524faabeea56c687bae2ca86d8e

807

py

Python

src/python/pants/backend/python/rules/setup_py_util_test.py

mpopenko-exos/pants

47d27037c8b13291fc9023e56ddd1b1defdf1b8e

[ "Apache-2.0" ]

null

src/python/pants/backend/python/rules/setup_py_util_test.py

mpopenko-exos/pants

47d27037c8b13291fc9023e56ddd1b1defdf1b8e

[ "Apache-2.0" ]

1

2018-09-04T17:37:34.000Z

2018-09-04T19:42:58.000Z

src/python/pants/backend/python/rules/setup_py_util_test.py

mpopenko-exos/pants

47d27037c8b13291fc9023e56ddd1b1defdf1b8e

[ "Apache-2.0" ]

null

# Copyright 2019 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). from pants.backend.python.rules.setup_py_util import distutils_repr testdata = { 'foo': 'bar', 'baz': { 'qux': [123, 456], 'quux': ('abc', b'xyz'), 'corge': {1, 2, 3} }, 'various_strings': [ "x'y", 'aaa\nbbb' ] } expected = """ { 'foo': 'bar', 'baz': { 'qux': [ 123, 456, ], 'quux': ( 'abc', 'xyz', ), 'corge': { 1, 2, 3, }, }, 'various_strings': [ 'x\\\'y', \"\"\"aaa\nbbb\"\"\", ], } """.strip() def test_distutils_repr(): assert expected == distutils_repr(testdata)

16.469388

67

0.448575

from pants.backend.python.rules.setup_py_util import distutils_repr testdata = { 'foo': 'bar', 'baz': { 'qux': [123, 456], 'quux': ('abc', b'xyz'), 'corge': {1, 2, 3} }, 'various_strings': [ "x'y", 'aaa\nbbb' ] } expected = """ { 'foo': 'bar', 'baz': { 'qux': [ 123, 456, ], 'quux': ( 'abc', 'xyz', ), 'corge': { 1, 2, 3, }, }, 'various_strings': [ 'x\\\'y', \"\"\"aaa\nbbb\"\"\", ], } """.strip() def test_distutils_repr(): assert expected == distutils_repr(testdata)

true

f71898d420e214a47c23384a2b7b0302f44ef350

175

py

Python

paginas/admin.py

DSheridanmt/Safety-Life

522578858f8e063e14d0274de008c345ef2c0a75

[ "MIT" ]

null

paginas/admin.py

DSheridanmt/Safety-Life

522578858f8e063e14d0274de008c345ef2c0a75

[ "MIT" ]

null

paginas/admin.py

DSheridanmt/Safety-Life

522578858f8e063e14d0274de008c345ef2c0a75

[ "MIT" ]

null

from django.contrib import admin #importar classes from .models import Publicacao, Tag # Register your models here. admin.site.register(Publicacao) admin.site.register(Tag)

19.444444

35

0.805714

from django.contrib import admin from .models import Publicacao, Tag admin.site.register(Publicacao) admin.site.register(Tag)

true

f7189913fe684be000682693e8c8998c0035fdb1

5,622

py

Python

2parser/sample.py

formalabstracts/CNL-CIC

c857ee0d52b4ba91dd06a51c8f9f3ec2749ca0eb

[ "MIT" ]

14

2019-06-27T16:34:39.000Z

2021-01-07T18:13:04.000Z

2parser/sample.py

formalabstracts/CNL-CIC

c857ee0d52b4ba91dd06a51c8f9f3ec2749ca0eb

[ "MIT" ]

8

2019-10-17T06:09:51.000Z

2020-03-25T15:51:32.000Z

2parser/sample.py

formalabstracts/CNL-CIC

c857ee0d52b4ba91dd06a51c8f9f3ec2749ca0eb

[ "MIT" ]

17

2019-06-27T16:34:53.000Z

2020-08-15T01:30:32.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Feb 16 05:48:26 2021 @author: thales Generate random samples from parsers """ from numpy.random import (poisson , binomial, randint) from tokenlib import (Item , Etok, mk_stream) import lib import state def bernoulli(p): return binomial(1,p) def ran(ls): if not ls: raise TypeError(f'ran, expected nonempty list {ls}') return ls return ls[randint(0,len(ls))] def mk_tok(v): toks = mk_stream(v) try: return toks.stream[0] except: raise IndexError(f'List index out of range. Empty list mk_tok({v})') def mk_toks(vs): toks = mk_stream(vs) return toks.stream def next_token(): return mk_tok('blah') def none(): return None def add_sample(self,other): def sample(): try: # debug acc1 = self.sample() acc2 = other.sample() return (acc1,acc2) except AttributeError as ex: raise AttributeError(f'MyAttributeError {other}') return sample def or_sample(self,other): def sample(): if bernoulli(0.5): return self.sample() return other.sample() return sample def treat_sample(self,treatment): def sample(): return treatment(self.sample()) return sample def some(self,sep,m): def sample(): if sep: if m==0: return [] return lib.flatten((self.sample(),sep.sample()) for _ in range(0,m-1))+[self.sample()] return [self.sample() for _ in range(0,m-1)] return sample def plus(self,sep): return some(self,sep,1 + poisson(0.5)) def many(self,sep): return some(self,sep,0 + poisson(0.5)) def atleast(self,n): return some(self,None,n + poisson(0.5)) def possibly(self): def sample(): if state.state.include_possibly: return self.sample() if bernoulli(0.5): return self.sample() return None return sample def if_test(self,p): def sample(): iteration_limit = 10 # arbitrary limit for _ in range(0,iteration_limit): acc = self.sample() # randomized guess if p(acc): return acc return next_token() # give up on test return sample def if_value(v): def sample(): return mk_tok(v) return sample def if_rawvalue(v): return if_value(v) def type_sample(ty:str): """ >>> type_sample('WORD') '...' """ d = {'STRING': ['"'+s+'"' for s in 'hello world so little time'.split()], 'CONTROLSEQ':['\\'+s for s in 'alpha beta gamma delta sum prod deg circ ast lneg times rtimes'.split()], 'DECIMAL':['3.14','2.718','1.0','4.96'], 'INTEGER': [str(i) for i in range(0,10)] , 'SYMBOL':['<','>','!=','+','-','*','^'], 'SYMBOL_QED':[r'\qed'], 'MAPSTO':[r'\mapsto'], 'MID':[r'\mid'], 'TMID':[r'\tmid'], 'ASSIGN':[':='], 'ARROW':[r'\to'], 'BLANK':['_'], 'ALT':['|'], 'PERIOD':['.'], 'COLON':[':'], 'APPLYSUB':[r'\sub'], 'COERCION': [r'\^'], 'LAMBDA':[r'\lambda'], 'PITY':[r'\Pity'], 'QUANTIFIER':[r'\forall',r'\exists'], 'VAR':[ f'{x}{n}' for x in 'b c x y z u v w'.split() for n in range(0,5)], 'WORD':"""estimate equation solution expression inequality random sample mean pair ordered function evaluate order operation property divisible exponent base multiple square common prime form factorization point plane line angle ray parallel intersecting perpendicular regular polygon degree circle diameter chord similar congruent symmetry leg triangle scalene equilateral trapezoid rotation transformation translation polyhedron integer positive opposite value origin coordinate area circumference word number blah part""".split(), 'ATOMIC_IDENTIFIER':'foo_bar bar3 foo22 sin_ cos_ atan2 ceil_ comb_ fabs_ factorial_ floor_ gcd_ sqrt_ log2 log10 pow_ '.split(), 'HIERARCHICAL_IDENTIFIER':['math.pi','math.ceil','math.abs'], 'FIELD_ACCESSOR':['.assoc','.distrib'], 'UNKNOWN':['?'], 'TEX_ERROR':[r'\error'] } return ran(d[ty]) def if_types(tys): """ >>> if_types(['WORD','INTEGER','DECIMAL'])() LexToken(...) """ def sample(): ty = ran(tys) return mk_tok(type_sample(ty)) return sample def all_sample(prs): def sample(): return [p.sample() for p in prs] return sample def first(prs): def sample(): if not prs: return None i = randint(0,len(prs)) return prs[i].sample() return sample #def lazy_call(pr): # def sample(): # return pr().sample() # return sample def first_word(ss): #DEBUG if not(ss): # raise IndexError(f'Index out of range, split first_word({ss})') s = ran(ss.split()) def sample(): return mk_tok(s) return sample def word_net_string(wn): s = ran([k for k in wn]) if not s: return '' return s + ' ' + word_net_string(wn[s]) def word_net(wn): def sample(): s = word_net_string(wn) return mk_toks(s) return sample if __name__ == "__main__": import doctest doctest.testmod(optionflags=doctest.ELLIPSIS | doctest.NORMALIZE_WHITESPACE) # doctest.testmod(verbose=True, optionflags=doctest.ELLIPSIS | doctest.NORMALIZE_WHITESPACE) # doctest.testmod()

26.394366

138

0.574173

from numpy.random import (poisson , binomial, randint) from tokenlib import (Item , Etok, mk_stream) import lib import state def bernoulli(p): return binomial(1,p) def ran(ls): if not ls: raise TypeError(f'ran, expected nonempty list {ls}') return ls return ls[randint(0,len(ls))] def mk_tok(v): toks = mk_stream(v) try: return toks.stream[0] except: raise IndexError(f'List index out of range. Empty list mk_tok({v})') def mk_toks(vs): toks = mk_stream(vs) return toks.stream def next_token(): return mk_tok('blah') def none(): return None def add_sample(self,other): def sample(): try: acc1 = self.sample() acc2 = other.sample() return (acc1,acc2) except AttributeError as ex: raise AttributeError(f'MyAttributeError {other}') return sample def or_sample(self,other): def sample(): if bernoulli(0.5): return self.sample() return other.sample() return sample def treat_sample(self,treatment): def sample(): return treatment(self.sample()) return sample def some(self,sep,m): def sample(): if sep: if m==0: return [] return lib.flatten((self.sample(),sep.sample()) for _ in range(0,m-1))+[self.sample()] return [self.sample() for _ in range(0,m-1)] return sample def plus(self,sep): return some(self,sep,1 + poisson(0.5)) def many(self,sep): return some(self,sep,0 + poisson(0.5)) def atleast(self,n): return some(self,None,n + poisson(0.5)) def possibly(self): def sample(): if state.state.include_possibly: return self.sample() if bernoulli(0.5): return self.sample() return None return sample def if_test(self,p): def sample(): iteration_limit = 10 for _ in range(0,iteration_limit): acc = self.sample() if p(acc): return acc return next_token() return sample def if_value(v): def sample(): return mk_tok(v) return sample def if_rawvalue(v): return if_value(v) def type_sample(ty:str): d = {'STRING': ['"'+s+'"' for s in 'hello world so little time'.split()], 'CONTROLSEQ':['\\'+s for s in 'alpha beta gamma delta sum prod deg circ ast lneg times rtimes'.split()], 'DECIMAL':['3.14','2.718','1.0','4.96'], 'INTEGER': [str(i) for i in range(0,10)] , 'SYMBOL':['<','>','!=','+','-','*','^'], 'SYMBOL_QED':[r'\qed'], 'MAPSTO':[r'\mapsto'], 'MID':[r'\mid'], 'TMID':[r'\tmid'], 'ASSIGN':[':='], 'ARROW':[r'\to'], 'BLANK':['_'], 'ALT':['|'], 'PERIOD':['.'], 'COLON':[':'], 'APPLYSUB':[r'\sub'], 'COERCION': [r'\^'], 'LAMBDA':[r'\lambda'], 'PITY':[r'\Pity'], 'QUANTIFIER':[r'\forall',r'\exists'], 'VAR':[ f'{x}{n}' for x in 'b c x y z u v w'.split() for n in range(0,5)], 'WORD':"""estimate equation solution expression inequality random sample mean pair ordered function evaluate order operation property divisible exponent base multiple square common prime form factorization point plane line angle ray parallel intersecting perpendicular regular polygon degree circle diameter chord similar congruent symmetry leg triangle scalene equilateral trapezoid rotation transformation translation polyhedron integer positive opposite value origin coordinate area circumference word number blah part""".split(), 'ATOMIC_IDENTIFIER':'foo_bar bar3 foo22 sin_ cos_ atan2 ceil_ comb_ fabs_ factorial_ floor_ gcd_ sqrt_ log2 log10 pow_ '.split(), 'HIERARCHICAL_IDENTIFIER':['math.pi','math.ceil','math.abs'], 'FIELD_ACCESSOR':['.assoc','.distrib'], 'UNKNOWN':['?'], 'TEX_ERROR':[r'\error'] } return ran(d[ty]) def if_types(tys): def sample(): ty = ran(tys) return mk_tok(type_sample(ty)) return sample def all_sample(prs): def sample(): return [p.sample() for p in prs] return sample def first(prs): def sample(): if not prs: return None i = randint(0,len(prs)) return prs[i].sample() return sample def first_word(ss): s = ran(ss.split()) def sample(): return mk_tok(s) return sample def word_net_string(wn): s = ran([k for k in wn]) if not s: return '' return s + ' ' + word_net_string(wn[s]) def word_net(wn): def sample(): s = word_net_string(wn) return mk_toks(s) return sample if __name__ == "__main__": import doctest doctest.testmod(optionflags=doctest.ELLIPSIS | doctest.NORMALIZE_WHITESPACE)

true

f7189aca9151d09325fd0e73daa10f100e064973

4,598

py

Python

onpolicy/envs/mpe/scenarios/simple_push.py

zoeyuchao/onpolicy-release

c2cb64e59c5b1f21cce022db76c378b396fd480e

[ "MIT" ]

1

2021-07-04T08:08:30.000Z

onpolicy/envs/mpe/scenarios/simple_push.py

zoeyuchao/onpolicy-release

c2cb64e59c5b1f21cce022db76c378b396fd480e

[ "MIT" ]

1

2021-06-11T15:28:11.000Z

onpolicy/envs/mpe/scenarios/simple_push.py

zoeyuchao/onpolicy-release

c2cb64e59c5b1f21cce022db76c378b396fd480e

[ "MIT" ]

1

2021-05-17T02:00:18.000Z

import numpy as np from onpolicy.envs.mpe.core import World, Agent, Landmark from onpolicy.envs.mpe.scenario import BaseScenario import random # # # the non-ensemble version of <ensemble_push> # # class Scenario(BaseScenario): def make_world(self, args): world = World() world.world_length = args.episode_length # set any world properties first world.dim_c = 2 num_agents = args.num_agents#2 num_adversaries = 1 num_landmarks = args.num_landmarks#2 # add agents world.agents = [Agent() for i in range(num_agents)] for i, agent in enumerate(world.agents): agent.name = 'agent %d' % i agent.collide = True agent.silent = True if i < num_adversaries: agent.adversary = True else: agent.adversary = False # agent.u_noise = 1e-1 # agent.c_noise = 1e-1 # add landmarks world.landmarks = [Landmark() for i in range(num_landmarks)] for i, landmark in enumerate(world.landmarks): landmark.name = 'landmark %d' % i landmark.collide = False landmark.movable = False # make initial conditions self.reset_world(world) return world def reset_world(self, world): # random properties for landmarks for i, landmark in enumerate(world.landmarks): landmark.color = np.array([0.1, 0.1, 0.1]) landmark.color[i + 1] += 0.8 landmark.index = i # set goal landmark goal = np.random.choice(world.landmarks) for i, agent in enumerate(world.agents): agent.goal_a = goal agent.color = np.array([0.25, 0.25, 0.25]) if agent.adversary: agent.color = np.array([0.75, 0.25, 0.25]) else: j = goal.index agent.color[j + 1] += 0.5 # set random initial states for agent in world.agents: agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p) agent.state.p_vel = np.zeros(world.dim_p) agent.state.c = np.zeros(world.dim_c) for i, landmark in enumerate(world.landmarks): landmark.state.p_pos = 0.8 * np.random.uniform(-1, +1, world.dim_p) landmark.state.p_vel = np.zeros(world.dim_p) def reward(self, agent, world): # Agents are rewarded based on minimum agent distance to each landmark return self.adversary_reward(agent, world) if agent.adversary else self.agent_reward(agent, world) def agent_reward(self, agent, world): # the distance to the goal return -np.sqrt(np.sum(np.square(agent.state.p_pos - agent.goal_a.state.p_pos))) def adversary_reward(self, agent, world): # keep the nearest good agents away from the goal agent_dist = [np.sqrt(np.sum(np.square(a.state.p_pos - a.goal_a.state.p_pos))) for a in world.agents if not a.adversary] pos_rew = min(agent_dist) #nearest_agent = world.good_agents[np.argmin(agent_dist)] #neg_rew = np.sqrt(np.sum(np.square(nearest_agent.state.p_pos - agent.state.p_pos))) neg_rew = np.sqrt(np.sum(np.square(agent.goal_a.state.p_pos - agent.state.p_pos))) #neg_rew = sum([np.sqrt(np.sum(np.square(a.state.p_pos - agent.state.p_pos))) for a in world.good_agents]) return pos_rew - neg_rew def observation(self, agent, world): # get positions of all entities in this agent's reference frame entity_pos = [] for entity in world.landmarks: # world.entities: entity_pos.append(entity.state.p_pos - agent.state.p_pos) # entity colors entity_color = [] for entity in world.landmarks: # world.entities: entity_color.append(entity.color) # communication of all other agents comm = [] other_pos = [] for other in world.agents: if other is agent: continue comm.append(other.state.c) other_pos.append(other.state.p_pos - agent.state.p_pos) if not agent.adversary: return np.concatenate([agent.state.p_vel] + [agent.goal_a.state.p_pos - agent.state.p_pos] + [agent.color] + entity_pos + entity_color + other_pos) else: #other_pos = list(reversed(other_pos)) if random.uniform(0,1) > 0.5 else other_pos # randomize position of other agents in adversary network return np.concatenate([agent.state.p_vel] + entity_pos + other_pos)

43.377358

159

0.61157

import numpy as np from onpolicy.envs.mpe.core import World, Agent, Landmark from onpolicy.envs.mpe.scenario import BaseScenario import random e_world(self, args): world = World() world.world_length = args.episode_length world.dim_c = 2 num_agents = args.num_agents num_adversaries = 1 num_landmarks = args.num_landmarks world.agents = [Agent() for i in range(num_agents)] for i, agent in enumerate(world.agents): agent.name = 'agent %d' % i agent.collide = True agent.silent = True if i < num_adversaries: agent.adversary = True else: agent.adversary = False world.landmarks = [Landmark() for i in range(num_landmarks)] for i, landmark in enumerate(world.landmarks): landmark.name = 'landmark %d' % i landmark.collide = False landmark.movable = False self.reset_world(world) return world def reset_world(self, world): for i, landmark in enumerate(world.landmarks): landmark.color = np.array([0.1, 0.1, 0.1]) landmark.color[i + 1] += 0.8 landmark.index = i goal = np.random.choice(world.landmarks) for i, agent in enumerate(world.agents): agent.goal_a = goal agent.color = np.array([0.25, 0.25, 0.25]) if agent.adversary: agent.color = np.array([0.75, 0.25, 0.25]) else: j = goal.index agent.color[j + 1] += 0.5 for agent in world.agents: agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p) agent.state.p_vel = np.zeros(world.dim_p) agent.state.c = np.zeros(world.dim_c) for i, landmark in enumerate(world.landmarks): landmark.state.p_pos = 0.8 * np.random.uniform(-1, +1, world.dim_p) landmark.state.p_vel = np.zeros(world.dim_p) def reward(self, agent, world): return self.adversary_reward(agent, world) if agent.adversary else self.agent_reward(agent, world) def agent_reward(self, agent, world): return -np.sqrt(np.sum(np.square(agent.state.p_pos - agent.goal_a.state.p_pos))) def adversary_reward(self, agent, world): agent_dist = [np.sqrt(np.sum(np.square(a.state.p_pos - a.goal_a.state.p_pos))) for a in world.agents if not a.adversary] pos_rew = min(agent_dist) neg_rew = np.sqrt(np.sum(np.square(agent.goal_a.state.p_pos - agent.state.p_pos))) return pos_rew - neg_rew def observation(self, agent, world): entity_pos = [] for entity in world.landmarks: # world.entities: entity_pos.append(entity.state.p_pos - agent.state.p_pos) # entity colors entity_color = [] for entity in world.landmarks: # world.entities: entity_color.append(entity.color) # communication of all other agents comm = [] other_pos = [] for other in world.agents: if other is agent: continue comm.append(other.state.c) other_pos.append(other.state.p_pos - agent.state.p_pos) if not agent.adversary: return np.concatenate([agent.state.p_vel] + [agent.goal_a.state.p_pos - agent.state.p_pos] + [agent.color] + entity_pos + entity_color + other_pos) else: #other_pos = list(reversed(other_pos)) if random.uniform(0,1) > 0.5 else other_pos # randomize position of other agents in adversary network return np.concatenate([agent.state.p_vel] + entity_pos + other_pos)

true

f7189bcea8006e2f10ec06aeeee0afb685dda826

15,186

py

Python

pysnmp/GBOND-TDIM-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

11

2021-02-02T16:27:16.000Z

2021-08-31T06:22:49.000Z

pysnmp/GBOND-TDIM-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

75

2021-02-24T17:30:31.000Z

2021-12-08T00:01:18.000Z

pysnmp/GBOND-TDIM-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

10

2019-04-30T05:51:36.000Z

2022-02-16T03:33:41.000Z

# # PySNMP MIB module GBOND-TDIM-MIB (http://snmplabs.com/pysmi) # ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/GBOND-TDIM-MIB # Produced by pysmi-0.3.4 at Mon Apr 29 19:05:16 2019 # On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4 # Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15) # OctetString, Integer, ObjectIdentifier = mibBuilder.importSymbols("ASN1", "OctetString", "Integer", "ObjectIdentifier") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ValueRangeConstraint, ConstraintsUnion, SingleValueConstraint, ValueSizeConstraint, ConstraintsIntersection = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueRangeConstraint", "ConstraintsUnion", "SingleValueConstraint", "ValueSizeConstraint", "ConstraintsIntersection") gBondMIB, = mibBuilder.importSymbols("GBOND-MIB", "gBondMIB") InterfaceIndex, ifIndex = mibBuilder.importSymbols("IF-MIB", "InterfaceIndex", "ifIndex") ObjectGroup, ModuleCompliance, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ObjectGroup", "ModuleCompliance", "NotificationGroup") Counter32, Gauge32, Unsigned32, NotificationType, Integer32, iso, MibScalar, MibTable, MibTableRow, MibTableColumn, ModuleIdentity, IpAddress, ObjectIdentity, TimeTicks, Bits, MibIdentifier, Counter64 = mibBuilder.importSymbols("SNMPv2-SMI", "Counter32", "Gauge32", "Unsigned32", "NotificationType", "Integer32", "iso", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "ModuleIdentity", "IpAddress", "ObjectIdentity", "TimeTicks", "Bits", "MibIdentifier", "Counter64") TextualConvention, DisplayString, TruthValue = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString", "TruthValue") gBondTdimMIB = ModuleIdentity((1, 3, 6, 1, 2, 1, 211, 3)) gBondTdimMIB.setRevisions(('2007-04-29 00:00',)) if mibBuilder.loadTexts: gBondTdimMIB.setLastUpdated('200704290000Z') if mibBuilder.loadTexts: gBondTdimMIB.setOrganization('IETF ADSL MIB Working Group') gBondTdimObjects = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 1)) gBondTdimConformance = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 2)) gBondTdimPort = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 1, 1)) class GBondTdimServiceIndex(TextualConvention, Unsigned32): status = 'current' displayHint = 'd' subtypeSpec = Unsigned32.subtypeSpec + ValueRangeConstraint(1, 60) gBondTdimPortNotifications = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 0)) gBondTdimServiceUp = NotificationType((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 0, 1)).setObjects(("GBOND-TDIM-MIB", "gBondTdimServiceIfIdx"), ("GBOND-TDIM-MIB", "gBondTdimServiceOperState")) if mibBuilder.loadTexts: gBondTdimServiceUp.setStatus('current') gBondTdimServiceDown = NotificationType((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 0, 2)).setObjects(("GBOND-TDIM-MIB", "gBondTdimServiceIfIdx"), ("GBOND-TDIM-MIB", "gBondTdimServiceOperState")) if mibBuilder.loadTexts: gBondTdimServiceDown.setStatus('current') gBondTdimPortConfTable = MibTable((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1), ) if mibBuilder.loadTexts: gBondTdimPortConfTable.setStatus('current') gBondTdimPortConfEntry = MibTableRow((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1), ).setIndexNames((0, "IF-MIB", "ifIndex")) if mibBuilder.loadTexts: gBondTdimPortConfEntry.setStatus('current') gBondTdimFecAdminState = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 1), TruthValue()).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecAdminState.setStatus('current') gBondTdimFecWordSize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 2), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(20, 255), ))).setUnits('octets').setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecWordSize.setStatus('current') gBondTdimFecRedundancySize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 3), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(2, 2), ValueRangeConstraint(4, 4), ValueRangeConstraint(8, 8), ValueRangeConstraint(16, 16), ValueRangeConstraint(20, 20), ))).setUnits('octets').setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecRedundancySize.setStatus('current') gBondTdimFecInterleaverType = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 4), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2))).clone(namedValues=NamedValues(("none", 0), ("block", 1), ("convolution", 2)))).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecInterleaverType.setStatus('current') gBondTdimFecInterleaverDepth = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 5), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(1, 1), ValueRangeConstraint(2, 2), ValueRangeConstraint(3, 3), ValueRangeConstraint(4, 4), ValueRangeConstraint(6, 6), ValueRangeConstraint(8, 8), ValueRangeConstraint(12, 12), ValueRangeConstraint(16, 16), ValueRangeConstraint(24, 24), ValueRangeConstraint(32, 32), ValueRangeConstraint(48, 48), ValueRangeConstraint(96, 96), ))).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecInterleaverDepth.setStatus('current') gBondTdimServiceUpDownEnable = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 6), TruthValue()).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimServiceUpDownEnable.setStatus('current') gBondTdimPortCapabilityTable = MibTable((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2), ) if mibBuilder.loadTexts: gBondTdimPortCapabilityTable.setStatus('current') gBondTdimPortCapabilityEntry = MibTableRow((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1), ).setIndexNames((0, "IF-MIB", "ifIndex")) if mibBuilder.loadTexts: gBondTdimPortCapabilityEntry.setStatus('current') gBondTdimFecSupported = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 1), TruthValue()).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecSupported.setStatus('current') gBondTdimFecMaxWordSize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 2), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(20, 255), ))).setUnits('octets').setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecMaxWordSize.setStatus('current') gBondTdimFecMaxRedundancySize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 3), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(2, 2), ValueRangeConstraint(4, 4), ValueRangeConstraint(8, 8), ValueRangeConstraint(16, 16), ValueRangeConstraint(20, 20), ))).setUnits('octets').setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecMaxRedundancySize.setStatus('current') gBondTdimFecInterleaverTypeSupported = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 4), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2, 3))).clone(namedValues=NamedValues(("none", 0), ("block", 1), ("convolution", 2), ("blockConvolution", 3)))).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecInterleaverTypeSupported.setStatus('current') gBondTdimFecMaxInterleaverDepth = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 5), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(1, 1), ValueRangeConstraint(2, 2), ValueRangeConstraint(3, 3), ValueRangeConstraint(4, 4), ValueRangeConstraint(6, 6), ValueRangeConstraint(8, 8), ValueRangeConstraint(12, 12), ValueRangeConstraint(16, 16), ValueRangeConstraint(24, 24), ValueRangeConstraint(32, 32), ValueRangeConstraint(48, 48), ValueRangeConstraint(96, 96), ))).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecMaxInterleaverDepth.setStatus('current') gBondTdimPortStatusTable = MibTable((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3), ) if mibBuilder.loadTexts: gBondTdimPortStatusTable.setStatus('current') gBondTdimPortStatusEntry = MibTableRow((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1), ).setIndexNames((0, "IF-MIB", "ifIndex")) if mibBuilder.loadTexts: gBondTdimPortStatusEntry.setStatus('current') gBondTdimCrc4Errors = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1, 1), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimCrc4Errors.setStatus('current') gBondTdimCrc6Errors = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1, 2), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimCrc6Errors.setStatus('current') gBondTdimCrc8Errors = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1, 3), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimCrc8Errors.setStatus('current') gBondTdimFltStatus = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1, 4), Bits().clone(namedValues=NamedValues(("serviceDown", 0), ("wrongConfig", 1)))).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFltStatus.setStatus('current') gBondTdimServiceTable = MibTable((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4), ) if mibBuilder.loadTexts: gBondTdimServiceTable.setStatus('current') gBondTdimServiceEntry = MibTableRow((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1), ).setIndexNames((0, "GBOND-TDIM-MIB", "gBondTdimServiceIdx")) if mibBuilder.loadTexts: gBondTdimServiceEntry.setStatus('current') gBondTdimServiceIdx = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 1), GBondTdimServiceIndex()) if mibBuilder.loadTexts: gBondTdimServiceIdx.setStatus('current') gBondTdimServiceIfIdx = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 2), InterfaceIndex()).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimServiceIfIdx.setStatus('current') gBondTdimServiceType = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 3), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10))).clone(namedValues=NamedValues(("ds1", 0), ("e1", 1), ("nxds0", 2), ("nxe0", 3), ("ds3", 4), ("e3", 5), ("clock", 6), ("ethernet", 7), ("atm", 8), ("gfpNoFCS", 9), ("gfp", 10)))).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimServiceType.setStatus('current') gBondTdimServiceSize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 4), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(20, 255), ))).setUnits('octets').setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimServiceSize.setStatus('current') gBondTdimServiceOperState = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 5), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("up", 1), ("down", 2)))).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimServiceOperState.setStatus('current') gBondTdimGroups = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 2, 1)) gBondTdimCompliances = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 2, 2)) gBondTdimBasicGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 211, 3, 2, 1, 1)).setObjects(("GBOND-TDIM-MIB", "gBondTdimCrc4Errors"), ("GBOND-TDIM-MIB", "gBondTdimCrc6Errors"), ("GBOND-TDIM-MIB", "gBondTdimCrc8Errors"), ("GBOND-TDIM-MIB", "gBondTdimFecSupported"), ("GBOND-TDIM-MIB", "gBondTdimServiceIfIdx"), ("GBOND-TDIM-MIB", "gBondTdimServiceType"), ("GBOND-TDIM-MIB", "gBondTdimServiceSize"), ("GBOND-TDIM-MIB", "gBondTdimServiceOperState"), ("GBOND-TDIM-MIB", "gBondTdimServiceUpDownEnable"), ("GBOND-TDIM-MIB", "gBondTdimFltStatus")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimBasicGroup = gBondTdimBasicGroup.setStatus('current') gBondTdimFecGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 211, 3, 2, 1, 2)).setObjects(("GBOND-TDIM-MIB", "gBondTdimFecSupported"), ("GBOND-TDIM-MIB", "gBondTdimFecAdminState"), ("GBOND-TDIM-MIB", "gBondTdimFecWordSize"), ("GBOND-TDIM-MIB", "gBondTdimFecRedundancySize"), ("GBOND-TDIM-MIB", "gBondTdimFecInterleaverType"), ("GBOND-TDIM-MIB", "gBondTdimFecInterleaverDepth"), ("GBOND-TDIM-MIB", "gBondTdimFecMaxWordSize"), ("GBOND-TDIM-MIB", "gBondTdimFecMaxRedundancySize"), ("GBOND-TDIM-MIB", "gBondTdimFecInterleaverTypeSupported"), ("GBOND-TDIM-MIB", "gBondTdimFecMaxInterleaverDepth")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimFecGroup = gBondTdimFecGroup.setStatus('current') gBondTdimAlarmConfGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 211, 3, 2, 1, 3)).setObjects(("GBOND-TDIM-MIB", "gBondTdimServiceUpDownEnable")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimAlarmConfGroup = gBondTdimAlarmConfGroup.setStatus('current') gBondTdimNotificationGroup = NotificationGroup((1, 3, 6, 1, 2, 1, 211, 3, 2, 1, 4)).setObjects(("GBOND-TDIM-MIB", "gBondTdimServiceUp"), ("GBOND-TDIM-MIB", "gBondTdimServiceDown")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimNotificationGroup = gBondTdimNotificationGroup.setStatus('current') gBondTdimCompliance = ModuleCompliance((1, 3, 6, 1, 2, 1, 211, 3, 2, 2, 1)).setObjects(("GBOND-TDIM-MIB", "gBondTdimBasicGroup"), ("GBOND-TDIM-MIB", "gBondTdimAlarmConfGroup"), ("GBOND-TDIM-MIB", "gBondTdimNotificationGroup"), ("GBOND-TDIM-MIB", "gBondTdimFecGroup")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimCompliance = gBondTdimCompliance.setStatus('current') mibBuilder.exportSymbols("GBOND-TDIM-MIB", gBondTdimFecInterleaverTypeSupported=gBondTdimFecInterleaverTypeSupported, gBondTdimPortConfTable=gBondTdimPortConfTable, gBondTdimFecMaxRedundancySize=gBondTdimFecMaxRedundancySize, gBondTdimServiceUp=gBondTdimServiceUp, gBondTdimPortConfEntry=gBondTdimPortConfEntry, gBondTdimPortCapabilityEntry=gBondTdimPortCapabilityEntry, GBondTdimServiceIndex=GBondTdimServiceIndex, gBondTdimNotificationGroup=gBondTdimNotificationGroup, gBondTdimServiceTable=gBondTdimServiceTable, gBondTdimFecGroup=gBondTdimFecGroup, gBondTdimServiceIdx=gBondTdimServiceIdx, gBondTdimFecMaxInterleaverDepth=gBondTdimFecMaxInterleaverDepth, gBondTdimServiceType=gBondTdimServiceType, gBondTdimFltStatus=gBondTdimFltStatus, gBondTdimServiceUpDownEnable=gBondTdimServiceUpDownEnable, gBondTdimFecSupported=gBondTdimFecSupported, gBondTdimServiceSize=gBondTdimServiceSize, gBondTdimFecMaxWordSize=gBondTdimFecMaxWordSize, gBondTdimPort=gBondTdimPort, gBondTdimFecInterleaverDepth=gBondTdimFecInterleaverDepth, gBondTdimMIB=gBondTdimMIB, gBondTdimConformance=gBondTdimConformance, gBondTdimGroups=gBondTdimGroups, gBondTdimCrc8Errors=gBondTdimCrc8Errors, gBondTdimBasicGroup=gBondTdimBasicGroup, gBondTdimPortCapabilityTable=gBondTdimPortCapabilityTable, gBondTdimServiceEntry=gBondTdimServiceEntry, gBondTdimAlarmConfGroup=gBondTdimAlarmConfGroup, gBondTdimPortStatusEntry=gBondTdimPortStatusEntry, gBondTdimFecInterleaverType=gBondTdimFecInterleaverType, gBondTdimObjects=gBondTdimObjects, gBondTdimPortStatusTable=gBondTdimPortStatusTable, gBondTdimServiceIfIdx=gBondTdimServiceIfIdx, gBondTdimServiceDown=gBondTdimServiceDown, PYSNMP_MODULE_ID=gBondTdimMIB, gBondTdimCompliance=gBondTdimCompliance, gBondTdimCompliances=gBondTdimCompliances, gBondTdimFecRedundancySize=gBondTdimFecRedundancySize, gBondTdimFecWordSize=gBondTdimFecWordSize, gBondTdimCrc4Errors=gBondTdimCrc4Errors, gBondTdimCrc6Errors=gBondTdimCrc6Errors, gBondTdimServiceOperState=gBondTdimServiceOperState, gBondTdimPortNotifications=gBondTdimPortNotifications, gBondTdimFecAdminState=gBondTdimFecAdminState)

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OctetString, Integer, ObjectIdentifier = mibBuilder.importSymbols("ASN1", "OctetString", "Integer", "ObjectIdentifier") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ValueRangeConstraint, ConstraintsUnion, SingleValueConstraint, ValueSizeConstraint, ConstraintsIntersection = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueRangeConstraint", "ConstraintsUnion", "SingleValueConstraint", "ValueSizeConstraint", "ConstraintsIntersection") gBondMIB, = mibBuilder.importSymbols("GBOND-MIB", "gBondMIB") InterfaceIndex, ifIndex = mibBuilder.importSymbols("IF-MIB", "InterfaceIndex", "ifIndex") ObjectGroup, ModuleCompliance, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ObjectGroup", "ModuleCompliance", "NotificationGroup") Counter32, Gauge32, Unsigned32, NotificationType, Integer32, iso, MibScalar, MibTable, MibTableRow, MibTableColumn, ModuleIdentity, IpAddress, ObjectIdentity, TimeTicks, Bits, MibIdentifier, Counter64 = mibBuilder.importSymbols("SNMPv2-SMI", "Counter32", "Gauge32", "Unsigned32", "NotificationType", "Integer32", "iso", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "ModuleIdentity", "IpAddress", "ObjectIdentity", "TimeTicks", "Bits", "MibIdentifier", "Counter64") TextualConvention, DisplayString, TruthValue = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString", "TruthValue") gBondTdimMIB = ModuleIdentity((1, 3, 6, 1, 2, 1, 211, 3)) gBondTdimMIB.setRevisions(('2007-04-29 00:00',)) if mibBuilder.loadTexts: gBondTdimMIB.setLastUpdated('200704290000Z') if mibBuilder.loadTexts: gBondTdimMIB.setOrganization('IETF ADSL MIB Working Group') gBondTdimObjects = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 1)) gBondTdimConformance = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 2)) gBondTdimPort = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 1, 1)) class GBondTdimServiceIndex(TextualConvention, Unsigned32): status = 'current' displayHint = 'd' subtypeSpec = Unsigned32.subtypeSpec + ValueRangeConstraint(1, 60) gBondTdimPortNotifications = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 0)) gBondTdimServiceUp = NotificationType((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 0, 1)).setObjects(("GBOND-TDIM-MIB", "gBondTdimServiceIfIdx"), ("GBOND-TDIM-MIB", "gBondTdimServiceOperState")) if mibBuilder.loadTexts: gBondTdimServiceUp.setStatus('current') gBondTdimServiceDown = NotificationType((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 0, 2)).setObjects(("GBOND-TDIM-MIB", "gBondTdimServiceIfIdx"), ("GBOND-TDIM-MIB", "gBondTdimServiceOperState")) if mibBuilder.loadTexts: gBondTdimServiceDown.setStatus('current') gBondTdimPortConfTable = MibTable((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1), ) if mibBuilder.loadTexts: gBondTdimPortConfTable.setStatus('current') gBondTdimPortConfEntry = MibTableRow((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1), ).setIndexNames((0, "IF-MIB", "ifIndex")) if mibBuilder.loadTexts: gBondTdimPortConfEntry.setStatus('current') gBondTdimFecAdminState = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 1), TruthValue()).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecAdminState.setStatus('current') gBondTdimFecWordSize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 2), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(20, 255), ))).setUnits('octets').setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecWordSize.setStatus('current') gBondTdimFecRedundancySize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 3), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(2, 2), ValueRangeConstraint(4, 4), ValueRangeConstraint(8, 8), ValueRangeConstraint(16, 16), ValueRangeConstraint(20, 20), ))).setUnits('octets').setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecRedundancySize.setStatus('current') gBondTdimFecInterleaverType = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 4), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2))).clone(namedValues=NamedValues(("none", 0), ("block", 1), ("convolution", 2)))).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecInterleaverType.setStatus('current') gBondTdimFecInterleaverDepth = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 5), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(1, 1), ValueRangeConstraint(2, 2), ValueRangeConstraint(3, 3), ValueRangeConstraint(4, 4), ValueRangeConstraint(6, 6), ValueRangeConstraint(8, 8), ValueRangeConstraint(12, 12), ValueRangeConstraint(16, 16), ValueRangeConstraint(24, 24), ValueRangeConstraint(32, 32), ValueRangeConstraint(48, 48), ValueRangeConstraint(96, 96), ))).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimFecInterleaverDepth.setStatus('current') gBondTdimServiceUpDownEnable = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 1, 1, 6), TruthValue()).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimServiceUpDownEnable.setStatus('current') gBondTdimPortCapabilityTable = MibTable((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2), ) if mibBuilder.loadTexts: gBondTdimPortCapabilityTable.setStatus('current') gBondTdimPortCapabilityEntry = MibTableRow((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1), ).setIndexNames((0, "IF-MIB", "ifIndex")) if mibBuilder.loadTexts: gBondTdimPortCapabilityEntry.setStatus('current') gBondTdimFecSupported = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 1), TruthValue()).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecSupported.setStatus('current') gBondTdimFecMaxWordSize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 2), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(20, 255), ))).setUnits('octets').setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecMaxWordSize.setStatus('current') gBondTdimFecMaxRedundancySize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 3), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(2, 2), ValueRangeConstraint(4, 4), ValueRangeConstraint(8, 8), ValueRangeConstraint(16, 16), ValueRangeConstraint(20, 20), ))).setUnits('octets').setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecMaxRedundancySize.setStatus('current') gBondTdimFecInterleaverTypeSupported = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 4), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2, 3))).clone(namedValues=NamedValues(("none", 0), ("block", 1), ("convolution", 2), ("blockConvolution", 3)))).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecInterleaverTypeSupported.setStatus('current') gBondTdimFecMaxInterleaverDepth = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 2, 1, 5), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(1, 1), ValueRangeConstraint(2, 2), ValueRangeConstraint(3, 3), ValueRangeConstraint(4, 4), ValueRangeConstraint(6, 6), ValueRangeConstraint(8, 8), ValueRangeConstraint(12, 12), ValueRangeConstraint(16, 16), ValueRangeConstraint(24, 24), ValueRangeConstraint(32, 32), ValueRangeConstraint(48, 48), ValueRangeConstraint(96, 96), ))).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFecMaxInterleaverDepth.setStatus('current') gBondTdimPortStatusTable = MibTable((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3), ) if mibBuilder.loadTexts: gBondTdimPortStatusTable.setStatus('current') gBondTdimPortStatusEntry = MibTableRow((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1), ).setIndexNames((0, "IF-MIB", "ifIndex")) if mibBuilder.loadTexts: gBondTdimPortStatusEntry.setStatus('current') gBondTdimCrc4Errors = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1, 1), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimCrc4Errors.setStatus('current') gBondTdimCrc6Errors = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1, 2), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimCrc6Errors.setStatus('current') gBondTdimCrc8Errors = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1, 3), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimCrc8Errors.setStatus('current') gBondTdimFltStatus = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 3, 1, 4), Bits().clone(namedValues=NamedValues(("serviceDown", 0), ("wrongConfig", 1)))).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimFltStatus.setStatus('current') gBondTdimServiceTable = MibTable((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4), ) if mibBuilder.loadTexts: gBondTdimServiceTable.setStatus('current') gBondTdimServiceEntry = MibTableRow((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1), ).setIndexNames((0, "GBOND-TDIM-MIB", "gBondTdimServiceIdx")) if mibBuilder.loadTexts: gBondTdimServiceEntry.setStatus('current') gBondTdimServiceIdx = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 1), GBondTdimServiceIndex()) if mibBuilder.loadTexts: gBondTdimServiceIdx.setStatus('current') gBondTdimServiceIfIdx = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 2), InterfaceIndex()).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimServiceIfIdx.setStatus('current') gBondTdimServiceType = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 3), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10))).clone(namedValues=NamedValues(("ds1", 0), ("e1", 1), ("nxds0", 2), ("nxe0", 3), ("ds3", 4), ("e3", 5), ("clock", 6), ("ethernet", 7), ("atm", 8), ("gfpNoFCS", 9), ("gfp", 10)))).setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimServiceType.setStatus('current') gBondTdimServiceSize = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 4), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(20, 255), ))).setUnits('octets').setMaxAccess("readwrite") if mibBuilder.loadTexts: gBondTdimServiceSize.setStatus('current') gBondTdimServiceOperState = MibTableColumn((1, 3, 6, 1, 2, 1, 211, 3, 1, 1, 4, 1, 5), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("up", 1), ("down", 2)))).setMaxAccess("readonly") if mibBuilder.loadTexts: gBondTdimServiceOperState.setStatus('current') gBondTdimGroups = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 2, 1)) gBondTdimCompliances = MibIdentifier((1, 3, 6, 1, 2, 1, 211, 3, 2, 2)) gBondTdimBasicGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 211, 3, 2, 1, 1)).setObjects(("GBOND-TDIM-MIB", "gBondTdimCrc4Errors"), ("GBOND-TDIM-MIB", "gBondTdimCrc6Errors"), ("GBOND-TDIM-MIB", "gBondTdimCrc8Errors"), ("GBOND-TDIM-MIB", "gBondTdimFecSupported"), ("GBOND-TDIM-MIB", "gBondTdimServiceIfIdx"), ("GBOND-TDIM-MIB", "gBondTdimServiceType"), ("GBOND-TDIM-MIB", "gBondTdimServiceSize"), ("GBOND-TDIM-MIB", "gBondTdimServiceOperState"), ("GBOND-TDIM-MIB", "gBondTdimServiceUpDownEnable"), ("GBOND-TDIM-MIB", "gBondTdimFltStatus")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimBasicGroup = gBondTdimBasicGroup.setStatus('current') gBondTdimFecGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 211, 3, 2, 1, 2)).setObjects(("GBOND-TDIM-MIB", "gBondTdimFecSupported"), ("GBOND-TDIM-MIB", "gBondTdimFecAdminState"), ("GBOND-TDIM-MIB", "gBondTdimFecWordSize"), ("GBOND-TDIM-MIB", "gBondTdimFecRedundancySize"), ("GBOND-TDIM-MIB", "gBondTdimFecInterleaverType"), ("GBOND-TDIM-MIB", "gBondTdimFecInterleaverDepth"), ("GBOND-TDIM-MIB", "gBondTdimFecMaxWordSize"), ("GBOND-TDIM-MIB", "gBondTdimFecMaxRedundancySize"), ("GBOND-TDIM-MIB", "gBondTdimFecInterleaverTypeSupported"), ("GBOND-TDIM-MIB", "gBondTdimFecMaxInterleaverDepth")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimFecGroup = gBondTdimFecGroup.setStatus('current') gBondTdimAlarmConfGroup = ObjectGroup((1, 3, 6, 1, 2, 1, 211, 3, 2, 1, 3)).setObjects(("GBOND-TDIM-MIB", "gBondTdimServiceUpDownEnable")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimAlarmConfGroup = gBondTdimAlarmConfGroup.setStatus('current') gBondTdimNotificationGroup = NotificationGroup((1, 3, 6, 1, 2, 1, 211, 3, 2, 1, 4)).setObjects(("GBOND-TDIM-MIB", "gBondTdimServiceUp"), ("GBOND-TDIM-MIB", "gBondTdimServiceDown")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimNotificationGroup = gBondTdimNotificationGroup.setStatus('current') gBondTdimCompliance = ModuleCompliance((1, 3, 6, 1, 2, 1, 211, 3, 2, 2, 1)).setObjects(("GBOND-TDIM-MIB", "gBondTdimBasicGroup"), ("GBOND-TDIM-MIB", "gBondTdimAlarmConfGroup"), ("GBOND-TDIM-MIB", "gBondTdimNotificationGroup"), ("GBOND-TDIM-MIB", "gBondTdimFecGroup")) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): gBondTdimCompliance = gBondTdimCompliance.setStatus('current') mibBuilder.exportSymbols("GBOND-TDIM-MIB", gBondTdimFecInterleaverTypeSupported=gBondTdimFecInterleaverTypeSupported, gBondTdimPortConfTable=gBondTdimPortConfTable, gBondTdimFecMaxRedundancySize=gBondTdimFecMaxRedundancySize, gBondTdimServiceUp=gBondTdimServiceUp, gBondTdimPortConfEntry=gBondTdimPortConfEntry, gBondTdimPortCapabilityEntry=gBondTdimPortCapabilityEntry, GBondTdimServiceIndex=GBondTdimServiceIndex, gBondTdimNotificationGroup=gBondTdimNotificationGroup, gBondTdimServiceTable=gBondTdimServiceTable, gBondTdimFecGroup=gBondTdimFecGroup, gBondTdimServiceIdx=gBondTdimServiceIdx, gBondTdimFecMaxInterleaverDepth=gBondTdimFecMaxInterleaverDepth, gBondTdimServiceType=gBondTdimServiceType, gBondTdimFltStatus=gBondTdimFltStatus, gBondTdimServiceUpDownEnable=gBondTdimServiceUpDownEnable, gBondTdimFecSupported=gBondTdimFecSupported, gBondTdimServiceSize=gBondTdimServiceSize, gBondTdimFecMaxWordSize=gBondTdimFecMaxWordSize, gBondTdimPort=gBondTdimPort, gBondTdimFecInterleaverDepth=gBondTdimFecInterleaverDepth, gBondTdimMIB=gBondTdimMIB, gBondTdimConformance=gBondTdimConformance, gBondTdimGroups=gBondTdimGroups, gBondTdimCrc8Errors=gBondTdimCrc8Errors, gBondTdimBasicGroup=gBondTdimBasicGroup, gBondTdimPortCapabilityTable=gBondTdimPortCapabilityTable, gBondTdimServiceEntry=gBondTdimServiceEntry, gBondTdimAlarmConfGroup=gBondTdimAlarmConfGroup, gBondTdimPortStatusEntry=gBondTdimPortStatusEntry, gBondTdimFecInterleaverType=gBondTdimFecInterleaverType, gBondTdimObjects=gBondTdimObjects, gBondTdimPortStatusTable=gBondTdimPortStatusTable, gBondTdimServiceIfIdx=gBondTdimServiceIfIdx, gBondTdimServiceDown=gBondTdimServiceDown, PYSNMP_MODULE_ID=gBondTdimMIB, gBondTdimCompliance=gBondTdimCompliance, gBondTdimCompliances=gBondTdimCompliances, gBondTdimFecRedundancySize=gBondTdimFecRedundancySize, gBondTdimFecWordSize=gBondTdimFecWordSize, gBondTdimCrc4Errors=gBondTdimCrc4Errors, gBondTdimCrc6Errors=gBondTdimCrc6Errors, gBondTdimServiceOperState=gBondTdimServiceOperState, gBondTdimPortNotifications=gBondTdimPortNotifications, gBondTdimFecAdminState=gBondTdimFecAdminState)

true

f7189c274d57bd65a3dbaf3a87aaaf696023de37

56,687

py

Python

src/_pytest/fixtures.py

blueyed/pytest

2b52e24a9fe013a043c36e3df3d62b4b4f6348f1

[ "MIT" ]

3

2019-11-26T02:30:12.000Z

2020-04-15T17:49:07.000Z

src/_pytest/fixtures.py

blueyed/pytest

2b52e24a9fe013a043c36e3df3d62b4b4f6348f1

[ "MIT" ]

59

2019-10-22T04:34:22.000Z

2021-11-27T18:23:11.000Z

src/_pytest/fixtures.py

blueyed/pytest

2b52e24a9fe013a043c36e3df3d62b4b4f6348f1

[ "MIT" ]

1

2019-11-14T16:47:19.000Z

import functools import inspect import itertools import sys import warnings from collections import defaultdict from collections import deque from typing import Dict from typing import List from typing import Optional from typing import Tuple import attr import py.path import _pytest from _pytest._code.code import FormattedExcinfo from _pytest._code.code import TerminalRepr from _pytest._code.source import getfslineno from _pytest.compat import _format_args from _pytest.compat import _PytestWrapper from _pytest.compat import get_real_func from _pytest.compat import get_real_method from _pytest.compat import getfuncargnames from _pytest.compat import getimfunc from _pytest.compat import getlocation from _pytest.compat import is_generator from _pytest.compat import NOTSET from _pytest.compat import order_preserving_dict from _pytest.compat import safe_getattr from _pytest.compat import TYPE_CHECKING from _pytest.deprecated import FIXTURE_POSITIONAL_ARGUMENTS from _pytest.deprecated import FUNCARGNAMES from _pytest.mark import ParameterSet from _pytest.outcomes import fail from _pytest.outcomes import TEST_OUTCOME if TYPE_CHECKING: from typing import Type from typing_extensions import Literal from _pytest import nodes from _pytest._io import TerminalWriter from _pytest.main import Session from _pytest.runner import _RuntestPhase _Scope = Literal["session", "package", "module", "class", "function"] @attr.s(frozen=True) class PseudoFixtureDef: cached_result = attr.ib() scope = attr.ib() def pytest_sessionstart(session: "Session"): import _pytest.python import _pytest.nodes scopename2class.update( { "package": _pytest.python.Package, "class": _pytest.python.Class, "module": _pytest.python.Module, "function": _pytest.nodes.Item, "session": _pytest.main.Session, } ) session._fixturemanager = FixtureManager(session) scopename2class = {} # type: Dict[str, Type[nodes.Node]] scope2props = dict(session=()) # type: Dict[str, Tuple[str, ...]] scope2props["package"] = ("fspath",) scope2props["module"] = ("fspath", "module") scope2props["class"] = scope2props["module"] + ("cls",) scope2props["instance"] = scope2props["class"] + ("instance",) scope2props["function"] = scope2props["instance"] + ("function", "keywords") def scopeproperty(name=None, doc=None): def decoratescope(func): scopename = name or func.__name__ def provide(self): if func.__name__ in scope2props[self.scope]: return func(self) raise AttributeError( "{} not available in {}-scoped context".format(scopename, self.scope) ) return property(provide, None, None, func.__doc__) return decoratescope def get_scope_package(node, fixturedef): import pytest cls = pytest.Package current = node fixture_package_name = "{}/{}".format(fixturedef.baseid, "__init__.py") while current and ( type(current) is not cls or fixture_package_name != current.nodeid ): current = current.parent if current is None: return node.session return current def get_scope_node(node, scope): cls = scopename2class.get(scope) if cls is None: raise ValueError("unknown scope") return node.getparent(cls) def add_funcarg_pseudo_fixture_def(collector, metafunc, fixturemanager): # this function will transform all collected calls to a functions # if they use direct funcargs (i.e. direct parametrization) # because we want later test execution to be able to rely on # an existing FixtureDef structure for all arguments. # XXX we can probably avoid this algorithm if we modify CallSpec2 # to directly care for creating the fixturedefs within its methods. if not metafunc._calls[0].funcargs: return # this function call does not have direct parametrization # collect funcargs of all callspecs into a list of values arg2params = {} arg2scope = {} for callspec in metafunc._calls: for argname, argvalue in callspec.funcargs.items(): assert argname not in callspec.params callspec.params[argname] = argvalue arg2params_list = arg2params.setdefault(argname, []) callspec.indices[argname] = len(arg2params_list) arg2params_list.append(argvalue) if argname not in arg2scope: scopenum = callspec._arg2scopenum.get(argname, scopenum_function) arg2scope[argname] = scopes[scopenum] callspec.funcargs.clear() # register artificial FixtureDef's so that later at test execution # time we can rely on a proper FixtureDef to exist for fixture setup. arg2fixturedefs = metafunc._arg2fixturedefs for argname, valuelist in arg2params.items(): # if we have a scope that is higher than function we need # to make sure we only ever create an according fixturedef on # a per-scope basis. We thus store and cache the fixturedef on the # node related to the scope. scope = arg2scope[argname] node = None if scope != "function": node = get_scope_node(collector, scope) if node is None: assert scope == "class" and isinstance(collector, _pytest.python.Module) # use module-level collector for class-scope (for now) node = collector if node and argname in node._name2pseudofixturedef: arg2fixturedefs[argname] = [node._name2pseudofixturedef[argname]] else: fixturedef = FixtureDef( fixturemanager, "", argname, get_direct_param_fixture_func, arg2scope[argname], valuelist, False, False, ) arg2fixturedefs[argname] = [fixturedef] if node is not None: node._name2pseudofixturedef[argname] = fixturedef def getfixturemarker(obj): """ return fixturemarker or None if it doesn't exist or raised exceptions.""" try: return getattr(obj, "_pytestfixturefunction", None) except TEST_OUTCOME: # some objects raise errors like request (from flask import request) # we don't expect them to be fixture functions return None def get_parametrized_fixture_keys(item, scopenum): """ return list of keys for all parametrized arguments which match the specified scope. """ assert scopenum < scopenum_function # function try: cs = item.callspec except AttributeError: pass else: # cs.indices.items() is random order of argnames. Need to # sort this so that different calls to # get_parametrized_fixture_keys will be deterministic. for argname, param_index in sorted(cs.indices.items()): if cs._arg2scopenum[argname] != scopenum: continue if scopenum == 0: # session key = (argname, param_index) elif scopenum == 1: # package key = (argname, param_index, item.fspath.dirpath()) elif scopenum == 2: # module key = (argname, param_index, item.fspath) elif scopenum == 3: # class key = (argname, param_index, item.fspath, item.cls) yield key # algorithm for sorting on a per-parametrized resource setup basis # it is called for scopenum==0 (session) first and performs sorting # down to the lower scopes such as to minimize number of "high scope" # setups and teardowns def reorder_items(items): argkeys_cache = {} items_by_argkey = {} for scopenum in range(0, scopenum_function): argkeys_cache[scopenum] = d = {} items_by_argkey[scopenum] = item_d = defaultdict(deque) for item in items: keys = order_preserving_dict.fromkeys( get_parametrized_fixture_keys(item, scopenum) ) if keys: d[item] = keys for key in keys: item_d[key].append(item) items = order_preserving_dict.fromkeys(items) return list(reorder_items_atscope(items, argkeys_cache, items_by_argkey, 0)) def fix_cache_order(item, argkeys_cache, items_by_argkey): for scopenum in range(0, scopenum_function): for key in argkeys_cache[scopenum].get(item, []): items_by_argkey[scopenum][key].appendleft(item) def reorder_items_atscope(items, argkeys_cache, items_by_argkey, scopenum): if scopenum >= scopenum_function or len(items) < 3: return items ignore = set() items_deque = deque(items) items_done = order_preserving_dict() scoped_items_by_argkey = items_by_argkey[scopenum] scoped_argkeys_cache = argkeys_cache[scopenum] while items_deque: no_argkey_group = order_preserving_dict() slicing_argkey = None while items_deque: item = items_deque.popleft() if item in items_done or item in no_argkey_group: continue argkeys = order_preserving_dict.fromkeys( k for k in scoped_argkeys_cache.get(item, []) if k not in ignore ) if not argkeys: no_argkey_group[item] = None else: slicing_argkey, _ = argkeys.popitem() # we don't have to remove relevant items from later in the deque because they'll just be ignored matching_items = [ i for i in scoped_items_by_argkey[slicing_argkey] if i in items ] for i in reversed(matching_items): fix_cache_order(i, argkeys_cache, items_by_argkey) items_deque.appendleft(i) break if no_argkey_group: no_argkey_group = reorder_items_atscope( no_argkey_group, argkeys_cache, items_by_argkey, scopenum + 1 ) for item in no_argkey_group: items_done[item] = None ignore.add(slicing_argkey) return items_done def fillfixtures(function): """ fill missing funcargs for a test function. """ try: request = function._request except AttributeError: # XXX this special code path is only expected to execute # with the oejskit plugin. It uses classes with funcargs # and we thus have to work a bit to allow this. fm = function.session._fixturemanager fi = fm.getfixtureinfo(function.parent, function.obj, None) function._fixtureinfo = fi request = function._request = FixtureRequest(function) request._fillfixtures() # prune out funcargs for jstests newfuncargs = {} for name in fi.argnames: newfuncargs[name] = function.funcargs[name] function.funcargs = newfuncargs else: request._fillfixtures() def get_direct_param_fixture_func(request): return request.param @attr.s(slots=True) class FuncFixtureInfo: # original function argument names argnames = attr.ib(type=tuple) # argnames that function immediately requires. These include argnames + # fixture names specified via usefixtures and via autouse=True in fixture # definitions. initialnames = attr.ib(type=tuple) names_closure = attr.ib() # type: List[str] name2fixturedefs = attr.ib() # type: Dict[str, List[FixtureDef]] def prune_dependency_tree(self): """Recompute names_closure from initialnames and name2fixturedefs Can only reduce names_closure, which means that the new closure will always be a subset of the old one. The order is preserved. This method is needed because direct parametrization may shadow some of the fixtures that were included in the originally built dependency tree. In this way the dependency tree can get pruned, and the closure of argnames may get reduced. """ closure = set() working_set = set(self.initialnames) while working_set: argname = working_set.pop() # argname may be smth not included in the original names_closure, # in which case we ignore it. This currently happens with pseudo # FixtureDefs which wrap 'get_direct_param_fixture_func(request)'. # So they introduce the new dependency 'request' which might have # been missing in the original tree (closure). if argname not in closure and argname in self.names_closure: closure.add(argname) if argname in self.name2fixturedefs: working_set.update(self.name2fixturedefs[argname][-1].argnames) self.names_closure[:] = sorted(closure, key=self.names_closure.index) class FixtureRequest: """ A request for a fixture from a test or fixture function. A request object gives access to the requesting test context and has an optional ``param`` attribute in case the fixture is parametrized indirectly. """ def __init__(self, pyfuncitem): self._pyfuncitem = pyfuncitem #: fixture for which this request is being performed self.fixturename = None #: Scope string, one of "function", "class", "module", "session" self.scope = "function" self._fixture_defs = {} # type: Dict[str, FixtureDef] fixtureinfo = pyfuncitem._fixtureinfo self._arg2fixturedefs = fixtureinfo.name2fixturedefs.copy() self._arg2index = {} self._fixturemanager = pyfuncitem.session._fixturemanager self._phase = None # type: Optional[_RuntestPhase] @property def fixturenames(self): """names of all active fixtures in this request""" result = list(self._pyfuncitem._fixtureinfo.names_closure) result.extend(set(self._fixture_defs).difference(result)) return result @property def funcargnames(self): """ alias attribute for ``fixturenames`` for pre-2.3 compatibility""" warnings.warn(FUNCARGNAMES, stacklevel=2) return self.fixturenames @property def node(self): """ underlying collection node (depends on current request scope)""" return self._getscopeitem(self.scope) def _getnextfixturedef(self, argname): fixturedefs = self._arg2fixturedefs.get(argname, None) if fixturedefs is None: # we arrive here because of a dynamic call to # getfixturevalue(argname) usage which was naturally # not known at parsing/collection time parentid = self._pyfuncitem.parent.nodeid fixturedefs = self._fixturemanager.getfixturedefs(argname, parentid) self._arg2fixturedefs[argname] = fixturedefs # fixturedefs list is immutable so we maintain a decreasing index index = self._arg2index.get(argname, 0) - 1 if fixturedefs is None or (-index > len(fixturedefs)): raise FixtureLookupError(argname, self) self._arg2index[argname] = index return fixturedefs[index] @property def config(self): """ the pytest config object associated with this request. """ return self._pyfuncitem.config @scopeproperty() def function(self): """ test function object if the request has a per-function scope. """ return self._pyfuncitem.obj @scopeproperty("class") def cls(self): """ class (can be None) where the test function was collected. """ clscol = self._pyfuncitem.getparent(_pytest.python.Class) if clscol: return clscol.obj @property def instance(self): """ instance (can be None) on which test function was collected. """ # unittest support hack, see _pytest.unittest.TestCaseFunction try: return self._pyfuncitem._testcase except AttributeError: function = getattr(self, "function", None) return getattr(function, "__self__", None) @scopeproperty() def module(self): """ python module object where the test function was collected. """ return self._pyfuncitem.getparent(_pytest.python.Module).obj @scopeproperty() def fspath(self) -> py.path.local: """ the file system path of the test module which collected this test. """ return self._pyfuncitem.fspath # type: ignore[no-any-return] @property def keywords(self): """ keywords/markers dictionary for the underlying node. """ return self.node.keywords @property def session(self): """ pytest session object. """ return self._pyfuncitem.session def addfinalizer(self, finalizer): """ add finalizer/teardown function to be called after the last test within the requesting test context finished execution. """ # XXX usually this method is shadowed by fixturedef specific ones self._addfinalizer(finalizer, scope=self.scope) def _addfinalizer(self, finalizer, scope): colitem = self._getscopeitem(scope) self._pyfuncitem.session._setupstate.addfinalizer( finalizer=finalizer, colitem=colitem ) def applymarker(self, marker): """ Apply a marker to a single test function invocation. This method is useful if you don't want to have a keyword/marker on all function invocations. :arg marker: a :py:class:`_pytest.mark.MarkDecorator` object created by a call to ``pytest.mark.NAME(...)``. """ self.node.add_marker(marker) def raiseerror(self, msg): """ raise a FixtureLookupError with the given message. """ raise self._fixturemanager.FixtureLookupError(None, self, msg) def _fillfixtures(self): item = self._pyfuncitem fixturenames = getattr(item, "fixturenames", self.fixturenames) for argname in fixturenames: if argname not in item.funcargs: item.funcargs[argname] = self.getfixturevalue(argname) def getfixturevalue(self, argname): """ Dynamically run a named fixture function. Declaring fixtures via function argument is recommended where possible. But if you can only decide whether to use another fixture at test setup time, you may use this function to retrieve it inside a fixture or test function body. """ return self._get_active_fixturedef(argname).cached_result[0] def _get_active_fixturedef(self, argname): try: return self._fixture_defs[argname] except KeyError: try: fixturedef = self._getnextfixturedef(argname) except FixtureLookupError: if argname == "request": cached_result = (self, [0], None) scope = "function" return PseudoFixtureDef(cached_result, scope) raise # remove indent to prevent the python3 exception # from leaking into the call self._compute_fixture_value(fixturedef) self._fixture_defs[argname] = fixturedef return fixturedef def _get_fixturestack(self): current = self values = [] while 1: fixturedef = getattr(current, "_fixturedef", None) if fixturedef is None: values.reverse() return values values.append(fixturedef) current = current._parent_request def _compute_fixture_value(self, fixturedef: "FixtureDef") -> None: """ Creates a SubRequest based on "self" and calls the execute method of the given fixturedef object. This will force the FixtureDef object to throw away any previous results and compute a new fixture value, which will be stored into the FixtureDef object itself. """ # prepare a subrequest object before calling fixture function # (latter managed by fixturedef) argname = fixturedef.argname funcitem = self._pyfuncitem scope = fixturedef.scope try: param = funcitem.callspec.getparam(argname) except (AttributeError, ValueError): param = NOTSET param_index = 0 has_params = fixturedef.params is not None fixtures_not_supported = getattr(funcitem, "nofuncargs", False) if has_params and fixtures_not_supported: msg = ( "{name} does not support fixtures, maybe unittest.TestCase subclass?\n" "Node id: {nodeid}\n" "Function type: {typename}" ).format( name=funcitem.name, nodeid=funcitem.nodeid, typename=type(funcitem).__name__, ) fail(msg, pytrace=False) if has_params: frame = inspect.stack()[3] frameinfo = inspect.getframeinfo(frame[0]) source_path = py.path.local(frameinfo.filename) source_lineno = frameinfo.lineno rel_source_path = source_path.relto(funcitem.config.rootdir) if rel_source_path: source_path_str = rel_source_path else: source_path_str = str(source_path) msg = ( "The requested fixture has no parameter defined for test:\n" " {}\n\n" "Requested fixture '{}' defined in:\n{}" "\n\nRequested here:\n{}:{}".format( funcitem.nodeid, fixturedef.argname, getlocation(fixturedef.func, funcitem.config.rootdir), source_path_str, source_lineno, ) ) fail(msg, pytrace=False) else: param_index = funcitem.callspec.indices[argname] # if a parametrize invocation set a scope it will override # the static scope defined with the fixture function paramscopenum = funcitem.callspec._arg2scopenum.get(argname) if paramscopenum is not None: scope = scopes[paramscopenum] subrequest = SubRequest(self, scope, param, param_index, fixturedef) # check if a higher-level scoped fixture accesses a lower level one subrequest._check_scope(argname, self.scope, scope) try: # call the fixture function fixturedef.execute(request=subrequest) finally: self._schedule_finalizers(fixturedef, subrequest) def _schedule_finalizers(self, fixturedef, subrequest): # if fixture function failed it might have registered finalizers self.session._setupstate.addfinalizer( functools.partial(fixturedef.finish, request=subrequest), subrequest.node ) def _check_scope(self, argname, invoking_scope, requested_scope): if argname == "request": return if scopemismatch(invoking_scope, requested_scope): # try to report something helpful lines = self._factorytraceback() fail( "ScopeMismatch: You tried to access the %r scoped " "fixture %r with a %r scoped request object, " "involved factories\n%s" % ((requested_scope, argname, invoking_scope, "\n".join(lines))), pytrace=False, ) def _factorytraceback(self): lines = [] for fixturedef in self._get_fixturestack(): factory = fixturedef.func fs, lineno = getfslineno(factory) p = self._pyfuncitem.session.fspath.bestrelpath(fs) args = _format_args(factory) lines.append("%s:%d: def %s%s" % (p, lineno + 1, factory.__name__, args)) return lines def _getscopeitem(self, scope): if scope == "function": # this might also be a non-function Item despite its attribute name return self._pyfuncitem if scope == "package": node = get_scope_package(self._pyfuncitem, self._fixturedef) else: node = get_scope_node(self._pyfuncitem, scope) if node is None and scope == "class": # fallback to function item itself node = self._pyfuncitem assert node, 'Could not obtain a node for scope "{}" for function {!r}'.format( scope, self._pyfuncitem ) return node def __repr__(self): return "<FixtureRequest for {!r} _phase={}>".format(self.node, self._phase) class SubRequest(FixtureRequest): """ a sub request for handling getting a fixture from a test function/fixture. """ def __init__( self, request: "FixtureRequest", scope: "_Scope", param, param_index: int, fixturedef: "FixtureDef", ) -> None: self._parent_request = request self.fixturename = fixturedef.argname if param is not NOTSET: self.param = param self.param_index = param_index self.scope = scope self._fixturedef = fixturedef self._pyfuncitem = request._pyfuncitem self._fixture_defs = request._fixture_defs self._arg2fixturedefs = request._arg2fixturedefs self._arg2index = request._arg2index self._fixturemanager = request._fixturemanager def __repr__(self): return "<SubRequest {!r} for {!r} _phase={}>".format( self.fixturename, self._pyfuncitem, self._phase ) @property def _phase(self) -> "Optional[_RuntestPhase]": # type: ignore[override] return self._parent_request._phase def addfinalizer(self, finalizer): self._fixturedef.addfinalizer(finalizer) def _schedule_finalizers(self, fixturedef, subrequest): # if the executing fixturedef was not explicitly requested in the argument list (via # getfixturevalue inside the fixture call) then ensure this fixture def will be finished # first if fixturedef.argname not in self.fixturenames: fixturedef.addfinalizer( functools.partial(self._fixturedef.finish, request=self) ) super()._schedule_finalizers(fixturedef, subrequest) scopes = "session package module class function".split() scopenum_function = scopes.index("function") def scopemismatch(currentscope, newscope): return scopes.index(newscope) > scopes.index(currentscope) def scope2index(scope, descr, where=None): """Look up the index of ``scope`` and raise a descriptive value error if not defined. """ try: return scopes.index(scope) except ValueError: fail( "{} {}got an unexpected scope value '{}'".format( descr, "from {} ".format(where) if where else "", scope ), pytrace=False, ) class FixtureLookupError(LookupError): """ could not return a requested Fixture (missing or invalid). """ def __init__(self, argname, request, msg=None): self.argname = argname self.request = request self.fixturestack = request._get_fixturestack() self.msg = msg def formatrepr(self) -> "FixtureLookupErrorRepr": tblines = [] # type: List[str] addline = tblines.append stack = [self.request._pyfuncitem.obj] stack.extend(map(lambda x: x.func, self.fixturestack)) msg = self.msg if msg is not None: # the last fixture raise an error, let's present # it at the requesting side stack = stack[:-1] for function in stack: fspath, lineno = getfslineno(function) try: lines, _ = inspect.getsourcelines(get_real_func(function)) except (OSError, IndexError, TypeError): error_msg = "file %s, line %s: source code not available" addline(error_msg % (fspath, lineno + 1)) else: addline("file {}, line {}".format(fspath, lineno + 1)) for i, line in enumerate(lines): line = line.rstrip() addline(" " + line) if line.lstrip().startswith("def"): break if msg is None: fm = self.request._fixturemanager available = set() parentid = self.request._pyfuncitem.parent.nodeid for name, fixturedefs in fm._arg2fixturedefs.items(): faclist = list(fm._matchfactories(fixturedefs, parentid)) if faclist: available.add(name) if self.argname in available: msg = " recursive dependency involving fixture '{}' detected".format( self.argname ) else: msg = "fixture '{}' not found".format(self.argname) msg += "\n available fixtures: {}".format(", ".join(sorted(available))) msg += "\n use 'pytest --fixtures [testpath]' for help on them." return FixtureLookupErrorRepr(fspath, lineno, tblines, msg, self.argname) class FixtureLookupErrorRepr(TerminalRepr): def __init__(self, filename, firstlineno, tblines, errorstring, argname): self.tblines = tblines self.errorstring = errorstring self.filename = filename self.firstlineno = firstlineno self.argname = argname def toterminal(self, tw: "TerminalWriter") -> None: # tw.line("FixtureLookupError: %s" %(self.argname), red=True) for tbline in self.tblines: tw.line(tbline.rstrip()) lines = self.errorstring.split("\n") if lines: tw.line( "{} {}".format(FormattedExcinfo.fail_marker, lines[0].strip()), red=True, ) for line in lines[1:]: tw.line( "{} {}".format(FormattedExcinfo.flow_marker, line.strip()), red=True, ) tw.line() tw.line("%s:%d" % (self.filename, self.firstlineno + 1)) def fail_fixturefunc(fixturefunc, msg): fs, lineno = getfslineno(fixturefunc) location = "{}:{}".format(fs, lineno + 1) source = _pytest._code.Source(fixturefunc) fail(msg + ":\n\n" + str(source.indent()) + "\n" + location, pytrace=False) def call_fixture_func(fixturefunc, request, kwargs): yieldctx = is_generator(fixturefunc) if yieldctx: it = fixturefunc(**kwargs) res = next(it) finalizer = functools.partial(_teardown_yield_fixture, fixturefunc, it) request.addfinalizer(finalizer) else: res = fixturefunc(**kwargs) return res def _teardown_yield_fixture(fixturefunc, it): """Executes the teardown of a fixture function by advancing the iterator after the yield and ensure the iteration ends (if not it means there is more than one yield in the function)""" try: next(it) except StopIteration: pass else: fail_fixturefunc( fixturefunc, "yield_fixture function has more than one 'yield'" ) def _eval_scope_callable(scope_callable, fixture_name, config): try: result = scope_callable(fixture_name=fixture_name, config=config) except Exception: raise TypeError( "Error evaluating {} while defining fixture '{}'.\n" "Expected a function with the signature (*, fixture_name, config)".format( scope_callable, fixture_name ) ) if not isinstance(result, str): fail( "Expected {} to return a 'str' while defining fixture '{}', but it returned:\n" "{!r}".format(scope_callable, fixture_name, result), pytrace=False, ) return result class FixtureDef: """ A container for a factory definition. """ def __init__( self, fixturemanager, baseid, argname, func, scope, params, unittest=False, ids=None, ): self._fixturemanager = fixturemanager self.baseid = baseid or "" self.has_location = baseid is not None self.func = func self.argname = argname if callable(scope): scope = _eval_scope_callable(scope, argname, fixturemanager.config) self.scope = scope self.scopenum = scope2index( scope or "function", descr="Fixture '{}'".format(func.__name__), where=baseid, ) self.params = params self.argnames = getfuncargnames(func, name=argname, is_method=unittest) self.unittest = unittest self.ids = ids self.cached_result = None self._finalizers = [] def addfinalizer(self, finalizer): self._finalizers.append(finalizer) def finish(self, request): exc = None try: while self._finalizers: try: func = self._finalizers.pop() func() except BaseException as e: # XXX Only first exception will be seen by user, # ideally all should be reported. if exc is None: exc = e if exc: raise exc finally: hook = self._fixturemanager.session.gethookproxy(request.node.fspath) hook.pytest_fixture_post_finalizer(fixturedef=self, request=request) # even if finalization fails, we invalidate # the cached fixture value and remove # all finalizers because they may be bound methods which will # keep instances alive self.cached_result = None self._finalizers = [] def execute(self, request): # get required arguments and register our own finish() # with their finalization for argname in self.argnames: fixturedef = request._get_active_fixturedef(argname) if argname != "request": fixturedef.addfinalizer(functools.partial(self.finish, request=request)) my_cache_key = self.cache_key(request) if self.cached_result is not None: result, cache_key, err = self.cached_result # note: comparison with `==` can fail (or be expensive) for e.g. # numpy arrays (#6497) if my_cache_key is cache_key: if err is not None: _, val, tb = err raise val.with_traceback(tb) else: return result # we have a previous but differently parametrized fixture instance # so we need to tear it down before creating a new one self.finish(request) assert self.cached_result is None hook = self._fixturemanager.session.gethookproxy(request.node.fspath) return hook.pytest_fixture_setup(fixturedef=self, request=request) def cache_key(self, request): return request.param_index if not hasattr(request, "param") else request.param def __repr__(self): return "<FixtureDef argname={!r} scope={!r} baseid={!r}>".format( self.argname, self.scope, self.baseid ) def resolve_fixture_function(fixturedef, request): """Gets the actual callable that can be called to obtain the fixture value, dealing with unittest-specific instances and bound methods. """ fixturefunc = fixturedef.func if fixturedef.unittest: if request.instance is not None: # bind the unbound method to the TestCase instance fixturefunc = fixturedef.func.__get__(request.instance) else: # the fixture function needs to be bound to the actual # request.instance so that code working with "fixturedef" behaves # as expected. if request.instance is not None: # handle the case where fixture is defined not in a test class, but some other class # (for example a plugin class with a fixture), see #2270 if hasattr(fixturefunc, "__self__") and not isinstance( request.instance, fixturefunc.__self__.__class__ ): return fixturefunc fixturefunc = getimfunc(fixturedef.func) if fixturefunc != fixturedef.func: fixturefunc = fixturefunc.__get__(request.instance) return fixturefunc def pytest_fixture_setup(fixturedef, request): """ Execution of fixture setup. """ kwargs = {} for argname in fixturedef.argnames: fixdef = request._get_active_fixturedef(argname) assert fixdef.cached_result is not None result, arg_cache_key, exc = fixdef.cached_result request._check_scope(argname, request.scope, fixdef.scope) kwargs[argname] = result fixturefunc = resolve_fixture_function(fixturedef, request) my_cache_key = fixturedef.cache_key(request) try: result = call_fixture_func(fixturefunc, request, kwargs) except TEST_OUTCOME: fixturedef.cached_result = (None, my_cache_key, sys.exc_info()) raise fixturedef.cached_result = (result, my_cache_key, None) return result def _ensure_immutable_ids(ids): if ids is None: return if callable(ids): return ids return tuple(ids) def wrap_function_to_error_out_if_called_directly(function, fixture_marker): """Wrap the given fixture function so we can raise an error about it being called directly, instead of used as an argument in a test function. """ message = ( 'Fixture "{name}" called directly. Fixtures are not meant to be called directly,\n' "but are created automatically when test functions request them as parameters.\n" "See https://docs.pytest.org/en/latest/fixture.html for more information about fixtures, and\n" "https://docs.pytest.org/en/latest/deprecations.html#calling-fixtures-directly about how to update your code." ).format(name=fixture_marker.name or function.__name__) @functools.wraps(function) def result(*args, **kwargs): fail(message, pytrace=False) # keep reference to the original function in our own custom attribute so we don't unwrap # further than this point and lose useful wrappings like @mock.patch (#3774) result.__pytest_wrapped__ = _PytestWrapper(function) return result @attr.s(frozen=True) class FixtureFunctionMarker: scope = attr.ib() params = attr.ib( type=Optional[Tuple[object, ...]], converter=attr.converters.optional(tuple), ) autouse = attr.ib(default=False) # Ignore type because of https://github.com/python/mypy/issues/6172. ids = attr.ib(default=None, converter=_ensure_immutable_ids) # type: ignore name = attr.ib(default=None) def __call__(self, function): if inspect.isclass(function): raise ValueError("class fixtures not supported (maybe in the future)") if getattr(function, "_pytestfixturefunction", False): raise ValueError( "fixture is being applied more than once to the same function" ) function = wrap_function_to_error_out_if_called_directly(function, self) name = self.name or function.__name__ if name == "request": location = getlocation(function) fail( "'request' is a reserved word for fixtures, use another name:\n {}".format( location ), pytrace=False, ) function._pytestfixturefunction = self return function FIXTURE_ARGS_ORDER = ("scope", "params", "autouse", "ids", "name") def _parse_fixture_args(callable_or_scope, *args, **kwargs): arguments = { "scope": "function", "params": None, "autouse": False, "ids": None, "name": None, } kwargs = { key: value for key, value in kwargs.items() if arguments.get(key) != value } fixture_function = None if isinstance(callable_or_scope, str): args = list(args) args.insert(0, callable_or_scope) else: fixture_function = callable_or_scope positionals = set() for positional, argument_name in zip(args, FIXTURE_ARGS_ORDER): arguments[argument_name] = positional positionals.add(argument_name) duplicated_kwargs = {kwarg for kwarg in kwargs.keys() if kwarg in positionals} if duplicated_kwargs: raise TypeError( "The fixture arguments are defined as positional and keyword: {}. " "Use only keyword arguments.".format(", ".join(duplicated_kwargs)) ) if positionals: warnings.warn(FIXTURE_POSITIONAL_ARGUMENTS, stacklevel=2) arguments.update(kwargs) return fixture_function, arguments def fixture( callable_or_scope=None, *args, scope="function", params=None, autouse=False, ids=None, name=None ): """Decorator to mark a fixture factory function. This decorator can be used, with or without parameters, to define a fixture function. The name of the fixture function can later be referenced to cause its invocation ahead of running tests: test modules or classes can use the ``pytest.mark.usefixtures(fixturename)`` marker. Test functions can directly use fixture names as input arguments in which case the fixture instance returned from the fixture function will be injected. Fixtures can provide their values to test functions using ``return`` or ``yield`` statements. When using ``yield`` the code block after the ``yield`` statement is executed as teardown code regardless of the test outcome, and must yield exactly once. :arg scope: the scope for which this fixture is shared, one of ``"function"`` (default), ``"class"``, ``"module"``, ``"package"`` or ``"session"`` (``"package"`` is considered **experimental** at this time). This parameter may also be a callable which receives ``(fixture_name, config)`` as parameters, and must return a ``str`` with one of the values mentioned above. See :ref:`dynamic scope` in the docs for more information. :arg params: an optional list of parameters which will cause multiple invocations of the fixture function and all of the tests using it. The current parameter is available in ``request.param``. :arg autouse: if True, the fixture func is activated for all tests that can see it. If False (the default) then an explicit reference is needed to activate the fixture. :arg ids: list of string ids each corresponding to the params so that they are part of the test id. If no ids are provided they will be generated automatically from the params. :arg name: the name of the fixture. This defaults to the name of the decorated function. If a fixture is used in the same module in which it is defined, the function name of the fixture will be shadowed by the function arg that requests the fixture; one way to resolve this is to name the decorated function ``fixture_<fixturename>`` and then use ``@pytest.fixture(name='<fixturename>')``. """ if params is not None: params = list(params) fixture_function, arguments = _parse_fixture_args( callable_or_scope, *args, scope=scope, params=params, autouse=autouse, ids=ids, name=name, ) scope = arguments.get("scope") params = arguments.get("params") autouse = arguments.get("autouse") ids = arguments.get("ids") name = arguments.get("name") if fixture_function and params is None and autouse is False: # direct decoration return FixtureFunctionMarker(scope, params, autouse, name=name)( fixture_function ) return FixtureFunctionMarker(scope, params, autouse, ids=ids, name=name) def yield_fixture( callable_or_scope=None, *args, scope="function", params=None, autouse=False, ids=None, name=None ): """ (return a) decorator to mark a yield-fixture factory function. .. deprecated:: 3.0 Use :py:func:`pytest.fixture` directly instead. """ return fixture( callable_or_scope, *args, scope=scope, params=params, autouse=autouse, ids=ids, name=name, ) defaultfuncargprefixmarker = fixture() @fixture(scope="session") def pytestconfig(request): """Session-scoped fixture that returns the :class:`_pytest.config.Config` object. Example:: def test_foo(pytestconfig): if pytestconfig.getoption("verbose") > 0: ... """ return request.config def pytest_addoption(parser): parser.addini( "usefixtures", type="args", default=[], help="list of default fixtures to be used with this project", ) class FixtureManager: """ pytest fixtures definitions and information is stored and managed from this class. During collection fm.parsefactories() is called multiple times to parse fixture function definitions into FixtureDef objects and internal data structures. During collection of test functions, metafunc-mechanics instantiate a FuncFixtureInfo object which is cached per node/func-name. This FuncFixtureInfo object is later retrieved by Function nodes which themselves offer a fixturenames attribute. The FuncFixtureInfo object holds information about fixtures and FixtureDefs relevant for a particular function. An initial list of fixtures is assembled like this: - ini-defined usefixtures - autouse-marked fixtures along the collection chain up from the function - usefixtures markers at module/class/function level - test function funcargs Subsequently the funcfixtureinfo.fixturenames attribute is computed as the closure of the fixtures needed to setup the initial fixtures, i. e. fixtures needed by fixture functions themselves are appended to the fixturenames list. Upon the test-setup phases all fixturenames are instantiated, retrieved by a lookup of their FuncFixtureInfo. """ FixtureLookupError = FixtureLookupError FixtureLookupErrorRepr = FixtureLookupErrorRepr def __init__(self, session): self.session = session self.config = session.config self._arg2fixturedefs = {} self._holderobjseen = set() self._nodeid_and_autousenames = [("", self.config.getini("usefixtures"))] session.config.pluginmanager.register(self, "funcmanage") def _get_direct_parametrize_args(self, node): """This function returns all the direct parametrization arguments of a node, so we don't mistake them for fixtures Check https://github.com/pytest-dev/pytest/issues/5036 This things are done later as well when dealing with parametrization so this could be improved """ parametrize_argnames = [] for marker in node.iter_markers(name="parametrize"): if not marker.kwargs.get("indirect", False): try: p_argnames, _ = ParameterSet._parse_parametrize_args( *marker.args, **marker.kwargs ) except TypeError: pass else: parametrize_argnames.extend(p_argnames) return parametrize_argnames def getfixtureinfo(self, node, func, cls, funcargs=True): if funcargs and not getattr(node, "nofuncargs", False): argnames = getfuncargnames(func, name=node.name, cls=cls) else: argnames = () usefixtures = itertools.chain.from_iterable( mark.args for mark in node.iter_markers(name="usefixtures") ) initialnames = tuple(usefixtures) + argnames fm = node.session._fixturemanager initialnames, names_closure, arg2fixturedefs = fm.getfixtureclosure( initialnames, node, ignore_args=self._get_direct_parametrize_args(node) ) return FuncFixtureInfo(argnames, initialnames, names_closure, arg2fixturedefs) def pytest_plugin_registered(self, plugin): nodeid = None try: p = py.path.local(plugin.__file__).realpath() except AttributeError: pass else: from _pytest import nodes # construct the base nodeid which is later used to check # what fixtures are visible for particular tests (as denoted # by their test id) if p.basename.startswith("conftest.py"): nodeid = p.dirpath().relto(self.config.rootdir) if p.sep != nodes.SEP: nodeid = nodeid.replace(p.sep, nodes.SEP) self.parsefactories(plugin, nodeid) def _getautousenames(self, nodeid): """ return a tuple of fixture names to be used. """ autousenames = [] for baseid, basenames in self._nodeid_and_autousenames: if nodeid.startswith(baseid): if baseid: i = len(baseid) nextchar = nodeid[i : i + 1] if nextchar and nextchar not in ":/": continue autousenames.extend(basenames) return autousenames def getfixtureclosure(self, fixturenames, parentnode, ignore_args=()): # collect the closure of all fixtures , starting with the given # fixturenames as the initial set. As we have to visit all # factory definitions anyway, we also return an arg2fixturedefs # mapping so that the caller can reuse it and does not have # to re-discover fixturedefs again for each fixturename # (discovering matching fixtures for a given name/node is expensive) parentid = parentnode.nodeid fixturenames_closure = self._getautousenames(parentid) def merge(otherlist): for arg in otherlist: if arg not in fixturenames_closure: fixturenames_closure.append(arg) merge(fixturenames) # at this point, fixturenames_closure contains what we call "initialnames", # which is a set of fixturenames the function immediately requests. We # need to return it as well, so save this. initialnames = tuple(fixturenames_closure) arg2fixturedefs = {} lastlen = -1 while lastlen != len(fixturenames_closure): lastlen = len(fixturenames_closure) for argname in fixturenames_closure: if argname in ignore_args: continue if argname in arg2fixturedefs: continue fixturedefs = self.getfixturedefs(argname, parentid) if fixturedefs: arg2fixturedefs[argname] = fixturedefs merge(fixturedefs[-1].argnames) def sort_by_scope(arg_name): try: fixturedefs = arg2fixturedefs[arg_name] except KeyError: return scopes.index("function") else: return fixturedefs[-1].scopenum fixturenames_closure.sort(key=sort_by_scope) return initialnames, fixturenames_closure, arg2fixturedefs def pytest_generate_tests(self, metafunc): for argname in metafunc.fixturenames: faclist = metafunc._arg2fixturedefs.get(argname) if faclist: fixturedef = faclist[-1] if fixturedef.params is not None: markers = list(metafunc.definition.iter_markers("parametrize")) for parametrize_mark in markers: if "argnames" in parametrize_mark.kwargs: argnames = parametrize_mark.kwargs["argnames"] else: argnames = parametrize_mark.args[0] if not isinstance(argnames, (tuple, list)): argnames = [ x.strip() for x in argnames.split(",") if x.strip() ] if argname in argnames: break else: metafunc.parametrize( argname, fixturedef.params, indirect=True, scope=fixturedef.scope, ids=fixturedef.ids, ) else: continue # will raise FixtureLookupError at setup time def pytest_collection_modifyitems(self, items): # separate parametrized setups items[:] = reorder_items(items) def parsefactories(self, node_or_obj, nodeid=NOTSET, unittest=False): if nodeid is not NOTSET: holderobj = node_or_obj else: holderobj = node_or_obj.obj nodeid = node_or_obj.nodeid if holderobj in self._holderobjseen: return self._holderobjseen.add(holderobj) autousenames = [] for name in dir(holderobj): # The attribute can be an arbitrary descriptor, so the attribute # access below can raise. safe_getatt() ignores such exceptions. obj = safe_getattr(holderobj, name, None) marker = getfixturemarker(obj) if not isinstance(marker, FixtureFunctionMarker): # magic globals with __getattr__ might have got us a wrong # fixture attribute continue if marker.name: name = marker.name # during fixture definition we wrap the original fixture function # to issue a warning if called directly, so here we unwrap it in order to not emit the warning # when pytest itself calls the fixture function obj = get_real_method(obj, holderobj) fixture_def = FixtureDef( self, nodeid, name, obj, marker.scope, marker.params, unittest=unittest, ids=marker.ids, ) faclist = self._arg2fixturedefs.setdefault(name, []) if fixture_def.has_location: faclist.append(fixture_def) else: # fixturedefs with no location are at the front # so this inserts the current fixturedef after the # existing fixturedefs from external plugins but # before the fixturedefs provided in conftests. i = len([f for f in faclist if not f.has_location]) faclist.insert(i, fixture_def) if marker.autouse: autousenames.append(name) if autousenames: self._nodeid_and_autousenames.append((nodeid or "", autousenames)) def getfixturedefs(self, argname, nodeid): """ Gets a list of fixtures which are applicable to the given node id. :param str argname: name of the fixture to search for :param str nodeid: full node id of the requesting test. :return: list[FixtureDef] """ try: fixturedefs = self._arg2fixturedefs[argname] except KeyError: return None return tuple(self._matchfactories(fixturedefs, nodeid)) def _matchfactories(self, fixturedefs, nodeid): from _pytest import nodes for fixturedef in fixturedefs: if nodes.ischildnode(fixturedef.baseid, nodeid): yield fixturedef

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import functools import inspect import itertools import sys import warnings from collections import defaultdict from collections import deque from typing import Dict from typing import List from typing import Optional from typing import Tuple import attr import py.path import _pytest from _pytest._code.code import FormattedExcinfo from _pytest._code.code import TerminalRepr from _pytest._code.source import getfslineno from _pytest.compat import _format_args from _pytest.compat import _PytestWrapper from _pytest.compat import get_real_func from _pytest.compat import get_real_method from _pytest.compat import getfuncargnames from _pytest.compat import getimfunc from _pytest.compat import getlocation from _pytest.compat import is_generator from _pytest.compat import NOTSET from _pytest.compat import order_preserving_dict from _pytest.compat import safe_getattr from _pytest.compat import TYPE_CHECKING from _pytest.deprecated import FIXTURE_POSITIONAL_ARGUMENTS from _pytest.deprecated import FUNCARGNAMES from _pytest.mark import ParameterSet from _pytest.outcomes import fail from _pytest.outcomes import TEST_OUTCOME if TYPE_CHECKING: from typing import Type from typing_extensions import Literal from _pytest import nodes from _pytest._io import TerminalWriter from _pytest.main import Session from _pytest.runner import _RuntestPhase _Scope = Literal["session", "package", "module", "class", "function"] @attr.s(frozen=True) class PseudoFixtureDef: cached_result = attr.ib() scope = attr.ib() def pytest_sessionstart(session: "Session"): import _pytest.python import _pytest.nodes scopename2class.update( { "package": _pytest.python.Package, "class": _pytest.python.Class, "module": _pytest.python.Module, "function": _pytest.nodes.Item, "session": _pytest.main.Session, } ) session._fixturemanager = FixtureManager(session) scopename2class = {} scope2props = dict(session=()) scope2props["package"] = ("fspath",) scope2props["module"] = ("fspath", "module") scope2props["class"] = scope2props["module"] + ("cls",) scope2props["instance"] = scope2props["class"] + ("instance",) scope2props["function"] = scope2props["instance"] + ("function", "keywords") def scopeproperty(name=None, doc=None): def decoratescope(func): scopename = name or func.__name__ def provide(self): if func.__name__ in scope2props[self.scope]: return func(self) raise AttributeError( "{} not available in {}-scoped context".format(scopename, self.scope) ) return property(provide, None, None, func.__doc__) return decoratescope def get_scope_package(node, fixturedef): import pytest cls = pytest.Package current = node fixture_package_name = "{}/{}".format(fixturedef.baseid, "__init__.py") while current and ( type(current) is not cls or fixture_package_name != current.nodeid ): current = current.parent if current is None: return node.session return current def get_scope_node(node, scope): cls = scopename2class.get(scope) if cls is None: raise ValueError("unknown scope") return node.getparent(cls) def add_funcarg_pseudo_fixture_def(collector, metafunc, fixturemanager): if not metafunc._calls[0].funcargs: return arg2params = {} arg2scope = {} for callspec in metafunc._calls: for argname, argvalue in callspec.funcargs.items(): assert argname not in callspec.params callspec.params[argname] = argvalue arg2params_list = arg2params.setdefault(argname, []) callspec.indices[argname] = len(arg2params_list) arg2params_list.append(argvalue) if argname not in arg2scope: scopenum = callspec._arg2scopenum.get(argname, scopenum_function) arg2scope[argname] = scopes[scopenum] callspec.funcargs.clear() # time we can rely on a proper FixtureDef to exist for fixture setup. arg2fixturedefs = metafunc._arg2fixturedefs for argname, valuelist in arg2params.items(): # if we have a scope that is higher than function we need # to make sure we only ever create an according fixturedef on # a per-scope basis. We thus store and cache the fixturedef on the # node related to the scope. scope = arg2scope[argname] node = None if scope != "function": node = get_scope_node(collector, scope) if node is None: assert scope == "class" and isinstance(collector, _pytest.python.Module) # use module-level collector for class-scope (for now) node = collector if node and argname in node._name2pseudofixturedef: arg2fixturedefs[argname] = [node._name2pseudofixturedef[argname]] else: fixturedef = FixtureDef( fixturemanager, "", argname, get_direct_param_fixture_func, arg2scope[argname], valuelist, False, False, ) arg2fixturedefs[argname] = [fixturedef] if node is not None: node._name2pseudofixturedef[argname] = fixturedef def getfixturemarker(obj): try: return getattr(obj, "_pytestfixturefunction", None) except TEST_OUTCOME: # some objects raise errors like request (from flask import request) # we don't expect them to be fixture functions return None def get_parametrized_fixture_keys(item, scopenum): assert scopenum < scopenum_function try: cs = item.callspec except AttributeError: pass else: for argname, param_index in sorted(cs.indices.items()): if cs._arg2scopenum[argname] != scopenum: continue if scopenum == 0: key = (argname, param_index) elif scopenum == 1: key = (argname, param_index, item.fspath.dirpath()) elif scopenum == 2: key = (argname, param_index, item.fspath) elif scopenum == 3: key = (argname, param_index, item.fspath, item.cls) yield key def reorder_items(items): argkeys_cache = {} items_by_argkey = {} for scopenum in range(0, scopenum_function): argkeys_cache[scopenum] = d = {} items_by_argkey[scopenum] = item_d = defaultdict(deque) for item in items: keys = order_preserving_dict.fromkeys( get_parametrized_fixture_keys(item, scopenum) ) if keys: d[item] = keys for key in keys: item_d[key].append(item) items = order_preserving_dict.fromkeys(items) return list(reorder_items_atscope(items, argkeys_cache, items_by_argkey, 0)) def fix_cache_order(item, argkeys_cache, items_by_argkey): for scopenum in range(0, scopenum_function): for key in argkeys_cache[scopenum].get(item, []): items_by_argkey[scopenum][key].appendleft(item) def reorder_items_atscope(items, argkeys_cache, items_by_argkey, scopenum): if scopenum >= scopenum_function or len(items) < 3: return items ignore = set() items_deque = deque(items) items_done = order_preserving_dict() scoped_items_by_argkey = items_by_argkey[scopenum] scoped_argkeys_cache = argkeys_cache[scopenum] while items_deque: no_argkey_group = order_preserving_dict() slicing_argkey = None while items_deque: item = items_deque.popleft() if item in items_done or item in no_argkey_group: continue argkeys = order_preserving_dict.fromkeys( k for k in scoped_argkeys_cache.get(item, []) if k not in ignore ) if not argkeys: no_argkey_group[item] = None else: slicing_argkey, _ = argkeys.popitem() matching_items = [ i for i in scoped_items_by_argkey[slicing_argkey] if i in items ] for i in reversed(matching_items): fix_cache_order(i, argkeys_cache, items_by_argkey) items_deque.appendleft(i) break if no_argkey_group: no_argkey_group = reorder_items_atscope( no_argkey_group, argkeys_cache, items_by_argkey, scopenum + 1 ) for item in no_argkey_group: items_done[item] = None ignore.add(slicing_argkey) return items_done def fillfixtures(function): try: request = function._request except AttributeError: fm = function.session._fixturemanager fi = fm.getfixtureinfo(function.parent, function.obj, None) function._fixtureinfo = fi request = function._request = FixtureRequest(function) request._fillfixtures() newfuncargs = {} for name in fi.argnames: newfuncargs[name] = function.funcargs[name] function.funcargs = newfuncargs else: request._fillfixtures() def get_direct_param_fixture_func(request): return request.param @attr.s(slots=True) class FuncFixtureInfo: argnames = attr.ib(type=tuple) initialnames = attr.ib(type=tuple) names_closure = attr.ib() name2fixturedefs = attr.ib() def prune_dependency_tree(self): closure = set() working_set = set(self.initialnames) while working_set: argname = working_set.pop() if argname not in closure and argname in self.names_closure: closure.add(argname) if argname in self.name2fixturedefs: working_set.update(self.name2fixturedefs[argname][-1].argnames) self.names_closure[:] = sorted(closure, key=self.names_closure.index) class FixtureRequest: def __init__(self, pyfuncitem): self._pyfuncitem = pyfuncitem self.fixturename = None self.scope = "function" self._fixture_defs = {} fixtureinfo = pyfuncitem._fixtureinfo self._arg2fixturedefs = fixtureinfo.name2fixturedefs.copy() self._arg2index = {} self._fixturemanager = pyfuncitem.session._fixturemanager self._phase = None @property def fixturenames(self): result = list(self._pyfuncitem._fixtureinfo.names_closure) result.extend(set(self._fixture_defs).difference(result)) return result @property def funcargnames(self): warnings.warn(FUNCARGNAMES, stacklevel=2) return self.fixturenames @property def node(self): return self._getscopeitem(self.scope) def _getnextfixturedef(self, argname): fixturedefs = self._arg2fixturedefs.get(argname, None) if fixturedefs is None: parentid = self._pyfuncitem.parent.nodeid fixturedefs = self._fixturemanager.getfixturedefs(argname, parentid) self._arg2fixturedefs[argname] = fixturedefs index = self._arg2index.get(argname, 0) - 1 if fixturedefs is None or (-index > len(fixturedefs)): raise FixtureLookupError(argname, self) self._arg2index[argname] = index return fixturedefs[index] @property def config(self): return self._pyfuncitem.config @scopeproperty() def function(self): return self._pyfuncitem.obj @scopeproperty("class") def cls(self): clscol = self._pyfuncitem.getparent(_pytest.python.Class) if clscol: return clscol.obj @property def instance(self): try: return self._pyfuncitem._testcase except AttributeError: function = getattr(self, "function", None) return getattr(function, "__self__", None) @scopeproperty() def module(self): return self._pyfuncitem.getparent(_pytest.python.Module).obj @scopeproperty() def fspath(self) -> py.path.local: return self._pyfuncitem.fspath @property def keywords(self): return self.node.keywords @property def session(self): return self._pyfuncitem.session def addfinalizer(self, finalizer): self._addfinalizer(finalizer, scope=self.scope) def _addfinalizer(self, finalizer, scope): colitem = self._getscopeitem(scope) self._pyfuncitem.session._setupstate.addfinalizer( finalizer=finalizer, colitem=colitem ) def applymarker(self, marker): self.node.add_marker(marker) def raiseerror(self, msg): raise self._fixturemanager.FixtureLookupError(None, self, msg) def _fillfixtures(self): item = self._pyfuncitem fixturenames = getattr(item, "fixturenames", self.fixturenames) for argname in fixturenames: if argname not in item.funcargs: item.funcargs[argname] = self.getfixturevalue(argname) def getfixturevalue(self, argname): return self._get_active_fixturedef(argname).cached_result[0] def _get_active_fixturedef(self, argname): try: return self._fixture_defs[argname] except KeyError: try: fixturedef = self._getnextfixturedef(argname) except FixtureLookupError: if argname == "request": cached_result = (self, [0], None) scope = "function" return PseudoFixtureDef(cached_result, scope) raise self._compute_fixture_value(fixturedef) self._fixture_defs[argname] = fixturedef return fixturedef def _get_fixturestack(self): current = self values = [] while 1: fixturedef = getattr(current, "_fixturedef", None) if fixturedef is None: values.reverse() return values values.append(fixturedef) current = current._parent_request def _compute_fixture_value(self, fixturedef: "FixtureDef") -> None: argname = fixturedef.argname funcitem = self._pyfuncitem scope = fixturedef.scope try: param = funcitem.callspec.getparam(argname) except (AttributeError, ValueError): param = NOTSET param_index = 0 has_params = fixturedef.params is not None fixtures_not_supported = getattr(funcitem, "nofuncargs", False) if has_params and fixtures_not_supported: msg = ( "{name} does not support fixtures, maybe unittest.TestCase subclass?\n" "Node id: {nodeid}\n" "Function type: {typename}" ).format( name=funcitem.name, nodeid=funcitem.nodeid, typename=type(funcitem).__name__, ) fail(msg, pytrace=False) if has_params: frame = inspect.stack()[3] frameinfo = inspect.getframeinfo(frame[0]) source_path = py.path.local(frameinfo.filename) source_lineno = frameinfo.lineno rel_source_path = source_path.relto(funcitem.config.rootdir) if rel_source_path: source_path_str = rel_source_path else: source_path_str = str(source_path) msg = ( "The requested fixture has no parameter defined for test:\n" " {}\n\n" "Requested fixture '{}' defined in:\n{}" "\n\nRequested here:\n{}:{}".format( funcitem.nodeid, fixturedef.argname, getlocation(fixturedef.func, funcitem.config.rootdir), source_path_str, source_lineno, ) ) fail(msg, pytrace=False) else: param_index = funcitem.callspec.indices[argname] paramscopenum = funcitem.callspec._arg2scopenum.get(argname) if paramscopenum is not None: scope = scopes[paramscopenum] subrequest = SubRequest(self, scope, param, param_index, fixturedef) subrequest._check_scope(argname, self.scope, scope) try: fixturedef.execute(request=subrequest) finally: self._schedule_finalizers(fixturedef, subrequest) def _schedule_finalizers(self, fixturedef, subrequest): self.session._setupstate.addfinalizer( functools.partial(fixturedef.finish, request=subrequest), subrequest.node ) def _check_scope(self, argname, invoking_scope, requested_scope): if argname == "request": return if scopemismatch(invoking_scope, requested_scope): lines = self._factorytraceback() fail( "ScopeMismatch: You tried to access the %r scoped " "fixture %r with a %r scoped request object, " "involved factories\n%s" % ((requested_scope, argname, invoking_scope, "\n".join(lines))), pytrace=False, ) def _factorytraceback(self): lines = [] for fixturedef in self._get_fixturestack(): factory = fixturedef.func fs, lineno = getfslineno(factory) p = self._pyfuncitem.session.fspath.bestrelpath(fs) args = _format_args(factory) lines.append("%s:%d: def %s%s" % (p, lineno + 1, factory.__name__, args)) return lines def _getscopeitem(self, scope): if scope == "function": return self._pyfuncitem if scope == "package": node = get_scope_package(self._pyfuncitem, self._fixturedef) else: node = get_scope_node(self._pyfuncitem, scope) if node is None and scope == "class": node = self._pyfuncitem assert node, 'Could not obtain a node for scope "{}" for function {!r}'.format( scope, self._pyfuncitem ) return node def __repr__(self): return "<FixtureRequest for {!r} _phase={}>".format(self.node, self._phase) class SubRequest(FixtureRequest): def __init__( self, request: "FixtureRequest", scope: "_Scope", param, param_index: int, fixturedef: "FixtureDef", ) -> None: self._parent_request = request self.fixturename = fixturedef.argname if param is not NOTSET: self.param = param self.param_index = param_index self.scope = scope self._fixturedef = fixturedef self._pyfuncitem = request._pyfuncitem self._fixture_defs = request._fixture_defs self._arg2fixturedefs = request._arg2fixturedefs self._arg2index = request._arg2index self._fixturemanager = request._fixturemanager def __repr__(self): return "<SubRequest {!r} for {!r} _phase={}>".format( self.fixturename, self._pyfuncitem, self._phase ) @property def _phase(self) -> "Optional[_RuntestPhase]": return self._parent_request._phase def addfinalizer(self, finalizer): self._fixturedef.addfinalizer(finalizer) def _schedule_finalizers(self, fixturedef, subrequest): if fixturedef.argname not in self.fixturenames: fixturedef.addfinalizer( functools.partial(self._fixturedef.finish, request=self) ) super()._schedule_finalizers(fixturedef, subrequest) scopes = "session package module class function".split() scopenum_function = scopes.index("function") def scopemismatch(currentscope, newscope): return scopes.index(newscope) > scopes.index(currentscope) def scope2index(scope, descr, where=None): try: return scopes.index(scope) except ValueError: fail( "{} {}got an unexpected scope value '{}'".format( descr, "from {} ".format(where) if where else "", scope ), pytrace=False, ) class FixtureLookupError(LookupError): def __init__(self, argname, request, msg=None): self.argname = argname self.request = request self.fixturestack = request._get_fixturestack() self.msg = msg def formatrepr(self) -> "FixtureLookupErrorRepr": tblines = [] addline = tblines.append stack = [self.request._pyfuncitem.obj] stack.extend(map(lambda x: x.func, self.fixturestack)) msg = self.msg if msg is not None: # it at the requesting side stack = stack[:-1] for function in stack: fspath, lineno = getfslineno(function) try: lines, _ = inspect.getsourcelines(get_real_func(function)) except (OSError, IndexError, TypeError): error_msg = "file %s, line %s: source code not available" addline(error_msg % (fspath, lineno + 1)) else: addline("file {}, line {}".format(fspath, lineno + 1)) for i, line in enumerate(lines): line = line.rstrip() addline(" " + line) if line.lstrip().startswith("def"): break if msg is None: fm = self.request._fixturemanager available = set() parentid = self.request._pyfuncitem.parent.nodeid for name, fixturedefs in fm._arg2fixturedefs.items(): faclist = list(fm._matchfactories(fixturedefs, parentid)) if faclist: available.add(name) if self.argname in available: msg = " recursive dependency involving fixture '{}' detected".format( self.argname ) else: msg = "fixture '{}' not found".format(self.argname) msg += "\n available fixtures: {}".format(", ".join(sorted(available))) msg += "\n use 'pytest --fixtures [testpath]' for help on them." return FixtureLookupErrorRepr(fspath, lineno, tblines, msg, self.argname) class FixtureLookupErrorRepr(TerminalRepr): def __init__(self, filename, firstlineno, tblines, errorstring, argname): self.tblines = tblines self.errorstring = errorstring self.filename = filename self.firstlineno = firstlineno self.argname = argname def toterminal(self, tw: "TerminalWriter") -> None: # tw.line("FixtureLookupError: %s" %(self.argname), red=True) for tbline in self.tblines: tw.line(tbline.rstrip()) lines = self.errorstring.split("\n") if lines: tw.line( "{} {}".format(FormattedExcinfo.fail_marker, lines[0].strip()), red=True, ) for line in lines[1:]: tw.line( "{} {}".format(FormattedExcinfo.flow_marker, line.strip()), red=True, ) tw.line() tw.line("%s:%d" % (self.filename, self.firstlineno + 1)) def fail_fixturefunc(fixturefunc, msg): fs, lineno = getfslineno(fixturefunc) location = "{}:{}".format(fs, lineno + 1) source = _pytest._code.Source(fixturefunc) fail(msg + ":\n\n" + str(source.indent()) + "\n" + location, pytrace=False) def call_fixture_func(fixturefunc, request, kwargs): yieldctx = is_generator(fixturefunc) if yieldctx: it = fixturefunc(**kwargs) res = next(it) finalizer = functools.partial(_teardown_yield_fixture, fixturefunc, it) request.addfinalizer(finalizer) else: res = fixturefunc(**kwargs) return res def _teardown_yield_fixture(fixturefunc, it): try: next(it) except StopIteration: pass else: fail_fixturefunc( fixturefunc, "yield_fixture function has more than one 'yield'" ) def _eval_scope_callable(scope_callable, fixture_name, config): try: result = scope_callable(fixture_name=fixture_name, config=config) except Exception: raise TypeError( "Error evaluating {} while defining fixture '{}'.\n" "Expected a function with the signature (*, fixture_name, config)".format( scope_callable, fixture_name ) ) if not isinstance(result, str): fail( "Expected {} to return a 'str' while defining fixture '{}', but it returned:\n" "{!r}".format(scope_callable, fixture_name, result), pytrace=False, ) return result class FixtureDef: def __init__( self, fixturemanager, baseid, argname, func, scope, params, unittest=False, ids=None, ): self._fixturemanager = fixturemanager self.baseid = baseid or "" self.has_location = baseid is not None self.func = func self.argname = argname if callable(scope): scope = _eval_scope_callable(scope, argname, fixturemanager.config) self.scope = scope self.scopenum = scope2index( scope or "function", descr="Fixture '{}'".format(func.__name__), where=baseid, ) self.params = params self.argnames = getfuncargnames(func, name=argname, is_method=unittest) self.unittest = unittest self.ids = ids self.cached_result = None self._finalizers = [] def addfinalizer(self, finalizer): self._finalizers.append(finalizer) def finish(self, request): exc = None try: while self._finalizers: try: func = self._finalizers.pop() func() except BaseException as e: # XXX Only first exception will be seen by user, # ideally all should be reported. if exc is None: exc = e if exc: raise exc finally: hook = self._fixturemanager.session.gethookproxy(request.node.fspath) hook.pytest_fixture_post_finalizer(fixturedef=self, request=request) # even if finalization fails, we invalidate # the cached fixture value and remove # all finalizers because they may be bound methods which will # keep instances alive self.cached_result = None self._finalizers = [] def execute(self, request): # get required arguments and register our own finish() # with their finalization for argname in self.argnames: fixturedef = request._get_active_fixturedef(argname) if argname != "request": fixturedef.addfinalizer(functools.partial(self.finish, request=request)) my_cache_key = self.cache_key(request) if self.cached_result is not None: result, cache_key, err = self.cached_result # note: comparison with `==` can fail (or be expensive) for e.g. # numpy arrays (#6497) if my_cache_key is cache_key: if err is not None: _, val, tb = err raise val.with_traceback(tb) else: return result # we have a previous but differently parametrized fixture instance # so we need to tear it down before creating a new one self.finish(request) assert self.cached_result is None hook = self._fixturemanager.session.gethookproxy(request.node.fspath) return hook.pytest_fixture_setup(fixturedef=self, request=request) def cache_key(self, request): return request.param_index if not hasattr(request, "param") else request.param def __repr__(self): return "<FixtureDef argname={!r} scope={!r} baseid={!r}>".format( self.argname, self.scope, self.baseid ) def resolve_fixture_function(fixturedef, request): fixturefunc = fixturedef.func if fixturedef.unittest: if request.instance is not None: # bind the unbound method to the TestCase instance fixturefunc = fixturedef.func.__get__(request.instance) else: # the fixture function needs to be bound to the actual # request.instance so that code working with "fixturedef" behaves # as expected. if request.instance is not None: # handle the case where fixture is defined not in a test class, but some other class # (for example a plugin class with a fixture), see #2270 if hasattr(fixturefunc, "__self__") and not isinstance( request.instance, fixturefunc.__self__.__class__ ): return fixturefunc fixturefunc = getimfunc(fixturedef.func) if fixturefunc != fixturedef.func: fixturefunc = fixturefunc.__get__(request.instance) return fixturefunc def pytest_fixture_setup(fixturedef, request): kwargs = {} for argname in fixturedef.argnames: fixdef = request._get_active_fixturedef(argname) assert fixdef.cached_result is not None result, arg_cache_key, exc = fixdef.cached_result request._check_scope(argname, request.scope, fixdef.scope) kwargs[argname] = result fixturefunc = resolve_fixture_function(fixturedef, request) my_cache_key = fixturedef.cache_key(request) try: result = call_fixture_func(fixturefunc, request, kwargs) except TEST_OUTCOME: fixturedef.cached_result = (None, my_cache_key, sys.exc_info()) raise fixturedef.cached_result = (result, my_cache_key, None) return result def _ensure_immutable_ids(ids): if ids is None: return if callable(ids): return ids return tuple(ids) def wrap_function_to_error_out_if_called_directly(function, fixture_marker): message = ( 'Fixture "{name}" called directly. Fixtures are not meant to be called directly,\n' "but are created automatically when test functions request them as parameters.\n" "See https://docs.pytest.org/en/latest/fixture.html for more information about fixtures, and\n" "https://docs.pytest.org/en/latest/deprecations.html#calling-fixtures-directly about how to update your code." ).format(name=fixture_marker.name or function.__name__) @functools.wraps(function) def result(*args, **kwargs): fail(message, pytrace=False) # keep reference to the original function in our own custom attribute so we don't unwrap esult.__pytest_wrapped__ = _PytestWrapper(function) return result @attr.s(frozen=True) class FixtureFunctionMarker: scope = attr.ib() params = attr.ib( type=Optional[Tuple[object, ...]], converter=attr.converters.optional(tuple), ) autouse = attr.ib(default=False) ids = attr.ib(default=None, converter=_ensure_immutable_ids) name = attr.ib(default=None) def __call__(self, function): if inspect.isclass(function): raise ValueError("class fixtures not supported (maybe in the future)") if getattr(function, "_pytestfixturefunction", False): raise ValueError( "fixture is being applied more than once to the same function" ) function = wrap_function_to_error_out_if_called_directly(function, self) name = self.name or function.__name__ if name == "request": location = getlocation(function) fail( "'request' is a reserved word for fixtures, use another name:\n {}".format( location ), pytrace=False, ) function._pytestfixturefunction = self return function FIXTURE_ARGS_ORDER = ("scope", "params", "autouse", "ids", "name") def _parse_fixture_args(callable_or_scope, *args, **kwargs): arguments = { "scope": "function", "params": None, "autouse": False, "ids": None, "name": None, } kwargs = { key: value for key, value in kwargs.items() if arguments.get(key) != value } fixture_function = None if isinstance(callable_or_scope, str): args = list(args) args.insert(0, callable_or_scope) else: fixture_function = callable_or_scope positionals = set() for positional, argument_name in zip(args, FIXTURE_ARGS_ORDER): arguments[argument_name] = positional positionals.add(argument_name) duplicated_kwargs = {kwarg for kwarg in kwargs.keys() if kwarg in positionals} if duplicated_kwargs: raise TypeError( "The fixture arguments are defined as positional and keyword: {}. " "Use only keyword arguments.".format(", ".join(duplicated_kwargs)) ) if positionals: warnings.warn(FIXTURE_POSITIONAL_ARGUMENTS, stacklevel=2) arguments.update(kwargs) return fixture_function, arguments def fixture( callable_or_scope=None, *args, scope="function", params=None, autouse=False, ids=None, name=None ): if params is not None: params = list(params) fixture_function, arguments = _parse_fixture_args( callable_or_scope, *args, scope=scope, params=params, autouse=autouse, ids=ids, name=name, ) scope = arguments.get("scope") params = arguments.get("params") autouse = arguments.get("autouse") ids = arguments.get("ids") name = arguments.get("name") if fixture_function and params is None and autouse is False: return FixtureFunctionMarker(scope, params, autouse, name=name)( fixture_function ) return FixtureFunctionMarker(scope, params, autouse, ids=ids, name=name) def yield_fixture( callable_or_scope=None, *args, scope="function", params=None, autouse=False, ids=None, name=None ): return fixture( callable_or_scope, *args, scope=scope, params=params, autouse=autouse, ids=ids, name=name, ) defaultfuncargprefixmarker = fixture() @fixture(scope="session") def pytestconfig(request): return request.config def pytest_addoption(parser): parser.addini( "usefixtures", type="args", default=[], help="list of default fixtures to be used with this project", ) class FixtureManager: FixtureLookupError = FixtureLookupError FixtureLookupErrorRepr = FixtureLookupErrorRepr def __init__(self, session): self.session = session self.config = session.config self._arg2fixturedefs = {} self._holderobjseen = set() self._nodeid_and_autousenames = [("", self.config.getini("usefixtures"))] session.config.pluginmanager.register(self, "funcmanage") def _get_direct_parametrize_args(self, node): parametrize_argnames = [] for marker in node.iter_markers(name="parametrize"): if not marker.kwargs.get("indirect", False): try: p_argnames, _ = ParameterSet._parse_parametrize_args( *marker.args, **marker.kwargs ) except TypeError: pass else: parametrize_argnames.extend(p_argnames) return parametrize_argnames def getfixtureinfo(self, node, func, cls, funcargs=True): if funcargs and not getattr(node, "nofuncargs", False): argnames = getfuncargnames(func, name=node.name, cls=cls) else: argnames = () usefixtures = itertools.chain.from_iterable( mark.args for mark in node.iter_markers(name="usefixtures") ) initialnames = tuple(usefixtures) + argnames fm = node.session._fixturemanager initialnames, names_closure, arg2fixturedefs = fm.getfixtureclosure( initialnames, node, ignore_args=self._get_direct_parametrize_args(node) ) return FuncFixtureInfo(argnames, initialnames, names_closure, arg2fixturedefs) def pytest_plugin_registered(self, plugin): nodeid = None try: p = py.path.local(plugin.__file__).realpath() except AttributeError: pass else: from _pytest import nodes if p.basename.startswith("conftest.py"): nodeid = p.dirpath().relto(self.config.rootdir) if p.sep != nodes.SEP: nodeid = nodeid.replace(p.sep, nodes.SEP) self.parsefactories(plugin, nodeid) def _getautousenames(self, nodeid): autousenames = [] for baseid, basenames in self._nodeid_and_autousenames: if nodeid.startswith(baseid): if baseid: i = len(baseid) nextchar = nodeid[i : i + 1] if nextchar and nextchar not in ":/": continue autousenames.extend(basenames) return autousenames def getfixtureclosure(self, fixturenames, parentnode, ignore_args=()): parentid = parentnode.nodeid fixturenames_closure = self._getautousenames(parentid) def merge(otherlist): for arg in otherlist: if arg not in fixturenames_closure: fixturenames_closure.append(arg) merge(fixturenames) initialnames = tuple(fixturenames_closure) arg2fixturedefs = {} lastlen = -1 while lastlen != len(fixturenames_closure): lastlen = len(fixturenames_closure) for argname in fixturenames_closure: if argname in ignore_args: continue if argname in arg2fixturedefs: continue fixturedefs = self.getfixturedefs(argname, parentid) if fixturedefs: arg2fixturedefs[argname] = fixturedefs merge(fixturedefs[-1].argnames) def sort_by_scope(arg_name): try: fixturedefs = arg2fixturedefs[arg_name] except KeyError: return scopes.index("function") else: return fixturedefs[-1].scopenum fixturenames_closure.sort(key=sort_by_scope) return initialnames, fixturenames_closure, arg2fixturedefs def pytest_generate_tests(self, metafunc): for argname in metafunc.fixturenames: faclist = metafunc._arg2fixturedefs.get(argname) if faclist: fixturedef = faclist[-1] if fixturedef.params is not None: markers = list(metafunc.definition.iter_markers("parametrize")) for parametrize_mark in markers: if "argnames" in parametrize_mark.kwargs: argnames = parametrize_mark.kwargs["argnames"] else: argnames = parametrize_mark.args[0] if not isinstance(argnames, (tuple, list)): argnames = [ x.strip() for x in argnames.split(",") if x.strip() ] if argname in argnames: break else: metafunc.parametrize( argname, fixturedef.params, indirect=True, scope=fixturedef.scope, ids=fixturedef.ids, ) else: continue def pytest_collection_modifyitems(self, items): items[:] = reorder_items(items) def parsefactories(self, node_or_obj, nodeid=NOTSET, unittest=False): if nodeid is not NOTSET: holderobj = node_or_obj else: holderobj = node_or_obj.obj nodeid = node_or_obj.nodeid if holderobj in self._holderobjseen: return self._holderobjseen.add(holderobj) autousenames = [] for name in dir(holderobj): obj = safe_getattr(holderobj, name, None) marker = getfixturemarker(obj) if not isinstance(marker, FixtureFunctionMarker): continue if marker.name: name = marker.name obj = get_real_method(obj, holderobj) fixture_def = FixtureDef( self, nodeid, name, obj, marker.scope, marker.params, unittest=unittest, ids=marker.ids, ) faclist = self._arg2fixturedefs.setdefault(name, []) if fixture_def.has_location: faclist.append(fixture_def) else: i = len([f for f in faclist if not f.has_location]) faclist.insert(i, fixture_def) if marker.autouse: autousenames.append(name) if autousenames: self._nodeid_and_autousenames.append((nodeid or "", autousenames)) def getfixturedefs(self, argname, nodeid): try: fixturedefs = self._arg2fixturedefs[argname] except KeyError: return None return tuple(self._matchfactories(fixturedefs, nodeid)) def _matchfactories(self, fixturedefs, nodeid): from _pytest import nodes for fixturedef in fixturedefs: if nodes.ischildnode(fixturedef.baseid, nodeid): yield fixturedef

true

f7189cf1777438042d5eeb717699cbd063289d08

10,871

py

Python

env/lib/python3.8/site-packages/plotly/validators/choroplethmapbox/_colorbar.py

acrucetta/Chicago_COVI_WebApp

a37c9f492a20dcd625f8647067394617988de913

[ "MIT", "Unlicense" ]

2

2021-07-07T20:16:23.000Z

2021-07-14T14:03:09.000Z

env/lib/python3.8/site-packages/plotly/validators/choroplethmapbox/_colorbar.py

acrucetta/Chicago_COVI_WebApp

a37c9f492a20dcd625f8647067394617988de913

[ "MIT", "Unlicense" ]

5

2020-06-05T20:56:21.000Z

2021-09-22T19:12:42.000Z

env/lib/python3.8/site-packages/plotly/validators/choroplethmapbox/_colorbar.py

acrucetta/Chicago_COVI_WebApp

a37c9f492a20dcd625f8647067394617988de913

[ "MIT", "Unlicense" ]

2

2020-07-05T12:57:14.000Z

2020-07-05T12:58:00.000Z

import _plotly_utils.basevalidators class ColorbarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="choroplethmapbox", **kwargs ): super(ColorbarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L<f>", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M<n>" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L<f>* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of :class:`plotly.graph_objects.choropl ethmapbox.colorbar.Tickformatstop` instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.choroplethmapbox.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of choroplethmapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on Chart Studio Cloud for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on Chart Studio Cloud for tickvals . tickwidth Sets the tick width (in px). title :class:`plotly.graph_objects.choroplethmapbox.c olorbar.Title` instance or dict with compatible properties titlefont Deprecated: Please use choroplethmapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choroplethmapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs )

47.060606

78

0.52663

import _plotly_utils.basevalidators class ColorbarValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__( self, plotly_name="colorbar", parent_name="choroplethmapbox", **kwargs ): super(ColorbarValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "ColorBar"), data_docs=kwargs.pop( "data_docs", """ bgcolor Sets the color of padded area. bordercolor Sets the axis line color. borderwidth Sets the width (in px) or the border enclosing this color bar. dtick Sets the step in-between ticks on this axis. Use with `tick0`. Must be a positive number, or special strings available to "log" and "date" axes. If the axis `type` is "log", then ticks are set every 10^(n*dtick) where n is the tick number. For example, to set a tick mark at 1, 10, 100, 1000, ... set dtick to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to log_10(5), or 0.69897000433. "log" has several special values; "L<f>", where `f` is a positive number, gives ticks linearly spaced in value (but not position). For example `tick0` = 0.1, `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus small digits between, use "D1" (all digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and "D2". If the axis `type` is "date", then you must convert the time to milliseconds. For example, to set the interval between ticks to one day, set `dtick` to 86400000.0. "date" also has special values "M<n>" gives ticks spaced by a number of months. `n` must be a positive integer. To set ticks on the 15th of every third month, set `tick0` to "2000-01-15" and `dtick` to "M3". To set ticks every 4 years, set `dtick` to "M48" exponentformat Determines a formatting rule for the tick exponents. For example, consider the number 1,000,000,000. If "none", it appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If "B", 1B. len Sets the length of the color bar This measure excludes the padding of both ends. That is, the color bar length is this length minus the padding on both ends. lenmode Determines whether this color bar's length (i.e. the measure in the color variation direction) is set in units of plot "fraction" or in *pixels. Use `len` to set the value. nticks Specifies the maximum number of ticks for the particular axis. The actual number of ticks will be chosen automatically to be less than or equal to `nticks`. Has an effect only if `tickmode` is set to "auto". outlinecolor Sets the axis line color. outlinewidth Sets the width (in px) of the axis line. separatethousands If "true", even 4-digit integers are separated showexponent If "all", all exponents are shown besides their significands. If "first", only the exponent of the first tick is shown. If "last", only the exponent of the last tick is shown. If "none", no exponents appear. showticklabels Determines whether or not the tick labels are drawn. showtickprefix If "all", all tick labels are displayed with a prefix. If "first", only the first tick is displayed with a prefix. If "last", only the last tick is displayed with a suffix. If "none", tick prefixes are hidden. showticksuffix Same as `showtickprefix` but for tick suffixes. thickness Sets the thickness of the color bar This measure excludes the size of the padding, ticks and labels. thicknessmode Determines whether this color bar's thickness (i.e. the measure in the constant color direction) is set in units of plot "fraction" or in "pixels". Use `thickness` to set the value. tick0 Sets the placement of the first tick on this axis. Use with `dtick`. If the axis `type` is "log", then you must take the log of your starting tick (e.g. to set the starting tick to 100, set the `tick0` to 2) except when `dtick`=*L<f>* (see `dtick` for more info). If the axis `type` is "date", it should be a date string, like date data. If the axis `type` is "category", it should be a number, using the scale where each category is assigned a serial number from zero in the order it appears. tickangle Sets the angle of the tick labels with respect to the horizontal. For example, a `tickangle` of -90 draws the tick labels vertically. tickcolor Sets the tick color. tickfont Sets the color bar's tick label font tickformat Sets the tick label formatting rule using d3 formatting mini-languages which are very similar to those in Python. For numbers, see: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-3.x-api- reference/blob/master/Time-Formatting.md#format We add one item to d3's date formatter: "%{n}f" for fractional seconds with n digits. For example, *2016-10-13 09:15:23.456* with tickformat "%H~%M~%S.%2f" would display "09~15~23.46" tickformatstops A tuple of :class:`plotly.graph_objects.choropl ethmapbox.colorbar.Tickformatstop` instances or dicts with compatible properties tickformatstopdefaults When used in a template (as layout.template.dat a.choroplethmapbox.colorbar.tickformatstopdefau lts), sets the default property values to use for elements of choroplethmapbox.colorbar.tickformatstops ticklen Sets the tick length (in px). tickmode Sets the tick mode for this axis. If "auto", the number of ticks is set via `nticks`. If "linear", the placement of the ticks is determined by a starting position `tick0` and a tick step `dtick` ("linear" is the default value if `tick0` and `dtick` are provided). If "array", the placement of the ticks is set via `tickvals` and the tick text is `ticktext`. ("array" is the default value if `tickvals` is provided). tickprefix Sets a tick label prefix. ticks Determines whether ticks are drawn or not. If "", this axis' ticks are not drawn. If "outside" ("inside"), this axis' are drawn outside (inside) the axis lines. ticksuffix Sets a tick label suffix. ticktext Sets the text displayed at the ticks position via `tickvals`. Only has an effect if `tickmode` is set to "array". Used with `tickvals`. ticktextsrc Sets the source reference on Chart Studio Cloud for ticktext . tickvals Sets the values at which ticks on this axis appear. Only has an effect if `tickmode` is set to "array". Used with `ticktext`. tickvalssrc Sets the source reference on Chart Studio Cloud for tickvals . tickwidth Sets the tick width (in px). title :class:`plotly.graph_objects.choroplethmapbox.c olorbar.Title` instance or dict with compatible properties titlefont Deprecated: Please use choroplethmapbox.colorbar.title.font instead. Sets this color bar's title font. Note that the title's font used to be set by the now deprecated `titlefont` attribute. titleside Deprecated: Please use choroplethmapbox.colorbar.title.side instead. Determines the location of color bar's title with respect to the color bar. Note that the title's location used to be set by the now deprecated `titleside` attribute. x Sets the x position of the color bar (in plot fraction). xanchor Sets this color bar's horizontal position anchor. This anchor binds the `x` position to the "left", "center" or "right" of the color bar. xpad Sets the amount of padding (in px) along the x direction. y Sets the y position of the color bar (in plot fraction). yanchor Sets this color bar's vertical position anchor This anchor binds the `y` position to the "top", "middle" or "bottom" of the color bar. ypad Sets the amount of padding (in px) along the y direction. """, ), **kwargs )

true

f7189d61c476bf7a949e07d688c92793680eb5d3

584

py

Python

polls/admin.py

Nachtalb/django-polls

e5f1065cdcff99c8f21ea4f211d2d6fa344b65c7

[ "MIT" ]

null

polls/admin.py

Nachtalb/django-polls

e5f1065cdcff99c8f21ea4f211d2d6fa344b65c7

[ "MIT" ]

null

polls/admin.py

Nachtalb/django-polls

e5f1065cdcff99c8f21ea4f211d2d6fa344b65c7

[ "MIT" ]

null

from .models import Choice from .models import Question from django.contrib import admin # Register your models here. class ChoiceInline(admin.TabularInline): model = Choice extra = 1 class QuestionAdmin(admin.ModelAdmin): fieldsets = [ (None, {'fields': ['question_text']}), ('Date information', {'fields': ['pub_date']}), ] inlines = [ChoiceInline] list_display = ('question_text', 'pub_date', 'was_published_recently') list_filter = ['pub_date'] search_fields = ['question_text'] admin.site.register(Question, QuestionAdmin)

22.461538

74

0.683219

from .models import Choice from .models import Question from django.contrib import admin class ChoiceInline(admin.TabularInline): model = Choice extra = 1 class QuestionAdmin(admin.ModelAdmin): fieldsets = [ (None, {'fields': ['question_text']}), ('Date information', {'fields': ['pub_date']}), ] inlines = [ChoiceInline] list_display = ('question_text', 'pub_date', 'was_published_recently') list_filter = ['pub_date'] search_fields = ['question_text'] admin.site.register(Question, QuestionAdmin)

true

f7189f5b921b09008dadabc0c25611488fd3ea71

3,408

py

Python

lib/spack/spack/cmd/tags.py

player1537-forks/spack

822b7632222ec5a91dc7b7cda5fc0e08715bd47c

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

11

2015-10-04T02:17:46.000Z

2018-02-07T18:23:00.000Z

lib/spack/spack/cmd/tags.py

player1537-forks/spack

822b7632222ec5a91dc7b7cda5fc0e08715bd47c

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

22

2017-08-01T22:45:10.000Z

2022-03-10T07:46:31.000Z

lib/spack/spack/cmd/tags.py

player1537-forks/spack

822b7632222ec5a91dc7b7cda5fc0e08715bd47c

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

4

2016-06-10T17:57:39.000Z

2018-09-11T04:59:38.000Z

# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) import sys import six import llnl.util.tty as tty import llnl.util.tty.colify as colify import spack.repo import spack.store import spack.tag description = "Show package tags and associated packages" section = "basic" level = "long" def report_tags(category, tags): buffer = six.StringIO() isatty = sys.stdout.isatty() if isatty: num = len(tags) fmt = '{0} package tag'.format(category) buffer.write("{0}:\n".format(spack.util.string.plural(num, fmt))) if tags: colify.colify(tags, output=buffer, tty=isatty, indent=4) else: buffer.write(" None\n") print(buffer.getvalue()) def setup_parser(subparser): subparser.epilog = ( "Tags from known packages will be used if no tags are provided on " "the command\nline. If tags are provided, packages with at least one " "will be reported.\n\nYou are not allowed to provide tags and use " "'--all' at the same time." ) subparser.add_argument( '-i', '--installed', action='store_true', default=False, help="show information for installed packages only" ) subparser.add_argument( '-a', '--all', action='store_true', default=False, help="show packages for all available tags" ) subparser.add_argument( 'tag', nargs='*', help="show packages with the specified tag" ) def tags(parser, args): # Disallow combining all option with (positional) tags to avoid confusion if args.all and args.tag: tty.die("Use the '--all' option OR provide tag(s) on the command line") # Provide a nice, simple message if database is empty if args.installed and not spack.environment.installed_specs(): tty.msg("No installed packages") return # unique list of available tags available_tags = sorted(spack.repo.path.tag_index.keys()) if not available_tags: tty.msg("No tagged packages") return show_packages = args.tag or args.all # Only report relevant, available tags if no packages are to be shown if not show_packages: if not args.installed: report_tags("available", available_tags) else: tag_pkgs = spack.tag.packages_with_tags(available_tags, True, True) tags = tag_pkgs.keys() if tag_pkgs else [] report_tags("installed", tags) return # Report packages associated with tags buffer = six.StringIO() isatty = sys.stdout.isatty() tags = args.tag if args.tag else available_tags tag_pkgs = spack.tag.packages_with_tags(tags, args.installed, False) missing = 'No installed packages' if args.installed else 'None' for tag in sorted(tag_pkgs): # TODO: Remove the sorting once we're sure noone has an old # TODO: tag cache since it can accumulate duplicates. packages = sorted(list(set(tag_pkgs[tag]))) if isatty: buffer.write("{0}:\n".format(tag)) if packages: colify.colify(packages, output=buffer, tty=isatty, indent=4) else: buffer.write(" {0}\n".format(missing)) buffer.write("\n") print(buffer.getvalue())

31.555556

79

0.649941

import sys import six import llnl.util.tty as tty import llnl.util.tty.colify as colify import spack.repo import spack.store import spack.tag description = "Show package tags and associated packages" section = "basic" level = "long" def report_tags(category, tags): buffer = six.StringIO() isatty = sys.stdout.isatty() if isatty: num = len(tags) fmt = '{0} package tag'.format(category) buffer.write("{0}:\n".format(spack.util.string.plural(num, fmt))) if tags: colify.colify(tags, output=buffer, tty=isatty, indent=4) else: buffer.write(" None\n") print(buffer.getvalue()) def setup_parser(subparser): subparser.epilog = ( "Tags from known packages will be used if no tags are provided on " "the command\nline. If tags are provided, packages with at least one " "will be reported.\n\nYou are not allowed to provide tags and use " "'--all' at the same time." ) subparser.add_argument( '-i', '--installed', action='store_true', default=False, help="show information for installed packages only" ) subparser.add_argument( '-a', '--all', action='store_true', default=False, help="show packages for all available tags" ) subparser.add_argument( 'tag', nargs='*', help="show packages with the specified tag" ) def tags(parser, args): if args.all and args.tag: tty.die("Use the '--all' option OR provide tag(s) on the command line") if args.installed and not spack.environment.installed_specs(): tty.msg("No installed packages") return available_tags = sorted(spack.repo.path.tag_index.keys()) if not available_tags: tty.msg("No tagged packages") return show_packages = args.tag or args.all if not show_packages: if not args.installed: report_tags("available", available_tags) else: tag_pkgs = spack.tag.packages_with_tags(available_tags, True, True) tags = tag_pkgs.keys() if tag_pkgs else [] report_tags("installed", tags) return buffer = six.StringIO() isatty = sys.stdout.isatty() tags = args.tag if args.tag else available_tags tag_pkgs = spack.tag.packages_with_tags(tags, args.installed, False) missing = 'No installed packages' if args.installed else 'None' for tag in sorted(tag_pkgs): # TODO: tag cache since it can accumulate duplicates. packages = sorted(list(set(tag_pkgs[tag]))) if isatty: buffer.write("{0}:\n".format(tag)) if packages: colify.colify(packages, output=buffer, tty=isatty, indent=4) else: buffer.write(" {0}\n".format(missing)) buffer.write("\n") print(buffer.getvalue())

true

f7189f8dd6f26d34536254222d1b19d45d633d5e

602

py

Python

ss/leads/migrations/0003_lead_owner.py

nishendra3/task_managent_tool

e228213df2c5d22e014e5efd8c7e1011160cf3ef

[ "MIT" ]

null

ss/leads/migrations/0003_lead_owner.py

nishendra3/task_managent_tool

e228213df2c5d22e014e5efd8c7e1011160cf3ef

[ "MIT" ]

null

ss/leads/migrations/0003_lead_owner.py

nishendra3/task_managent_tool

e228213df2c5d22e014e5efd8c7e1011160cf3ef

[ "MIT" ]

null

# Generated by Django 3.2 on 2021-04-26 09:28 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('leads', '0002_rename_leads_lead'), ] operations = [ migrations.AddField( model_name='lead', name='owner', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, related_name='leads', to=settings.AUTH_USER_MODEL), ), ]

27.363636

143

0.677741

from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('leads', '0002_rename_leads_lead'), ] operations = [ migrations.AddField( model_name='lead', name='owner', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, related_name='leads', to=settings.AUTH_USER_MODEL), ), ]

true

f718a013ca7dbd568d075d456a25634b7ca18e7d

615

py

Python

setup.py

tavyc/lockex

e6b8d5440b21b08899785f7d97803b5b4ed16ab4

[ "BSD-3-Clause" ]

null

setup.py

tavyc/lockex

e6b8d5440b21b08899785f7d97803b5b4ed16ab4

[ "BSD-3-Clause" ]

null

setup.py

tavyc/lockex

e6b8d5440b21b08899785f7d97803b5b4ed16ab4

[ "BSD-3-Clause" ]

null

from setuptools import setup, find_packages setup(name="lockex", version="0.3", description="Get lock from zookeeper and execute", packages=find_packages(exclude=["__pycache__"]), install_requires=['click==7.1.1', 'python_gflags==3.1.2', 'kazoo==2.8.0', 'pure-sasl==0.6.2', 'psutil==5.7.0', 'future==0.18.2'], setup_requires=['flake8==2.5.4'], tests_require=['tox==2.3.1', 'pytest==2.6.3', 'testfixtures==4.9.1', 'mock==1.0.1'], entry_points={'console_scripts': ['lockex = lockex.execute:execute']}, extras_require=dict(test=['testfixtures'],), license='BSD',)

51.25

135

0.634146

from setuptools import setup, find_packages setup(name="lockex", version="0.3", description="Get lock from zookeeper and execute", packages=find_packages(exclude=["__pycache__"]), install_requires=['click==7.1.1', 'python_gflags==3.1.2', 'kazoo==2.8.0', 'pure-sasl==0.6.2', 'psutil==5.7.0', 'future==0.18.2'], setup_requires=['flake8==2.5.4'], tests_require=['tox==2.3.1', 'pytest==2.6.3', 'testfixtures==4.9.1', 'mock==1.0.1'], entry_points={'console_scripts': ['lockex = lockex.execute:execute']}, extras_require=dict(test=['testfixtures'],), license='BSD',)

true

f718a027b0346912471874053f7c8deab0ce9e6d

3,017

py

Python

test/unit_tests/providers/test_vimeo.py

ourresearch/total-impact-webapp

ab0d011dc783491bc85aadc2dc9c0f204e59429e

[ "MIT" ]

4

2015-10-22T10:11:01.000Z

2017-06-04T18:08:28.000Z

test/unit_tests/providers/test_vimeo.py

Impactstory/total-impact-webapp

ab0d011dc783491bc85aadc2dc9c0f204e59429e

[ "MIT" ]

2

2015-01-11T05:45:59.000Z

2015-02-11T20:37:05.000Z

test/unit_tests/providers/test_vimeo.py

Impactstory/total-impact-webapp

ab0d011dc783491bc85aadc2dc9c0f204e59429e

[ "MIT" ]

3

2015-01-10T03:23:13.000Z

2015-10-11T15:49:41.000Z

from test.unit_tests.providers import common from test.unit_tests.providers.common import ProviderTestCase from totalimpact.providers.provider import Provider, ProviderContentMalformedError from test.utils import http import os import collections from nose.tools import assert_equals, assert_items_equal, raises, nottest datadir = os.path.join(os.path.split(__file__)[0], "../../../extras/sample_provider_pages/vimeo") SAMPLE_EXTRACT_METRICS_PAGE = os.path.join(datadir, "metrics") SAMPLE_EXTRACT_BIBLIO_PAGE = os.path.join(datadir, "biblio") class TestVimeo(ProviderTestCase): provider_name = "vimeo" testitem_aliases = ("url", "http://vimeo.com/48605764") testitem_metrics = ("url", "http://vimeo.com/48605764") testitem_biblio = ("url", "http://vimeo.com/48605764") def setUp(self): ProviderTestCase.setUp(self) def test_is_relevant_alias(self): # ensure that it matches an appropriate ids assert_equals(self.provider.is_relevant_alias(self.testitem_aliases), True) assert_equals(self.provider.is_relevant_alias(("url", "NOT A VIMEO ID")), False) def test_extract_metrics_success(self): f = open(SAMPLE_EXTRACT_METRICS_PAGE, "r") metrics_dict = self.provider._extract_metrics(f.read(), id=self.testitem_metrics[1]) print metrics_dict assert_equals(metrics_dict["vimeo:plays"], 83) def test_extract_biblio_success(self): f = open(SAMPLE_EXTRACT_BIBLIO_PAGE, "r") biblio_dict = self.provider._extract_biblio(f.read(), self.testitem_biblio[1]) print biblio_dict expected = {'repository': 'Vimeo', 'title': 'Wheat Rust Inoculation Protocol Video', 'url': 'http://vimeo.com/48605764', 'year': '2012', 'authors': 'Huang Lab', 'published_date': '2012-08-31 12:20:16'} assert_equals(biblio_dict, expected) def test_provenance_url(self): provenance_url = self.provider.provenance_url("github:forks", [self.testitem_aliases]) assert_equals(provenance_url, 'http://vimeo.com/48605764') @http def test_metrics(self): metrics_dict = self.provider.metrics([self.testitem_metrics]) print metrics_dict expected = {'vimeo:plays': (83, 'http://vimeo.com/48605764')} for key in expected: assert metrics_dict[key][0] >= expected[key][0], [key, metrics_dict[key], expected[key]] assert metrics_dict[key][1] == expected[key][1], [key, metrics_dict[key], expected[key]] @http def test_biblio(self): biblio_dict = self.provider.biblio([self.testitem_biblio]) print biblio_dict expected = {'repository': 'Vimeo', 'title': u'Wheat Rust Inoculation Protocol Video', 'url': u'http://vimeo.com/48605764', 'year': u'2012', 'authors': u'Huang Lab', 'published_date': u'2012-08-31 12:20:16'} assert_items_equal(biblio_dict.keys(), expected.keys()) for key in ['year', 'published_date', 'title', 'url']: assert_equals(biblio_dict[key], expected[key])

46.415385

214

0.69705

from test.unit_tests.providers import common from test.unit_tests.providers.common import ProviderTestCase from totalimpact.providers.provider import Provider, ProviderContentMalformedError from test.utils import http import os import collections from nose.tools import assert_equals, assert_items_equal, raises, nottest datadir = os.path.join(os.path.split(__file__)[0], "../../../extras/sample_provider_pages/vimeo") SAMPLE_EXTRACT_METRICS_PAGE = os.path.join(datadir, "metrics") SAMPLE_EXTRACT_BIBLIO_PAGE = os.path.join(datadir, "biblio") class TestVimeo(ProviderTestCase): provider_name = "vimeo" testitem_aliases = ("url", "http://vimeo.com/48605764") testitem_metrics = ("url", "http://vimeo.com/48605764") testitem_biblio = ("url", "http://vimeo.com/48605764") def setUp(self): ProviderTestCase.setUp(self) def test_is_relevant_alias(self): assert_equals(self.provider.is_relevant_alias(self.testitem_aliases), True) assert_equals(self.provider.is_relevant_alias(("url", "NOT A VIMEO ID")), False) def test_extract_metrics_success(self): f = open(SAMPLE_EXTRACT_METRICS_PAGE, "r") metrics_dict = self.provider._extract_metrics(f.read(), id=self.testitem_metrics[1]) print metrics_dict assert_equals(metrics_dict["vimeo:plays"], 83) def test_extract_biblio_success(self): f = open(SAMPLE_EXTRACT_BIBLIO_PAGE, "r") biblio_dict = self.provider._extract_biblio(f.read(), self.testitem_biblio[1]) print biblio_dict expected = {'repository': 'Vimeo', 'title': 'Wheat Rust Inoculation Protocol Video', 'url': 'http://vimeo.com/48605764', 'year': '2012', 'authors': 'Huang Lab', 'published_date': '2012-08-31 12:20:16'} assert_equals(biblio_dict, expected) def test_provenance_url(self): provenance_url = self.provider.provenance_url("github:forks", [self.testitem_aliases]) assert_equals(provenance_url, 'http://vimeo.com/48605764') @http def test_metrics(self): metrics_dict = self.provider.metrics([self.testitem_metrics]) print metrics_dict expected = {'vimeo:plays': (83, 'http://vimeo.com/48605764')} for key in expected: assert metrics_dict[key][0] >= expected[key][0], [key, metrics_dict[key], expected[key]] assert metrics_dict[key][1] == expected[key][1], [key, metrics_dict[key], expected[key]] @http def test_biblio(self): biblio_dict = self.provider.biblio([self.testitem_biblio]) print biblio_dict expected = {'repository': 'Vimeo', 'title': u'Wheat Rust Inoculation Protocol Video', 'url': u'http://vimeo.com/48605764', 'year': u'2012', 'authors': u'Huang Lab', 'published_date': u'2012-08-31 12:20:16'} assert_items_equal(biblio_dict.keys(), expected.keys()) for key in ['year', 'published_date', 'title', 'url']: assert_equals(biblio_dict[key], expected[key])

false

true

f718a0367b4270d581488b88bdf48bcb02c744fd

3,379

py

Python

pychron/core/ui/qt/color_map_bar_editor.py

ael-noblegas/pychron

6ebbbb1f66a614972b62b7a9be4c784ae61b5d62

[ "Apache-2.0" ]

1

2019-02-27T21:57:44.000Z

pychron/core/ui/qt/color_map_bar_editor.py

ael-noblegas/pychron

6ebbbb1f66a614972b62b7a9be4c784ae61b5d62

[ "Apache-2.0" ]

80

2018-07-17T20:10:20.000Z

2021-08-17T15:38:24.000Z

pychron/core/ui/qt/color_map_bar_editor.py

AGESLDEO/pychron

1a81e05d9fba43b797f335ceff6837c016633bcf

[ "Apache-2.0" ]

null

# =============================================================================== # Copyright 2012 Jake Ross # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # =============================================================================== # ============= enthought library imports ======================= from __future__ import absolute_import from chaco.data_range_1d import DataRange1D from chaco.default_colormaps import color_map_dict, color_map_name_dict from pyface.qt.QtGui import QPainter, QColor, QFrame from traits.api import Float, Int, Str from traitsui.basic_editor_factory import BasicEditorFactory from traitsui.qt4.editor import Editor from numpy import array # ============= local library imports ========================== # from matplotlib.cm import get_cmap class Bar(QFrame): value = None low = 0 high = 1 color_scalar = 1 colormap = 'jet' bar_width = 100 scale = 'power' # def __init__(self, parent, ident=-1): # super(Bar, self).__init__() # self._cmap = get_cmap(self.colormap) def paintEvent(self, e): qp = QPainter() qp.begin(self) qp.setBrush(QColor(*self.value)) qp.drawRect(0, 0, self.bar_width, 20) qp.end() def set_value(self, v): """ map v to users color scale use power law v=A*x**(1/cs) increase cs increases the rate of change at low values increase cs will make it easier to see small pertubations (more color change) at the low end. """ if self.scale == 'power': N = 1 / float(self.color_scalar) A = 1 / self.high ** N nv = A * v ** N else: nv = min(1, max(0, (v - self.low) / (self.high - self.low))) vs = self.cmap.map_screen(array([nv,]))[0][:3] self.value = [x * 255 for x in vs] self.update() class _BarGaugeEditor(Editor): def init(self, parent): self.control = Bar() self.control.low = low = self.factory.low self.control.high = high = self.factory.high self.control.color_scalar = self.factory.color_scalar self.control.bar_width = self.factory.width self.control.scale = self.factory.scale # if self.factory.scale == 'power': # high = N = 1 / float(self.color_scalar) # A = 1 / self.high ** N self.control.cmap = color_map_name_dict[self.factory.colormap](DataRange1D(low_setting=0, high_setting=1)) def update_editor(self): if self.control: self.control.set_value(self.value) class BarGaugeEditor(BasicEditorFactory): klass = _BarGaugeEditor low = Float high = Float color_scalar = Int(1) scale = Str('power') colormap = Str('jet') width = Int(100) # ============= EOF =============================================

33.455446

114

0.587452

from __future__ import absolute_import from chaco.data_range_1d import DataRange1D from chaco.default_colormaps import color_map_dict, color_map_name_dict from pyface.qt.QtGui import QPainter, QColor, QFrame from traits.api import Float, Int, Str from traitsui.basic_editor_factory import BasicEditorFactory from traitsui.qt4.editor import Editor from numpy import array class Bar(QFrame): value = None low = 0 high = 1 color_scalar = 1 colormap = 'jet' bar_width = 100 scale = 'power' def paintEvent(self, e): qp = QPainter() qp.begin(self) qp.setBrush(QColor(*self.value)) qp.drawRect(0, 0, self.bar_width, 20) qp.end() def set_value(self, v): if self.scale == 'power': N = 1 / float(self.color_scalar) A = 1 / self.high ** N nv = A * v ** N else: nv = min(1, max(0, (v - self.low) / (self.high - self.low))) vs = self.cmap.map_screen(array([nv,]))[0][:3] self.value = [x * 255 for x in vs] self.update() class _BarGaugeEditor(Editor): def init(self, parent): self.control = Bar() self.control.low = low = self.factory.low self.control.high = high = self.factory.high self.control.color_scalar = self.factory.color_scalar self.control.bar_width = self.factory.width self.control.scale = self.factory.scale self.control.cmap = color_map_name_dict[self.factory.colormap](DataRange1D(low_setting=0, high_setting=1)) def update_editor(self): if self.control: self.control.set_value(self.value) class BarGaugeEditor(BasicEditorFactory): klass = _BarGaugeEditor low = Float high = Float color_scalar = Int(1) scale = Str('power') colormap = Str('jet') width = Int(100)

true

f718a03a93d543af426ee374eecee7750397b95b

8,579

py

Python

public/code/simpleCropPredictSpektogram.py

awinawin1/prediksi

b3d552555f775d7b6a1b22077146443fe09bbf5d

[ "MIT" ]

null

public/code/simpleCropPredictSpektogram.py

awinawin1/prediksi

b3d552555f775d7b6a1b22077146443fe09bbf5d

[ "MIT" ]

null

public/code/simpleCropPredictSpektogram.py

awinawin1/prediksi

b3d552555f775d7b6a1b22077146443fe09bbf5d

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Sat May 15 00:21:05 2021 @author: marina """ import os import shutil import pyedflib import numpy as np import pandas as pd import sys import mne from pywt import wavedec from sklearn.preprocessing import LabelEncoder import matplotlib.pyplot as plt from scipy import signal from keras.models import Sequential #importing layers from keras.layers import Conv2D,Flatten,Dense,MaxPooling2D from tensorflow.keras.optimizers import SGD # pathDataSet = "D:\\Kuliah\Tugas Akhir\chb-mit-scalp-eeg-database-1.0.0\\chb07\\" pathDataSet = "/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/uploadedSpektogram/" pathSaveData = "/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/uploadedSpektogram/spektogram/" def data_load(FILE, selected_channels=[]): fullNm = pathDataSet + FILE # fullNm = FILE f = pyedflib.EdfReader(fullNm ) n = f.signals_in_file signal_labels = f.getSignalLabels() channel_freq = f.getSampleFrequencies() sigbufs = np.zeros((n, f.getNSamples()[0])) for i in np.arange(n): sigbufs[i, :] = f.readSignal(i) f.close() # and load the data into a DataFrame df_signals = pd.DataFrame(sigbufs) df_signals = df_signals.transpose() df_signals.columns = signal_labels df_signals = df_signals.loc[:,~df_signals.columns.duplicated()] df_signals = df_signals[selected_channels].astype('float32') return df_signals,channel_freq[0] def mne_object(data, freq, events = None): info = mne.create_info(ch_names=list(data.columns), sfreq=freq, ch_types=['eeg']*data.shape[-1]) data_T = data.transpose() raw = mne.io.RawArray(data_T, info,verbose=False) if events: start_times = np.array(events[::2]) end_times = np.array(events[1::2]) anno_length = end_times-start_times event_name = np.array(['Ictal']*len(anno_length)) raw.set_annotations(mne.Annotations(start_times, anno_length, event_name)) return raw def loadAndFiltering(FILE,channel_keeps): raw_data, freq = data_load(FILE, channel_keeps) if len(raw_data) ==0: print("no data ") return raw_data mne_data = mne_object(raw_data, freq) raw=mne_data.copy() return raw def extract_windows(array, start, max_time, sub_window_size, stride_size): sub_windows = ( start + np.expand_dims(np.arange(sub_window_size), 0) + np.expand_dims(np.arange(max_time + 1- sub_window_size-start, step=stride_size), 0).T ) return array[:,sub_windows] def Crop(raw): cropS = 3 strides = 1 tMin=0 tMax=raw.get_data().shape[1]#18*256*cropS sub_window_size,stride_size = 256*cropS,256*strides cropData = extract_windows(raw.get_data(), tMin, tMax , sub_window_size,stride_size) cropData = cropData.reshape(cropData.shape[1],cropData.shape[0],cropData.shape[2]) return cropData # def create_modelCNN(input_shape, num_class,flatten=False): # from tensorflow.keras.models import Sequential # from tensorflow.keras.layers import Dense # from tensorflow.keras.backend import clear_session # from tensorflow.keras.optimizers import Adam # from tensorflow.keras.layers import Conv1D#, Input # from tensorflow.keras.layers import MaxPooling1D # from tensorflow.keras.layers import GlobalAveragePooling1D#, GlobalMaxPooling1D # from keras.layers import Activation,Flatten, Dropout # clear_session() # model = Sequential() # def add_conv_block(model, num_filters, input_shape=None): # if input_shape: # model.add(Conv1D(num_filters, kernel_size=3, activation='relu', padding='same', input_shape=input_shape)) # else: # model.add(Conv1D(num_filters, kernel_size=3, activation='relu', padding='same')) # return model # model = add_conv_block(model, 128, input_shape=input_shape[1:]) # model = add_conv_block(model, 128) # model.add(Dropout(0.3)) # model.add(MaxPooling1D(pool_size=3, # size of the window # strides=2, # factor to downsample # padding='same')) # model.add(Dropout(0.1)) # for i in range(2): # model.add(Conv1D(filters=256,kernel_size=3,padding="same",activation='relu')) # model.add(Dropout(0.1)) # if flatten: # model.add(Flatten()) # else: # model.add(GlobalAveragePooling1D()) # model.add(Dense(units=128,activation='relu')) # model.add(Dropout(0.1)) # model.add(Dense(num_class)) # model.add(Activation('softmax')) # model.compile(optimizer=Adam(0.0001), # loss='categorical_crossentropy', # metrics=['accuracy']) # return model def modelCNN2(input_shape,nb_classes): model = Sequential() model.add(Conv2D(32, (3, 3), activation='relu', padding='same', input_shape=input_shape)) model.add(Conv2D(32, (3, 3), activation='relu', padding='same')) model.add(MaxPooling2D((2, 2))) model.add(Conv2D(64, (3, 3), activation='relu', padding='same')) model.add(Conv2D(64, (3, 3), activation='relu', padding='same')) model.add(MaxPooling2D((2, 2))) model.add(Conv2D(128, (3, 3), activation='relu', padding='same')) model.add(Conv2D(128, (3, 3), activation='relu', padding='same')) model.add(MaxPooling2D((2, 2))) model.add(Flatten()) model.add(Dense(128, activation='relu')) model.add(Dense(nb_classes, activation='softmax')) # compile model opt = SGD(lr=0.001, momentum=0.9) model.compile(optimizer=opt, loss='categorical_crossentropy', metrics=['accuracy']) return model def plotSpektogram(x,fs,nmFile=''): f, t, Sxx = signal.spectrogram(x, fs) cut=10 imgAll=[] for i,sinyal in enumerate(Sxx): img = plt.pcolormesh(t, f[:cut], sinyal[:cut], shading='gouraud') imgAll.append([(r, g, b) for r, g, b, a in img.to_rgba(img.get_array())]) # print(nmFile) # if nmFile !='': #(18, 30, 3) # print("masuk sini") # plt.savefig(nmFile) # plt.show() # plt.imsave(nmFile, imgAll) # imgAll = np.array(imgAll)# .reshape(-1,3) imgAll = np.array(imgAll).ravel() #(18, 30, 3) return imgAll if __name__ == '__main__': FILE=sys.argv[1] # FILE = 'D:\\Kuliah\Tugas Akhir\chb-mit-scalp-eeg-database-1.0.0\\chb24\\chb24_22.edf' # FILE = 'chb07_12.edf' FILE = FILE.replace("'","") dir_path = "/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/fitur3Kelas30DetikImg/" # if(os.path.isdir(dir_path+FILE)): # shutil.rmtree(dir_path+FILE) # os.mkdir("/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/fitur3Kelas30DetikImg/"+FILE,0o777) loaded = np.load("/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/spektogram/channel_keeps.npz") selected_channels =loaded['channel_keeps'] segmen=[] raw = loadAndFiltering(FILE,selected_channels) cropData = Crop(raw) numCH = cropData[0].shape[0] oneData = cropData[0] oneData = plotSpektogram(oneData,256) oneData = oneData.reshape(1,numCH,-1, 3) KELAS = 3 bntk_input = (18, 30, 3) model = modelCNN2(bntk_input,KELAS) # model = modelCNN2(oneData.shape,KELAS)#,False) nmModel = '/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/modelCNNSpektrogram_3.h5' model.load_weights(nmModel) cnt=0 for idx in range(cropData.shape[0]): numCH = cropData[idx].shape[0] oneData = cropData[idx] nmFile = "/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/fitur3Kelas30DetikImg/%s/%s_%d.png"%(FILE,FILE,idx) # nmFile = dir+"%s_%s.png"%(FILE,idx) oneData = plotSpektogram(oneData,256,nmFile) oneData = oneData.reshape(1,numCH,-1, 3) yPred = model.predict(oneData) yPred = np.argmax(yPred,axis=1) if yPred[0] == 0: hasil = "Normal" elif yPred[0] == 1: hasil = "Inter" else: hasil = "Ictal" # break segmen.append(hasil) # print("segment=%d prediksi=%s <br>"%(idx,hasil)) cnt+=1 if cnt>1000: break saveHistory = open(pathSaveData+FILE+".txt","w") saveHistory.write(str(segmen)) saveHistory.close() print(segmen)

36.198312

136

0.645879

import os import shutil import pyedflib import numpy as np import pandas as pd import sys import mne from pywt import wavedec from sklearn.preprocessing import LabelEncoder import matplotlib.pyplot as plt from scipy import signal from keras.models import Sequential from keras.layers import Conv2D,Flatten,Dense,MaxPooling2D from tensorflow.keras.optimizers import SGD pathDataSet = "/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/uploadedSpektogram/" pathSaveData = "/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/uploadedSpektogram/spektogram/" def data_load(FILE, selected_channels=[]): fullNm = pathDataSet + FILE f = pyedflib.EdfReader(fullNm ) n = f.signals_in_file signal_labels = f.getSignalLabels() channel_freq = f.getSampleFrequencies() sigbufs = np.zeros((n, f.getNSamples()[0])) for i in np.arange(n): sigbufs[i, :] = f.readSignal(i) f.close() df_signals = pd.DataFrame(sigbufs) df_signals = df_signals.transpose() df_signals.columns = signal_labels df_signals = df_signals.loc[:,~df_signals.columns.duplicated()] df_signals = df_signals[selected_channels].astype('float32') return df_signals,channel_freq[0] def mne_object(data, freq, events = None): info = mne.create_info(ch_names=list(data.columns), sfreq=freq, ch_types=['eeg']*data.shape[-1]) data_T = data.transpose() raw = mne.io.RawArray(data_T, info,verbose=False) if events: start_times = np.array(events[::2]) end_times = np.array(events[1::2]) anno_length = end_times-start_times event_name = np.array(['Ictal']*len(anno_length)) raw.set_annotations(mne.Annotations(start_times, anno_length, event_name)) return raw def loadAndFiltering(FILE,channel_keeps): raw_data, freq = data_load(FILE, channel_keeps) if len(raw_data) ==0: print("no data ") return raw_data mne_data = mne_object(raw_data, freq) raw=mne_data.copy() return raw def extract_windows(array, start, max_time, sub_window_size, stride_size): sub_windows = ( start + np.expand_dims(np.arange(sub_window_size), 0) + np.expand_dims(np.arange(max_time + 1- sub_window_size-start, step=stride_size), 0).T ) return array[:,sub_windows] def Crop(raw): cropS = 3 strides = 1 tMin=0 tMax=raw.get_data().shape[1] sub_window_size,stride_size = 256*cropS,256*strides cropData = extract_windows(raw.get_data(), tMin, tMax , sub_window_size,stride_size) cropData = cropData.reshape(cropData.shape[1],cropData.shape[0],cropData.shape[2]) return cropData asses): model = Sequential() model.add(Conv2D(32, (3, 3), activation='relu', padding='same', input_shape=input_shape)) model.add(Conv2D(32, (3, 3), activation='relu', padding='same')) model.add(MaxPooling2D((2, 2))) model.add(Conv2D(64, (3, 3), activation='relu', padding='same')) model.add(Conv2D(64, (3, 3), activation='relu', padding='same')) model.add(MaxPooling2D((2, 2))) model.add(Conv2D(128, (3, 3), activation='relu', padding='same')) model.add(Conv2D(128, (3, 3), activation='relu', padding='same')) model.add(MaxPooling2D((2, 2))) model.add(Flatten()) model.add(Dense(128, activation='relu')) model.add(Dense(nb_classes, activation='softmax')) opt = SGD(lr=0.001, momentum=0.9) model.compile(optimizer=opt, loss='categorical_crossentropy', metrics=['accuracy']) return model def plotSpektogram(x,fs,nmFile=''): f, t, Sxx = signal.spectrogram(x, fs) cut=10 imgAll=[] for i,sinyal in enumerate(Sxx): img = plt.pcolormesh(t, f[:cut], sinyal[:cut], shading='gouraud') imgAll.append([(r, g, b) for r, g, b, a in img.to_rgba(img.get_array())]) .array(imgAll).ravel() return imgAll if __name__ == '__main__': FILE=sys.argv[1] FILE = FILE.replace("'","") dir_path = "/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/fitur3Kelas30DetikImg/" # if(os.path.isdir(dir_path+FILE)): # shutil.rmtree(dir_path+FILE) # os.mkdir("/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/fitur3Kelas30DetikImg/"+FILE,0o777) loaded = np.load("/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/spektogram/channel_keeps.npz") selected_channels =loaded['channel_keeps'] segmen=[] raw = loadAndFiltering(FILE,selected_channels) cropData = Crop(raw) numCH = cropData[0].shape[0] oneData = cropData[0] oneData = plotSpektogram(oneData,256) oneData = oneData.reshape(1,numCH,-1, 3) KELAS = 3 bntk_input = (18, 30, 3) model = modelCNN2(bntk_input,KELAS) # model = modelCNN2(oneData.shape,KELAS)#,False) nmModel = '/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/modelCNNSpektrogram_3.h5' model.load_weights(nmModel) cnt=0 for idx in range(cropData.shape[0]): numCH = cropData[idx].shape[0] oneData = cropData[idx] nmFile = "/Applications/XAMPP/xamppfiles/htdocs/prediksi/storage/app/public/fitur3Kelas30DetikImg/%s/%s_%d.png"%(FILE,FILE,idx) # nmFile = dir+"%s_%s.png"%(FILE,idx) oneData = plotSpektogram(oneData,256,nmFile) oneData = oneData.reshape(1,numCH,-1, 3) yPred = model.predict(oneData) yPred = np.argmax(yPred,axis=1) if yPred[0] == 0: hasil = "Normal" elif yPred[0] == 1: hasil = "Inter" else: hasil = "Ictal" # break segmen.append(hasil) # print("segment=%d prediksi=%s <br>"%(idx,hasil)) cnt+=1 if cnt>1000: break saveHistory = open(pathSaveData+FILE+".txt","w") saveHistory.write(str(segmen)) saveHistory.close() print(segmen)

true

f718a057f6fbb3615714ace7248ca6eec06c111c

713

py

Python

TPs/TP4/test_flower.py

Aympab/BigDataHadoopSparkDaskCourse

42f9e0475cbd7c5db240ccc6dc00c19b9006012a

[ "Apache-2.0" ]

null

TPs/TP4/test_flower.py

Aympab/BigDataHadoopSparkDaskCourse

42f9e0475cbd7c5db240ccc6dc00c19b9006012a

[ "Apache-2.0" ]

null

TPs/TP4/test_flower.py

Aympab/BigDataHadoopSparkDaskCourse

42f9e0475cbd7c5db240ccc6dc00c19b9006012a

[ "Apache-2.0" ]

1

2022-01-31T17:14:27.000Z

import pyspark from pyspark import SparkContext from pyspark.sql import Row from pyspark.sql import SQLContext from pyspark import SparkFiles import os import pandas as pd sc =SparkContext() sqlContext = SQLContext(sc) data_dir="/work/irlin355_1/gratienj/ParallelProgrammingCourse/BigDataHadoopSpark/data" file = os.path.join(data_dir,"iris.csv") panda_df = pd.read_csv(file) sqlContext = SQLContext(sc) #df = sqlContext.read.csv(SparkFiles.get("iris.csv"), header=True, inferSchema= True) df=sqlContext.createDataFrame(panda_df) df.printSchema() df.show(5, truncate = False) df.select('petal_width','variety').show(5) df.groupBy("variety").count().sort("count",ascending=True).show() df.describe().show()

26.407407

86

0.779804

import pyspark from pyspark import SparkContext from pyspark.sql import Row from pyspark.sql import SQLContext from pyspark import SparkFiles import os import pandas as pd sc =SparkContext() sqlContext = SQLContext(sc) data_dir="/work/irlin355_1/gratienj/ParallelProgrammingCourse/BigDataHadoopSpark/data" file = os.path.join(data_dir,"iris.csv") panda_df = pd.read_csv(file) sqlContext = SQLContext(sc) df=sqlContext.createDataFrame(panda_df) df.printSchema() df.show(5, truncate = False) df.select('petal_width','variety').show(5) df.groupBy("variety").count().sort("count",ascending=True).show() df.describe().show()

true

f718a2b72257a97c4d973393e72a8863d380eada

3,752

py

Python

tests/gallery/test_raster_transform.py

krisHans3n/geoalchemy2-mysql

38a44d51c242d867f40d4c5503c91f52a8269ff4

[ "MIT" ]

null

tests/gallery/test_raster_transform.py

krisHans3n/geoalchemy2-mysql

38a44d51c242d867f40d4c5503c91f52a8269ff4

[ "MIT" ]

null

tests/gallery/test_raster_transform.py

krisHans3n/geoalchemy2-mysql

38a44d51c242d867f40d4c5503c91f52a8269ff4

[ "MIT" ]

null

""" Reproject a Raster using ST_Transform ===================================== The `ST_Transform()` function (and a few others like `ST_SnapToGrid()`) can be used on both `Geometry` and `Raster` types. In `GeoAlchemy2`, this function is only defined for `Geometry` as it can not be defined for several types at the same time. Thus using this function on `Raster` requires minor tweaking. This example uses both SQLAlchemy core and ORM queries. """ from sqlalchemy import Column from sqlalchemy import Integer from sqlalchemy import MetaData from sqlalchemy import Table from sqlalchemy import func from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import Query from geoalchemy2 import Geometry from geoalchemy2 import Raster # Tests imports from tests import select metadata = MetaData() Base = declarative_base(metadata=metadata) table = Table( "raster_table", metadata, Column("id", Integer, primary_key=True), Column("geom", Geometry("POLYGON", 4326)), Column("rast", Raster()), ) class RasterTable(Base): __tablename__ = 'raster_table_orm' id = Column(Integer, primary_key=True) geom = Column(Geometry("POLYGON", 4326)) rast = Column(Raster()) def __init__(self, rast): self.rast = rast def test_transform_core(): # Define the transform query for both the geometry and the raster in a naive way wrong_query = select([ func.ST_Transform(table.c.geom, 2154), func.ST_Transform(table.c.rast, 2154) ]) # Check the query assert str(wrong_query) == ( "SELECT " "ST_AsEWKB(" "ST_Transform(raster_table.geom, :ST_Transform_2)) AS \"ST_Transform_1\", " "ST_AsEWKB(" # <= Note that the raster is processed as a Geometry here "ST_Transform(raster_table.rast, :ST_Transform_4)) AS \"ST_Transform_3\" \n" "FROM raster_table" ) # Define the transform query for both the geometry and the raster in the correct way correct_query = select([ func.ST_Transform(table.c.geom, 2154), func.ST_Transform(table.c.rast, 2154, type_=Raster) ]) # Check the query assert str(correct_query) == ( "SELECT " "ST_AsEWKB(" "ST_Transform(raster_table.geom, :ST_Transform_2)) AS \"ST_Transform_1\", " "raster(" # <= This time the raster is correctly processed as a Raster "ST_Transform(raster_table.rast, :ST_Transform_4)) AS \"ST_Transform_3\" \n" "FROM raster_table" ) def test_transform_ORM(): # Define the transform query for both the geometry and the raster in a naive way wrong_query = Query([ RasterTable.geom.ST_Transform(2154), RasterTable.rast.ST_Transform(2154) ]) # Check the query assert str(wrong_query) == ( "SELECT " "ST_AsEWKB(" "ST_Transform(raster_table_orm.geom, :ST_Transform_2)) AS \"ST_Transform_1\", " "ST_AsEWKB(" # <= Note that the raster is processed as a Geometry here "ST_Transform(raster_table_orm.rast, :ST_Transform_4)) AS \"ST_Transform_3\" \n" "FROM raster_table_orm" ) # Define the transform query for both the geometry and the raster in the correct way correct_query = Query([ RasterTable.geom.ST_Transform(2154), RasterTable.rast.ST_Transform(2154, type_=Raster) ]) # Check the query assert str(correct_query) == ( "SELECT " "ST_AsEWKB(" "ST_Transform(raster_table_orm.geom, :ST_Transform_2)) AS \"ST_Transform_1\", " "raster(" # <= This time the raster is correctly processed as a Raster "ST_Transform(raster_table_orm.rast, :ST_Transform_4)) AS \"ST_Transform_3\" \n" "FROM raster_table_orm" )

32.912281

88

0.673507

from sqlalchemy import Column from sqlalchemy import Integer from sqlalchemy import MetaData from sqlalchemy import Table from sqlalchemy import func from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import Query from geoalchemy2 import Geometry from geoalchemy2 import Raster from tests import select metadata = MetaData() Base = declarative_base(metadata=metadata) table = Table( "raster_table", metadata, Column("id", Integer, primary_key=True), Column("geom", Geometry("POLYGON", 4326)), Column("rast", Raster()), ) class RasterTable(Base): __tablename__ = 'raster_table_orm' id = Column(Integer, primary_key=True) geom = Column(Geometry("POLYGON", 4326)) rast = Column(Raster()) def __init__(self, rast): self.rast = rast def test_transform_core(): wrong_query = select([ func.ST_Transform(table.c.geom, 2154), func.ST_Transform(table.c.rast, 2154) ]) assert str(wrong_query) == ( "SELECT " "ST_AsEWKB(" "ST_Transform(raster_table.geom, :ST_Transform_2)) AS \"ST_Transform_1\", " "ST_AsEWKB(" "ST_Transform(raster_table.rast, :ST_Transform_4)) AS \"ST_Transform_3\" \n" "FROM raster_table" ) correct_query = select([ func.ST_Transform(table.c.geom, 2154), func.ST_Transform(table.c.rast, 2154, type_=Raster) ]) assert str(correct_query) == ( "SELECT " "ST_AsEWKB(" "ST_Transform(raster_table.geom, :ST_Transform_2)) AS \"ST_Transform_1\", " "raster(" "ST_Transform(raster_table.rast, :ST_Transform_4)) AS \"ST_Transform_3\" \n" "FROM raster_table" ) def test_transform_ORM(): wrong_query = Query([ RasterTable.geom.ST_Transform(2154), RasterTable.rast.ST_Transform(2154) ]) assert str(wrong_query) == ( "SELECT " "ST_AsEWKB(" "ST_Transform(raster_table_orm.geom, :ST_Transform_2)) AS \"ST_Transform_1\", " "ST_AsEWKB(" "ST_Transform(raster_table_orm.rast, :ST_Transform_4)) AS \"ST_Transform_3\" \n" "FROM raster_table_orm" ) correct_query = Query([ RasterTable.geom.ST_Transform(2154), RasterTable.rast.ST_Transform(2154, type_=Raster) ]) assert str(correct_query) == ( "SELECT " "ST_AsEWKB(" "ST_Transform(raster_table_orm.geom, :ST_Transform_2)) AS \"ST_Transform_1\", " "raster(" "ST_Transform(raster_table_orm.rast, :ST_Transform_4)) AS \"ST_Transform_3\" \n" "FROM raster_table_orm" )

true

f718a32adc8e23215976b6874f7a9baff2ac6fb1

2,262

py

Python

acme/agents/actors_tf2_test.py

owenshen24/acme

71434dffd3449236f9b8aaf7a53ceab515e75a2a

[ "Apache-2.0" ]

1

2020-06-03T18:33:40.000Z

acme/agents/actors_tf2_test.py

owenshen24/acme

71434dffd3449236f9b8aaf7a53ceab515e75a2a

[ "Apache-2.0" ]

null

acme/agents/actors_tf2_test.py

owenshen24/acme

71434dffd3449236f9b8aaf7a53ceab515e75a2a

[ "Apache-2.0" ]

1

2021-11-26T22:51:55.000Z

# python3 # Copyright 2018 DeepMind Technologies Limited. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for actors_tf2.""" from absl.testing import absltest from acme import environment_loop from acme import specs from acme.agents import actors_tf2 from acme.testing import fakes import dm_env import numpy as np import sonnet as snt import tensorflow as tf def _make_fake_env() -> dm_env.Environment: env_spec = specs.EnvironmentSpec( observations=specs.Array(shape=(10, 5), dtype=np.float32), actions=specs.DiscreteArray(num_values=3), rewards=specs.Array(shape=(), dtype=np.float32), discounts=specs.BoundedArray( shape=(), dtype=np.float32, minimum=0., maximum=1.), ) return fakes.Environment(env_spec, episode_length=10) class ActorTest(absltest.TestCase): def test_feedforward(self): environment = _make_fake_env() env_spec = specs.make_environment_spec(environment) network = snt.Sequential([ snt.Flatten(), snt.Linear(env_spec.actions.num_values), lambda x: tf.argmax(x, axis=-1, output_type=env_spec.actions.dtype), ]) actor = actors_tf2.FeedForwardActor(network) loop = environment_loop.EnvironmentLoop(environment, actor) loop.run(20) def test_recurrent(self): environment = _make_fake_env() env_spec = specs.make_environment_spec(environment) network = snt.DeepRNN([ snt.Flatten(), snt.Linear(env_spec.actions.num_values), lambda x: tf.argmax(x, axis=-1, output_type=env_spec.actions.dtype), ]) actor = actors_tf2.RecurrentActor(network) loop = environment_loop.EnvironmentLoop(environment, actor) loop.run(20) if __name__ == '__main__': absltest.main()

30.16

76

0.728559

from absl.testing import absltest from acme import environment_loop from acme import specs from acme.agents import actors_tf2 from acme.testing import fakes import dm_env import numpy as np import sonnet as snt import tensorflow as tf def _make_fake_env() -> dm_env.Environment: env_spec = specs.EnvironmentSpec( observations=specs.Array(shape=(10, 5), dtype=np.float32), actions=specs.DiscreteArray(num_values=3), rewards=specs.Array(shape=(), dtype=np.float32), discounts=specs.BoundedArray( shape=(), dtype=np.float32, minimum=0., maximum=1.), ) return fakes.Environment(env_spec, episode_length=10) class ActorTest(absltest.TestCase): def test_feedforward(self): environment = _make_fake_env() env_spec = specs.make_environment_spec(environment) network = snt.Sequential([ snt.Flatten(), snt.Linear(env_spec.actions.num_values), lambda x: tf.argmax(x, axis=-1, output_type=env_spec.actions.dtype), ]) actor = actors_tf2.FeedForwardActor(network) loop = environment_loop.EnvironmentLoop(environment, actor) loop.run(20) def test_recurrent(self): environment = _make_fake_env() env_spec = specs.make_environment_spec(environment) network = snt.DeepRNN([ snt.Flatten(), snt.Linear(env_spec.actions.num_values), lambda x: tf.argmax(x, axis=-1, output_type=env_spec.actions.dtype), ]) actor = actors_tf2.RecurrentActor(network) loop = environment_loop.EnvironmentLoop(environment, actor) loop.run(20) if __name__ == '__main__': absltest.main()

true

f718a32e9858f3ea9274a1aadac3baae13a0a7c1

64,546

py

Python

tools/blender-dff/io_scene_dff.py

FakeYou/mashed

902d8f514872cfa22e2a2904e215d360bf48cae1

[ "MIT" ]

5

2016-12-31T13:51:31.000Z

2018-06-12T18:36:52.000Z

tools/blender-dff/io_scene_dff.py

andrenanninga/mashed

902d8f514872cfa22e2a2904e215d360bf48cae1

[ "MIT" ]

1

2021-03-26T20:53:34.000Z

tools/blender-dff/io_scene_dff.py

FakeYou/mashed

902d8f514872cfa22e2a2904e215d360bf48cae1

[ "MIT" ]

7

2016-10-08T15:38:30.000Z

2019-01-25T11:34:31.000Z

bl_info = { "name": "RenderWare importer/exporter for GTA III/VC/SA (.dff)", "author": "Ago Allikmaa (maxorator)", "version": (0, 9, 2), "blender": (2, 6, 3), "location": "File > Import-Export > Renderware (.dff) ", "description": "RenderWare importer/exporter for GTA III/VC/SA", "category": "Import-Export" } import struct import os import zlib import base64 from collections import deque import bpy import math import mathutils from bpy.props import * class RwTypes(): ANY = -1 STRUCT = 0x0001 STRING = 0x0002 EXTENSION = 0x0003 TEXTURE = 0x0006 MATERIAL = 0x0007 MATERIALLIST = 0x0008 FRAMELIST = 0x000E GEOMETRY = 0x000F CLUMP = 0x0010 ATOMIC = 0x0014 GEOMETRYLIST = 0x001A RENDERRIGHTS = 0x001F MORPHPLG = 0x0105 SKINPLG = 0x116 HANIMPLG = 0x11E MATEFFECTS = 0x0120 BINMESHPLG = 0x050E FRAMENAME = 0x253F2FE COLLISION = 0x253F2FA MATSPECULAR = 0x253F2F6 NIGHTCOLS = 0x253F2F9 MATREFLECTION = 0x253F2FC MESHEXTENSION = 0x253F2FD def decodeVersion(version): if (version & 0xFFFF0000) == 0: return version << 8 else: p1 = ((version >> 14) & 0x3FF00) + 0x30000 p2 = (version >> 16) & 0x3F return p1 | p2 class RpGeomFlag: TRISTRIP = 0x0001 POSITIONS = 0x0002 TEXTURED = 0x0004 PRELIT = 0x0008 NORMALS = 0x0010 LIGHT = 0x0020 MODULATEMATERIALCOLOR = 0x0040 TEXTURED2 = 0x0080 class ImportRenderware: class RwTriangle: def __init__(self, verts, mat): self.verts = verts self.mat = mat def desc(self): return (self.verts[0], self.verts[1], self.verts[2]) class RwVertex: def __init__(self, coords, normal): self.coords = coords self.normal = normal self.uv = None self.uv_env = None def desc(self): return (self.coords[0], self.coords[1], self.coords[2]) class RwFrame: def __init__(self, loader, index, rot, pos, parent): self.loader = loader self.index = index self.geometry = None self.atomic = None self.blobj = None self.bldata = None self.hanimdata = None self.name = None rmatrix = mathutils.Matrix.Identity(3) rmatrix[0] = rot[0], rot[1], rot[2] rmatrix[1] = rot[3], rot[4], rot[5] rmatrix[2] = rot[6], rot[7], rot[8] rmatrix.resize_4x4() rmatrix.translation = pos[0], pos[1], pos[2] self.matrix = rmatrix self.parent = parent self.loader.childrenOf[parent+1].append(self.index) def setAtomic(self, atomic): self.atomic = atomic self.geometry = atomic.geometry def build(self): if self.name is None: self.name = "noname_" + str(self.index); if self.geometry: self.bldata = self.geometry.build(self.name) self.blobj = bpy.data.objects.new(self.name, self.bldata) if self.parent >= 0: self.blobj.parent = self.loader.frames[self.parent].blobj self.blobj.matrix_local = self.matrix bpy.context.scene.objects.link(self.blobj) for frame in self.loader.childrenOf[self.index+1]: self.loader.frames[frame].build() if "_vlo" in self.name or "_dam" in self.name: self.blobj.hide = True self.blobj.hide_render = True if self.loader.colhex and self.index == self.loader.childrenOf[0][0]: textobj = bpy.data.texts.new(name = ("zrwcoll_" + self.name)) textobj.from_string(self.loader.colhex) self.blobj.collhex = textobj.name if self.hanimdata: textobj = bpy.data.texts.new(name = ("zrwhanim" + str(self.index) + "_" + self.name)) textobj.from_string(self.hanimdata) self.blobj.rw_hanimdata = textobj.name if self.geometry and self.geometry.skindata: textobj = bpy.data.texts.new(name = ("zrwskin_" + self.name)) textobj.from_string(self.geometry.skindata) self.blobj.rw_skindata = textobj.name if self.atomic and self.atomic.renderPlugin != None and self.atomic.renderExtra != None: self.blobj.renderright = self.atomic.renderPlugin self.blobj.renderextra = self.atomic.renderExtra if self.atomic and self.atomic.matfxpipe: self.blobj.matfxpipe = True class RpGeometry: def __init__(self, loader, index): self.loader = loader self.index = index self.vertices = [] self.triangles = [] self.materials = [] self.mesh = None self.atomic = None self.skindata = None self.hasEnvUV = False self.vertCol = None self.nightVertCol = None self.hasNormals = False def setAtomic(self, atomic): self.atomic = atomic def addMaterial(self, material): material.setIndex(len(self.materials)) self.materials.append(material) def addVertex(self, vertex): self.vertices.append(vertex) def addTriangle(self, triangle): self.triangles.append(triangle) def build(self, name): self.mesh = bpy.data.meshes.new(name) pyverts = [] pypolys = [] for vertex in self.vertices: pyverts.append(vertex.desc()) for triangle in self.triangles: pypolys.append(triangle.desc()) self.mesh.from_pydata(pyverts, [], pypolys) self.mesh.update() if self.vertCol: vcol = self.mesh.vertex_colors.new("Normal") self.mesh.vertex_colors.active = vcol for i in range(len(self.vertices)): vcol.data[i].color = (self.vertCol[i][0], self.vertCol[i][1], self.vertCol[i][2]) if self.nightVertCol: nvcol = self.mesh.vertex_colors.new("Night") self.mesh.vertex_colors.active = nvcol for i in range(len(self.vertices)): nvcol.data[i].color = (self.nightVertCol[i][0], self.nightVertCol[i][1], self.nightVertCol[i][2]) uvtexture = self.mesh.uv_textures.new() uvtexture.name = "MainUV" uvlayer = self.mesh.uv_layers[-1] for i in range(len(self.triangles)): for j in range(3): uvlayer.data[3*i + j].uv = self.vertices[self.triangles[i].verts[j]].uv if self.hasEnvUV: euvtexture = self.mesh.uv_textures.new() euvtexture.name = "EnvUV" euvlayer = self.mesh.uv_layers[-1] for i in range(len(self.triangles)): for j in range(3): euvlayer.data[3*i + j].uv = self.vertices[self.triangles[i].verts[j]].uv_env for material in self.materials: material.build() for i in range(len(self.triangles)): self.mesh.polygons[i].material_index = self.triangles[i].mat return self.mesh class RpMaterial: def __init__(self, geometry, flags=None, col=None, textured=None, ambient=None, specular=None, diffuse=None): self.index = None self.name = "g" + str(geometry.index) + "m" self.geometry = geometry self.flags = flags self.col = col self.ambient = ambient self.specular = specular self.diffuse = diffuse self.textured = textured self.texture = None self.blmat = None self.envtex = None self.readenvmap = False self.envIntensity = 1 self.reflectColour = None self.reflectIntensity = None self.spectex = None def setIndex(self, index): self.index = index self.name = "g" + str(self.geometry.index) + "m" + str(index) def setTexture(self, texture): self.texture = texture def setEnvTexture(self, texture): self.envtex = texture def setSpecTexture(self, texture): self.spectex = texture def setReflection(self, colour, intensity): self.reflectColour = colour self.reflectIntensity = intensity def build(self): self.blmat = bpy.data.materials.new(self.name) self.blmat.diffuse_color = (self.col[0]/255, self.col[1]/255, self.col[2]/255) self.blmat.diffuse_intensity = self.diffuse self.blmat.ambient = self.ambient self.blmat.specular_intensity = self.specular if self.geometry.vertCol: self.blmat.use_vertex_color_light = True if self.col[3] < 255: self.blmat.use_transparency = True self.blmat.alpha = self.col[3]/255 if self.envtex: self.envtex.build() if self.spectex: self.spectex.build() if self.texture: self.texture.build() self.blmat.active_texture_index = 0 if self.reflectColour and self.reflectIntensity: self.blmat.mirror_color = self.reflectColour self.blmat.raytrace_mirror.use = True self.blmat.raytrace_mirror.reflect_factor = self.reflectIntensity self.geometry.mesh.materials.append(self.blmat) class RwTexture: def __init__(self, loader, material, name, texType, intensity=1): self.material = material self.bltex = None self.bltexslot = None self.name = name self.loader = loader self.texType = texType self.intensity = intensity def build(self): if self.texType == 1 and self.name in self.loader.envtexpool: self.bltex = self.loader.envtexpool[self.name] elif self.texType != 1 and self.name in self.loader.texpool: self.bltex = self.loader.texpool[self.name] else: if self.texType == 1: self.bltex = bpy.data.textures.new(self.name, "ENVIRONMENT_MAP") self.bltex.__class__ = bpy.types.EnvironmentMapTexture self.bltex.environment_map.source = "IMAGE_FILE" self.loader.envtexpool[self.name] = self.bltex else: self.bltex = bpy.data.textures.new(self.name, "IMAGE") self.bltex.__class__ = bpy.types.ImageTexture self.loader.texpool[self.name] = self.bltex imgfile = self.loader.filename + "_tex\\" + self.name + ".png" if os.path.isfile(imgfile): self.bltex.image = bpy.data.images.load(imgfile) self.bltexslot = self.material.blmat.texture_slots.create(self.texType) self.bltexslot.texture_coords = "UV" self.bltexslot.texture = self.bltex if (self.texType == 1 or self.texType == 2) and self.material.geometry.hasEnvUV: self.bltexslot.uv_layer = "EnvUV" else: self.bltexslot.uv_layer = "MainUV" if self.texType == 1: self.bltexslot.diffuse_factor = self.intensity elif self.texType == 2: self.bltexslot.use_map_diffuse = False self.bltexslot.use_map_color_diffuse = False self.bltexslot.use_map_color_spec = True self.bltexslot.specular_color_factor = self.intensity class RpAtomic: def __init__(self, loader, frame, geometry, flags): self.loader = loader self.frame = frame self.geometry = geometry self.flags = flags self.renderPlugin = None self.renderExtra = None self.matfxpipe = False frame.setAtomic(self) geometry.setAtomic(self) def setRenderRights(self, plugin, extra): self.renderPlugin = plugin self.renderExtra = extra def __init__(self, filename): self.filename = filename self.texpool = {} self.envtexpool = {} self.colhex = None self.childrenOf = None self.frames = [] self.geoms = [] self.f = open(filename, "rb") self.readSection(RwTypes.CLUMP) self.f.close() for frame in self.childrenOf[0]: self.frames[frame].build() def writeDebug(self, text): g = open(self.filename + ".txt", "a") g.write(text + "\n") g.close() def readFormat(self, format): return struct.unpack(format, self.f.read(struct.calcsize(format))) def readSlice(self, format, slice): size = struct.calcsize(format) if(len(slice) < size): raise Exception("Failed to read slice, buffer is too small.") return struct.unpack(format, slice[:size]), slice[size:] def readSection(self, type, extra = None): header = self.readFormat("III") header = (header[0], header[1], RwTypes.decodeVersion(header[2])) if type >= 0 and header[0] != type: raise Exception("Expected type " + str(type) + ", found " + str(header[0])) curPos = self.f.tell() res = None if header[0] == RwTypes.STRUCT: res = self.readSectionStruct(header) elif header[0] == RwTypes.STRING: res = self.readSectionString(header) elif header[0] == RwTypes.EXTENSION: res = self.readSectionExtension(header, extra) elif header[0] == RwTypes.TEXTURE: res = self.readSectionTexture(header, extra) elif header[0] == RwTypes.MATERIAL: res = self.readSectionMaterial(header, extra) elif header[0] == RwTypes.MATERIALLIST: res = self.readSectionMaterialList(header, extra) elif header[0] == RwTypes.FRAMELIST: res = self.readSectionFrameList(header) elif header[0] == RwTypes.GEOMETRY: res = self.readSectionGeometry(header, extra) elif header[0] == RwTypes.CLUMP: res = self.readSectionClump(header) elif header[0] == RwTypes.ATOMIC: res = self.readSectionAtomic(header) elif header[0] == RwTypes.GEOMETRYLIST: res = self.readSectionGeometryList(header) elif header[0] == RwTypes.MORPHPLG: res = self.readSectionMorphPLG(header, extra) elif header[0] == RwTypes.BINMESHPLG: res = self.readSectionBinMeshPLG(header, extra) elif header[0] == RwTypes.FRAMENAME: res = self.readSectionFrameName(header, extra) elif header[0] == RwTypes.COLLISION: res = self.readSectionCollision(header, extra) elif header[0] == RwTypes.MATEFFECTS: res = self.readSectionMatEffects(header, extra) elif header[0] == RwTypes.MATSPECULAR: res = self.readSectionMatSpecular(header, extra) elif header[0] == RwTypes.MATREFLECTION: res = self.readSectionMatReflection(header, extra) elif header[0] == RwTypes.MESHEXTENSION: res = self.readSectionMeshExtension(header, extra) elif header[0] == RwTypes.RENDERRIGHTS: res = self.readSectionRenderRights(header, extra) elif header[0] == RwTypes.HANIMPLG: res = self.readSectionHAnimPLG(header, extra) elif header[0] == RwTypes.SKINPLG: res = self.readSectionSkinPLG(header, extra) elif header[0] == RwTypes.NIGHTCOLS: res = self.readSectionNightCols(header, extra) elif type >= 0: raise Exception("Missing read function for section type " + str(type)) else: print("Ignoring extension data of type " + hex(header[0])) self.f.seek(curPos + header[1]) return res def readSectionStruct(self, header): return header, self.f.read(header[1]) def readSectionString(self, header): byteList = b"" for i in range(header[1]): newByte = self.f.read(1) if newByte[0] == 0: break byteList += newByte return header, byteList.decode("ascii") def readSectionExtension(self, header, extra): endPos = self.f.tell() + header[1] while self.f.tell() < endPos: self.readSection(RwTypes.ANY, extra) return header, None def readSectionTexture(self, header, material): metaHeader, slice = self.readSection(RwTypes.STRUCT) (flags, x), slice = self.readSlice("HH", slice) x, texName = self.readSection(RwTypes.STRING) x, alphaName = self.readSection(RwTypes.STRING) if material.readenvmap: texture = self.RwTexture(self, material, texName, 1, material.envIntensity) material.setEnvTexture(texture) else: texture = self.RwTexture(self, material, texName, 0, 1) material.setTexture(texture) self.readSection(RwTypes.EXTENSION) return header, None def readSectionMaterial(self, header, geometry): metaHeader, slice = self.readSection(RwTypes.STRUCT) (flags,), slice = self.readSlice("I", slice) col, slice = self.readSlice("BBBB", slice) (x, textured, ambient, specular, diffuse), slice = self.readSlice("iifff", slice) material = self.RpMaterial(geometry, flags, col, textured, ambient, specular, diffuse) geometry.addMaterial(material) if textured > 0: self.readSection(RwTypes.TEXTURE, material) self.readSection(RwTypes.EXTENSION, material) return header, None def readSectionMaterialList(self, header, geometry): metaHeader, slice = self.readSection(RwTypes.STRUCT) (matCount,), slice = self.readSlice("i", slice) for i in range(matCount): junk, slice = self.readSlice("i", slice) for i in range(matCount): self.readSection(RwTypes.MATERIAL, geometry) return header, None def readSectionFrameList(self, header): metaHeader, slice = self.readSection(RwTypes.STRUCT) (frameCount,), slice = self.readSlice("i", slice) self.childrenOf = [] for i in range(frameCount+1): self.childrenOf.append([]) for i in range(frameCount): rot, slice = self.readSlice("fffffffff", slice) pos, slice = self.readSlice("fff", slice) (parent, flags), slice = self.readSlice("ii", slice) self.frames.append(self.RwFrame(self, i, rot, pos, parent)) for i in range(frameCount): self.readSection(RwTypes.EXTENSION, self.frames[i]) return header, None def readSectionGeometry(self, header, index): metaHeader, slice = self.readSection(RwTypes.STRUCT) (flags, texCount, triCount, vertCount, morphCount), slice = self.readSlice("HHiii", slice) geometry = self.RpGeometry(self, index) self.geoms.append(geometry) geometry.flags = flags if metaHeader[2] < 0x34001: (surfAmbient, surfSpecular, surfDiffuse), slice = self.readSlice("fff", slice) for i in range(vertCount): geometry.addVertex(self.RwVertex(None, None)) if flags & RpGeomFlag.PRELIT: geometry.vertCol = [] for i in range(vertCount): (vcr, vcg, vcb, vca), slice = self.readSlice("BBBB", slice) geometry.vertCol.append((vcr / 255, vcg / 255, vcb / 255)) for i in range(vertCount): uv, slice = self.readSlice("ff", slice) geometry.vertices[i].uv = (uv[0], 1-uv[1]) if texCount > 1: geometry.hasEnvUV = True for i in range(vertCount): uv_env, slice = self.readSlice("ff", slice) geometry.vertices[i].uv_env = (uv_env[0], 1-uv_env[1]) if texCount > 2: slice = slice[struct.calcsize("ff")*(texCount-2)*(vertCount):] for i in range(triCount): (c, b, mat, a), slice = self.readSlice("HHHH", slice) if a >= vertCount or b >= vertCount or c >= vertCount: raise Exception("Vertex indices out of range for triangle.") geometry.addTriangle(self.RwTriangle((a, b, c), mat)) if morphCount is not 1: raise Exception("Multiple frames not supported") for i in range(morphCount): (bx, by, bz, br, hasVerts, hasNormals), slice = self.readSlice("ffffii", slice) if hasVerts > 0: for j in range(vertCount): coords, slice = self.readSlice("fff", slice) geometry.vertices[j].coords = coords if hasNormals > 0: geometry.hasNormals = True for j in range(vertCount): normal, slice = self.readSlice("fff", slice) geometry.vertices[j].normal = normal self.readSection(RwTypes.MATERIALLIST, geometry) self.readSection(RwTypes.EXTENSION, geometry) return header, None def readSectionClump(self, header): metaHeader, slice = self.readSection(RwTypes.STRUCT) (atomicCount,), slice = self.readSlice("i", slice) if metaHeader[2] > 0x33000: (lightCount, cameraCount), slice = self.readSlice("ii", slice) self.readSection(RwTypes.FRAMELIST) self.readSection(RwTypes.GEOMETRYLIST) for i in range(atomicCount): self.readSection(RwTypes.ATOMIC) self.readSection(RwTypes.EXTENSION) return header, None def readSectionAtomic(self, header): metaHeader, slice = self.readSection(RwTypes.STRUCT) (frameIndex, geomIndex, flags, x, x, x, x), slice = self.readSlice("iiBBBBi", slice) atomic = self.RpAtomic(self, self.frames[frameIndex], self.geoms[geomIndex], flags) self.readSection(RwTypes.EXTENSION, atomic) return header, None def readSectionGeometryList(self, header): metaHeader, slice = self.readSection(RwTypes.STRUCT) (geomCount,), slice = self.readSlice("i", slice) for i in range(geomCount): self.readSection(RwTypes.GEOMETRY, i) def readSectionMorphPLG(self, header, geometry): return header, None def readSectionBinMeshPLG(self, header, geometry): slice = self.f.read(header[1]) (type, splits, total), slice = self.readSlice("iii", slice) if type != 0 and type != 1: print("Morph PLG section in unknown type - ignoring.") return header, None lookup = {} for i in range(len(geometry.triangles)): v = geometry.triangles[i].verts v = list(v) v.sort() lookup[tuple(v)] = i totals = 0 for i in range(splits): (sub, mat), slice = self.readSlice("ii", slice) if type == 0: for j in range(sub//3): vx, slice = self.readSlice("iii", slice) vx = list(vx) vx.sort() vx = tuple(vx) if vx in lookup: geometry.triangles[lookup[vx]].mat = mat else: elems = deque() for j in range(sub): if len(elems) > 2: elems.popleft() (item,), slice = self.readSlice("i", slice) if len(elems) > 1: checklist = [elems[0], elems[1], item] checklist.sort() check = tuple(checklist) if check in lookup: geometry.triangles[lookup[check]].mat = mat elems.append(item) return header, None def readSectionFrameName(self, header, frame): frame.name = self.f.read(header[1]).decode("ascii") return header, None def readSectionCollision(self, header, geometry): if not self.childrenOf or len(self.childrenOf[0]) is 0: print("Collision extension - no frame to attach to.") return header, None binary = self.f.read(header[1]) self.colhex = base64.b64encode(zlib.compress(binary)).decode("ascii") return header, None def readSectionMatEffects(self, header, parent): if parent.__class__ == self.RpMaterial: return self.readSectionMaterialMatEffects(header, parent) elif parent.__class__ == self.RpAtomic: return self.readSectionAtomicMatEffects(header, parent) return header, None def readSectionMaterialMatEffects(self, header, material): (flags,) = self.readFormat("I") for i in range(2): (effectType,) = self.readFormat("I") if effectType == 0: continue elif effectType != 2: print("Unknown material effect type.") return header, None (coefficient, frameBufferAlpha, textured) = self.readFormat("fii") if textured: material.readenvmap = True material.envIntensity = coefficient self.readSection(RwTypes.TEXTURE, material) def readSectionAtomicMatEffects(self, header, atomic): (check,) = self.readFormat("i") if check != 0: atomic.matfxpipe = True return header, None def readSectionMatSpecular(self, header, material): slice = self.f.read(header[1]) (intensity,), slice = self.readSlice("f", slice) specName = "" for i in range(len(slice)): if int(slice[i]) == 0: break specName += slice[i:i+1].decode("ascii") texture = self.RwTexture(self, material, specName, 2, intensity) material.setSpecTexture(texture) return header, None def readSectionMatReflection(self, header, material): slice = self.f.read(header[1]) colour, slice = self.readSlice("fff", slice) (x, intensity), slice = self.readSlice("ff", slice) material.setReflection(colour, intensity) return header, None def readSectionMeshExtension(self, header, geometry): slice = self.f.read(header[1]) (hasData,), slice = self.readSlice("i", slice) if hasData: print("Mesh extension extension actually has data. Not sure what to do with it.") return header, None def readSectionRenderRights(self, header, atomic): if not hasattr(atomic, "__class__") or atomic.__class__ != self.RpAtomic: print("Render rights extension is not in the right section, should be in atomic.") return slice = self.f.read(header[1]) (plugin, extra), slice = self.readSlice("ii", slice) atomic.setRenderRights(plugin, extra) def readSectionHAnimPLG(self, header, frame): if not hasattr(frame, "__class__") or frame.__class__ != self.RwFrame: print("HAnim extension is not in the right section, should be in frame.") return binary = self.f.read(header[1]) frame.hanimdata = base64.b64encode(zlib.compress(binary)).decode("ascii") return header, None def readSectionSkinPLG(self, header, geometry): if not hasattr(geometry, "__class__") or geometry.__class__ != self.RpGeometry: print("Skin extension is not in the right section, should be in geometry.") return binary = self.f.read(header[1]) geometry.skindata = base64.b64encode(zlib.compress(binary)).decode("ascii") return header, None def readSectionNightCols(self, header, geometry): if not hasattr(geometry, "__class__") or geometry.__class__ != self.RpGeometry: print("Night vertex colours extension is not in the right section, should be in geometry.") return slice = self.f.read(header[1]) (x,), slice = self.readSlice("I", slice) geometry.nightVertCol = [] for i in range(len(geometry.vertices)): (vcr, vcg, vcb, vca), slice = self.readSlice("BBBB", slice) geometry.nightVertCol.append((vcr / 255, vcg / 255, vcb / 255)) return header, None class ExportRenderware: class RwChunkHeader: def __init__(self, type, size): self.type = type self.size = size def bin(self): return struct.pack("III", self.type, self.size, ExportRenderware.targetVer) class RwVector3: def __init__(self, x, y, z): self.x = x self.y = y self.z = z def bin(self): return struct.pack("fff", self.x, self.y, self.z) class RwRotMatrix: def __init__(self): self.m = [1, 0, 0, 0, 1, 0, 0, 0, 1] def bin(self): return struct.pack("9f", *self.m) class RwFrameList: def __init__(self): self.R = ExportRenderware self.frames = [] def bin(self): payload = struct.pack("i", len(self.frames)) for frame in self.frames: payload += frame.binraw() payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload for frame in self.frames: payload += frame.binext() header = self.R.RwChunkHeader(RwTypes.FRAMELIST, len(payload)).bin() return header + payload class RwFrame: def __init__(self, clump, object, parentFrame): self.R = ExportRenderware self.clump = clump self.object = object self.index = len(clump.frameList.frames) clump.frameList.frames.append(self) self.name = self.object.name self.parent = parentFrame self.rotation = self.R.RwRotMatrix() self.position = self.R.RwVector3(0, 0, 0) if parentFrame is not None: ux = object.matrix_local.to_3x3() self.rotation.m = [ux[0][0], ux[0][1], ux[0][2], ux[1][0], ux[1][1], ux[1][2], ux[2][0], ux[2][1], ux[2][2]] self.position.x = object.matrix_local.translation[0] self.position.y = object.matrix_local.translation[1] self.position.z = object.matrix_local.translation[2] if str(object.type) == "MESH": self.atomic = self.R.RpAtomic(self) elif str(object.type) == "EMPTY": self.atomic = None else: raise Exception("Unsupported object type selected: " + str(object.type)) for child in self.object.children: if str(object.type) != "MESH" and str(object.type) != "EMPTY": print("Ignoring object " + object.name + ", type " + object.type) continue self.R.RwFrame(self.clump, child, self) if not clump.colbin: try: if len(object.collhex) > 0: textf = bpy.data.texts[object.collhex].as_string() clump.colbin = zlib.decompress(base64.b64decode(bytes(textf, "ascii"))) except: clump.colbin = None def binraw(self): payload = self.rotation.bin() payload += self.position.bin() payload += struct.pack("ii", -1 if self.parent is None else self.parent.index, 0) return payload def binext_name(self): noname = "noname_" if self.name[:len(noname)] == noname: return b"" writename = self.R.unmangleName(self.name) if len(writename) > 23: writename = writename[:23] print("Warning, frame name '", writename , "' truncated to 23 characters.") payload = struct.pack(str(len(writename)) + "s", bytearray(writename, "ascii")) header = self.R.RwChunkHeader(RwTypes.FRAMENAME, len(payload)).bin() return header + payload def binext_hanim(self): object = self.object try: if len(object.rw_hanimdata) > 0: textf = bpy.data.texts[object.rw_hanimdata].as_string() rawdata = zlib.decompress(base64.b64decode(bytes(textf, "ascii"))) else: return b"" except: return b"" payload = rawdata header = self.R.RwChunkHeader(RwTypes.HANIMPLG, len(payload)).bin() return header + payload def binext(self): payload = self.binext_name() + self.binext_hanim() header = self.R.RwChunkHeader(RwTypes.EXTENSION, len(payload)).bin() return header + payload class RpAtomicChunkInfo: def __init__(self, frameIndex, geometryIndex, flags): self.R = ExportRenderware self.frameIndex = frameIndex self.geometryIndex = geometryIndex self.flags = flags def bin(self): payload = struct.pack("iiii", self.frameIndex, self.geometryIndex, self.flags, 0) header = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() return header + payload class RpAtomic: def __init__(self, frame): self.R = ExportRenderware self.clump = frame.clump self.frame = frame self.mesh = frame.object.to_mesh(self.clump.context.scene, False, "PREVIEW") self.geometry = self.R.RpGeometry(self) self.flags = 5 def binext_rights(self): if self.frame.object.renderright == 0: return b"" payload = struct.pack("ii", self.frame.object.renderright, self.frame.object.renderextra) header = self.R.RwChunkHeader(RwTypes.RENDERRIGHTS, len(payload)).bin() return header + payload def binext_matfx(self): if self.frame.object.matfxpipe != True and self.R.decodedVer > 0x34003: return b"" payload = struct.pack("i", 1) header = self.R.RwChunkHeader(RwTypes.MATEFFECTS, len(payload)).bin() return header + payload def bin(self): payload = self.R.RpAtomicChunkInfo(self.frame.index, self.geometry.index, self.flags).bin() extensions = self.binext_rights() + self.binext_matfx() extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.ATOMIC, len(payload)).bin() return header + payload class RpVertex: def __init__(self, pos, uv, uve, normal): self.pos = pos self.uv = uv self.uve = uve self.normal = normal class RpTriangle: def __init__(self, a, b, c, mat): self.a = a self.b = b self.c = c self.mat = mat def bin(self): return struct.pack("HHHH", self.a, self.b, self.mat, self.c) class RwUVCoord: def __init__(self, u, v): self.u = u self.v = v def bin(self): return struct.pack("ff", self.u, 1-self.v) class RwTexture: def __init__(self, material, bltexslot): self.R = ExportRenderware self.material = material self.bltexslot = bltexslot self.bltex = bltexslot.texture def bin(self): payload = struct.pack("HH", 0x1106, 0) payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload strdata = struct.pack(str(len(self.bltex.name)) + "s", bytearray(self.bltex.name, "ascii")) for i in range(4 - (len(self.bltex.name)&3)): strdata += struct.pack("B", 0) payload += self.R.RwChunkHeader(RwTypes.STRING, len(strdata)).bin() + strdata strdata = struct.pack("i", 0) payload += self.R.RwChunkHeader(RwTypes.STRING, len(strdata)).bin() + strdata extensions = b"" extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.TEXTURE, len(payload)).bin() return header + payload class RpMaterial: def __init__(self, materialList, blMaterial): self.R = ExportRenderware self.materialList = materialList self.index = len(materialList.mats) self.mesh = materialList.mesh self.blmaterial = blMaterial self.red = min(255, max(0, blMaterial.diffuse_color[0] * 256)) self.green = min(255, max(0, blMaterial.diffuse_color[1] * 256)) self.blue = min(255, max(0, blMaterial.diffuse_color[2] * 256)) self.alpha = min(255, max(0, blMaterial.alpha * 256)) self.ambient = blMaterial.ambient self.specular = blMaterial.specular_intensity self.diffuse = blMaterial.diffuse_intensity self.bltex_diffuse = self.findTexSlot("DIFFUSE") self.bltex_specular = self.findTexSlot("SPECULAR") self.bltex_envmap = self.findTexSlot("ENVMAP") self.tex_diffuse = None self.tex_envmap = None if self.bltex_diffuse: self.tex_diffuse = self.R.RwTexture(self, self.bltex_diffuse) if self.bltex_diffuse.texture_coords == "UV" and len(self.bltex_diffuse.uv_layer) > 0 and not self.materialList.geometry.uvname_diff: self.materialList.geometry.uvname_diff = self.bltex_diffuse.uv_layer if self.bltex_envmap: self.tex_envmap = self.R.RwTexture(self, self.bltex_envmap) if self.bltex_envmap.texture_coords == "UV" and len(self.bltex_envmap.uv_layer) > 0 and not self.materialList.geometry.uvname_env: self.materialList.geometry.uvname_env = self.bltex_envmap.uv_layer def findTexSlot(self, type): for i in range(len(self.blmaterial.texture_slots)): textype = "" slot = self.blmaterial.texture_slots[i] if slot and slot.texture: if slot.texture.type == "ENVIRONMENT_MAP": textype = "ENVMAP" elif slot.use_map_color_spec and not slot.use_map_color_diffuse: textype = "SPECULAR" elif slot.use_map_color_diffuse and not slot.use_map_color_spec: textype = "DIFFUSE" if textype == type: return slot return None def binext_matfx(self): if not self.tex_envmap: return b"" payload = struct.pack("iifii", 2, 2, self.bltex_envmap.specular_color_factor, 0, 1) payload += self.tex_envmap.bin() payload += struct.pack("i", 0) header = self.R.RwChunkHeader(RwTypes.MATEFFECTS, len(payload)).bin() return header + payload def binext_reflect(self): if not self.blmaterial.raytrace_mirror.use and ExportRenderware.decodedVer <= 0x34003: return b"" factor = self.blmaterial.raytrace_mirror.reflect_factor if self.blmaterial.raytrace_mirror.use else 0 colour = self.blmaterial.mirror_color payload = struct.pack("fffffi", colour[0], colour[1], colour[2], 1, self.blmaterial.raytrace_mirror.reflect_factor, 0) header = self.R.RwChunkHeader(RwTypes.MATREFLECTION, len(payload)).bin() return header + payload def binext_specular(self): if not self.bltex_specular: return b"" payload = struct.pack("f", self.bltex_specular.specular_color_factor) texname = bytes(self.bltex_specular.texture.name, "ascii") payload += texname[:23] nullbyte = struct.pack("B", 0) for i in range(24 - min(23, len(texname))): payload += nullbyte header = self.R.RwChunkHeader(RwTypes.MATSPECULAR, len(payload)).bin() return header + payload def bin(self): payload = struct.pack("iBBBBiIfff", 0, int(self.red), int(self.green), int(self.blue), int(self.alpha), 0, 1 if self.tex_diffuse else 0, self.ambient, self.specular, self.diffuse) payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload if self.tex_diffuse: payload += self.tex_diffuse.bin() extensions = self.binext_matfx() + self.binext_reflect() + self.binext_specular() extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.MATERIAL, len(payload)).bin() return header + payload class RpMaterialList: def __init__(self, geometry): self.R = ExportRenderware self.geometry = geometry self.clump = geometry.clump self.mesh = geometry.mesh self.mats = [] for mat in self.mesh.materials: self.mats.append(self.R.RpMaterial(self, mat)) def bin(self): payload = struct.pack("i", len(self.mesh.materials)) for mat in self.mats: payload += struct.pack("i", -1) payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload for mat in self.mats: payload += mat.bin() header = self.R.RwChunkHeader(RwTypes.MATERIALLIST, len(payload)).bin() return header + payload class RpGeometryList: def __init__(self): self.R = ExportRenderware self.geoms = [] def bin(self): payload = struct.pack("i", len(self.geoms)) payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload for geom in self.geoms: payload += geom.bin() header = self.R.RwChunkHeader(RwTypes.GEOMETRYLIST, len(payload)).bin() return header + payload class RpGeometryChunkInfo: def __init__(self): self.flags = RpGeomFlag.TEXTURED | RpGeomFlag.NORMALS | RpGeomFlag.LIGHT | RpGeomFlag.MODULATEMATERIALCOLOR self.texCount = 1 self.triangleCount = 0 self.vertexCount = 0 self.frameCount = 1 def binraw(self): return struct.pack("HHiii", self.flags, self.texCount, self.triangleCount, self.vertexCount, self.frameCount) class RpGeometry: def __init__(self, atomic): self.R = ExportRenderware self.clump = atomic.clump self.atomic = atomic self.mesh = atomic.mesh self.index = len(self.clump.geometryList.geoms) self.clump.geometryList.geoms.append(self) self.chunkInfo = self.R.RpGeometryChunkInfo() self.uvname_diff = None self.uvname_env = None self.materialList = self.R.RpMaterialList(self) self.matTris = [] for i in range(len(self.materialList.mats)): self.matTris.append([]) mesh = self.mesh self.vdict = [] for i in range(len(mesh.vertices)): self.vdict.append({}) self.uvc = self.getUVData(self.uvname_diff) self.uvce = None if self.uvname_env and self.uvname_env != self.uvname_diff: self.uvce = self.getUVData(self.uvname_env) self.vertices = [] self.triangles = [] self.vertCol = None self.nightVertCol = None self.vertColData = None self.nightVertColData = None for vcol in self.mesh.vertex_colors: if vcol.name.lower() == "night" and self.nightVertCol is None: self.nightVertCol = [] self.nightVertColData = vcol.data elif self.vertCol is None: self.vertCol = [] self.vertColData = vcol.data for poly in mesh.polygons: self.addBlenderPoly(poly) if len(self.vertices) > 65535: raise Exception("Aborting export: vertex count exceeds 65535") self.maxDist = 0 for v in self.mesh.vertices: self.maxDist = max(self.maxDist, math.sqrt(v.co[0]*v.co[0] + v.co[1]*v.co[1] + v.co[2]*v.co[2])) self.chunkInfo.triangleCount = len(self.triangles) self.chunkInfo.vertexCount = len(self.vertices) if self.uvce: self.chunkInfo.texCount = 2 self.chunkInfo.flags = self.chunkInfo.flags & (~RpGeomFlag.TEXTURED) self.chunkInfo.flags |= RpGeomFlag.TEXTURED2 if self.R.decodedVer > 0x34003: self.chunkInfo.flags |= RpGeomFlag.POSITIONS if self.vertColData: self.chunkInfo.flags |= RpGeomFlag.PRELIT def findVertex(self, type): for i in range(len(self.blmaterial.texture_slots)): textype = "" slot = self.blmaterial.texture_slots[i] if slot and slot.texture: if slot.texture.type == "ENVIRONMENT_MAP": textype = "ENVMAP" elif slot.use_map_color_spec and not slot.use_map_color_diffuse: textype = "SPECULAR" elif slot.use_map_color_diffuse and not slot.use_map_color_spec: textype = "DIFFUSE" if textype == type: return slot return None def getUVData(self, name): for i in range(len(self.mesh.uv_textures)): if name and self.mesh.uv_textures[i] and self.mesh.uv_textures[i].name == name: return self.mesh.uv_layers[i].data return None def newVertId(self, id, uv, uve): if (uv + uve) not in self.vdict[id]: self.vdict[id][uv + uve] = len(self.vertices) self.vertices.append(self.R.RpVertex(self.mesh.vertices[id].co, uv, uve, self.mesh.vertices[id].normal)) if self.vertColData: self.vertCol.append((int(self.vertColData[id].color[0]*255), int(self.vertColData[id].color[1]*255), int(self.vertColData[id].color[2]*255))) if self.nightVertColData: self.nightVertCol.append((int(self.nightVertColData[id].color[0]*255), int(self.nightVertColData[id].color[1]*255), int(self.nightVertColData[id].color[2]*255))) return self.vdict[id][(uv + uve)] def addRawPoly(self, verts, uvs, mat): newIds = [] for i in range(3): uv = tuple(self.uvc[uvs[i]].uv) if self.uvc else (0, 0) uve = tuple(self.uvce[uvs[i]].uv) if self.uvce else (0, 0) newIds.append(self.newVertId(verts[i], uv, uve)) self.triangles.append(self.R.RpTriangle(newIds[0], newIds[1], newIds[2], mat)) if mat >= 0: self.matTris[mat].append(newIds[0]) self.matTris[mat].append(newIds[1]) self.matTris[mat].append(newIds[2]) def addBlenderPoly(self, p): if len(p.vertices) < 3 or len(p.vertices) > 4: raise Exception("Aborting export: Invalid number of vertices on an edge.") self.addRawPoly([p.vertices[0], p.vertices[1], p.vertices[2]], [p.loop_indices[0], p.loop_indices[1], p.loop_indices[2]], p.material_index) if len(p.vertices) == 4: self.addRawPoly([p.vertices[0], p.vertices[3], p.vertices[2]], [p.loop_indices[0], p.loop_indices[3], p.loop_indices[2]], p.material_index) def binext_binmesh(self): payload = b"" splits = 0 total = 0 for i in range(len(self.matTris)): if len(self.matTris[i]) == 0: continue splits += 1 total += len(self.matTris[i]) payload += struct.pack("ii", len(self.matTris[i]), i) for id in self.matTris[i]: payload += struct.pack("i", id) payload = struct.pack("iii", 0, splits, total) + payload header = self.R.RwChunkHeader(RwTypes.BINMESHPLG, len(payload)).bin() return header + payload def binext_morph(self): if self.R.decodedVer > 0x34003 or self.R.decodedVer < 0x33000: return b"" payload = struct.pack("i", 0) header = self.R.RwChunkHeader(RwTypes.MORPHPLG, len(payload)).bin() return header + payload def binext_meshext(self): if self.R.decodedVer <= 0x34003: return b"" payload = struct.pack("i", 0) header = self.R.RwChunkHeader(RwTypes.MESHEXTENSION, len(payload)).bin() return header + payload def binext_skin(self): object = self.atomic.frame.object try: if len(object.rw_skindata) > 0: textf = bpy.data.texts[object.rw_skindata].as_string() rawdata = zlib.decompress(base64.b64decode(bytes(textf, "ascii"))) else: return b"" except: return b"" payload = rawdata header = self.R.RwChunkHeader(RwTypes.SKINPLG, len(payload)).bin() return header + payload def binext_nightcol(self): if not self.nightVertCol: return b"" payload = struct.pack("I", 1) for col in self.nightVertCol: payload += struct.pack("BBBB", col[0], col[1], col[2], 255) header = self.R.RwChunkHeader(RwTypes.NIGHTCOLS, len(payload)).bin() return header + payload def bin(self): payload = self.chunkInfo.binraw() if self.R.decodedVer < 0x34001: payload += struct.pack("fff", 0, 0, 1) if self.vertCol: for col in self.vertCol: payload += struct.pack("BBBB", col[0], col[1], col[2], 255) for vertex in self.vertices: payload += self.R.RwUVCoord(vertex.uv[0], vertex.uv[1]).bin() if self.uvce: for vertex in self.vertices: payload += self.R.RwUVCoord(vertex.uve[0], vertex.uve[1]).bin() for triangle in self.triangles: payload += triangle.bin() payload += struct.pack("ffffii", 0, 0, 0, self.maxDist, 1, 1) for vertex in self.vertices: payload += self.R.RwVector3(vertex.pos[0], vertex.pos[1], vertex.pos[2]).bin() for vertex in self.vertices: payload += self.R.RwVector3(vertex.normal[0], vertex.normal[1], vertex.normal[2]).bin() payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload payload += self.materialList.bin() extensions = self.binext_binmesh() + self.binext_skin() + self.binext_morph() + self.binext_meshext() + self.binext_nightcol() extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.GEOMETRY, len(payload)).bin() return header + payload class RpClumpChunkInfo: def __init__(self, atomicCount, lightCount, cameraCount): self.R = ExportRenderware self.atomicCount = atomicCount self.lightCount = lightCount self.cameraCount = cameraCount def bin(self): payload = struct.pack("i", self.atomicCount) if self.R.decodedVer > 0x33000: payload += struct.pack("ii", self.lightCount, self.cameraCount) header = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() return header + payload class RpClump: def __init__(self, context, exportVer): self.R = ExportRenderware self.R.targetVer = exportVer self.R.decodedVer = RwTypes.decodeVersion(self.R.targetVer) self.context = context self.frameList = self.R.RwFrameList() self.geometryList = self.R.RpGeometryList() self.colbin = None exportables = [] for object in context.selected_objects: parent = object.parent add = True while parent: if parent in context.selected_objects: add = False break parent = parent.parent if add: exportables.append(object) for object in exportables: if str(object.type) != "MESH" and str(object.type) != "EMPTY": print("Ignoring object " + object.name + ", type " + object.type) continue self.R.RwFrame(self, object, None) if len(self.frameList.frames) == 0: raise Exception("Aborting export: no frames selected.") def binext_coll(self): if not self.colbin: return b"" payload = self.colbin header = self.R.RwChunkHeader(RwTypes.COLLISION, len(self.colbin)).bin() return header + payload def bin(self): payload = self.R.RpClumpChunkInfo(len(self.geometryList.geoms), 0, 0).bin() payload += self.frameList.bin() payload += self.geometryList.bin() for geometry in self.geometryList.geoms: payload += geometry.atomic.bin() extensions = self.binext_coll() extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.CLUMP, len(payload)).bin() return header + payload def __init__(self, context, exportVerIndex, filepath): if exportVerIndex == "1": exportVer = 0x0800FFFF elif exportVerIndex == "2": exportVer = 0x1003FFFF else: exportVer = 0x1803FFFF outf = open(filepath, "wb") outf.write(self.RpClump(context, exportVer).bin()) outf.close() def unmangleName(name): if len(name) > 4 and name[-4] == "." and name[-3:].isnumeric(): return name[:-4] else: return name class ExportRenderwareMenu(bpy.types.Operator): expVersionValues = (("1", "GTA III", ""), ("2", "Vice City", ""), ("3", "San Andreas", "")) bl_idname = "export_rw.dff" bl_label = "Export Renderware (.dff)" filename_ext = ".dff" filepath = StringProperty(subtype = "FILE_PATH") expVersion = EnumProperty(name = "Export version", items = expVersionValues, default="2") def invoke(self, context, event): wm = context.window_manager wm.fileselect_add(self) return {"RUNNING_MODAL"} def execute(self, context): setupProps() ExportRenderware(context, self.expVersion, self.filepath) return {"FINISHED"} class ImportRenderwareMenu(bpy.types.Operator): bl_idname = "import_rw.dff" bl_label = "Import Renderware (.dff)" filename_ext = ".dff" filepath = StringProperty(subtype = "FILE_PATH") def invoke(self, context, event): wm = context.window_manager wm.fileselect_add(self) return {"RUNNING_MODAL"} def execute(self, context): setupProps() ImportRenderware(self.filepath) return {"FINISHED"} def export_func(self, context): self.layout.operator(ExportRenderwareMenu.bl_idname, text="Renderware (.dff)") def import_func(self, context): self.layout.operator(ImportRenderwareMenu.bl_idname, text="Renderware (.dff)") def register(): bpy.utils.register_module(__name__) bpy.types.INFO_MT_file_export.append(export_func) bpy.types.INFO_MT_file_import.append(import_func) def unregister(): bpy.utils.unregister_module(__name__) bpy.types.INFO_MT_file_export.remove(export_func) bpy.types.INFO_MT_file_import.remove(import_func) def setupProps(): class renderwarePanel(bpy.types.Panel): bl_space_type = "VIEW_3D" bl_region_type = "UI" bl_label = "Renderware" def draw(self, context): self.layout.prop(bpy.context.active_object, "renderright") self.layout.prop(bpy.context.active_object, "renderextra") self.layout.prop(bpy.context.active_object, "matfxpipe") self.layout.prop(bpy.context.active_object, "collhex") self.layout.prop(bpy.context.active_object, "rw_hanimdata") self.layout.prop(bpy.context.active_object, "rw_skindata") if hasattr(bpy.types.Object, "collhex"): return bpy.types.Object.collhex = bpy.props.StringProperty(name = "Collision", description = "Name of the text object that contains collision binary data.", maxlen = 100) bpy.types.Object.renderright = bpy.props.IntProperty(name = "RenderRight", description = "Index of the plugin whose pipeline is used for rendering.") bpy.types.Object.renderextra = bpy.props.IntProperty(name = "RenderExtra", description = "Extra arguments to the render pipeline.") bpy.types.Object.matfxpipe = bpy.props.BoolProperty(name = "MatFX pipeline", description = "Whether rendering is handled by MatFX pipeline.") bpy.types.Object.rw_hanimdata = bpy.props.StringProperty(name = "HAnimData", description = "Info for this skin bone.", maxlen = 100) bpy.types.Object.rw_skindata = bpy.props.StringProperty(name = "SkinData", description = "Skin data (bone vertices etc) for this mesh.", maxlen = 100) bpy.utils.register_class(renderwarePanel) if __name__ == "__main__": unregister() register() setupProps()

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bl_info = { "name": "RenderWare importer/exporter for GTA III/VC/SA (.dff)", "author": "Ago Allikmaa (maxorator)", "version": (0, 9, 2), "blender": (2, 6, 3), "location": "File > Import-Export > Renderware (.dff) ", "description": "RenderWare importer/exporter for GTA III/VC/SA", "category": "Import-Export" } import struct import os import zlib import base64 from collections import deque import bpy import math import mathutils from bpy.props import * class RwTypes(): ANY = -1 STRUCT = 0x0001 STRING = 0x0002 EXTENSION = 0x0003 TEXTURE = 0x0006 MATERIAL = 0x0007 MATERIALLIST = 0x0008 FRAMELIST = 0x000E GEOMETRY = 0x000F CLUMP = 0x0010 ATOMIC = 0x0014 GEOMETRYLIST = 0x001A RENDERRIGHTS = 0x001F MORPHPLG = 0x0105 SKINPLG = 0x116 HANIMPLG = 0x11E MATEFFECTS = 0x0120 BINMESHPLG = 0x050E FRAMENAME = 0x253F2FE COLLISION = 0x253F2FA MATSPECULAR = 0x253F2F6 NIGHTCOLS = 0x253F2F9 MATREFLECTION = 0x253F2FC MESHEXTENSION = 0x253F2FD def decodeVersion(version): if (version & 0xFFFF0000) == 0: return version << 8 else: p1 = ((version >> 14) & 0x3FF00) + 0x30000 p2 = (version >> 16) & 0x3F return p1 | p2 class RpGeomFlag: TRISTRIP = 0x0001 POSITIONS = 0x0002 TEXTURED = 0x0004 PRELIT = 0x0008 NORMALS = 0x0010 LIGHT = 0x0020 MODULATEMATERIALCOLOR = 0x0040 TEXTURED2 = 0x0080 class ImportRenderware: class RwTriangle: def __init__(self, verts, mat): self.verts = verts self.mat = mat def desc(self): return (self.verts[0], self.verts[1], self.verts[2]) class RwVertex: def __init__(self, coords, normal): self.coords = coords self.normal = normal self.uv = None self.uv_env = None def desc(self): return (self.coords[0], self.coords[1], self.coords[2]) class RwFrame: def __init__(self, loader, index, rot, pos, parent): self.loader = loader self.index = index self.geometry = None self.atomic = None self.blobj = None self.bldata = None self.hanimdata = None self.name = None rmatrix = mathutils.Matrix.Identity(3) rmatrix[0] = rot[0], rot[1], rot[2] rmatrix[1] = rot[3], rot[4], rot[5] rmatrix[2] = rot[6], rot[7], rot[8] rmatrix.resize_4x4() rmatrix.translation = pos[0], pos[1], pos[2] self.matrix = rmatrix self.parent = parent self.loader.childrenOf[parent+1].append(self.index) def setAtomic(self, atomic): self.atomic = atomic self.geometry = atomic.geometry def build(self): if self.name is None: self.name = "noname_" + str(self.index); if self.geometry: self.bldata = self.geometry.build(self.name) self.blobj = bpy.data.objects.new(self.name, self.bldata) if self.parent >= 0: self.blobj.parent = self.loader.frames[self.parent].blobj self.blobj.matrix_local = self.matrix bpy.context.scene.objects.link(self.blobj) for frame in self.loader.childrenOf[self.index+1]: self.loader.frames[frame].build() if "_vlo" in self.name or "_dam" in self.name: self.blobj.hide = True self.blobj.hide_render = True if self.loader.colhex and self.index == self.loader.childrenOf[0][0]: textobj = bpy.data.texts.new(name = ("zrwcoll_" + self.name)) textobj.from_string(self.loader.colhex) self.blobj.collhex = textobj.name if self.hanimdata: textobj = bpy.data.texts.new(name = ("zrwhanim" + str(self.index) + "_" + self.name)) textobj.from_string(self.hanimdata) self.blobj.rw_hanimdata = textobj.name if self.geometry and self.geometry.skindata: textobj = bpy.data.texts.new(name = ("zrwskin_" + self.name)) textobj.from_string(self.geometry.skindata) self.blobj.rw_skindata = textobj.name if self.atomic and self.atomic.renderPlugin != None and self.atomic.renderExtra != None: self.blobj.renderright = self.atomic.renderPlugin self.blobj.renderextra = self.atomic.renderExtra if self.atomic and self.atomic.matfxpipe: self.blobj.matfxpipe = True class RpGeometry: def __init__(self, loader, index): self.loader = loader self.index = index self.vertices = [] self.triangles = [] self.materials = [] self.mesh = None self.atomic = None self.skindata = None self.hasEnvUV = False self.vertCol = None self.nightVertCol = None self.hasNormals = False def setAtomic(self, atomic): self.atomic = atomic def addMaterial(self, material): material.setIndex(len(self.materials)) self.materials.append(material) def addVertex(self, vertex): self.vertices.append(vertex) def addTriangle(self, triangle): self.triangles.append(triangle) def build(self, name): self.mesh = bpy.data.meshes.new(name) pyverts = [] pypolys = [] for vertex in self.vertices: pyverts.append(vertex.desc()) for triangle in self.triangles: pypolys.append(triangle.desc()) self.mesh.from_pydata(pyverts, [], pypolys) self.mesh.update() if self.vertCol: vcol = self.mesh.vertex_colors.new("Normal") self.mesh.vertex_colors.active = vcol for i in range(len(self.vertices)): vcol.data[i].color = (self.vertCol[i][0], self.vertCol[i][1], self.vertCol[i][2]) if self.nightVertCol: nvcol = self.mesh.vertex_colors.new("Night") self.mesh.vertex_colors.active = nvcol for i in range(len(self.vertices)): nvcol.data[i].color = (self.nightVertCol[i][0], self.nightVertCol[i][1], self.nightVertCol[i][2]) uvtexture = self.mesh.uv_textures.new() uvtexture.name = "MainUV" uvlayer = self.mesh.uv_layers[-1] for i in range(len(self.triangles)): for j in range(3): uvlayer.data[3*i + j].uv = self.vertices[self.triangles[i].verts[j]].uv if self.hasEnvUV: euvtexture = self.mesh.uv_textures.new() euvtexture.name = "EnvUV" euvlayer = self.mesh.uv_layers[-1] for i in range(len(self.triangles)): for j in range(3): euvlayer.data[3*i + j].uv = self.vertices[self.triangles[i].verts[j]].uv_env for material in self.materials: material.build() for i in range(len(self.triangles)): self.mesh.polygons[i].material_index = self.triangles[i].mat return self.mesh class RpMaterial: def __init__(self, geometry, flags=None, col=None, textured=None, ambient=None, specular=None, diffuse=None): self.index = None self.name = "g" + str(geometry.index) + "m" self.geometry = geometry self.flags = flags self.col = col self.ambient = ambient self.specular = specular self.diffuse = diffuse self.textured = textured self.texture = None self.blmat = None self.envtex = None self.readenvmap = False self.envIntensity = 1 self.reflectColour = None self.reflectIntensity = None self.spectex = None def setIndex(self, index): self.index = index self.name = "g" + str(self.geometry.index) + "m" + str(index) def setTexture(self, texture): self.texture = texture def setEnvTexture(self, texture): self.envtex = texture def setSpecTexture(self, texture): self.spectex = texture def setReflection(self, colour, intensity): self.reflectColour = colour self.reflectIntensity = intensity def build(self): self.blmat = bpy.data.materials.new(self.name) self.blmat.diffuse_color = (self.col[0]/255, self.col[1]/255, self.col[2]/255) self.blmat.diffuse_intensity = self.diffuse self.blmat.ambient = self.ambient self.blmat.specular_intensity = self.specular if self.geometry.vertCol: self.blmat.use_vertex_color_light = True if self.col[3] < 255: self.blmat.use_transparency = True self.blmat.alpha = self.col[3]/255 if self.envtex: self.envtex.build() if self.spectex: self.spectex.build() if self.texture: self.texture.build() self.blmat.active_texture_index = 0 if self.reflectColour and self.reflectIntensity: self.blmat.mirror_color = self.reflectColour self.blmat.raytrace_mirror.use = True self.blmat.raytrace_mirror.reflect_factor = self.reflectIntensity self.geometry.mesh.materials.append(self.blmat) class RwTexture: def __init__(self, loader, material, name, texType, intensity=1): self.material = material self.bltex = None self.bltexslot = None self.name = name self.loader = loader self.texType = texType self.intensity = intensity def build(self): if self.texType == 1 and self.name in self.loader.envtexpool: self.bltex = self.loader.envtexpool[self.name] elif self.texType != 1 and self.name in self.loader.texpool: self.bltex = self.loader.texpool[self.name] else: if self.texType == 1: self.bltex = bpy.data.textures.new(self.name, "ENVIRONMENT_MAP") self.bltex.__class__ = bpy.types.EnvironmentMapTexture self.bltex.environment_map.source = "IMAGE_FILE" self.loader.envtexpool[self.name] = self.bltex else: self.bltex = bpy.data.textures.new(self.name, "IMAGE") self.bltex.__class__ = bpy.types.ImageTexture self.loader.texpool[self.name] = self.bltex imgfile = self.loader.filename + "_tex\\" + self.name + ".png" if os.path.isfile(imgfile): self.bltex.image = bpy.data.images.load(imgfile) self.bltexslot = self.material.blmat.texture_slots.create(self.texType) self.bltexslot.texture_coords = "UV" self.bltexslot.texture = self.bltex if (self.texType == 1 or self.texType == 2) and self.material.geometry.hasEnvUV: self.bltexslot.uv_layer = "EnvUV" else: self.bltexslot.uv_layer = "MainUV" if self.texType == 1: self.bltexslot.diffuse_factor = self.intensity elif self.texType == 2: self.bltexslot.use_map_diffuse = False self.bltexslot.use_map_color_diffuse = False self.bltexslot.use_map_color_spec = True self.bltexslot.specular_color_factor = self.intensity class RpAtomic: def __init__(self, loader, frame, geometry, flags): self.loader = loader self.frame = frame self.geometry = geometry self.flags = flags self.renderPlugin = None self.renderExtra = None self.matfxpipe = False frame.setAtomic(self) geometry.setAtomic(self) def setRenderRights(self, plugin, extra): self.renderPlugin = plugin self.renderExtra = extra def __init__(self, filename): self.filename = filename self.texpool = {} self.envtexpool = {} self.colhex = None self.childrenOf = None self.frames = [] self.geoms = [] self.f = open(filename, "rb") self.readSection(RwTypes.CLUMP) self.f.close() for frame in self.childrenOf[0]: self.frames[frame].build() def writeDebug(self, text): g = open(self.filename + ".txt", "a") g.write(text + "\n") g.close() def readFormat(self, format): return struct.unpack(format, self.f.read(struct.calcsize(format))) def readSlice(self, format, slice): size = struct.calcsize(format) if(len(slice) < size): raise Exception("Failed to read slice, buffer is too small.") return struct.unpack(format, slice[:size]), slice[size:] def readSection(self, type, extra = None): header = self.readFormat("III") header = (header[0], header[1], RwTypes.decodeVersion(header[2])) if type >= 0 and header[0] != type: raise Exception("Expected type " + str(type) + ", found " + str(header[0])) curPos = self.f.tell() res = None if header[0] == RwTypes.STRUCT: res = self.readSectionStruct(header) elif header[0] == RwTypes.STRING: res = self.readSectionString(header) elif header[0] == RwTypes.EXTENSION: res = self.readSectionExtension(header, extra) elif header[0] == RwTypes.TEXTURE: res = self.readSectionTexture(header, extra) elif header[0] == RwTypes.MATERIAL: res = self.readSectionMaterial(header, extra) elif header[0] == RwTypes.MATERIALLIST: res = self.readSectionMaterialList(header, extra) elif header[0] == RwTypes.FRAMELIST: res = self.readSectionFrameList(header) elif header[0] == RwTypes.GEOMETRY: res = self.readSectionGeometry(header, extra) elif header[0] == RwTypes.CLUMP: res = self.readSectionClump(header) elif header[0] == RwTypes.ATOMIC: res = self.readSectionAtomic(header) elif header[0] == RwTypes.GEOMETRYLIST: res = self.readSectionGeometryList(header) elif header[0] == RwTypes.MORPHPLG: res = self.readSectionMorphPLG(header, extra) elif header[0] == RwTypes.BINMESHPLG: res = self.readSectionBinMeshPLG(header, extra) elif header[0] == RwTypes.FRAMENAME: res = self.readSectionFrameName(header, extra) elif header[0] == RwTypes.COLLISION: res = self.readSectionCollision(header, extra) elif header[0] == RwTypes.MATEFFECTS: res = self.readSectionMatEffects(header, extra) elif header[0] == RwTypes.MATSPECULAR: res = self.readSectionMatSpecular(header, extra) elif header[0] == RwTypes.MATREFLECTION: res = self.readSectionMatReflection(header, extra) elif header[0] == RwTypes.MESHEXTENSION: res = self.readSectionMeshExtension(header, extra) elif header[0] == RwTypes.RENDERRIGHTS: res = self.readSectionRenderRights(header, extra) elif header[0] == RwTypes.HANIMPLG: res = self.readSectionHAnimPLG(header, extra) elif header[0] == RwTypes.SKINPLG: res = self.readSectionSkinPLG(header, extra) elif header[0] == RwTypes.NIGHTCOLS: res = self.readSectionNightCols(header, extra) elif type >= 0: raise Exception("Missing read function for section type " + str(type)) else: print("Ignoring extension data of type " + hex(header[0])) self.f.seek(curPos + header[1]) return res def readSectionStruct(self, header): return header, self.f.read(header[1]) def readSectionString(self, header): byteList = b"" for i in range(header[1]): newByte = self.f.read(1) if newByte[0] == 0: break byteList += newByte return header, byteList.decode("ascii") def readSectionExtension(self, header, extra): endPos = self.f.tell() + header[1] while self.f.tell() < endPos: self.readSection(RwTypes.ANY, extra) return header, None def readSectionTexture(self, header, material): metaHeader, slice = self.readSection(RwTypes.STRUCT) (flags, x), slice = self.readSlice("HH", slice) x, texName = self.readSection(RwTypes.STRING) x, alphaName = self.readSection(RwTypes.STRING) if material.readenvmap: texture = self.RwTexture(self, material, texName, 1, material.envIntensity) material.setEnvTexture(texture) else: texture = self.RwTexture(self, material, texName, 0, 1) material.setTexture(texture) self.readSection(RwTypes.EXTENSION) return header, None def readSectionMaterial(self, header, geometry): metaHeader, slice = self.readSection(RwTypes.STRUCT) (flags,), slice = self.readSlice("I", slice) col, slice = self.readSlice("BBBB", slice) (x, textured, ambient, specular, diffuse), slice = self.readSlice("iifff", slice) material = self.RpMaterial(geometry, flags, col, textured, ambient, specular, diffuse) geometry.addMaterial(material) if textured > 0: self.readSection(RwTypes.TEXTURE, material) self.readSection(RwTypes.EXTENSION, material) return header, None def readSectionMaterialList(self, header, geometry): metaHeader, slice = self.readSection(RwTypes.STRUCT) (matCount,), slice = self.readSlice("i", slice) for i in range(matCount): junk, slice = self.readSlice("i", slice) for i in range(matCount): self.readSection(RwTypes.MATERIAL, geometry) return header, None def readSectionFrameList(self, header): metaHeader, slice = self.readSection(RwTypes.STRUCT) (frameCount,), slice = self.readSlice("i", slice) self.childrenOf = [] for i in range(frameCount+1): self.childrenOf.append([]) for i in range(frameCount): rot, slice = self.readSlice("fffffffff", slice) pos, slice = self.readSlice("fff", slice) (parent, flags), slice = self.readSlice("ii", slice) self.frames.append(self.RwFrame(self, i, rot, pos, parent)) for i in range(frameCount): self.readSection(RwTypes.EXTENSION, self.frames[i]) return header, None def readSectionGeometry(self, header, index): metaHeader, slice = self.readSection(RwTypes.STRUCT) (flags, texCount, triCount, vertCount, morphCount), slice = self.readSlice("HHiii", slice) geometry = self.RpGeometry(self, index) self.geoms.append(geometry) geometry.flags = flags if metaHeader[2] < 0x34001: (surfAmbient, surfSpecular, surfDiffuse), slice = self.readSlice("fff", slice) for i in range(vertCount): geometry.addVertex(self.RwVertex(None, None)) if flags & RpGeomFlag.PRELIT: geometry.vertCol = [] for i in range(vertCount): (vcr, vcg, vcb, vca), slice = self.readSlice("BBBB", slice) geometry.vertCol.append((vcr / 255, vcg / 255, vcb / 255)) for i in range(vertCount): uv, slice = self.readSlice("ff", slice) geometry.vertices[i].uv = (uv[0], 1-uv[1]) if texCount > 1: geometry.hasEnvUV = True for i in range(vertCount): uv_env, slice = self.readSlice("ff", slice) geometry.vertices[i].uv_env = (uv_env[0], 1-uv_env[1]) if texCount > 2: slice = slice[struct.calcsize("ff")*(texCount-2)*(vertCount):] for i in range(triCount): (c, b, mat, a), slice = self.readSlice("HHHH", slice) if a >= vertCount or b >= vertCount or c >= vertCount: raise Exception("Vertex indices out of range for triangle.") geometry.addTriangle(self.RwTriangle((a, b, c), mat)) if morphCount is not 1: raise Exception("Multiple frames not supported") for i in range(morphCount): (bx, by, bz, br, hasVerts, hasNormals), slice = self.readSlice("ffffii", slice) if hasVerts > 0: for j in range(vertCount): coords, slice = self.readSlice("fff", slice) geometry.vertices[j].coords = coords if hasNormals > 0: geometry.hasNormals = True for j in range(vertCount): normal, slice = self.readSlice("fff", slice) geometry.vertices[j].normal = normal self.readSection(RwTypes.MATERIALLIST, geometry) self.readSection(RwTypes.EXTENSION, geometry) return header, None def readSectionClump(self, header): metaHeader, slice = self.readSection(RwTypes.STRUCT) (atomicCount,), slice = self.readSlice("i", slice) if metaHeader[2] > 0x33000: (lightCount, cameraCount), slice = self.readSlice("ii", slice) self.readSection(RwTypes.FRAMELIST) self.readSection(RwTypes.GEOMETRYLIST) for i in range(atomicCount): self.readSection(RwTypes.ATOMIC) self.readSection(RwTypes.EXTENSION) return header, None def readSectionAtomic(self, header): metaHeader, slice = self.readSection(RwTypes.STRUCT) (frameIndex, geomIndex, flags, x, x, x, x), slice = self.readSlice("iiBBBBi", slice) atomic = self.RpAtomic(self, self.frames[frameIndex], self.geoms[geomIndex], flags) self.readSection(RwTypes.EXTENSION, atomic) return header, None def readSectionGeometryList(self, header): metaHeader, slice = self.readSection(RwTypes.STRUCT) (geomCount,), slice = self.readSlice("i", slice) for i in range(geomCount): self.readSection(RwTypes.GEOMETRY, i) def readSectionMorphPLG(self, header, geometry): return header, None def readSectionBinMeshPLG(self, header, geometry): slice = self.f.read(header[1]) (type, splits, total), slice = self.readSlice("iii", slice) if type != 0 and type != 1: print("Morph PLG section in unknown type - ignoring.") return header, None lookup = {} for i in range(len(geometry.triangles)): v = geometry.triangles[i].verts v = list(v) v.sort() lookup[tuple(v)] = i totals = 0 for i in range(splits): (sub, mat), slice = self.readSlice("ii", slice) if type == 0: for j in range(sub//3): vx, slice = self.readSlice("iii", slice) vx = list(vx) vx.sort() vx = tuple(vx) if vx in lookup: geometry.triangles[lookup[vx]].mat = mat else: elems = deque() for j in range(sub): if len(elems) > 2: elems.popleft() (item,), slice = self.readSlice("i", slice) if len(elems) > 1: checklist = [elems[0], elems[1], item] checklist.sort() check = tuple(checklist) if check in lookup: geometry.triangles[lookup[check]].mat = mat elems.append(item) return header, None def readSectionFrameName(self, header, frame): frame.name = self.f.read(header[1]).decode("ascii") return header, None def readSectionCollision(self, header, geometry): if not self.childrenOf or len(self.childrenOf[0]) is 0: print("Collision extension - no frame to attach to.") return header, None binary = self.f.read(header[1]) self.colhex = base64.b64encode(zlib.compress(binary)).decode("ascii") return header, None def readSectionMatEffects(self, header, parent): if parent.__class__ == self.RpMaterial: return self.readSectionMaterialMatEffects(header, parent) elif parent.__class__ == self.RpAtomic: return self.readSectionAtomicMatEffects(header, parent) return header, None def readSectionMaterialMatEffects(self, header, material): (flags,) = self.readFormat("I") for i in range(2): (effectType,) = self.readFormat("I") if effectType == 0: continue elif effectType != 2: print("Unknown material effect type.") return header, None (coefficient, frameBufferAlpha, textured) = self.readFormat("fii") if textured: material.readenvmap = True material.envIntensity = coefficient self.readSection(RwTypes.TEXTURE, material) def readSectionAtomicMatEffects(self, header, atomic): (check,) = self.readFormat("i") if check != 0: atomic.matfxpipe = True return header, None def readSectionMatSpecular(self, header, material): slice = self.f.read(header[1]) (intensity,), slice = self.readSlice("f", slice) specName = "" for i in range(len(slice)): if int(slice[i]) == 0: break specName += slice[i:i+1].decode("ascii") texture = self.RwTexture(self, material, specName, 2, intensity) material.setSpecTexture(texture) return header, None def readSectionMatReflection(self, header, material): slice = self.f.read(header[1]) colour, slice = self.readSlice("fff", slice) (x, intensity), slice = self.readSlice("ff", slice) material.setReflection(colour, intensity) return header, None def readSectionMeshExtension(self, header, geometry): slice = self.f.read(header[1]) (hasData,), slice = self.readSlice("i", slice) if hasData: print("Mesh extension extension actually has data. Not sure what to do with it.") return header, None def readSectionRenderRights(self, header, atomic): if not hasattr(atomic, "__class__") or atomic.__class__ != self.RpAtomic: print("Render rights extension is not in the right section, should be in atomic.") return slice = self.f.read(header[1]) (plugin, extra), slice = self.readSlice("ii", slice) atomic.setRenderRights(plugin, extra) def readSectionHAnimPLG(self, header, frame): if not hasattr(frame, "__class__") or frame.__class__ != self.RwFrame: print("HAnim extension is not in the right section, should be in frame.") return binary = self.f.read(header[1]) frame.hanimdata = base64.b64encode(zlib.compress(binary)).decode("ascii") return header, None def readSectionSkinPLG(self, header, geometry): if not hasattr(geometry, "__class__") or geometry.__class__ != self.RpGeometry: print("Skin extension is not in the right section, should be in geometry.") return binary = self.f.read(header[1]) geometry.skindata = base64.b64encode(zlib.compress(binary)).decode("ascii") return header, None def readSectionNightCols(self, header, geometry): if not hasattr(geometry, "__class__") or geometry.__class__ != self.RpGeometry: print("Night vertex colours extension is not in the right section, should be in geometry.") return slice = self.f.read(header[1]) (x,), slice = self.readSlice("I", slice) geometry.nightVertCol = [] for i in range(len(geometry.vertices)): (vcr, vcg, vcb, vca), slice = self.readSlice("BBBB", slice) geometry.nightVertCol.append((vcr / 255, vcg / 255, vcb / 255)) return header, None class ExportRenderware: class RwChunkHeader: def __init__(self, type, size): self.type = type self.size = size def bin(self): return struct.pack("III", self.type, self.size, ExportRenderware.targetVer) class RwVector3: def __init__(self, x, y, z): self.x = x self.y = y self.z = z def bin(self): return struct.pack("fff", self.x, self.y, self.z) class RwRotMatrix: def __init__(self): self.m = [1, 0, 0, 0, 1, 0, 0, 0, 1] def bin(self): return struct.pack("9f", *self.m) class RwFrameList: def __init__(self): self.R = ExportRenderware self.frames = [] def bin(self): payload = struct.pack("i", len(self.frames)) for frame in self.frames: payload += frame.binraw() payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload for frame in self.frames: payload += frame.binext() header = self.R.RwChunkHeader(RwTypes.FRAMELIST, len(payload)).bin() return header + payload class RwFrame: def __init__(self, clump, object, parentFrame): self.R = ExportRenderware self.clump = clump self.object = object self.index = len(clump.frameList.frames) clump.frameList.frames.append(self) self.name = self.object.name self.parent = parentFrame self.rotation = self.R.RwRotMatrix() self.position = self.R.RwVector3(0, 0, 0) if parentFrame is not None: ux = object.matrix_local.to_3x3() self.rotation.m = [ux[0][0], ux[0][1], ux[0][2], ux[1][0], ux[1][1], ux[1][2], ux[2][0], ux[2][1], ux[2][2]] self.position.x = object.matrix_local.translation[0] self.position.y = object.matrix_local.translation[1] self.position.z = object.matrix_local.translation[2] if str(object.type) == "MESH": self.atomic = self.R.RpAtomic(self) elif str(object.type) == "EMPTY": self.atomic = None else: raise Exception("Unsupported object type selected: " + str(object.type)) for child in self.object.children: if str(object.type) != "MESH" and str(object.type) != "EMPTY": print("Ignoring object " + object.name + ", type " + object.type) continue self.R.RwFrame(self.clump, child, self) if not clump.colbin: try: if len(object.collhex) > 0: textf = bpy.data.texts[object.collhex].as_string() clump.colbin = zlib.decompress(base64.b64decode(bytes(textf, "ascii"))) except: clump.colbin = None def binraw(self): payload = self.rotation.bin() payload += self.position.bin() payload += struct.pack("ii", -1 if self.parent is None else self.parent.index, 0) return payload def binext_name(self): noname = "noname_" if self.name[:len(noname)] == noname: return b"" writename = self.R.unmangleName(self.name) if len(writename) > 23: writename = writename[:23] print("Warning, frame name '", writename , "' truncated to 23 characters.") payload = struct.pack(str(len(writename)) + "s", bytearray(writename, "ascii")) header = self.R.RwChunkHeader(RwTypes.FRAMENAME, len(payload)).bin() return header + payload def binext_hanim(self): object = self.object try: if len(object.rw_hanimdata) > 0: textf = bpy.data.texts[object.rw_hanimdata].as_string() rawdata = zlib.decompress(base64.b64decode(bytes(textf, "ascii"))) else: return b"" except: return b"" payload = rawdata header = self.R.RwChunkHeader(RwTypes.HANIMPLG, len(payload)).bin() return header + payload def binext(self): payload = self.binext_name() + self.binext_hanim() header = self.R.RwChunkHeader(RwTypes.EXTENSION, len(payload)).bin() return header + payload class RpAtomicChunkInfo: def __init__(self, frameIndex, geometryIndex, flags): self.R = ExportRenderware self.frameIndex = frameIndex self.geometryIndex = geometryIndex self.flags = flags def bin(self): payload = struct.pack("iiii", self.frameIndex, self.geometryIndex, self.flags, 0) header = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() return header + payload class RpAtomic: def __init__(self, frame): self.R = ExportRenderware self.clump = frame.clump self.frame = frame self.mesh = frame.object.to_mesh(self.clump.context.scene, False, "PREVIEW") self.geometry = self.R.RpGeometry(self) self.flags = 5 def binext_rights(self): if self.frame.object.renderright == 0: return b"" payload = struct.pack("ii", self.frame.object.renderright, self.frame.object.renderextra) header = self.R.RwChunkHeader(RwTypes.RENDERRIGHTS, len(payload)).bin() return header + payload def binext_matfx(self): if self.frame.object.matfxpipe != True and self.R.decodedVer > 0x34003: return b"" payload = struct.pack("i", 1) header = self.R.RwChunkHeader(RwTypes.MATEFFECTS, len(payload)).bin() return header + payload def bin(self): payload = self.R.RpAtomicChunkInfo(self.frame.index, self.geometry.index, self.flags).bin() extensions = self.binext_rights() + self.binext_matfx() extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.ATOMIC, len(payload)).bin() return header + payload class RpVertex: def __init__(self, pos, uv, uve, normal): self.pos = pos self.uv = uv self.uve = uve self.normal = normal class RpTriangle: def __init__(self, a, b, c, mat): self.a = a self.b = b self.c = c self.mat = mat def bin(self): return struct.pack("HHHH", self.a, self.b, self.mat, self.c) class RwUVCoord: def __init__(self, u, v): self.u = u self.v = v def bin(self): return struct.pack("ff", self.u, 1-self.v) class RwTexture: def __init__(self, material, bltexslot): self.R = ExportRenderware self.material = material self.bltexslot = bltexslot self.bltex = bltexslot.texture def bin(self): payload = struct.pack("HH", 0x1106, 0) payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload strdata = struct.pack(str(len(self.bltex.name)) + "s", bytearray(self.bltex.name, "ascii")) for i in range(4 - (len(self.bltex.name)&3)): strdata += struct.pack("B", 0) payload += self.R.RwChunkHeader(RwTypes.STRING, len(strdata)).bin() + strdata strdata = struct.pack("i", 0) payload += self.R.RwChunkHeader(RwTypes.STRING, len(strdata)).bin() + strdata extensions = b"" extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.TEXTURE, len(payload)).bin() return header + payload class RpMaterial: def __init__(self, materialList, blMaterial): self.R = ExportRenderware self.materialList = materialList self.index = len(materialList.mats) self.mesh = materialList.mesh self.blmaterial = blMaterial self.red = min(255, max(0, blMaterial.diffuse_color[0] * 256)) self.green = min(255, max(0, blMaterial.diffuse_color[1] * 256)) self.blue = min(255, max(0, blMaterial.diffuse_color[2] * 256)) self.alpha = min(255, max(0, blMaterial.alpha * 256)) self.ambient = blMaterial.ambient self.specular = blMaterial.specular_intensity self.diffuse = blMaterial.diffuse_intensity self.bltex_diffuse = self.findTexSlot("DIFFUSE") self.bltex_specular = self.findTexSlot("SPECULAR") self.bltex_envmap = self.findTexSlot("ENVMAP") self.tex_diffuse = None self.tex_envmap = None if self.bltex_diffuse: self.tex_diffuse = self.R.RwTexture(self, self.bltex_diffuse) if self.bltex_diffuse.texture_coords == "UV" and len(self.bltex_diffuse.uv_layer) > 0 and not self.materialList.geometry.uvname_diff: self.materialList.geometry.uvname_diff = self.bltex_diffuse.uv_layer if self.bltex_envmap: self.tex_envmap = self.R.RwTexture(self, self.bltex_envmap) if self.bltex_envmap.texture_coords == "UV" and len(self.bltex_envmap.uv_layer) > 0 and not self.materialList.geometry.uvname_env: self.materialList.geometry.uvname_env = self.bltex_envmap.uv_layer def findTexSlot(self, type): for i in range(len(self.blmaterial.texture_slots)): textype = "" slot = self.blmaterial.texture_slots[i] if slot and slot.texture: if slot.texture.type == "ENVIRONMENT_MAP": textype = "ENVMAP" elif slot.use_map_color_spec and not slot.use_map_color_diffuse: textype = "SPECULAR" elif slot.use_map_color_diffuse and not slot.use_map_color_spec: textype = "DIFFUSE" if textype == type: return slot return None def binext_matfx(self): if not self.tex_envmap: return b"" payload = struct.pack("iifii", 2, 2, self.bltex_envmap.specular_color_factor, 0, 1) payload += self.tex_envmap.bin() payload += struct.pack("i", 0) header = self.R.RwChunkHeader(RwTypes.MATEFFECTS, len(payload)).bin() return header + payload def binext_reflect(self): if not self.blmaterial.raytrace_mirror.use and ExportRenderware.decodedVer <= 0x34003: return b"" factor = self.blmaterial.raytrace_mirror.reflect_factor if self.blmaterial.raytrace_mirror.use else 0 colour = self.blmaterial.mirror_color payload = struct.pack("fffffi", colour[0], colour[1], colour[2], 1, self.blmaterial.raytrace_mirror.reflect_factor, 0) header = self.R.RwChunkHeader(RwTypes.MATREFLECTION, len(payload)).bin() return header + payload def binext_specular(self): if not self.bltex_specular: return b"" payload = struct.pack("f", self.bltex_specular.specular_color_factor) texname = bytes(self.bltex_specular.texture.name, "ascii") payload += texname[:23] nullbyte = struct.pack("B", 0) for i in range(24 - min(23, len(texname))): payload += nullbyte header = self.R.RwChunkHeader(RwTypes.MATSPECULAR, len(payload)).bin() return header + payload def bin(self): payload = struct.pack("iBBBBiIfff", 0, int(self.red), int(self.green), int(self.blue), int(self.alpha), 0, 1 if self.tex_diffuse else 0, self.ambient, self.specular, self.diffuse) payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload if self.tex_diffuse: payload += self.tex_diffuse.bin() extensions = self.binext_matfx() + self.binext_reflect() + self.binext_specular() extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.MATERIAL, len(payload)).bin() return header + payload class RpMaterialList: def __init__(self, geometry): self.R = ExportRenderware self.geometry = geometry self.clump = geometry.clump self.mesh = geometry.mesh self.mats = [] for mat in self.mesh.materials: self.mats.append(self.R.RpMaterial(self, mat)) def bin(self): payload = struct.pack("i", len(self.mesh.materials)) for mat in self.mats: payload += struct.pack("i", -1) payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload for mat in self.mats: payload += mat.bin() header = self.R.RwChunkHeader(RwTypes.MATERIALLIST, len(payload)).bin() return header + payload class RpGeometryList: def __init__(self): self.R = ExportRenderware self.geoms = [] def bin(self): payload = struct.pack("i", len(self.geoms)) payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload for geom in self.geoms: payload += geom.bin() header = self.R.RwChunkHeader(RwTypes.GEOMETRYLIST, len(payload)).bin() return header + payload class RpGeometryChunkInfo: def __init__(self): self.flags = RpGeomFlag.TEXTURED | RpGeomFlag.NORMALS | RpGeomFlag.LIGHT | RpGeomFlag.MODULATEMATERIALCOLOR self.texCount = 1 self.triangleCount = 0 self.vertexCount = 0 self.frameCount = 1 def binraw(self): return struct.pack("HHiii", self.flags, self.texCount, self.triangleCount, self.vertexCount, self.frameCount) class RpGeometry: def __init__(self, atomic): self.R = ExportRenderware self.clump = atomic.clump self.atomic = atomic self.mesh = atomic.mesh self.index = len(self.clump.geometryList.geoms) self.clump.geometryList.geoms.append(self) self.chunkInfo = self.R.RpGeometryChunkInfo() self.uvname_diff = None self.uvname_env = None self.materialList = self.R.RpMaterialList(self) self.matTris = [] for i in range(len(self.materialList.mats)): self.matTris.append([]) mesh = self.mesh self.vdict = [] for i in range(len(mesh.vertices)): self.vdict.append({}) self.uvc = self.getUVData(self.uvname_diff) self.uvce = None if self.uvname_env and self.uvname_env != self.uvname_diff: self.uvce = self.getUVData(self.uvname_env) self.vertices = [] self.triangles = [] self.vertCol = None self.nightVertCol = None self.vertColData = None self.nightVertColData = None for vcol in self.mesh.vertex_colors: if vcol.name.lower() == "night" and self.nightVertCol is None: self.nightVertCol = [] self.nightVertColData = vcol.data elif self.vertCol is None: self.vertCol = [] self.vertColData = vcol.data for poly in mesh.polygons: self.addBlenderPoly(poly) if len(self.vertices) > 65535: raise Exception("Aborting export: vertex count exceeds 65535") self.maxDist = 0 for v in self.mesh.vertices: self.maxDist = max(self.maxDist, math.sqrt(v.co[0]*v.co[0] + v.co[1]*v.co[1] + v.co[2]*v.co[2])) self.chunkInfo.triangleCount = len(self.triangles) self.chunkInfo.vertexCount = len(self.vertices) if self.uvce: self.chunkInfo.texCount = 2 self.chunkInfo.flags = self.chunkInfo.flags & (~RpGeomFlag.TEXTURED) self.chunkInfo.flags |= RpGeomFlag.TEXTURED2 if self.R.decodedVer > 0x34003: self.chunkInfo.flags |= RpGeomFlag.POSITIONS if self.vertColData: self.chunkInfo.flags |= RpGeomFlag.PRELIT def findVertex(self, type): for i in range(len(self.blmaterial.texture_slots)): textype = "" slot = self.blmaterial.texture_slots[i] if slot and slot.texture: if slot.texture.type == "ENVIRONMENT_MAP": textype = "ENVMAP" elif slot.use_map_color_spec and not slot.use_map_color_diffuse: textype = "SPECULAR" elif slot.use_map_color_diffuse and not slot.use_map_color_spec: textype = "DIFFUSE" if textype == type: return slot return None def getUVData(self, name): for i in range(len(self.mesh.uv_textures)): if name and self.mesh.uv_textures[i] and self.mesh.uv_textures[i].name == name: return self.mesh.uv_layers[i].data return None def newVertId(self, id, uv, uve): if (uv + uve) not in self.vdict[id]: self.vdict[id][uv + uve] = len(self.vertices) self.vertices.append(self.R.RpVertex(self.mesh.vertices[id].co, uv, uve, self.mesh.vertices[id].normal)) if self.vertColData: self.vertCol.append((int(self.vertColData[id].color[0]*255), int(self.vertColData[id].color[1]*255), int(self.vertColData[id].color[2]*255))) if self.nightVertColData: self.nightVertCol.append((int(self.nightVertColData[id].color[0]*255), int(self.nightVertColData[id].color[1]*255), int(self.nightVertColData[id].color[2]*255))) return self.vdict[id][(uv + uve)] def addRawPoly(self, verts, uvs, mat): newIds = [] for i in range(3): uv = tuple(self.uvc[uvs[i]].uv) if self.uvc else (0, 0) uve = tuple(self.uvce[uvs[i]].uv) if self.uvce else (0, 0) newIds.append(self.newVertId(verts[i], uv, uve)) self.triangles.append(self.R.RpTriangle(newIds[0], newIds[1], newIds[2], mat)) if mat >= 0: self.matTris[mat].append(newIds[0]) self.matTris[mat].append(newIds[1]) self.matTris[mat].append(newIds[2]) def addBlenderPoly(self, p): if len(p.vertices) < 3 or len(p.vertices) > 4: raise Exception("Aborting export: Invalid number of vertices on an edge.") self.addRawPoly([p.vertices[0], p.vertices[1], p.vertices[2]], [p.loop_indices[0], p.loop_indices[1], p.loop_indices[2]], p.material_index) if len(p.vertices) == 4: self.addRawPoly([p.vertices[0], p.vertices[3], p.vertices[2]], [p.loop_indices[0], p.loop_indices[3], p.loop_indices[2]], p.material_index) def binext_binmesh(self): payload = b"" splits = 0 total = 0 for i in range(len(self.matTris)): if len(self.matTris[i]) == 0: continue splits += 1 total += len(self.matTris[i]) payload += struct.pack("ii", len(self.matTris[i]), i) for id in self.matTris[i]: payload += struct.pack("i", id) payload = struct.pack("iii", 0, splits, total) + payload header = self.R.RwChunkHeader(RwTypes.BINMESHPLG, len(payload)).bin() return header + payload def binext_morph(self): if self.R.decodedVer > 0x34003 or self.R.decodedVer < 0x33000: return b"" payload = struct.pack("i", 0) header = self.R.RwChunkHeader(RwTypes.MORPHPLG, len(payload)).bin() return header + payload def binext_meshext(self): if self.R.decodedVer <= 0x34003: return b"" payload = struct.pack("i", 0) header = self.R.RwChunkHeader(RwTypes.MESHEXTENSION, len(payload)).bin() return header + payload def binext_skin(self): object = self.atomic.frame.object try: if len(object.rw_skindata) > 0: textf = bpy.data.texts[object.rw_skindata].as_string() rawdata = zlib.decompress(base64.b64decode(bytes(textf, "ascii"))) else: return b"" except: return b"" payload = rawdata header = self.R.RwChunkHeader(RwTypes.SKINPLG, len(payload)).bin() return header + payload def binext_nightcol(self): if not self.nightVertCol: return b"" payload = struct.pack("I", 1) for col in self.nightVertCol: payload += struct.pack("BBBB", col[0], col[1], col[2], 255) header = self.R.RwChunkHeader(RwTypes.NIGHTCOLS, len(payload)).bin() return header + payload def bin(self): payload = self.chunkInfo.binraw() if self.R.decodedVer < 0x34001: payload += struct.pack("fff", 0, 0, 1) if self.vertCol: for col in self.vertCol: payload += struct.pack("BBBB", col[0], col[1], col[2], 255) for vertex in self.vertices: payload += self.R.RwUVCoord(vertex.uv[0], vertex.uv[1]).bin() if self.uvce: for vertex in self.vertices: payload += self.R.RwUVCoord(vertex.uve[0], vertex.uve[1]).bin() for triangle in self.triangles: payload += triangle.bin() payload += struct.pack("ffffii", 0, 0, 0, self.maxDist, 1, 1) for vertex in self.vertices: payload += self.R.RwVector3(vertex.pos[0], vertex.pos[1], vertex.pos[2]).bin() for vertex in self.vertices: payload += self.R.RwVector3(vertex.normal[0], vertex.normal[1], vertex.normal[2]).bin() payload = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() + payload payload += self.materialList.bin() extensions = self.binext_binmesh() + self.binext_skin() + self.binext_morph() + self.binext_meshext() + self.binext_nightcol() extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.GEOMETRY, len(payload)).bin() return header + payload class RpClumpChunkInfo: def __init__(self, atomicCount, lightCount, cameraCount): self.R = ExportRenderware self.atomicCount = atomicCount self.lightCount = lightCount self.cameraCount = cameraCount def bin(self): payload = struct.pack("i", self.atomicCount) if self.R.decodedVer > 0x33000: payload += struct.pack("ii", self.lightCount, self.cameraCount) header = self.R.RwChunkHeader(RwTypes.STRUCT, len(payload)).bin() return header + payload class RpClump: def __init__(self, context, exportVer): self.R = ExportRenderware self.R.targetVer = exportVer self.R.decodedVer = RwTypes.decodeVersion(self.R.targetVer) self.context = context self.frameList = self.R.RwFrameList() self.geometryList = self.R.RpGeometryList() self.colbin = None exportables = [] for object in context.selected_objects: parent = object.parent add = True while parent: if parent in context.selected_objects: add = False break parent = parent.parent if add: exportables.append(object) for object in exportables: if str(object.type) != "MESH" and str(object.type) != "EMPTY": print("Ignoring object " + object.name + ", type " + object.type) continue self.R.RwFrame(self, object, None) if len(self.frameList.frames) == 0: raise Exception("Aborting export: no frames selected.") def binext_coll(self): if not self.colbin: return b"" payload = self.colbin header = self.R.RwChunkHeader(RwTypes.COLLISION, len(self.colbin)).bin() return header + payload def bin(self): payload = self.R.RpClumpChunkInfo(len(self.geometryList.geoms), 0, 0).bin() payload += self.frameList.bin() payload += self.geometryList.bin() for geometry in self.geometryList.geoms: payload += geometry.atomic.bin() extensions = self.binext_coll() extensions = self.R.RwChunkHeader(RwTypes.EXTENSION, len(extensions)).bin() + extensions payload += extensions header = self.R.RwChunkHeader(RwTypes.CLUMP, len(payload)).bin() return header + payload def __init__(self, context, exportVerIndex, filepath): if exportVerIndex == "1": exportVer = 0x0800FFFF elif exportVerIndex == "2": exportVer = 0x1003FFFF else: exportVer = 0x1803FFFF outf = open(filepath, "wb") outf.write(self.RpClump(context, exportVer).bin()) outf.close() def unmangleName(name): if len(name) > 4 and name[-4] == "." and name[-3:].isnumeric(): return name[:-4] else: return name class ExportRenderwareMenu(bpy.types.Operator): expVersionValues = (("1", "GTA III", ""), ("2", "Vice City", ""), ("3", "San Andreas", "")) bl_idname = "export_rw.dff" bl_label = "Export Renderware (.dff)" filename_ext = ".dff" filepath = StringProperty(subtype = "FILE_PATH") expVersion = EnumProperty(name = "Export version", items = expVersionValues, default="2") def invoke(self, context, event): wm = context.window_manager wm.fileselect_add(self) return {"RUNNING_MODAL"} def execute(self, context): setupProps() ExportRenderware(context, self.expVersion, self.filepath) return {"FINISHED"} class ImportRenderwareMenu(bpy.types.Operator): bl_idname = "import_rw.dff" bl_label = "Import Renderware (.dff)" filename_ext = ".dff" filepath = StringProperty(subtype = "FILE_PATH") def invoke(self, context, event): wm = context.window_manager wm.fileselect_add(self) return {"RUNNING_MODAL"} def execute(self, context): setupProps() ImportRenderware(self.filepath) return {"FINISHED"} def export_func(self, context): self.layout.operator(ExportRenderwareMenu.bl_idname, text="Renderware (.dff)") def import_func(self, context): self.layout.operator(ImportRenderwareMenu.bl_idname, text="Renderware (.dff)") def register(): bpy.utils.register_module(__name__) bpy.types.INFO_MT_file_export.append(export_func) bpy.types.INFO_MT_file_import.append(import_func) def unregister(): bpy.utils.unregister_module(__name__) bpy.types.INFO_MT_file_export.remove(export_func) bpy.types.INFO_MT_file_import.remove(import_func) def setupProps(): class renderwarePanel(bpy.types.Panel): bl_space_type = "VIEW_3D" bl_region_type = "UI" bl_label = "Renderware" def draw(self, context): self.layout.prop(bpy.context.active_object, "renderright") self.layout.prop(bpy.context.active_object, "renderextra") self.layout.prop(bpy.context.active_object, "matfxpipe") self.layout.prop(bpy.context.active_object, "collhex") self.layout.prop(bpy.context.active_object, "rw_hanimdata") self.layout.prop(bpy.context.active_object, "rw_skindata") if hasattr(bpy.types.Object, "collhex"): return bpy.types.Object.collhex = bpy.props.StringProperty(name = "Collision", description = "Name of the text object that contains collision binary data.", maxlen = 100) bpy.types.Object.renderright = bpy.props.IntProperty(name = "RenderRight", description = "Index of the plugin whose pipeline is used for rendering.") bpy.types.Object.renderextra = bpy.props.IntProperty(name = "RenderExtra", description = "Extra arguments to the render pipeline.") bpy.types.Object.matfxpipe = bpy.props.BoolProperty(name = "MatFX pipeline", description = "Whether rendering is handled by MatFX pipeline.") bpy.types.Object.rw_hanimdata = bpy.props.StringProperty(name = "HAnimData", description = "Info for this skin bone.", maxlen = 100) bpy.types.Object.rw_skindata = bpy.props.StringProperty(name = "SkinData", description = "Skin data (bone vertices etc) for this mesh.", maxlen = 100) bpy.utils.register_class(renderwarePanel) if __name__ == "__main__": unregister() register() setupProps()

true

f718a33508e80df74065a9e4fa1542458bff559b

2,125

py

Python

formatdata/bin/extract_ref_bimf.py

lvclark/h3agwas

5e42e60123b819d3c331a91b25ee50846e55af3b

[ "MIT" ]

62

2016-08-29T11:27:35.000Z

2022-03-10T17:16:14.000Z

formatdata/bin/extract_ref_bimf.py

lvclark/h3agwas

5e42e60123b819d3c331a91b25ee50846e55af3b

[ "MIT" ]

33

2016-12-26T13:48:19.000Z

2021-12-05T13:34:06.000Z

formatdata/bin/extract_ref_bimf.py

lvclark/h3agwas

5e42e60123b819d3c331a91b25ee50846e55af3b

[ "MIT" ]

50

2017-04-15T04:17:43.000Z

2022-03-30T07:26:01.000Z

#!/usr/bin/env python3 import sys import os import argparse import gzip def readfastagz(File) : Dic={} with gzip.open(File, "r") as ReadL : for ligne in ReadL: ligne=ligne.decode('utf-8').replace('\n','') if ligne[0]=='>' : Key=ligne.split(' ')[0].split('|')[0].split('\t')[0].replace('>','') if Key in Dic : print(Dic.keys()) print('fasta file '+ File+' more than one time same chro '+ Key) sys.exit(2) Dic[Key]="" Dic[Key]+=ligne return Dic def readfastastdin() : Dic={} for ligne in sys.stdin: ligne=ligne.replace('\n','') if ligne[0]=='>' : Key=ligne.split(' ')[0].split('|')[0].split('\t')[0].replace('>','') if Key in Dic : print(Dic.keys()) print('fasta file '+ File+' more than one time same chro '+ Key) sys.exit(2) Dic[Key]="" Dic[Key]+=ligne return Dic def parseArguments(): parser = argparse.ArgumentParser(description='transform file and header') parser.add_argument('--bim',type=str,required=True, help="input file association") parser.add_argument('--fasta',type=str,required=False, help="input file association") parser.add_argument('--out',type=str,required=True, help="input file association") parser.add_argument('--run', type=str, required=False, default='False') args = parser.parse_args() return args args=parseArguments() if args.run[0]=='T': if args.fasta : fasta=readfastagz(args.fasta) else : fasta=readfastastdin() readbim=open(args.bim) writetodel=open(args.out+'.del') writeref=open(args.out+'.allref') for line in readbim: spll=line.split() chro=spll[0] #0 200610-10 0 0 C T #26 200610-37 0 16482 G A if chro in fasta : pos=int(spll[3]) all1=spll[4] all2=spll[5] allref=fasta[chro][pos-1] if allref == all1 or allref == all2: writeref.write(spll[1]+'\t'+allref+'\n') writetodel.write("\t".join([chro,str(pos),spll[1],spll[4], spll[5], allref])+'\n') else : writetodel.write("\t".join([chro,str(pos),spll[1],spll[4], spll[5], "NA"])+'\n')

29.513889

91

0.602353

import sys import os import argparse import gzip def readfastagz(File) : Dic={} with gzip.open(File, "r") as ReadL : for ligne in ReadL: ligne=ligne.decode('utf-8').replace('\n','') if ligne[0]=='>' : Key=ligne.split(' ')[0].split('|')[0].split('\t')[0].replace('>','') if Key in Dic : print(Dic.keys()) print('fasta file '+ File+' more than one time same chro '+ Key) sys.exit(2) Dic[Key]="" Dic[Key]+=ligne return Dic def readfastastdin() : Dic={} for ligne in sys.stdin: ligne=ligne.replace('\n','') if ligne[0]=='>' : Key=ligne.split(' ')[0].split('|')[0].split('\t')[0].replace('>','') if Key in Dic : print(Dic.keys()) print('fasta file '+ File+' more than one time same chro '+ Key) sys.exit(2) Dic[Key]="" Dic[Key]+=ligne return Dic def parseArguments(): parser = argparse.ArgumentParser(description='transform file and header') parser.add_argument('--bim',type=str,required=True, help="input file association") parser.add_argument('--fasta',type=str,required=False, help="input file association") parser.add_argument('--out',type=str,required=True, help="input file association") parser.add_argument('--run', type=str, required=False, default='False') args = parser.parse_args() return args args=parseArguments() if args.run[0]=='T': if args.fasta : fasta=readfastagz(args.fasta) else : fasta=readfastastdin() readbim=open(args.bim) writetodel=open(args.out+'.del') writeref=open(args.out+'.allref') for line in readbim: spll=line.split() chro=spll[0] if chro in fasta : pos=int(spll[3]) all1=spll[4] all2=spll[5] allref=fasta[chro][pos-1] if allref == all1 or allref == all2: writeref.write(spll[1]+'\t'+allref+'\n') writetodel.write("\t".join([chro,str(pos),spll[1],spll[4], spll[5], allref])+'\n') else : writetodel.write("\t".join([chro,str(pos),spll[1],spll[4], spll[5], "NA"])+'\n')

true

f718a3bfab465e69af8eecdfc4731de81a8437f6

3,893

py

Python

deletionwatcher.py

Floern/SmokeDetector

2818bbd23af15440836c61c4023d063264433c66

[ "Apache-2.0", "MIT" ]

null

deletionwatcher.py

Floern/SmokeDetector

2818bbd23af15440836c61c4023d063264433c66

[ "Apache-2.0", "MIT" ]

null

deletionwatcher.py

Floern/SmokeDetector

2818bbd23af15440836c61c4023d063264433c66

[ "Apache-2.0", "MIT" ]

1

2018-10-11T13:41:49.000Z

# coding=utf-8 import json import requests import time # noinspection PyPackageRequirements import websocket # noinspection PyPackageRequirements from bs4 import BeautifulSoup from threading import Thread from urllib.parse import urlparse import metasmoke from globalvars import GlobalVars import datahandling # noinspection PyClassHasNoInit,PyBroadException,PyMethodParameters class DeletionWatcher: @classmethod def update_site_id_list(self): soup = BeautifulSoup(requests.get("https://meta.stackexchange.com/topbar/site-switcher/site-list").text, "html.parser") site_id_dict = {} for site in soup.findAll("a", attrs={"data-id": True}): site_name = urlparse(site["href"]).netloc site_id = site["data-id"] site_id_dict[site_name] = site_id GlobalVars.site_id_dict = site_id_dict @classmethod def check_websocket_for_deletion(self, post_site_id, post_url, timeout): time_to_check = time.time() + timeout post_id = post_site_id[0] post_type = post_site_id[2] if post_type == "answer": question_id = str(datahandling.get_post_site_id_link(post_site_id)) if question_id is None: return else: question_id = post_id post_site = post_site_id[1] if post_site not in GlobalVars.site_id_dict: return site_id = GlobalVars.site_id_dict[post_site] ws = websocket.create_connection("wss://qa.sockets.stackexchange.com/") ws.send(site_id + "-question-" + question_id) while time.time() < time_to_check: ws.settimeout(time_to_check - time.time()) try: a = ws.recv() except websocket.WebSocketTimeoutException: t_metasmoke = Thread(name="metasmoke send deletion stats", target=metasmoke.Metasmoke.send_deletion_stats_for_post, args=(post_url, False)) t_metasmoke.start() return False if a is not None and a != "": try: action = json.loads(a)["action"] if action == "hb": ws.send("hb") continue else: d = json.loads(json.loads(a)["data"]) except: continue if d["a"] == "post-deleted" and str(d["qId"]) == question_id \ and ((post_type == "answer" and "aId" in d and str(d["aId"]) == post_id) or post_type == "question"): t_metasmoke = Thread(name="metasmoke send deletion stats", target=metasmoke.Metasmoke.send_deletion_stats_for_post, args=(post_url, True)) t_metasmoke.start() return True t_metasmoke = Thread(name="metasmoke send deletion stats", target=metasmoke.Metasmoke.send_deletion_stats_for_post, args=(post_url, False)) t_metasmoke.start() return False @classmethod def check_if_report_was_deleted(self, post_site_id, post_url, message): was_report_deleted = self.check_websocket_for_deletion(post_site_id, post_url, 1200) if was_report_deleted: try: message.delete() except: pass @classmethod def post_message_if_not_deleted(self, post_site_id, post_url, message_text, room): was_report_deleted = self.check_websocket_for_deletion(post_site_id, post_url, 300) if not was_report_deleted and not datahandling.is_false_positive(post_site_id[0:2]) and not \ datahandling.is_ignored_post(post_site_id[0:2]): room.send_message(message_text)

40.552083

120

0.599281

import json import requests import time import websocket from bs4 import BeautifulSoup from threading import Thread from urllib.parse import urlparse import metasmoke from globalvars import GlobalVars import datahandling class DeletionWatcher: @classmethod def update_site_id_list(self): soup = BeautifulSoup(requests.get("https://meta.stackexchange.com/topbar/site-switcher/site-list").text, "html.parser") site_id_dict = {} for site in soup.findAll("a", attrs={"data-id": True}): site_name = urlparse(site["href"]).netloc site_id = site["data-id"] site_id_dict[site_name] = site_id GlobalVars.site_id_dict = site_id_dict @classmethod def check_websocket_for_deletion(self, post_site_id, post_url, timeout): time_to_check = time.time() + timeout post_id = post_site_id[0] post_type = post_site_id[2] if post_type == "answer": question_id = str(datahandling.get_post_site_id_link(post_site_id)) if question_id is None: return else: question_id = post_id post_site = post_site_id[1] if post_site not in GlobalVars.site_id_dict: return site_id = GlobalVars.site_id_dict[post_site] ws = websocket.create_connection("wss://qa.sockets.stackexchange.com/") ws.send(site_id + "-question-" + question_id) while time.time() < time_to_check: ws.settimeout(time_to_check - time.time()) try: a = ws.recv() except websocket.WebSocketTimeoutException: t_metasmoke = Thread(name="metasmoke send deletion stats", target=metasmoke.Metasmoke.send_deletion_stats_for_post, args=(post_url, False)) t_metasmoke.start() return False if a is not None and a != "": try: action = json.loads(a)["action"] if action == "hb": ws.send("hb") continue else: d = json.loads(json.loads(a)["data"]) except: continue if d["a"] == "post-deleted" and str(d["qId"]) == question_id \ and ((post_type == "answer" and "aId" in d and str(d["aId"]) == post_id) or post_type == "question"): t_metasmoke = Thread(name="metasmoke send deletion stats", target=metasmoke.Metasmoke.send_deletion_stats_for_post, args=(post_url, True)) t_metasmoke.start() return True t_metasmoke = Thread(name="metasmoke send deletion stats", target=metasmoke.Metasmoke.send_deletion_stats_for_post, args=(post_url, False)) t_metasmoke.start() return False @classmethod def check_if_report_was_deleted(self, post_site_id, post_url, message): was_report_deleted = self.check_websocket_for_deletion(post_site_id, post_url, 1200) if was_report_deleted: try: message.delete() except: pass @classmethod def post_message_if_not_deleted(self, post_site_id, post_url, message_text, room): was_report_deleted = self.check_websocket_for_deletion(post_site_id, post_url, 300) if not was_report_deleted and not datahandling.is_false_positive(post_site_id[0:2]) and not \ datahandling.is_ignored_post(post_site_id[0:2]): room.send_message(message_text)

true

f718a4274f3aa4ad39db83b7e97ebcddc1e14a69

3,159

py

Python

NLP/code.py

prasadph/ga-learner-dsmp-repo

ac1cc9d96250718f2842592e643c885d54ab2903

[ "MIT" ]

1

2021-01-18T15:24:07.000Z

NLP/code.py

prasadph/ga-learner-dsmp-repo

ac1cc9d96250718f2842592e643c885d54ab2903

[ "MIT" ]

null

NLP/code.py

prasadph/ga-learner-dsmp-repo

ac1cc9d96250718f2842592e643c885d54ab2903

[ "MIT" ]

1

2019-05-01T04:24:19.000Z

# -------------- # import packages import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns import re from nltk.corpus import stopwords from sklearn.model_selection import train_test_split from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer from sklearn.naive_bayes import MultinomialNB from sklearn.multiclass import OneVsRestClassifier from sklearn.linear_model import LogisticRegression from sklearn.metrics import accuracy_score ,confusion_matrix # Code starts here # load data news = pd.read_csv(path) # subset data news = news[["TITLE","CATEGORY"]] # distribution of classes dist = news.CATEGORY.value_counts() # display class distribution print(dist) # display data print(news.head()) # Code ends here # -------------- # Code starts here # stopwords stop = set(stopwords.words('english')) # retain only alphabets news.TITLE = news.TITLE.apply(lambda x:re.sub("[^a-zA-Z]", " ",x)) # convert to lowercase and tokenize news.TITLE = news.TITLE.apply(lambda row:row.lower().split()) # remove stopwords news.TITLE = news.TITLE.apply(lambda row:[i for i in row if i not in stop] ) # join list elements news.TITLE = news.TITLE.apply(lambda x: ' '.join(x)) # split into training and test sets X_train, X_test, y_train, y_test = train_test_split(news['TITLE'], news['CATEGORY'], test_size=0.2, random_state=3) # Code ends here # -------------- # Code starts here # initialize count vectorizer count_vectorizer = CountVectorizer() # initialize tfidf vectorizer tfidf_vectorizer = TfidfVectorizer(ngram_range=(1,3)) # fit and transform with count vectorizer X_train_count = count_vectorizer.fit_transform(X_train) X_test_count = count_vectorizer.transform(X_test) # fit and transform with tfidf vectorizer X_train_tfidf = tfidf_vectorizer.fit_transform(X_train) X_test_tfidf = tfidf_vectorizer.transform(X_test) # Code ends here # -------------- # Code starts here # initialize multinomial naive bayes nb_1 = MultinomialNB() nb_2 = MultinomialNB() # fit on count vectorizer training data nb_1.fit(X_train_count, y_train) # fit on tfidf vectorizer training data nb_2.fit(X_train_tfidf, y_train) # accuracy with count vectorizer acc_count_nb = accuracy_score(nb_1.predict(X_test_count), y_test) # accuracy with tfidf vectorizer acc_tfidf_nb = accuracy_score(nb_2.predict(X_test_tfidf), y_test) # display accuracies print(acc_count_nb) print(acc_tfidf_nb) # Code ends here # -------------- import warnings warnings.filterwarnings('ignore') # initialize logistic regression logreg_1 = OneVsRestClassifier(LogisticRegression(random_state=10)) logreg_2 = OneVsRestClassifier(LogisticRegression(random_state=10)) # fit on count vectorizer training data logreg_1.fit(X_train_count, y_train) # fit on tfidf vectorizer training data logreg_2.fit(X_train_tfidf, y_train) # accuracy with count vectorizer acc_count_logreg = accuracy_score(logreg_1.predict(X_test_count), y_test) # accuracy with tfidf vectorizer acc_tfidf_logreg = accuracy_score(logreg_2.predict(X_test_tfidf), y_test) # display accuracies print(acc_count_logreg) print(acc_tfidf_logreg) # Code ends here

24.874016

115

0.773663

import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns import re from nltk.corpus import stopwords from sklearn.model_selection import train_test_split from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer from sklearn.naive_bayes import MultinomialNB from sklearn.multiclass import OneVsRestClassifier from sklearn.linear_model import LogisticRegression from sklearn.metrics import accuracy_score ,confusion_matrix news = pd.read_csv(path) news = news[["TITLE","CATEGORY"]] dist = news.CATEGORY.value_counts() print(dist) print(news.head()) stop = set(stopwords.words('english')) news.TITLE = news.TITLE.apply(lambda x:re.sub("[^a-zA-Z]", " ",x)) news.TITLE = news.TITLE.apply(lambda row:row.lower().split()) news.TITLE = news.TITLE.apply(lambda row:[i for i in row if i not in stop] ) news.TITLE = news.TITLE.apply(lambda x: ' '.join(x)) X_train, X_test, y_train, y_test = train_test_split(news['TITLE'], news['CATEGORY'], test_size=0.2, random_state=3) count_vectorizer = CountVectorizer() tfidf_vectorizer = TfidfVectorizer(ngram_range=(1,3)) X_train_count = count_vectorizer.fit_transform(X_train) X_test_count = count_vectorizer.transform(X_test) X_train_tfidf = tfidf_vectorizer.fit_transform(X_train) X_test_tfidf = tfidf_vectorizer.transform(X_test) nb_1 = MultinomialNB() nb_2 = MultinomialNB() nb_1.fit(X_train_count, y_train) nb_2.fit(X_train_tfidf, y_train) acc_count_nb = accuracy_score(nb_1.predict(X_test_count), y_test) acc_tfidf_nb = accuracy_score(nb_2.predict(X_test_tfidf), y_test) print(acc_count_nb) print(acc_tfidf_nb) import warnings warnings.filterwarnings('ignore') logreg_1 = OneVsRestClassifier(LogisticRegression(random_state=10)) logreg_2 = OneVsRestClassifier(LogisticRegression(random_state=10)) logreg_1.fit(X_train_count, y_train) logreg_2.fit(X_train_tfidf, y_train) acc_count_logreg = accuracy_score(logreg_1.predict(X_test_count), y_test) acc_tfidf_logreg = accuracy_score(logreg_2.predict(X_test_tfidf), y_test) print(acc_count_logreg) print(acc_tfidf_logreg)

true

f718a4ee414e973fde7694a37fb7480545ae3804

3,814

py

Python

onnx/backend/test/case/node/xor.py

okdshin/onnx

31ca96ca3331d05884a71c38975d34870eb9c81d

[ "MIT" ]

2

2021-07-31T20:42:42.000Z

2021-11-17T11:01:14.000Z

onnx/backend/test/case/node/xor.py

lokitoth/onnx

27b40225ea98f6412ae2879ed67211d49564af2a

[ "MIT" ]

null

onnx/backend/test/case/node/xor.py

lokitoth/onnx

27b40225ea98f6412ae2879ed67211d49564af2a

[ "MIT" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np import onnx from ..base import Base from . import expect class Xor(Base): @staticmethod def export(): node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], ) # 2d x = (np.random.randn(3, 4) > 0).astype(np.bool) y = (np.random.randn(3, 4) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor2d') # 3d x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) y = (np.random.randn(3, 4, 5) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor3d') # 4d x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) y = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor4d') @staticmethod def export_xor_broadcast(): node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, ) #3d vs 1d x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) y = (np.random.randn(5) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_bcast3v1d') #3d vs 2d x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) y = (np.random.randn(4, 5) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_bcast3v2d') #4d vs 2d x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) y = (np.random.randn(5, 6) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_bcast4v2d') #4d vs 3d x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) y = (np.random.randn(4, 5, 6) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_bcast4v3d') @staticmethod def export_xor_axis(): x = (np.random.randn(5, 5, 5, 5) > 0).astype(np.bool) y = (np.random.randn(5) > 0).astype(np.bool) node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, axis=0, ) z = np.logical_xor(x, y[:, np.newaxis, np.newaxis, np.newaxis]) expect(node, inputs=[x, y], outputs=[z], name='test_xor_axis0') node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, axis=1, ) z = np.logical_xor(x, y[:, np.newaxis, np.newaxis,]) expect(node, inputs=[x, y], outputs=[z], name='test_xor_axis1') node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, axis=2, ) z = np.logical_xor(x, y[:, np.newaxis,]) expect(node, inputs=[x, y], outputs=[z], name='test_xor_axis2') node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, axis=3, ) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_axis3')

28.893939

71

0.484793

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np import onnx from ..base import Base from . import expect class Xor(Base): @staticmethod def export(): node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], ) x = (np.random.randn(3, 4) > 0).astype(np.bool) y = (np.random.randn(3, 4) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor2d') x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) y = (np.random.randn(3, 4, 5) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor3d') x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) y = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor4d') @staticmethod def export_xor_broadcast(): node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, ) x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) y = (np.random.randn(5) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_bcast3v1d') x = (np.random.randn(3, 4, 5) > 0).astype(np.bool) y = (np.random.randn(4, 5) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_bcast3v2d') x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) y = (np.random.randn(5, 6) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_bcast4v2d') x = (np.random.randn(3, 4, 5, 6) > 0).astype(np.bool) y = (np.random.randn(4, 5, 6) > 0).astype(np.bool) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_bcast4v3d') @staticmethod def export_xor_axis(): x = (np.random.randn(5, 5, 5, 5) > 0).astype(np.bool) y = (np.random.randn(5) > 0).astype(np.bool) node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, axis=0, ) z = np.logical_xor(x, y[:, np.newaxis, np.newaxis, np.newaxis]) expect(node, inputs=[x, y], outputs=[z], name='test_xor_axis0') node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, axis=1, ) z = np.logical_xor(x, y[:, np.newaxis, np.newaxis,]) expect(node, inputs=[x, y], outputs=[z], name='test_xor_axis1') node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, axis=2, ) z = np.logical_xor(x, y[:, np.newaxis,]) expect(node, inputs=[x, y], outputs=[z], name='test_xor_axis2') node = onnx.helper.make_node( 'Xor', inputs=['x', 'y'], outputs=['xor'], broadcast=1, axis=3, ) z = np.logical_xor(x, y) expect(node, inputs=[x, y], outputs=[z], name='test_xor_axis3')

true

f718a52a8a96bb85eb0cdd0745fb1c73e627e679

21,417

py

Python

pandas/tests/io/test_common.py

kuantan/pandas

e18921eb0cc86f71c84a4aa0bd6d0c1b7de89def

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "ECL-2.0", "BSD-3-Clause" ]

1

2021-02-20T13:36:45.000Z

pandas/tests/io/test_common.py

fanoway/pandas

71312683b41b5177faf7ecd63555059504853cbd

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "MIT-0", "ECL-2.0", "BSD-3-Clause" ]

4

2019-12-14T16:32:46.000Z

2022-02-12T00:32:28.000Z

pandas/tests/io/test_common.py

lithomas1/pandas

e18921eb0cc86f71c84a4aa0bd6d0c1b7de89def

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "ECL-2.0", "BSD-3-Clause" ]

null

""" Tests for the pandas.io.common functionalities """ import codecs import errno from functools import partial from io import ( BytesIO, StringIO, UnsupportedOperation, ) import mmap import os from pathlib import Path import tempfile import pytest from pandas.compat import is_platform_windows import pandas.util._test_decorators as td import pandas as pd import pandas._testing as tm import pandas.io.common as icom class CustomFSPath: """For testing fspath on unknown objects""" def __init__(self, path): self.path = path def __fspath__(self): return self.path # Functions that consume a string path and return a string or path-like object path_types = [str, CustomFSPath, Path] try: from py.path import local as LocalPath path_types.append(LocalPath) except ImportError: pass HERE = os.path.abspath(os.path.dirname(__file__)) # https://github.com/cython/cython/issues/1720 @pytest.mark.filterwarnings("ignore:can't resolve package:ImportWarning") class TestCommonIOCapabilities: data1 = """index,A,B,C,D foo,2,3,4,5 bar,7,8,9,10 baz,12,13,14,15 qux,12,13,14,15 foo2,12,13,14,15 bar2,12,13,14,15 """ def test_expand_user(self): filename = "~/sometest" expanded_name = icom._expand_user(filename) assert expanded_name != filename assert os.path.isabs(expanded_name) assert os.path.expanduser(filename) == expanded_name def test_expand_user_normal_path(self): filename = "/somefolder/sometest" expanded_name = icom._expand_user(filename) assert expanded_name == filename assert os.path.expanduser(filename) == expanded_name def test_stringify_path_pathlib(self): rel_path = icom.stringify_path(Path(".")) assert rel_path == "." redundant_path = icom.stringify_path(Path("foo//bar")) assert redundant_path == os.path.join("foo", "bar") @td.skip_if_no("py.path") def test_stringify_path_localpath(self): path = os.path.join("foo", "bar") abs_path = os.path.abspath(path) lpath = LocalPath(path) assert icom.stringify_path(lpath) == abs_path def test_stringify_path_fspath(self): p = CustomFSPath("foo/bar.csv") result = icom.stringify_path(p) assert result == "foo/bar.csv" def test_stringify_file_and_path_like(self): # GH 38125: do not stringify file objects that are also path-like fsspec = pytest.importorskip("fsspec") with tm.ensure_clean() as path: with fsspec.open(f"file://{path}", mode="wb") as fsspec_obj: assert fsspec_obj == icom.stringify_path(fsspec_obj) @pytest.mark.parametrize("path_type", path_types) def test_infer_compression_from_path(self, compression_format, path_type): extension, expected = compression_format path = path_type("foo/bar.csv" + extension) compression = icom.infer_compression(path, compression="infer") assert compression == expected @pytest.mark.parametrize("path_type", [str, CustomFSPath, Path]) def test_get_handle_with_path(self, path_type): # ignore LocalPath: it creates strange paths: /absolute/~/sometest with tempfile.TemporaryDirectory(dir=Path.home()) as tmp: filename = path_type("~/" + Path(tmp).name + "/sometest") with icom.get_handle(filename, "w") as handles: assert Path(handles.handle.name).is_absolute() assert os.path.expanduser(filename) == handles.handle.name def test_get_handle_with_buffer(self): input_buffer = StringIO() with icom.get_handle(input_buffer, "r") as handles: assert handles.handle == input_buffer assert not input_buffer.closed input_buffer.close() # Test that BytesIOWrapper(get_handle) returns correct amount of bytes every time def test_bytesiowrapper_returns_correct_bytes(self): # Test latin1, ucs-2, and ucs-4 chars data = """a,b,c 1,2,3 ©,®,® Look,a snake,🐍""" with icom.get_handle(StringIO(data), "rb", is_text=False) as handles: result = b"" chunksize = 5 while True: chunk = handles.handle.read(chunksize) # Make sure each chunk is correct amount of bytes assert len(chunk) <= chunksize if len(chunk) < chunksize: # Can be less amount of bytes, but only at EOF # which happens when read returns empty assert len(handles.handle.read()) == 0 result += chunk break result += chunk assert result == data.encode("utf-8") # Test that pyarrow can handle a file opened with get_handle @td.skip_if_no("pyarrow", min_version="0.15.0") def test_get_handle_pyarrow_compat(self): from pyarrow import csv # Test latin1, ucs-2, and ucs-4 chars data = """a,b,c 1,2,3 ©,®,® Look,a snake,🐍""" expected = pd.DataFrame( {"a": ["1", "©", "Look"], "b": ["2", "®", "a snake"], "c": ["3", "®", "🐍"]} ) s = StringIO(data) with icom.get_handle(s, "rb", is_text=False) as handles: df = csv.read_csv(handles.handle).to_pandas() tm.assert_frame_equal(df, expected) assert not s.closed def test_iterator(self): with pd.read_csv(StringIO(self.data1), chunksize=1) as reader: result = pd.concat(reader, ignore_index=True) expected = pd.read_csv(StringIO(self.data1)) tm.assert_frame_equal(result, expected) # GH12153 with pd.read_csv(StringIO(self.data1), chunksize=1) as it: first = next(it) tm.assert_frame_equal(first, expected.iloc[[0]]) tm.assert_frame_equal(pd.concat(it), expected.iloc[1:]) @pytest.mark.parametrize( "reader, module, error_class, fn_ext", [ (pd.read_csv, "os", FileNotFoundError, "csv"), (pd.read_fwf, "os", FileNotFoundError, "txt"), (pd.read_excel, "xlrd", FileNotFoundError, "xlsx"), (pd.read_feather, "pyarrow", OSError, "feather"), (pd.read_hdf, "tables", FileNotFoundError, "h5"), (pd.read_stata, "os", FileNotFoundError, "dta"), (pd.read_sas, "os", FileNotFoundError, "sas7bdat"), (pd.read_json, "os", ValueError, "json"), (pd.read_pickle, "os", FileNotFoundError, "pickle"), ], ) def test_read_non_existent(self, reader, module, error_class, fn_ext): pytest.importorskip(module) path = os.path.join(HERE, "data", "does_not_exist." + fn_ext) msg1 = fr"File (b')?.+does_not_exist\.{fn_ext}'? does not exist" msg2 = fr"\[Errno 2\] No such file or directory: '.+does_not_exist\.{fn_ext}'" msg3 = "Expected object or value" msg4 = "path_or_buf needs to be a string file path or file-like" msg5 = ( fr"\[Errno 2\] File .+does_not_exist\.{fn_ext} does not exist: " fr"'.+does_not_exist\.{fn_ext}'" ) msg6 = fr"\[Errno 2\] 没有那个文件或目录: '.+does_not_exist\.{fn_ext}'" msg7 = ( fr"\[Errno 2\] File o directory non esistente: '.+does_not_exist\.{fn_ext}'" ) msg8 = fr"Failed to open local file.+does_not_exist\.{fn_ext}" with pytest.raises( error_class, match=fr"({msg1}|{msg2}|{msg3}|{msg4}|{msg5}|{msg6}|{msg7}|{msg8})", ): reader(path) @pytest.mark.parametrize( "method, module, error_class, fn_ext", [ (pd.DataFrame.to_csv, "os", OSError, "csv"), (pd.DataFrame.to_html, "os", OSError, "html"), (pd.DataFrame.to_excel, "xlrd", OSError, "xlsx"), (pd.DataFrame.to_feather, "pyarrow", OSError, "feather"), (pd.DataFrame.to_parquet, "pyarrow", OSError, "parquet"), (pd.DataFrame.to_stata, "os", OSError, "dta"), (pd.DataFrame.to_json, "os", OSError, "json"), (pd.DataFrame.to_pickle, "os", OSError, "pickle"), ], ) # NOTE: Missing parent directory for pd.DataFrame.to_hdf is handled by PyTables def test_write_missing_parent_directory(self, method, module, error_class, fn_ext): pytest.importorskip(module) dummy_frame = pd.DataFrame({"a": [1, 2, 3], "b": [2, 3, 4], "c": [3, 4, 5]}) path = os.path.join(HERE, "data", "missing_folder", "does_not_exist." + fn_ext) with pytest.raises( error_class, match=r"Cannot save file into a non-existent directory: .*missing_folder", ): method(dummy_frame, path) @pytest.mark.parametrize( "reader, module, error_class, fn_ext", [ (pd.read_csv, "os", FileNotFoundError, "csv"), (pd.read_table, "os", FileNotFoundError, "csv"), (pd.read_fwf, "os", FileNotFoundError, "txt"), (pd.read_excel, "xlrd", FileNotFoundError, "xlsx"), (pd.read_feather, "pyarrow", OSError, "feather"), (pd.read_hdf, "tables", FileNotFoundError, "h5"), (pd.read_stata, "os", FileNotFoundError, "dta"), (pd.read_sas, "os", FileNotFoundError, "sas7bdat"), (pd.read_json, "os", ValueError, "json"), (pd.read_pickle, "os", FileNotFoundError, "pickle"), ], ) def test_read_expands_user_home_dir( self, reader, module, error_class, fn_ext, monkeypatch ): pytest.importorskip(module) path = os.path.join("~", "does_not_exist." + fn_ext) monkeypatch.setattr(icom, "_expand_user", lambda x: os.path.join("foo", x)) msg1 = fr"File (b')?.+does_not_exist\.{fn_ext}'? does not exist" msg2 = fr"\[Errno 2\] No such file or directory: '.+does_not_exist\.{fn_ext}'" msg3 = "Unexpected character found when decoding 'false'" msg4 = "path_or_buf needs to be a string file path or file-like" msg5 = ( fr"\[Errno 2\] File .+does_not_exist\.{fn_ext} does not exist: " fr"'.+does_not_exist\.{fn_ext}'" ) msg6 = fr"\[Errno 2\] 没有那个文件或目录: '.+does_not_exist\.{fn_ext}'" msg7 = ( fr"\[Errno 2\] File o directory non esistente: '.+does_not_exist\.{fn_ext}'" ) msg8 = fr"Failed to open local file.+does_not_exist\.{fn_ext}" with pytest.raises( error_class, match=fr"({msg1}|{msg2}|{msg3}|{msg4}|{msg5}|{msg6}|{msg7}|{msg8})", ): reader(path) @pytest.mark.parametrize( "reader, module, path", [ (pd.read_csv, "os", ("io", "data", "csv", "iris.csv")), (pd.read_table, "os", ("io", "data", "csv", "iris.csv")), ( pd.read_fwf, "os", ("io", "data", "fixed_width", "fixed_width_format.txt"), ), (pd.read_excel, "xlrd", ("io", "data", "excel", "test1.xlsx")), ( pd.read_feather, "pyarrow", ("io", "data", "feather", "feather-0_3_1.feather"), ), ( pd.read_hdf, "tables", ("io", "data", "legacy_hdf", "datetimetz_object.h5"), ), (pd.read_stata, "os", ("io", "data", "stata", "stata10_115.dta")), (pd.read_sas, "os", ("io", "sas", "data", "test1.sas7bdat")), (pd.read_json, "os", ("io", "json", "data", "tsframe_v012.json")), ( pd.read_pickle, "os", ("io", "data", "pickle", "categorical.0.25.0.pickle"), ), ], ) @pytest.mark.filterwarnings( "ignore:CategoricalBlock is deprecated:DeprecationWarning" ) @pytest.mark.filterwarnings( # pytables np.object usage "ignore:`np.object` is a deprecated alias:DeprecationWarning" ) def test_read_fspath_all(self, reader, module, path, datapath): pytest.importorskip(module) path = datapath(*path) mypath = CustomFSPath(path) result = reader(mypath) expected = reader(path) if path.endswith(".pickle"): # categorical tm.assert_categorical_equal(result, expected) else: tm.assert_frame_equal(result, expected) @pytest.mark.filterwarnings("ignore:In future versions `DataFrame.to_latex`") @pytest.mark.parametrize( "writer_name, writer_kwargs, module", [ ("to_csv", {}, "os"), ("to_excel", {"engine": "xlwt"}, "xlwt"), ("to_feather", {}, "pyarrow"), ("to_html", {}, "os"), ("to_json", {}, "os"), ("to_latex", {}, "os"), ("to_pickle", {}, "os"), ("to_stata", {"time_stamp": pd.to_datetime("2019-01-01 00:00")}, "os"), ], ) def test_write_fspath_all(self, writer_name, writer_kwargs, module): p1 = tm.ensure_clean("string") p2 = tm.ensure_clean("fspath") df = pd.DataFrame({"A": [1, 2]}) with p1 as string, p2 as fspath: pytest.importorskip(module) mypath = CustomFSPath(fspath) writer = getattr(df, writer_name) writer(string, **writer_kwargs) with open(string, "rb") as f: expected = f.read() writer(mypath, **writer_kwargs) with open(fspath, "rb") as f: result = f.read() assert result == expected @pytest.mark.filterwarnings( # pytables np.object usage "ignore:`np.object` is a deprecated alias:DeprecationWarning" ) def test_write_fspath_hdf5(self): # Same test as write_fspath_all, except HDF5 files aren't # necessarily byte-for-byte identical for a given dataframe, so we'll # have to read and compare equality pytest.importorskip("tables") df = pd.DataFrame({"A": [1, 2]}) p1 = tm.ensure_clean("string") p2 = tm.ensure_clean("fspath") with p1 as string, p2 as fspath: mypath = CustomFSPath(fspath) df.to_hdf(mypath, key="bar") df.to_hdf(string, key="bar") result = pd.read_hdf(fspath, key="bar") expected = pd.read_hdf(string, key="bar") tm.assert_frame_equal(result, expected) @pytest.fixture def mmap_file(datapath): return datapath("io", "data", "csv", "test_mmap.csv") class TestMMapWrapper: def test_constructor_bad_file(self, mmap_file): non_file = StringIO("I am not a file") non_file.fileno = lambda: -1 # the error raised is different on Windows if is_platform_windows(): msg = "The parameter is incorrect" err = OSError else: msg = "[Errno 22]" err = mmap.error with pytest.raises(err, match=msg): icom._MMapWrapper(non_file) target = open(mmap_file) target.close() msg = "I/O operation on closed file" with pytest.raises(ValueError, match=msg): icom._MMapWrapper(target) def test_get_attr(self, mmap_file): with open(mmap_file) as target: wrapper = icom._MMapWrapper(target) attrs = dir(wrapper.mmap) attrs = [attr for attr in attrs if not attr.startswith("__")] attrs.append("__next__") for attr in attrs: assert hasattr(wrapper, attr) assert not hasattr(wrapper, "foo") def test_next(self, mmap_file): with open(mmap_file) as target: wrapper = icom._MMapWrapper(target) lines = target.readlines() for line in lines: next_line = next(wrapper) assert next_line.strip() == line.strip() with pytest.raises(StopIteration, match=r"^$"): next(wrapper) def test_unknown_engine(self): with tm.ensure_clean() as path: df = tm.makeDataFrame() df.to_csv(path) with pytest.raises(ValueError, match="Unknown engine"): pd.read_csv(path, engine="pyt") def test_binary_mode(self): """ 'encoding' shouldn't be passed to 'open' in binary mode. GH 35058 """ with tm.ensure_clean() as path: df = tm.makeDataFrame() df.to_csv(path, mode="w+b") tm.assert_frame_equal(df, pd.read_csv(path, index_col=0)) @pytest.mark.parametrize("encoding", ["utf-16", "utf-32"]) @pytest.mark.parametrize("compression_", ["bz2", "xz"]) def test_warning_missing_utf_bom(self, encoding, compression_): """ bz2 and xz do not write the byte order mark (BOM) for utf-16/32. https://stackoverflow.com/questions/55171439 GH 35681 """ df = tm.makeDataFrame() with tm.ensure_clean() as path: with tm.assert_produces_warning(UnicodeWarning): df.to_csv(path, compression=compression_, encoding=encoding) # reading should fail (otherwise we wouldn't need the warning) msg = r"UTF-\d+ stream does not start with BOM" with pytest.raises(UnicodeError, match=msg): pd.read_csv(path, compression=compression_, encoding=encoding) def test_is_fsspec_url(): assert icom.is_fsspec_url("gcs://pandas/somethingelse.com") assert icom.is_fsspec_url("gs://pandas/somethingelse.com") # the following is the only remote URL that is handled without fsspec assert not icom.is_fsspec_url("http://pandas/somethingelse.com") assert not icom.is_fsspec_url("random:pandas/somethingelse.com") assert not icom.is_fsspec_url("/local/path") assert not icom.is_fsspec_url("relative/local/path") @pytest.mark.parametrize("encoding", [None, "utf-8"]) @pytest.mark.parametrize("format", ["csv", "json"]) def test_codecs_encoding(encoding, format): # GH39247 expected = tm.makeDataFrame() with tm.ensure_clean() as path: with codecs.open(path, mode="w", encoding=encoding) as handle: getattr(expected, f"to_{format}")(handle) with codecs.open(path, mode="r", encoding=encoding) as handle: if format == "csv": df = pd.read_csv(handle, index_col=0) else: df = pd.read_json(handle) tm.assert_frame_equal(expected, df) def test_codecs_get_writer_reader(): # GH39247 expected = tm.makeDataFrame() with tm.ensure_clean() as path: with open(path, "wb") as handle: with codecs.getwriter("utf-8")(handle) as encoded: expected.to_csv(encoded) with open(path, "rb") as handle: with codecs.getreader("utf-8")(handle) as encoded: df = pd.read_csv(encoded, index_col=0) tm.assert_frame_equal(expected, df) @pytest.mark.parametrize( "io_class,mode,msg", [ (BytesIO, "t", "a bytes-like object is required, not 'str'"), (StringIO, "b", "string argument expected, got 'bytes'"), ], ) def test_explicit_encoding(io_class, mode, msg): # GH39247; this test makes sure that if a user provides mode="*t" or "*b", # it is used. In the case of this test it leads to an error as intentionally the # wrong mode is requested expected = tm.makeDataFrame() with io_class() as buffer: with pytest.raises(TypeError, match=msg): expected.to_csv(buffer, mode=f"w{mode}") @pytest.mark.parametrize("encoding_errors", [None, "strict", "replace"]) @pytest.mark.parametrize("format", ["csv", "json"]) def test_encoding_errors(encoding_errors, format): # GH39450 msg = "'utf-8' codec can't decode byte" bad_encoding = b"\xe4" if format == "csv": return content = bad_encoding + b"\n" + bad_encoding reader = pd.read_csv else: content = ( b'{"' + bad_encoding * 2 + b'": {"' + bad_encoding + b'":"' + bad_encoding + b'"}}' ) reader = partial(pd.read_json, orient="index") with tm.ensure_clean() as path: file = Path(path) file.write_bytes(content) if encoding_errors != "replace": with pytest.raises(UnicodeDecodeError, match=msg): reader(path, encoding_errors=encoding_errors) else: df = reader(path, encoding_errors=encoding_errors) decoded = bad_encoding.decode(errors=encoding_errors) expected = pd.DataFrame({decoded: [decoded]}, index=[decoded * 2]) tm.assert_frame_equal(df, expected) def test_bad_encdoing_errors(): # GH 39777 with tm.ensure_clean() as path: with pytest.raises(LookupError, match="unknown error handler name"): icom.get_handle(path, "w", errors="bad") def test_errno_attribute(): # GH 13872 with pytest.raises(FileNotFoundError, match="\\[Errno 2\\]") as err: pd.read_csv("doesnt_exist") assert err.errno == errno.ENOENT def test_fail_mmap(): with pytest.raises(UnsupportedOperation, match="fileno"): with BytesIO() as buffer: icom.get_handle(buffer, "rb", memory_map=True)

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import codecs import errno from functools import partial from io import ( BytesIO, StringIO, UnsupportedOperation, ) import mmap import os from pathlib import Path import tempfile import pytest from pandas.compat import is_platform_windows import pandas.util._test_decorators as td import pandas as pd import pandas._testing as tm import pandas.io.common as icom class CustomFSPath: def __init__(self, path): self.path = path def __fspath__(self): return self.path path_types = [str, CustomFSPath, Path] try: from py.path import local as LocalPath path_types.append(LocalPath) except ImportError: pass HERE = os.path.abspath(os.path.dirname(__file__)) @pytest.mark.filterwarnings("ignore:can't resolve package:ImportWarning") class TestCommonIOCapabilities: data1 = """index,A,B,C,D foo,2,3,4,5 bar,7,8,9,10 baz,12,13,14,15 qux,12,13,14,15 foo2,12,13,14,15 bar2,12,13,14,15 """ def test_expand_user(self): filename = "~/sometest" expanded_name = icom._expand_user(filename) assert expanded_name != filename assert os.path.isabs(expanded_name) assert os.path.expanduser(filename) == expanded_name def test_expand_user_normal_path(self): filename = "/somefolder/sometest" expanded_name = icom._expand_user(filename) assert expanded_name == filename assert os.path.expanduser(filename) == expanded_name def test_stringify_path_pathlib(self): rel_path = icom.stringify_path(Path(".")) assert rel_path == "." redundant_path = icom.stringify_path(Path("foo//bar")) assert redundant_path == os.path.join("foo", "bar") @td.skip_if_no("py.path") def test_stringify_path_localpath(self): path = os.path.join("foo", "bar") abs_path = os.path.abspath(path) lpath = LocalPath(path) assert icom.stringify_path(lpath) == abs_path def test_stringify_path_fspath(self): p = CustomFSPath("foo/bar.csv") result = icom.stringify_path(p) assert result == "foo/bar.csv" def test_stringify_file_and_path_like(self): # GH 38125: do not stringify file objects that are also path-like fsspec = pytest.importorskip("fsspec") with tm.ensure_clean() as path: with fsspec.open(f"file://{path}", mode="wb") as fsspec_obj: assert fsspec_obj == icom.stringify_path(fsspec_obj) @pytest.mark.parametrize("path_type", path_types) def test_infer_compression_from_path(self, compression_format, path_type): extension, expected = compression_format path = path_type("foo/bar.csv" + extension) compression = icom.infer_compression(path, compression="infer") assert compression == expected @pytest.mark.parametrize("path_type", [str, CustomFSPath, Path]) def test_get_handle_with_path(self, path_type): # ignore LocalPath: it creates strange paths: /absolute/~/sometest with tempfile.TemporaryDirectory(dir=Path.home()) as tmp: filename = path_type("~/" + Path(tmp).name + "/sometest") with icom.get_handle(filename, "w") as handles: assert Path(handles.handle.name).is_absolute() assert os.path.expanduser(filename) == handles.handle.name def test_get_handle_with_buffer(self): input_buffer = StringIO() with icom.get_handle(input_buffer, "r") as handles: assert handles.handle == input_buffer assert not input_buffer.closed input_buffer.close() # Test that BytesIOWrapper(get_handle) returns correct amount of bytes every time def test_bytesiowrapper_returns_correct_bytes(self): # Test latin1, ucs-2, and ucs-4 chars data = """a,b,c 1,2,3 ©,®,® Look,a snake,🐍""" with icom.get_handle(StringIO(data), "rb", is_text=False) as handles: result = b"" chunksize = 5 while True: chunk = handles.handle.read(chunksize) # Make sure each chunk is correct amount of bytes assert len(chunk) <= chunksize if len(chunk) < chunksize: # Can be less amount of bytes, but only at EOF # which happens when read returns empty assert len(handles.handle.read()) == 0 result += chunk break result += chunk assert result == data.encode("utf-8") # Test that pyarrow can handle a file opened with get_handle @td.skip_if_no("pyarrow", min_version="0.15.0") def test_get_handle_pyarrow_compat(self): from pyarrow import csv # Test latin1, ucs-2, and ucs-4 chars data = """a,b,c 1,2,3 ©,®,® Look,a snake,🐍""" expected = pd.DataFrame( {"a": ["1", "©", "Look"], "b": ["2", "®", "a snake"], "c": ["3", "®", "🐍"]} ) s = StringIO(data) with icom.get_handle(s, "rb", is_text=False) as handles: df = csv.read_csv(handles.handle).to_pandas() tm.assert_frame_equal(df, expected) assert not s.closed def test_iterator(self): with pd.read_csv(StringIO(self.data1), chunksize=1) as reader: result = pd.concat(reader, ignore_index=True) expected = pd.read_csv(StringIO(self.data1)) tm.assert_frame_equal(result, expected) # GH12153 with pd.read_csv(StringIO(self.data1), chunksize=1) as it: first = next(it) tm.assert_frame_equal(first, expected.iloc[[0]]) tm.assert_frame_equal(pd.concat(it), expected.iloc[1:]) @pytest.mark.parametrize( "reader, module, error_class, fn_ext", [ (pd.read_csv, "os", FileNotFoundError, "csv"), (pd.read_fwf, "os", FileNotFoundError, "txt"), (pd.read_excel, "xlrd", FileNotFoundError, "xlsx"), (pd.read_feather, "pyarrow", OSError, "feather"), (pd.read_hdf, "tables", FileNotFoundError, "h5"), (pd.read_stata, "os", FileNotFoundError, "dta"), (pd.read_sas, "os", FileNotFoundError, "sas7bdat"), (pd.read_json, "os", ValueError, "json"), (pd.read_pickle, "os", FileNotFoundError, "pickle"), ], ) def test_read_non_existent(self, reader, module, error_class, fn_ext): pytest.importorskip(module) path = os.path.join(HERE, "data", "does_not_exist." + fn_ext) msg1 = fr"File (b')?.+does_not_exist\.{fn_ext}'? does not exist" msg2 = fr"\[Errno 2\] No such file or directory: '.+does_not_exist\.{fn_ext}'" msg3 = "Expected object or value" msg4 = "path_or_buf needs to be a string file path or file-like" msg5 = ( fr"\[Errno 2\] File .+does_not_exist\.{fn_ext} does not exist: " fr"'.+does_not_exist\.{fn_ext}'" ) msg6 = fr"\[Errno 2\] 没有那个文件或目录: '.+does_not_exist\.{fn_ext}'" msg7 = ( fr"\[Errno 2\] File o directory non esistente: '.+does_not_exist\.{fn_ext}'" ) msg8 = fr"Failed to open local file.+does_not_exist\.{fn_ext}" with pytest.raises( error_class, match=fr"({msg1}|{msg2}|{msg3}|{msg4}|{msg5}|{msg6}|{msg7}|{msg8})", ): reader(path) @pytest.mark.parametrize( "method, module, error_class, fn_ext", [ (pd.DataFrame.to_csv, "os", OSError, "csv"), (pd.DataFrame.to_html, "os", OSError, "html"), (pd.DataFrame.to_excel, "xlrd", OSError, "xlsx"), (pd.DataFrame.to_feather, "pyarrow", OSError, "feather"), (pd.DataFrame.to_parquet, "pyarrow", OSError, "parquet"), (pd.DataFrame.to_stata, "os", OSError, "dta"), (pd.DataFrame.to_json, "os", OSError, "json"), (pd.DataFrame.to_pickle, "os", OSError, "pickle"), ], ) # NOTE: Missing parent directory for pd.DataFrame.to_hdf is handled by PyTables def test_write_missing_parent_directory(self, method, module, error_class, fn_ext): pytest.importorskip(module) dummy_frame = pd.DataFrame({"a": [1, 2, 3], "b": [2, 3, 4], "c": [3, 4, 5]}) path = os.path.join(HERE, "data", "missing_folder", "does_not_exist." + fn_ext) with pytest.raises( error_class, match=r"Cannot save file into a non-existent directory: .*missing_folder", ): method(dummy_frame, path) @pytest.mark.parametrize( "reader, module, error_class, fn_ext", [ (pd.read_csv, "os", FileNotFoundError, "csv"), (pd.read_table, "os", FileNotFoundError, "csv"), (pd.read_fwf, "os", FileNotFoundError, "txt"), (pd.read_excel, "xlrd", FileNotFoundError, "xlsx"), (pd.read_feather, "pyarrow", OSError, "feather"), (pd.read_hdf, "tables", FileNotFoundError, "h5"), (pd.read_stata, "os", FileNotFoundError, "dta"), (pd.read_sas, "os", FileNotFoundError, "sas7bdat"), (pd.read_json, "os", ValueError, "json"), (pd.read_pickle, "os", FileNotFoundError, "pickle"), ], ) def test_read_expands_user_home_dir( self, reader, module, error_class, fn_ext, monkeypatch ): pytest.importorskip(module) path = os.path.join("~", "does_not_exist." + fn_ext) monkeypatch.setattr(icom, "_expand_user", lambda x: os.path.join("foo", x)) msg1 = fr"File (b')?.+does_not_exist\.{fn_ext}'? does not exist" msg2 = fr"\[Errno 2\] No such file or directory: '.+does_not_exist\.{fn_ext}'" msg3 = "Unexpected character found when decoding 'false'" msg4 = "path_or_buf needs to be a string file path or file-like" msg5 = ( fr"\[Errno 2\] File .+does_not_exist\.{fn_ext} does not exist: " fr"'.+does_not_exist\.{fn_ext}'" ) msg6 = fr"\[Errno 2\] 没有那个文件或目录: '.+does_not_exist\.{fn_ext}'" msg7 = ( fr"\[Errno 2\] File o directory non esistente: '.+does_not_exist\.{fn_ext}'" ) msg8 = fr"Failed to open local file.+does_not_exist\.{fn_ext}" with pytest.raises( error_class, match=fr"({msg1}|{msg2}|{msg3}|{msg4}|{msg5}|{msg6}|{msg7}|{msg8})", ): reader(path) @pytest.mark.parametrize( "reader, module, path", [ (pd.read_csv, "os", ("io", "data", "csv", "iris.csv")), (pd.read_table, "os", ("io", "data", "csv", "iris.csv")), ( pd.read_fwf, "os", ("io", "data", "fixed_width", "fixed_width_format.txt"), ), (pd.read_excel, "xlrd", ("io", "data", "excel", "test1.xlsx")), ( pd.read_feather, "pyarrow", ("io", "data", "feather", "feather-0_3_1.feather"), ), ( pd.read_hdf, "tables", ("io", "data", "legacy_hdf", "datetimetz_object.h5"), ), (pd.read_stata, "os", ("io", "data", "stata", "stata10_115.dta")), (pd.read_sas, "os", ("io", "sas", "data", "test1.sas7bdat")), (pd.read_json, "os", ("io", "json", "data", "tsframe_v012.json")), ( pd.read_pickle, "os", ("io", "data", "pickle", "categorical.0.25.0.pickle"), ), ], ) @pytest.mark.filterwarnings( "ignore:CategoricalBlock is deprecated:DeprecationWarning" ) @pytest.mark.filterwarnings( # pytables np.object usage "ignore:`np.object` is a deprecated alias:DeprecationWarning" ) def test_read_fspath_all(self, reader, module, path, datapath): pytest.importorskip(module) path = datapath(*path) mypath = CustomFSPath(path) result = reader(mypath) expected = reader(path) if path.endswith(".pickle"): # categorical tm.assert_categorical_equal(result, expected) else: tm.assert_frame_equal(result, expected) @pytest.mark.filterwarnings("ignore:In future versions `DataFrame.to_latex`") @pytest.mark.parametrize( "writer_name, writer_kwargs, module", [ ("to_csv", {}, "os"), ("to_excel", {"engine": "xlwt"}, "xlwt"), ("to_feather", {}, "pyarrow"), ("to_html", {}, "os"), ("to_json", {}, "os"), ("to_latex", {}, "os"), ("to_pickle", {}, "os"), ("to_stata", {"time_stamp": pd.to_datetime("2019-01-01 00:00")}, "os"), ], ) def test_write_fspath_all(self, writer_name, writer_kwargs, module): p1 = tm.ensure_clean("string") p2 = tm.ensure_clean("fspath") df = pd.DataFrame({"A": [1, 2]}) with p1 as string, p2 as fspath: pytest.importorskip(module) mypath = CustomFSPath(fspath) writer = getattr(df, writer_name) writer(string, **writer_kwargs) with open(string, "rb") as f: expected = f.read() writer(mypath, **writer_kwargs) with open(fspath, "rb") as f: result = f.read() assert result == expected @pytest.mark.filterwarnings( # pytables np.object usage "ignore:`np.object` is a deprecated alias:DeprecationWarning" ) def test_write_fspath_hdf5(self): # Same test as write_fspath_all, except HDF5 files aren't # have to read and compare equality pytest.importorskip("tables") df = pd.DataFrame({"A": [1, 2]}) p1 = tm.ensure_clean("string") p2 = tm.ensure_clean("fspath") with p1 as string, p2 as fspath: mypath = CustomFSPath(fspath) df.to_hdf(mypath, key="bar") df.to_hdf(string, key="bar") result = pd.read_hdf(fspath, key="bar") expected = pd.read_hdf(string, key="bar") tm.assert_frame_equal(result, expected) @pytest.fixture def mmap_file(datapath): return datapath("io", "data", "csv", "test_mmap.csv") class TestMMapWrapper: def test_constructor_bad_file(self, mmap_file): non_file = StringIO("I am not a file") non_file.fileno = lambda: -1 # the error raised is different on Windows if is_platform_windows(): msg = "The parameter is incorrect" err = OSError else: msg = "[Errno 22]" err = mmap.error with pytest.raises(err, match=msg): icom._MMapWrapper(non_file) target = open(mmap_file) target.close() msg = "I/O operation on closed file" with pytest.raises(ValueError, match=msg): icom._MMapWrapper(target) def test_get_attr(self, mmap_file): with open(mmap_file) as target: wrapper = icom._MMapWrapper(target) attrs = dir(wrapper.mmap) attrs = [attr for attr in attrs if not attr.startswith("__")] attrs.append("__next__") for attr in attrs: assert hasattr(wrapper, attr) assert not hasattr(wrapper, "foo") def test_next(self, mmap_file): with open(mmap_file) as target: wrapper = icom._MMapWrapper(target) lines = target.readlines() for line in lines: next_line = next(wrapper) assert next_line.strip() == line.strip() with pytest.raises(StopIteration, match=r"^$"): next(wrapper) def test_unknown_engine(self): with tm.ensure_clean() as path: df = tm.makeDataFrame() df.to_csv(path) with pytest.raises(ValueError, match="Unknown engine"): pd.read_csv(path, engine="pyt") def test_binary_mode(self): with tm.ensure_clean() as path: df = tm.makeDataFrame() df.to_csv(path, mode="w+b") tm.assert_frame_equal(df, pd.read_csv(path, index_col=0)) @pytest.mark.parametrize("encoding", ["utf-16", "utf-32"]) @pytest.mark.parametrize("compression_", ["bz2", "xz"]) def test_warning_missing_utf_bom(self, encoding, compression_): df = tm.makeDataFrame() with tm.ensure_clean() as path: with tm.assert_produces_warning(UnicodeWarning): df.to_csv(path, compression=compression_, encoding=encoding) # reading should fail (otherwise we wouldn't need the warning) msg = r"UTF-\d+ stream does not start with BOM" with pytest.raises(UnicodeError, match=msg): pd.read_csv(path, compression=compression_, encoding=encoding) def test_is_fsspec_url(): assert icom.is_fsspec_url("gcs://pandas/somethingelse.com") assert icom.is_fsspec_url("gs://pandas/somethingelse.com") assert not icom.is_fsspec_url("http://pandas/somethingelse.com") assert not icom.is_fsspec_url("random:pandas/somethingelse.com") assert not icom.is_fsspec_url("/local/path") assert not icom.is_fsspec_url("relative/local/path") @pytest.mark.parametrize("encoding", [None, "utf-8"]) @pytest.mark.parametrize("format", ["csv", "json"]) def test_codecs_encoding(encoding, format): expected = tm.makeDataFrame() with tm.ensure_clean() as path: with codecs.open(path, mode="w", encoding=encoding) as handle: getattr(expected, f"to_{format}")(handle) with codecs.open(path, mode="r", encoding=encoding) as handle: if format == "csv": df = pd.read_csv(handle, index_col=0) else: df = pd.read_json(handle) tm.assert_frame_equal(expected, df) def test_codecs_get_writer_reader(): expected = tm.makeDataFrame() with tm.ensure_clean() as path: with open(path, "wb") as handle: with codecs.getwriter("utf-8")(handle) as encoded: expected.to_csv(encoded) with open(path, "rb") as handle: with codecs.getreader("utf-8")(handle) as encoded: df = pd.read_csv(encoded, index_col=0) tm.assert_frame_equal(expected, df) @pytest.mark.parametrize( "io_class,mode,msg", [ (BytesIO, "t", "a bytes-like object is required, not 'str'"), (StringIO, "b", "string argument expected, got 'bytes'"), ], ) def test_explicit_encoding(io_class, mode, msg): expected = tm.makeDataFrame() with io_class() as buffer: with pytest.raises(TypeError, match=msg): expected.to_csv(buffer, mode=f"w{mode}") @pytest.mark.parametrize("encoding_errors", [None, "strict", "replace"]) @pytest.mark.parametrize("format", ["csv", "json"]) def test_encoding_errors(encoding_errors, format): msg = "'utf-8' codec can't decode byte" bad_encoding = b"\xe4" if format == "csv": return content = bad_encoding + b"\n" + bad_encoding reader = pd.read_csv else: content = ( b'{"' + bad_encoding * 2 + b'": {"' + bad_encoding + b'":"' + bad_encoding + b'"}}' ) reader = partial(pd.read_json, orient="index") with tm.ensure_clean() as path: file = Path(path) file.write_bytes(content) if encoding_errors != "replace": with pytest.raises(UnicodeDecodeError, match=msg): reader(path, encoding_errors=encoding_errors) else: df = reader(path, encoding_errors=encoding_errors) decoded = bad_encoding.decode(errors=encoding_errors) expected = pd.DataFrame({decoded: [decoded]}, index=[decoded * 2]) tm.assert_frame_equal(df, expected) def test_bad_encdoing_errors(): # GH 39777 with tm.ensure_clean() as path: with pytest.raises(LookupError, match="unknown error handler name"): icom.get_handle(path, "w", errors="bad") def test_errno_attribute(): # GH 13872 with pytest.raises(FileNotFoundError, match="\\[Errno 2\\]") as err: pd.read_csv("doesnt_exist") assert err.errno == errno.ENOENT def test_fail_mmap(): with pytest.raises(UnsupportedOperation, match="fileno"): with BytesIO() as buffer: icom.get_handle(buffer, "rb", memory_map=True)

true

f718a539f818b3cbab4eb694387294e8a9cc035e

54,358

py

Python

python/ccxt/async_support/hitbtc2.py

OliverNChalk/ccxt

fcf55e88f3523d2969f905cbed3b4deec1433a5e

[ "MIT" ]

null

python/ccxt/async_support/hitbtc2.py

OliverNChalk/ccxt

fcf55e88f3523d2969f905cbed3b4deec1433a5e

[ "MIT" ]

null

python/ccxt/async_support/hitbtc2.py

OliverNChalk/ccxt

fcf55e88f3523d2969f905cbed3b4deec1433a5e

[ "MIT" ]

null

# -*- coding: utf-8 -*- # PLEASE DO NOT EDIT THIS FILE, IT IS GENERATED AND WILL BE OVERWRITTEN: # https://github.com/ccxt/ccxt/blob/master/CONTRIBUTING.md#how-to-contribute-code from ccxt.async_support.hitbtc import hitbtc import base64 import math from ccxt.base.errors import ExchangeError from ccxt.base.errors import PermissionDenied from ccxt.base.errors import InsufficientFunds from ccxt.base.errors import InvalidOrder from ccxt.base.errors import OrderNotFound from ccxt.base.errors import ExchangeNotAvailable from ccxt.base.decimal_to_precision import TRUNCATE from ccxt.base.decimal_to_precision import DECIMAL_PLACES class hitbtc2 (hitbtc): def describe(self): return self.deep_extend(super(hitbtc2, self).describe(), { 'id': 'hitbtc2', 'name': 'HitBTC', 'countries': ['HK'], 'rateLimit': 1500, 'version': '2', 'has': { 'createDepositAddress': True, 'fetchDepositAddress': True, 'CORS': True, 'editOrder': True, 'fetchCurrencies': True, 'fetchOHLCV': True, 'fetchTickers': True, 'fetchOrder': True, 'fetchOrders': False, 'fetchOpenOrders': True, 'fetchClosedOrders': True, 'fetchMyTrades': True, 'withdraw': True, 'fetchOrderTrades': False, # not implemented yet 'fetchDeposits': False, 'fetchWithdrawals': False, 'fetchTransactions': True, 'fetchTradingFee': True, }, 'timeframes': { '1m': 'M1', '3m': 'M3', '5m': 'M5', '15m': 'M15', '30m': 'M30', # default '1h': 'H1', '4h': 'H4', '1d': 'D1', '1w': 'D7', '1M': '1M', }, 'urls': { 'logo': 'https://user-images.githubusercontent.com/1294454/27766555-8eaec20e-5edc-11e7-9c5b-6dc69fc42f5e.jpg', 'api': 'https://api.hitbtc.com', 'www': 'https://hitbtc.com', 'referral': 'https://hitbtc.com/?ref_id=5a5d39a65d466', 'doc': [ 'https://api.hitbtc.com', 'https://github.com/hitbtc-com/hitbtc-api/blob/master/APIv2.md', ], 'fees': [ 'https://hitbtc.com/fees-and-limits', 'https://support.hitbtc.com/hc/en-us/articles/115005148605-Fees-and-limits', ], }, 'api': { 'public': { 'get': [ 'symbol', # Available Currency Symbols 'symbol/{symbol}', # Get symbol info 'currency', # Available Currencies 'currency/{currency}', # Get currency info 'ticker', # Ticker list for all symbols 'ticker/{symbol}', # Ticker for symbol 'trades/{symbol}', # Trades 'orderbook/{symbol}', # Orderbook 'candles/{symbol}', # Candles ], }, 'private': { 'get': [ 'order', # List your current open orders 'order/{clientOrderId}', # Get a single order by clientOrderId 'trading/balance', # Get trading balance 'trading/fee/all', # Get trading fee rate 'trading/fee/{symbol}', # Get trading fee rate 'history/trades', # Get historical trades 'history/order', # Get historical orders 'history/order/{id}/trades', # Get historical trades by specified order 'account/balance', # Get main acccount balance 'account/transactions', # Get account transactions 'account/transactions/{id}', # Get account transaction by id 'account/crypto/address/{currency}', # Get deposit crypro address ], 'post': [ 'order', # Create new order 'account/crypto/withdraw', # Withdraw crypro 'account/crypto/address/{currency}', # Create new deposit crypro address 'account/transfer', # Transfer amount to trading ], 'put': [ 'order/{clientOrderId}', # Create new order 'account/crypto/withdraw/{id}', # Commit withdraw crypro ], 'delete': [ 'order', # Cancel all open orders 'order/{clientOrderId}', # Cancel order 'account/crypto/withdraw/{id}', # Rollback withdraw crypro ], 'patch': [ 'order/{clientOrderId}', # Cancel Replace order ], }, }, 'fees': { 'trading': { 'tierBased': False, 'percentage': True, 'maker': 0.1 / 100, 'taker': 0.2 / 100, }, 'funding': { 'tierBased': False, 'percentage': False, 'withdraw': { 'BTC': 0.001, 'BCC': 0.0018, 'ETH': 0.00958, 'BCH': 0.0018, 'USDT': 100, 'DASH': 0.03, 'BTG': 0.0005, 'XRP': 0.509, 'LTC': 0.003, 'ZEC': 0.0001, 'XMR': 0.09, '1ST': 0.84, 'ADX': 5.7, 'AE': 6.7, 'AEON': 0.01006, 'AIR': 565, 'AMM': 14, 'AMP': 342, 'ANT': 6.7, 'ARDR': 1, 'ARN': 18.5, 'ART': 26, 'ATB': 0.0004, 'ATL': 27, 'ATM': 504, 'ATS': 860, 'AVT': 1.9, 'BAS': 113, 'BCN': 0.1, 'BET': 124, 'BKB': 46, 'BMC': 32, 'BMT': 100, 'BNT': 2.57, 'BQX': 4.7, 'BTCA': 351.21, 'BTM': 40, 'BTX': 0.04, 'BUS': 0.004, 'CAPP': 97, 'CCT': 6, 'CDT': 100, 'CDX': 30, 'CFI': 61, 'CL': 13.85, 'CLD': 0.88, 'CND': 574, 'CNX': 0.04, 'COSS': 65, 'CPAY': 5.487, 'CSNO': 16, 'CTR': 15, 'CTX': 146, 'CVC': 8.46, 'DATA': 12.949, 'DBIX': 0.0168, 'DCN': 1280, 'DCT': 0.02, 'DDF': 342, 'DENT': 1000, 'DGB': 0.4, 'DGD': 0.01, 'DICE': 0.32, 'DLT': 0.26, 'DNT': 0.21, 'DOGE': 2, 'DOV': 34, 'DRPU': 24, 'DRT': 240, 'DSH': 0.017, 'EBET': 84, 'EBTC': 20, 'EBTCOLD': 6.6, 'ECAT': 14, 'EDG': 2, 'EDO': 2.9, 'EKO': 1136.36, 'ELE': 0.00172, 'ELM': 0.004, 'EMC': 0.03, 'MGO': 14, 'ENJ': 163, 'EOS': 1.5, 'ERO': 34, 'ETBS': 15, 'ETC': 0.002, 'ETP': 0.004, 'EVX': 5.4, 'EXN': 456, 'FCN': 0.000005, 'FRD': 65, 'FUEL': 123.00105, 'FUN': 202.9598309, 'FYN': 1.849, 'FYP': 66.13, 'GAME': 0.004, 'GNO': 0.0034, 'GUP': 4, 'GVT': 1.2, 'HSR': 0.04, 'HAC': 144, 'HDG': 7, 'HGT': 1082, 'HPC': 0.4, 'HVN': 120, 'ICN': 0.55, 'ICO': 34, 'ICOS': 0.35, 'IND': 76, 'INDI': 790, 'ITS': 15.0012, 'IXT': 11, 'KBR': 143, 'KICK': 112, 'KMD': 4, 'LA': 41, 'LEND': 388, 'LAT': 1.44, 'LIFE': 13000, 'LRC': 27, 'LSK': 0.3, 'LOC': 11.076, 'LUN': 0.34, 'MAID': 5, 'MANA': 143, 'MCAP': 5.44, 'MIPS': 43, 'MNE': 1.33, 'MSP': 121, 'MCO': 0.357, 'MTH': 92, 'MYB': 3.9, 'NDC': 165, 'NEBL': 0.04, 'NET': 3.96, 'NTO': 998, 'NGC': 2.368, 'NXC': 13.39, 'NXT': 3, 'OAX': 15, 'ODN': 0.004, 'OMG': 2, 'OPT': 335, 'ORME': 2.8, 'OTN': 0.57, 'PAY': 3.1, 'PIX': 96, 'PLBT': 0.33, 'PLR': 114, 'PLU': 0.87, 'POE': 784, 'POLL': 3.5, 'PPT': 2, 'PRE': 32, 'PRG': 39, 'PRO': 41, 'PRS': 60, 'PTOY': 0.5, 'QAU': 63, 'QCN': 0.03, 'QTUM': 0.04, 'QVT': 64, 'REP': 0.02, 'RKC': 15, 'RLC': 1.21, 'RVT': 14, 'SC': 30, 'SAN': 2.24, 'SBD': 0.03, 'SCL': 2.6, 'SISA': 1640, 'SKIN': 407, 'SWFTC': 352.94, 'SMART': 0.4, 'SMS': 0.0375, 'SNC': 36, 'SNGLS': 4, 'SNM': 48, 'SNT': 233, 'STAR': 0.144, 'STORM': 153.19, 'STEEM': 0.01, 'STRAT': 0.01, 'SPF': 14.4, 'STU': 14, 'STX': 11, 'SUB': 17, 'SUR': 3, 'SWT': 0.51, 'TAAS': 0.91, 'TBT': 2.37, 'TFL': 15, 'TIME': 0.03, 'TIX': 7.1, 'TKN': 1, 'TGT': 173, 'TKR': 84, 'TNT': 90, 'TRST': 1.6, 'TRX': 270, 'UET': 480, 'UGT': 15, 'UTT': 3, 'VEN': 14, 'VERI': 0.037, 'VIB': 50, 'VIBE': 145, 'VOISE': 618, 'WEALTH': 0.0168, 'WINGS': 2.4, 'WTC': 0.75, 'WRC': 48, 'XAUR': 3.23, 'XDN': 0.01, 'XEM': 15, 'XUC': 0.9, 'YOYOW': 140, 'ZAP': 24, 'ZRX': 23, 'ZSC': 191, }, 'deposit': { 'BTC': 0, 'ETH': 0, 'BCH': 0, 'USDT': 0, 'BTG': 0, 'LTC': 0, 'ZEC': 0, 'XMR': 0, '1ST': 0, 'ADX': 0, 'AE': 0, 'AEON': 0, 'AIR': 0, 'AMP': 0, 'ANT': 0, 'ARDR': 0, 'ARN': 0, 'ART': 0, 'ATB': 0, 'ATL': 0, 'ATM': 0, 'ATS': 0, 'AVT': 0, 'BAS': 0, 'BCN': 0, 'BET': 0, 'BKB': 0, 'BMC': 0, 'BMT': 0, 'BNT': 0, 'BQX': 0, 'BTM': 0, 'BTX': 0, 'BUS': 0, 'CCT': 0, 'CDT': 0, 'CDX': 0, 'CFI': 0, 'CLD': 0, 'CND': 0, 'CNX': 0, 'COSS': 0, 'CSNO': 0, 'CTR': 0, 'CTX': 0, 'CVC': 0, 'DBIX': 0, 'DCN': 0, 'DCT': 0, 'DDF': 0, 'DENT': 0, 'DGB': 0, 'DGD': 0, 'DICE': 0, 'DLT': 0, 'DNT': 0, 'DOGE': 0, 'DOV': 0, 'DRPU': 0, 'DRT': 0, 'DSH': 0, 'EBET': 0, 'EBTC': 0, 'EBTCOLD': 0, 'ECAT': 0, 'EDG': 0, 'EDO': 0, 'ELE': 0, 'ELM': 0, 'EMC': 0, 'EMGO': 0, 'ENJ': 0, 'EOS': 0, 'ERO': 0, 'ETBS': 0, 'ETC': 0, 'ETP': 0, 'EVX': 0, 'EXN': 0, 'FRD': 0, 'FUEL': 0, 'FUN': 0, 'FYN': 0, 'FYP': 0, 'GNO': 0, 'GUP': 0, 'GVT': 0, 'HAC': 0, 'HDG': 0, 'HGT': 0, 'HPC': 0, 'HVN': 0, 'ICN': 0, 'ICO': 0, 'ICOS': 0, 'IND': 0, 'INDI': 0, 'ITS': 0, 'IXT': 0, 'KBR': 0, 'KICK': 0, 'LA': 0, 'LAT': 0, 'LIFE': 0, 'LRC': 0, 'LSK': 0, 'LUN': 0, 'MAID': 0, 'MANA': 0, 'MCAP': 0, 'MIPS': 0, 'MNE': 0, 'MSP': 0, 'MTH': 0, 'MYB': 0, 'NDC': 0, 'NEBL': 0, 'NET': 0, 'NTO': 0, 'NXC': 0, 'NXT': 0, 'OAX': 0, 'ODN': 0, 'OMG': 0, 'OPT': 0, 'ORME': 0, 'OTN': 0, 'PAY': 0, 'PIX': 0, 'PLBT': 0, 'PLR': 0, 'PLU': 0, 'POE': 0, 'POLL': 0, 'PPT': 0, 'PRE': 0, 'PRG': 0, 'PRO': 0, 'PRS': 0, 'PTOY': 0, 'QAU': 0, 'QCN': 0, 'QTUM': 0, 'QVT': 0, 'REP': 0, 'RKC': 0, 'RVT': 0, 'SAN': 0, 'SBD': 0, 'SCL': 0, 'SISA': 0, 'SKIN': 0, 'SMART': 0, 'SMS': 0, 'SNC': 0, 'SNGLS': 0, 'SNM': 0, 'SNT': 0, 'STEEM': 0, 'STRAT': 0, 'STU': 0, 'STX': 0, 'SUB': 0, 'SUR': 0, 'SWT': 0, 'TAAS': 0, 'TBT': 0, 'TFL': 0, 'TIME': 0, 'TIX': 0, 'TKN': 0, 'TKR': 0, 'TNT': 0, 'TRST': 0, 'TRX': 0, 'UET': 0, 'UGT': 0, 'VEN': 0, 'VERI': 0, 'VIB': 0, 'VIBE': 0, 'VOISE': 0, 'WEALTH': 0, 'WINGS': 0, 'WTC': 0, 'XAUR': 0, 'XDN': 0, 'XEM': 0, 'XUC': 0, 'YOYOW': 0, 'ZAP': 0, 'ZRX': 0, 'ZSC': 0, }, }, }, 'options': { 'defaultTimeInForce': 'FOK', }, 'exceptions': { '1003': PermissionDenied, # "Action is forbidden for self API key" '2010': InvalidOrder, # "Quantity not a valid number" '2011': InvalidOrder, # "Quantity too low" '2020': InvalidOrder, # "Price not a valid number" '20002': OrderNotFound, # canceling non-existent order '20001': InsufficientFunds, }, }) def fee_to_precision(self, symbol, fee): return self.decimal_to_precision(fee, TRUNCATE, 8, DECIMAL_PLACES) async def fetch_markets(self, params={}): response = await self.publicGetSymbol(params) result = [] for i in range(0, len(response)): market = response[i] id = self.safe_string(market, 'id') baseId = self.safe_string(market, 'baseCurrency') quoteId = self.safe_string(market, 'quoteCurrency') base = self.safe_currency_code(baseId) quote = self.safe_currency_code(quoteId) symbol = base + '/' + quote lot = self.safe_float(market, 'quantityIncrement') step = self.safe_float(market, 'tickSize') precision = { 'price': self.precision_from_string(market['tickSize']), # FIXME: for lots > 1 the following line returns 0 # 'amount': self.precision_from_string(market['quantityIncrement']), 'amount': -1 * int(math.log10(lot)), } taker = self.safe_float(market, 'takeLiquidityRate') maker = self.safe_float(market, 'provideLiquidityRate') result.append(self.extend(self.fees['trading'], { 'info': market, 'id': id, 'symbol': symbol, 'base': base, 'quote': quote, 'baseId': baseId, 'quoteId': quoteId, 'active': True, 'taker': taker, 'maker': maker, 'precision': precision, 'limits': { 'amount': { 'min': lot, 'max': None, }, 'price': { 'min': step, 'max': None, }, 'cost': { 'min': lot * step, 'max': None, }, }, })) return result async def fetch_currencies(self, params={}): response = await self.publicGetCurrency(params) result = {} for i in range(0, len(response)): currency = response[i] id = self.safe_string(currency, 'id') # todo: will need to rethink the fees # to add support for multiple withdrawal/deposit methods and # differentiated fees for each particular method precision = 8 # default precision, todo: fix "magic constants" code = self.safe_currency_code(id) payin = self.safe_value(currency, 'payinEnabled') payout = self.safe_value(currency, 'payoutEnabled') transfer = self.safe_value(currency, 'transferEnabled') active = payin and payout and transfer if 'disabled' in currency: if currency['disabled']: active = False type = 'fiat' if ('crypto' in list(currency.keys())) and currency['crypto']: type = 'crypto' name = self.safe_string(currency, 'fullName') result[code] = { 'id': id, 'code': code, 'type': type, 'payin': payin, 'payout': payout, 'transfer': transfer, 'info': currency, 'name': name, 'active': active, 'fee': self.safe_float(currency, 'payoutFee'), # todo: redesign 'precision': precision, 'limits': { 'amount': { 'min': math.pow(10, -precision), 'max': math.pow(10, precision), }, 'price': { 'min': math.pow(10, -precision), 'max': math.pow(10, precision), }, 'cost': { 'min': None, 'max': None, }, 'withdraw': { 'min': None, 'max': math.pow(10, precision), }, }, } return result async def fetch_trading_fee(self, symbol, params={}): await self.load_markets() market = self.market(symbol) request = self.extend({ 'symbol': market['id'], }, self.omit(params, 'symbol')) response = await self.privateGetTradingFeeSymbol(request) # # { # takeLiquidityRate: '0.001', # provideLiquidityRate: '-0.0001' # } # return { 'info': response, 'maker': self.safe_float(response, 'provideLiquidityRate'), 'taker': self.safe_float(response, 'takeLiquidityRate'), } async def fetch_balance(self, params={}): await self.load_markets() type = self.safe_string(params, 'type', 'trading') method = 'privateGet' + self.capitalize(type) + 'Balance' query = self.omit(params, 'type') response = await getattr(self, method)(query) result = {'info': response} for i in range(0, len(response)): balance = response[i] currencyId = self.safe_string(balance, 'currency') code = self.safe_currency_code(currencyId) account = self.account() account['free'] = self.safe_float(balance, 'available') account['used'] = self.safe_float(balance, 'reserved') result[code] = account return self.parse_balance(result) def parse_ohlcv(self, ohlcv, market=None, timeframe='1d', since=None, limit=None): timestamp = self.parse8601(ohlcv['timestamp']) return [ timestamp, float(ohlcv['open']), float(ohlcv['max']), float(ohlcv['min']), float(ohlcv['close']), float(ohlcv['volume']), ] async def fetch_ohlcv(self, symbol, timeframe='1m', since=None, limit=None, params={}): await self.load_markets() market = self.market(symbol) request = { 'symbol': market['id'], 'period': self.timeframes[timeframe], } if since is not None: request['from'] = self.iso8601(since) if limit is not None: request['limit'] = limit response = await self.publicGetCandlesSymbol(self.extend(request, params)) return self.parse_ohlcvs(response, market, timeframe, since, limit) async def fetch_order_book(self, symbol, limit=None, params={}): await self.load_markets() request = { 'symbol': self.market_id(symbol), } if limit is not None: request['limit'] = limit # default = 100, 0 = unlimited response = await self.publicGetOrderbookSymbol(self.extend(request, params)) return self.parse_order_book(response, None, 'bid', 'ask', 'price', 'size') def parse_ticker(self, ticker, market=None): timestamp = self.parse8601(ticker['timestamp']) symbol = None if market is not None: symbol = market['symbol'] baseVolume = self.safe_float(ticker, 'volume') quoteVolume = self.safe_float(ticker, 'volumeQuote') open = self.safe_float(ticker, 'open') last = self.safe_float(ticker, 'last') change = None percentage = None average = None if last is not None and open is not None: change = last - open average = self.sum(last, open) / 2 if open > 0: percentage = change / open * 100 vwap = None if quoteVolume is not None: if baseVolume is not None: if baseVolume > 0: vwap = quoteVolume / baseVolume return { 'symbol': symbol, 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'high': self.safe_float(ticker, 'high'), 'low': self.safe_float(ticker, 'low'), 'bid': self.safe_float(ticker, 'bid'), 'bidVolume': None, 'ask': self.safe_float(ticker, 'ask'), 'askVolume': None, 'vwap': vwap, 'open': open, 'close': last, 'last': last, 'previousClose': None, 'change': change, 'percentage': percentage, 'average': average, 'baseVolume': baseVolume, 'quoteVolume': quoteVolume, 'info': ticker, } async def fetch_tickers(self, symbols=None, params={}): await self.load_markets() response = await self.publicGetTicker(params) result = {} for i in range(0, len(response)): ticker = response[i] marketId = self.safe_string(ticker, 'symbol') if marketId is not None: if marketId in self.markets_by_id: market = self.markets_by_id[marketId] symbol = market['symbol'] result[symbol] = self.parse_ticker(ticker, market) else: result[marketId] = self.parse_ticker(ticker) return result async def fetch_ticker(self, symbol, params={}): await self.load_markets() market = self.market(symbol) request = { 'symbol': market['id'], } response = await self.publicGetTickerSymbol(self.extend(request, params)) if 'message' in response: raise ExchangeError(self.id + ' ' + response['message']) return self.parse_ticker(response, market) def parse_trade(self, trade, market=None): # # createMarketOrder # # { fee: "0.0004644", # id: 386394956, # price: "0.4644", # quantity: "1", # timestamp: "2018-10-25T16:41:44.780Z"} # # fetchTrades ... # # fetchMyTrades ... # timestamp = self.parse8601(trade['timestamp']) symbol = None marketId = self.safe_string(trade, 'symbol') if marketId is not None: if marketId in self.markets_by_id: market = self.markets_by_id[marketId] symbol = market['symbol'] else: symbol = marketId if symbol is None: if market is not None: symbol = market['symbol'] fee = None feeCost = self.safe_float(trade, 'fee') if feeCost is not None: feeCurrency = market['quote'] if market else None fee = { 'cost': feeCost, 'currency': feeCurrency, } # we use clientOrderId as the order id with HitBTC intentionally # because most of their endpoints will require clientOrderId # explained here: https://github.com/ccxt/ccxt/issues/5674 orderId = self.safe_string(trade, 'clientOrderId') price = self.safe_float(trade, 'price') amount = self.safe_float(trade, 'quantity') cost = price * amount side = self.safe_string(trade, 'side') id = self.safe_string(trade, 'id') return { 'info': trade, 'id': id, 'order': orderId, 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'symbol': symbol, 'type': None, 'side': side, 'takerOrMaker': None, 'price': price, 'amount': amount, 'cost': cost, 'fee': fee, } async def fetch_transactions(self, code=None, since=None, limit=None, params={}): await self.load_markets() currency = None request = {} if code is not None: currency = self.currency(code) request['asset'] = currency['id'] if since is not None: request['startTime'] = since response = await self.privateGetAccountTransactions(self.extend(request, params)) return self.parseTransactions(response, currency, since, limit) def parse_transaction(self, transaction, currency=None): # # { # id: 'd53ee9df-89bf-4d09-886e-849f8be64647', # index: 1044718371, # type: 'payout', # status: 'success', # currency: 'ETH', # amount: '4.522683200000000000000000', # createdAt: '2018-06-07T00:43:32.426Z', # updatedAt: '2018-06-07T00:45:36.447Z', # hash: '0x973e5683dfdf80a1fb1e0b96e19085b6489221d2ddf864daa46903c5ec283a0f', # address: '0xC5a59b21948C1d230c8C54f05590000Eb3e1252c', # fee: '0.00958', # }, # { # id: 'e6c63331-467e-4922-9edc-019e75d20ba3', # index: 1044714672, # type: 'exchangeToBank', # status: 'success', # currency: 'ETH', # amount: '4.532263200000000000', # createdAt: '2018-06-07T00:42:39.543Z', # updatedAt: '2018-06-07T00:42:39.683Z', # }, # { # id: '3b052faa-bf97-4636-a95c-3b5260015a10', # index: 1009280164, # type: 'bankToExchange', # status: 'success', # currency: 'CAS', # amount: '104797.875800000000000000', # createdAt: '2018-05-19T02:34:36.750Z', # updatedAt: '2018-05-19T02:34:36.857Z', # }, # { # id: 'd525249f-7498-4c81-ba7b-b6ae2037dc08', # index: 1009279948, # type: 'payin', # status: 'success', # currency: 'CAS', # amount: '104797.875800000000000000', # createdAt: '2018-05-19T02:30:16.698Z', # updatedAt: '2018-05-19T02:34:28.159Z', # hash: '0xa6530e1231de409cf1f282196ed66533b103eac1df2aa4a7739d56b02c5f0388', # address: '0xd53ed559a6d963af7cb3f3fcd0e7ca499054db8b', # } # # { # "id": "4f351f4f-a8ee-4984-a468-189ed590ddbd", # "index": 3112719565, # "type": "withdraw", # "status": "success", # "currency": "BCHOLD", # "amount": "0.02423133", # "createdAt": "2019-07-16T16:52:04.494Z", # "updatedAt": "2019-07-16T16:54:07.753Z" # } id = self.safe_string(transaction, 'id') timestamp = self.parse8601(self.safe_string(transaction, 'createdAt')) updated = self.parse8601(self.safe_string(transaction, 'updatedAt')) currencyId = self.safe_string(transaction, 'currency') code = self.safe_currency_code(currencyId, currency) status = self.parse_transaction_status(self.safe_string(transaction, 'status')) amount = self.safe_float(transaction, 'amount') address = self.safe_string(transaction, 'address') txid = self.safe_string(transaction, 'hash') fee = None feeCost = self.safe_float(transaction, 'fee') if feeCost is not None: fee = { 'cost': feeCost, 'currency': code, } type = self.parse_transaction_type(self.safe_string(transaction, 'type')) return { 'info': transaction, 'id': id, 'txid': txid, 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'address': address, 'tag': None, 'type': type, 'amount': amount, 'currency': code, 'status': status, 'updated': updated, 'fee': fee, } def parse_transaction_status(self, status): statuses = { 'pending': 'pending', 'failed': 'failed', 'success': 'ok', } return self.safe_string(statuses, status, status) def parse_transaction_type(self, type): types = { 'payin': 'deposit', 'payout': 'withdrawal', 'withdraw': 'withdrawal', } return self.safe_string(types, type, type) async def fetch_trades(self, symbol, since=None, limit=None, params={}): await self.load_markets() market = self.market(symbol) request = { 'symbol': market['id'], } if limit is not None: request['limit'] = limit if since is not None: request['sort'] = 'ASC' request['from'] = self.iso8601(since) response = await self.publicGetTradesSymbol(self.extend(request, params)) return self.parse_trades(response, market, since, limit) async def create_order(self, symbol, type, side, amount, price=None, params={}): await self.load_markets() market = self.market(symbol) # we use clientOrderId as the order id with HitBTC intentionally # because most of their endpoints will require clientOrderId # explained here: https://github.com/ccxt/ccxt/issues/5674 # their max accepted length is 32 characters uuid = self.uuid() parts = uuid.split('-') clientOrderId = ''.join(parts) clientOrderId = clientOrderId[0:32] amount = float(amount) request = { 'clientOrderId': clientOrderId, 'symbol': market['id'], 'side': side, 'quantity': self.amount_to_precision(symbol, amount), 'type': type, } if type == 'limit': request['price'] = self.price_to_precision(symbol, price) else: request['timeInForce'] = self.options['defaultTimeInForce'] response = await self.privatePostOrder(self.extend(request, params)) order = self.parse_order(response) if order['status'] == 'rejected': raise InvalidOrder(self.id + ' order was rejected by the exchange ' + self.json(order)) id = order['id'] self.orders[id] = order return order async def edit_order(self, id, symbol, type, side, amount=None, price=None, params={}): await self.load_markets() # we use clientOrderId as the order id with HitBTC intentionally # because most of their endpoints will require clientOrderId # explained here: https://github.com/ccxt/ccxt/issues/5674 # their max accepted length is 32 characters uuid = self.uuid() parts = uuid.split('-') requestClientId = ''.join(parts) requestClientId = requestClientId[0:32] request = { 'clientOrderId': id, 'requestClientId': requestClientId, } if amount is not None: request['quantity'] = self.amount_to_precision(symbol, amount) if price is not None: request['price'] = self.price_to_precision(symbol, price) response = await self.privatePatchOrderClientOrderId(self.extend(request, params)) order = self.parse_order(response) self.orders[order['id']] = order return order async def cancel_order(self, id, symbol=None, params={}): await self.load_markets() # we use clientOrderId as the order id with HitBTC intentionally # because most of their endpoints will require clientOrderId # explained here: https://github.com/ccxt/ccxt/issues/5674 request = { 'clientOrderId': id, } response = await self.privateDeleteOrderClientOrderId(self.extend(request, params)) return self.parse_order(response) def parse_order_status(self, status): statuses = { 'new': 'open', 'suspended': 'open', 'partiallyFilled': 'open', 'filled': 'closed', 'canceled': 'canceled', 'expired': 'failed', } return self.safe_string(statuses, status, status) def parse_order(self, order, market=None): # # createMarketOrder # # {clientOrderId: "fe36aa5e190149bf9985fb673bbb2ea0", # createdAt: "2018-10-25T16:41:44.780Z", # cumQuantity: "1", # id: "66799540063", # quantity: "1", # side: "sell", # status: "filled", # symbol: "XRPUSDT", # timeInForce: "FOK", # tradesReport: [{ fee: "0.0004644", # id: 386394956, # price: "0.4644", # quantity: "1", # timestamp: "2018-10-25T16:41:44.780Z"}], # type: "market", # updatedAt: "2018-10-25T16:41:44.780Z" } # created = self.parse8601(self.safe_string(order, 'createdAt')) updated = self.parse8601(self.safe_string(order, 'updatedAt')) marketId = self.safe_string(order, 'symbol') symbol = None if marketId is not None: if marketId in self.markets_by_id: market = self.markets_by_id[marketId] symbol = market['symbol'] else: symbol = marketId if symbol is None: if market is not None: symbol = market['id'] amount = self.safe_float(order, 'quantity') filled = self.safe_float(order, 'cumQuantity') status = self.parse_order_status(self.safe_string(order, 'status')) # we use clientOrderId as the order id with HitBTC intentionally # because most of their endpoints will require clientOrderId # explained here: https://github.com/ccxt/ccxt/issues/5674 id = self.safe_string(order, 'clientOrderId') price = self.safe_float(order, 'price') if price is None: if id in self.orders: price = self.orders[id]['price'] remaining = None cost = None if amount is not None: if filled is not None: remaining = amount - filled if price is not None: cost = filled * price type = self.safe_string(order, 'type') side = self.safe_string(order, 'side') trades = self.safe_value(order, 'tradesReport') fee = None average = None if trades is not None: trades = self.parse_trades(trades, market) feeCost = None numTrades = len(trades) tradesCost = 0 for i in range(0, numTrades): if feeCost is None: feeCost = 0 tradesCost = self.sum(tradesCost, trades[i]['cost']) feeCost = self.sum(feeCost, trades[i]['fee']['cost']) cost = tradesCost if (filled is not None) and (filled > 0): average = cost / filled if type == 'market': if price is None: price = average if feeCost is not None: fee = { 'cost': feeCost, 'currency': market['quote'], } return { 'id': id, 'timestamp': created, 'datetime': self.iso8601(created), 'lastTradeTimestamp': updated, 'status': status, 'symbol': symbol, 'type': type, 'side': side, 'price': price, 'average': average, 'amount': amount, 'cost': cost, 'filled': filled, 'remaining': remaining, 'fee': fee, 'trades': trades, 'info': order, } async def fetch_order(self, id, symbol=None, params={}): await self.load_markets() # we use clientOrderId as the order id with HitBTC intentionally # because most of their endpoints will require clientOrderId # explained here: https://github.com/ccxt/ccxt/issues/5674 request = { 'clientOrderId': id, } response = await self.privateGetHistoryOrder(self.extend(request, params)) numOrders = len(response) if numOrders > 0: return self.parse_order(response[0]) raise OrderNotFound(self.id + ' order ' + id + ' not found') async def fetch_open_order(self, id, symbol=None, params={}): await self.load_markets() # we use clientOrderId as the order id with HitBTC intentionally # because most of their endpoints will require clientOrderId # explained here: https://github.com/ccxt/ccxt/issues/5674 request = { 'clientOrderId': id, } response = await self.privateGetOrderClientOrderId(self.extend(request, params)) return self.parse_order(response) async def fetch_open_orders(self, symbol=None, since=None, limit=None, params={}): await self.load_markets() market = None request = {} if symbol is not None: market = self.market(symbol) request['symbol'] = market['id'] response = await self.privateGetOrder(self.extend(request, params)) return self.parse_orders(response, market, since, limit) async def fetch_closed_orders(self, symbol=None, since=None, limit=None, params={}): await self.load_markets() market = None request = {} if symbol is not None: market = self.market(symbol) request['symbol'] = market['id'] if limit is not None: request['limit'] = limit if since is not None: request['from'] = self.iso8601(since) response = await self.privateGetHistoryOrder(self.extend(request, params)) parsedOrders = self.parse_orders(response, market) orders = [] for i in range(0, len(parsedOrders)): order = parsedOrders[i] status = order['status'] if (status == 'closed') or (status == 'canceled'): orders.append(order) return self.filter_by_since_limit(orders, since, limit) async def fetch_my_trades(self, symbol=None, since=None, limit=None, params={}): await self.load_markets() request = { # 'symbol': 'BTC/USD', # optional # 'sort': 'DESC', # or 'ASC' # 'by': 'timestamp', # or 'id' String timestamp by default, or id # 'from': 'Datetime or Number', # ISO 8601 # 'till': 'Datetime or Number', # 'limit': 100, # 'offset': 0, } market = None if symbol is not None: market = self.market(symbol) request['symbol'] = market['id'] if since is not None: request['from'] = self.iso8601(since) if limit is not None: request['limit'] = limit response = await self.privateGetHistoryTrades(self.extend(request, params)) # # [ # { # "id": 9535486, # "clientOrderId": "f8dbaab336d44d5ba3ff578098a68454", # "orderId": 816088377, # "symbol": "ETHBTC", # "side": "sell", # "quantity": "0.061", # "price": "0.045487", # "fee": "0.000002775", # "timestamp": "2017-05-17T12:32:57.848Z" # }, # { # "id": 9535437, # "clientOrderId": "27b9bfc068b44194b1f453c7af511ed6", # "orderId": 816088021, # "symbol": "ETHBTC", # "side": "buy", # "quantity": "0.038", # "price": "0.046000", # "fee": "-0.000000174", # "timestamp": "2017-05-17T12:30:57.848Z" # } # ] # return self.parse_trades(response, market, since, limit) async def fetch_order_trades(self, id, symbol=None, since=None, limit=None, params={}): # The id needed here is the exchange's id, and not the clientOrderID, # which is the id that is stored in the unified order id # To get the exchange's id you need to grab it from order['info']['id'] await self.load_markets() market = None if symbol is not None: market = self.market(symbol) request = { 'id': id, } response = await self.privateGetHistoryOrderIdTrades(self.extend(request, params)) numOrders = len(response) if numOrders > 0: return self.parse_trades(response, market, since, limit) raise OrderNotFound(self.id + ' order ' + id + ' not found, ' + self.id + '.fetchOrderTrades() requires an exchange-specific order id, you need to grab it from order["info"]["id"]') async def create_deposit_address(self, code, params={}): await self.load_markets() currency = self.currency(code) request = { 'currency': currency['id'], } response = await self.privatePostAccountCryptoAddressCurrency(self.extend(request, params)) address = self.safe_string(response, 'address') self.check_address(address) tag = self.safe_string(response, 'paymentId') return { 'currency': currency, 'address': address, 'tag': tag, 'info': response, } async def fetch_deposit_address(self, code, params={}): await self.load_markets() currency = self.currency(code) request = { 'currency': currency['id'], } response = await self.privateGetAccountCryptoAddressCurrency(self.extend(request, params)) address = self.safe_string(response, 'address') self.check_address(address) tag = self.safe_string(response, 'paymentId') return { 'currency': currency['code'], 'address': address, 'tag': tag, 'info': response, } async def withdraw(self, code, amount, address, tag=None, params={}): await self.load_markets() self.check_address(address) currency = self.currency(code) request = { 'currency': currency['id'], 'amount': float(amount), 'address': address, } if tag: request['paymentId'] = tag response = await self.privatePostAccountCryptoWithdraw(self.extend(request, params)) return { 'info': response, 'id': response['id'], } def sign(self, path, api='public', method='GET', params={}, headers=None, body=None): url = '/api/' + self.version + '/' query = self.omit(params, self.extract_params(path)) if api == 'public': url += api + '/' + self.implode_params(path, params) if query: url += '?' + self.urlencode(query) else: self.check_required_credentials() url += self.implode_params(path, params) if method == 'GET': if query: url += '?' + self.urlencode(query) elif query: body = self.json(query) payload = self.encode(self.apiKey + ':' + self.secret) auth = base64.b64encode(payload) headers = { 'Authorization': 'Basic ' + self.decode(auth), 'Content-Type': 'application/json', } url = self.urls['api'] + url return {'url': url, 'method': method, 'body': body, 'headers': headers} def handle_errors(self, code, reason, url, method, headers, body, response, requestHeaders, requestBody): if response is None: return if code >= 400: feedback = self.id + ' ' + body # {"code":504,"message":"Gateway Timeout","description":""} if (code == 503) or (code == 504): raise ExchangeNotAvailable(feedback) # {"error":{"code":20002,"message":"Order not found","description":""}} if body[0] == '{': if 'error' in response: code = self.safe_string(response['error'], 'code') exceptions = self.exceptions if code in exceptions: raise exceptions[code](feedback) message = self.safe_string(response['error'], 'message') if message == 'Duplicate clientOrderId': raise InvalidOrder(feedback) raise ExchangeError(feedback)

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rt.hitbtc import hitbtc import base64 import math from ccxt.base.errors import ExchangeError from ccxt.base.errors import PermissionDenied from ccxt.base.errors import InsufficientFunds from ccxt.base.errors import InvalidOrder from ccxt.base.errors import OrderNotFound from ccxt.base.errors import ExchangeNotAvailable from ccxt.base.decimal_to_precision import TRUNCATE from ccxt.base.decimal_to_precision import DECIMAL_PLACES class hitbtc2 (hitbtc): def describe(self): return self.deep_extend(super(hitbtc2, self).describe(), { 'id': 'hitbtc2', 'name': 'HitBTC', 'countries': ['HK'], 'rateLimit': 1500, 'version': '2', 'has': { 'createDepositAddress': True, 'fetchDepositAddress': True, 'CORS': True, 'editOrder': True, 'fetchCurrencies': True, 'fetchOHLCV': True, 'fetchTickers': True, 'fetchOrder': True, 'fetchOrders': False, 'fetchOpenOrders': True, 'fetchClosedOrders': True, 'fetchMyTrades': True, 'withdraw': True, 'fetchOrderTrades': False, 'fetchDeposits': False, 'fetchWithdrawals': False, 'fetchTransactions': True, 'fetchTradingFee': True, }, 'timeframes': { '1m': 'M1', '3m': 'M3', '5m': 'M5', '15m': 'M15', '30m': 'M30', '1h': 'H1', '4h': 'H4', '1d': 'D1', '1w': 'D7', '1M': '1M', }, 'urls': { 'logo': 'https://user-images.githubusercontent.com/1294454/27766555-8eaec20e-5edc-11e7-9c5b-6dc69fc42f5e.jpg', 'api': 'https://api.hitbtc.com', 'www': 'https://hitbtc.com', 'referral': 'https://hitbtc.com/?ref_id=5a5d39a65d466', 'doc': [ 'https://api.hitbtc.com', 'https://github.com/hitbtc-com/hitbtc-api/blob/master/APIv2.md', ], 'fees': [ 'https://hitbtc.com/fees-and-limits', 'https://support.hitbtc.com/hc/en-us/articles/115005148605-Fees-and-limits', ], }, 'api': { 'public': { 'get': [ 'symbol', 'symbol/{symbol}', 'currency', 'currency/{currency}', 'ticker', 'ticker/{symbol}', 'trades/{symbol}', 'orderbook/{symbol}', 'candles/{symbol}', ], }, 'private': { 'get': [ 'order', 'order/{clientOrderId}', 'trading/balance', 'trading/fee/all', 'trading/fee/{symbol}', 'history/trades', 'history/order', 'history/order/{id}/trades', 'account/balance', 'account/transactions', 'account/transactions/{id}', 'account/crypto/address/{currency}', ], 'post': [ 'order', 'account/crypto/withdraw', 'account/crypto/address/{currency}', 'account/transfer', ], 'put': [ 'order/{clientOrderId}', 'account/crypto/withdraw/{id}', ], 'delete': [ 'order', 'order/{clientOrderId}', 'account/crypto/withdraw/{id}', ], 'patch': [ 'order/{clientOrderId}', ], }, }, 'fees': { 'trading': { 'tierBased': False, 'percentage': True, 'maker': 0.1 / 100, 'taker': 0.2 / 100, }, 'funding': { 'tierBased': False, 'percentage': False, 'withdraw': { 'BTC': 0.001, 'BCC': 0.0018, 'ETH': 0.00958, 'BCH': 0.0018, 'USDT': 100, 'DASH': 0.03, 'BTG': 0.0005, 'XRP': 0.509, 'LTC': 0.003, 'ZEC': 0.0001, 'XMR': 0.09, '1ST': 0.84, 'ADX': 5.7, 'AE': 6.7, 'AEON': 0.01006, 'AIR': 565, 'AMM': 14, 'AMP': 342, 'ANT': 6.7, 'ARDR': 1, 'ARN': 18.5, 'ART': 26, 'ATB': 0.0004, 'ATL': 27, 'ATM': 504, 'ATS': 860, 'AVT': 1.9, 'BAS': 113, 'BCN': 0.1, 'BET': 124, 'BKB': 46, 'BMC': 32, 'BMT': 100, 'BNT': 2.57, 'BQX': 4.7, 'BTCA': 351.21, 'BTM': 40, 'BTX': 0.04, 'BUS': 0.004, 'CAPP': 97, 'CCT': 6, 'CDT': 100, 'CDX': 30, 'CFI': 61, 'CL': 13.85, 'CLD': 0.88, 'CND': 574, 'CNX': 0.04, 'COSS': 65, 'CPAY': 5.487, 'CSNO': 16, 'CTR': 15, 'CTX': 146, 'CVC': 8.46, 'DATA': 12.949, 'DBIX': 0.0168, 'DCN': 1280, 'DCT': 0.02, 'DDF': 342, 'DENT': 1000, 'DGB': 0.4, 'DGD': 0.01, 'DICE': 0.32, 'DLT': 0.26, 'DNT': 0.21, 'DOGE': 2, 'DOV': 34, 'DRPU': 24, 'DRT': 240, 'DSH': 0.017, 'EBET': 84, 'EBTC': 20, 'EBTCOLD': 6.6, 'ECAT': 14, 'EDG': 2, 'EDO': 2.9, 'EKO': 1136.36, 'ELE': 0.00172, 'ELM': 0.004, 'EMC': 0.03, 'MGO': 14, 'ENJ': 163, 'EOS': 1.5, 'ERO': 34, 'ETBS': 15, 'ETC': 0.002, 'ETP': 0.004, 'EVX': 5.4, 'EXN': 456, 'FCN': 0.000005, 'FRD': 65, 'FUEL': 123.00105, 'FUN': 202.9598309, 'FYN': 1.849, 'FYP': 66.13, 'GAME': 0.004, 'GNO': 0.0034, 'GUP': 4, 'GVT': 1.2, 'HSR': 0.04, 'HAC': 144, 'HDG': 7, 'HGT': 1082, 'HPC': 0.4, 'HVN': 120, 'ICN': 0.55, 'ICO': 34, 'ICOS': 0.35, 'IND': 76, 'INDI': 790, 'ITS': 15.0012, 'IXT': 11, 'KBR': 143, 'KICK': 112, 'KMD': 4, 'LA': 41, 'LEND': 388, 'LAT': 1.44, 'LIFE': 13000, 'LRC': 27, 'LSK': 0.3, 'LOC': 11.076, 'LUN': 0.34, 'MAID': 5, 'MANA': 143, 'MCAP': 5.44, 'MIPS': 43, 'MNE': 1.33, 'MSP': 121, 'MCO': 0.357, 'MTH': 92, 'MYB': 3.9, 'NDC': 165, 'NEBL': 0.04, 'NET': 3.96, 'NTO': 998, 'NGC': 2.368, 'NXC': 13.39, 'NXT': 3, 'OAX': 15, 'ODN': 0.004, 'OMG': 2, 'OPT': 335, 'ORME': 2.8, 'OTN': 0.57, 'PAY': 3.1, 'PIX': 96, 'PLBT': 0.33, 'PLR': 114, 'PLU': 0.87, 'POE': 784, 'POLL': 3.5, 'PPT': 2, 'PRE': 32, 'PRG': 39, 'PRO': 41, 'PRS': 60, 'PTOY': 0.5, 'QAU': 63, 'QCN': 0.03, 'QTUM': 0.04, 'QVT': 64, 'REP': 0.02, 'RKC': 15, 'RLC': 1.21, 'RVT': 14, 'SC': 30, 'SAN': 2.24, 'SBD': 0.03, 'SCL': 2.6, 'SISA': 1640, 'SKIN': 407, 'SWFTC': 352.94, 'SMART': 0.4, 'SMS': 0.0375, 'SNC': 36, 'SNGLS': 4, 'SNM': 48, 'SNT': 233, 'STAR': 0.144, 'STORM': 153.19, 'STEEM': 0.01, 'STRAT': 0.01, 'SPF': 14.4, 'STU': 14, 'STX': 11, 'SUB': 17, 'SUR': 3, 'SWT': 0.51, 'TAAS': 0.91, 'TBT': 2.37, 'TFL': 15, 'TIME': 0.03, 'TIX': 7.1, 'TKN': 1, 'TGT': 173, 'TKR': 84, 'TNT': 90, 'TRST': 1.6, 'TRX': 270, 'UET': 480, 'UGT': 15, 'UTT': 3, 'VEN': 14, 'VERI': 0.037, 'VIB': 50, 'VIBE': 145, 'VOISE': 618, 'WEALTH': 0.0168, 'WINGS': 2.4, 'WTC': 0.75, 'WRC': 48, 'XAUR': 3.23, 'XDN': 0.01, 'XEM': 15, 'XUC': 0.9, 'YOYOW': 140, 'ZAP': 24, 'ZRX': 23, 'ZSC': 191, }, 'deposit': { 'BTC': 0, 'ETH': 0, 'BCH': 0, 'USDT': 0, 'BTG': 0, 'LTC': 0, 'ZEC': 0, 'XMR': 0, '1ST': 0, 'ADX': 0, 'AE': 0, 'AEON': 0, 'AIR': 0, 'AMP': 0, 'ANT': 0, 'ARDR': 0, 'ARN': 0, 'ART': 0, 'ATB': 0, 'ATL': 0, 'ATM': 0, 'ATS': 0, 'AVT': 0, 'BAS': 0, 'BCN': 0, 'BET': 0, 'BKB': 0, 'BMC': 0, 'BMT': 0, 'BNT': 0, 'BQX': 0, 'BTM': 0, 'BTX': 0, 'BUS': 0, 'CCT': 0, 'CDT': 0, 'CDX': 0, 'CFI': 0, 'CLD': 0, 'CND': 0, 'CNX': 0, 'COSS': 0, 'CSNO': 0, 'CTR': 0, 'CTX': 0, 'CVC': 0, 'DBIX': 0, 'DCN': 0, 'DCT': 0, 'DDF': 0, 'DENT': 0, 'DGB': 0, 'DGD': 0, 'DICE': 0, 'DLT': 0, 'DNT': 0, 'DOGE': 0, 'DOV': 0, 'DRPU': 0, 'DRT': 0, 'DSH': 0, 'EBET': 0, 'EBTC': 0, 'EBTCOLD': 0, 'ECAT': 0, 'EDG': 0, 'EDO': 0, 'ELE': 0, 'ELM': 0, 'EMC': 0, 'EMGO': 0, 'ENJ': 0, 'EOS': 0, 'ERO': 0, 'ETBS': 0, 'ETC': 0, 'ETP': 0, 'EVX': 0, 'EXN': 0, 'FRD': 0, 'FUEL': 0, 'FUN': 0, 'FYN': 0, 'FYP': 0, 'GNO': 0, 'GUP': 0, 'GVT': 0, 'HAC': 0, 'HDG': 0, 'HGT': 0, 'HPC': 0, 'HVN': 0, 'ICN': 0, 'ICO': 0, 'ICOS': 0, 'IND': 0, 'INDI': 0, 'ITS': 0, 'IXT': 0, 'KBR': 0, 'KICK': 0, 'LA': 0, 'LAT': 0, 'LIFE': 0, 'LRC': 0, 'LSK': 0, 'LUN': 0, 'MAID': 0, 'MANA': 0, 'MCAP': 0, 'MIPS': 0, 'MNE': 0, 'MSP': 0, 'MTH': 0, 'MYB': 0, 'NDC': 0, 'NEBL': 0, 'NET': 0, 'NTO': 0, 'NXC': 0, 'NXT': 0, 'OAX': 0, 'ODN': 0, 'OMG': 0, 'OPT': 0, 'ORME': 0, 'OTN': 0, 'PAY': 0, 'PIX': 0, 'PLBT': 0, 'PLR': 0, 'PLU': 0, 'POE': 0, 'POLL': 0, 'PPT': 0, 'PRE': 0, 'PRG': 0, 'PRO': 0, 'PRS': 0, 'PTOY': 0, 'QAU': 0, 'QCN': 0, 'QTUM': 0, 'QVT': 0, 'REP': 0, 'RKC': 0, 'RVT': 0, 'SAN': 0, 'SBD': 0, 'SCL': 0, 'SISA': 0, 'SKIN': 0, 'SMART': 0, 'SMS': 0, 'SNC': 0, 'SNGLS': 0, 'SNM': 0, 'SNT': 0, 'STEEM': 0, 'STRAT': 0, 'STU': 0, 'STX': 0, 'SUB': 0, 'SUR': 0, 'SWT': 0, 'TAAS': 0, 'TBT': 0, 'TFL': 0, 'TIME': 0, 'TIX': 0, 'TKN': 0, 'TKR': 0, 'TNT': 0, 'TRST': 0, 'TRX': 0, 'UET': 0, 'UGT': 0, 'VEN': 0, 'VERI': 0, 'VIB': 0, 'VIBE': 0, 'VOISE': 0, 'WEALTH': 0, 'WINGS': 0, 'WTC': 0, 'XAUR': 0, 'XDN': 0, 'XEM': 0, 'XUC': 0, 'YOYOW': 0, 'ZAP': 0, 'ZRX': 0, 'ZSC': 0, }, }, }, 'options': { 'defaultTimeInForce': 'FOK', }, 'exceptions': { '1003': PermissionDenied, '2010': InvalidOrder, '2011': InvalidOrder, '2020': InvalidOrder, '20002': OrderNotFound, '20001': InsufficientFunds, }, }) def fee_to_precision(self, symbol, fee): return self.decimal_to_precision(fee, TRUNCATE, 8, DECIMAL_PLACES) async def fetch_markets(self, params={}): response = await self.publicGetSymbol(params) result = [] for i in range(0, len(response)): market = response[i] id = self.safe_string(market, 'id') baseId = self.safe_string(market, 'baseCurrency') quoteId = self.safe_string(market, 'quoteCurrency') base = self.safe_currency_code(baseId) quote = self.safe_currency_code(quoteId) symbol = base + '/' + quote lot = self.safe_float(market, 'quantityIncrement') step = self.safe_float(market, 'tickSize') precision = { 'price': self.precision_from_string(market['tickSize']), 'amount': -1 * int(math.log10(lot)), } taker = self.safe_float(market, 'takeLiquidityRate') maker = self.safe_float(market, 'provideLiquidityRate') result.append(self.extend(self.fees['trading'], { 'info': market, 'id': id, 'symbol': symbol, 'base': base, 'quote': quote, 'baseId': baseId, 'quoteId': quoteId, 'active': True, 'taker': taker, 'maker': maker, 'precision': precision, 'limits': { 'amount': { 'min': lot, 'max': None, }, 'price': { 'min': step, 'max': None, }, 'cost': { 'min': lot * step, 'max': None, }, }, })) return result async def fetch_currencies(self, params={}): response = await self.publicGetCurrency(params) result = {} for i in range(0, len(response)): currency = response[i] id = self.safe_string(currency, 'id') precision = 8 code = self.safe_currency_code(id) payin = self.safe_value(currency, 'payinEnabled') payout = self.safe_value(currency, 'payoutEnabled') transfer = self.safe_value(currency, 'transferEnabled') active = payin and payout and transfer if 'disabled' in currency: if currency['disabled']: active = False type = 'fiat' if ('crypto' in list(currency.keys())) and currency['crypto']: type = 'crypto' name = self.safe_string(currency, 'fullName') result[code] = { 'id': id, 'code': code, 'type': type, 'payin': payin, 'payout': payout, 'transfer': transfer, 'info': currency, 'name': name, 'active': active, 'fee': self.safe_float(currency, 'payoutFee'), 'precision': precision, 'limits': { 'amount': { 'min': math.pow(10, -precision), 'max': math.pow(10, precision), }, 'price': { 'min': math.pow(10, -precision), 'max': math.pow(10, precision), }, 'cost': { 'min': None, 'max': None, }, 'withdraw': { 'min': None, 'max': math.pow(10, precision), }, }, } return result async def fetch_trading_fee(self, symbol, params={}): await self.load_markets() market = self.market(symbol) request = self.extend({ 'symbol': market['id'], }, self.omit(params, 'symbol')) response = await self.privateGetTradingFeeSymbol(request) return { 'info': response, 'maker': self.safe_float(response, 'provideLiquidityRate'), 'taker': self.safe_float(response, 'takeLiquidityRate'), } async def fetch_balance(self, params={}): await self.load_markets() type = self.safe_string(params, 'type', 'trading') method = 'privateGet' + self.capitalize(type) + 'Balance' query = self.omit(params, 'type') response = await getattr(self, method)(query) result = {'info': response} for i in range(0, len(response)): balance = response[i] currencyId = self.safe_string(balance, 'currency') code = self.safe_currency_code(currencyId) account = self.account() account['free'] = self.safe_float(balance, 'available') account['used'] = self.safe_float(balance, 'reserved') result[code] = account return self.parse_balance(result) def parse_ohlcv(self, ohlcv, market=None, timeframe='1d', since=None, limit=None): timestamp = self.parse8601(ohlcv['timestamp']) return [ timestamp, float(ohlcv['open']), float(ohlcv['max']), float(ohlcv['min']), float(ohlcv['close']), float(ohlcv['volume']), ] async def fetch_ohlcv(self, symbol, timeframe='1m', since=None, limit=None, params={}): await self.load_markets() market = self.market(symbol) request = { 'symbol': market['id'], 'period': self.timeframes[timeframe], } if since is not None: request['from'] = self.iso8601(since) if limit is not None: request['limit'] = limit response = await self.publicGetCandlesSymbol(self.extend(request, params)) return self.parse_ohlcvs(response, market, timeframe, since, limit) async def fetch_order_book(self, symbol, limit=None, params={}): await self.load_markets() request = { 'symbol': self.market_id(symbol), } if limit is not None: request['limit'] = limit response = await self.publicGetOrderbookSymbol(self.extend(request, params)) return self.parse_order_book(response, None, 'bid', 'ask', 'price', 'size') def parse_ticker(self, ticker, market=None): timestamp = self.parse8601(ticker['timestamp']) symbol = None if market is not None: symbol = market['symbol'] baseVolume = self.safe_float(ticker, 'volume') quoteVolume = self.safe_float(ticker, 'volumeQuote') open = self.safe_float(ticker, 'open') last = self.safe_float(ticker, 'last') change = None percentage = None average = None if last is not None and open is not None: change = last - open average = self.sum(last, open) / 2 if open > 0: percentage = change / open * 100 vwap = None if quoteVolume is not None: if baseVolume is not None: if baseVolume > 0: vwap = quoteVolume / baseVolume return { 'symbol': symbol, 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'high': self.safe_float(ticker, 'high'), 'low': self.safe_float(ticker, 'low'), 'bid': self.safe_float(ticker, 'bid'), 'bidVolume': None, 'ask': self.safe_float(ticker, 'ask'), 'askVolume': None, 'vwap': vwap, 'open': open, 'close': last, 'last': last, 'previousClose': None, 'change': change, 'percentage': percentage, 'average': average, 'baseVolume': baseVolume, 'quoteVolume': quoteVolume, 'info': ticker, } async def fetch_tickers(self, symbols=None, params={}): await self.load_markets() response = await self.publicGetTicker(params) result = {} for i in range(0, len(response)): ticker = response[i] marketId = self.safe_string(ticker, 'symbol') if marketId is not None: if marketId in self.markets_by_id: market = self.markets_by_id[marketId] symbol = market['symbol'] result[symbol] = self.parse_ticker(ticker, market) else: result[marketId] = self.parse_ticker(ticker) return result async def fetch_ticker(self, symbol, params={}): await self.load_markets() market = self.market(symbol) request = { 'symbol': market['id'], } response = await self.publicGetTickerSymbol(self.extend(request, params)) if 'message' in response: raise ExchangeError(self.id + ' ' + response['message']) return self.parse_ticker(response, market) def parse_trade(self, trade, market=None): timestamp = self.parse8601(trade['timestamp']) symbol = None marketId = self.safe_string(trade, 'symbol') if marketId is not None: if marketId in self.markets_by_id: market = self.markets_by_id[marketId] symbol = market['symbol'] else: symbol = marketId if symbol is None: if market is not None: symbol = market['symbol'] fee = None feeCost = self.safe_float(trade, 'fee') if feeCost is not None: feeCurrency = market['quote'] if market else None fee = { 'cost': feeCost, 'currency': feeCurrency, } orderId = self.safe_string(trade, 'clientOrderId') price = self.safe_float(trade, 'price') amount = self.safe_float(trade, 'quantity') cost = price * amount side = self.safe_string(trade, 'side') id = self.safe_string(trade, 'id') return { 'info': trade, 'id': id, 'order': orderId, 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'symbol': symbol, 'type': None, 'side': side, 'takerOrMaker': None, 'price': price, 'amount': amount, 'cost': cost, 'fee': fee, } async def fetch_transactions(self, code=None, since=None, limit=None, params={}): await self.load_markets() currency = None request = {} if code is not None: currency = self.currency(code) request['asset'] = currency['id'] if since is not None: request['startTime'] = since response = await self.privateGetAccountTransactions(self.extend(request, params)) return self.parseTransactions(response, currency, since, limit) def parse_transaction(self, transaction, currency=None): id = self.safe_string(transaction, 'id') timestamp = self.parse8601(self.safe_string(transaction, 'createdAt')) updated = self.parse8601(self.safe_string(transaction, 'updatedAt')) currencyId = self.safe_string(transaction, 'currency') code = self.safe_currency_code(currencyId, currency) status = self.parse_transaction_status(self.safe_string(transaction, 'status')) amount = self.safe_float(transaction, 'amount') address = self.safe_string(transaction, 'address') txid = self.safe_string(transaction, 'hash') fee = None feeCost = self.safe_float(transaction, 'fee') if feeCost is not None: fee = { 'cost': feeCost, 'currency': code, } type = self.parse_transaction_type(self.safe_string(transaction, 'type')) return { 'info': transaction, 'id': id, 'txid': txid, 'timestamp': timestamp, 'datetime': self.iso8601(timestamp), 'address': address, 'tag': None, 'type': type, 'amount': amount, 'currency': code, 'status': status, 'updated': updated, 'fee': fee, } def parse_transaction_status(self, status): statuses = { 'pending': 'pending', 'failed': 'failed', 'success': 'ok', } return self.safe_string(statuses, status, status) def parse_transaction_type(self, type): types = { 'payin': 'deposit', 'payout': 'withdrawal', 'withdraw': 'withdrawal', } return self.safe_string(types, type, type) async def fetch_trades(self, symbol, since=None, limit=None, params={}): await self.load_markets() market = self.market(symbol) request = { 'symbol': market['id'], } if limit is not None: request['limit'] = limit if since is not None: request['sort'] = 'ASC' request['from'] = self.iso8601(since) response = await self.publicGetTradesSymbol(self.extend(request, params)) return self.parse_trades(response, market, since, limit) async def create_order(self, symbol, type, side, amount, price=None, params={}): await self.load_markets() market = self.market(symbol) uuid = self.uuid() parts = uuid.split('-') clientOrderId = ''.join(parts) clientOrderId = clientOrderId[0:32] amount = float(amount) request = { 'clientOrderId': clientOrderId, 'symbol': market['id'], 'side': side, 'quantity': self.amount_to_precision(symbol, amount), 'type': type, } if type == 'limit': request['price'] = self.price_to_precision(symbol, price) else: request['timeInForce'] = self.options['defaultTimeInForce'] response = await self.privatePostOrder(self.extend(request, params)) order = self.parse_order(response) if order['status'] == 'rejected': raise InvalidOrder(self.id + ' order was rejected by the exchange ' + self.json(order)) id = order['id'] self.orders[id] = order return order async def edit_order(self, id, symbol, type, side, amount=None, price=None, params={}): await self.load_markets() uuid = self.uuid() parts = uuid.split('-') requestClientId = ''.join(parts) requestClientId = requestClientId[0:32] request = { 'clientOrderId': id, 'requestClientId': requestClientId, } if amount is not None: request['quantity'] = self.amount_to_precision(symbol, amount) if price is not None: request['price'] = self.price_to_precision(symbol, price) response = await self.privatePatchOrderClientOrderId(self.extend(request, params)) order = self.parse_order(response) self.orders[order['id']] = order return order async def cancel_order(self, id, symbol=None, params={}): await self.load_markets() request = { 'clientOrderId': id, } response = await self.privateDeleteOrderClientOrderId(self.extend(request, params)) return self.parse_order(response) def parse_order_status(self, status): statuses = { 'new': 'open', 'suspended': 'open', 'partiallyFilled': 'open', 'filled': 'closed', 'canceled': 'canceled', 'expired': 'failed', } return self.safe_string(statuses, status, status) def parse_order(self, order, market=None): created = self.parse8601(self.safe_string(order, 'createdAt')) updated = self.parse8601(self.safe_string(order, 'updatedAt')) marketId = self.safe_string(order, 'symbol') symbol = None if marketId is not None: if marketId in self.markets_by_id: market = self.markets_by_id[marketId] symbol = market['symbol'] else: symbol = marketId if symbol is None: if market is not None: symbol = market['id'] amount = self.safe_float(order, 'quantity') filled = self.safe_float(order, 'cumQuantity') status = self.parse_order_status(self.safe_string(order, 'status')) id = self.safe_string(order, 'clientOrderId') price = self.safe_float(order, 'price') if price is None: if id in self.orders: price = self.orders[id]['price'] remaining = None cost = None if amount is not None: if filled is not None: remaining = amount - filled if price is not None: cost = filled * price type = self.safe_string(order, 'type') side = self.safe_string(order, 'side') trades = self.safe_value(order, 'tradesReport') fee = None average = None if trades is not None: trades = self.parse_trades(trades, market) feeCost = None numTrades = len(trades) tradesCost = 0 for i in range(0, numTrades): if feeCost is None: feeCost = 0 tradesCost = self.sum(tradesCost, trades[i]['cost']) feeCost = self.sum(feeCost, trades[i]['fee']['cost']) cost = tradesCost if (filled is not None) and (filled > 0): average = cost / filled if type == 'market': if price is None: price = average if feeCost is not None: fee = { 'cost': feeCost, 'currency': market['quote'], } return { 'id': id, 'timestamp': created, 'datetime': self.iso8601(created), 'lastTradeTimestamp': updated, 'status': status, 'symbol': symbol, 'type': type, 'side': side, 'price': price, 'average': average, 'amount': amount, 'cost': cost, 'filled': filled, 'remaining': remaining, 'fee': fee, 'trades': trades, 'info': order, } async def fetch_order(self, id, symbol=None, params={}): await self.load_markets() request = { 'clientOrderId': id, } response = await self.privateGetHistoryOrder(self.extend(request, params)) numOrders = len(response) if numOrders > 0: return self.parse_order(response[0]) raise OrderNotFound(self.id + ' order ' + id + ' not found') async def fetch_open_order(self, id, symbol=None, params={}): await self.load_markets() request = { 'clientOrderId': id, } response = await self.privateGetOrderClientOrderId(self.extend(request, params)) return self.parse_order(response) async def fetch_open_orders(self, symbol=None, since=None, limit=None, params={}): await self.load_markets() market = None request = {} if symbol is not None: market = self.market(symbol) request['symbol'] = market['id'] response = await self.privateGetOrder(self.extend(request, params)) return self.parse_orders(response, market, since, limit) async def fetch_closed_orders(self, symbol=None, since=None, limit=None, params={}): await self.load_markets() market = None request = {} if symbol is not None: market = self.market(symbol) request['symbol'] = market['id'] if limit is not None: request['limit'] = limit if since is not None: request['from'] = self.iso8601(since) response = await self.privateGetHistoryOrder(self.extend(request, params)) parsedOrders = self.parse_orders(response, market) orders = [] for i in range(0, len(parsedOrders)): order = parsedOrders[i] status = order['status'] if (status == 'closed') or (status == 'canceled'): orders.append(order) return self.filter_by_since_limit(orders, since, limit) async def fetch_my_trades(self, symbol=None, since=None, limit=None, params={}): await self.load_markets() request = { } market = None if symbol is not None: market = self.market(symbol) request['symbol'] = market['id'] if since is not None: request['from'] = self.iso8601(since) if limit is not None: request['limit'] = limit response = await self.privateGetHistoryTrades(self.extend(request, params)) return self.parse_trades(response, market, since, limit) async def fetch_order_trades(self, id, symbol=None, since=None, limit=None, params={}): # which is the id that is stored in the unified order id # To get the exchange's id you need to grab it from order['info']['id'] await self.load_markets() market = None if symbol is not None: market = self.market(symbol) request = { 'id': id, } response = await self.privateGetHistoryOrderIdTrades(self.extend(request, params)) numOrders = len(response) if numOrders > 0: return self.parse_trades(response, market, since, limit) raise OrderNotFound(self.id + ' order ' + id + ' not found, ' + self.id + '.fetchOrderTrades() requires an exchange-specific order id, you need to grab it from order["info"]["id"]') async def create_deposit_address(self, code, params={}): await self.load_markets() currency = self.currency(code) request = { 'currency': currency['id'], } response = await self.privatePostAccountCryptoAddressCurrency(self.extend(request, params)) address = self.safe_string(response, 'address') self.check_address(address) tag = self.safe_string(response, 'paymentId') return { 'currency': currency, 'address': address, 'tag': tag, 'info': response, } async def fetch_deposit_address(self, code, params={}): await self.load_markets() currency = self.currency(code) request = { 'currency': currency['id'], } response = await self.privateGetAccountCryptoAddressCurrency(self.extend(request, params)) address = self.safe_string(response, 'address') self.check_address(address) tag = self.safe_string(response, 'paymentId') return { 'currency': currency['code'], 'address': address, 'tag': tag, 'info': response, } async def withdraw(self, code, amount, address, tag=None, params={}): await self.load_markets() self.check_address(address) currency = self.currency(code) request = { 'currency': currency['id'], 'amount': float(amount), 'address': address, } if tag: request['paymentId'] = tag response = await self.privatePostAccountCryptoWithdraw(self.extend(request, params)) return { 'info': response, 'id': response['id'], } def sign(self, path, api='public', method='GET', params={}, headers=None, body=None): url = '/api/' + self.version + '/' query = self.omit(params, self.extract_params(path)) if api == 'public': url += api + '/' + self.implode_params(path, params) if query: url += '?' + self.urlencode(query) else: self.check_required_credentials() url += self.implode_params(path, params) if method == 'GET': if query: url += '?' + self.urlencode(query) elif query: body = self.json(query) payload = self.encode(self.apiKey + ':' + self.secret) auth = base64.b64encode(payload) headers = { 'Authorization': 'Basic ' + self.decode(auth), 'Content-Type': 'application/json', } url = self.urls['api'] + url return {'url': url, 'method': method, 'body': body, 'headers': headers} def handle_errors(self, code, reason, url, method, headers, body, response, requestHeaders, requestBody): if response is None: return if code >= 400: feedback = self.id + ' ' + body if (code == 503) or (code == 504): raise ExchangeNotAvailable(feedback) if body[0] == '{': if 'error' in response: code = self.safe_string(response['error'], 'code') exceptions = self.exceptions if code in exceptions: raise exceptions[code](feedback) message = self.safe_string(response['error'], 'message') if message == 'Duplicate clientOrderId': raise InvalidOrder(feedback) raise ExchangeError(feedback)

true

f718a55c5117ea9a28e1c1de9ac32377c6e29ca9

20,501

py

Python

skfda/_utils/_utils.py

GAA-UAM/scikit-fda

a9953a3104195ce9796397d094b17b1b90fd090f

[ "BSD-3-Clause" ]

147

2019-05-10T20:46:42.000Z

2022-03-25T17:23:19.000Z

skfda/_utils/_utils.py

GAA-UAM/scikit-fda

a9953a3104195ce9796397d094b17b1b90fd090f

[ "BSD-3-Clause" ]

306

2019-04-26T08:56:05.000Z

2022-03-30T11:12:48.000Z

skfda/_utils/_utils.py

GAA-UAM/scikit-fda

a9953a3104195ce9796397d094b17b1b90fd090f

[ "BSD-3-Clause" ]

38

2019-09-03T17:24:04.000Z

2022-01-06T05:09:18.000Z

"""Module with generic methods.""" from __future__ import annotations import functools import numbers from typing import ( TYPE_CHECKING, Any, Callable, Iterable, List, Optional, Sequence, Tuple, TypeVar, Union, cast, overload, ) import numpy as np import scipy.integrate from numpy import ndarray from pandas.api.indexers import check_array_indexer from sklearn.base import clone from sklearn.preprocessing import LabelEncoder from sklearn.utils.multiclass import check_classification_targets from typing_extensions import Literal, Protocol from ..representation._typing import ( ArrayLike, DomainRange, DomainRangeLike, GridPoints, GridPointsLike, ) from ..representation.extrapolation import ExtrapolationLike RandomStateLike = Optional[Union[int, np.random.RandomState]] if TYPE_CHECKING: from ..exploratory.depth import Depth from ..representation import FData, FDataGrid from ..representation.basis import Basis T = TypeVar("T", bound=FData) def check_is_univariate(fd: FData) -> None: """Check if an FData is univariate and raises an error. Args: fd: Functional object to check if is univariate. Raises: ValueError: If it is not univariate, i.e., `fd.dim_domain != 1` or `fd.dim_codomain != 1`. """ if fd.dim_domain != 1 or fd.dim_codomain != 1: domain_str = ( "" if fd.dim_domain == 1 else f"(currently is {fd.dim_domain}) " ) codomain_str = ( "" if fd.dim_codomain == 1 else f"(currently is {fd.dim_codomain})" ) raise ValueError( f"The functional data must be univariate, i.e., " f"with dim_domain=1 {domain_str}" f"and dim_codomain=1 {codomain_str}", ) def _check_compatible_fdata(fdata1: FData, fdata2: FData) -> None: """Check that fdata is compatible.""" if (fdata1.dim_domain != fdata2.dim_domain): raise ValueError( f"Functional data has incompatible domain dimensions: " f"{fdata1.dim_domain} != {fdata2.dim_domain}", ) if (fdata1.dim_codomain != fdata2.dim_codomain): raise ValueError( f"Functional data has incompatible codomain dimensions: " f"{fdata1.dim_codomain} != {fdata2.dim_codomain}", ) def _to_grid( X: FData, y: FData, eval_points: Optional[np.ndarray] = None, ) -> Tuple[FDataGrid, FDataGrid]: """Transform a pair of FDatas in grids to perform calculations.""" from .. import FDataGrid x_is_grid = isinstance(X, FDataGrid) y_is_grid = isinstance(y, FDataGrid) if eval_points is not None: X = X.to_grid(eval_points) y = y.to_grid(eval_points) elif x_is_grid and not y_is_grid: y = y.to_grid(X.grid_points[0]) elif not x_is_grid and y_is_grid: X = X.to_grid(y.grid_points[0]) elif not x_is_grid and not y_is_grid: X = X.to_grid() y = y.to_grid() return X, y def _to_grid_points(grid_points_like: GridPointsLike) -> GridPoints: """Convert to grid points. If the original list is one-dimensional (e.g. [1, 2, 3]), return list to array (in this case [array([1, 2, 3])]). If the original list is two-dimensional (e.g. [[1, 2, 3], [4, 5]]), return a list containing other one-dimensional arrays (in this case [array([1, 2, 3]), array([4, 5])]). In any other case the behaviour is unespecified. """ unidimensional = False if not isinstance(grid_points_like, Iterable): grid_points_like = [grid_points_like] if not isinstance(grid_points_like[0], Iterable): unidimensional = True if unidimensional: return (_int_to_real(np.asarray(grid_points_like)),) return tuple(_int_to_real(np.asarray(i)) for i in grid_points_like) def _to_domain_range(sequence: DomainRangeLike) -> DomainRange: """Convert sequence to a proper domain range.""" seq_aux = cast( Sequence[Sequence[float]], (sequence,) if isinstance(sequence[0], numbers.Real) else sequence, ) tuple_aux = tuple(tuple(s) for s in seq_aux) if not all(len(s) == 2 and s[0] <= s[1] for s in tuple_aux): raise ValueError( "Domain intervals should have 2 bounds for " "dimension: (lower, upper).", ) return cast(DomainRange, tuple_aux) def _to_array_maybe_ragged( array: Iterable[ArrayLike], *, row_shape: Optional[Sequence[int]] = None, ) -> np.ndarray: """ Convert to an array where each element may or may not be of equal length. If each element is of equal length the array is multidimensional. Otherwise it is a ragged array. """ def convert_row(row: ArrayLike) -> np.ndarray: r = np.array(row) if row_shape is not None: r = r.reshape(row_shape) return r array_list = [convert_row(a) for a in array] shapes = [a.shape for a in array_list] if all(s == shapes[0] for s in shapes): return np.array(array_list) res = np.empty(len(array_list), dtype=np.object_) for i, a in enumerate(array_list): res[i] = a return res @overload def _cartesian_product( axes: Sequence[np.ndarray], *, flatten: bool = True, return_shape: Literal[False] = False, ) -> np.ndarray: pass @overload def _cartesian_product( axes: Sequence[np.ndarray], *, flatten: bool = True, return_shape: Literal[True], ) -> Tuple[np.ndarray, Tuple[int, ...]]: pass def _cartesian_product( # noqa: WPS234 axes: Sequence[np.ndarray], *, flatten: bool = True, return_shape: bool = False, ) -> Union[np.ndarray, Tuple[np.ndarray, Tuple[int, ...]]]: """ Compute the cartesian product of the axes. Computes the cartesian product of the axes and returns a numpy array of 1 dimension with all the possible combinations, for an arbitrary number of dimensions. Args: axes: List with axes. flatten: Whether to return the flatten array or keep one dimension per axis. return_shape: If ``True`` return the shape of the array before flattening. Returns: Numpy 2-D array with all the possible combinations. The entry (i,j) represent the j-th coordinate of the i-th point. If ``return_shape`` is ``True`` returns also the shape of the array before flattening. Examples: >>> from skfda._utils import _cartesian_product >>> axes = [[0,1],[2,3]] >>> _cartesian_product(axes) array([[0, 2], [0, 3], [1, 2], [1, 3]]) >>> axes = [[0,1],[2,3],[4]] >>> _cartesian_product(axes) array([[0, 2, 4], [0, 3, 4], [1, 2, 4], [1, 3, 4]]) >>> axes = [[0,1]] >>> _cartesian_product(axes) array([[0], [1]]) """ cartesian = np.stack(np.meshgrid(*axes, indexing='ij'), -1) shape = cartesian.shape if flatten: cartesian = cartesian.reshape(-1, len(axes)) if return_shape: return cartesian, shape return cartesian def _same_domain(fd: Union[Basis, FData], fd2: Union[Basis, FData]) -> bool: """Check if the domain range of two objects is the same.""" return np.array_equal(fd.domain_range, fd2.domain_range) @overload def _reshape_eval_points( eval_points: ArrayLike, *, aligned: Literal[True], n_samples: int, dim_domain: int, ) -> np.ndarray: pass @overload def _reshape_eval_points( eval_points: Sequence[ArrayLike], *, aligned: Literal[True], n_samples: int, dim_domain: int, ) -> np.ndarray: pass @overload def _reshape_eval_points( eval_points: Union[ArrayLike, Sequence[ArrayLike]], *, aligned: bool, n_samples: int, dim_domain: int, ) -> np.ndarray: pass def _reshape_eval_points( eval_points: Union[ArrayLike, Iterable[ArrayLike]], *, aligned: bool, n_samples: int, dim_domain: int, ) -> np.ndarray: """Convert and reshape the eval_points to ndarray. Args: eval_points: Evaluation points to be reshaped. aligned: Boolean flag. True if all the samples will be evaluated at the same evaluation_points. n_samples: Number of observations. dim_domain: Dimension of the domain. Returns: Numpy array with the eval_points, if evaluation_aligned is True with shape `number of evaluation points` x `dim_domain`. If the points are not aligned the shape of the points will be `n_samples` x `number of evaluation points` x `dim_domain`. """ if aligned: eval_points = np.asarray(eval_points) else: eval_points = cast(Iterable[ArrayLike], eval_points) eval_points = _to_array_maybe_ragged( eval_points, row_shape=(-1, dim_domain), ) # Case evaluation of a single value, i.e., f(0) # Only allowed for aligned evaluation if aligned and ( eval_points.shape == (dim_domain,) or (eval_points.ndim == 0 and dim_domain == 1) ): eval_points = np.array([eval_points]) if aligned: # Samples evaluated at same eval points eval_points = eval_points.reshape( (eval_points.shape[0], dim_domain), ) else: # Different eval_points for each sample if eval_points.shape[0] != n_samples: raise ValueError( f"eval_points should be a list " f"of length {n_samples} with the " f"evaluation points for each sample.", ) return eval_points def _one_grid_to_points( axes: GridPointsLike, *, dim_domain: int, ) -> Tuple[np.ndarray, Tuple[int, ...]]: """ Convert a list of ndarrays, one per domain dimension, in the points. Returns also the shape containing the information of how each point is formed. """ axes = _to_grid_points(axes) if len(axes) != dim_domain: raise ValueError( f"Length of axes should be {dim_domain}", ) cartesian, shape = _cartesian_product(axes, return_shape=True) # Drop domain size dimension, as it is not needed to reshape the output shape = shape[:-1] return cartesian, shape class EvaluateMethod(Protocol): """Evaluation method.""" def __call__( self, __eval_points: np.ndarray, # noqa: WPS112 extrapolation: Optional[ExtrapolationLike], aligned: bool, ) -> np.ndarray: """Evaluate a function.""" pass @overload def _evaluate_grid( axes: GridPointsLike, *, evaluate_method: EvaluateMethod, n_samples: int, dim_domain: int, dim_codomain: int, extrapolation: Optional[ExtrapolationLike] = None, aligned: Literal[True] = True, ) -> np.ndarray: pass @overload def _evaluate_grid( axes: Iterable[GridPointsLike], *, evaluate_method: EvaluateMethod, n_samples: int, dim_domain: int, dim_codomain: int, extrapolation: Optional[ExtrapolationLike] = None, aligned: Literal[False], ) -> np.ndarray: pass def _evaluate_grid( # noqa: WPS234 axes: Union[GridPointsLike, Iterable[GridPointsLike]], *, evaluate_method: EvaluateMethod, n_samples: int, dim_domain: int, dim_codomain: int, extrapolation: Optional[ExtrapolationLike] = None, aligned: bool = True, ) -> np.ndarray: """ Evaluate the functional object in the cartesian grid. This method is called internally by :meth:`evaluate` when the argument `grid` is True. Evaluates the functional object in the grid generated by the cartesian product of the axes. The length of the list of axes should be equal than the domain dimension of the object. If the list of axes has lengths :math:`n_1, n_2, ..., n_m`, where :math:`m` is equal than the dimension of the domain, the result of the evaluation in the grid will be a matrix with :math:`m+1` dimensions and shape :math:`n_{samples} x n_1 x n_2 x ... x n_m`. If `aligned` is false each sample is evaluated in a different grid, and the list of axes should contain a list of axes for each sample. If the domain dimension is 1, the result of the behaviour of the evaluation will be the same than :meth:`evaluate` without the grid option, but with worst performance. Args: axes: List of axes to generated the grid where the object will be evaluated. evaluate_method: Function used to evaluate the functional object. n_samples: Number of samples. dim_domain: Domain dimension. dim_codomain: Codomain dimension. extrapolation: Controls the extrapolation mode for elements outside the domain range. By default it is used the mode defined during the instance of the object. aligned: If False evaluates each sample in a different grid. evaluate_method: method to use to evaluate the points n_samples: number of samples dim_domain: dimension of the domain dim_codomain: dimensions of the codomain Returns: Numpy array with dim_domain + 1 dimensions with the result of the evaluation. Raises: ValueError: If there are a different number of axes than the domain dimension. """ # Compute intersection points and resulting shapes if aligned: axes = cast(GridPointsLike, axes) eval_points, shape = _one_grid_to_points(axes, dim_domain=dim_domain) else: axes_per_sample = cast(Iterable[GridPointsLike], axes) axes_per_sample = list(axes_per_sample) eval_points_tuple, shape_tuple = zip( *[ _one_grid_to_points(a, dim_domain=dim_domain) for a in axes_per_sample ], ) if len(eval_points_tuple) != n_samples: raise ValueError( "Should be provided a list of axis per sample", ) eval_points = _to_array_maybe_ragged(eval_points_tuple) # Evaluate the points evaluated = evaluate_method( eval_points, extrapolation=extrapolation, aligned=aligned, ) # Reshape the result if aligned: res = evaluated.reshape( [n_samples] + list(shape) + [dim_codomain], ) else: res = _to_array_maybe_ragged([ r.reshape(list(s) + [dim_codomain]) for r, s in zip(evaluated, shape_tuple) ]) return res def nquad_vec( func: Callable[[np.ndarray], np.ndarray], ranges: Sequence[Tuple[float, float]], ) -> np.ndarray: """Perform multiple integration of vector valued functions.""" initial_depth = len(ranges) - 1 def integrate(*args: Any, depth: int) -> np.ndarray: # noqa: WPS430 if depth == 0: f = functools.partial(func, *args) else: f = functools.partial(integrate, *args, depth=depth - 1) return scipy.integrate.quad_vec(f, *ranges[initial_depth - depth])[0] return integrate(depth=initial_depth) def _map_in_batches( function: Callable[..., np.ndarray], arguments: Tuple[Union[FData, np.ndarray], ...], indexes: Tuple[np.ndarray, ...], memory_per_batch: Optional[int] = None, **kwargs: Any, ) -> np.ndarray: """ Map a function over samples of FData or ndarray tuples efficiently. This function prevents a large set of indexes to use all available memory and hang the PC. """ if memory_per_batch is None: # 256MB is not too big memory_per_batch = 256 * 1024 * 1024 # noqa: WPS432 memory_per_element = sum(a.nbytes // len(a) for a in arguments) n_elements_per_batch_allowed = memory_per_batch // memory_per_element if n_elements_per_batch_allowed < 1: raise ValueError("Too few memory allowed for the operation") n_indexes = len(indexes[0]) assert all(n_indexes == len(i) for i in indexes) batches: List[np.ndarray] = [] for pos in range(0, n_indexes, n_elements_per_batch_allowed): batch_args = tuple( a[i[pos:pos + n_elements_per_batch_allowed]] for a, i in zip(arguments, indexes) ) batches.append(function(*batch_args, **kwargs)) return np.concatenate(batches, axis=0) def _pairwise_symmetric( function: Callable[..., np.ndarray], arg1: Union[FData, np.ndarray], arg2: Optional[Union[FData, np.ndarray]] = None, memory_per_batch: Optional[int] = None, **kwargs: Any, ) -> np.ndarray: """Compute pairwise a commutative function.""" dim1 = len(arg1) if arg2 is None or arg2 is arg1: indices = np.triu_indices(dim1) matrix = np.empty((dim1, dim1)) triang_vec = _map_in_batches( function, (arg1, arg1), indices, memory_per_batch=memory_per_batch, **kwargs, ) # Set upper matrix matrix[indices] = triang_vec # Set lower matrix matrix[(indices[1], indices[0])] = triang_vec return matrix dim2 = len(arg2) indices = np.indices((dim1, dim2)) vec = _map_in_batches( function, (arg1, arg2), (indices[0].ravel(), indices[1].ravel()), memory_per_batch=memory_per_batch, **kwargs, ) return vec.reshape((dim1, dim2)) def _int_to_real(array: np.ndarray) -> np.ndarray: """Convert integer arrays to floating point.""" return array + 0.0 def _check_array_key(array: np.ndarray, key: Any) -> Any: """Check a getitem key.""" key = check_array_indexer(array, key) if isinstance(key, tuple): non_ellipsis = [i for i in key if i is not Ellipsis] if len(non_ellipsis) > 1: raise KeyError(key) key = non_ellipsis[0] if isinstance(key, numbers.Integral): # To accept also numpy ints key = int(key) key = range(len(array))[key] return slice(key, key + 1) return key def _check_estimator(estimator): from sklearn.utils.estimator_checks import ( check_get_params_invariance, check_set_params, ) name = estimator.__name__ instance = estimator() check_get_params_invariance(name, instance) check_set_params(name, instance) def _classifier_get_classes(y: ndarray) -> Tuple[ndarray, ndarray]: check_classification_targets(y) le = LabelEncoder() y_ind = le.fit_transform(y) classes = le.classes_ if classes.size < 2: raise ValueError( f'The number of classes has to be greater than' f'one; got {classes.size} class', ) return classes, y_ind def _classifier_get_depth_methods( classes: ndarray, X: T, y_ind: ndarray, depth_methods: Sequence[Depth[T]], ) -> Sequence[Depth[T]]: return [ clone(depth_method).fit(X[y_ind == cur_class]) for cur_class in range(classes.size) for depth_method in depth_methods ] def _classifier_fit_depth_methods( X: T, y: ndarray, depth_methods: Sequence[Depth[T]], ) -> Tuple[ndarray, Sequence[Depth[T]]]: classes, y_ind = _classifier_get_classes(y) class_depth_methods_ = _classifier_get_depth_methods( classes, X, y_ind, depth_methods, ) return classes, class_depth_methods_ _DependenceMeasure = Callable[[np.ndarray, np.ndarray], np.ndarray] def _compute_dependence( X: np.ndarray, y: np.ndarray, *, dependence_measure: _DependenceMeasure, ) -> np.ndarray: """ Compute dependence between points and target. Computes the dependence of each point in each trajectory in X with the corresponding class label in Y. """ from dcor import rowwise # Move n_samples to the end # The shape is now input_shape + n_samples + n_output X = np.moveaxis(X, 0, -2) input_shape = X.shape[:-2] # Join input in a list for rowwise X = X.reshape(-1, X.shape[-2], X.shape[-1]) if y.ndim == 1: y = np.atleast_2d(y).T Y = np.array([y] * len(X)) dependence_results = rowwise(dependence_measure, X, Y) return dependence_results.reshape(input_shape)

26.728814

78

0.632457

from __future__ import annotations import functools import numbers from typing import ( TYPE_CHECKING, Any, Callable, Iterable, List, Optional, Sequence, Tuple, TypeVar, Union, cast, overload, ) import numpy as np import scipy.integrate from numpy import ndarray from pandas.api.indexers import check_array_indexer from sklearn.base import clone from sklearn.preprocessing import LabelEncoder from sklearn.utils.multiclass import check_classification_targets from typing_extensions import Literal, Protocol from ..representation._typing import ( ArrayLike, DomainRange, DomainRangeLike, GridPoints, GridPointsLike, ) from ..representation.extrapolation import ExtrapolationLike RandomStateLike = Optional[Union[int, np.random.RandomState]] if TYPE_CHECKING: from ..exploratory.depth import Depth from ..representation import FData, FDataGrid from ..representation.basis import Basis T = TypeVar("T", bound=FData) def check_is_univariate(fd: FData) -> None: if fd.dim_domain != 1 or fd.dim_codomain != 1: domain_str = ( "" if fd.dim_domain == 1 else f"(currently is {fd.dim_domain}) " ) codomain_str = ( "" if fd.dim_codomain == 1 else f"(currently is {fd.dim_codomain})" ) raise ValueError( f"The functional data must be univariate, i.e., " f"with dim_domain=1 {domain_str}" f"and dim_codomain=1 {codomain_str}", ) def _check_compatible_fdata(fdata1: FData, fdata2: FData) -> None: if (fdata1.dim_domain != fdata2.dim_domain): raise ValueError( f"Functional data has incompatible domain dimensions: " f"{fdata1.dim_domain} != {fdata2.dim_domain}", ) if (fdata1.dim_codomain != fdata2.dim_codomain): raise ValueError( f"Functional data has incompatible codomain dimensions: " f"{fdata1.dim_codomain} != {fdata2.dim_codomain}", ) def _to_grid( X: FData, y: FData, eval_points: Optional[np.ndarray] = None, ) -> Tuple[FDataGrid, FDataGrid]: from .. import FDataGrid x_is_grid = isinstance(X, FDataGrid) y_is_grid = isinstance(y, FDataGrid) if eval_points is not None: X = X.to_grid(eval_points) y = y.to_grid(eval_points) elif x_is_grid and not y_is_grid: y = y.to_grid(X.grid_points[0]) elif not x_is_grid and y_is_grid: X = X.to_grid(y.grid_points[0]) elif not x_is_grid and not y_is_grid: X = X.to_grid() y = y.to_grid() return X, y def _to_grid_points(grid_points_like: GridPointsLike) -> GridPoints: unidimensional = False if not isinstance(grid_points_like, Iterable): grid_points_like = [grid_points_like] if not isinstance(grid_points_like[0], Iterable): unidimensional = True if unidimensional: return (_int_to_real(np.asarray(grid_points_like)),) return tuple(_int_to_real(np.asarray(i)) for i in grid_points_like) def _to_domain_range(sequence: DomainRangeLike) -> DomainRange: seq_aux = cast( Sequence[Sequence[float]], (sequence,) if isinstance(sequence[0], numbers.Real) else sequence, ) tuple_aux = tuple(tuple(s) for s in seq_aux) if not all(len(s) == 2 and s[0] <= s[1] for s in tuple_aux): raise ValueError( "Domain intervals should have 2 bounds for " "dimension: (lower, upper).", ) return cast(DomainRange, tuple_aux) def _to_array_maybe_ragged( array: Iterable[ArrayLike], *, row_shape: Optional[Sequence[int]] = None, ) -> np.ndarray: def convert_row(row: ArrayLike) -> np.ndarray: r = np.array(row) if row_shape is not None: r = r.reshape(row_shape) return r array_list = [convert_row(a) for a in array] shapes = [a.shape for a in array_list] if all(s == shapes[0] for s in shapes): return np.array(array_list) res = np.empty(len(array_list), dtype=np.object_) for i, a in enumerate(array_list): res[i] = a return res @overload def _cartesian_product( axes: Sequence[np.ndarray], *, flatten: bool = True, return_shape: Literal[False] = False, ) -> np.ndarray: pass @overload def _cartesian_product( axes: Sequence[np.ndarray], *, flatten: bool = True, return_shape: Literal[True], ) -> Tuple[np.ndarray, Tuple[int, ...]]: pass def _cartesian_product( axes: Sequence[np.ndarray], *, flatten: bool = True, return_shape: bool = False, ) -> Union[np.ndarray, Tuple[np.ndarray, Tuple[int, ...]]]: cartesian = np.stack(np.meshgrid(*axes, indexing='ij'), -1) shape = cartesian.shape if flatten: cartesian = cartesian.reshape(-1, len(axes)) if return_shape: return cartesian, shape return cartesian def _same_domain(fd: Union[Basis, FData], fd2: Union[Basis, FData]) -> bool: return np.array_equal(fd.domain_range, fd2.domain_range) @overload def _reshape_eval_points( eval_points: ArrayLike, *, aligned: Literal[True], n_samples: int, dim_domain: int, ) -> np.ndarray: pass @overload def _reshape_eval_points( eval_points: Sequence[ArrayLike], *, aligned: Literal[True], n_samples: int, dim_domain: int, ) -> np.ndarray: pass @overload def _reshape_eval_points( eval_points: Union[ArrayLike, Sequence[ArrayLike]], *, aligned: bool, n_samples: int, dim_domain: int, ) -> np.ndarray: pass def _reshape_eval_points( eval_points: Union[ArrayLike, Iterable[ArrayLike]], *, aligned: bool, n_samples: int, dim_domain: int, ) -> np.ndarray: if aligned: eval_points = np.asarray(eval_points) else: eval_points = cast(Iterable[ArrayLike], eval_points) eval_points = _to_array_maybe_ragged( eval_points, row_shape=(-1, dim_domain), ) if aligned and ( eval_points.shape == (dim_domain,) or (eval_points.ndim == 0 and dim_domain == 1) ): eval_points = np.array([eval_points]) if aligned: eval_points = eval_points.reshape( (eval_points.shape[0], dim_domain), ) else: if eval_points.shape[0] != n_samples: raise ValueError( f"eval_points should be a list " f"of length {n_samples} with the " f"evaluation points for each sample.", ) return eval_points def _one_grid_to_points( axes: GridPointsLike, *, dim_domain: int, ) -> Tuple[np.ndarray, Tuple[int, ...]]: axes = _to_grid_points(axes) if len(axes) != dim_domain: raise ValueError( f"Length of axes should be {dim_domain}", ) cartesian, shape = _cartesian_product(axes, return_shape=True) shape = shape[:-1] return cartesian, shape class EvaluateMethod(Protocol): def __call__( self, __eval_points: np.ndarray, extrapolation: Optional[ExtrapolationLike], aligned: bool, ) -> np.ndarray: pass @overload def _evaluate_grid( axes: GridPointsLike, *, evaluate_method: EvaluateMethod, n_samples: int, dim_domain: int, dim_codomain: int, extrapolation: Optional[ExtrapolationLike] = None, aligned: Literal[True] = True, ) -> np.ndarray: pass @overload def _evaluate_grid( axes: Iterable[GridPointsLike], *, evaluate_method: EvaluateMethod, n_samples: int, dim_domain: int, dim_codomain: int, extrapolation: Optional[ExtrapolationLike] = None, aligned: Literal[False], ) -> np.ndarray: pass def _evaluate_grid( axes: Union[GridPointsLike, Iterable[GridPointsLike]], *, evaluate_method: EvaluateMethod, n_samples: int, dim_domain: int, dim_codomain: int, extrapolation: Optional[ExtrapolationLike] = None, aligned: bool = True, ) -> np.ndarray: if aligned: axes = cast(GridPointsLike, axes) eval_points, shape = _one_grid_to_points(axes, dim_domain=dim_domain) else: axes_per_sample = cast(Iterable[GridPointsLike], axes) axes_per_sample = list(axes_per_sample) eval_points_tuple, shape_tuple = zip( *[ _one_grid_to_points(a, dim_domain=dim_domain) for a in axes_per_sample ], ) if len(eval_points_tuple) != n_samples: raise ValueError( "Should be provided a list of axis per sample", ) eval_points = _to_array_maybe_ragged(eval_points_tuple) evaluated = evaluate_method( eval_points, extrapolation=extrapolation, aligned=aligned, ) if aligned: res = evaluated.reshape( [n_samples] + list(shape) + [dim_codomain], ) else: res = _to_array_maybe_ragged([ r.reshape(list(s) + [dim_codomain]) for r, s in zip(evaluated, shape_tuple) ]) return res def nquad_vec( func: Callable[[np.ndarray], np.ndarray], ranges: Sequence[Tuple[float, float]], ) -> np.ndarray: initial_depth = len(ranges) - 1 def integrate(*args: Any, depth: int) -> np.ndarray: if depth == 0: f = functools.partial(func, *args) else: f = functools.partial(integrate, *args, depth=depth - 1) return scipy.integrate.quad_vec(f, *ranges[initial_depth - depth])[0] return integrate(depth=initial_depth) def _map_in_batches( function: Callable[..., np.ndarray], arguments: Tuple[Union[FData, np.ndarray], ...], indexes: Tuple[np.ndarray, ...], memory_per_batch: Optional[int] = None, **kwargs: Any, ) -> np.ndarray: if memory_per_batch is None: memory_per_batch = 256 * 1024 * 1024 memory_per_element = sum(a.nbytes // len(a) for a in arguments) n_elements_per_batch_allowed = memory_per_batch // memory_per_element if n_elements_per_batch_allowed < 1: raise ValueError("Too few memory allowed for the operation") n_indexes = len(indexes[0]) assert all(n_indexes == len(i) for i in indexes) batches: List[np.ndarray] = [] for pos in range(0, n_indexes, n_elements_per_batch_allowed): batch_args = tuple( a[i[pos:pos + n_elements_per_batch_allowed]] for a, i in zip(arguments, indexes) ) batches.append(function(*batch_args, **kwargs)) return np.concatenate(batches, axis=0) def _pairwise_symmetric( function: Callable[..., np.ndarray], arg1: Union[FData, np.ndarray], arg2: Optional[Union[FData, np.ndarray]] = None, memory_per_batch: Optional[int] = None, **kwargs: Any, ) -> np.ndarray: dim1 = len(arg1) if arg2 is None or arg2 is arg1: indices = np.triu_indices(dim1) matrix = np.empty((dim1, dim1)) triang_vec = _map_in_batches( function, (arg1, arg1), indices, memory_per_batch=memory_per_batch, **kwargs, ) matrix[indices] = triang_vec matrix[(indices[1], indices[0])] = triang_vec return matrix dim2 = len(arg2) indices = np.indices((dim1, dim2)) vec = _map_in_batches( function, (arg1, arg2), (indices[0].ravel(), indices[1].ravel()), memory_per_batch=memory_per_batch, **kwargs, ) return vec.reshape((dim1, dim2)) def _int_to_real(array: np.ndarray) -> np.ndarray: return array + 0.0 def _check_array_key(array: np.ndarray, key: Any) -> Any: key = check_array_indexer(array, key) if isinstance(key, tuple): non_ellipsis = [i for i in key if i is not Ellipsis] if len(non_ellipsis) > 1: raise KeyError(key) key = non_ellipsis[0] if isinstance(key, numbers.Integral): key = int(key) key = range(len(array))[key] return slice(key, key + 1) return key def _check_estimator(estimator): from sklearn.utils.estimator_checks import ( check_get_params_invariance, check_set_params, ) name = estimator.__name__ instance = estimator() check_get_params_invariance(name, instance) check_set_params(name, instance) def _classifier_get_classes(y: ndarray) -> Tuple[ndarray, ndarray]: check_classification_targets(y) le = LabelEncoder() y_ind = le.fit_transform(y) classes = le.classes_ if classes.size < 2: raise ValueError( f'The number of classes has to be greater than' f'one; got {classes.size} class', ) return classes, y_ind def _classifier_get_depth_methods( classes: ndarray, X: T, y_ind: ndarray, depth_methods: Sequence[Depth[T]], ) -> Sequence[Depth[T]]: return [ clone(depth_method).fit(X[y_ind == cur_class]) for cur_class in range(classes.size) for depth_method in depth_methods ] def _classifier_fit_depth_methods( X: T, y: ndarray, depth_methods: Sequence[Depth[T]], ) -> Tuple[ndarray, Sequence[Depth[T]]]: classes, y_ind = _classifier_get_classes(y) class_depth_methods_ = _classifier_get_depth_methods( classes, X, y_ind, depth_methods, ) return classes, class_depth_methods_ _DependenceMeasure = Callable[[np.ndarray, np.ndarray], np.ndarray] def _compute_dependence( X: np.ndarray, y: np.ndarray, *, dependence_measure: _DependenceMeasure, ) -> np.ndarray: from dcor import rowwise X = np.moveaxis(X, 0, -2) input_shape = X.shape[:-2] X = X.reshape(-1, X.shape[-2], X.shape[-1]) if y.ndim == 1: y = np.atleast_2d(y).T Y = np.array([y] * len(X)) dependence_results = rowwise(dependence_measure, X, Y) return dependence_results.reshape(input_shape)

true

f718a596d8438f0be366ac1bbc612312c7461493

671

py

Python

tests/test_windows.py

tombackstrom/mdct

f59e708f9a7f65ee672dbf44e6f164e79c82d83a

[ "MIT" ]

40

2016-11-16T14:45:36.000Z

2021-12-02T20:56:07.000Z

tests/test_windows.py

tombackstrom/mdct

f59e708f9a7f65ee672dbf44e6f164e79c82d83a

[ "MIT" ]

3

2017-06-17T11:48:30.000Z

2021-06-28T04:47:00.000Z

tests/test_windows.py

tombackstrom/mdct

f59e708f9a7f65ee672dbf44e6f164e79c82d83a

[ "MIT" ]

9

2016-10-01T20:20:40.000Z

2021-12-09T08:56:31.000Z

import pytest import numpy import mdct.windows def test_kbd(): M = 100 w = mdct.windows.kaiser_derived(M, beta=4.) assert numpy.allclose(w[:M//2] ** 2 + w[-M//2:] ** 2, 1.) with pytest.raises(ValueError): mdct.windows.kaiser_derived(M + 1, beta=4.) assert numpy.allclose( mdct.windows.kaiser_derived(2, beta=numpy.pi/2)[:1], [numpy.sqrt(2)/2]) assert numpy.allclose( mdct.windows.kaiser_derived(4, beta=numpy.pi/2)[:2], [0.518562710536, 0.855039598640]) assert numpy.allclose( mdct.windows.kaiser_derived(6, beta=numpy.pi/2)[:3], [0.436168993154, 0.707106781187, 0.899864772847])

25.807692

61

0.630402

import pytest import numpy import mdct.windows def test_kbd(): M = 100 w = mdct.windows.kaiser_derived(M, beta=4.) assert numpy.allclose(w[:M//2] ** 2 + w[-M//2:] ** 2, 1.) with pytest.raises(ValueError): mdct.windows.kaiser_derived(M + 1, beta=4.) assert numpy.allclose( mdct.windows.kaiser_derived(2, beta=numpy.pi/2)[:1], [numpy.sqrt(2)/2]) assert numpy.allclose( mdct.windows.kaiser_derived(4, beta=numpy.pi/2)[:2], [0.518562710536, 0.855039598640]) assert numpy.allclose( mdct.windows.kaiser_derived(6, beta=numpy.pi/2)[:3], [0.436168993154, 0.707106781187, 0.899864772847])

true

f718a61c448b93dcd1b999fa459d8e7cef048f93

22,011

py

Python

trainer.py

dpetrini/nova

00b7637901420f68c7d805c13ccd4c39d514efb1

[ "MIT" ]

1

2020-10-19T23:49:00.000Z

trainer.py

dpetrini/nova

00b7637901420f68c7d805c13ccd4c39d514efb1

[ "MIT" ]

null

trainer.py

dpetrini/nova

00b7637901420f68c7d805c13ccd4c39d514efb1

[ "MIT" ]

null

from matplotlib.pyplot import show import torch from torch.autograd import Variable from torch.cuda.amp import GradScaler, autocast import numpy as np from sklearn.metrics import roc_auc_score from callbacks.cb_handler import CallbackHandler from callbacks.cb_base import BaseCB from callbacks.cb_lr_patch_clf import LR_SchedCB_patch from callbacks.cb_lr_full_clf import LR_SchedCB_full from callbacks.cb_lr_2views_clf import LR_SchedCB_2views from callbacks.cb_lr_w_cyc_cos import LR_SchedCB_W_Cyc_Cos from callbacks.cb_lr_w_cos import LR_SchedCB_W_Cos from callbacks.cb_auc import AUC_CB # from parallel import DataParallelModel, DataParallelCriterion from util.util import show_auc, calc_auc_desv parallel = False #APAGAR import cv2 # Accuracy def acc(y_hat, labels): """ Default accuracy """ # para parallel if len(y_hat) > 1 and parallel: y_hat = torch.cat(y_hat) return (torch.argmax(y_hat, dim=1) == labels).float().sum() class Trainer(): """ Many possible configurations for Trainer config = { 'num_epochs': NUM_EPOCHS, 'batch_size': MINI_BATCH, 'name': 'example', 'title': 'Cats & Dogs Classifier', 'save_last': True, # optional: Save last model (default=False) 'save_best': True, # optional: Save best models (ACC, {AUC}) (default=True) 'stable_metric: N # optional: extend epochs number to wait N epochs with no metric change (ex.AUC) 'save_checkpoints': N, # Save checkpoint each N epochs 'features': ['auc'], # optional: features like auc stats or some scheduler (if none default:optim) 'save_path': folder, # if want to save artifacts in other place (eg.cloud) 'show_plots': False, # if want to show plots 'make_plots': False, # if want to disable plots 'cv_k': (number), # interactio number if using Cross Validation } """ def __init__(self, model, train_dataloader, val_dataloader, loss_criterion, optimizer, optimizer_args, device, config): self.model = model self.device = device self.loss_criterion = loss_criterion # parts of config are only retrieved in callbacks self.epochs = int(config['num_epochs']) if 'num_epochs' in config else 10 self.mini_batch = int(config['batch_size']) if 'batch_size' in config else 1 self.first_epoch = int(config['start_epoch']) if 'start_epoch' in config else 1 self.stable_metric = int(config['stable_metric']) if 'stable_metric' in config else False self.name = config['name'] if 'name' in config else 'default' self.title = config['title'] if 'title' in config else 'Classifier' self.features = config['features'] if 'features' in config else [] self.make_plots = config['make_plots'] if 'make_plots' in config else True if train_dataloader: self.train_dataloader = train_dataloader else: return self.train_dataloader = train_dataloader self.val_dataloader = val_dataloader self.optimizer = optimizer self.optimizer_args = optimizer_args print(self.title) # Load Callbacks for this session callbacks = [BaseCB(self.name, self.title, config)] for feat in self.features: if feat == 'auc': callbacks.append(AUC_CB(self.name, config)) if feat == 'lr_step_full': callbacks.append(LR_SchedCB_full()) if feat == 'lr_step_patch': callbacks.append(LR_SchedCB_patch()) if feat == 'lr_step_2views': callbacks.append(LR_SchedCB_2views()) if feat == 'lr_warmup_cos': callbacks.append(LR_SchedCB_W_Cos()) if feat == 'lr_warmup_cyc_cos': callbacks.append(LR_SchedCB_W_Cyc_Cos()) if feat == 'LR_SchedCB_W_Cos': callbacks.append(LR_SchedCB_W_Cos()) self.cb = CallbackHandler(callbacks) def train_and_validate(self, **kwargs): """ Main train and validate function that runs main loop (fit). Receives all parameters and feed callback system. Loop through epochs and executes pytorch forward, loss, backpropagation and optimization (grads calc). Returns the model trained. """ calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc input_dict = kwargs.get('input_dict') if kwargs.get('input_dict') else [] if not self.cb.begin_train_val(self.epochs, self.model, self.train_dataloader, self.val_dataloader, self.mini_batch, self.optimizer): return self.cb.update_loss(self.loss_criterion, calc_acc) device = self.device for epoch in range(self.first_epoch, self.epochs+1): self.model.train() train_loss, train_acc = 0.0, 0.0 val_loss, val_acc = 0.0, 0.0 if not self.cb.begin_epoch(epoch): return # noqa: E701 optim = self.cb.update_LR(epoch, self.model, self.optimizer, self.optimizer_args) if optim: self.optimizer = optim # Train loop for _, (inputs, labels) in enumerate(self.train_dataloader): if isinstance(inputs, dict): for key in input_dict: inputs[key] = inputs[key].to(device) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) # inserting MIXUP handling res = self.cb.begin_batch(inputs, labels) if res: inputs, labels, self.loss_criterion, calc_acc = res self.optimizer.zero_grad() # clean existing gradients outputs = self.model(inputs) # forward pass loss = self.loss_criterion(outputs, labels) # compute loss if parallel: loss = loss.mean() # list in this case loss.backward() # backprop the gradients self.optimizer.step() # update parameters train_loss += loss.item() * labels.size(0) # inputs.size(0) == mini_batch size train_acc += calc_acc(outputs, labels).item() self.cb.after_step(labels.size(0), labels, outputs) # validation - no gradient tracking needed with torch.no_grad(): self.model.eval() self.cb.begin_val() # validation loop for _, (inputs, labels) in enumerate(self.val_dataloader): if isinstance(inputs, dict): for key in input_dict: inputs[key] = inputs[key].to(device) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = self.model(inputs) # forward pass loss = self.loss_criterion(outputs, labels) # compute loss if parallel: loss = loss.mean() val_loss += loss.item() * labels.size(0) # inputs.size(0) == mini_batch size val_acc += calc_acc(outputs, labels).item() self.cb.after_step_val(labels.size(0), labels, outputs) self.cb.after_epoch(self.model, train_acc, train_loss, val_acc, val_loss) self.cb.after_train_val() return self.model def train_and_validate_amp(self, **kwargs): """ Mixed precision (automatic) version for train_and_validate. Uses FP16 and FP32 in main loop with pytorch Automatic Mixed Precision. In simple tests: use 75% of memory in 66% of time. Less memory and faster. Sometimes it just don't work and get worse, like for resnest... """ assert torch.__version__ >= '1.6.0', "[Mixed precision] Please use PyTorch 1.6.0+" print('Using AMP') calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc input_dict = kwargs.get('input_dict') if kwargs.get('input_dict') else [] if not self.cb.begin_train_val(self.epochs, self.model, self.train_dataloader, self.val_dataloader, self.mini_batch, self.optimizer): return # Creates a GradScaler once at the beginning of training. scaler = GradScaler() device = self.device # for epoch in range(self.first_epoch, self.epochs+1): epoch = self.first_epoch # suport for "wait N epochs after best metric" last_epoch = self.epochs while epoch <= last_epoch: self.model.train() train_loss, train_acc = 0.0, 0.0 val_loss, val_acc = 0.0, 0.0 if not self.cb.begin_epoch(epoch): return # noqa: E701 optim = self.cb.update_LR(epoch, self.model, self.optimizer, self.optimizer_args) if optim: self.optimizer = optim # Train loop for _, (inputs, labels) in enumerate(self.train_dataloader): if isinstance(inputs, dict): for key in input_dict: inputs[key] = inputs[key].to(device) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) self.optimizer.zero_grad() # clean existing gradients # Runs the forward pass with autocasting. with autocast(): outputs = self.model(inputs) # forward pass loss = self.loss_criterion(outputs, labels) # compute loss if parallel: loss = loss.mean() # list in this case scaler.scale(loss).backward() # backward() on scaled loss for scaled gradients. scaler.step(self.optimizer) # update parameters scaler.update() # Updates the scale for next iteration. train_loss += loss.item() * labels.size(0) # == mini_batch size train_acc += calc_acc(outputs, labels).item() self.cb.after_step(labels.size(0), labels, outputs) # validation - no gradient tracking needed with torch.no_grad(): self.model.eval() # validation loop for _, (inputs, labels) in enumerate(self.val_dataloader): if isinstance(inputs, dict): for key in input_dict: inputs[key] = inputs[key].to(device) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = self.model(inputs) # forward pass loss = self.loss_criterion(outputs, labels) # compute loss if parallel: loss = loss.mean() val_loss += loss.item() * labels.size(0) # == mini_batch size val_acc += calc_acc(outputs, labels).item() self.cb.after_step_val(labels.size(0), labels, outputs) self.cb.after_epoch(self.model, train_acc, train_loss, val_acc, val_loss) epoch += 1 # print('-', self.cb.best_metric_epoch[self.cb.metric_name[-1]], last_epoch) # Is use stable metric - will stop training earlier, after # stable_metric epochs without validation metric (to be selected) improve # last_epoch = self.epochs if not self.stable_metric else max(self.epochs, self.cb.best_metric_epoch[self.cb.metric_name[-1]] + self.stable_metric) # for metric in self.cb.metric_name: # print(metric) last_epoch = self.epochs if not self.stable_metric else min(self.epochs, self.cb.best_metric_epoch[self.cb.metric_name[-1]] + self.stable_metric) self.cb.after_train_val() values = [self.cb.best_metric, self.cb.best_metric_epoch, self.cb.elapsed_mins, self.cb.metric_name, self.cb.loss_plot, self.cb.metric_plot, self.cb.best_model_file] return values def run_test(self, test_dataloader, model_type, **kwargs): """ Run test from test_dataloader according to model_type. if model_type = 'normal' : use last saved model if model_type = 'best' : use best model Uses: loss function from Trainer Input: test_dataloader """ calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc quiet = kwargs.get('quiet') if kwargs.get('quiet') else False if model_type == 'normal': model = self.cb.last_model elif model_type == 'best': model = self.cb.best_model elif model_type == 'bootstrap': model = self.model test_acc, test_loss = 0., 0. batch_val_counter = 0 device = self.device with torch.no_grad(): model.eval() # validation loop for _, (inputs, labels) in enumerate(test_dataloader): if isinstance(inputs, dict): for key in ['CC', 'MLO']: inputs[key] = inputs[key].to(device) labels = Variable(labels.to(device)) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = model(inputs) # forward pass loss = self.loss_criterion(outputs, labels) # compute loss if parallel: loss = loss.mean() test_loss += loss.item() * labels.size(0) test_acc += calc_acc(outputs, labels).item() batch_val_counter += labels.size(0) # Find average test loss and test accuracy avg_test_loss = test_loss/batch_val_counter avg_test_acc = test_acc/batch_val_counter if not quiet: print(f'Model: {model_type} - Test accuracy : {avg_test_acc:.5f}' + f' Test loss : {avg_test_loss:.5f}') return avg_test_acc def run_test_auc(self, test_dataloader, model_type, **kwargs): """ Run test from test_dataloader, calculating AUC and ROC curve According to model_type: if model_type = 'normal' : use last saved model if model_type = 'best' : use best model If we are running test iunference only can pass model through kwargs. Uses: loss function from Trainer Input: test_dataloader """ calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc model = kwargs.get('model') if kwargs.get('model') else None show_results = kwargs.get('show_results') if kwargs.get('show_results') else False m_positive = kwargs.get('m') if kwargs.get('m') else False n_negative = kwargs.get('n') if kwargs.get('n') else False if model is None: if model_type == 'normal': model = self.cb.last_model elif model_type == 'best': model = self.cb.best_model elif model_type == 'test': model = self.model elif model_type == 'bootstrap': model = self.model test_acc, test_loss = 0., 0. batch_val_counter = 0 y_hat_auc, label_auc = [], [] device = self.device with torch.no_grad(): model.eval() # validation loop for _, (inputs, labels) in enumerate(test_dataloader): if isinstance(inputs, dict): for key in ['CC', 'MLO']: inputs[key] = inputs[key].to(device) labels = Variable(labels.to(device)) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = model(inputs) # forward pass loss = self.loss_criterion(outputs, labels) # compute loss test_loss += loss.item() * labels.size(0) # calculate acc test_acc += calc_acc(outputs, labels).item() batch_val_counter += labels.size(0) # Store auc for malignant label_auc = np.append(label_auc, labels.cpu().detach().numpy()) y_hat_auc = np.append(y_hat_auc, torch.softmax(outputs, dim=1)[:, 1].cpu().detach().numpy()) # enter show result mode if self.mini_batch == 1 and show_results: print(f'{labels.item()} {torch.softmax(outputs, dim=1)[:, 1].item():.3f}') # Find average test loss and test accuracy avg_test_loss = test_loss/batch_val_counter avg_test_acc = test_acc/batch_val_counter print(f"Model: {model_type} - Test accuracy : {avg_test_acc:.3f}" + f" Test loss : {avg_test_loss:.4f}", end='') # calculate AUC TEST auc_mal_val = roc_auc_score(label_auc.ravel(), y_hat_auc.ravel()) # print(f' AUC Malignant: {auc_mal_val:.4f}', end='') if m_positive and n_negative: auc_final = f'{auc_mal_val:.4f}±{calc_auc_desv(m_positive, n_negative, auc_mal_val):.4f}' # print(f'±{calc_auc_desv(m_positive, n_negative, auc_mal_val):.4f}') print(f' AUC Malignant: {auc_final}') else: auc_final = f'{auc_mal_val:.4f}' print(f' AUC Malignant: {auc_final}') # print() if self.make_plots: show_auc(label_auc, y_hat_auc, self.title, show_plt=False) # return auc_mal_val return auc_final # Not fully tested yet (2021-05) # it seems to be working - maybe integrate in single function as above # and use kwargs to indicate that it is test-data- aug? def run_test_data_aug_auc(self, test_dataloader, model_type, **kwargs): """ Run test from test_dataloader, calculating AUC and ROC curve --> Using test-data augmentation: rotation 0°, 90°, 180°, 270° --> All rotated sample will be infered and AUC will consider all. According to model_type: if model_type = 'normal' : use last saved model if model_type = 'best' : use best model If we are running test iunference only can pass model through kwargs. Uses: loss function from Trainer Input: test_dataloader """ calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc model = kwargs.get('model') if kwargs.get('model') else None if model is None: if model_type == 'normal': model = self.cb.last_model elif model_type == 'best': model = self.cb.best_model elif model_type == 'test': model = self.model test_acc, test_loss = 0., 0. batch_val_counter = 0 y_hat_auc, label_auc = [], [] device = self.device with torch.no_grad(): model.eval() # validation loop for _, (inputs, labels) in enumerate(test_dataloader): for rot in range(0,4): # print(rot, inputs.shape) inputs = torch.rot90(inputs, rot, [2, 3]) # inputs = Variable(inputs.to(device)) # labels = Variable(labels.to(device)) # print(counter, rot, inputs.shape) inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) # img = inputs.cpu().detach().numpy() # img = img.transpose(0,2,3,1) # print(img[0, :, :, 0:3].shape) # cv2.imwrite('thrash/test-aug_'+str(rot)+'.png', img[0, :, :, 0:3]*65535) outputs = model(inputs) # forward pass loss = self.loss_criterion(outputs, labels) # compute loss test_loss += loss.item() * labels.size(0) # calculate acc test_acc += calc_acc(outputs, labels).item() batch_val_counter += labels.size(0) # Store auc for malignant label_auc = np.append(label_auc, labels.cpu().detach().numpy()) y_hat_auc = np.append(y_hat_auc, torch.softmax(outputs, dim=1)[:, 1].cpu().detach().numpy()) # enter show result mode if self.mini_batch == 1: print(f'{labels.item()} {torch.softmax(outputs, dim=1)[:, 1].item():.3f}') print('batch_val_counter ', batch_val_counter) # Find average test loss and test accuracy avg_test_loss = test_loss/batch_val_counter avg_test_acc = test_acc/batch_val_counter print(f"Model: {model_type} - Test accuracy : {avg_test_acc:.3f}" + f" Test loss : {avg_test_loss:.4f}", end='') # calculate AUC TEST auc_mal_val = roc_auc_score(label_auc.ravel(), y_hat_auc.ravel()) print(f' AUC Malignant: {auc_mal_val:.4f}') if self.make_plots: show_auc(label_auc, y_hat_auc, self.title, show_plt=False) return auc_mal_val

42.005725

159

0.564445

from matplotlib.pyplot import show import torch from torch.autograd import Variable from torch.cuda.amp import GradScaler, autocast import numpy as np from sklearn.metrics import roc_auc_score from callbacks.cb_handler import CallbackHandler from callbacks.cb_base import BaseCB from callbacks.cb_lr_patch_clf import LR_SchedCB_patch from callbacks.cb_lr_full_clf import LR_SchedCB_full from callbacks.cb_lr_2views_clf import LR_SchedCB_2views from callbacks.cb_lr_w_cyc_cos import LR_SchedCB_W_Cyc_Cos from callbacks.cb_lr_w_cos import LR_SchedCB_W_Cos from callbacks.cb_auc import AUC_CB from util.util import show_auc, calc_auc_desv parallel = False import cv2 def acc(y_hat, labels): if len(y_hat) > 1 and parallel: y_hat = torch.cat(y_hat) return (torch.argmax(y_hat, dim=1) == labels).float().sum() class Trainer(): def __init__(self, model, train_dataloader, val_dataloader, loss_criterion, optimizer, optimizer_args, device, config): self.model = model self.device = device self.loss_criterion = loss_criterion self.epochs = int(config['num_epochs']) if 'num_epochs' in config else 10 self.mini_batch = int(config['batch_size']) if 'batch_size' in config else 1 self.first_epoch = int(config['start_epoch']) if 'start_epoch' in config else 1 self.stable_metric = int(config['stable_metric']) if 'stable_metric' in config else False self.name = config['name'] if 'name' in config else 'default' self.title = config['title'] if 'title' in config else 'Classifier' self.features = config['features'] if 'features' in config else [] self.make_plots = config['make_plots'] if 'make_plots' in config else True if train_dataloader: self.train_dataloader = train_dataloader else: return self.train_dataloader = train_dataloader self.val_dataloader = val_dataloader self.optimizer = optimizer self.optimizer_args = optimizer_args print(self.title) callbacks = [BaseCB(self.name, self.title, config)] for feat in self.features: if feat == 'auc': callbacks.append(AUC_CB(self.name, config)) if feat == 'lr_step_full': callbacks.append(LR_SchedCB_full()) if feat == 'lr_step_patch': callbacks.append(LR_SchedCB_patch()) if feat == 'lr_step_2views': callbacks.append(LR_SchedCB_2views()) if feat == 'lr_warmup_cos': callbacks.append(LR_SchedCB_W_Cos()) if feat == 'lr_warmup_cyc_cos': callbacks.append(LR_SchedCB_W_Cyc_Cos()) if feat == 'LR_SchedCB_W_Cos': callbacks.append(LR_SchedCB_W_Cos()) self.cb = CallbackHandler(callbacks) def train_and_validate(self, **kwargs): calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc input_dict = kwargs.get('input_dict') if kwargs.get('input_dict') else [] if not self.cb.begin_train_val(self.epochs, self.model, self.train_dataloader, self.val_dataloader, self.mini_batch, self.optimizer): return self.cb.update_loss(self.loss_criterion, calc_acc) device = self.device for epoch in range(self.first_epoch, self.epochs+1): self.model.train() train_loss, train_acc = 0.0, 0.0 val_loss, val_acc = 0.0, 0.0 if not self.cb.begin_epoch(epoch): return optim = self.cb.update_LR(epoch, self.model, self.optimizer, self.optimizer_args) if optim: self.optimizer = optim for _, (inputs, labels) in enumerate(self.train_dataloader): if isinstance(inputs, dict): for key in input_dict: inputs[key] = inputs[key].to(device) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) res = self.cb.begin_batch(inputs, labels) if res: inputs, labels, self.loss_criterion, calc_acc = res self.optimizer.zero_grad() outputs = self.model(inputs) loss = self.loss_criterion(outputs, labels) if parallel: loss = loss.mean() loss.backward() self.optimizer.step() train_loss += loss.item() * labels.size(0) train_acc += calc_acc(outputs, labels).item() self.cb.after_step(labels.size(0), labels, outputs) with torch.no_grad(): self.model.eval() self.cb.begin_val() for _, (inputs, labels) in enumerate(self.val_dataloader): if isinstance(inputs, dict): for key in input_dict: inputs[key] = inputs[key].to(device) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = self.model(inputs) loss = self.loss_criterion(outputs, labels) if parallel: loss = loss.mean() val_loss += loss.item() * labels.size(0) val_acc += calc_acc(outputs, labels).item() self.cb.after_step_val(labels.size(0), labels, outputs) self.cb.after_epoch(self.model, train_acc, train_loss, val_acc, val_loss) self.cb.after_train_val() return self.model def train_and_validate_amp(self, **kwargs): assert torch.__version__ >= '1.6.0', "[Mixed precision] Please use PyTorch 1.6.0+" print('Using AMP') calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc input_dict = kwargs.get('input_dict') if kwargs.get('input_dict') else [] if not self.cb.begin_train_val(self.epochs, self.model, self.train_dataloader, self.val_dataloader, self.mini_batch, self.optimizer): return scaler = GradScaler() device = self.device epoch = self.first_epoch last_epoch = self.epochs while epoch <= last_epoch: self.model.train() train_loss, train_acc = 0.0, 0.0 val_loss, val_acc = 0.0, 0.0 if not self.cb.begin_epoch(epoch): return optim = self.cb.update_LR(epoch, self.model, self.optimizer, self.optimizer_args) if optim: self.optimizer = optim for _, (inputs, labels) in enumerate(self.train_dataloader): if isinstance(inputs, dict): for key in input_dict: inputs[key] = inputs[key].to(device) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) self.optimizer.zero_grad() with autocast(): outputs = self.model(inputs) loss = self.loss_criterion(outputs, labels) if parallel: loss = loss.mean() scaler.scale(loss).backward() scaler.step(self.optimizer) scaler.update() train_loss += loss.item() * labels.size(0) train_acc += calc_acc(outputs, labels).item() self.cb.after_step(labels.size(0), labels, outputs) with torch.no_grad(): self.model.eval() for _, (inputs, labels) in enumerate(self.val_dataloader): if isinstance(inputs, dict): for key in input_dict: inputs[key] = inputs[key].to(device) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = self.model(inputs) loss = self.loss_criterion(outputs, labels) if parallel: loss = loss.mean() val_loss += loss.item() * labels.size(0) val_acc += calc_acc(outputs, labels).item() self.cb.after_step_val(labels.size(0), labels, outputs) self.cb.after_epoch(self.model, train_acc, train_loss, val_acc, val_loss) epoch += 1 last_epoch = self.epochs if not self.stable_metric else min(self.epochs, self.cb.best_metric_epoch[self.cb.metric_name[-1]] + self.stable_metric) self.cb.after_train_val() values = [self.cb.best_metric, self.cb.best_metric_epoch, self.cb.elapsed_mins, self.cb.metric_name, self.cb.loss_plot, self.cb.metric_plot, self.cb.best_model_file] return values def run_test(self, test_dataloader, model_type, **kwargs): calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc quiet = kwargs.get('quiet') if kwargs.get('quiet') else False if model_type == 'normal': model = self.cb.last_model elif model_type == 'best': model = self.cb.best_model elif model_type == 'bootstrap': model = self.model test_acc, test_loss = 0., 0. batch_val_counter = 0 device = self.device with torch.no_grad(): model.eval() for _, (inputs, labels) in enumerate(test_dataloader): if isinstance(inputs, dict): for key in ['CC', 'MLO']: inputs[key] = inputs[key].to(device) labels = Variable(labels.to(device)) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = model(inputs) loss = self.loss_criterion(outputs, labels) if parallel: loss = loss.mean() test_loss += loss.item() * labels.size(0) test_acc += calc_acc(outputs, labels).item() batch_val_counter += labels.size(0) avg_test_loss = test_loss/batch_val_counter avg_test_acc = test_acc/batch_val_counter if not quiet: print(f'Model: {model_type} - Test accuracy : {avg_test_acc:.5f}' + f' Test loss : {avg_test_loss:.5f}') return avg_test_acc def run_test_auc(self, test_dataloader, model_type, **kwargs): calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc model = kwargs.get('model') if kwargs.get('model') else None show_results = kwargs.get('show_results') if kwargs.get('show_results') else False m_positive = kwargs.get('m') if kwargs.get('m') else False n_negative = kwargs.get('n') if kwargs.get('n') else False if model is None: if model_type == 'normal': model = self.cb.last_model elif model_type == 'best': model = self.cb.best_model elif model_type == 'test': model = self.model elif model_type == 'bootstrap': model = self.model test_acc, test_loss = 0., 0. batch_val_counter = 0 y_hat_auc, label_auc = [], [] device = self.device with torch.no_grad(): model.eval() for _, (inputs, labels) in enumerate(test_dataloader): if isinstance(inputs, dict): for key in ['CC', 'MLO']: inputs[key] = inputs[key].to(device) labels = Variable(labels.to(device)) else: inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = model(inputs) loss = self.loss_criterion(outputs, labels) test_loss += loss.item() * labels.size(0) test_acc += calc_acc(outputs, labels).item() batch_val_counter += labels.size(0) label_auc = np.append(label_auc, labels.cpu().detach().numpy()) y_hat_auc = np.append(y_hat_auc, torch.softmax(outputs, dim=1)[:, 1].cpu().detach().numpy()) if self.mini_batch == 1 and show_results: print(f'{labels.item()} {torch.softmax(outputs, dim=1)[:, 1].item():.3f}') avg_test_loss = test_loss/batch_val_counter avg_test_acc = test_acc/batch_val_counter print(f"Model: {model_type} - Test accuracy : {avg_test_acc:.3f}" + f" Test loss : {avg_test_loss:.4f}", end='') auc_mal_val = roc_auc_score(label_auc.ravel(), y_hat_auc.ravel()) if m_positive and n_negative: auc_final = f'{auc_mal_val:.4f}±{calc_auc_desv(m_positive, n_negative, auc_mal_val):.4f}' print(f' AUC Malignant: {auc_final}') else: auc_final = f'{auc_mal_val:.4f}' print(f' AUC Malignant: {auc_final}') if self.make_plots: show_auc(label_auc, y_hat_auc, self.title, show_plt=False) return auc_final def run_test_data_aug_auc(self, test_dataloader, model_type, **kwargs): calc_acc = kwargs.get('accuracy') if kwargs.get('accuracy') else acc model = kwargs.get('model') if kwargs.get('model') else None if model is None: if model_type == 'normal': model = self.cb.last_model elif model_type == 'best': model = self.cb.best_model elif model_type == 'test': model = self.model test_acc, test_loss = 0., 0. batch_val_counter = 0 y_hat_auc, label_auc = [], [] device = self.device with torch.no_grad(): model.eval() for _, (inputs, labels) in enumerate(test_dataloader): for rot in range(0,4): inputs = torch.rot90(inputs, rot, [2, 3]) inputs = Variable(inputs.to(device)) labels = Variable(labels.to(device)) outputs = model(inputs) loss = self.loss_criterion(outputs, labels) test_loss += loss.item() * labels.size(0) test_acc += calc_acc(outputs, labels).item() batch_val_counter += labels.size(0) label_auc = np.append(label_auc, labels.cpu().detach().numpy()) y_hat_auc = np.append(y_hat_auc, torch.softmax(outputs, dim=1)[:, 1].cpu().detach().numpy()) if self.mini_batch == 1: print(f'{labels.item()} {torch.softmax(outputs, dim=1)[:, 1].item():.3f}') print('batch_val_counter ', batch_val_counter) avg_test_loss = test_loss/batch_val_counter avg_test_acc = test_acc/batch_val_counter print(f"Model: {model_type} - Test accuracy : {avg_test_acc:.3f}" + f" Test loss : {avg_test_loss:.4f}", end='') auc_mal_val = roc_auc_score(label_auc.ravel(), y_hat_auc.ravel()) print(f' AUC Malignant: {auc_mal_val:.4f}') if self.make_plots: show_auc(label_auc, y_hat_auc, self.title, show_plt=False) return auc_mal_val

true

f718a6e4efe0bc6650e570e12bb690e1b246fd8d

315

py

Python

data.py

thIYan-EsWar/Machine-Learning-Breast-Cancer-Prediction

349e6be13476dcfb602ab1e6f812bc464a7affc3

[ "Apache-2.0" ]

null

data.py

thIYan-EsWar/Machine-Learning-Breast-Cancer-Prediction

349e6be13476dcfb602ab1e6f812bc464a7affc3

[ "Apache-2.0" ]

null

data.py

thIYan-EsWar/Machine-Learning-Breast-Cancer-Prediction

349e6be13476dcfb602ab1e6f812bc464a7affc3

[ "Apache-2.0" ]

null

from random import shuffle, sample with open('data.txt', 'r') as f: contents = f.readlines() contents = sample(contents, len(contents)) with open('train_data.txt', 'w') as f: [f.write(content) for content in contents[: 601]] with open('test_data.txt', 'w') as f: [f.write(content) for content in contents[601:]]

39.375

50

0.698413

from random import shuffle, sample with open('data.txt', 'r') as f: contents = f.readlines() contents = sample(contents, len(contents)) with open('train_data.txt', 'w') as f: [f.write(content) for content in contents[: 601]] with open('test_data.txt', 'w') as f: [f.write(content) for content in contents[601:]]

true

f718a8aa9f9b0c450e9a61914792a726a1d423d4

13,080

py

Python

tests/templates/test_subroutines/test_qmc.py

QDaria/pennylane

5a28983fc7bd950cde8a4014e54261fef4b54293

[ "Apache-2.0" ]

null

tests/templates/test_subroutines/test_qmc.py

QDaria/pennylane

5a28983fc7bd950cde8a4014e54261fef4b54293

[ "Apache-2.0" ]

null

tests/templates/test_subroutines/test_qmc.py

QDaria/pennylane

5a28983fc7bd950cde8a4014e54261fef4b54293

[ "Apache-2.0" ]

null

# Copyright 2018-2021 Xanadu Quantum Technologies Inc. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np import pytest from scipy.stats import norm import pennylane as qml from pennylane.templates.subroutines.qmc import ( QuantumMonteCarlo, _make_V, _make_Z, func_to_unitary, make_Q, probs_to_unitary, ) from pennylane.wires import Wires class TestProbsToUnitary: """Tests for the probs_to_unitary function""" def test_invalid_distribution_sum_to_not_one(self): """Test if a ValueError is raised when a distribution that does not sum to one is input""" p = np.ones(4) with pytest.raises(ValueError, match="A valid probability distribution of non-negative"): probs_to_unitary(p) def test_invalid_distribution_negative(self): """Test if a ValueError is raised when a distribution with a negative value is input""" p = [2, 0, 0, -1] with pytest.raises(ValueError, match="A valid probability distribution of non-negative"): probs_to_unitary(p) ps = [ [0.46085261032920616, 0.5391473896707938], [0.2111821738452515, 0.4235979103670337, 0.36521991578771484], [0.3167916924190049, 0.2651843704361695, 0.1871934980886578, 0.23083043905616774], [0.8123242419241959, 0.07990911578859018, 0.07983919018902215, 0.027927452098191852], ] @pytest.mark.parametrize("p", ps) def test_fixed_examples(self, p): """Test if the correct unitary is returned for fixed input examples. A correct unitary has its first column equal to the square root of the distribution and satisfies U @ U.T = U.T @ U = I.""" unitary = probs_to_unitary(p) assert np.allclose(np.sqrt(p), unitary[:, 0]) assert np.allclose(unitary @ unitary.T, np.eye(len(unitary))) assert np.allclose(unitary.T @ unitary, np.eye(len(unitary))) class TestFuncToUnitary: """Tests for the func_to_unitary function""" def test_not_bounded_func(self): """Test if a ValueError is raised if a function that evaluates outside of the [0, 1] interval is provided""" func = lambda i: np.sin(i) with pytest.raises(ValueError, match="func must be bounded within the interval"): func_to_unitary(func, 8) def test_example(self): """Test for a fixed example if the returned unitary maps input states to the expected output state as well as if the unitary satisfies U @ U.T = U.T @ U = I.""" M = 8 func = lambda i: np.sin(i) ** 2 r = func_to_unitary(func, M) for i in range(M): # The control qubit is the last qubit, so we have to look at every other term # using [::2]. output_state = r[::2][i] output_0 = output_state[::2] output_1 = output_state[1::2] assert np.allclose(output_0[i], np.sqrt(1 - func(i))) assert np.allclose(output_1[i], np.sqrt(func(i))) assert np.allclose(r @ r.T, np.eye(2 * M)) assert np.allclose(r.T @ r, np.eye(2 * M)) def test_example_with_pl(self): """Test for a fixed example if the returned unitary behaves as expected when used within a PennyLane circuit, i.e., so that the probability of the final control wire encodes the function.""" wires = 3 M = 2**wires func = lambda i: np.sin(i) ** 2 r = func_to_unitary(func, M) dev = qml.device("default.qubit", wires=(wires + 1)) @qml.qnode(dev) def apply_r(input_state): qml.QubitStateVector(input_state, wires=range(wires)) qml.QubitUnitary(r, wires=range(wires + 1)) return qml.probs(wires) for i, state in enumerate(np.eye(M)): p = apply_r(state)[1] assert np.allclose(p, func(i)) def test_V(): """Test for the _make_V function""" dim = 4 V_expected = -np.eye(dim) V_expected[1, 1] = V_expected[3, 3] = 1 V = _make_V(dim) assert np.allclose(V, V_expected) def test_Z(): """Test for the _make_Z function""" dim = 4 Z_expected = -np.eye(dim) Z_expected[0, 0] = 1 Z = _make_Z(dim) assert np.allclose(Z, Z_expected) def test_Q(): """Test for the make_Q function using a fixed example""" A = np.array( [ [0.85358423 - 0.32239299j, -0.12753659 + 0.38883306j], [0.39148136 - 0.11915985j, 0.34064316 - 0.84646648j], ] ) R = np.array( [ [ 0.45885289 + 0.03972856j, 0.2798685 - 0.05981098j, 0.64514642 - 0.51555038j, 0.11015177 - 0.10877695j, ], [ 0.19407005 - 0.35483005j, 0.29756077 + 0.80153453j, -0.19147104 + 0.0507968j, 0.15553799 - 0.20493631j, ], [ 0.35083011 - 0.20807392j, -0.27602911 - 0.13934692j, 0.11874165 + 0.34532609j, -0.45945242 - 0.62734969j, ], [ -0.11379919 - 0.66706921j, -0.21120956 - 0.2165113j, 0.30133006 + 0.23367271j, 0.54593491 + 0.08446372j, ], ] ) Q_expected = np.array( [ [ -0.46513201 - 1.38777878e-17j, -0.13035515 - 2.23341802e-01j, -0.74047856 + 7.08652160e-02j, -0.0990036 - 3.91977176e-01j, ], [ 0.13035515 - 2.23341802e-01j, 0.46494302 + 0.00000000e00j, 0.05507901 - 1.19182067e-01j, -0.80370146 - 2.31904873e-01j, ], [ -0.74047856 - 7.08652160e-02j, -0.05507901 - 1.19182067e-01j, 0.62233412 - 2.77555756e-17j, -0.0310774 - 2.02894077e-01j, ], [ 0.0990036 - 3.91977176e-01j, -0.80370146 + 2.31904873e-01j, 0.0310774 - 2.02894077e-01j, -0.30774091 + 2.77555756e-17j, ], ] ) Q = make_Q(A, R) assert np.allclose(Q, Q_expected) class TestQuantumMonteCarlo: """Tests for the QuantumMonteCarlo template""" @staticmethod def func(i): return np.sin(i) ** 2 def test_non_flat(self): """Test if a ValueError is raised when a non-flat array is input""" p = np.ones((4, 1)) / 4 with pytest.raises(ValueError, match="The probability distribution must be specified as a"): QuantumMonteCarlo(p, self.func, range(3), range(3, 5)) def test_wrong_size_p(self): """Test if a ValueError is raised when a probability distribution is passed whose length cannot be mapped to qubits""" p = np.ones(5) / 5 with pytest.raises(ValueError, match="The probability distribution must have a length"): QuantumMonteCarlo(p, self.func, range(3), range(3, 5)) def test_unexpected_target_wires_number(self): """Test if a ValueError is raised when the number of target wires is incompatible with the expected number of target wires inferred from the length of the input probability distribution""" p = np.ones(4) / 4 with pytest.raises( ValueError, match="The probability distribution of dimension 4 requires" " 3 target wires", ): QuantumMonteCarlo(p, self.func, range(4), range(4, 6)) def test_expected_circuit(self): """Test if the circuit applied when using the QMC template is the same as the expected circuit for a fixed example""" p = np.ones(4) / 4 target_wires, estimation_wires = Wires(range(3)), Wires(range(3, 5)) op = QuantumMonteCarlo(p, self.func, target_wires, estimation_wires) tape = op.expand() # Do expansion in two steps to avoid also decomposing the first QubitUnitary queue_before_qpe = tape.operations[:2] # 2-qubit decomposition has 10 operations, and after is a 3-qubit gate so start at 11 queue_after_qpe = tape.expand().operations[11:] A = probs_to_unitary(p) R = func_to_unitary(self.func, 4) assert len(queue_before_qpe) == 2 assert queue_before_qpe[0].name == "QubitUnitary" assert queue_before_qpe[1].name == "QubitUnitary" assert np.allclose(queue_before_qpe[0].matrix, A) assert np.allclose(queue_before_qpe[1].matrix, R) assert queue_before_qpe[0].wires == target_wires[:-1] assert queue_before_qpe[1].wires == target_wires Q = make_Q(A, R) with qml.tape.QuantumTape() as qpe_tape: qml.QuantumPhaseEstimation(Q, target_wires, estimation_wires) qpe_tape = qpe_tape.expand() assert len(queue_after_qpe) == len(qpe_tape.operations) assert all(o1.name == o2.name for o1, o2 in zip(queue_after_qpe, qpe_tape.operations)) assert all( np.allclose(o1.matrix, o2.matrix) for o1, o2 in zip(queue_after_qpe, qpe_tape.operations) ) assert all(o1.wires == o2.wires for o1, o2 in zip(queue_after_qpe, qpe_tape.operations)) def test_expected_value(self): """Test that the QuantumMonteCarlo template can correctly estimate the expectation value following the example in the usage details""" m = 5 M = 2**m xmax = np.pi xs = np.linspace(-xmax, xmax, M) probs = np.array([norm().pdf(x) for x in xs]) probs /= np.sum(probs) func = lambda i: np.cos(xs[i]) ** 2 estimates = [] for n in range(4, 11): N = 2**n target_wires = range(m + 1) estimation_wires = range(m + 1, n + m + 1) dev = qml.device("default.qubit", wires=(n + m + 1)) @qml.qnode(dev) def circuit(): qml.QuantumMonteCarlo( probs, func, target_wires=target_wires, estimation_wires=estimation_wires ) return qml.probs(estimation_wires) phase_estimated = np.argmax(circuit()[: int(N / 2)]) / N mu_estimated = (1 - np.cos(np.pi * phase_estimated)) / 2 estimates.append(mu_estimated) exact = 0.432332358381693654 # Check that the error is monotonically decreasing for i in range(len(estimates) - 1): err1 = np.abs(estimates[i] - exact) err2 = np.abs(estimates[i + 1] - exact) assert err1 >= err2 assert np.allclose(estimates[-1], exact, rtol=1e-3) def test_expected_value_custom_wires(self): """Test that the QuantumMonteCarlo template can correctly estimate the expectation value following the example in the usage details when the wires have custom labels""" m = 5 M = 2**m xmax = np.pi xs = np.linspace(-xmax, xmax, M) probs = np.array([norm().pdf(x) for x in xs]) probs /= np.sum(probs) func = lambda i: np.cos(xs[i]) ** 2 n = 10 N = 2**n target_wires = [0, "a", -1.1, -10, "bbb", 1000] estimation_wires = ["bob", -3, 42, "penny", "lane", 247, "straw", "berry", 5.5, 6.6] dev = qml.device("default.qubit", wires=target_wires + estimation_wires) @qml.qnode(dev) def circuit(): qml.QuantumMonteCarlo( probs, func, target_wires=target_wires, estimation_wires=estimation_wires ) return qml.probs(estimation_wires) phase_estimated = np.argmax(circuit()[: int(N / 2)]) / N mu_estimated = (1 - np.cos(np.pi * phase_estimated)) / 2 exact = 0.432332358381693654 assert np.allclose(mu_estimated, exact, rtol=1e-3) def test_id(self): """Tests that the id attribute can be set.""" xs = np.linspace(-np.pi, np.pi, 2**5) probs = np.array([norm().pdf(x) for x in xs]) probs /= np.sum(probs) func = lambda i: np.cos(xs[i]) ** 2 target_wires = [0, "a", -1.1, -10, "bbb", 1000] estimation_wires = ["bob", -3, 42, "penny", "lane", 247, "straw", "berry", 5.5, 6.6] template = qml.QuantumMonteCarlo( probs, func, target_wires=target_wires, estimation_wires=estimation_wires, id="a" ) assert template.id == "a"

34.603175

100

0.58815

import numpy as np import pytest from scipy.stats import norm import pennylane as qml from pennylane.templates.subroutines.qmc import ( QuantumMonteCarlo, _make_V, _make_Z, func_to_unitary, make_Q, probs_to_unitary, ) from pennylane.wires import Wires class TestProbsToUnitary: def test_invalid_distribution_sum_to_not_one(self): p = np.ones(4) with pytest.raises(ValueError, match="A valid probability distribution of non-negative"): probs_to_unitary(p) def test_invalid_distribution_negative(self): p = [2, 0, 0, -1] with pytest.raises(ValueError, match="A valid probability distribution of non-negative"): probs_to_unitary(p) ps = [ [0.46085261032920616, 0.5391473896707938], [0.2111821738452515, 0.4235979103670337, 0.36521991578771484], [0.3167916924190049, 0.2651843704361695, 0.1871934980886578, 0.23083043905616774], [0.8123242419241959, 0.07990911578859018, 0.07983919018902215, 0.027927452098191852], ] @pytest.mark.parametrize("p", ps) def test_fixed_examples(self, p): unitary = probs_to_unitary(p) assert np.allclose(np.sqrt(p), unitary[:, 0]) assert np.allclose(unitary @ unitary.T, np.eye(len(unitary))) assert np.allclose(unitary.T @ unitary, np.eye(len(unitary))) class TestFuncToUnitary: def test_not_bounded_func(self): func = lambda i: np.sin(i) with pytest.raises(ValueError, match="func must be bounded within the interval"): func_to_unitary(func, 8) def test_example(self): M = 8 func = lambda i: np.sin(i) ** 2 r = func_to_unitary(func, M) for i in range(M): output_state = r[::2][i] output_0 = output_state[::2] output_1 = output_state[1::2] assert np.allclose(output_0[i], np.sqrt(1 - func(i))) assert np.allclose(output_1[i], np.sqrt(func(i))) assert np.allclose(r @ r.T, np.eye(2 * M)) assert np.allclose(r.T @ r, np.eye(2 * M)) def test_example_with_pl(self): wires = 3 M = 2**wires func = lambda i: np.sin(i) ** 2 r = func_to_unitary(func, M) dev = qml.device("default.qubit", wires=(wires + 1)) @qml.qnode(dev) def apply_r(input_state): qml.QubitStateVector(input_state, wires=range(wires)) qml.QubitUnitary(r, wires=range(wires + 1)) return qml.probs(wires) for i, state in enumerate(np.eye(M)): p = apply_r(state)[1] assert np.allclose(p, func(i)) def test_V(): dim = 4 V_expected = -np.eye(dim) V_expected[1, 1] = V_expected[3, 3] = 1 V = _make_V(dim) assert np.allclose(V, V_expected) def test_Z(): dim = 4 Z_expected = -np.eye(dim) Z_expected[0, 0] = 1 Z = _make_Z(dim) assert np.allclose(Z, Z_expected) def test_Q(): A = np.array( [ [0.85358423 - 0.32239299j, -0.12753659 + 0.38883306j], [0.39148136 - 0.11915985j, 0.34064316 - 0.84646648j], ] ) R = np.array( [ [ 0.45885289 + 0.03972856j, 0.2798685 - 0.05981098j, 0.64514642 - 0.51555038j, 0.11015177 - 0.10877695j, ], [ 0.19407005 - 0.35483005j, 0.29756077 + 0.80153453j, -0.19147104 + 0.0507968j, 0.15553799 - 0.20493631j, ], [ 0.35083011 - 0.20807392j, -0.27602911 - 0.13934692j, 0.11874165 + 0.34532609j, -0.45945242 - 0.62734969j, ], [ -0.11379919 - 0.66706921j, -0.21120956 - 0.2165113j, 0.30133006 + 0.23367271j, 0.54593491 + 0.08446372j, ], ] ) Q_expected = np.array( [ [ -0.46513201 - 1.38777878e-17j, -0.13035515 - 2.23341802e-01j, -0.74047856 + 7.08652160e-02j, -0.0990036 - 3.91977176e-01j, ], [ 0.13035515 - 2.23341802e-01j, 0.46494302 + 0.00000000e00j, 0.05507901 - 1.19182067e-01j, -0.80370146 - 2.31904873e-01j, ], [ -0.74047856 - 7.08652160e-02j, -0.05507901 - 1.19182067e-01j, 0.62233412 - 2.77555756e-17j, -0.0310774 - 2.02894077e-01j, ], [ 0.0990036 - 3.91977176e-01j, -0.80370146 + 2.31904873e-01j, 0.0310774 - 2.02894077e-01j, -0.30774091 + 2.77555756e-17j, ], ] ) Q = make_Q(A, R) assert np.allclose(Q, Q_expected) class TestQuantumMonteCarlo: @staticmethod def func(i): return np.sin(i) ** 2 def test_non_flat(self): p = np.ones((4, 1)) / 4 with pytest.raises(ValueError, match="The probability distribution must be specified as a"): QuantumMonteCarlo(p, self.func, range(3), range(3, 5)) def test_wrong_size_p(self): p = np.ones(5) / 5 with pytest.raises(ValueError, match="The probability distribution must have a length"): QuantumMonteCarlo(p, self.func, range(3), range(3, 5)) def test_unexpected_target_wires_number(self): p = np.ones(4) / 4 with pytest.raises( ValueError, match="The probability distribution of dimension 4 requires" " 3 target wires", ): QuantumMonteCarlo(p, self.func, range(4), range(4, 6)) def test_expected_circuit(self): p = np.ones(4) / 4 target_wires, estimation_wires = Wires(range(3)), Wires(range(3, 5)) op = QuantumMonteCarlo(p, self.func, target_wires, estimation_wires) tape = op.expand() queue_before_qpe = tape.operations[:2] queue_after_qpe = tape.expand().operations[11:] A = probs_to_unitary(p) R = func_to_unitary(self.func, 4) assert len(queue_before_qpe) == 2 assert queue_before_qpe[0].name == "QubitUnitary" assert queue_before_qpe[1].name == "QubitUnitary" assert np.allclose(queue_before_qpe[0].matrix, A) assert np.allclose(queue_before_qpe[1].matrix, R) assert queue_before_qpe[0].wires == target_wires[:-1] assert queue_before_qpe[1].wires == target_wires Q = make_Q(A, R) with qml.tape.QuantumTape() as qpe_tape: qml.QuantumPhaseEstimation(Q, target_wires, estimation_wires) qpe_tape = qpe_tape.expand() assert len(queue_after_qpe) == len(qpe_tape.operations) assert all(o1.name == o2.name for o1, o2 in zip(queue_after_qpe, qpe_tape.operations)) assert all( np.allclose(o1.matrix, o2.matrix) for o1, o2 in zip(queue_after_qpe, qpe_tape.operations) ) assert all(o1.wires == o2.wires for o1, o2 in zip(queue_after_qpe, qpe_tape.operations)) def test_expected_value(self): m = 5 M = 2**m xmax = np.pi xs = np.linspace(-xmax, xmax, M) probs = np.array([norm().pdf(x) for x in xs]) probs /= np.sum(probs) func = lambda i: np.cos(xs[i]) ** 2 estimates = [] for n in range(4, 11): N = 2**n target_wires = range(m + 1) estimation_wires = range(m + 1, n + m + 1) dev = qml.device("default.qubit", wires=(n + m + 1)) @qml.qnode(dev) def circuit(): qml.QuantumMonteCarlo( probs, func, target_wires=target_wires, estimation_wires=estimation_wires ) return qml.probs(estimation_wires) phase_estimated = np.argmax(circuit()[: int(N / 2)]) / N mu_estimated = (1 - np.cos(np.pi * phase_estimated)) / 2 estimates.append(mu_estimated) exact = 0.432332358381693654 for i in range(len(estimates) - 1): err1 = np.abs(estimates[i] - exact) err2 = np.abs(estimates[i + 1] - exact) assert err1 >= err2 assert np.allclose(estimates[-1], exact, rtol=1e-3) def test_expected_value_custom_wires(self): m = 5 M = 2**m xmax = np.pi xs = np.linspace(-xmax, xmax, M) probs = np.array([norm().pdf(x) for x in xs]) probs /= np.sum(probs) func = lambda i: np.cos(xs[i]) ** 2 n = 10 N = 2**n target_wires = [0, "a", -1.1, -10, "bbb", 1000] estimation_wires = ["bob", -3, 42, "penny", "lane", 247, "straw", "berry", 5.5, 6.6] dev = qml.device("default.qubit", wires=target_wires + estimation_wires) @qml.qnode(dev) def circuit(): qml.QuantumMonteCarlo( probs, func, target_wires=target_wires, estimation_wires=estimation_wires ) return qml.probs(estimation_wires) phase_estimated = np.argmax(circuit()[: int(N / 2)]) / N mu_estimated = (1 - np.cos(np.pi * phase_estimated)) / 2 exact = 0.432332358381693654 assert np.allclose(mu_estimated, exact, rtol=1e-3) def test_id(self): xs = np.linspace(-np.pi, np.pi, 2**5) probs = np.array([norm().pdf(x) for x in xs]) probs /= np.sum(probs) func = lambda i: np.cos(xs[i]) ** 2 target_wires = [0, "a", -1.1, -10, "bbb", 1000] estimation_wires = ["bob", -3, 42, "penny", "lane", 247, "straw", "berry", 5.5, 6.6] template = qml.QuantumMonteCarlo( probs, func, target_wires=target_wires, estimation_wires=estimation_wires, id="a" ) assert template.id == "a"

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pages/tests/pages_tests.py

odyaka341/django-page-cms

eca92673f735f5ad158d5a81b72280705057bf52

[ "BSD-3-Clause" ]

null

pages/tests/pages_tests.py

odyaka341/django-page-cms

eca92673f735f5ad158d5a81b72280705057bf52

[ "BSD-3-Clause" ]

null

pages/tests/pages_tests.py

odyaka341/django-page-cms

eca92673f735f5ad158d5a81b72280705057bf52

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """Django page CMS test suite module""" import django from django.conf import settings from django.test.client import Client from django.template import Template, RequestContext, TemplateDoesNotExist from django.http import HttpResponse, HttpResponseRedirect from django.shortcuts import render_to_response from pages.models import Page, Content, PageAlias from pages.tests.testcase import TestCase class PagesTestCase(TestCase): """Django page CMS test suite class""" def test_01_add_page(self): """Test that the add admin page could be displayed via the admin""" c = Client() c.login(username= 'batiste', password='b') response = c.get('/admin/pages/page/add/') self.assertEqual(response.status_code, 200) def test_02_create_page(self): """Test that a page can be created via the admin.""" #setattr(settings, "SITE_ID", 2) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') slug_content = Content.objects.get_content_slug_by_slug( page_data['slug'] ) assert(slug_content is not None) page = slug_content.page self.assertEqual(page.title(), page_data['title']) self.assertEqual(page.slug(), page_data['slug']) self.assertNotEqual(page.last_modification_date, None) def test_03_slug_collision(self): """Test a slug collision.""" setattr(settings, "PAGE_UNIQUE_SLUG_REQUIRED", True) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') setattr(settings, "PAGE_UNIQUE_SLUG_REQUIRED", False) response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) page1 = Content.objects.get_content_slug_by_slug(page_data['slug']).page page_data['position'] = 'first-child' page_data['target'] = page1.id response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page2 = Content.objects.get_content_slug_by_slug(page_data['slug']).page self.assertNotEqual(page1.id, page2.id) def test_04_details_view(self): """Test the details view""" c = Client() c.login(username= 'batiste', password='b') try: response = c.get('/pages/') except TemplateDoesNotExist, e: if e.args != ('404.html',): raise page_data = self.get_new_page_data() page_data['status'] = Page.DRAFT response = c.post('/admin/pages/page/add/', page_data) try: response = c.get('/pages/') except TemplateDoesNotExist, e: if e.args != ('404.html',): raise page_data = self.get_new_page_data() page_data['status'] = Page.PUBLISHED page_data['slug'] = 'test-page-2' page_data['template'] = 'pages/index.html' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') response = c.get('/pages/test-page-2/') self.assertEqual(response.status_code, 200) def test_05_edit_page(self): """Test that a page can edited via the admin""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page = Page.objects.all()[0] response = c.get('/admin/pages/page/%d/' % page.id) self.assertEqual(response.status_code, 200) page_data['title'] = 'changed title' page_data['body'] = 'changed body' response = c.post('/admin/pages/page/%d/' % page.id, page_data) self.assertRedirects(response, '/admin/pages/page/') page = Page.objects.get(id=page.id) self.assertEqual(page.title(), 'changed title') body = Content.objects.get_content(page, 'en-us', 'body') self.assertEqual(body, 'changed body') def test_06_site_framework(self): """Test the site framework, and test if it's possible to disable it""" # this is necessary to make the test pass from pages import settings as pages_settings setattr(pages_settings, "SITE_ID", 2) setattr(pages_settings, "PAGE_USE_SITE_ID", True) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data["sites"] = [2] response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page = Content.objects.get_content_slug_by_slug(page_data['slug']).page self.assertEqual(page.sites.count(), 1) self.assertEqual(page.sites.all()[0].id, 2) page_data = self.get_new_page_data() page_data["sites"] = [3] response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') # we cannot get a slug that doesn't exist content = Content.objects.get_content_slug_by_slug("this doesn't exist") self.assertEqual(content, None) # we cannot get the data posted on another site content = Content.objects.get_content_slug_by_slug(page_data['slug']) self.assertEqual(content, None) setattr(pages_settings, "SITE_ID", 3) page = Content.objects.get_content_slug_by_slug(page_data['slug']).page self.assertEqual(page.sites.count(), 1) self.assertEqual(page.sites.all()[0].id, 3) # with param self.assertEqual(Page.objects.on_site(2).count(), 1) self.assertEqual(Page.objects.on_site(3).count(), 1) # without param self.assertEqual(Page.objects.on_site().count(), 1) setattr(pages_settings, "SITE_ID", 2) self.assertEqual(Page.objects.on_site().count(), 1) page_data = self.get_new_page_data() page_data["sites"] = [2, 3] response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') self.assertEqual(Page.objects.on_site(3).count(), 2) self.assertEqual(Page.objects.on_site(2).count(), 2) self.assertEqual(Page.objects.on_site().count(), 2) setattr(pages_settings, "PAGE_USE_SITE_ID", False) # we should get everything self.assertEqual(Page.objects.on_site().count(), 3) def test_07_languages(self): """Test post a page with different languages and test that the admin views works correctly.""" c = Client() user = c.login(username= 'batiste', password='b') # test that the client language setting is used in add page admin c.cookies["django_language"] = 'de' response = c.get('/admin/pages/page/add/') self.assertContains(response, 'value="de" selected="selected"') c.cookies["django_language"] = 'fr-ch' response = c.get('/admin/pages/page/add/') self.assertContains(response, 'value="fr-ch" selected="selected"') page_data = self.get_new_page_data() page_data["title"] = 'english title' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page = Page.objects.all()[0] self.assertEqual(page.get_languages(), ['en-us']) # this test only works in version superior of 1.0.2 django_version = django.get_version().rsplit()[0].split('.') if len(django_version) > 2: major, middle, minor = [int(v) for v in django_version] else: major, middle = [int(v) for v in django_version] if major >= 1 and middle > 0: response = c.get('/admin/pages/page/%d/?language=de' % page.id) self.assertContains(response, 'value="de" selected="selected"') # add a french version of the same page page_data["language"] = 'fr-ch' page_data["title"] = 'french title' response = c.post('/admin/pages/page/%d/' % page.id, page_data) self.assertRedirects(response, '/admin/pages/page/') #setattr(settings, "PAGE_DEFAULT_LANGUAGE", 'en-us') # test that the frontend view use the good parameters # I cannot find a way of setting the accept-language HTTP # header so I used django_language cookie instead c = Client() c.cookies["django_language"] = 'en-us' response = c.get('/pages/') self.assertContains(response, 'english title') self.assertContains(response, 'lang="en-us"') self.assertNotContains(response, 'french title') c = Client() c.cookies["django_language"] = 'fr-ch' response = c.get('/pages/') self.assertContains(response, 'french title') self.assertContains(response, 'lang="fr-ch"') self.assertNotContains(response, 'english title') # this should be mapped to the fr-ch content c = Client() c.cookies["django_language"] = 'fr-fr' response = c.get('/pages/') self.assertContains(response, 'french title') self.assertContains(response, 'lang="fr-ch"') def test_08_revision(self): """Test that a page can edited several times.""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) page = Page.objects.all()[0] page_data['body'] = 'changed body' response = c.post('/admin/pages/page/%d/' % page.id, page_data) self.assertEqual(Content.objects.get_content(page, 'en-us', 'body'), 'changed body') page_data['body'] = 'changed body 2' response = c.post('/admin/pages/page/%d/' % page.id, page_data) self.assertEqual(Content.objects.get_content(page, 'en-us', 'body'), 'changed body 2') response = c.get('/pages/') self.assertContains(response, 'changed body 2', 1) setattr(settings, "PAGE_CONTENT_REVISION", False) self.assertEqual(Content.objects.get_content(page, 'en-us', 'body'), 'changed body 2') def test_09_placeholder(self): """ Test that the placeholder is correctly displayed in the admin """ setattr(settings, "SITE_ID", 2) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['template'] = 'pages/nice.html' response = c.post('/admin/pages/page/add/', page_data) page = Page.objects.all()[0] response = c.get('/admin/pages/page/%d/' % page.id) self.assertEqual(response.status_code, 200) self.assertContains(response, 'name="right-column"', 1) def test_10_directory_slug(self): """ Test diretory slugs """ setattr(settings, "PAGE_UNIQUE_SLUG_REQUIRED", False) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['title'] = 'parent title' page_data['slug'] = 'same-slug' response = c.post('/admin/pages/page/add/', page_data) # the redirect tell that the page has been create correctly self.assertRedirects(response, '/admin/pages/page/') response = c.get('/pages/same-slug/') self.assertEqual(response.status_code, 200) page = Page.objects.all()[0] response = c.post('/admin/pages/page/add/', page_data) # we cannot create 2 root page with the same slug # this assert test that the creation fails as wanted self.assertEqual(response.status_code, 200) page1 = Content.objects.get_content_slug_by_slug(page_data['slug']).page self.assertEqual(page1.id, page.id) page_data['title'] = 'children title' page_data['target'] = page1.id page_data['position'] = 'first-child' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') # finaly test that we can get every page according the path response = c.get('/pages/same-slug') self.assertContains(response, "parent title", 2) response = c.get('/pages/same-slug/same-slug') self.assertContains(response, "children title", 2) def test_11_show_content_tag(self): """ Test the {% show_content %} template tag """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) page = Page.objects.all()[0] class request: REQUEST = {'language': 'en'} GET = {} context = RequestContext(request, {'page': page, 'lang':'en-us', 'path':'/page-1/'}) template = Template('{% load pages_tags %}' '{% show_content page "title" "en-us" %}') self.assertEqual(template.render(context), page_data['title']) template = Template('{% load pages_tags %}' '{% show_content page "title" %}') self.assertEqual(template.render(context), page_data['title']) def test_12_get_content_tag(self): """ Test the {% get_content %} template tag """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) page = Page.objects.all()[0] class request: REQUEST = {'language': 'en'} GET = {} context = RequestContext(request, {'page': page}) template = Template('{% load pages_tags %}' '{% get_content page "title" "en-us" as content %}' '{{ content }}') self.assertEqual(template.render(context), page_data['title']) template = Template('{% load pages_tags %}' '{% get_content page "title" as content %}' '{{ content }}') self.assertEqual(template.render(context), page_data['title']) def test_17_request_mockup(self): from pages.utils import get_request_mock request = get_request_mock() self.assertEqual(hasattr(request, 'session'), True) def test_18_tree_admin_interface(self): """ Test that moving/creating page in the tree is working properly using the admin interface """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'root' response = c.post('/admin/pages/page/add/', page_data) root_page = Content.objects.get_content_slug_by_slug('root').page self.assertTrue(root_page.is_first_root()) page_data['position'] = 'first-child' page_data['target'] = root_page.id page_data['slug'] = 'child-1' response = c.post('/admin/pages/page/add/', page_data) child_1 = Content.objects.get_content_slug_by_slug('child-1').page self.assertFalse(child_1.is_first_root()) page_data['slug'] = 'child-2' response = c.post('/admin/pages/page/add/', page_data) child_2 = Content.objects.get_content_slug_by_slug('child-2').page self.assertEqual(str(Page.objects.all()), "[<Page: root>, <Page: child-2>, <Page: child-1>]") # move page 1 in the first position response = c.post('/admin/pages/page/%d/move-page/' % child_1.id, {'position':'first-child', 'target':root_page.id}) self.assertEqual(str(Page.objects.all()), "[<Page: root>, <Page: child-1>, <Page: child-2>]") # move page 2 in the first position response = c.post('/admin/pages/page/%d/move-page/' % child_2.id, {'position': 'left', 'target': child_1.id}) self.assertEqual(str(Page.objects.all()), "[<Page: root>, <Page: child-2>, <Page: child-1>]") # try to create a sibling with the same slug, via left, right from pages import settings as pages_settings setattr(pages_settings, "PAGE_UNIQUE_SLUG_REQUIRED", False) page_data['target'] = child_2.id page_data['position'] = 'left' response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) # try to create a sibling with the same slug, via first-child page_data['target'] = root_page.id page_data['position'] = 'first-child' response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) # try to create a second page 2 in root del page_data['target'] del page_data['position'] setattr(pages_settings, "PAGE_UNIQUE_SLUG_REQUIRED", True) # cannot create because slug exists response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) # Now it should work beause the page is not a sibling setattr(pages_settings, "PAGE_UNIQUE_SLUG_REQUIRED", False) response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 302) self.assertEqual(Page.objects.count(), 4) # Should not work because we already have sibling at the same level response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) # try to change the page 2 slug into page 1 page_data['slug'] = 'child-1' response = c.post('/admin/pages/page/%d/' % child_2.id, page_data) self.assertEqual(response.status_code, 200) setattr(pages_settings, "PAGE_UNIQUE_SLUG_REQUIRED", True) response = c.post('/admin/pages/page/%d/' % child_2.id, page_data) self.assertEqual(response.status_code, 200) def test_19_tree(self): """ Test that the navigation tree works properly with mptt """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'page1' response = c.post('/admin/pages/page/add/', page_data) page_data['slug'] = 'page2' response = c.post('/admin/pages/page/add/', page_data) page_data['slug'] = 'page3' response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(str(Page.objects.navigation()), "[<Page: page1>, <Page: page2>, <Page: page3>]") p1 = Content.objects.get_content_slug_by_slug('page1').page p2 = Content.objects.get_content_slug_by_slug('page2').page p3 = Content.objects.get_content_slug_by_slug('page3').page p2.move_to(p1, 'left') p2.save() self.assertEqual(str(Page.objects.navigation()), "[<Page: page2>, <Page: page1>, <Page: page3>]") p3.move_to(p2, 'left') p3.save() self.assertEqual(str(Page.objects.navigation()), "[<Page: page3>, <Page: page2>, <Page: page1>]") p1 = Content.objects.get_content_slug_by_slug('page1').page p2 = Content.objects.get_content_slug_by_slug('page2').page p3 = Content.objects.get_content_slug_by_slug('page3').page p3.move_to(p1, 'first-child') p2.move_to(p1, 'first-child') self.assertEqual(str(Page.objects.navigation()), "[<Page: page1>]") p3 = Content.objects.get_content_slug_by_slug('page3').page p3.move_to(p1, 'left') self.assertEqual(str(Page.objects.navigation()), "[<Page: page3>, <Page: page1>]") def test_20_ajax_language(self): """Test that language is working properly""" c = Client() c.login(username= 'batiste', password='b') # Activate a language other than settings.LANGUAGE_CODE response = c.post('/i18n/setlang/', {'language':'fr-ch' }) self.assertEqual(c.session.get('django_language', False), 'fr-ch') # Make sure we're in french response = c.get('/admin/pages/page/') self.assertEqual(response.status_code, 200) self.assertTrue('Auteur' in response.content) # Create some pages (taken from test_18_tree_admin_interface) page_data = self.get_new_page_data() page_data['slug'] = 'root' response = c.post('/admin/pages/page/add/', page_data) root_page = Content.objects.get_content_slug_by_slug('root').page page_data['position'] = 'first-child' page_data['target'] = root_page.id page_data['slug'] = 'child-1' response = c.post('/admin/pages/page/add/', page_data) child_1 = Content.objects.get_content_slug_by_slug('child-1').page page_data['slug'] = 'child-2' response = c.post('/admin/pages/page/add/', page_data) child_2 = Content.objects.get_content_slug_by_slug('child-2').page self.assertEqual(str(Page.objects.all()), "[<Page: root>, <Page: child-2>, <Page: child-1>]") """ The relevant bit, fixed by rev 501: the response issued by a move command returns content localized in settings.LANGUAGE_CODE (i.e. 'en´) even though the original AJAX request passed in a the correct session ID localizing this client as fr-ch This is probably because the LocaleMiddleware gets instantiated with a couple request_mocks which have no real connection to the AJAX request *but* django.utils.translation caches the active language on a per thread basis. This means that the first "bogus" call to LocaleMiddleware.process_request will "kill" the localization data for the AJAX request. Rev. 501 fixes this by passing in the language code from the original request. """ response = c.post('/admin/pages/page/%d/move-page/' % child_1.id, {'position':'first-child', 'target':root_page.id}) # Make sure the content response we got was in french self.assertTrue('Auteur' in response.content) def test_21_view_context(self): """ Test that the default view can only return the context """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'page1' # create a page for the example otherwise you will get a Http404 error response = c.post('/admin/pages/page/add/', page_data) page1 = Content.objects.get_content_slug_by_slug('page1').page from pages.views import details from pages.utils import get_request_mock request = get_request_mock() context = details(request, only_context=True) self.assertEqual(context['current_page'], page1) def test_24_page_valid_targets(self): """Test page valid_targets method""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'root' response = c.post('/admin/pages/page/add/', page_data) root_page = Content.objects.get_content_slug_by_slug('root').page page_data['position'] = 'first-child' page_data['target'] = root_page.id page_data['slug'] = 'child-1' response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 302) c1 = Content.objects.get_content_slug_by_slug('child-1').page root_page = Content.objects.get_content_slug_by_slug('root').page self.assertEqual(len(root_page.valid_targets()), 0) self.assertEqual(str(c1.valid_targets()), "[<Page: root>]") def test_25_page_admin_view(self): """Test page admin view""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'page-1' response = c.post('/admin/pages/page/add/', page_data) page = Content.objects.get_content_slug_by_slug('page-1').page self.assertEqual(page.status, 1) response = c.post('/admin/pages/page/%d/change-status/' % page.id, {'status':Page.DRAFT}) page = Content.objects.get_content_slug_by_slug('page-1').page self.assertEqual(page.status, Page.DRAFT) url = '/admin/pages/page/%d/modify-content/title/en-us/' % page.id response = c.post(url, {'content': 'test content'}) self.assertEqual(page.title(), 'test content') # TODO: realy test these methods url = '/admin/pages/page/%d/traduction/en-us/' % page.id response = c.get(url) self.assertEqual(response.status_code, 200) url = '/admin/pages/page/%d/sub-menu/' % page.id response = c.get(url) self.assertEqual(response.status_code, 200) url = '/admin/pages/page/%d/get-content/1/' % page.id response = c.get(url) self.assertEqual(response.status_code, 200) def test_26_page_alias(self): """Test page aliasing system""" c = Client() c.login(username= 'batiste', password='b') # create some pages page_data = self.get_new_page_data() page_data['title'] = 'home-page-title' page_data['slug'] = 'home-page' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page_data['title'] = 'downloads-page-title' page_data['slug'] = 'downloads-page' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') # create aliases for the pages page = Page.objects.from_path('home-page', None) self.assertTrue(page) p = PageAlias(page=page, url='/index.php') p.save() page = Page.objects.from_path('downloads-page', None) self.assertTrue(page) p = PageAlias(page=page, url='index.php?page=downloads') p.save() # now check whether we can retrieve the pages. # is the homepage available from is alias response = c.get('/pages/index.php') self.assertRedirects(response, '/pages/home-page', 301) # for the download page, the slug is canonical response = c.get('/pages/downloads-page/') self.assertContains(response, "downloads-page-title", 2) # calling via its alias must cause redirect response = c.get('/pages/index.php?page=downloads') self.assertRedirects(response, '/pages/downloads-page', 301) def test_27_page_redirect_to(self): """Test page redirected to an other page.""" client = Client() client.login(username= 'batiste', password='b') # create some pages page1 = self.create_new_page(client) page2 = self.create_new_page(client) page1.redirect_to = page2 page1.save() # now check whether you go to the target page. response = client.get(page1.get_absolute_url()) self.assertRedirects(response, page2.get_absolute_url(), 301) def test_28_page_redirect_to_url(self): """Test page redirected to external url.""" client = Client() client.login(username= 'batiste', password='b') page1 = self.create_new_page(client) url = 'http://code.google.com/p/django-page-cms/' page1.redirect_to_url = url page1.save() # now check whether we can retrieve the page. response = client.get(page1.get_absolute_url()) self.assertTrue(response.status_code == 301) self.assertTrue(response['Location'] == url)

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94

0.611551

"""Django page CMS test suite module""" import django from django.conf import settings from django.test.client import Client from django.template import Template, RequestContext, TemplateDoesNotExist from django.http import HttpResponse, HttpResponseRedirect from django.shortcuts import render_to_response from pages.models import Page, Content, PageAlias from pages.tests.testcase import TestCase class PagesTestCase(TestCase): """Django page CMS test suite class""" def test_01_add_page(self): """Test that the add admin page could be displayed via the admin""" c = Client() c.login(username= 'batiste', password='b') response = c.get('/admin/pages/page/add/') self.assertEqual(response.status_code, 200) def test_02_create_page(self): """Test that a page can be created via the admin.""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') slug_content = Content.objects.get_content_slug_by_slug( page_data['slug'] ) assert(slug_content is not None) page = slug_content.page self.assertEqual(page.title(), page_data['title']) self.assertEqual(page.slug(), page_data['slug']) self.assertNotEqual(page.last_modification_date, None) def test_03_slug_collision(self): """Test a slug collision.""" setattr(settings, "PAGE_UNIQUE_SLUG_REQUIRED", True) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') setattr(settings, "PAGE_UNIQUE_SLUG_REQUIRED", False) response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) page1 = Content.objects.get_content_slug_by_slug(page_data['slug']).page page_data['position'] = 'first-child' page_data['target'] = page1.id response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page2 = Content.objects.get_content_slug_by_slug(page_data['slug']).page self.assertNotEqual(page1.id, page2.id) def test_04_details_view(self): """Test the details view""" c = Client() c.login(username= 'batiste', password='b') try: response = c.get('/pages/') except TemplateDoesNotExist, e: if e.args != ('404.html',): raise page_data = self.get_new_page_data() page_data['status'] = Page.DRAFT response = c.post('/admin/pages/page/add/', page_data) try: response = c.get('/pages/') except TemplateDoesNotExist, e: if e.args != ('404.html',): raise page_data = self.get_new_page_data() page_data['status'] = Page.PUBLISHED page_data['slug'] = 'test-page-2' page_data['template'] = 'pages/index.html' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') response = c.get('/pages/test-page-2/') self.assertEqual(response.status_code, 200) def test_05_edit_page(self): """Test that a page can edited via the admin""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page = Page.objects.all()[0] response = c.get('/admin/pages/page/%d/' % page.id) self.assertEqual(response.status_code, 200) page_data['title'] = 'changed title' page_data['body'] = 'changed body' response = c.post('/admin/pages/page/%d/' % page.id, page_data) self.assertRedirects(response, '/admin/pages/page/') page = Page.objects.get(id=page.id) self.assertEqual(page.title(), 'changed title') body = Content.objects.get_content(page, 'en-us', 'body') self.assertEqual(body, 'changed body') def test_06_site_framework(self): """Test the site framework, and test if it's possible to disable it""" # this is necessary to make the test pass from pages import settings as pages_settings setattr(pages_settings, "SITE_ID", 2) setattr(pages_settings, "PAGE_USE_SITE_ID", True) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data["sites"] = [2] response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page = Content.objects.get_content_slug_by_slug(page_data['slug']).page self.assertEqual(page.sites.count(), 1) self.assertEqual(page.sites.all()[0].id, 2) page_data = self.get_new_page_data() page_data["sites"] = [3] response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') # we cannot get a slug that doesn't exist content = Content.objects.get_content_slug_by_slug("this doesn't exist") self.assertEqual(content, None) # we cannot get the data posted on another site content = Content.objects.get_content_slug_by_slug(page_data['slug']) self.assertEqual(content, None) setattr(pages_settings, "SITE_ID", 3) page = Content.objects.get_content_slug_by_slug(page_data['slug']).page self.assertEqual(page.sites.count(), 1) self.assertEqual(page.sites.all()[0].id, 3) # with param self.assertEqual(Page.objects.on_site(2).count(), 1) self.assertEqual(Page.objects.on_site(3).count(), 1) # without param self.assertEqual(Page.objects.on_site().count(), 1) setattr(pages_settings, "SITE_ID", 2) self.assertEqual(Page.objects.on_site().count(), 1) page_data = self.get_new_page_data() page_data["sites"] = [2, 3] response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') self.assertEqual(Page.objects.on_site(3).count(), 2) self.assertEqual(Page.objects.on_site(2).count(), 2) self.assertEqual(Page.objects.on_site().count(), 2) setattr(pages_settings, "PAGE_USE_SITE_ID", False) # we should get everything self.assertEqual(Page.objects.on_site().count(), 3) def test_07_languages(self): """Test post a page with different languages and test that the admin views works correctly.""" c = Client() user = c.login(username= 'batiste', password='b') # test that the client language setting is used in add page admin c.cookies["django_language"] = 'de' response = c.get('/admin/pages/page/add/') self.assertContains(response, 'value="de" selected="selected"') c.cookies["django_language"] = 'fr-ch' response = c.get('/admin/pages/page/add/') self.assertContains(response, 'value="fr-ch" selected="selected"') page_data = self.get_new_page_data() page_data["title"] = 'english title' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page = Page.objects.all()[0] self.assertEqual(page.get_languages(), ['en-us']) # this test only works in version superior of 1.0.2 django_version = django.get_version().rsplit()[0].split('.') if len(django_version) > 2: major, middle, minor = [int(v) for v in django_version] else: major, middle = [int(v) for v in django_version] if major >= 1 and middle > 0: response = c.get('/admin/pages/page/%d/?language=de' % page.id) self.assertContains(response, 'value="de" selected="selected"') # add a french version of the same page page_data["language"] = 'fr-ch' page_data["title"] = 'french title' response = c.post('/admin/pages/page/%d/' % page.id, page_data) self.assertRedirects(response, '/admin/pages/page/') #setattr(settings, "PAGE_DEFAULT_LANGUAGE", 'en-us') # test that the frontend view use the good parameters # I cannot find a way of setting the accept-language HTTP # header so I used django_language cookie instead c = Client() c.cookies["django_language"] = 'en-us' response = c.get('/pages/') self.assertContains(response, 'english title') self.assertContains(response, 'lang="en-us"') self.assertNotContains(response, 'french title') c = Client() c.cookies["django_language"] = 'fr-ch' response = c.get('/pages/') self.assertContains(response, 'french title') self.assertContains(response, 'lang="fr-ch"') self.assertNotContains(response, 'english title') # this should be mapped to the fr-ch content c = Client() c.cookies["django_language"] = 'fr-fr' response = c.get('/pages/') self.assertContains(response, 'french title') self.assertContains(response, 'lang="fr-ch"') def test_08_revision(self): """Test that a page can edited several times.""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) page = Page.objects.all()[0] page_data['body'] = 'changed body' response = c.post('/admin/pages/page/%d/' % page.id, page_data) self.assertEqual(Content.objects.get_content(page, 'en-us', 'body'), 'changed body') page_data['body'] = 'changed body 2' response = c.post('/admin/pages/page/%d/' % page.id, page_data) self.assertEqual(Content.objects.get_content(page, 'en-us', 'body'), 'changed body 2') response = c.get('/pages/') self.assertContains(response, 'changed body 2', 1) setattr(settings, "PAGE_CONTENT_REVISION", False) self.assertEqual(Content.objects.get_content(page, 'en-us', 'body'), 'changed body 2') def test_09_placeholder(self): """ Test that the placeholder is correctly displayed in the admin """ setattr(settings, "SITE_ID", 2) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['template'] = 'pages/nice.html' response = c.post('/admin/pages/page/add/', page_data) page = Page.objects.all()[0] response = c.get('/admin/pages/page/%d/' % page.id) self.assertEqual(response.status_code, 200) self.assertContains(response, 'name="right-column"', 1) def test_10_directory_slug(self): """ Test diretory slugs """ setattr(settings, "PAGE_UNIQUE_SLUG_REQUIRED", False) c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['title'] = 'parent title' page_data['slug'] = 'same-slug' response = c.post('/admin/pages/page/add/', page_data) # the redirect tell that the page has been create correctly self.assertRedirects(response, '/admin/pages/page/') response = c.get('/pages/same-slug/') self.assertEqual(response.status_code, 200) page = Page.objects.all()[0] response = c.post('/admin/pages/page/add/', page_data) # we cannot create 2 root page with the same slug # this assert test that the creation fails as wanted self.assertEqual(response.status_code, 200) page1 = Content.objects.get_content_slug_by_slug(page_data['slug']).page self.assertEqual(page1.id, page.id) page_data['title'] = 'children title' page_data['target'] = page1.id page_data['position'] = 'first-child' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') # finaly test that we can get every page according the path response = c.get('/pages/same-slug') self.assertContains(response, "parent title", 2) response = c.get('/pages/same-slug/same-slug') self.assertContains(response, "children title", 2) def test_11_show_content_tag(self): """ Test the {% show_content %} template tag """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) page = Page.objects.all()[0] class request: REQUEST = {'language': 'en'} GET = {} context = RequestContext(request, {'page': page, 'lang':'en-us', 'path':'/page-1/'}) template = Template('{% load pages_tags %}' '{% show_content page "title" "en-us" %}') self.assertEqual(template.render(context), page_data['title']) template = Template('{% load pages_tags %}' '{% show_content page "title" %}') self.assertEqual(template.render(context), page_data['title']) def test_12_get_content_tag(self): """ Test the {% get_content %} template tag """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() response = c.post('/admin/pages/page/add/', page_data) page = Page.objects.all()[0] class request: REQUEST = {'language': 'en'} GET = {} context = RequestContext(request, {'page': page}) template = Template('{% load pages_tags %}' '{% get_content page "title" "en-us" as content %}' '{{ content }}') self.assertEqual(template.render(context), page_data['title']) template = Template('{% load pages_tags %}' '{% get_content page "title" as content %}' '{{ content }}') self.assertEqual(template.render(context), page_data['title']) def test_17_request_mockup(self): from pages.utils import get_request_mock request = get_request_mock() self.assertEqual(hasattr(request, 'session'), True) def test_18_tree_admin_interface(self): """ Test that moving/creating page in the tree is working properly using the admin interface """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'root' response = c.post('/admin/pages/page/add/', page_data) root_page = Content.objects.get_content_slug_by_slug('root').page self.assertTrue(root_page.is_first_root()) page_data['position'] = 'first-child' page_data['target'] = root_page.id page_data['slug'] = 'child-1' response = c.post('/admin/pages/page/add/', page_data) child_1 = Content.objects.get_content_slug_by_slug('child-1').page self.assertFalse(child_1.is_first_root()) page_data['slug'] = 'child-2' response = c.post('/admin/pages/page/add/', page_data) child_2 = Content.objects.get_content_slug_by_slug('child-2').page self.assertEqual(str(Page.objects.all()), "[<Page: root>, <Page: child-2>, <Page: child-1>]") # move page 1 in the first position response = c.post('/admin/pages/page/%d/move-page/' % child_1.id, {'position':'first-child', 'target':root_page.id}) self.assertEqual(str(Page.objects.all()), "[<Page: root>, <Page: child-1>, <Page: child-2>]") # move page 2 in the first position response = c.post('/admin/pages/page/%d/move-page/' % child_2.id, {'position': 'left', 'target': child_1.id}) self.assertEqual(str(Page.objects.all()), "[<Page: root>, <Page: child-2>, <Page: child-1>]") # try to create a sibling with the same slug, via left, right from pages import settings as pages_settings setattr(pages_settings, "PAGE_UNIQUE_SLUG_REQUIRED", False) page_data['target'] = child_2.id page_data['position'] = 'left' response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) # try to create a sibling with the same slug, via first-child page_data['target'] = root_page.id page_data['position'] = 'first-child' response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) # try to create a second page 2 in root del page_data['target'] del page_data['position'] setattr(pages_settings, "PAGE_UNIQUE_SLUG_REQUIRED", True) # cannot create because slug exists response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) # Now it should work beause the page is not a sibling setattr(pages_settings, "PAGE_UNIQUE_SLUG_REQUIRED", False) response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 302) self.assertEqual(Page.objects.count(), 4) # Should not work because we already have sibling at the same level response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 200) # try to change the page 2 slug into page 1 page_data['slug'] = 'child-1' response = c.post('/admin/pages/page/%d/' % child_2.id, page_data) self.assertEqual(response.status_code, 200) setattr(pages_settings, "PAGE_UNIQUE_SLUG_REQUIRED", True) response = c.post('/admin/pages/page/%d/' % child_2.id, page_data) self.assertEqual(response.status_code, 200) def test_19_tree(self): """ Test that the navigation tree works properly with mptt """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'page1' response = c.post('/admin/pages/page/add/', page_data) page_data['slug'] = 'page2' response = c.post('/admin/pages/page/add/', page_data) page_data['slug'] = 'page3' response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(str(Page.objects.navigation()), "[<Page: page1>, <Page: page2>, <Page: page3>]") p1 = Content.objects.get_content_slug_by_slug('page1').page p2 = Content.objects.get_content_slug_by_slug('page2').page p3 = Content.objects.get_content_slug_by_slug('page3').page p2.move_to(p1, 'left') p2.save() self.assertEqual(str(Page.objects.navigation()), "[<Page: page2>, <Page: page1>, <Page: page3>]") p3.move_to(p2, 'left') p3.save() self.assertEqual(str(Page.objects.navigation()), "[<Page: page3>, <Page: page2>, <Page: page1>]") p1 = Content.objects.get_content_slug_by_slug('page1').page p2 = Content.objects.get_content_slug_by_slug('page2').page p3 = Content.objects.get_content_slug_by_slug('page3').page p3.move_to(p1, 'first-child') p2.move_to(p1, 'first-child') self.assertEqual(str(Page.objects.navigation()), "[<Page: page1>]") p3 = Content.objects.get_content_slug_by_slug('page3').page p3.move_to(p1, 'left') self.assertEqual(str(Page.objects.navigation()), "[<Page: page3>, <Page: page1>]") def test_20_ajax_language(self): """Test that language is working properly""" c = Client() c.login(username= 'batiste', password='b') # Activate a language other than settings.LANGUAGE_CODE response = c.post('/i18n/setlang/', {'language':'fr-ch' }) self.assertEqual(c.session.get('django_language', False), 'fr-ch') # Make sure we're in french response = c.get('/admin/pages/page/') self.assertEqual(response.status_code, 200) self.assertTrue('Auteur' in response.content) page_data = self.get_new_page_data() page_data['slug'] = 'root' response = c.post('/admin/pages/page/add/', page_data) root_page = Content.objects.get_content_slug_by_slug('root').page page_data['position'] = 'first-child' page_data['target'] = root_page.id page_data['slug'] = 'child-1' response = c.post('/admin/pages/page/add/', page_data) child_1 = Content.objects.get_content_slug_by_slug('child-1').page page_data['slug'] = 'child-2' response = c.post('/admin/pages/page/add/', page_data) child_2 = Content.objects.get_content_slug_by_slug('child-2').page self.assertEqual(str(Page.objects.all()), "[<Page: root>, <Page: child-2>, <Page: child-1>]") """ The relevant bit, fixed by rev 501: the response issued by a move command returns content localized in settings.LANGUAGE_CODE (i.e. 'en´) even though the original AJAX request passed in a the correct session ID localizing this client as fr-ch This is probably because the LocaleMiddleware gets instantiated with a couple request_mocks which have no real connection to the AJAX request *but* django.utils.translation caches the active language on a per thread basis. This means that the first "bogus" call to LocaleMiddleware.process_request will "kill" the localization data for the AJAX request. Rev. 501 fixes this by passing in the language code from the original request. """ response = c.post('/admin/pages/page/%d/move-page/' % child_1.id, {'position':'first-child', 'target':root_page.id}) # Make sure the content response we got was in french self.assertTrue('Auteur' in response.content) def test_21_view_context(self): """ Test that the default view can only return the context """ c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'page1' # create a page for the example otherwise you will get a Http404 error response = c.post('/admin/pages/page/add/', page_data) page1 = Content.objects.get_content_slug_by_slug('page1').page from pages.views import details from pages.utils import get_request_mock request = get_request_mock() context = details(request, only_context=True) self.assertEqual(context['current_page'], page1) def test_24_page_valid_targets(self): """Test page valid_targets method""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'root' response = c.post('/admin/pages/page/add/', page_data) root_page = Content.objects.get_content_slug_by_slug('root').page page_data['position'] = 'first-child' page_data['target'] = root_page.id page_data['slug'] = 'child-1' response = c.post('/admin/pages/page/add/', page_data) self.assertEqual(response.status_code, 302) c1 = Content.objects.get_content_slug_by_slug('child-1').page root_page = Content.objects.get_content_slug_by_slug('root').page self.assertEqual(len(root_page.valid_targets()), 0) self.assertEqual(str(c1.valid_targets()), "[<Page: root>]") def test_25_page_admin_view(self): """Test page admin view""" c = Client() c.login(username= 'batiste', password='b') page_data = self.get_new_page_data() page_data['slug'] = 'page-1' response = c.post('/admin/pages/page/add/', page_data) page = Content.objects.get_content_slug_by_slug('page-1').page self.assertEqual(page.status, 1) response = c.post('/admin/pages/page/%d/change-status/' % page.id, {'status':Page.DRAFT}) page = Content.objects.get_content_slug_by_slug('page-1').page self.assertEqual(page.status, Page.DRAFT) url = '/admin/pages/page/%d/modify-content/title/en-us/' % page.id response = c.post(url, {'content': 'test content'}) self.assertEqual(page.title(), 'test content') # TODO: realy test these methods url = '/admin/pages/page/%d/traduction/en-us/' % page.id response = c.get(url) self.assertEqual(response.status_code, 200) url = '/admin/pages/page/%d/sub-menu/' % page.id response = c.get(url) self.assertEqual(response.status_code, 200) url = '/admin/pages/page/%d/get-content/1/' % page.id response = c.get(url) self.assertEqual(response.status_code, 200) def test_26_page_alias(self): """Test page aliasing system""" c = Client() c.login(username= 'batiste', password='b') # create some pages page_data = self.get_new_page_data() page_data['title'] = 'home-page-title' page_data['slug'] = 'home-page' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') page_data['title'] = 'downloads-page-title' page_data['slug'] = 'downloads-page' response = c.post('/admin/pages/page/add/', page_data) self.assertRedirects(response, '/admin/pages/page/') # create aliases for the pages page = Page.objects.from_path('home-page', None) self.assertTrue(page) p = PageAlias(page=page, url='/index.php') p.save() page = Page.objects.from_path('downloads-page', None) self.assertTrue(page) p = PageAlias(page=page, url='index.php?page=downloads') p.save() # now check whether we can retrieve the pages. # is the homepage available from is alias response = c.get('/pages/index.php') self.assertRedirects(response, '/pages/home-page', 301) # for the download page, the slug is canonical response = c.get('/pages/downloads-page/') self.assertContains(response, "downloads-page-title", 2) # calling via its alias must cause redirect response = c.get('/pages/index.php?page=downloads') self.assertRedirects(response, '/pages/downloads-page', 301) def test_27_page_redirect_to(self): """Test page redirected to an other page.""" client = Client() client.login(username= 'batiste', password='b') # create some pages page1 = self.create_new_page(client) page2 = self.create_new_page(client) page1.redirect_to = page2 page1.save() # now check whether you go to the target page. response = client.get(page1.get_absolute_url()) self.assertRedirects(response, page2.get_absolute_url(), 301) def test_28_page_redirect_to_url(self): """Test page redirected to external url.""" client = Client() client.login(username= 'batiste', password='b') page1 = self.create_new_page(client) url = 'http://code.google.com/p/django-page-cms/' page1.redirect_to_url = url page1.save() # now check whether we can retrieve the page. response = client.get(page1.get_absolute_url()) self.assertTrue(response.status_code == 301) self.assertTrue(response['Location'] == url)

false

true

f718a9f8275917290bfff9a6aebebcef23211c45

1,313

py

Python

systems/chordpy/demo.py

DistributedComponents/verdi-chord

762fe660c648d7f2a009d2beaa5cf3b8ea4ac593

[ "BSD-2-Clause" ]

12

2016-11-22T19:33:39.000Z

2020-04-14T13:00:27.000Z

systems/chordpy/demo.py

DistributedComponents/verdi-chord

762fe660c648d7f2a009d2beaa5cf3b8ea4ac593

[ "BSD-2-Clause" ]

17

2016-11-22T07:01:08.000Z

2018-11-23T19:59:50.000Z

systems/chordpy/demo.py

DistributedComponents/verdi-chord

762fe660c648d7f2a009d2beaa5cf3b8ea4ac593

[ "BSD-2-Clause" ]

1

2017-07-31T23:10:31.000Z

import logging import multiprocessing import sys import time from data import Pointer, SUCC_LIST_LEN from node import Node def launch_node(ip, pred, succ_list): node = Node(ip=ip, pred=pred, succ_list=succ_list) p = multiprocessing.Process(target=node.start) p.daemon = True p.start() return node, p def launch_ring_of(n): ptrs = sorted([Pointer(ip="127.0.0.{}".format(i)) for i in range(1, n+1)]) nodes = [] procs = [] for i, p in enumerate(ptrs): succs = ptrs[i+1:i+1+SUCC_LIST_LEN] if len(succs) < SUCC_LIST_LEN: succs += ptrs[:SUCC_LIST_LEN-len(succs)] node, proc = launch_node(p.ip, ptrs[i - 1], succs) nodes.append(node) procs.append(proc) return nodes, procs def kill_demo(): logging.debug("running kill_demo()") nodes, procs = launch_ring_of(40) time.sleep(2) for kill_idx in [3, 5, 12]: logging.warn("killing node {}".format(nodes[kill_idx].state.ptr.id)) procs[kill_idx].terminate() known = nodes[0].state.ptr new_node = Node("127.0.0.100") time.sleep(0.5) print "adding new node:", new_node.state.ptr new_node.start(known) procs[0].join() if __name__ == "__main__": logging.basicConfig(level=logging.DEBUG, stream=sys.stdout) kill_demo()

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78

0.642803

import logging import multiprocessing import sys import time from data import Pointer, SUCC_LIST_LEN from node import Node def launch_node(ip, pred, succ_list): node = Node(ip=ip, pred=pred, succ_list=succ_list) p = multiprocessing.Process(target=node.start) p.daemon = True p.start() return node, p def launch_ring_of(n): ptrs = sorted([Pointer(ip="127.0.0.{}".format(i)) for i in range(1, n+1)]) nodes = [] procs = [] for i, p in enumerate(ptrs): succs = ptrs[i+1:i+1+SUCC_LIST_LEN] if len(succs) < SUCC_LIST_LEN: succs += ptrs[:SUCC_LIST_LEN-len(succs)] node, proc = launch_node(p.ip, ptrs[i - 1], succs) nodes.append(node) procs.append(proc) return nodes, procs def kill_demo(): logging.debug("running kill_demo()") nodes, procs = launch_ring_of(40) time.sleep(2) for kill_idx in [3, 5, 12]: logging.warn("killing node {}".format(nodes[kill_idx].state.ptr.id)) procs[kill_idx].terminate() known = nodes[0].state.ptr new_node = Node("127.0.0.100") time.sleep(0.5) print "adding new node:", new_node.state.ptr new_node.start(known) procs[0].join() if __name__ == "__main__": logging.basicConfig(level=logging.DEBUG, stream=sys.stdout) kill_demo()

false

true

f718aa985e504d915baf7c952316a24a64b1820b

5,825

py

Python

tests/test_nnet.py

kgizdov/hep_ml

114ac9e896c3a601761092760a7b315f448d59c6

[ "Apache-2.0" ]

null

tests/test_nnet.py

kgizdov/hep_ml

114ac9e896c3a601761092760a7b315f448d59c6

[ "Apache-2.0" ]

null

tests/test_nnet.py

kgizdov/hep_ml

114ac9e896c3a601761092760a7b315f448d59c6

[ "Apache-2.0" ]

1

2020-11-11T08:39:52.000Z

from __future__ import division, print_function import numpy from sklearn.linear_model.logistic import LogisticRegression from sklearn.metrics import roc_auc_score, mean_squared_error, log_loss from sklearn.base import clone from sklearn.datasets import make_blobs from hep_ml import nnet from hep_ml.commonutils import generate_sample from hep_ml.nnet import MLPRegressor from hep_ml.preprocessing import BinTransformer, IronTransformer __author__ = 'Alex Rogozhnikov' nn_types = [ nnet.SimpleNeuralNetwork, nnet.MLPClassifier, nnet.SoftmaxNeuralNetwork, nnet.RBFNeuralNetwork, nnet.PairwiseNeuralNetwork, nnet.PairwiseSoftplusNeuralNetwork, ] # TODO test pipelines, bagging and boosting def check_single_classification_network(neural_network, n_samples=200, n_features=7, distance=0.8, retry_attempts=3): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) # each combination is tried 3 times. before raising exception for retry_attempt in range(retry_attempts): # to initial state neural_network = clone(neural_network) neural_network.set_params(random_state=42 + retry_attempt) print(neural_network) neural_network.fit(X, y) quality = roc_auc_score(y, neural_network.predict_proba(X)[:, 1]) # checking that computations don't fail computed_loss = neural_network.compute_loss(X, y, sample_weight=y * 0 + 1) if quality > 0.8: break else: print('attempt {} : {}'.format(retry_attempt, quality)) if retry_attempt == retry_attempts - 1: raise RuntimeError('quality of model is too low: {} {}'.format(quality, neural_network)) def test_classification_nnets(): """ checking combinations of losses, nn_types, trainers, most of them are used once during tests. """ attempts = max(len(nnet.losses), len(nnet.trainers), len(nn_types)) losses_shift = numpy.random.randint(10) trainers_shift = numpy.random.randint(10) for combination in range(attempts): loss = list(nnet.losses.keys())[(combination + losses_shift) % len(nnet.losses)] trainer = list(nnet.trainers.keys())[(combination + trainers_shift) % len(nnet.trainers)] nn_type = nn_types[combination % len(nn_types)] neural_network = nn_type(layers=[5], loss=loss, trainer=trainer, epochs=200) yield check_single_classification_network, neural_network def test_regression_nnets(): from sklearn.datasets import make_regression X, y = make_regression(n_samples=300, n_features=20, n_informative=10, bias=5) print(y[:20]) original_mse = mean_squared_error(y, y * 0 + y.mean()) for loss in ['mse_loss', 'smooth_huber_loss']: reg = MLPRegressor(layers=(5,), loss=loss) reg.fit(X, y) p = reg.predict(X) print(numpy.sort(abs(p))[-10:]) mse = mean_squared_error(y, p) assert mse < original_mse * 0.3 # fitting a constant y[:] = 100. for loss in ['mse_loss', 'smooth_huber_loss']: reg = MLPRegressor(layers=(1,), loss=loss, epochs=300) reg.fit(X, y) print(mean_squared_error(y, reg.predict(X))) assert mean_squared_error(y, reg.predict(X)) < 5., "doesn't fit constant" def compare_nnets_quality(n_samples=200, n_features=7, distance=0.8): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) # checking all possible combinations for loss in ['log_loss']: # nnet.losses: for NNType in nn_types: for trainer in nnet.trainers: nn = NNType(layers=[5], loss=loss, trainer=trainer, epochs=100, random_state=42) nn.fit(X, y) print(roc_auc_score(y, nn.predict_proba(X)[:, 1]), nn) lr = LogisticRegression().fit(X, y) print(roc_auc_score(y, lr.predict_proba(X)[:, 1]), lr) def test_network_with_scaler(n_samples=200, n_features=15, distance=0.5): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) for scaler in [BinTransformer(max_bins=16), IronTransformer()]: clf = nnet.SimpleNeuralNetwork(scaler=scaler, epochs=300) clf.fit(X, y) p = clf.predict_proba(X) assert roc_auc_score(y, p[:, 1]) > 0.8, 'quality is too low for model: {}'.format(clf) def test_adaptive_methods(n_samples=200, n_features=15, distance=0.5): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) for trainer in ['sgd', 'adadelta']: clf = nnet.SimpleNeuralNetwork(trainer=trainer, trainer_parameters={'batch': 1}) clf.fit(X, y) assert roc_auc_score(y, clf.predict_proba(X)[:, 1]) > 0.8, 'quality is too low for model: {}'.format(clf) def test_reproducibility(n_samples=200, n_features=15, distance=0.5): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) for trainer in nnet.trainers.keys(): clf1 = nnet.MLPClassifier(trainer=trainer, random_state=42).fit(X, y) clf2 = nnet.MLPClassifier(trainer=trainer, random_state=42).fit(X, y) assert numpy.allclose(clf1.predict_proba(X), clf2.predict_proba(X)) def test_multiclassification(n_samples=200, n_features=10): for n_classes in [2, 3, 4]: X, y = make_blobs(n_samples=n_samples, centers=n_classes, n_features=n_features) losses = [] for n_epochs in [1, 10, 100]: clf = nnet.MLPMultiClassifier(epochs=n_epochs).fit(X, y) loss1 = log_loss(y, clf.predict_proba(X)) loss2 = clf.compute_loss(X, y) assert numpy.allclose(loss1, loss2), 'computed losses are different' losses.append(loss1) assert losses[0] > losses[-1], 'loss is not decreasing'

41.607143

117

0.687725

from __future__ import division, print_function import numpy from sklearn.linear_model.logistic import LogisticRegression from sklearn.metrics import roc_auc_score, mean_squared_error, log_loss from sklearn.base import clone from sklearn.datasets import make_blobs from hep_ml import nnet from hep_ml.commonutils import generate_sample from hep_ml.nnet import MLPRegressor from hep_ml.preprocessing import BinTransformer, IronTransformer __author__ = 'Alex Rogozhnikov' nn_types = [ nnet.SimpleNeuralNetwork, nnet.MLPClassifier, nnet.SoftmaxNeuralNetwork, nnet.RBFNeuralNetwork, nnet.PairwiseNeuralNetwork, nnet.PairwiseSoftplusNeuralNetwork, ] def check_single_classification_network(neural_network, n_samples=200, n_features=7, distance=0.8, retry_attempts=3): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) for retry_attempt in range(retry_attempts): neural_network = clone(neural_network) neural_network.set_params(random_state=42 + retry_attempt) print(neural_network) neural_network.fit(X, y) quality = roc_auc_score(y, neural_network.predict_proba(X)[:, 1]) computed_loss = neural_network.compute_loss(X, y, sample_weight=y * 0 + 1) if quality > 0.8: break else: print('attempt {} : {}'.format(retry_attempt, quality)) if retry_attempt == retry_attempts - 1: raise RuntimeError('quality of model is too low: {} {}'.format(quality, neural_network)) def test_classification_nnets(): attempts = max(len(nnet.losses), len(nnet.trainers), len(nn_types)) losses_shift = numpy.random.randint(10) trainers_shift = numpy.random.randint(10) for combination in range(attempts): loss = list(nnet.losses.keys())[(combination + losses_shift) % len(nnet.losses)] trainer = list(nnet.trainers.keys())[(combination + trainers_shift) % len(nnet.trainers)] nn_type = nn_types[combination % len(nn_types)] neural_network = nn_type(layers=[5], loss=loss, trainer=trainer, epochs=200) yield check_single_classification_network, neural_network def test_regression_nnets(): from sklearn.datasets import make_regression X, y = make_regression(n_samples=300, n_features=20, n_informative=10, bias=5) print(y[:20]) original_mse = mean_squared_error(y, y * 0 + y.mean()) for loss in ['mse_loss', 'smooth_huber_loss']: reg = MLPRegressor(layers=(5,), loss=loss) reg.fit(X, y) p = reg.predict(X) print(numpy.sort(abs(p))[-10:]) mse = mean_squared_error(y, p) assert mse < original_mse * 0.3 # fitting a constant y[:] = 100. for loss in ['mse_loss', 'smooth_huber_loss']: reg = MLPRegressor(layers=(1,), loss=loss, epochs=300) reg.fit(X, y) print(mean_squared_error(y, reg.predict(X))) assert mean_squared_error(y, reg.predict(X)) < 5., "doesn't fit constant" def compare_nnets_quality(n_samples=200, n_features=7, distance=0.8): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) for loss in ['log_loss']: for NNType in nn_types: for trainer in nnet.trainers: nn = NNType(layers=[5], loss=loss, trainer=trainer, epochs=100, random_state=42) nn.fit(X, y) print(roc_auc_score(y, nn.predict_proba(X)[:, 1]), nn) lr = LogisticRegression().fit(X, y) print(roc_auc_score(y, lr.predict_proba(X)[:, 1]), lr) def test_network_with_scaler(n_samples=200, n_features=15, distance=0.5): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) for scaler in [BinTransformer(max_bins=16), IronTransformer()]: clf = nnet.SimpleNeuralNetwork(scaler=scaler, epochs=300) clf.fit(X, y) p = clf.predict_proba(X) assert roc_auc_score(y, p[:, 1]) > 0.8, 'quality is too low for model: {}'.format(clf) def test_adaptive_methods(n_samples=200, n_features=15, distance=0.5): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) for trainer in ['sgd', 'adadelta']: clf = nnet.SimpleNeuralNetwork(trainer=trainer, trainer_parameters={'batch': 1}) clf.fit(X, y) assert roc_auc_score(y, clf.predict_proba(X)[:, 1]) > 0.8, 'quality is too low for model: {}'.format(clf) def test_reproducibility(n_samples=200, n_features=15, distance=0.5): X, y = generate_sample(n_samples=n_samples, n_features=n_features, distance=distance) for trainer in nnet.trainers.keys(): clf1 = nnet.MLPClassifier(trainer=trainer, random_state=42).fit(X, y) clf2 = nnet.MLPClassifier(trainer=trainer, random_state=42).fit(X, y) assert numpy.allclose(clf1.predict_proba(X), clf2.predict_proba(X)) def test_multiclassification(n_samples=200, n_features=10): for n_classes in [2, 3, 4]: X, y = make_blobs(n_samples=n_samples, centers=n_classes, n_features=n_features) losses = [] for n_epochs in [1, 10, 100]: clf = nnet.MLPMultiClassifier(epochs=n_epochs).fit(X, y) loss1 = log_loss(y, clf.predict_proba(X)) loss2 = clf.compute_loss(X, y) assert numpy.allclose(loss1, loss2), 'computed losses are different' losses.append(loss1) assert losses[0] > losses[-1], 'loss is not decreasing'

true

f718ab3528673e47153b5a348e4c10a0b0f010a8

780

py

Python

setup.py

metabolize/harrison

0d0f26fda1947785ee7a00a8a7bf5b6a95e06372

[ "BSD-2-Clause" ]

4

2019-10-02T03:23:04.000Z

2021-01-26T04:25:06.000Z

setup.py

metabolize/harrison

0d0f26fda1947785ee7a00a8a7bf5b6a95e06372

[ "BSD-2-Clause" ]

31

2019-08-29T17:13:06.000Z

2021-06-25T15:25:18.000Z

setup.py

metabolize/harrison

0d0f26fda1947785ee7a00a8a7bf5b6a95e06372

[ "BSD-2-Clause" ]

1

2017-10-24T23:24:48.000Z

from setuptools import setup version_info = {} exec(open("harrison/package_version.py").read(), version_info) setup( name="harrison", version=version_info["__version__"], author="Body Labs, Metabolize", author_email="github@paulmelnikow.com", description="Time a block of code", long_description=open("README.md").read(), long_description_content_type="text/markdown", url="https://github.com/metabolize/harrison", license="MIT", packages=["harrison", "harrison/util"], classifiers=[ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python :: 3", ], )

31.2

62

0.661538

from setuptools import setup version_info = {} exec(open("harrison/package_version.py").read(), version_info) setup( name="harrison", version=version_info["__version__"], author="Body Labs, Metabolize", author_email="github@paulmelnikow.com", description="Time a block of code", long_description=open("README.md").read(), long_description_content_type="text/markdown", url="https://github.com/metabolize/harrison", license="MIT", packages=["harrison", "harrison/util"], classifiers=[ "Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved :: BSD License", "Operating System :: OS Independent", "Programming Language :: Python :: 3", ], )

true

f718abf37912a57ece457c7724017ea32c14fa31

8,330

py

Python

tests/symbol_dependent_transients_test.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

1

2022-03-11T13:36:34.000Z

tests/symbol_dependent_transients_test.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

null

tests/symbol_dependent_transients_test.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

null

# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved. import dace import numpy as np import pytest from dace.libraries import standard from dace.transformation import interstate def _make_sdfg(name, storage=dace.dtypes.StorageType.CPU_Heap, isview=False): N = dace.symbol('N', dtype=dace.int32, integer=True, positive=True) i = dace.symbol('i', dtype=dace.int32, integer=True) sdfg = dace.SDFG(name) _, A = sdfg.add_array('A', [N, N, N], dtype=dace.float64) _, B = sdfg.add_array('B', [N], dtype=dace.float64) if isview: _, tmp1 = sdfg.add_view('tmp1', [N - 4, N - 4, N - i], dtype=dace.float64, storage=storage, strides=A.strides) else: _, tmp1 = sdfg.add_transient('tmp1', [N - 4, N - 4, N - i], dtype=dace.float64, storage=storage) _, tmp2 = sdfg.add_transient('tmp2', [1], dtype=dace.float64, storage=storage) begin_state = sdfg.add_state("begin", is_start_state=True) guard_state = sdfg.add_state("guard") body1_state = sdfg.add_state("body1") body2_state = sdfg.add_state("body2") body3_state = sdfg.add_state("body3") end_state = sdfg.add_state("end") sdfg.add_edge(begin_state, guard_state, dace.InterstateEdge(assignments=dict(i='0'))) sdfg.add_edge(guard_state, body1_state, dace.InterstateEdge(condition=f'i<{N}')) sdfg.add_edge(guard_state, end_state, dace.InterstateEdge(condition=f'i>={N}')) sdfg.add_edge(body1_state, body2_state, dace.InterstateEdge()) sdfg.add_edge(body2_state, body3_state, dace.InterstateEdge()) sdfg.add_edge(body3_state, guard_state, dace.InterstateEdge(assignments=dict(i='i+1'))) if not isview: read_a = body1_state.add_read('A') write_tmp1 = body1_state.add_write('tmp1') body1_state.add_nedge(read_a, write_tmp1, dace.Memlet(f'A[2:{N}-2, 2:{N}-2, i:{N}]')) if isview: read_a = body2_state.add_read('A') read_tmp1 = body2_state.add_access('tmp1') body2_state.add_nedge(read_a, read_tmp1, dace.Memlet(f'A[2:{N}-2, 2:{N}-2, i:{N}]')) else: read_tmp1 = body2_state.add_read('tmp1') rednode = standard.Reduce(wcr='lambda a, b : a + b', identity=0) if storage == dace.dtypes.StorageType.GPU_Global: rednode.implementation = 'CUDA (device)' elif storage == dace.dtypes.StorageType.FPGA_Global: rednode.implementation = 'FPGAPartialReduction' body2_state.add_node(rednode) write_tmp2 = body2_state.add_write('tmp2') body2_state.add_nedge(read_tmp1, rednode, dace.Memlet.from_array('tmp1', tmp1)) body2_state.add_nedge(rednode, write_tmp2, dace.Memlet('tmp2[0]')) read_tmp2 = body3_state.add_read('tmp2') write_b = body3_state.add_write('B') body3_state.add_nedge(read_tmp2, write_b, dace.Memlet('B[i]')) return sdfg def test_symbol_dependent_heap_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_heap_array") # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) def test_symbol_dependent_register_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_register_array", storage=dace.dtypes.StorageType.Register) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) def test_symbol_dependent_threadlocal_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_threadlocal_array", storage=dace.dtypes.StorageType.CPU_ThreadLocal) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) def test_symbol_dependent_cpu_view(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_cpu_view", isview=True) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) @pytest.mark.gpu def test_symbol_dependent_gpu_global_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_gpu_global_array", storage=dace.dtypes.StorageType.GPU_Global) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) @pytest.mark.gpu def test_symbol_dependent_pinned_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_pinned_array", storage=dace.dtypes.StorageType.CPU_Pinned) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) @pytest.mark.skip # @pytest.mark.gpu def test_symbol_dependent_gpu_view(): # NOTE: This test cannot produce the correct result since the input # data of the reduction are not contiguous and cub:reduce doesn't support # such data. A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_gpu_view", storage=dace.dtypes.StorageType.GPU_Global, isview=True) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) @pytest.mark.skip def test_symbol_dependent_fpga_global_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_fpga_global_array", storage=dace.dtypes.StorageType.FPGA_Global) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) def test_symbol_dependent_array_in_map(): @dace.program def symbol_dependent_array_in_map(A: dace.float32[10]): out = np.ndarray(10, dtype=np.float32) for i in dace.map[0:10]: tmp = A[0:i + 1] out[i] = np.sum(tmp) return out # Compile manually to avoid simplification sdfg = symbol_dependent_array_in_map.to_sdfg(simplify=False) sdfg.apply_transformations_repeated(interstate.StateFusion) sdfg.apply_transformations_repeated(interstate.InlineSDFG) # NOTE: Temporary fix for issue with symbols/free_symbols if 'i' in sdfg.free_symbols: sdfg.remove_symbol('i') func = sdfg.compile() A = np.random.randn(10).astype(np.float32) val = func(A=A) ref = np.cumsum(A) assert (np.allclose(val, ref)) if __name__ == '__main__': test_symbol_dependent_heap_array() test_symbol_dependent_register_array() test_symbol_dependent_threadlocal_array() test_symbol_dependent_cpu_view() test_symbol_dependent_gpu_global_array() test_symbol_dependent_pinned_array() # test_symbol_dependent_gpu_view() # test_symbol_dependent_fpga_global_array() test_symbol_dependent_array_in_map()

37.022222

118

0.677431

import dace import numpy as np import pytest from dace.libraries import standard from dace.transformation import interstate def _make_sdfg(name, storage=dace.dtypes.StorageType.CPU_Heap, isview=False): N = dace.symbol('N', dtype=dace.int32, integer=True, positive=True) i = dace.symbol('i', dtype=dace.int32, integer=True) sdfg = dace.SDFG(name) _, A = sdfg.add_array('A', [N, N, N], dtype=dace.float64) _, B = sdfg.add_array('B', [N], dtype=dace.float64) if isview: _, tmp1 = sdfg.add_view('tmp1', [N - 4, N - 4, N - i], dtype=dace.float64, storage=storage, strides=A.strides) else: _, tmp1 = sdfg.add_transient('tmp1', [N - 4, N - 4, N - i], dtype=dace.float64, storage=storage) _, tmp2 = sdfg.add_transient('tmp2', [1], dtype=dace.float64, storage=storage) begin_state = sdfg.add_state("begin", is_start_state=True) guard_state = sdfg.add_state("guard") body1_state = sdfg.add_state("body1") body2_state = sdfg.add_state("body2") body3_state = sdfg.add_state("body3") end_state = sdfg.add_state("end") sdfg.add_edge(begin_state, guard_state, dace.InterstateEdge(assignments=dict(i='0'))) sdfg.add_edge(guard_state, body1_state, dace.InterstateEdge(condition=f'i<{N}')) sdfg.add_edge(guard_state, end_state, dace.InterstateEdge(condition=f'i>={N}')) sdfg.add_edge(body1_state, body2_state, dace.InterstateEdge()) sdfg.add_edge(body2_state, body3_state, dace.InterstateEdge()) sdfg.add_edge(body3_state, guard_state, dace.InterstateEdge(assignments=dict(i='i+1'))) if not isview: read_a = body1_state.add_read('A') write_tmp1 = body1_state.add_write('tmp1') body1_state.add_nedge(read_a, write_tmp1, dace.Memlet(f'A[2:{N}-2, 2:{N}-2, i:{N}]')) if isview: read_a = body2_state.add_read('A') read_tmp1 = body2_state.add_access('tmp1') body2_state.add_nedge(read_a, read_tmp1, dace.Memlet(f'A[2:{N}-2, 2:{N}-2, i:{N}]')) else: read_tmp1 = body2_state.add_read('tmp1') rednode = standard.Reduce(wcr='lambda a, b : a + b', identity=0) if storage == dace.dtypes.StorageType.GPU_Global: rednode.implementation = 'CUDA (device)' elif storage == dace.dtypes.StorageType.FPGA_Global: rednode.implementation = 'FPGAPartialReduction' body2_state.add_node(rednode) write_tmp2 = body2_state.add_write('tmp2') body2_state.add_nedge(read_tmp1, rednode, dace.Memlet.from_array('tmp1', tmp1)) body2_state.add_nedge(rednode, write_tmp2, dace.Memlet('tmp2[0]')) read_tmp2 = body3_state.add_read('tmp2') write_b = body3_state.add_write('B') body3_state.add_nedge(read_tmp2, write_b, dace.Memlet('B[i]')) return sdfg def test_symbol_dependent_heap_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_heap_array") sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) def test_symbol_dependent_register_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_register_array", storage=dace.dtypes.StorageType.Register) sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) def test_symbol_dependent_threadlocal_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_threadlocal_array", storage=dace.dtypes.StorageType.CPU_ThreadLocal) sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) def test_symbol_dependent_cpu_view(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_cpu_view", isview=True) sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) @pytest.mark.gpu def test_symbol_dependent_gpu_global_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_gpu_global_array", storage=dace.dtypes.StorageType.GPU_Global) sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) @pytest.mark.gpu def test_symbol_dependent_pinned_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_pinned_array", storage=dace.dtypes.StorageType.CPU_Pinned) sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) @pytest.mark.skip def test_symbol_dependent_gpu_view(): # such data. A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_gpu_view", storage=dace.dtypes.StorageType.GPU_Global, isview=True) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) @pytest.mark.skip def test_symbol_dependent_fpga_global_array(): A = np.random.randn(10, 10, 10) B = np.ndarray(10, dtype=np.float64) sdfg = _make_sdfg("symbol_dependent_fpga_global_array", storage=dace.dtypes.StorageType.FPGA_Global) # Compile manually to avoid simplification sdfg_exec = sdfg.compile() sdfg_exec(A=A, B=B, N=10) del sdfg_exec B_ref = np.ndarray(10, dtype=np.float64) for i in range(10): tmp = A[2:-2, 2:-2, i:] B_ref[i] = np.sum(tmp) assert (np.allclose(B, B_ref)) def test_symbol_dependent_array_in_map(): @dace.program def symbol_dependent_array_in_map(A: dace.float32[10]): out = np.ndarray(10, dtype=np.float32) for i in dace.map[0:10]: tmp = A[0:i + 1] out[i] = np.sum(tmp) return out # Compile manually to avoid simplification sdfg = symbol_dependent_array_in_map.to_sdfg(simplify=False) sdfg.apply_transformations_repeated(interstate.StateFusion) sdfg.apply_transformations_repeated(interstate.InlineSDFG) # NOTE: Temporary fix for issue with symbols/free_symbols if 'i' in sdfg.free_symbols: sdfg.remove_symbol('i') func = sdfg.compile() A = np.random.randn(10).astype(np.float32) val = func(A=A) ref = np.cumsum(A) assert (np.allclose(val, ref)) if __name__ == '__main__': test_symbol_dependent_heap_array() test_symbol_dependent_register_array() test_symbol_dependent_threadlocal_array() test_symbol_dependent_cpu_view() test_symbol_dependent_gpu_global_array() test_symbol_dependent_pinned_array() # test_symbol_dependent_gpu_view() # test_symbol_dependent_fpga_global_array() test_symbol_dependent_array_in_map()

true

f718acc04225ae3f6eed972d1bf2068588023593

4,524

py

Python

factory_powerstations/hooks.py

alexdali/test_factory_powerstations

d07faf7a254e7d7a11b17565d2f9236863846c79

[ "MIT" ]

null

factory_powerstations/hooks.py

alexdali/test_factory_powerstations

d07faf7a254e7d7a11b17565d2f9236863846c79

[ "MIT" ]

null

factory_powerstations/hooks.py

alexdali/test_factory_powerstations

d07faf7a254e7d7a11b17565d2f9236863846c79

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from . import __version__ as app_version app_name = "factory_powerstations" app_title = "Factory Powerstations" app_publisher = "Alex Tas" app_description = "Factory Management System" app_icon = "octicon octicon-file-directory" app_color = "grey" app_email = "alextas@example.com" app_license = "MIT" # Includes in <head> # ------------------ # include js, css files in header of desk.html # app_include_css = "/assets/factory_powerstations/css/factory_powerstations.css" # app_include_js = "/assets/factory_powerstations/js/factory_powerstations.js" # include js, css files in header of web template # web_include_css = "/assets/factory_powerstations/css/factory_powerstations.css" # web_include_js = "/assets/factory_powerstations/js/factory_powerstations.js" # include custom scss in every website theme (without file extension ".scss") # website_theme_scss = "factory_powerstations/public/scss/website" # include js, css files in header of web form # webform_include_js = {"doctype": "public/js/doctype.js"} # webform_include_css = {"doctype": "public/css/doctype.css"} # include js in page # page_js = {"page" : "public/js/file.js"} # include js in doctype views # doctype_js = {"doctype" : "public/js/doctype.js"} # doctype_list_js = {"doctype" : "public/js/doctype_list.js"} # doctype_tree_js = {"doctype" : "public/js/doctype_tree.js"} # doctype_calendar_js = {"doctype" : "public/js/doctype_calendar.js"} # Home Pages # ---------- # application home page (will override Website Settings) # home_page = "login" # website user home page (by Role) # role_home_page = { # "Role": "home_page" # } # Generators # ---------- # automatically create page for each record of this doctype # website_generators = ["Web Page"] # Jinja # ---------- # add methods and filters to jinja environment # jinja = { # "methods": "factory_powerstations.utils.jinja_methods", # "filters": "factory_powerstations.utils.jinja_filters" # } # Installation # ------------ # before_install = "factory_powerstations.install.before_install" # after_install = "factory_powerstations.install.after_install" # Desk Notifications # ------------------ # See frappe.core.notifications.get_notification_config # notification_config = "factory_powerstations.notifications.get_notification_config" # Permissions # ----------- # Permissions evaluated in scripted ways # permission_query_conditions = { # "Event": "frappe.desk.doctype.event.event.get_permission_query_conditions", # } # # has_permission = { # "Event": "frappe.desk.doctype.event.event.has_permission", # } # DocType Class # --------------- # Override standard doctype classes # override_doctype_class = { # "ToDo": "custom_app.overrides.CustomToDo" # } # Document Events # --------------- # Hook on document methods and events # doc_events = { # "*": { # "on_update": "method", # "on_cancel": "method", # "on_trash": "method" # } # } # Scheduled Tasks # --------------- # scheduler_events = { # "all": [ # "factory_powerstations.tasks.all" # ], # "daily": [ # "factory_powerstations.tasks.daily" # ], # "hourly": [ # "factory_powerstations.tasks.hourly" # ], # "weekly": [ # "factory_powerstations.tasks.weekly" # ] # "monthly": [ # "factory_powerstations.tasks.monthly" # ] # } # Testing # ------- # before_tests = "factory_powerstations.install.before_tests" # Overriding Methods # ------------------------------ # # override_whitelisted_methods = { # "frappe.desk.doctype.event.event.get_events": "factory_powerstations.event.get_events" # } # # each overriding function accepts a `data` argument; # generated from the base implementation of the doctype dashboard, # along with any modifications made in other Frappe apps # override_doctype_dashboards = { # "Task": "factory_powerstations.task.get_dashboard_data" # } # exempt linked doctypes from being automatically cancelled # # auto_cancel_exempted_doctypes = ["Auto Repeat"] # User Data Protection # -------------------- user_data_fields = [ { "doctype": "{doctype_1}", "filter_by": "{filter_by}", "redact_fields": ["{field_1}", "{field_2}"], "partial": 1, }, { "doctype": "{doctype_2}", "filter_by": "{filter_by}", "partial": 1, }, { "doctype": "{doctype_3}", "strict": False, }, { "doctype": "{doctype_4}" } ] # Authentication and authorization # -------------------------------- # auth_hooks = [ # "factory_powerstations.auth.validate" # ] fixtures = ["Order_PS"]

23.936508

89

0.682803

from __future__ import unicode_literals from . import __version__ as app_version app_name = "factory_powerstations" app_title = "Factory Powerstations" app_publisher = "Alex Tas" app_description = "Factory Management System" app_icon = "octicon octicon-file-directory" app_color = "grey" app_email = "alextas@example.com" app_license = "MIT" user_data_fields = [ { "doctype": "{doctype_1}", "filter_by": "{filter_by}", "redact_fields": ["{field_1}", "{field_2}"], "partial": 1, }, { "doctype": "{doctype_2}", "filter_by": "{filter_by}", "partial": 1, }, { "doctype": "{doctype_3}", "strict": False, }, { "doctype": "{doctype_4}" } ] fixtures = ["Order_PS"]

true

f718ad5022211872d6795c97dd3d1de6282cac0b

10,500

py

Python

pypy/translator/goal/richards.py

camillobruni/pygirl

ddbd442d53061d6ff4af831c1eab153bcc771b5a

[ "MIT" ]

12

2016-01-06T07:10:28.000Z

2021-05-13T23:02:02.000Z

pypy/translator/goal/richards.py

woodrow/pyoac

b5dc59e6a38e7912db47f26fb23ffa4764a3c0e7

[ "MIT" ]

null

pypy/translator/goal/richards.py

woodrow/pyoac

b5dc59e6a38e7912db47f26fb23ffa4764a3c0e7

[ "MIT" ]

2

2016-07-29T07:09:50.000Z

2016-10-16T08:50:26.000Z

# based on a Java version: # Based on original version written in BCPL by Dr Martin Richards # in 1981 at Cambridge University Computer Laboratory, England # and a C++ version derived from a Smalltalk version written by # L Peter Deutsch. # Java version: Copyright (C) 1995 Sun Microsystems, Inc. # Translation from C++, Mario Wolczko # Outer loop added by Alex Jacoby # Task IDs I_IDLE = 1 I_WORK = 2 I_HANDLERA = 3 I_HANDLERB = 4 I_DEVA = 5 I_DEVB = 6 # Packet types K_DEV = 1000 K_WORK = 1001 # Packet BUFSIZE = 4 BUFSIZE_RANGE = range(BUFSIZE) class Packet(object): def __init__(self,l,i,k): self.link = l self.ident = i self.kind = k self.datum = 0 self.data = [0] * BUFSIZE def append_to(self,lst): self.link = None if lst is None: return self else: p = lst next = p.link while next is not None: p = next next = p.link p.link = self return lst # Task Records class TaskRec(object): pass class DeviceTaskRec(TaskRec): def __init__(self): self.pending = None class IdleTaskRec(TaskRec): def __init__(self): self.control = 1 self.count = 10000 class HandlerTaskRec(TaskRec): def __init__(self): self.work_in = None self.device_in = None def workInAdd(self,p): self.work_in = p.append_to(self.work_in) return self.work_in def deviceInAdd(self,p): self.device_in = p.append_to(self.device_in) return self.device_in class WorkerTaskRec(TaskRec): def __init__(self): self.destination = I_HANDLERA self.count = 0 # Task class TaskState(object): def __init__(self): self.packet_pending = True self.task_waiting = False self.task_holding = False def packetPending(self): self.packet_pending = True self.task_waiting = False self.task_holding = False return self def waiting(self): self.packet_pending = False self.task_waiting = True self.task_holding = False return self def running(self): self.packet_pending = False self.task_waiting = False self.task_holding = False return self def waitingWithPacket(self): self.packet_pending = True self.task_waiting = True self.task_holding = False return self def isPacketPending(self): return self.packet_pending def isTaskWaiting(self): return self.task_waiting def isTaskHolding(self): return self.task_holding def isTaskHoldingOrWaiting(self): return self.task_holding or (not self.packet_pending and self.task_waiting) def isWaitingWithPacket(self): return self.packet_pending and self.task_waiting and not self.task_holding tracing = False layout = 0 def trace(a): global layout layout -= 1 if layout <= 0: print layout = 50 print a, TASKTABSIZE = 10 class TaskWorkArea(object): def __init__(self): self.taskTab = [None] * TASKTABSIZE self.taskList = None self.holdCount = 0 self.qpktCount = 0 taskWorkArea = TaskWorkArea() class Task(TaskState): def __init__(self,i,p,w,initialState,r): self.link = taskWorkArea.taskList self.ident = i self.priority = p self.input = w self.packet_pending = initialState.isPacketPending() self.task_waiting = initialState.isTaskWaiting() self.task_holding = initialState.isTaskHolding() self.handle = r taskWorkArea.taskList = self taskWorkArea.taskTab[i] = self def fn(self,pkt,r): raise NotImplementedError def addPacket(self,p,old): if self.input is None: self.input = p self.packet_pending = True if self.priority > old.priority: return self else: p.append_to(self.input) return old def runTask(self): if self.isWaitingWithPacket(): msg = self.input self.input = msg.link if self.input is None: self.running() else: self.packetPending() else: msg = None return self.fn(msg,self.handle) def waitTask(self): self.task_waiting = True return self def hold(self): taskWorkArea.holdCount += 1 self.task_holding = True return self.link def release(self,i): t = self.findtcb(i) t.task_holding = False if t.priority > self.priority: return t else: return self def qpkt(self,pkt): t = self.findtcb(pkt.ident) taskWorkArea.qpktCount += 1 pkt.link = None pkt.ident = self.ident return t.addPacket(pkt,self) def findtcb(self,id): t = taskWorkArea.taskTab[id] if t is None: raise Exception("Bad task id %d" % id) return t # DeviceTask class DeviceTask(Task): def __init__(self,i,p,w,s,r): Task.__init__(self,i,p,w,s,r) def fn(self,pkt,r): d = r assert isinstance(d, DeviceTaskRec) if pkt is None: pkt = d.pending if pkt is None: return self.waitTask() else: d.pending = None return self.qpkt(pkt) else: d.pending = pkt if tracing: trace(pkt.datum) return self.hold() class HandlerTask(Task): def __init__(self,i,p,w,s,r): Task.__init__(self,i,p,w,s,r) def fn(self,pkt,r): h = r assert isinstance(h, HandlerTaskRec) if pkt is not None: if pkt.kind == K_WORK: h.workInAdd(pkt) else: h.deviceInAdd(pkt) work = h.work_in if work is None: return self.waitTask() count = work.datum if count >= BUFSIZE: h.work_in = work.link return self.qpkt(work) dev = h.device_in if dev is None: return self.waitTask() h.device_in = dev.link dev.datum = work.data[count] work.datum = count + 1 return self.qpkt(dev) # IdleTask class IdleTask(Task): def __init__(self,i,p,w,s,r): Task.__init__(self,i,0,None,s,r) def fn(self,pkt,r): i = r assert isinstance(i, IdleTaskRec) i.count -= 1 if i.count == 0: return self.hold() elif i.control & 1 == 0: i.control /= 2 return self.release(I_DEVA) else: i.control = i.control/2 ^ 0xd008 return self.release(I_DEVB) # WorkTask A = ord('A') class WorkTask(Task): def __init__(self,i,p,w,s,r): Task.__init__(self,i,p,w,s,r) def fn(self,pkt,r): w = r assert isinstance(w, WorkerTaskRec) if pkt is None: return self.waitTask() if w.destination == I_HANDLERA: dest = I_HANDLERB else: dest = I_HANDLERA w.destination = dest pkt.ident = dest pkt.datum = 0 for i in BUFSIZE_RANGE: # xrange(BUFSIZE) w.count += 1 if w.count > 26: w.count = 1 pkt.data[i] = A + w.count - 1 return self.qpkt(pkt) import time def schedule(): t = taskWorkArea.taskList while t is not None: pkt = None if tracing: print "tcb =",t.ident if t.isTaskHoldingOrWaiting(): t = t.link else: if tracing: trace(chr(ord("0")+t.ident)) t = t.runTask() class Richards(object): def run(self, iterations): for i in xrange(iterations): taskWorkArea.holdCount = 0 taskWorkArea.qpktCount = 0 IdleTask(I_IDLE, 1, 10000, TaskState().running(), IdleTaskRec()) wkq = Packet(None, 0, K_WORK) wkq = Packet(wkq , 0, K_WORK) WorkTask(I_WORK, 1000, wkq, TaskState().waitingWithPacket(), WorkerTaskRec()) wkq = Packet(None, I_DEVA, K_DEV) wkq = Packet(wkq , I_DEVA, K_DEV) wkq = Packet(wkq , I_DEVA, K_DEV) HandlerTask(I_HANDLERA, 2000, wkq, TaskState().waitingWithPacket(), HandlerTaskRec()) wkq = Packet(None, I_DEVB, K_DEV) wkq = Packet(wkq , I_DEVB, K_DEV) wkq = Packet(wkq , I_DEVB, K_DEV) HandlerTask(I_HANDLERB, 3000, wkq, TaskState().waitingWithPacket(), HandlerTaskRec()) wkq = None; DeviceTask(I_DEVA, 4000, wkq, TaskState().waiting(), DeviceTaskRec()); DeviceTask(I_DEVB, 5000, wkq, TaskState().waiting(), DeviceTaskRec()); schedule() if taskWorkArea.holdCount == 9297 and taskWorkArea.qpktCount == 23246: pass else: return False return True def entry_point(iterations): r = Richards() startTime = time.time() result = r.run(iterations) endTime = time.time() return result, startTime, endTime def main(entry_point = entry_point, iterations = 10): print "Richards benchmark (Python) starting... [%r]" % entry_point result, startTime, endTime = entry_point(iterations) if not result: print "Incorrect results!" return -1 print "finished." total_s = endTime - startTime print "Total time for %d iterations: %.2f secs" %(iterations,total_s) print "Average time per iteration: %.2f ms" %(total_s*1000/iterations) return 42 try: import sys if '-nojit' in sys.argv: sys.argv.remove('-nojit') raise ImportError import pypyjit except ImportError: pass else: import types for item in globals().values(): if isinstance(item, types.FunctionType): pypyjit.enable(item.func_code) elif isinstance(item, type): for it in item.__dict__.values(): if isinstance(it, types.FunctionType): pypyjit.enable(it.func_code) if __name__ == '__main__': import sys if len(sys.argv) >= 2: main(iterations = int(sys.argv[1])) else: main()

23.809524

97

0.567524

I_IDLE = 1 I_WORK = 2 I_HANDLERA = 3 I_HANDLERB = 4 I_DEVA = 5 I_DEVB = 6 K_DEV = 1000 K_WORK = 1001 BUFSIZE = 4 BUFSIZE_RANGE = range(BUFSIZE) class Packet(object): def __init__(self,l,i,k): self.link = l self.ident = i self.kind = k self.datum = 0 self.data = [0] * BUFSIZE def append_to(self,lst): self.link = None if lst is None: return self else: p = lst next = p.link while next is not None: p = next next = p.link p.link = self return lst class TaskRec(object): pass class DeviceTaskRec(TaskRec): def __init__(self): self.pending = None class IdleTaskRec(TaskRec): def __init__(self): self.control = 1 self.count = 10000 class HandlerTaskRec(TaskRec): def __init__(self): self.work_in = None self.device_in = None def workInAdd(self,p): self.work_in = p.append_to(self.work_in) return self.work_in def deviceInAdd(self,p): self.device_in = p.append_to(self.device_in) return self.device_in class WorkerTaskRec(TaskRec): def __init__(self): self.destination = I_HANDLERA self.count = 0 class TaskState(object): def __init__(self): self.packet_pending = True self.task_waiting = False self.task_holding = False def packetPending(self): self.packet_pending = True self.task_waiting = False self.task_holding = False return self def waiting(self): self.packet_pending = False self.task_waiting = True self.task_holding = False return self def running(self): self.packet_pending = False self.task_waiting = False self.task_holding = False return self def waitingWithPacket(self): self.packet_pending = True self.task_waiting = True self.task_holding = False return self def isPacketPending(self): return self.packet_pending def isTaskWaiting(self): return self.task_waiting def isTaskHolding(self): return self.task_holding def isTaskHoldingOrWaiting(self): return self.task_holding or (not self.packet_pending and self.task_waiting) def isWaitingWithPacket(self): return self.packet_pending and self.task_waiting and not self.task_holding tracing = False layout = 0 def trace(a): global layout layout -= 1 if layout <= 0: print layout = 50 print a, TASKTABSIZE = 10 class TaskWorkArea(object): def __init__(self): self.taskTab = [None] * TASKTABSIZE self.taskList = None self.holdCount = 0 self.qpktCount = 0 taskWorkArea = TaskWorkArea() class Task(TaskState): def __init__(self,i,p,w,initialState,r): self.link = taskWorkArea.taskList self.ident = i self.priority = p self.input = w self.packet_pending = initialState.isPacketPending() self.task_waiting = initialState.isTaskWaiting() self.task_holding = initialState.isTaskHolding() self.handle = r taskWorkArea.taskList = self taskWorkArea.taskTab[i] = self def fn(self,pkt,r): raise NotImplementedError def addPacket(self,p,old): if self.input is None: self.input = p self.packet_pending = True if self.priority > old.priority: return self else: p.append_to(self.input) return old def runTask(self): if self.isWaitingWithPacket(): msg = self.input self.input = msg.link if self.input is None: self.running() else: self.packetPending() else: msg = None return self.fn(msg,self.handle) def waitTask(self): self.task_waiting = True return self def hold(self): taskWorkArea.holdCount += 1 self.task_holding = True return self.link def release(self,i): t = self.findtcb(i) t.task_holding = False if t.priority > self.priority: return t else: return self def qpkt(self,pkt): t = self.findtcb(pkt.ident) taskWorkArea.qpktCount += 1 pkt.link = None pkt.ident = self.ident return t.addPacket(pkt,self) def findtcb(self,id): t = taskWorkArea.taskTab[id] if t is None: raise Exception("Bad task id %d" % id) return t class DeviceTask(Task): def __init__(self,i,p,w,s,r): Task.__init__(self,i,p,w,s,r) def fn(self,pkt,r): d = r assert isinstance(d, DeviceTaskRec) if pkt is None: pkt = d.pending if pkt is None: return self.waitTask() else: d.pending = None return self.qpkt(pkt) else: d.pending = pkt if tracing: trace(pkt.datum) return self.hold() class HandlerTask(Task): def __init__(self,i,p,w,s,r): Task.__init__(self,i,p,w,s,r) def fn(self,pkt,r): h = r assert isinstance(h, HandlerTaskRec) if pkt is not None: if pkt.kind == K_WORK: h.workInAdd(pkt) else: h.deviceInAdd(pkt) work = h.work_in if work is None: return self.waitTask() count = work.datum if count >= BUFSIZE: h.work_in = work.link return self.qpkt(work) dev = h.device_in if dev is None: return self.waitTask() h.device_in = dev.link dev.datum = work.data[count] work.datum = count + 1 return self.qpkt(dev) class IdleTask(Task): def __init__(self,i,p,w,s,r): Task.__init__(self,i,0,None,s,r) def fn(self,pkt,r): i = r assert isinstance(i, IdleTaskRec) i.count -= 1 if i.count == 0: return self.hold() elif i.control & 1 == 0: i.control /= 2 return self.release(I_DEVA) else: i.control = i.control/2 ^ 0xd008 return self.release(I_DEVB) A = ord('A') class WorkTask(Task): def __init__(self,i,p,w,s,r): Task.__init__(self,i,p,w,s,r) def fn(self,pkt,r): w = r assert isinstance(w, WorkerTaskRec) if pkt is None: return self.waitTask() if w.destination == I_HANDLERA: dest = I_HANDLERB else: dest = I_HANDLERA w.destination = dest pkt.ident = dest pkt.datum = 0 for i in BUFSIZE_RANGE: w.count += 1 if w.count > 26: w.count = 1 pkt.data[i] = A + w.count - 1 return self.qpkt(pkt) import time def schedule(): t = taskWorkArea.taskList while t is not None: pkt = None if tracing: print "tcb =",t.ident if t.isTaskHoldingOrWaiting(): t = t.link else: if tracing: trace(chr(ord("0")+t.ident)) t = t.runTask() class Richards(object): def run(self, iterations): for i in xrange(iterations): taskWorkArea.holdCount = 0 taskWorkArea.qpktCount = 0 IdleTask(I_IDLE, 1, 10000, TaskState().running(), IdleTaskRec()) wkq = Packet(None, 0, K_WORK) wkq = Packet(wkq , 0, K_WORK) WorkTask(I_WORK, 1000, wkq, TaskState().waitingWithPacket(), WorkerTaskRec()) wkq = Packet(None, I_DEVA, K_DEV) wkq = Packet(wkq , I_DEVA, K_DEV) wkq = Packet(wkq , I_DEVA, K_DEV) HandlerTask(I_HANDLERA, 2000, wkq, TaskState().waitingWithPacket(), HandlerTaskRec()) wkq = Packet(None, I_DEVB, K_DEV) wkq = Packet(wkq , I_DEVB, K_DEV) wkq = Packet(wkq , I_DEVB, K_DEV) HandlerTask(I_HANDLERB, 3000, wkq, TaskState().waitingWithPacket(), HandlerTaskRec()) wkq = None; DeviceTask(I_DEVA, 4000, wkq, TaskState().waiting(), DeviceTaskRec()); DeviceTask(I_DEVB, 5000, wkq, TaskState().waiting(), DeviceTaskRec()); schedule() if taskWorkArea.holdCount == 9297 and taskWorkArea.qpktCount == 23246: pass else: return False return True def entry_point(iterations): r = Richards() startTime = time.time() result = r.run(iterations) endTime = time.time() return result, startTime, endTime def main(entry_point = entry_point, iterations = 10): print "Richards benchmark (Python) starting... [%r]" % entry_point result, startTime, endTime = entry_point(iterations) if not result: print "Incorrect results!" return -1 print "finished." total_s = endTime - startTime print "Total time for %d iterations: %.2f secs" %(iterations,total_s) print "Average time per iteration: %.2f ms" %(total_s*1000/iterations) return 42 try: import sys if '-nojit' in sys.argv: sys.argv.remove('-nojit') raise ImportError import pypyjit except ImportError: pass else: import types for item in globals().values(): if isinstance(item, types.FunctionType): pypyjit.enable(item.func_code) elif isinstance(item, type): for it in item.__dict__.values(): if isinstance(it, types.FunctionType): pypyjit.enable(it.func_code) if __name__ == '__main__': import sys if len(sys.argv) >= 2: main(iterations = int(sys.argv[1])) else: main()

false

true

f718adc9b2a9c127df3f8b525ea928e4dd8d5e7d

1,240

py

Python

intro-python/parsing-json/nested_data.py

myounker/dnav3-code

fbb1e4d1d3cc642cc7089f8a9de35298c33f1ee0

[ "MIT" ]

null

intro-python/parsing-json/nested_data.py

myounker/dnav3-code

fbb1e4d1d3cc642cc7089f8a9de35298c33f1ee0

[ "MIT" ]

null

intro-python/parsing-json/nested_data.py

myounker/dnav3-code

fbb1e4d1d3cc642cc7089f8a9de35298c33f1ee0

[ "MIT" ]

null

#!/usr/bin/env python """Working with nested data hands-on exercise / coding challenge.""" """ code by myounker 1 Sep 2018 """ import json import os # Get the absolute path for the directory where this file is located "here" here = os.path.abspath(os.path.dirname(__file__)) #open file with interfaces and import text to variable called json_text with open(os.path.join(here, "interfaces.json")) as file: json_text = file.read() #put json string into py native format json_data = json.loads(json_text) # Loop through the interfaces in the JSON data and print out each # interface's name, ip, and netmask. print("\n") for interface in json_data["ietf-interfaces:interfaces"]["interface"]: print(interface["name"] + ': ' + interface["ietf-ip:ipv4"]["address"][0]["ip"] + ' ' + interface["ietf-ip:ipv4"]["address"][0]["netmask"] ) print("\n") ''' solution on git used .format. I need to learn that!!! https://github.com/CiscoDevNet/dnav3-code/blob/solutions/intro-python/parsing-json/nested_data.py print("{name}: {ip} {netmask}".format( name=interface["name"], ip=interface["ietf-ip:ipv4"]["address"][0]["ip"], netmask=interface["ietf-ip:ipv4"]["address"][0]["netmask"], '''

31

97

0.678226

import json import os here = os.path.abspath(os.path.dirname(__file__)) with open(os.path.join(here, "interfaces.json")) as file: json_text = file.read() json_data = json.loads(json_text) print("\n") for interface in json_data["ietf-interfaces:interfaces"]["interface"]: print(interface["name"] + ': ' + interface["ietf-ip:ipv4"]["address"][0]["ip"] + ' ' + interface["ietf-ip:ipv4"]["address"][0]["netmask"] ) print("\n")

true

f718ae668683de5a9982de18699f332fc0998603

333

py

Python

betterLogger/filter.py

GreenJon902/BetterLogger

7333cc83d0bb9350781e5506e15fc0476e7d2791

[ "MIT" ]

null

betterLogger/filter.py

GreenJon902/BetterLogger

7333cc83d0bb9350781e5506e15fc0476e7d2791

[ "MIT" ]

null

betterLogger/filter.py

GreenJon902/BetterLogger

7333cc83d0bb9350781e5506e15fc0476e7d2791

[ "MIT" ]

null

from logging import Filter as _Filter from betterLogger import config class Filter(_Filter): def filter(self, record): return (not config.log_whitelist_on or any(record.name.startswith(name) for name in config.log_whitelist)) and \ not any(record.name.startswith(name) for name in config.log_blacklist)

33.3

120

0.738739

from logging import Filter as _Filter from betterLogger import config class Filter(_Filter): def filter(self, record): return (not config.log_whitelist_on or any(record.name.startswith(name) for name in config.log_whitelist)) and \ not any(record.name.startswith(name) for name in config.log_blacklist)

true

f718ae8d0d6ecee7a425e414aeeb37eb1faffce6

5,323

py

Python

flexagon.py

dlp/flexagon

c8ac58e125c6f405d9942245bdaa71fab658def6

[ "MIT" ]

null

flexagon.py

dlp/flexagon

c8ac58e125c6f405d9942245bdaa71fab658def6

[ "MIT" ]

null

flexagon.py

dlp/flexagon

c8ac58e125c6f405d9942245bdaa71fab658def6

[ "MIT" ]

null

#!/usr/bin/env python ############################################################################### # Simple PIL-based flexagon generator # # For the time being, it creates only 2D trihexaflexagons. # # Daniel Prokesch <daniel.prokesch@gmail.com> ############################################################################### """USAGE: {} image1 image2 image3 output""" from PIL import Image, ImageOps, ImageDraw from math import sqrt, sin, cos, pi import sys # The flexagon is composed of small equilateral triangles. # The height equals side * sqrt(3)/2 sqrt3_2 = sqrt(3.0)/2.0 def crop_size(img): """Crop the image to have the appropriate ratio for a flexagon.""" width, height = img.size # could use fit, with the assumption that the height will be sufficient # return ImageOps.fit(img, (width, int(width * sqrt3_2))) # better make a case distinction if height > (width * sqrt3_2): new_height = int(width * sqrt3_2) diff_2 = (height - new_height) / 2 # left, upper, right, lower box = (0, diff_2, width, diff_2 + new_height) else: new_width = int(height / sqrt3_2) diff_2 = (width - new_width) / 2 # left, upper, right, lower box = (diff_2, 0, diff_2 + new_width, height) return img.crop(box) def rot_trans(center, angle, new_center): """Return an array for PIL's affine transform. It describes a rotation of angle degrees around center, followed by a translation to new_center. According to PIL's documentation, 'For each pixel (x, y) in the output image, the new value is taken from a position (a x + b y + c, d x + e y + f) in the input image, rounded to nearest pixel.' As result, the matrix is not an object transform matrix but an axis transform matrix (inverse of the former). """ rho = angle*pi / 180.0 cosine, sine = cos(rho), sin(rho) cx, cy = center nx, ny = new_center return [ cosine, sine, -nx*cosine -ny*sine +cx, -sine, cosine, nx*sine -ny*cosine +cy] def xform(mat, pt): """Apply the transformation of mat to a point pt. The transform in mat is described by a 6-element tuple, as returned by rot_trans. """ x, y = pt return (x*mat[0] + y*mat[1] + mat[2], x*mat[3] + y*mat[4] + mat[5]) def xform_arr(mat, arr): """Apply the transformation of mat to a sequence arr of points.""" return [xform(mat, pt) for pt in arr] ############################################################################### if __name__ == "__main__": if len(sys.argv) != 5: print >>sys.stderr, __doc__.format(sys.argv[0]) exit(1) try: images = [crop_size(Image.open(sys.argv[i])) for i in range(1,4)] except IOError as e: print >>sys.stderr, e exit(1) common_size = min(img.size for img in images) for img in images: img.thumbnail(common_size) s, h = map(lambda x: x/2, common_size) flexagon = Image.new("RGB", map(int,(2*h, 5.5*s)), color=(255,255,255)) def paste_and_mask(img, angle, trans, poly_base): """Get a patch from img and paste it to the flexagon.""" mat = rot_trans((s, h), angle, trans) patch = img.transform(flexagon.size, Image.AFFINE, mat) mask = Image.new("1", flexagon.size) # The mask polygon is only translated. As rot_trans describes an axis # transformation, we specify the translation as center. ImageDraw.Draw(mask).polygon( xform_arr(rot_trans(trans, 0, (0,0)), poly_base), fill=1) flexagon.paste(patch, (0,0), mask) mask_poly_dbl = [(0,-s), (0,0), (h,0.5*s), (h,-0.5*s)] # double mask_poly_sl = [(0,0), (h,0.5*s), (h,-0.5*s)] # single left mask_poly_slb = [(0,0), (0,-s), (h,-0.5*s)] # single left bottom # each patch has three parameters: # rotation in degrees, the translation w.r.t. the centre point, and the # mask (which is designed as to be translated with the same coordinates) t1_AB = 90, (h, 1.5*s), mask_poly_dbl t1_CF = -30, (0, 3.0*s), mask_poly_dbl t1_DE = -150, (h, 4.5*s), mask_poly_dbl t2_AB = 90, (0, 2.0*s), mask_poly_dbl t2_CF = -30, (h, 3.5*s), mask_poly_dbl t2_D = -150, (h, 0.5*s), mask_poly_sl t2_E = -150, (0, 5.0*s), mask_poly_slb t3_A = 150, (0, 1.0*s), mask_poly_sl t3_BC = 30, (h, 2.5*s), mask_poly_dbl t3_EF = -90, (0, 4.0*s), mask_poly_dbl t3_D = 150, (h, 5.5*s), mask_poly_slb for t in [t1_AB, t1_CF, t1_DE]: paste_and_mask(images[0], *t) for t in [t2_AB, t2_CF, t2_D, t2_E]: paste_and_mask(images[1], *t) for t in [t3_A, t3_BC, t3_EF, t3_D]: paste_and_mask(images[2], *t) # draw lines dw = ImageDraw.Draw(flexagon) # vertical lines dw.line([(0, s), (0, 5*s)], fill=0) dw.line([(h, 0.5*s), (h, 5.5*s)], fill=0) dw.line([(2*h-1, 0), (2*h-1, 5*s)], fill=0) # -1 offset to stay on canvas # from left bottom to right top (last one is cropped) for i in range(6): dw.line([(0, (i+1)*s), (2*h, i*s)], fill=0) # from left top to right bottom (first one starts in half) dw.line([(h, 0.5*s), (2*h, s)], fill=0) for i in range(1,5): dw.line([(0, i*s), (2*h, (i+1)*s)], fill=0) flexagon.save(sys.argv[4])

34.79085

79

0.57956

true

f718af111d82c6f2a7d6c664a42657d4c6707646

5,845

py

Python

rnacentral_pipeline/rnacentral/genome_mapping/blat.py

RNAcentral/rnacentral-import-pipeline

238e573440c72581a051b16c15f56fcd25bece74

[ "Apache-2.0" ]

1

2018-08-09T14:41:16.000Z

rnacentral_pipeline/rnacentral/genome_mapping/blat.py

RNAcentral/rnacentral-import-pipeline

238e573440c72581a051b16c15f56fcd25bece74

[ "Apache-2.0" ]

60

2015-02-04T16:43:53.000Z

2022-01-27T10:28:43.000Z

rnacentral_pipeline/rnacentral/genome_mapping/blat.py

RNAcentral/rnacentral-import-pipeline

238e573440c72581a051b16c15f56fcd25bece74

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ Copyright [2009-2018] EMBL-European Bioinformatics Institute Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import csv import json import operator as op import itertools as it import logging import attr from attr.validators import instance_of as is_a from rnacentral_pipeline import utils from rnacentral_pipeline.databases.data.regions import Exon from rnacentral_pipeline.databases.data.regions import Strand from rnacentral_pipeline.databases.data.regions import SequenceRegion from rnacentral_pipeline.databases.data.regions import CoordinateSystem LOGGER = logging.getLogger(__name__) FIELDS = [ "matches", # Number of bases that match that aren't repeats "misMatches", # Number of bases that don't match "repMatches", # Number of bases that match but are part of repeats "nCount", # Number of "N" bases "qNumInsert", # Number of inserts in query "qBaseInsert", # Number of bases inserted in query "tNumInsert", # Number of inserts in target "tBaseInsert", # Number of bases inserted in target "strand", # "+" or "-" for query strand. For translated alignments, second "+"or "-" is for target genomic strand. "qName", # Query sequence name "qSize", # Query sequence size. "qStart", # Alignment start position in query "qEnd", # Alignment end position in query "tName", # Target sequence name "tSize", # Target sequence size "tStart", # Alignment start position in target "tEnd", # Alignment end position in target "blockCount", # Number of blocks in the alignment (a block contains no gaps) "blockSizes", # Comma-separated list of sizes of each block. If the query is a protein and the target the genome, blockSizes are in amino acids. See below for more information on protein query PSLs. "qStarts", # Comma-separated list of starting positions of each block in query "tStarts", # Comma-separated list of starting positions of each block in target ] @attr.s(frozen=True) class BlatHit(object): upi = attr.ib(validator=is_a(str), converter=str) sequence_length = attr.ib(validator=is_a(int)) matches = attr.ib(validator=is_a(int)) target_insertions = attr.ib(validator=is_a(int)) region = attr.ib(validator=is_a(SequenceRegion)) @classmethod def build(cls, assembly_id, raw): parts = zip(raw["tStarts"], raw["blockSizes"]) exons = [Exon(s, s + l) for (s, l) in parts] return cls( upi=raw["qName"], sequence_length=raw["qSize"], matches=raw["matches"], target_insertions=raw["tBaseInsert"], region=SequenceRegion( assembly_id=assembly_id, chromosome=raw["tName"], strand=raw["strand"], exons=exons, coordinate_system=CoordinateSystem.zero_based(), ), ) @property def name(self): return self.region.name(upi=self.upi) @property def match_fraction(self): return float(self.matches) / float(self.sequence_length) def writeable(self): return self.region.writeable(self.upi, is_upi=True) def select_possible(hit): if hit.matches < 100 and hit.target_insertions > 25: return False if hit.matches == hit.sequence_length: return True if ( hit.sequence_length > 15 and hit.match_fraction > 0.95 and hit.match_fraction < 1 ): return True return False def select_best(hits): hits = list(hits) best = max(hits, key=op.attrgetter("match_fraction")) if best.match_fraction == 1.0: return [h for h in hits if h.match_fraction == best.match_fraction] return hits def parse_psl(assembly_id, handle): to_split = ["blockSizes", "qStarts", "tStarts"] for row in csv.reader(handle, delimiter="\t"): result = dict(zip(FIELDS, row)) for key in to_split: result[key] = [int(v) for v in result[key].split(",") if v] lens = {len(result[k]) for k in to_split} assert len(lens) == 1 for key, value in result.items(): if key not in to_split and "Name" not in key and key != "strand": result[key] = int(value) yield BlatHit.build(assembly_id, result) def select_hits(hits, sort=False): key = op.attrgetter("upi") if sort: hits = sorted(hits, key=key) for upi, subhits in it.groupby(hits, key=key): selected = list(filter(select_possible, subhits)) if not selected: LOGGER.warn("No possible matches for %s", upi) continue best = select_best(selected) if not best: raise ValueError("Failed to select a best hit for %s" % upi) for hit in best: yield hit def write_importable(handle, output): hits = utils.unpickle_stream(handle) writeable = map(op.methodcaller("writeable"), hits) writeable = it.chain.from_iterable(writeable) csv.writer(output).writerows(writeable) def as_pickle(assembly_id, hits, output): parsed = parse_psl(assembly_id, hits) utils.pickle_stream(parsed, output) def select_pickle(handle, output, sort=False): hits = utils.unpickle_stream(handle) selected = select_hits(hits, sort=sort) utils.pickle_stream(selected, output)

34.181287

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0.670488

import csv import json import operator as op import itertools as it import logging import attr from attr.validators import instance_of as is_a from rnacentral_pipeline import utils from rnacentral_pipeline.databases.data.regions import Exon from rnacentral_pipeline.databases.data.regions import Strand from rnacentral_pipeline.databases.data.regions import SequenceRegion from rnacentral_pipeline.databases.data.regions import CoordinateSystem LOGGER = logging.getLogger(__name__) FIELDS = [ "matches", "misMatches", # Number of bases that don't match "repMatches", "nCount", "qNumInsert", "qBaseInsert", "tNumInsert", "tBaseInsert", "strand", "qName", "qSize", "qStart", "qEnd", "tName", "tSize", "tStart", "tEnd", "blockCount", "blockSizes", "qStarts", "tStarts", ] @attr.s(frozen=True) class BlatHit(object): upi = attr.ib(validator=is_a(str), converter=str) sequence_length = attr.ib(validator=is_a(int)) matches = attr.ib(validator=is_a(int)) target_insertions = attr.ib(validator=is_a(int)) region = attr.ib(validator=is_a(SequenceRegion)) @classmethod def build(cls, assembly_id, raw): parts = zip(raw["tStarts"], raw["blockSizes"]) exons = [Exon(s, s + l) for (s, l) in parts] return cls( upi=raw["qName"], sequence_length=raw["qSize"], matches=raw["matches"], target_insertions=raw["tBaseInsert"], region=SequenceRegion( assembly_id=assembly_id, chromosome=raw["tName"], strand=raw["strand"], exons=exons, coordinate_system=CoordinateSystem.zero_based(), ), ) @property def name(self): return self.region.name(upi=self.upi) @property def match_fraction(self): return float(self.matches) / float(self.sequence_length) def writeable(self): return self.region.writeable(self.upi, is_upi=True) def select_possible(hit): if hit.matches < 100 and hit.target_insertions > 25: return False if hit.matches == hit.sequence_length: return True if ( hit.sequence_length > 15 and hit.match_fraction > 0.95 and hit.match_fraction < 1 ): return True return False def select_best(hits): hits = list(hits) best = max(hits, key=op.attrgetter("match_fraction")) if best.match_fraction == 1.0: return [h for h in hits if h.match_fraction == best.match_fraction] return hits def parse_psl(assembly_id, handle): to_split = ["blockSizes", "qStarts", "tStarts"] for row in csv.reader(handle, delimiter="\t"): result = dict(zip(FIELDS, row)) for key in to_split: result[key] = [int(v) for v in result[key].split(",") if v] lens = {len(result[k]) for k in to_split} assert len(lens) == 1 for key, value in result.items(): if key not in to_split and "Name" not in key and key != "strand": result[key] = int(value) yield BlatHit.build(assembly_id, result) def select_hits(hits, sort=False): key = op.attrgetter("upi") if sort: hits = sorted(hits, key=key) for upi, subhits in it.groupby(hits, key=key): selected = list(filter(select_possible, subhits)) if not selected: LOGGER.warn("No possible matches for %s", upi) continue best = select_best(selected) if not best: raise ValueError("Failed to select a best hit for %s" % upi) for hit in best: yield hit def write_importable(handle, output): hits = utils.unpickle_stream(handle) writeable = map(op.methodcaller("writeable"), hits) writeable = it.chain.from_iterable(writeable) csv.writer(output).writerows(writeable) def as_pickle(assembly_id, hits, output): parsed = parse_psl(assembly_id, hits) utils.pickle_stream(parsed, output) def select_pickle(handle, output, sort=False): hits = utils.unpickle_stream(handle) selected = select_hits(hits, sort=sort) utils.pickle_stream(selected, output)

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