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""" Classes holding information on global DOFs and mapping of all DOFs - equations (active DOFs). Helper functions for the equation mapping. """ import numpy as nm import scipy.sparse as sp from sfepy.base.base import assert_, Struct, basestr from sfepy.discrete.functions import Function from sfepy.discrete.condition...
[ "sfepy.base.base.Struct", "sfepy.discrete.conditions.get_condition_value", "numpy.ravel", "numpy.empty", "numpy.zeros", "sfepy.base.base.Struct.__init__", "numpy.ones", "numpy.setdiff1d", "numpy.nonzero", "scipy.sparse.coo_matrix", "numpy.where", "numpy.arange", "sfepy.base.base.assert_", ...
[((570, 601), 'numpy.repeat', 'nm.repeat', (['nods', 'n_dof_per_node'], {}), '(nods, n_dof_per_node)\n', (579, 601), True, 'import numpy as nm\n'), ((663, 704), 'numpy.arange', 'nm.arange', (['n_dof_per_node'], {'dtype': 'nm.int32'}), '(n_dof_per_node, dtype=nm.int32)\n', (672, 704), True, 'import numpy as nm\n'), ((27...
import numpy from numba import jit from . import misc_functions as m #from importlib import reload #reload(m) ############################################################ ############################################################ ################ Find best split functions ################ #######################...
[ "numpy.argsort", "numba.jit", "numpy.sum", "numpy.isnan" ]
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# Generated by Django 3.2.5 on 2021-07-29 23:32 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('contact', '0004_feedback_user'), ] operations = [ migrations.AlterModelOptions( name='feedback', options={'verbose_name_plur...
[ "django.db.migrations.AlterModelOptions" ]
[((222, 317), 'django.db.migrations.AlterModelOptions', 'migrations.AlterModelOptions', ([], {'name': '"""feedback"""', 'options': "{'verbose_name_plural': 'Feedback'}"}), "(name='feedback', options={\n 'verbose_name_plural': 'Feedback'})\n", (250, 317), False, 'from django.db import migrations\n')]
import logging import os import random from typing import Generator import numpy as np import pandas as pd import tensorflow as tf from baselines.common import tf_util from cluster_work import ClusterWork from kb_learning.envs import MultiObjectDirectControlEnv, NormalizeActionWrapper from kb_learning.policy_networks...
[ "kb_learning.envs.NormalizeActionWrapper", "numpy.random.seed", "numpy.sum", "baselines.common.tf_util.make_session", "kb_learning.tools.trpo_tools.ActWrapper.load", "kb_learning.tools.trpo_tools.traj_segment_generator_ma", "tensorflow.set_random_seed", "tensorflow.ConfigProto", "numpy.mean", "ran...
[((586, 611), 'logging.getLogger', 'logging.getLogger', (['"""trpo"""'], {}), "('trpo')\n", (603, 611), False, 'import logging\n'), ((1130, 1239), 'tensorflow.ConfigProto', 'tf.ConfigProto', ([], {'allow_soft_placement': '(True)', 'inter_op_parallelism_threads': '(2)', 'intra_op_parallelism_threads': '(1)'}), '(allow_s...
import matplotlib.pyplot as plt import numpy as np import bootstraphistogram # create histogram hist = bootstraphistogram.BootstrapHistogram( bootstraphistogram.axis.Regular(10, -3.0, 3.0), numsamples=10 ) # fill with some random normal data data = np.random.normal(size=1000) hist.fill(data) # plot the median s...
[ "bootstraphistogram.plot.step", "bootstraphistogram.axis.Regular", "matplotlib.pyplot.show", "numpy.random.normal" ]
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""" @version: @author: DQ @time: 2021-10-13 @file: main.py @function: @modify: """ import pygame import time from packages import * WIN_SIZE = (640, 480) class Main(): def __init__(self): pygame.init() window = pygame.display.set_mode(WIN_SIZE) icon = pygame.image.l...
[ "pygame.display.set_icon", "pygame.event.get", "pygame.display.set_mode", "time.perf_counter", "pygame.init", "pygame.display.flip", "pygame.display.update", "pygame.image.load", "pygame.display.set_caption" ]
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# Código para obter posição do mouse import pyautogui import time time.sleep(7) x, y = pyautogui.position() print ("x = "+str(x)+" y = "+str(y))
[ "pyautogui.position", "time.sleep" ]
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""" @date: 2021-02-05 @author: HelleDaryd """ from datetime import datetime, timezone import dateutil.parser as dparser from twisted.plugin import IPlugin from twisted.words.protocols.irc import assembleFormattedText as colour, attributes as A from zope.interface import implementer from desertbot.message import IRC...
[ "twisted.words.protocols.irc.assembleFormattedText", "zope.interface.implementer", "dateutil.parser.isoparse", "datetime.datetime.now", "jq.compile" ]
[((592, 621), 'zope.interface.implementer', 'implementer', (['IPlugin', 'IModule'], {}), '(IPlugin, IModule)\n', (603, 621), False, 'from zope.interface import implementer\n'), ((783, 1862), 'jq.compile', 'jq.compile', (['"""\n def e(f): if f == "[]" then null else f end;\n [ .data.Catalog.searchStore.ele...
# Copyright Contributors to the Amundsen project. # SPDX-License-Identifier: Apache-2.0 import attr from marshmallow_annotations.ext.attrs import AttrsSchema @attr.s(auto_attribs=True, kw_only=True) class Badge: badge_name: str = attr.ib() category: str = attr.ib() class BadgeSchema(AttrsSchema): class...
[ "attr.s", "attr.ib" ]
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# coding=utf-8 # Copyright 2020 The Uncertainty Baselines 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 ap...
[ "tensorflow_datasets.core.Version", "absl.logging.info", "tensorflow_datasets.core.MetadataDict", "tensorflow_datasets.builder", "tensorflow.io.parse_example", "tensorflow.data.Dataset.list_files", "tensorflow.io.FixedLenFeature", "os.path.join", "tensorflow_datasets.core.ReadInstruction" ]
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# 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 t...
[ "keystone.openstack.common.versionutils.deprecated" ]
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# (Draft) of a unified agent similar to NARS from random import seed, randint import numba import Debug # initialize random number generator seed() # TODO< sort concepts > # TODO< add time > # TODO< add time of events/tasks > # TODO< feedback of priority after derivation in the attention system > # TODO< fix per...
[ "Debug.msg", "TruthValue.TruthValue", "time.process_time", "Task.Task", "random.seed", "Reasoner.Reasoner", "Distributed.genRandom" ]
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from django.contrib import admin from django.contrib.auth.models import User from .models import Comment, Post, Subneddit # Register your models here. admin.site.register(Subneddit) admin.site.register(Post) admin.site.register(Comment)
[ "django.contrib.admin.site.register" ]
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# ----------------------------------------------------------------------------- # Copyright (c) 2013-2021, NeXpy Development Team. # # Distributed under the terms of the Modified BSD License. # # The full license is in the file COPYING, distributed with this software. # -------------------------------------------------...
[ "nexusformat.nexus.NXdata", "cctbx.crystal.symmetry", "numpy.abs", "nexusformat.nexus.NXsample", "numpy.arctan2", "numpy.sum", "nexusformat.nexus.NXlink", "pkg_resources.resource_filename", "numpy.isclose", "numpy.sin", "numpy.linalg.norm", "julia.Julia", "numpy.arange", "os.path.join", ...
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import sys sys.path.append('../src/meta_rule/') sys.path.append('../dd_lnn/') import time import copy import argparse from meta_interpretive import BaseMetaPredicate, MetaRule, Project, DisjunctionRule from train_test import score, align_labels, train from read import load_data, load_metadata, load_labels import pand...
[ "sys.path.append", "meta_interpretive.BaseMetaPredicate", "copy.deepcopy", "numpy.set_printoptions", "read.load_data", "argparse.ArgumentParser", "torch.nn.BCEWithLogitsLoss", "torch.LongTensor", "train_test.align_labels", "train_test.score", "meta_interpretive.Project", "time.time", "meta_i...
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import matplotlib.pyplot as plt import numpy as np import matplotlib as mpl import pandas as pd import sys sys.path.append("..") mpl.use('tkagg') # issues with Big Sur import matplotlib.pyplot as plt from strategy.standard_deviation import sd from backtest import Backtest from evaluate import SharpeRatio, MaxDrawdown...
[ "sys.path.append", "pandas.Timestamp", "strategy.standard_deviation.sd.plot_SD", "matplotlib.pyplot.show", "pandas.read_csv", "strategy.standard_deviation.sd.cal_SD", "matplotlib.use", "strategy.standard_deviation.sd" ]
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from __future__ import print_function import sys from runstats import Statistics as FastStatistics from runstats import Regression as FastRegression from runstats.core import Statistics as CoreStatistics from runstats.core import Regression as CoreRegression from .test_runstats import mean, variance, stddev, skewnes...
[ "runstats.Regression", "runstats.core.Statistics", "runstats.core.Regression", "runstats.Statistics" ]
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import csv import dateutil.parser import os import splparser.parser from user import * from query import * from logging import getLogger as get_logger from os import path from splparser.exceptions import SPLSyntaxError, TerminatingSPLSyntaxError BYTES_IN_MB = 1048576 LIMIT = 2000*BYTES_IN_MB logger = get_logger("q...
[ "os.path.abspath", "csv.DictReader", "os.path.getsize", "os.walk", "logging.getLogger" ]
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#!python3 import numpy as np from magLabUtilities.optimizers.costFunctions import rmsNdNorm from magLabUtilities.signalutilities.signals import SignalThread, Signal, SignalBundle if __name__=='__main__': tThread = SignalThread(np.array([0,1,2], dtype=np.float64)) refM = SignalThread(np.array([0,1,2]...
[ "magLabUtilities.signalutilities.signals.Signal.fromThreadPair", "magLabUtilities.optimizers.costFunctions.rmsNdNorm", "numpy.array", "magLabUtilities.signalutilities.signals.SignalBundle" ]
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from typing import Dict import numpy def likelihood(simulated: Dict[int, int], realdata: Dict[int, int]): total_simulated = sum(simulated.values()) total_realdata = sum(realdata.values()) res = 0 for size, occur in realdata.items(): if occur == 0: continue if size not in simulated: continue res += ((...
[ "numpy.log" ]
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# Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the LICENSE # file in the root directory of this source tree. from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_li...
[ "mcrouter.test.MCProcess.Mcrouter" ]
[((788, 864), 'mcrouter.test.MCProcess.Mcrouter', 'Mcrouter', (['self.null_route_config'], {'extra_args': 'self.mcrouter_server_extra_args'}), '(self.null_route_config, extra_args=self.mcrouter_server_extra_args)\n', (796, 864), False, 'from mcrouter.test.MCProcess import Mcrouter\n')]
# terrascript/azure_preview/r.py # Automatically generated by tools/makecode.py () import warnings warnings.warn( "using the 'legacy layout' is deprecated", DeprecationWarning, stacklevel=2 ) import terrascript class azurepreview_budget(terrascript.Resource): pass class azurepreview_subscription(terrascri...
[ "warnings.warn" ]
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#!/usr/bin/env python3 """This routine parses plain-text parameter files that list runtime parameters for use in our codes. The general format of a parameter is: max_step integer 1 small_dt real 1.d-10 xlo_boundary_type ...
[ "argparse.ArgumentParser", "os.path.basename", "os.path.isfile", "re.findall", "sys.exit" ]
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import sys import os import time import imp import threading import traceback from utils import session from case_ble import def_ble from datetime import timedelta from datetime import datetime from case_ble import cmd_list import json g_sock_mobile = None g_sock_session = None g_q_mobile_rsp = ['BLEMobileRspQueue',...
[ "threading.Thread", "utils.session.q", "traceback.print_exc", "json.loads", "utils.session.bind", "utils.session.do_qinit", "utils.session.disconnect", "json.dumps", "time.sleep", "utils.session.get_host", "os._exit", "utils.session.do_qclr", "utils.session.connect", "utils.session.send", ...
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import time import json import base64 import redis import sys class Cloud_Event_Queue(): def __init__(self,redis): self.redis = redis def store_event_queue( self, event, data,status ="RED" ): log_data = {} log_data["event"] = event log_data["data"] = data log_da...
[ "redis.hincrby", "json.dumps", "time.time", "base64.b64encode", "redis.StrictRedis" ]
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#!/usr/bin/env python # coding: utf-8 # # Introduction to matplotlib # I find matplotlib more confusing than most Python tools, but it is very important to learn, because: # * matplotlib is the most widely used visualization library in Python. If you are reading someone else's code, there is a good chance you will un...
[ "matplotlib.pyplot.xlim", "matplotlib.pyplot.subplot", "matplotlib.pyplot.tight_layout", "matplotlib.pyplot.plot", "matplotlib.pyplot.close", "numpy.sin", "numpy.arange", "numpy.exp", "numpy.cos", "matplotlib.pyplot.subplots" ]
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from __future__ import annotations from pathlib import Path from typing import Optional import typer from biteme import pybites __all__ = ["cli"] cli = typer.Typer(context_settings={"auto_envvar_prefix": "PYBITES"}) @cli.command() def info(bite: int) -> None: bite_info = pybites._bite_info(bite) typer....
[ "typer.echo", "biteme.pybites._bite_info", "typer.Argument", "typer.Typer", "typer.Option", "biteme.pybites.download_bite" ]
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import unittest from typing import cast, List import icontract_hypothesis from icontract import require from python_by_contract_corpus.common import Lines from python_by_contract_corpus.correct.ethz_eprog_2019.exercise_02 import problem_02 class TestWithIcontractHypothesis(unittest.TestCase): def test_functions...
[ "unittest.main", "icontract_hypothesis.test_with_inferred_strategy", "typing.cast", "icontract.require", "python_by_contract_corpus.correct.ethz_eprog_2019.exercise_02.problem_02.draw" ]
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from timeit import Timer def bench(reps, setup, test): Timer(test, setup).timeit(reps) return int(Timer(test, setup).timeit(reps) * 1000)
[ "timeit.Timer" ]
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import torch import torch.autograd as autograd import torch.nn as nn import torch.optim as optim from transformers import BertModel import torch.nn.functional as F CLS = False class FT_Match(nn.Module): def __init__(self, args): super(FT_Match, self).__init__() self.BertM = BertM...
[ "torch.nn.Sequential", "torch.nn.LeakyReLU", "torch.nn.Linear", "transformers.BertModel.from_pretrained", "torch.nn.LSTM" ]
[((315, 361), 'transformers.BertModel.from_pretrained', 'BertModel.from_pretrained', (['"""bert-base-chinese"""'], {}), "('bert-base-chinese')\n", (340, 361), False, 'from transformers import BertModel\n'), ((419, 497), 'torch.nn.LSTM', 'nn.LSTM', ([], {'input_size': '(768)', 'hidden_size': '(768)', 'bidirectional': '(...
from __future__ import print_function import os # this perl command deletes all the comments in iriflip... # my compiler was having trouble with them, for some reason cmd = "perl -pi -e 's/![\.|-].*$//g' iriflip.for" print(cmd) os.system(cmd)
[ "os.system" ]
[((229, 243), 'os.system', 'os.system', (['cmd'], {}), '(cmd)\n', (238, 243), False, 'import os\n')]
# coding=utf-8 # Licensed Materials - Property of IBM # Copyright IBM Corp. 2018 from streamsx.spl import spl # Only loaded during extraction so spl.extracting() # should always be set. if not spl.extracting(): raise ValueError("spl.extacting is not true: " + str(spl.extracting()))
[ "streamsx.spl.spl.extracting" ]
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# -*- coding:utf-8 -*- """ 系统配置Model """ from django.db import models from codelieche.tools.password import Cryptography # from account.models import User class Config(models.Model): CATEGORY_CHOICES = ( ('text', '文本'), ('number', '数字'), ('int', '整数'), ('float', '浮点数'), (...
[ "django.db.models.TextField", "django.db.models.CharField", "django.db.models.BooleanField", "django.db.models.SlugField", "codelieche.tools.password.Cryptography" ]
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# -*- coding: utf-8 -*- """ Created on Tue Jan 26 13:26:40 2021 @author: rdavi Organize RAVDESS folders according to emotions """ # %% Imports import sys sys.path.append('..') import os import zipfile import shutil # %% Extract zip file def extract_zip(): path_raw = '../../data/raw/' with zipfile.ZipFile(p...
[ "sys.path.append", "os.mkdir", "zipfile.ZipFile", "os.makedirs", "os.walk", "os.path.exists", "os.replace", "shutil.rmtree" ]
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import os from enum import Enum from dotenv import load_dotenv load_dotenv() API_ID: str = os.getenv("API_ID") API_HASH: str = os.getenv("API_HASH") CHAT_NAME: list[str] = os.getenv("CHAT_NAME").split(":") CHAT_FORWARD_LIST: list[str] = os.getenv("CHAT_FORWARD_LIST").split(",") class Constants(Enum): API_ID = A...
[ "dotenv.load_dotenv", "os.getenv" ]
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import json import httplib import logging from urllib2 import build_opener, HTTPHandler, Request import boto3 logger = logging.getLogger() logger.setLevel(logging.INFO) def handler(event, context): logger.info('REQUEST RECEIVED:\n {}'.format(event)) logger.info('REQUEST RECEIVED:\n {}'.format(context)) # ...
[ "logging.getLogger", "boto3.client" ]
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# Copyright 2020 Catalyst Cloud # # 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 agre...
[ "oslo_log.log.getLogger", "time.sleep" ]
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from __future__ import print_function import boto3 def lambda_handler(event, context): '''forward all incoming requests to SNS ''' print(str(event)) boto3.client('sns').publish( TopicArn='arn:aws:sns:REGION:ACCOUNT_ID:pingonMe', Message='Check pingon.me!\n\n{0}'.format(str(event)) ...
[ "boto3.client" ]
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#!/usr/bin/env python import argparse import json import requests import sys import pdpyras def find_shifts(session, vacationing_user, start, end, schedule_ids): """Find all on-call shifts on the specified schedules between `since` and `until`""" params = {"since": start, "until": end} shifts = {} # L...
[ "pdpyras.APISession", "argparse.ArgumentParser" ]
[((1012, 1308), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""For a given user going on vacation, and another given user who will fill their shoes while away, create overrides on all the vacationing user\'s schedules, such that the replacement user covers all the shifts that the vacatio...
# coding: utf-8 """ FreeClimb API FreeClimb is a cloud-based application programming interface (API) that puts the power of the Vail platform in your hands. FreeClimb simplifies the process of creating applications that can use a full range of telephony features without requiring specialized or on-site teleph...
[ "freeclimb.configuration.Configuration", "six.iteritems" ]
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import glob import os from pomodoro_timer.configs.main_configs import IMG_TEMP_DIR def remove_temp_img(): files = glob.glob(os.path.join(IMG_TEMP_DIR, "*")) for f in files: os.remove(f)
[ "os.remove", "os.path.join" ]
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# -*- coding: utf-8 -*- ''' Created on Mar 11, 2012 @author: moloch Copyright 2012 Root the Box 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/licen...
[ "uuid.uuid4", "sqlalchemy.types.String", "models.dbsession.query", "netaddr.IPAddress", "sqlalchemy.ForeignKey", "xml.etree.cElementTree.SubElement" ]
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import pytest from test import test_common test_definitions = { "test/struct_initializer.cu": ['somekernel', 'somekernel2', 'getFooValue', 'getBarValue'], "test/phiaddressspace.cu": ['mykernel'], "test/test_local.cu": ['testLocal', 'testLocal2'], "test/pointerpointer.cu": ['mykernel', 'myte6kernel'] }...
[ "test.test_common.build_kernel", "pytest.mark.xfail", "test.test_common.cu_to_cl" ]
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# Copyright (c) 2019 <NAME>, <NAME>, <NAME>, <NAME>, <NAME> # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, this ...
[ "h5py.File" ]
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# Module: hibernate # Description: Hibernates the system # Usage: !hibernate or !hibernate secondsToHibernation # Dependencies: time, os import time, os, asyncio, configs async def hibernate(ctx, seconds=0): await ctx.send("Hibernating system.") if configs.operating_sys == "Windows": if time != 0: ...
[ "os.system", "asyncio.sleep", "time.sleep" ]
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import json import torch from flask import Flask, request, jsonify from prometheus_flask_exporter.multiprocess import GunicornInternalPrometheusMetrics from prometheus_client import Counter app = Flask(__name__, static_url_path="") metrics = GunicornInternalPrometheusMetrics(app) PREDICTION_COUNT = Counter("predicti...
[ "prometheus_flask_exporter.multiprocess.GunicornInternalPrometheusMetrics", "flask.Flask", "flask.jsonify", "prometheus_client.Counter", "torch.jit.load", "flask.request.get_json", "torch.tensor" ]
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import pytest from pybrary.databrary.types.gender import Gender from pybrary.databrary.types.ethnicity import Ethnicity from pybrary.databrary.types.race import Race from pybrary.databrary.participant import Participant @pytest.fixture def expected_participant_dict(): return { "key": "2631", "ID"...
[ "pytest.raises", "pybrary.databrary.participant.Participant.from_databrary", "pybrary.databrary.participant.Participant" ]
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import gc import sys sys.path.append('taming-transformers') from omegaconf import OmegaConf from taming.models import cond_transformer, vqgan import torch class VqganHelper: gumbel: bool def __init__(self): self.gumbel = False def load_vqgan_model(self, config_path, checkpoint_path): s...
[ "sys.path.append", "taming.models.cond_transformer.Net2NetTransformer", "omegaconf.OmegaConf.load", "taming.models.vqgan.GumbelVQ", "gc.collect", "torch.cuda.empty_cache", "taming.models.vqgan.VQModel" ]
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""" Distributed under the terms of the BSD 3-Clause License. The full license is in the file LICENSE, distributed with this software. Author: <NAME> <<EMAIL>>, <NAME> <<EMAIL>> Copyright (C) European X-Ray Free-Electron Laser Facility GmbH. All rights reserved. """ from collections import OrderedDict import json fr...
[ "PyQt5.QtWidgets.QComboBox", "PyQt5.QtWidgets.QLabel", "json.loads", "PyQt5.QtWidgets.QTableWidget", "PyQt5.QtWidgets.QGridLayout", "PyQt5.QtGui.QDoubleValidator", "PyQt5.QtWidgets.QPushButton", "PyQt5.QtWidgets.QCheckBox", "PyQt5.QtWidgets.QFileDialog.getOpenFileName", "collections.OrderedDict" ]
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# Copyright 2015 The TensorFlow Authors. 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 applica...
[ "numpy.ones_like", "matplotlib.pyplot.legend", "numpy.array", "numpy.exp", "numpy.convolve", "matplotlib.pyplot.xlabel", "matplotlib.pyplot.grid" ]
[((1390, 1411), 'numpy.exp', 'np.exp', (['(-(x / 5) ** 2)'], {}), '(-(x / 5) ** 2)\n', (1396, 1411), True, 'import numpy as np\n'), ((1422, 1438), 'numpy.array', 'np.array', (['values'], {}), '(values)\n', (1430, 1438), True, 'import numpy as np\n'), ((1451, 1471), 'numpy.ones_like', 'np.ones_like', (['values'], {}), '...
from django.conf import settings from django.dispatch import receiver from rosetta.signals import post_save @receiver(post_save) def restart_server(sender, **kwargs): """ Restart server after rosetta translations fix. """ import os os.system(f"kill -HUP `cat {settings.GUNICORN_PID}`")
[ "django.dispatch.receiver", "os.system" ]
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''' Main python function to utilize MLR (Multiple Linear Regression) on the stock data being stored in our DB. First, the user will select a company that they want to analyze. Then, the data will be transformed, cleaned, and then sent to the MLR for analyzing. From here, we can check how well the MLR did with predicti...
[ "source.helper.query_data_to_df", "source.multiple_linear_regression.MultipleLinearRegression", "source.helper.split_data", "data.database.StockDB", "source.helper.df_to_train_dataset" ]
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# Copyright (c) 2013, GPy authors (see AUTHORS.txt). # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np from ..core.mapping import Mapping class Linear(Mapping): """ Mapping based on a linear model. .. math:: f(\mathbf{x}*) = \mathbf{W}\mathbf{x}^* + \mathbf{b} :p...
[ "numpy.dot", "numpy.sqrt", "numpy.array", "numpy.random.randn" ]
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# -*- coding: utf-8 -*- """ models.meta ~~~~~~~~~~~ Meta models. """ from .core import BaseModel, ORMMeta from schematics.types import ( # NOQA StringType, BooleanType, DateTimeType, IntType, UUIDType ) class Declaration(BaseModel, metaclass=ORMMeta): """Various declarations of a conflict of i...
[ "schematics.types.StringType" ]
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import numpy as np from sklearn.datasets import make_classification from sklearn.mixture import GMM from sklearn.preprocessing import StandardScaler from sklearn import svm def fvecs_read(filename, c_contiguous=True): fv = np.fromfile(filename, dtype=np.float32) if fv.size == 0: return np.zeros((0, 0)...
[ "numpy.sum", "sklearn.preprocessing.StandardScaler", "numpy.abs", "numpy.fromfile", "sklearn.mixture.GMM", "sklearn.datasets.make_classification", "numpy.zeros", "numpy.isnan", "numpy.sign", "sklearn.svm.LinearSVC", "numpy.dot", "numpy.sqrt", "numpy.atleast_2d" ]
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""" Module for keysight devices, like e.g. oscilloscopes. File name: keysight.py Author: <NAME>, <NAME> Date created: 2020/11/11 Python Version: 3.7 """ from typing import NamedTuple, Tuple, get_type_hints import re import pyvisa as visa import numpy as np from ._mock.keysight import PyvisaDummy class Preamble(Name...
[ "pyvisa.ResourceManager", "numpy.arange", "re.match", "typing.get_type_hints" ]
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# Copyright 2014 DreamHost, LLC # # Author: DreamHost, 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 # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
[ "django.utils.translation.ugettext", "django.template.loader.render_to_string", "logging.getLogger" ]
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from flask import Flask from flask_sqlalchemy import SQLAlchemy from flask_bcrypt import Bcrypt from flask_login import LoginManager import os from sqlalchemy_utils import create_database, database_exists app = Flask(__name__) # configure Flask using environment variables # app.config.from_pyfile("config.py") # not u...
[ "flask.Flask", "os.environ.get", "flask_sqlalchemy.SQLAlchemy", "flask_bcrypt.Bcrypt", "flask_login.LoginManager" ]
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import secrets from typing import Tuple import cipher_common import gcd from sm2_common import * # inferred from sm2_common.n _pt_chunk_length = 31 _ct_chunk_length = 96 _byte_int_conversion_endian = 'big' _p = 265371653 _g = 2 def gen_key() -> Tuple[fp, ECPoint]: # [0, n - 1) -> [1, n) x = secrets.randbel...
[ "cipher_common.decrypt_file", "secrets.randbelow", "cipher_common.encrypt_file", "gcd.get_modular_inverse" ]
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from django.contrib import admin # Register your models here. from .models import Music admin.site.register(Music)
[ "django.contrib.admin.site.register" ]
[((90, 116), 'django.contrib.admin.site.register', 'admin.site.register', (['Music'], {}), '(Music)\n', (109, 116), False, 'from django.contrib import admin\n')]
from guardian.admin import GuardedModelAdmin from django.utils.translation import gettext as _ from user.admin import fileshare_site from permission.models import BigUserObjectPermission class ObjectAdminPermissions(GuardedModelAdmin): list_display = ('id', 'object_pk', 'permission') search_fields = ('objec...
[ "user.admin.fileshare_site.register" ]
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"""entry point to run all tests""" import distutils.util import os.path import sys import unittest if __name__ == '__main__': plat_specifier = 'lib.{0}-{1}'.format(distutils.util.get_platform(), sys.version[0:3]) tests_dir = os.path.dirname(os.path.abspath(__file__)) ...
[ "unittest.main" ]
[((839, 854), 'unittest.main', 'unittest.main', ([], {}), '()\n', (852, 854), False, 'import unittest\n')]
import librosa import numpy as np import seaborn as sns import matplotlib.pyplot as plt import os import time import multiprocessing import pickle import torch from data_tools import extract_features def smoothing_v1(label): smoothed_label = [] # Smooth with 3 consecutive windows for i in range(2, len(la...
[ "pickle.dump", "matplotlib.pyplot.figure", "torch.device", "os.path.join", "multiprocessing.cpu_count", "matplotlib.pyplot.close", "torch.load", "matplotlib.pyplot.yticks", "data_tools.extract_features", "matplotlib.pyplot.xticks", "seaborn.set", "matplotlib.pyplot.show", "torch.max", "tor...
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# -*- coding: utf-8 -*- # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- # vi: set ft=python sts=4 ts=4 sw=4 et: from uuid import uuid5 import logging from pathlib import Path from nipype.pipeline import engine as pe from fmriprep import config from .factory import FactoryContext from .mriqc...
[ "pathlib.Path", "uuid.uuid5", "logging.getLogger" ]
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# Copyright 2017 QuantRocket - 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 ...
[ "quantrocket.houston.houston.raise_for_status_with_json", "quantrocket.cli.utils.output.json_to_cli" ]
[((1300, 1344), 'quantrocket.houston.houston.raise_for_status_with_json', 'houston.raise_for_status_with_json', (['response'], {}), '(response)\n', (1334, 1344), False, 'from quantrocket.houston import houston\n'), ((1880, 1924), 'quantrocket.houston.houston.raise_for_status_with_json', 'houston.raise_for_status_with_j...
# coding=utf-8 from django.contrib import admin from models import Post # Register your models here. admin.site.register(Post)
[ "django.contrib.admin.site.register" ]
[((102, 127), 'django.contrib.admin.site.register', 'admin.site.register', (['Post'], {}), '(Post)\n', (121, 127), False, 'from django.contrib import admin\n')]
''' Created on Nov 23, 2021 @author: mballance ''' import os import subprocess from typing import List from mkdv.job_spec import JobSpec from mkdv.runners.allure_reporter import AllureReporter from mkdv.runners.runner import Runner from mkdv.runners.runner_spec import RunnerSpec from allure_commons.model2 import Stat...
[ "copy.deepcopy", "subprocess.Popen", "mkdv.runners.allure_reporter.AllureReporter", "os.getcwd", "os.path.join" ]
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import cv2 import os import pickle dataset = list() dataset_test = list() # dataset = pickle.load(open('/Users/michaelshan/Documents/BUAA/实验室项目/data_yinlie.pkl','rb')) img_cnt = 0 for root, dirs, files in os.walk('/home/syb/documents/Crack_Image_WSOD/data/cut/0/'): for file in files: # for macos i...
[ "cv2.ximgproc.segmentation.createSelectiveSearchSegmentation", "cv2.imread", "os.walk", "cv2.resize" ]
[((207, 266), 'os.walk', 'os.walk', (['"""/home/syb/documents/Crack_Image_WSOD/data/cut/0/"""'], {}), "('/home/syb/documents/Crack_Image_WSOD/data/cut/0/')\n", (214, 266), False, 'import os\n'), ((2693, 2752), 'os.walk', 'os.walk', (['"""/home/syb/documents/Crack_Image_WSOD/data/cut/1/"""'], {}), "('/home/syb/documents...
from sklearn.preprocessing import LabelBinarizer, MultiLabelBinarizer from .BaseEncoder import BaseEncoder # This is a copy and paste of tfidf_extractor.py with some code moving, testing for the moment class GenericLabelBinarizer(BaseEncoder): _is_multiclass = None _is_multilabel = None _encoder = None ...
[ "sklearn.preprocessing.LabelBinarizer", "sklearn.preprocessing.MultiLabelBinarizer" ]
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#Import dependencies import numpy as np import sqlalchemy from sqlalchemy.ext.automap import automap_base from sqlalchemy.orm import Session from sqlalchemy import create_engine, func #Use Flask to create your routes. from flask import Flask, jsonify #Home page. engine = create_engine("sqlite:///Resources/hawaii.sq...
[ "numpy.ravel", "flask.Flask", "sqlalchemy.orm.Session", "flask.jsonify", "sqlalchemy.create_engine", "sqlalchemy.ext.automap.automap_base" ]
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import time import asyncio start = time.time() def tic(): return 'at %1.1f seconds' % (time.time() - start) async def gr1(): # Busy waits for a second, but we don't want to stick around... print('gr1 started work: {}'.format(tic())) await asyncio.sleep(2) print('gr1 ended work: {}'.format(tic()...
[ "asyncio.sleep", "asyncio.get_event_loop", "asyncio.wait", "time.time" ]
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#!/usr/bin/python import re class Printer: def __init__(self): self.r_file = open("ThostFtdcUserApiStruct.h") self.o_file = open('ThostFtdcUserApiStructPrint.hh', 'wb') self.struct_status = False self.stru_name = '' self.obj_name = '' def fileHead(self): self.o...
[ "re.compile" ]
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# Copyright (c) 2021 PaddlePaddle Authors. 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 appli...
[ "tqdm.tqdm", "numpy.load", "sklearn.preprocessing.StandardScaler", "argparse.ArgumentParser", "logging.info", "pathlib.Path", "jsonlines.open", "paddlespeech.t2s.datasets.data_table.DataTable", "operator.itemgetter" ]
[((2270, 2399), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Normalize dumped raw features (See detail in parallel_wavegan/bin/normalize.py)."""'}), "(description=\n 'Normalize dumped raw features (See detail in parallel_wavegan/bin/normalize.py).'\n )\n", (2293, 2399), False, 'i...
from angr.state_plugins import SimSolver from archinfo.arch_amd64 import ArchAMD64 import claripy import copy import datetime import itertools import os from pathlib import Path from kalm import utils from kalm.plugins.sizes import SizesPlugin from kalm.solver import KalmSolver from klint import ghostmap...
[ "copy.deepcopy", "archinfo.arch_amd64.ArchAMD64", "klint.statistics.work_start", "klint.statistics.work_end", "itertools.count", "kalm.plugins.sizes.SizesPlugin", "pathlib.Path", "angr.state_plugins.SimSolver", "klint.verif.symbex.symbex", "datetime.datetime.now", "kalm.solver.KalmSolver" ]
[((1763, 1787), 'itertools.count', 'itertools.count', (['(1000000)'], {}), '(1000000)\n', (1778, 1787), False, 'import itertools\n'), ((2263, 2293), 'klint.statistics.work_start', 'statistics.work_start', (['"""verif"""'], {}), "('verif')\n", (2284, 2293), False, 'from klint import statistics\n'), ((2486, 2553), 'klint...
#!/usr/bin/env python3 # coding: utf-8 # # © 2021 Qualcomm Innovation Center, Inc. All rights reserved. # # SPDX-License-Identifier: BSD-3-Clause """ Top-level configuration file for Gunyah build system. This module constructs an instance of AbstractBuildGraph, and passes it to the real build system which is in tools...
[ "json.dump", "os.makedirs", "os.getcwd", "os.path.dirname", "runpy.run_path", "pipes.quote", "os.path.relpath", "os.path.normpath", "os.path.join", "re.sub", "re.compile" ]
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import torch.nn as nn def get_loss_function(loss_type: str = "cross_entropy_loss"): if loss_type == "cross_entropy_loss": return nn.CrossEntropyLoss() else: raise NotImplmentedError(f"loss type: {loss_type} not implemented")
[ "torch.nn.CrossEntropyLoss" ]
[((144, 165), 'torch.nn.CrossEntropyLoss', 'nn.CrossEntropyLoss', ([], {}), '()\n', (163, 165), True, 'import torch.nn as nn\n')]
""" Trains a network-enhanced autoencoder (netAE) for semi-supervised dimensionality reduction of single-cell RNA-sequencing. @author: <NAME> @contact: <EMAIL> @date: 10/16/2019 """ import numpy as np import torch import torch.nn as nn import torch.optim as optim import argparse # define device # make sure to conver...
[ "torch.LongTensor", "torch.optim.lr_scheduler.ReduceLROnPlateau", "data.Dataset", "torch.save", "torch.cuda.is_available", "torch.no_grad" ]
[((394, 419), 'torch.cuda.is_available', 'torch.cuda.is_available', ([], {}), '()\n', (417, 419), False, 'import torch\n'), ((3801, 3963), 'torch.optim.lr_scheduler.ReduceLROnPlateau', 'optim.lr_scheduler.ReduceLROnPlateau', (['optimizer'], {'mode': '"""min"""', 'factor': 'lr_decay', 'patience': '(5)', 'verbose': '(Tru...
from __future__ import annotations import os import sys from argparse import ArgumentParser from pathlib import Path from typing import Any import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sns from scipy.stats import exponnorm, gamma, lognorm, norm from clovars.utils import Qu...
[ "seaborn.lineplot", "seaborn.kdeplot", "argparse.ArgumentParser", "numpy.amin", "matplotlib.pyplot.ylim", "pandas.read_csv", "numpy.roll", "os.path.exists", "numpy.amax", "pandas.read_excel", "pathlib.Path", "numpy.histogram", "matplotlib.pyplot.subplots" ]
[((810, 826), 'pathlib.Path', 'Path', (['input_file'], {}), '(input_file)\n', (814, 826), False, 'from pathlib import Path\n'), ((1332, 1348), 'argparse.ArgumentParser', 'ArgumentParser', ([], {}), '()\n', (1346, 1348), False, 'from argparse import ArgumentParser\n'), ((5077, 5109), 'numpy.histogram', 'np.histogram', (...
from django.urls import path # from .views import AboutUs, Home from .views import * urlpatterns = [ path('', Home, name='home-page'), # http://localhost:8000/ path('about/', AboutUs, name='about-page'), # http://localhost:8000/about/ path('contact/', ContactUs, name='contact-page'), ]
[ "django.urls.path" ]
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""" Definition of the :class:`DataAcquisitionViewSet` class. """ from django.conf import settings from django.contrib.contenttypes.models import ContentType from django.db.models.query import QuerySet from pylabber.views.defaults import DefaultsMixin from research.filters.data_acquisition_filter import DataAcquisitionF...
[ "research.utils.data_acquisition_models.get_data_acquisition_models", "django.contrib.contenttypes.models.ContentType.objects.all" ]
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import os from unittest import TestCase TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "files") class BaseTestCase(TestCase): def _create_file(self, filename, content=""): self.files.append(filename) with open(filename, "a") as file_: file_.write(content) def setUp(self...
[ "os.path.dirname", "os.remove" ]
[((71, 96), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (86, 96), False, 'import os\n'), ((367, 392), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (382, 392), False, 'import os\n'), ((500, 519), 'os.remove', 'os.remove', (['filename'], {}), '(filename)\n', (509...
from django.db import models from phonenumber_field.modelfields import PhoneNumberField class CustomerDetails(models.Model): """ Stores the information about all the customers """ name = models.CharField(max_length=20, unique=True) first_name = models.CharField(max_length=30) telephone_number ...
[ "django.db.models.CharField", "django.db.models.DateTimeField", "django.db.models.DateField", "phonenumber_field.modelfields.PhoneNumberField" ]
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import pytest import unipixel from . import utils PARAMS = utils.product_dict(**{ "pin": [None], "n": [16], "auto_write": [True, False], "bpp": [3, 4], "pixel_order": [unipixel.RGB, unipixel.GRB, unipixel.RGBW, unipixel.GRBW, None] }) @pytest.fixture(params=PARAMS) def test_strip(request): p...
[ "unipixel.UniPixel", "pytest.fixture" ]
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import numpy as np from core.ukf import build_ekf, build_ukf, get_QR class VGraph(object): """ Simple wrapper for visibility graph """ # TODO : unify dynamic container interface or something. # (i.e. with Landmarks() ) def __init__(self, cvt, cap0=1024): # processing handle self.cvt_ = ...
[ "numpy.random.uniform", "core.ukf.build_ekf", "numpy.empty", "numpy.float32", "numpy.asarray", "numpy.argsort", "numpy.where", "numpy.linalg.norm", "numpy.arange", "numpy.int32", "core.ukf.get_QR", "numpy.cos", "numpy.sin", "numpy.matmul", "numpy.unique" ]
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from lesion_coder import utils from lesion_coder.dataset import ImageData from lesion_coder.model import BaseAutoEncoder import pandas as pd import torch import torch.nn as nn import argparse import os from tqdm import tqdm import time from torchvision.utils import save_image from test import test import matplotlib.pyp...
[ "matplotlib.pyplot.title", "lesion_coder.utils.get_train_transform", "argparse.ArgumentParser", "lesion_coder.model.BaseAutoEncoder", "pandas.read_csv", "time.strftime", "torch.cat", "matplotlib.pyplot.figure", "torch.device", "torch.no_grad", "os.path.join", "pandas.DataFrame", "torch.nn.MS...
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import os import numpy as np import time from algs.aecnn.genetic.population import Population, Individual, DenseUnit, ResUnit, PoolUnit from compute.file import get_algo_local_dir from comm.log import Log import platform from algs.aecnn.genetic.statusupdatetool import StatusUpdateTool class Utils(object): @classm...
[ "algs.aecnn.genetic.statusupdatetool.StatusUpdateTool.get_input_size", "time.strftime", "algs.aecnn.genetic.population.DenseUnit", "algs.aecnn.genetic.population.Individual", "os.path.dirname", "os.path.exists", "compute.file.get_algo_local_dir", "numpy.max", "algs.aecnn.genetic.statusupdatetool.Sta...
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import hashlib import time from Crypto.Cipher import AES import base64 def user_sign_api(data, private_key): """ 用户签名+时间戳 md5加密 :param data: :param private_key: :return: """ api_key = private_key # 当前时间 now_time = time.time() client_time = str(now_time).split('.')[0] # si...
[ "base64.urlsafe_b64encode", "hashlib.md5", "Crypto.Cipher.AES.new", "time.time" ]
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# -*- coding: utf-8 -*- import logging import os import sys from logging.config import dictConfig from scrapy.settings import Settings from scrapy.utils.log import DEFAULT_LOGGING, TopLevelFormatter from twisted.python import log from twisted.python.log import startLoggingWithObserver from twisted.python.logfile impor...
[ "twisted.python.log.err", "logging.NullHandler", "os.path.join", "twisted.python.log.startLoggingWithObserver", "logging.FileHandler", "twisted.python.log.FileLogObserver.emit", "os.path.exists", "logging.root.setLevel", "twisted.python.log.msg", "scrapy.settings.Settings", "logging.StreamHandle...
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import argparse import sys import runpy from aocd import get_data parser = argparse.ArgumentParser(description="Process some integers.") parser.add_argument("--year", "-y", type=int, default=2021) parser.add_argument("--day", "-d", type=int) parser.add_argument("--file", "-f", type=argparse.FileType("r")) args = par...
[ "runpy.importlib.import_module", "argparse.ArgumentParser", "aocd.get_data", "argparse.FileType" ]
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""" Base class for Mask objects. Contains many common utilities used for accessing masks. The mask itself is represented under the hood as a three dimensional numpy :obj:`ndarray` object. The dimensions are ``[NUM_FREQ, NUM_HOPS, NUM_CHAN]``. Safe accessors for these array indices are in :ref:`constants` as well as b...
[ "numpy.array_equal", "numpy.ones", "numpy.zeros", "numpy.expand_dims" ]
[((6801, 6838), 'numpy.array_equal', 'np.array_equal', (['self.mask', 'other.mask'], {}), '(self.mask, other.mask)\n', (6815, 6838), True, 'import numpy as np\n'), ((2584, 2637), 'numpy.expand_dims', 'np.expand_dims', (['value'], {'axis': 'constants.STFT_CHAN_INDEX'}), '(value, axis=constants.STFT_CHAN_INDEX)\n', (2598...
# !/usr/bin/python # -*- coding: utf-8 -*- import os import logging import hashlib import pybpodgui_api from pybpodgui_api.utils.send2trash_wrapper import send2trash from sca.formats import json from pybpodgui_api.models.project.project_base import ProjectBase logger = logging.getLogger(__name__) class ProjectIO(P...
[ "os.makedirs", "os.path.basename", "os.path.exists", "os.path.isfile", "pybpodgui_api.utils.send2trash_wrapper.send2trash", "sca.formats.json.load", "sca.formats.json.dump", "os.path.join", "os.listdir", "logging.getLogger" ]
[((273, 300), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (290, 300), False, 'import logging\n'), ((876, 906), 'os.path.basename', 'os.path.basename', (['project_path'], {}), '(project_path)\n', (892, 906), False, 'import os\n'), ((1195, 1227), 'os.path.join', 'os.path.join', (['self.p...
import cv2 import numpy as np import asyncio from cursor_func import cursorControl from unified_detector import Fingertips from hand_detector.detector import SOLO, YOLO status = False hand_detection_method = 'yolo' if hand_detection_method is 'solo': hand = SOLO(weights='weights/solo.h5', threshold=0.8) elif han...
[ "asyncio.get_event_loop", "hand_detector.detector.SOLO", "cursor_func.cursorControl", "cv2.waitKey", "numpy.asarray", "cv2.imshow", "cv2.VideoCapture", "numpy.mean", "cv2.rectangle", "unified_detector.Fingertips", "cv2.destroyAllWindows", "hand_detector.detector.YOLO" ]
[((564, 605), 'unified_detector.Fingertips', 'Fingertips', ([], {'weights': '"""weights/classes8.h5"""'}), "(weights='weights/classes8.h5')\n", (574, 605), False, 'from unified_detector import Fingertips\n'), ((613, 632), 'cv2.VideoCapture', 'cv2.VideoCapture', (['(0)'], {}), '(0)\n', (629, 632), False, 'import cv2\n')...
from PyQt4 import QtGui import sys app = QtGui.QApplication(sys.argv) w = QtGui.QWidget() w.resize(250, 150) w.move(300, 300) w.setWindowTitle('Simple') w.show() tuopan = QtGui.QSystemTrayIcon(w) icon1 = QtGui.QIcon('tuopan.jpg') tuopan.setIcon(icon1) tuopan.show() tuopan.showMessage("haha","content...
[ "PyQt4.QtGui.QSystemTrayIcon", "PyQt4.QtGui.QIcon", "PyQt4.QtGui.QApplication", "PyQt4.QtGui.QWidget" ]
[((45, 73), 'PyQt4.QtGui.QApplication', 'QtGui.QApplication', (['sys.argv'], {}), '(sys.argv)\n', (63, 73), False, 'from PyQt4 import QtGui\n'), ((81, 96), 'PyQt4.QtGui.QWidget', 'QtGui.QWidget', ([], {}), '()\n', (94, 96), False, 'from PyQt4 import QtGui\n'), ((187, 211), 'PyQt4.QtGui.QSystemTrayIcon', 'QtGui.QSystemT...
from dateutil.parser import parse from datetime import timedelta from . import ForecastMixin class Forecast(ForecastMixin): url = 'https://opendata.atmo-na.org/api/v1/indice/atmo/' zone_type = 'insee' insee_list = ['33063', '79005', '16102', '64102', '64445', '19272', '87085', '24322', '40088', '17...
[ "dateutil.parser.parse", "datetime.timedelta" ]
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#!/usr/bin/env python # Copyright (c) 2012 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Unit tests for classes in chromium_utils.py.""" import os import sys import tempfile import unittest import test_env # pylint...
[ "unittest.main", "tempfile.NamedTemporaryFile", "os.remove", "common.chromium_utils.RunCommand", "common.chromium_utils.GetBotsFromBuildersFile" ]
[((6900, 6915), 'unittest.main', 'unittest.main', ([], {}), '()\n', (6913, 6915), False, 'import unittest\n'), ((1168, 1254), 'common.chromium_utils.RunCommand', 'chromium_utils.RunCommand', (['mycmd'], {'print_cmd': '(False)', 'parser_func': 'parser.ProcessLine'}), '(mycmd, print_cmd=False, parser_func=parser.\n Pr...
#!/usr/bin/env python """TODO: place all consensus methods here load_consensus_map make_consensus_tree etc... """ from t2t.nlevel import RANK_ORDER from numpy import zeros, where, logical_or, long def taxa_score(master, reps): """Score taxa strings by contradictions observed in reps""" n_ranks = len(RANK_OR...
[ "numpy.logical_or" ]
[((2013, 2063), 'numpy.logical_or', 'logical_or', (['(rep_hash == master_hash)', '(rep_hash == 0)'], {}), '(rep_hash == master_hash, rep_hash == 0)\n', (2023, 2063), False, 'from numpy import zeros, where, logical_or, long\n')]
import asyncio from .protocol import SseServerProtocol __all__ = ['serve'] @asyncio.coroutine def serve(sse_handler, host=None, port=None, *, klass=SseServerProtocol, **kwargs): return (yield from asyncio.get_event_loop().create_server( lambda: klass(sse_handler), host, port, **kwargs))
[ "asyncio.get_event_loop" ]
[((215, 239), 'asyncio.get_event_loop', 'asyncio.get_event_loop', ([], {}), '()\n', (237, 239), False, 'import asyncio\n')]
from collections import namedtuple from typing import NamedTuple from pybaum.typecheck import get_type def test_namedtuple_is_discovered(): bla = namedtuple("bla", ["a", "b"])(1, 2) assert get_type(bla) == namedtuple def test_typed_namedtuple_is_discovered(): class Blubb(NamedTuple): a: int ...
[ "pybaum.typecheck.get_type", "collections.namedtuple" ]
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""" Created: 04 May 2020 Author: <NAME> """ from administration.models import ArtistAnalyticsCalculation # ----------------------------------------------------------------------------- def retrieve_calculation(calculation_name, default=None): try: calc = ArtistAnalyticsCalculation.objects.get(name=calcul...
[ "administration.models.ArtistAnalyticsCalculation.objects.get" ]
[((270, 331), 'administration.models.ArtistAnalyticsCalculation.objects.get', 'ArtistAnalyticsCalculation.objects.get', ([], {'name': 'calculation_name'}), '(name=calculation_name)\n', (308, 331), False, 'from administration.models import ArtistAnalyticsCalculation\n')]
from discord.ext import commands import dice class Roll(commands.Cog): def __init__(self, bot): self.bot = bot @commands.command() async def roll(self, ctx, arg): try: await ctx.send(dice.roll(arg)) except dice.DiceBaseException as e: print(e.pretty_print())
[ "discord.ext.commands.command", "dice.roll" ]
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