uid stringlengths 24 24 | split stringclasses 1
value | category stringclasses 2
values | content stringlengths 5 482k | signature stringlengths 1 14k | suffix stringlengths 1 482k | prefix stringlengths 9 14k | prefix_token_count int64 3 5.01k | prefix_token_budget int64 64 256 | element_token_count int64 1 292k | signature_token_count int64 1 5.01k | prefix_context_token_count int64 0 255 | repo stringlengths 7 112 | path stringlengths 4 208 | language stringclasses 1
value | name stringlengths 1 218 | qualname stringlengths 1 218 | start_line int64 1 26.7k | end_line int64 1 26.7k | signature_start_line int64 1 26.7k | signature_end_line int64 1 26.7k | source_hash stringlengths 40 40 | source_dataset stringclasses 1
value | source_split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1d938643f65b54f7f885c268 | train | class | class TestVagrantBaseBoxes(TestCase):
def test_vagrant_base_boxes(self):
with patch('burlap.vagrant.vagrant._box_list') as mock_list:
mock_list.return_value = [
('lucid32', 'virtualbox'),
('precise64', 'virtualbox'),
]
from burlap.vagrant ... | class TestVagrantBaseBoxes(TestCase):
| def test_vagrant_base_boxes(self):
with patch('burlap.vagrant.vagrant._box_list') as mock_list:
mock_list.return_value = [
('lucid32', 'virtualbox'),
('precise64', 'virtualbox'),
]
from burlap.vagrant import vagrant
self.assertE... | ")
from burlap.vagrant import vagrant
res = vagrant._box_list_human_readable()
self.assertEqual(res, [
# ('lucid32', 'virtualbox'),
('precise64', 'virtualbox'),
])
class TestVagrantBaseBoxes(TestCase):
| 63 | 64 | 95 | 9 | 54 | tutordelphia/burlap | burlap/tests/test_vagrant_base_boxes.py | Python | TestVagrantBaseBoxes | TestVagrantBaseBoxes | 55 | 64 | 55 | 56 | 5589e508d42030563b93ed062b9a621a8869720c | bigcode/the-stack | train |
0bf72fe9bc7abdd28389c945 | train | function | def get_json_builder(obj):
"""Instantiate or retrieve a JSON representation builder for the given
object.
"""
if type(obj) is type:
cls = obj
else:
cls = obj.__class__
# Lookup the builder instance in the builder module
builder = getattr(ggrc.builder, cls.__name__, None)
if not builder:
# Cr... | def get_json_builder(obj):
| """Instantiate or retrieve a JSON representation builder for the given
object.
"""
if type(obj) is type:
cls = obj
else:
cls = obj.__class__
# Lookup the builder instance in the builder module
builder = getattr(ggrc.builder, cls.__name__, None)
if not builder:
# Create the builder and cache ... | RelationshipProperty
from werkzeug.exceptions import BadRequest
"""JSON resource state representation handler for gGRC models."""
def view_url_for(obj):
view = getattr(ggrc.views, obj.__class__.__name__, None)
return view.url_for(obj) if view else None
def get_json_builder(obj):
| 64 | 64 | 114 | 6 | 57 | alaeddine10/ggrc-core | src/ggrc/builder/json.py | Python | get_json_builder | get_json_builder | 25 | 39 | 25 | 25 | b45d11fb8eaf1c817508a979e6d748af169cb619 | bigcode/the-stack | train |
386fc05bd359c659dced80c7 | train | function | def publish(obj, inclusions=()):
"""Translate ``obj`` into a valid JSON value. Objects with properties are
translated into a ``dict`` object representing a JSON object while simple
values are returned unchanged or specially formatted if needed.
"""
publisher = get_json_builder(obj)
if publisher and hasattr(... | def publish(obj, inclusions=()):
| """Translate ``obj`` into a valid JSON value. Objects with properties are
translated into a ``dict`` object representing a JSON object while simple
values are returned unchanged or specially formatted if needed.
"""
publisher = get_json_builder(obj)
if publisher and hasattr(publisher, '_publish_attrs') \
... | builder = getattr(ggrc.builder, cls.__name__, None)
if not builder:
# Create the builder and cache it in the builder module
builder = Builder(cls)
setattr(ggrc.builder, cls.__name__, builder)
return builder
def publish(obj, inclusions=()):
| 64 | 64 | 165 | 8 | 55 | alaeddine10/ggrc-core | src/ggrc/builder/json.py | Python | publish | publish | 41 | 59 | 41 | 41 | fc4e15d6fe691a208383519a3e27962000b12c14 | bigcode/the-stack | train |
57f2ed4db40d3249b6d9e11d | train | class | class UpdateAttrHandler(object):
"""Performs the translation of a JSON state representation into update
actions performed on a model object instance.
"""
@classmethod
def do_update_attr(cls, obj, json_obj, attr):
"""Perform the update to ``obj`` required to make the attribute attr
equivalent in ``obj`... | class UpdateAttrHandler(object):
| """Performs the translation of a JSON state representation into update
actions performed on a model object instance.
"""
@classmethod
def do_update_attr(cls, obj, json_obj, attr):
"""Perform the update to ``obj`` required to make the attribute attr
equivalent in ``obj`` and ``json_obj``.
"""
i... | self_url:
ret['selfLink'] = self_url
view_url = view_url_for(obj)
if view_url:
ret['viewLink'] = view_url
ret.update(publisher.publish_contribution(obj, inclusions))
return ret
# Otherwise, just return the value itself by default
return obj
def update(obj, json_obj):
"""Translate the... | 256 | 256 | 1,119 | 6 | 250 | alaeddine10/ggrc-core | src/ggrc/builder/json.py | Python | UpdateAttrHandler | UpdateAttrHandler | 82 | 201 | 82 | 82 | 9891a0b9b91ebecc53ac5f3e9fa7e65f456f2394 | bigcode/the-stack | train |
e79b1fb5253b2be28527897a | train | class | class Builder(AttributeInfo):
"""JSON Dictionary builder for ggrc.models.* objects and their mixins."""
def generate_link_object_for(self, obj, inclusions, include):
"""Generate a link object for this object. If there are property paths
to be included specified in the ``inclusions`` parameter, those proper... | class Builder(AttributeInfo):
| """JSON Dictionary builder for ggrc.models.* objects and their mixins."""
def generate_link_object_for(self, obj, inclusions, include):
"""Generate a link object for this object. If there are property paths
to be included specified in the ``inclusions`` parameter, those properties
will be added to the ... | attr_name, class_attr.property.uselist)
@classmethod
def AssociationProxy(cls, obj, json_obj, attr_name, class_attr):
"""Translate the JSON value for an ``AssociationProxy``."""
rel_class = class_attr.remote_attr.property.mapper.class_
return cls.query_for(rel_class, json_obj, attr_name, True)
@cla... | 256 | 256 | 1,121 | 5 | 250 | alaeddine10/ggrc-core | src/ggrc/builder/json.py | Python | Builder | Builder | 203 | 324 | 203 | 203 | dd778f648eaa3ca540ed06968827a1d94e376f23 | bigcode/the-stack | train |
21812268ba3d1a0c420fcd62 | train | function | def create(obj, json_obj):
"""Translate the state represented by ``json_obj`` into update actions
performed upon the new model object ``obj``. After performing the update
``obj`` and ``json_obj`` should be equivalent representations of the model
state.
"""
creator = get_json_builder(obj)
if creator:
c... | def create(obj, json_obj):
| """Translate the state represented by ``json_obj`` into update actions
performed upon the new model object ``obj``. After performing the update
``obj`` and ``json_obj`` should be equivalent representations of the model
state.
"""
creator = get_json_builder(obj)
if creator:
creator.create(obj, json_obj... | json_obj`` should be equivalent representations of the model state.
"""
updater = get_json_builder(obj)
if updater:
updater.update(obj, json_obj)
#FIXME what to do if no updater??
#Nothing, perhaps log, assume omitted by design
def create(obj, json_obj):
| 64 | 64 | 80 | 7 | 56 | alaeddine10/ggrc-core | src/ggrc/builder/json.py | Python | create | create | 72 | 80 | 72 | 72 | 5e5391ff626b300786775a17996c690860da22df | bigcode/the-stack | train |
cb2a73fa515ce98f9a6adbbd | train | function | def view_url_for(obj):
view = getattr(ggrc.views, obj.__class__.__name__, None)
return view.url_for(obj) if view else None
| def view_url_for(obj):
| view = getattr(ggrc.views, obj.__class__.__name__, None)
return view.url_for(obj) if view else None
|
from ggrc.services.util import url_for
from sqlalchemy.ext.associationproxy import AssociationProxy
from sqlalchemy.orm.attributes import InstrumentedAttribute
from sqlalchemy.orm.properties import RelationshipProperty
from werkzeug.exceptions import BadRequest
"""JSON resource state representation handler for gGRC m... | 64 | 64 | 35 | 6 | 58 | alaeddine10/ggrc-core | src/ggrc/builder/json.py | Python | view_url_for | view_url_for | 21 | 23 | 21 | 21 | 65aa664658a9f6e1cf31a7afe413b82b459f50bd | bigcode/the-stack | train |
3d120e3c21fa725c0fc7c20d | train | function | def update(obj, json_obj):
"""Translate the state represented by ``json_obj`` into update actions
performed upon the model object ``obj``. After performing the update ``obj``
and ``json_obj`` should be equivalent representations of the model state.
"""
updater = get_json_builder(obj)
if updater:
updater... | def update(obj, json_obj):
| """Translate the state represented by ``json_obj`` into update actions
performed upon the model object ``obj``. After performing the update ``obj``
and ``json_obj`` should be equivalent representations of the model state.
"""
updater = get_json_builder(obj)
if updater:
updater.update(obj, json_obj)
| view_url = view_url_for(obj)
if view_url:
ret['viewLink'] = view_url
ret.update(publisher.publish_contribution(obj, inclusions))
return ret
# Otherwise, just return the value itself by default
return obj
def update(obj, json_obj):
| 64 | 64 | 77 | 7 | 56 | alaeddine10/ggrc-core | src/ggrc/builder/json.py | Python | update | update | 61 | 68 | 61 | 61 | 3986915ecb1d0d459a262a5e72e0f9054c25f964 | bigcode/the-stack | train |
0913bf6bd0b23f4f76eacd86 | train | function | def test_fetch_rcv1():
try:
data1 = fetch_rcv1(shuffle=False, download_if_missing=False)
except IOError as e:
if e.errno == errno.ENOENT:
raise SkipTest("Download RCV1 dataset to run this test.")
X1, Y1 = data1.data, data1.target
cat_list, s1 = data1.target_names.tolist(), d... | def test_fetch_rcv1():
| try:
data1 = fetch_rcv1(shuffle=False, download_if_missing=False)
except IOError as e:
if e.errno == errno.ENOENT:
raise SkipTest("Download RCV1 dataset to run this test.")
X1, Y1 = data1.data, data1.target
cat_list, s1 = data1.target_names.tolist(), data1.sample_id
# t... | """Test the rcv1 loader.
Skipped if rcv1 is not already downloaded to data_home.
"""
import errno
import scipy.sparse as sp
import numpy as np
from functools import partial
from sklearn.datasets import fetch_rcv1
from sklearn.datasets.tests.test_common import check_return_X_y
from sklearn.utils.testing import assert_... | 113 | 183 | 610 | 7 | 105 | OlegMoiseev/introduction-to-ml | venv/lib/python3.7/site-packages/sklearn/datasets/tests/test_rcv1.py | Python | test_fetch_rcv1 | test_fetch_rcv1 | 19 | 78 | 19 | 19 | 9018f4e6a18fced5dc42c19ff87bc8a406720b88 | bigcode/the-stack | train |
1104aeb737db6e966042cb02 | train | class | class Client(QWebPage):
def __init__(self,url):
self.app = QApplication(sys.argv)
#starting the application
QWebPage.__init__(self)
self.loadFinished.connect(self.on_page_load)
#connecting method when method is finished -> Could work directly with webpage object
self... | class Client(QWebPage):
| def __init__(self,url):
self.app = QApplication(sys.argv)
#starting the application
QWebPage.__init__(self)
self.loadFinished.connect(self.on_page_load)
#connecting method when method is finished -> Could work directly with webpage object
self.mainFrame().load(QUrl(ur... | import sys
#QT is system arguments
from PyQt5.QtWidgets import QApplication
from PyQt5.QtCore import QUrl
from PyQt5.QtWebEngineWidgets import QWebEnginePage
import bs4 as bs
import urllib.request
class Client(QWebPage):
| 58 | 64 | 92 | 6 | 51 | jjohn50/Python3-by-practice | Training Modules/03 Regex/Parser using NLP/Web_scraping_Dynamic_Javascript_Scraping_DOES_NOT_WORK.py | Python | Client | Client | 10 | 22 | 10 | 11 | 858dcbf0abada9bdf1873aeb5bebc9c6a5258082 | bigcode/the-stack | train |
e08a51f5f97c5325294fce45 | train | function | def mass_metadata(config, library):
logger.info("")
util.separator(f"Mass Editing {'Movie' if library.is_movie else 'Show'} Library: {library.name}")
logger.info("")
radarr_adds = []
sonarr_adds = []
items = library.Plex.all()
for i, item in enumerate(items, 1):
util.print_return(f"P... | def mass_metadata(config, library):
| logger.info("")
util.separator(f"Mass Editing {'Movie' if library.is_movie else 'Show'} Library: {library.name}")
logger.info("")
radarr_adds = []
sonarr_adds = []
items = library.Plex.all()
for i, item in enumerate(items, 1):
util.print_return(f"Processing: {i}/{len(items)} {item.ti... | library_handler = logging.handlers.RotatingFileHandler(col_file_logger, mode="w", backupCount=3, encoding="utf-8")
util.apply_formatter(library_handler)
logger.addHandler(library_handler)
library_handler.addFilter(fmt_filter)
os.environ["PLEXAPI_PLEXAPI_T... | 256 | 256 | 1,215 | 7 | 249 | ItsCinnabar/Plex-Meta-Manager | plex_meta_manager.py | Python | mass_metadata | mass_metadata | 247 | 356 | 247 | 247 | 70997fbac7afeee9d33a77af8881203c6c9615a8 | bigcode/the-stack | train |
ed4ced4efb28d02f8b73412d | train | function | def fmt_filter(record):
record.levelname = f"[{record.levelname}]"
record.filename = f"[{record.filename}:{record.lineno}]"
return True
| def fmt_filter(record):
| record.levelname = f"[{record.levelname}]"
record.filename = f"[{record.filename}:{record.lineno}]"
return True
| "config.yml")): raise util.Failed(f"Config Error: config not found at {os.path.abspath(default_dir)}")
os.makedirs(os.path.join(default_dir, "logs"), exist_ok=True)
logger = logging.getLogger("Plex Meta Manager")
logger.setLevel(logging.DEBUG)
def fmt_filter(record):
| 64 | 64 | 37 | 5 | 59 | ItsCinnabar/Plex-Meta-Manager | plex_meta_manager.py | Python | fmt_filter | fmt_filter | 79 | 82 | 79 | 79 | 28e3e6bc92daeb1bcfb5e19542954be3e14f9ad7 | bigcode/the-stack | train |
384bd640ae87cc0fceaf1727 | train | function | def update_libraries(config):
for library in config.libraries:
os.makedirs(os.path.join(default_dir, "logs", library.mapping_name, "collections"), exist_ok=True)
col_file_logger = os.path.join(default_dir, "logs", library.mapping_name, "library.log")
should_roll_over = os.path.isfile(col_fil... | def update_libraries(config):
| for library in config.libraries:
os.makedirs(os.path.join(default_dir, "logs", library.mapping_name, "collections"), exist_ok=True)
col_file_logger = os.path.join(default_dir, "logs", library.mapping_name, "library.log")
should_roll_over = os.path.isfile(col_file_logger)
library_hand... | "))
logger.info(util.centered(" |___/ "))
logger.info(util.centered(" Version: 1.10.0 "))
if time_scheduled: start_type = f"{time_scheduled} "
e... | 256 | 256 | 1,072 | 6 | 250 | ItsCinnabar/Plex-Meta-Manager | plex_meta_manager.py | Python | update_libraries | update_libraries | 130 | 245 | 130 | 130 | 5603cd1a2b5f510213b7753d7f9215ee7fea1841 | bigcode/the-stack | train |
f063144f7a698563bc2abd8a | train | function | def start(config_path, is_test=False, time_scheduled=None, requested_collections=None, requested_libraries=None, resume_from=None):
file_logger = os.path.join(default_dir, "logs", "meta.log")
should_roll_over = os.path.isfile(file_logger)
file_handler = logging.handlers.RotatingFileHandler(file_logger, dela... | def start(config_path, is_test=False, time_scheduled=None, requested_collections=None, requested_libraries=None, resume_from=None):
| file_logger = os.path.join(default_dir, "logs", "meta.log")
should_roll_over = os.path.isfile(file_logger)
file_handler = logging.handlers.RotatingFileHandler(file_logger, delay=True, mode="w", backupCount=10, encoding="utf-8")
util.apply_formatter(file_handler)
file_handler.addFilter(fmt_filter)
... | found at {os.path.abspath(config_file)}")
elif not os.path.exists(os.path.join(default_dir, "config.yml")): raise util.Failed(f"Config Error: config not found at {os.path.abspath(default_dir)}")
os.makedirs(os.path.join(default_dir, "logs"), exist_ok=True)
logger = logging.getLogger("Plex Meta Manager")
logger.set... | 183 | 183 | 613 | 28 | 154 | ItsCinnabar/Plex-Meta-Manager | plex_meta_manager.py | Python | start | start | 91 | 128 | 91 | 91 | 805cdb7016f7a0744b1faf7ead132da9056a6063 | bigcode/the-stack | train |
caa9531a9017116a5e286f32 | train | function | def run_collection(config, library, metadata, requested_collections):
logger.info("")
for mapping_name, collection_attrs in requested_collections.items():
collection_start = datetime.now()
if config.test_mode and ("test" not in collection_attrs or collection_attrs["test"] is not True):
... | def run_collection(config, library, metadata, requested_collections):
| logger.info("")
for mapping_name, collection_attrs in requested_collections.items():
collection_start = datetime.now()
if config.test_mode and ("test" not in collection_attrs or collection_attrs["test"] is not True):
no_template_test = True
if "template" in collection_att... | (util.adjust_space(f"{item.title[:25]:<25} | No Rating Found"))
else:
if library.mass_audience_rating_update and str(item.audienceRating) != str(new_rating):
library.edit_query(item, {"audienceRating.value": new_rating, "audienceRating.locked": 1})
... | 256 | 256 | 955 | 13 | 243 | ItsCinnabar/Plex-Meta-Manager | plex_meta_manager.py | Python | run_collection | run_collection | 358 | 466 | 358 | 358 | 437830415f78ef7a0c1b815c94c67766d8f6d127 | bigcode/the-stack | train |
3c07051ed5b22b60a60fe03c | train | function | def check_bool(env_str, default):
env_var = os.environ.get(env_str)
if env_var is not None:
if env_var is True or env_var is False:
return env_var
elif env_var.lower() in ["t", "true"]:
return True
else:
return False
else:
return default
| def check_bool(env_str, default):
| env_var = os.environ.get(env_str)
if env_var is not None:
if env_var is True or env_var is False:
return env_var
elif env_var.lower() in ["t", "true"]:
return True
else:
return False
else:
return default
| ", help="Character that divides the sections (Default: '=')", default="=", type=str)
parser.add_argument("-w", "--width", dest="width", help="Screen Width (Default: 100)", default=100, type=int)
args = parser.parse_args()
def check_bool(env_str, default):
| 64 | 64 | 74 | 8 | 56 | ItsCinnabar/Plex-Meta-Manager | plex_meta_manager.py | Python | check_bool | check_bool | 33 | 43 | 33 | 33 | f8111c50a8758738d46e2da9cc7faf3e36ff7dca | bigcode/the-stack | train |
723061c44836c994bca96719 | train | class | class Button(ElementBase):
def click(self):
self._behavior.click(self.locator)
| class Button(ElementBase):
| def click(self):
self._behavior.click(self.locator)
| from common.elements.element_base import ElementBase
class Button(ElementBase):
| 14 | 64 | 19 | 5 | 8 | bobjiangps/python3_test_framework | common/elements/button.py | Python | Button | Button | 4 | 7 | 4 | 5 | e7e09d90191dddae14805595bf9b3301f072535e | bigcode/the-stack | train |
66415f5eb9f07fc88aa13170 | train | class | class ADF(logfileparser.Logfile):
"""An ADF log file"""
def __init__(self, *args, **kwargs):
# Call the __init__ method of the superclass
super(ADF, self).__init__(logname="ADF", *args, **kwargs)
def __str__(self):
"""Return a string representation of the object."""
... | class ADF(logfileparser.Logfile):
| """An ADF log file"""
def __init__(self, *args, **kwargs):
# Call the __init__ method of the superclass
super(ADF, self).__init__(logname="ADF", *args, **kwargs)
def __str__(self):
"""Return a string representation of the object."""
return "ADF log file %s" % (sel... | ## -*- coding: utf-8 -*-
#
# Copyright (c) 2017, the cclib development team
#
# This file is part of cclib (http://cclib.github.io) and is distributed under
# the terms of the BSD 3-Clause License.
"""Parser for ADF output files"""
from __future__ import print_function
import itertools
import re
impor... | 112 | 256 | 11,404 | 9 | 102 | alesgenova/cclib | cclib/parser/adfparser.py | Python | ADF | ADF | 21 | 1,172 | 21 | 21 | d5c2ff401a611b956f1b49d7f264cc88448fdde9 | bigcode/the-stack | train |
947bdd915ee9d16db32a6597 | train | class | class StringArray(PandasArray):
"""
Extension array for string data.
.. versionadded:: 1.0.0
.. warning::
StringArray is considered experimental. The implementation and
parts of the API may change without warning.
In particular, the NA value used may change to no longer be
... | class StringArray(PandasArray):
| """
Extension array for string data.
.. versionadded:: 1.0.0
.. warning::
StringArray is considered experimental. The implementation and
parts of the API may change without warning.
In particular, the NA value used may change to no longer be
``numpy.nan``.
Parameters... |
@property
def type(self) -> Type:
return str
@property
def name(self) -> str:
"""
The alias for StringDtype is ``'string'``.
"""
return "string"
@classmethod
def construct_from_string(cls, string: str) -> ExtensionDtype:
if string == "string":
... | 256 | 256 | 1,601 | 7 | 249 | DorAmram/pandas | pandas/core/arrays/string_.py | Python | StringArray | StringArray | 96 | 318 | 96 | 96 | d9a5f097a03fb82fff8f0277bc05f45851256955 | bigcode/the-stack | train |
7597e31f6ca5736d56bbae6d | train | class | @register_extension_dtype
class StringDtype(ExtensionDtype):
"""
Extension dtype for string data.
.. versionadded:: 1.0.0
.. warning::
StringDtype is considered experimental. The implementation and
parts of the API may change without warning.
In particular, StringDtype.na_value ... | @register_extension_dtype
class StringDtype(ExtensionDtype):
| """
Extension dtype for string data.
.. versionadded:: 1.0.0
.. warning::
StringDtype is considered experimental. The implementation and
parts of the API may change without warning.
In particular, StringDtype.na_value may change to no longer be
``numpy.nan``.
Attribu... | from pandas.core.dtypes.base import ExtensionDtype
from pandas.core.dtypes.common import pandas_dtype
from pandas.core.dtypes.dtypes import register_extension_dtype
from pandas.core.dtypes.generic import ABCDataFrame, ABCIndexClass, ABCSeries
from pandas.core.dtypes.inference import is_array_like
from pandas import co... | 116 | 116 | 387 | 14 | 101 | DorAmram/pandas | pandas/core/arrays/string_.py | Python | StringDtype | StringDtype | 21 | 93 | 21 | 22 | 8e1b9599b7cd4e655d079d28e8b028311e21971a | bigcode/the-stack | train |
ee8e9b369f6cda1e3c19854a | train | class | class _DatasetIterGE(_DatasetIter):
"""Iter for ge"""
def __init__(self, dataset):
super(_DatasetIterGE, self).__init__(dataset)
self.loop_count = self.get_loop_count(dataset)
parallel_mode = _get_parallel_mode()
self.need_to_full = parallel_mode in (ParallelMode.SEMI_AUTO_PARALL... | class _DatasetIterGE(_DatasetIter):
| """Iter for ge"""
def __init__(self, dataset):
super(_DatasetIterGE, self).__init__(dataset)
self.loop_count = self.get_loop_count(dataset)
parallel_mode = _get_parallel_mode()
self.need_to_full = parallel_mode in (ParallelMode.SEMI_AUTO_PARALLEL, ParallelMode.AUTO_PARALLEL)
... | MS, self).__init__(dataset)
self.loop_count = dataset.get_dataset_size()
self.loop_size = 1
queue_name = dataset.__ME_INITED__
self.op = GetNextSingleOp(self.dataset_types, self.dataset_shapes, queue_name)
class _DatasetIterGE(_DatasetIter):
| 64 | 64 | 146 | 9 | 55 | huxiaoman7/mindspore | mindspore/train/dataset_helper.py | Python | _DatasetIterGE | _DatasetIterGE | 138 | 152 | 138 | 138 | db3adc2cc46f359b062f5f4fa3bfa17eaaf249b3 | bigcode/the-stack | train |
5795d9d6357141fa3f8e25d6 | train | class | class _DatasetIterFeed:
"""Iter for feed data"""
def __init__(self, dataset):
self.dataset = dataset
self.device_num = _get_device_num()
self.global_rank = _get_global_rank()
self.repeat_count = dataset.get_repeat_count()
self.repeat_ind = 0
self.loop_count = data... | class _DatasetIterFeed:
| """Iter for feed data"""
def __init__(self, dataset):
self.dataset = dataset
self.device_num = _get_device_num()
self.global_rank = _get_global_rank()
self.repeat_count = dataset.get_repeat_count()
self.repeat_ind = 0
self.loop_count = dataset.get_dataset_size()
... | ALLEL)
batch_expand_num = 1
if self.need_to_full:
batch_expand_num = _get_device_num()
tensor_list_run = _construct_tensor_list(self.dataset_types, self.dataset_shapes, batch_expand_num)
def op():
return tensor_list_run
self.op = op
class _DatasetIterFeed... | 71 | 71 | 237 | 6 | 64 | huxiaoman7/mindspore | mindspore/train/dataset_helper.py | Python | _DatasetIterFeed | _DatasetIterFeed | 155 | 184 | 155 | 155 | 3da154ffba48bef996e282ced43d64e2517891ec | bigcode/the-stack | train |
4df18520a0baece76c96ff01 | train | class | class _DatasetIter:
"""Base iter for dataset help"""
def __init__(self, dataset):
self.loop_size = 1
if not hasattr(dataset, '__ME_INITED__'):
if not hasattr(dataset, '__loop_size__'):
self.loop_size = dataset.get_dataset_size()
else:
self.... | class _DatasetIter:
| """Base iter for dataset help"""
def __init__(self, dataset):
self.loop_size = 1
if not hasattr(dataset, '__ME_INITED__'):
if not hasattr(dataset, '__loop_size__'):
self.loop_size = dataset.get_dataset_size()
else:
self.loop_size = dataset.... | "):
if context.get_context("enable_loop_sink"):
iterclass = _DatasetIterMSLoopSink
else:
iterclass = _DatasetIterMS
self.iter = iterclass(dataset)
def __iter__(self):
return self.iter.__iter__()
# A temp solution for loop sink. Delete la... | 121 | 121 | 405 | 5 | 115 | huxiaoman7/mindspore | mindspore/train/dataset_helper.py | Python | _DatasetIter | _DatasetIter | 71 | 114 | 71 | 71 | 85bb44ccb4d96d162af3ed21199afdb3cff4c2db | bigcode/the-stack | train |
e314cc05f4f9c51cd3a9b6c2 | train | class | class _DatasetIterMS(_DatasetIter):
"""Iter for context (enable_loop_sink=False)"""
def __init__(self, dataset):
super(_DatasetIterMS, self).__init__(dataset)
self.loop_count = dataset.get_dataset_size()
self.loop_size = 1
queue_name = dataset.__ME_INITED__
self.op = GetN... | class _DatasetIterMS(_DatasetIter):
| """Iter for context (enable_loop_sink=False)"""
def __init__(self, dataset):
super(_DatasetIterMS, self).__init__(dataset)
self.loop_count = dataset.get_dataset_size()
self.loop_size = 1
queue_name = dataset.__ME_INITED__
self.op = GetNextSingleOp(self.dataset_types, self... | enable_loop_sink=True)"""
def __init__(self, dataset):
super(_DatasetIterMSLoopSink, self).__init__(dataset)
self.loop_count = self.get_loop_count(dataset)
def op():
return tuple()
self.op = op
class _DatasetIterMS(_DatasetIter):
| 64 | 64 | 90 | 9 | 54 | huxiaoman7/mindspore | mindspore/train/dataset_helper.py | Python | _DatasetIterMS | _DatasetIterMS | 128 | 135 | 128 | 128 | 3a3df79444189e1759da1963d36aa3665bc559d8 | bigcode/the-stack | train |
2f7421c7140db476bafcc738 | train | class | class _DatasetIterMSLoopSink(_DatasetIter):
"""Iter for context (enable_loop_sink=True)"""
def __init__(self, dataset):
super(_DatasetIterMSLoopSink, self).__init__(dataset)
self.loop_count = self.get_loop_count(dataset)
def op():
return tuple()
self.op = op
| class _DatasetIterMSLoopSink(_DatasetIter):
| """Iter for context (enable_loop_sink=True)"""
def __init__(self, dataset):
super(_DatasetIterMSLoopSink, self).__init__(dataset)
self.loop_count = self.get_loop_count(dataset)
def op():
return tuple()
self.op = op
| loop_size != 0:
raise ValueError(f'Dataset size {dataset.get_dataset_size()} and '
f'loop_size {loop_size} are not matched.')
loop_count = int(dataset.get_dataset_size()/loop_size)
return loop_count
class _DatasetIterMSLoopSink(_DatasetIter):
| 64 | 64 | 72 | 11 | 52 | huxiaoman7/mindspore | mindspore/train/dataset_helper.py | Python | _DatasetIterMSLoopSink | _DatasetIterMSLoopSink | 117 | 125 | 117 | 117 | 1159244f508ed6af1c7999b29123f8964e144a4d | bigcode/the-stack | train |
2c278419a28b19c1bcacf031 | train | class | class DatasetHelper:
"""
Help function to use the Minddata dataset.
According to different context, change the iter of dataset, to use the same for loop in different context.
Note:
The iter of DatasetHelper will give one epoch data.
Args:
dataset (DataSet): The dataset.
da... | class DatasetHelper:
| """
Help function to use the Minddata dataset.
According to different context, change the iter of dataset, to use the same for loop in different context.
Note:
The iter of DatasetHelper will give one epoch data.
Args:
dataset (DataSet): The dataset.
dataset_sink_mode (bool... | import check_bool
from .. import context
from .parallel_utils import ParallelMode
from ._utils import _exec_datagraph, _get_types_and_shapes, _to_tensor, \
_construct_tensor_list, _to_full_shapes, _to_full_tensor
from ..nn.wrap import GetNextSingleOp
from ..parallel._utils import _get_device_num, _get_global_rank,... | 89 | 89 | 297 | 4 | 84 | huxiaoman7/mindspore | mindspore/train/dataset_helper.py | Python | DatasetHelper | DatasetHelper | 25 | 68 | 25 | 25 | f099b3fca43834b16338e5cbe8838a9ece67c189 | bigcode/the-stack | train |
9a0352ac369536bfa43bbd02 | train | class | class RARIngestor(PackageSupport, Ingestor):
MIME_TYPES = ["application/rar" "application/x-rar"]
EXTENSIONS = ["rar"]
SCORE = 4
def unpack(self, file_path, entity, temp_dir):
# FIXME: need to figure out how to unpack multi-part files.
try:
with rarfile.RarFile(file_path.as_... | class RARIngestor(PackageSupport, Ingestor):
| MIME_TYPES = ["application/rar" "application/x-rar"]
EXTENSIONS = ["rar"]
SCORE = 4
def unpack(self, file_path, entity, temp_dir):
# FIXME: need to figure out how to unpack multi-part files.
try:
with rarfile.RarFile(file_path.as_posix()) as rf:
names = rf.na... | import logging
import rarfile
from ingestors.ingestor import Ingestor
from ingestors.support.package import PackageSupport
from ingestors.exc import ProcessingException
log = logging.getLogger(__name__)
class RARIngestor(PackageSupport, Ingestor):
| 56 | 96 | 322 | 14 | 42 | simonwoerpel/ingest-file | ingestors/packages/rar.py | Python | RARIngestor | RARIngestor | 11 | 43 | 11 | 11 | 99564b80d373591a05b4efccb1a22e24025a0438 | bigcode/the-stack | train |
6a0df453b2ae952eead446bc | train | class | class AlexNetModel(kserve.KFModel):
def __init__(self, name: str):
super().__init__(name)
self.name = name
self.load()
def load(self):
model = models.alexnet(pretrained=True)
model.eval()
self.model = model
self.ready = True
def predict(self, request... | class AlexNetModel(kserve.KFModel):
| def __init__(self, name: str):
super().__init__(name)
self.name = name
self.load()
def load(self):
model = models.alexnet(pretrained=True)
model.eval()
self.model = model
self.ready = True
def predict(self, request: Dict) -> Dict:
inputs = re... | 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 kserve
from torchvision import models, transforms
from typing import Dict
import torc... | 85 | 85 | 286 | 10 | 74 | Suresh-Nakkeran/kserve | python/custom_model/model.py | Python | AlexNetModel | AlexNetModel | 24 | 63 | 24 | 24 | 52a0281bfdc38e7cce9883f193e4e63e62f39100 | bigcode/the-stack | train |
996362a925b8bc0b53e837ee | train | class | class AST_Matrix_Row(AST_Node):
def __init__(self, context, elements):
AST_Node.__init__(self, context)
self.elements = elements
if not isinstance(self.elements, list):
raise ValueError(
"AST_Matrix_Row() expects a list of elements, got " +
str(typ... | class AST_Matrix_Row(AST_Node):
| def __init__(self, context, elements):
AST_Node.__init__(self, context)
self.elements = elements
if not isinstance(self.elements, list):
raise ValueError(
"AST_Matrix_Row() expects a list of elements, got " +
str(type(self.elements)))
def prov... | from .ast_node import AST_Node
from .ast_values import AST_Constant
import dace
class AST_Matrix_Row(AST_Node):
| 28 | 84 | 283 | 8 | 19 | gronerl/dace | dace/frontend/octave/ast_matrix.py | Python | AST_Matrix_Row | AST_Matrix_Row | 7 | 49 | 7 | 7 | 3be9ec05082fdc37ffd8aa40615ba5c4291fc795 | bigcode/the-stack | train |
27698dc524a50554ad65bbcc | train | class | class AST_Transpose(AST_Node):
def __init__(self, context, arg, op):
AST_Node.__init__(self, context)
self.arg = arg
self.op = op
def __repr__(self):
return "AST_Transpose(" + str(self.arg) + ", " + str(self.op) + ")"
def get_children(self):
return [self.arg]
d... | class AST_Transpose(AST_Node):
| def __init__(self, context, arg, op):
AST_Node.__init__(self, context)
self.arg = arg
self.op = op
def __repr__(self):
return "AST_Transpose(" + str(self.arg) + ", " + str(self.op) + ")"
def get_children(self):
return [self.arg]
def get_dims(self):
dims... | out", mx, None,
dace.memlet.Memlet.from_array(trans.data, trans.desc(sdfg)))
sdfg.nodes()[state].add_edge(
mx, None, trans, None,
dace.memlet.Memlet.from_array(trans.data, trans.desc(sdfg)))
print("The const expr " + str(self) + " will be stored i... | 180 | 181 | 604 | 7 | 173 | gronerl/dace | dace/frontend/octave/ast_matrix.py | Python | AST_Transpose | AST_Transpose | 152 | 214 | 152 | 152 | c4183c705e2b016d18e466cabafcbbc1b1a5db9f | bigcode/the-stack | train |
96d86d73c810326f54c45fb0 | train | class | class AST_Matrix(AST_Node):
def __init__(self, context, rows):
AST_Node.__init__(self, context)
self.rows = rows
self.children = self.rows
if not isinstance(self.rows, list):
raise ValueError("AST_Matrix() expects a list of rows, got " +
str(t... | class AST_Matrix(AST_Node):
| def __init__(self, context, rows):
AST_Node.__init__(self, context)
self.rows = rows
self.children = self.rows
if not isinstance(self.rows, list):
raise ValueError("AST_Matrix() expects a list of rows, got " +
str(type(self.rows)))
for... | raise ValueError(
"AST_Matrix_Row() expects a list of elements, got " +
str(type(self.elements)))
def provide_parents(self, parent):
self.parent = parent
for e in self.elements:
e.provide_parents(self)
def __repr__(self):
return "AST_MatrixR... | 245 | 246 | 823 | 7 | 238 | gronerl/dace | dace/frontend/octave/ast_matrix.py | Python | AST_Matrix | AST_Matrix | 52 | 149 | 52 | 52 | 7d23689dd19d19b995d7c8e0304be69dae0aa2c8 | bigcode/the-stack | train |
093e0661ef7852ef2f7df095 | train | function | @pytest.fixture(scope = "module")
def lossless_prio_dscp_map(duthost):
config_facts = duthost.config_facts(host=duthost.hostname, source="persistent")['ansible_facts']
if "PORT_QOS_MAP" not in config_facts.keys():
return None
port_qos_map = config_facts["PORT_QOS_MAP"]
lossless_priorities = li... | @pytest.fixture(scope = "module")
def lossless_prio_dscp_map(duthost):
| config_facts = duthost.config_facts(host=duthost.hostname, source="persistent")['ansible_facts']
if "PORT_QOS_MAP" not in config_facts.keys():
return None
port_qos_map = config_facts["PORT_QOS_MAP"]
lossless_priorities = list()
intf = port_qos_map.keys()[0]
if 'pfc_enable' not in port_... | import pytest
from common.fixtures.conn_graph_facts import conn_graph_facts
@pytest.fixture(scope = "module")
def lossless_prio_dscp_map(duthost):
| 36 | 75 | 251 | 19 | 16 | mykolaf/sonic-mgmt | tests/qos/qos_fixtures.py | Python | lossless_prio_dscp_map | lossless_prio_dscp_map | 5 | 33 | 5 | 6 | 07120689b70ce09a82c83d44e0ccbe522ca2f2dd | bigcode/the-stack | train |
ba2a41fb540425ea1b508c36 | train | function | @pytest.fixture(scope = "module")
def leaf_fanouts(conn_graph_facts):
"""
@summary: Fixture for getting the list of leaf fanout switches
@param conn_graph_facts: Topology connectivity information
@return: Return the list of leaf fanout switches
"""
leaf_fanouts = []
conn_facts = conn_graph_f... | @pytest.fixture(scope = "module")
def leaf_fanouts(conn_graph_facts):
| """
@summary: Fixture for getting the list of leaf fanout switches
@param conn_graph_facts: Topology connectivity information
@return: Return the list of leaf fanout switches
"""
leaf_fanouts = []
conn_facts = conn_graph_facts['device_conn']
""" for each interface of DUT """
for int... | dscp_to_tc_map[profile]:
tc = dscp_to_tc_map[profile][dscp]
if int(tc) in lossless_priorities:
result[int(tc)].append(int(dscp))
return result
@pytest.fixture(scope = "module")
def leaf_fanouts(conn_graph_facts):
| 64 | 64 | 139 | 17 | 46 | mykolaf/sonic-mgmt | tests/qos/qos_fixtures.py | Python | leaf_fanouts | leaf_fanouts | 36 | 52 | 36 | 37 | b444906f1006adaf94f8f4a612b7caee16fa24a0 | bigcode/the-stack | train |
d3f242b7cc578b0cabfc8e4c | train | class | class MigrationsEmulatorTest(spanner_emulator_testlib.TestCase):
TEST_MIGRATIONS_DIR = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'migrations_for_emulator_test',
)
def setUp(self):
super().setUp()
self.run_orm_migrations(self.TEST_MIGRATIONS_DIR)
def test_basic(self):
mo... | class MigrationsEmulatorTest(spanner_emulator_testlib.TestCase):
| TEST_MIGRATIONS_DIR = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'migrations_for_emulator_test',
)
def setUp(self):
super().setUp()
self.run_orm_migrations(self.TEST_MIGRATIONS_DIR)
def test_basic(self):
models.SmallTestModel({'key': 'key', 'value_1': 'value'}).save()
... | 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 datetime
import logging
import os
import unittest
import spanner_orm
from spanner_orm.tests import models
from spanner_orm.tes... | 110 | 110 | 368 | 15 | 94 | GavinDuggan/python-spanner-orm | spanner_orm/tests/migrations_emulator_test.py | Python | MigrationsEmulatorTest | MigrationsEmulatorTest | 27 | 73 | 27 | 27 | ba0621dd7f7bdbf2c9bedc8e6a1d662162fd1b1c | bigcode/the-stack | train |
ce36de9c716f7345ff9794d1 | train | function | def return_error(msg):
print(msg, file=sys.stderr)
sys.exit(1)
| def return_error(msg):
| print(msg, file=sys.stderr)
sys.exit(1)
| #!/usr/bin/env python
from __future__ import print_function
import json
import sys
import ast
def return_error(msg):
| 28 | 64 | 19 | 5 | 22 | bdclark/docker-telegraf-consul | bin/parse_config.py | Python | return_error | return_error | 9 | 11 | 9 | 9 | c2e68cdc856f2816e3dd7f97d314070919a87629 | bigcode/the-stack | train |
a9201c9d399bfee445733c0e | train | function | def is_num(val):
if val is True or val is False:
return False
try:
float(val)
return True
except ValueError:
return False
| def is_num(val):
| if val is True or val is False:
return False
try:
float(val)
return True
except ValueError:
return False
| #!/usr/bin/env python
from __future__ import print_function
import json
import sys
import ast
def return_error(msg):
print(msg, file=sys.stderr)
sys.exit(1)
def is_num(val):
| 47 | 64 | 39 | 5 | 42 | bdclark/docker-telegraf-consul | bin/parse_config.py | Python | is_num | is_num | 14 | 21 | 14 | 14 | 17745356f43ad4cec711ebac5e6b1af264120b3e | bigcode/the-stack | train |
b7cb224d94ad5caa16d3e1e1 | train | function | def convert_dict(d):
if not isinstance(d, dict):
error_out("{} not a map".format(d))
for k, v in d.iteritems():
if isinstance(v, dict):
v = convert_dict(v)
elif v.startswith('[') and v.endswith(']'):
# treat as literal list
d[k] = ast.literal_eval(v)
... | def convert_dict(d):
| if not isinstance(d, dict):
error_out("{} not a map".format(d))
for k, v in d.iteritems():
if isinstance(v, dict):
v = convert_dict(v)
elif v.startswith('[') and v.endswith(']'):
# treat as literal list
d[k] = ast.literal_eval(v)
elif v == '{}'... |
def return_error(msg):
print(msg, file=sys.stderr)
sys.exit(1)
def is_num(val):
if val is True or val is False:
return False
try:
float(val)
return True
except ValueError:
return False
def convert_dict(d):
| 64 | 64 | 160 | 5 | 58 | bdclark/docker-telegraf-consul | bin/parse_config.py | Python | convert_dict | convert_dict | 24 | 43 | 24 | 24 | e8e9859c1d08b84257aa203d92b81abfbf6a1b3a | bigcode/the-stack | train |
8a1233757bcd4015fcd7f7ca | train | class | class ExecutionsApi(object):
"""NOTE: This class is auto generated by OpenAPI Generator
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_cli... | class ExecutionsApi(object):
| """NOTE: This class is auto generated by OpenAPI Generator
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def delete_execution... | # coding: utf-8
"""
LUSID API
FINBOURNE Technology # noqa: E501
The version of the OpenAPI document: 0.11.3923
Contact: info@finbourne.com
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility lib... | 247 | 256 | 8,158 | 6 | 240 | finbourne/lusid-sdk-python-asyncio-preview | sdk/lusid_asyncio/api/executions_api.py | Python | ExecutionsApi | ExecutionsApi | 35 | 730 | 35 | 35 | f84af561d7f2da3b2cd38010493c63ca59618818 | bigcode/the-stack | train |
dfefd5aeefd390e0eeda5704 | train | function | def get_imgs(img_path, imsize, bbox=None,
transform=None, normalize=None):
img = Image.open(img_path).convert('RGB')
width, height = img.size
if bbox is not None:
r = int(np.maximum(bbox[2], bbox[3]) * 0.75)
center_x = int((2 * bbox[0] + bbox[2]) / 2)
center_y = int((2 *... | def get_imgs(img_path, imsize, bbox=None,
transform=None, normalize=None):
| img = Image.open(img_path).convert('RGB')
width, height = img.size
if bbox is not None:
r = int(np.maximum(bbox[2], bbox[3]) * 0.75)
center_x = int((2 * bbox[0] + bbox[2]) / 2)
center_y = int((2 * bbox[1] + bbox[3]) / 2)
y1 = np.maximum(0, center_y - r)
y2 = np.minimu... | :
captions = Variable(captions).cuda()
sorted_cap_lens = Variable(sorted_cap_lens).cuda()
else:
captions = Variable(captions)
sorted_cap_lens = Variable(sorted_cap_lens)
return [real_imgs, captions, sorted_cap_lens,
class_ids, keys]
def get_imgs(img_path, imsize, bbo... | 86 | 86 | 287 | 19 | 67 | FangxiangFeng/DM-GAN-MDD | code/datasets.py | Python | get_imgs | get_imgs | 59 | 88 | 59 | 60 | 42b87ec7a7874fc2fe1a65f303a2f1c62fa25f05 | bigcode/the-stack | train |
cee902639163e55a7e068531 | train | function | def prepare_data(data):
imgs, captions, captions_lens, class_ids, keys = data
# sort data by the length in a decreasing order
sorted_cap_lens, sorted_cap_indices = \
torch.sort(captions_lens, 0, True)
real_imgs = []
for i in range(len(imgs)):
imgs[i] = imgs[i][sorted_cap_indices]
... | def prepare_data(data):
| imgs, captions, captions_lens, class_ids, keys = data
# sort data by the length in a decreasing order
sorted_cap_lens, sorted_cap_indices = \
torch.sort(captions_lens, 0, True)
real_imgs = []
for i in range(len(imgs)):
imgs[i] = imgs[i][sorted_cap_indices]
if cfg.CUDA:
... | torch.utils.data as data
from torch.autograd import Variable
import torchvision.transforms as transforms
import os
import sys
import numpy as np
import pandas as pd
from PIL import Image
import numpy.random as random
if sys.version_info[0] == 2:
import cPickle as pickle
else:
import pickle
def prepare_data(da... | 76 | 76 | 256 | 5 | 70 | FangxiangFeng/DM-GAN-MDD | code/datasets.py | Python | prepare_data | prepare_data | 28 | 56 | 28 | 28 | e55ad08943334f88f0b08a9a991513ff3788df4c | bigcode/the-stack | train |
63d098fc78cc6a0abcfbf99c | train | class | class FlowersTextDataset(data.Dataset):
def __init__(self, data_dir, split='train',
base_size=64,
transform=None, target_transform=None):
self.transform = transform
self.norm = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(... | class FlowersTextDataset(data.Dataset):
| def __init__(self, data_dir, split='train',
base_size=64,
transform=None, target_transform=None):
self.transform = transform
self.norm = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
... | mis_match_captions_len = torch.zeros(99)
i = 0
while len(mis_match_captions_t) < 99:
idx = random.randint(0, self.number_example)
if cls_id == self.class_id[idx]:
continue
sent_ix = random.randint(0, self.embeddings_num)
new_sent_ix... | 256 | 256 | 2,138 | 7 | 249 | FangxiangFeng/DM-GAN-MDD | code/datasets.py | Python | FlowersTextDataset | FlowersTextDataset | 391 | 609 | 391 | 391 | cb72e57f5139d65287866cd624ebd15a5299968f | bigcode/the-stack | train |
66b616fcc673dac377d58196 | train | function | def get_caption(raw_sent, dictionary):
caption_ixs = [ ]
tokenizer = RegexpTokenizer(r'\w+')
tokens = tokenizer.tokenize(raw_sent.lower())
for tok in tokens:
if tok in dictionary:
caption_ixs.append(dictionary[tok])
# a list of indices for a sentence
sent_caption = np.asarray... | def get_caption(raw_sent, dictionary):
| caption_ixs = [ ]
tokenizer = RegexpTokenizer(r'\w+')
tokens = tokenizer.tokenize(raw_sent.lower())
for tok in tokens:
if tok in dictionary:
caption_ixs.append(dictionary[tok])
# a list of indices for a sentence
sent_caption = np.asarray(caption_ixs).astype('int64')
if (s... | )]
else:
for i in range(cfg.TREE.BRANCH_NUM):
# print(imsize[i])
if i < (cfg.TREE.BRANCH_NUM - 1):
re_img = transforms.Scale(imsize[i])(img)
else:
re_img = img
ret.append(normalize(re_img))
return ret
def get_caption(raw_se... | 81 | 81 | 271 | 8 | 72 | FangxiangFeng/DM-GAN-MDD | code/datasets.py | Python | get_caption | get_caption | 90 | 114 | 90 | 90 | a5ffabda9609f928d71e0a9b81eea81a598e1d5b | bigcode/the-stack | train |
79bd81e5bd672cdcdc7c348a | train | class | class TextDataset(data.Dataset):
def __init__(self, data_dir, split='train',
base_size=64,
transform=None, target_transform=None):
self.transform = transform
self.norm = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, 0... | class TextDataset(data.Dataset):
| def __init__(self, data_dir, split='train',
base_size=64,
transform=None, target_transform=None):
self.transform = transform
self.norm = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
... | .size
if bbox is not None:
r = int(np.maximum(bbox[2], bbox[3]) * 0.75)
center_x = int((2 * bbox[0] + bbox[2]) / 2)
center_y = int((2 * bbox[1] + bbox[3]) / 2)
y1 = np.maximum(0, center_y - r)
y2 = np.minimum(height, center_y + r)
x1 = np.maximum(0, center_x - r)
... | 256 | 256 | 2,302 | 6 | 249 | FangxiangFeng/DM-GAN-MDD | code/datasets.py | Python | TextDataset | TextDataset | 147 | 389 | 147 | 147 | b954d7f2b750cf1a027718d020278e9a979d3bbd | bigcode/the-stack | train |
38f484f03c277fc257d32da2 | train | function | def get_imgs(img_path, imsize, bbox=None,
transform=None, normalize=None):
img = Image.open(img_path).convert('RGB')
width, height = img.size
if bbox is not None:
r = int(np.maximum(bbox[2], bbox[3]) * 0.75)
center_x = int((2 * bbox[0] + bbox[2]) / 2)
center_y = int((2 *... | def get_imgs(img_path, imsize, bbox=None,
transform=None, normalize=None):
| img = Image.open(img_path).convert('RGB')
width, height = img.size
if bbox is not None:
r = int(np.maximum(bbox[2], bbox[3]) * 0.75)
center_x = int((2 * bbox[0] + bbox[2]) / 2)
center_y = int((2 * bbox[1] + bbox[3]) / 2)
y1 = np.maximum(0, center_y - r)
y2 = np.minimu... | 1, 2, 3,..., maxNum
np.random.shuffle(ix)
ix = ix[:cfg.TEXT.WORDS_NUM]
ix = np.sort(ix)
x[:, 0] = sent_caption[ix]
x_len = cfg.TEXT.WORDS_NUM
return x, x_len
def get_imgs(img_path, imsize, bbox=None,
transform=None, normalize=None):
| 86 | 86 | 287 | 19 | 66 | FangxiangFeng/DM-GAN-MDD | code/datasets.py | Python | get_imgs | get_imgs | 116 | 145 | 116 | 117 | 42b87ec7a7874fc2fe1a65f303a2f1c62fa25f05 | bigcode/the-stack | train |
a5da016b7fb95f341501d308 | train | function | def prepare_train_and_show(neural_network: NeuralNetwork,
train_data: np.ndarray,
train_labels: np.ndarray,
test_data: np.ndarray,
test_labels: np.ndarray):
data_scaler = MinMaxScaler((0, 1))
labels_scale... | def prepare_train_and_show(neural_network: NeuralNetwork,
train_data: np.ndarray,
train_labels: np.ndarray,
test_data: np.ndarray,
test_labels: np.ndarray):
| data_scaler = MinMaxScaler((0, 1))
labels_scaler = MinMaxScaler((0, 1))
print("Press Ctrl + C to interrupt, exit button in window may not close the program")
plt.ion()
figure, ax = plt.subplots()
figure.canvas.draw_idle()
for i in range(1, FRAMES):
neural_network.train(
... |
import numpy as np
from sklearn.preprocessing import MinMaxScaler
from neural_network import NeuralNetwork
ITERATION_PER_FRAME = 100
FRAMES = 1_000_000
def prepare_train_and_show(neural_network: NeuralNetwork,
train_data: np.ndarray,
train_labels: np.ndarray,
... | 79 | 79 | 264 | 40 | 38 | ErykKrupa/python-course | list6/train.py | Python | prepare_train_and_show | prepare_train_and_show | 10 | 38 | 10 | 14 | 8af40b2eb871d56512acf2b243b3b492270a52ef | bigcode/the-stack | train |
cbf6cae6827ec9cc0520fa26 | train | class | class CommManager:
def __init__(self):
self.MPI = MPI
self.communicators = {}
self.intra_communicators = {}
self.add_communicator('main', MPI.COMM_WORLD)
def __getitem__(self, index):
if index in self.intra_communicators:
return self.intra_communicators[index... | class CommManager:
| def __init__(self):
self.MPI = MPI
self.communicators = {}
self.intra_communicators = {}
self.add_communicator('main', MPI.COMM_WORLD)
def __getitem__(self, index):
if index in self.intra_communicators:
return self.intra_communicators[index]
elif inde... | from mpi4py import MPI
class CommManager:
| 11 | 64 | 156 | 4 | 6 | gandresr/PTSNET | ptsnet/parallel/comm.py | Python | CommManager | CommManager | 3 | 22 | 3 | 3 | 6645b9a66cab4d0bad86af5243b3dfe8f767a9ce | bigcode/the-stack | train |
023bae7dc620de636df04978 | train | function | def canonicals_for_language(data, language):
canonicals = set()
for d in data:
lang, dictionary, is_canonical, canonical = d.split(six.b('|'))
if language is None or lang == language:
canonicals.add(canonical)
return canonicals
| def canonicals_for_language(data, language):
| canonicals = set()
for d in data:
lang, dictionary, is_canonical, canonical = d.split(six.b('|'))
if language is None or lang == language:
canonicals.add(canonical)
return canonicals
| .address_expansions.gazetteers import *
from geodata.encoding import safe_decode, safe_encode
from geodata.text.normalize import normalized_tokens
from geodata.text.tokenize import tokenize_raw, token_types
from geodata.text.utils import non_breaking_dash_regex
def canonicals_for_language(data, language):
| 64 | 64 | 61 | 9 | 54 | Fillr/libpostal | scripts/geodata/address_expansions/equivalence.py | Python | canonicals_for_language | canonicals_for_language | 14 | 22 | 14 | 14 | 3d0b45af4f42a1f5edfe65f916e8d06a0bd1a69b | bigcode/the-stack | train |
8dc241b11a8fcab958f3fa75 | train | function | def equivalent(s1, s2, gazetteer, language):
'''
Address/place equivalence
-------------------------
OSM discourages abbreviations, but to make our training data map better
to real-world input, we can safely replace the canonical phrase with an
abbreviated version and retain the meaning of the ... | def equivalent(s1, s2, gazetteer, language):
| '''
Address/place equivalence
-------------------------
OSM discourages abbreviations, but to make our training data map better
to real-world input, we can safely replace the canonical phrase with an
abbreviated version and retain the meaning of the words
'''
tokens_s1 = normalized_tok... | token_types
from geodata.text.utils import non_breaking_dash_regex
def canonicals_for_language(data, language):
canonicals = set()
for d in data:
lang, dictionary, is_canonical, canonical = d.split(six.b('|'))
if language is None or lang == language:
canonicals.add(canonical)
... | 90 | 90 | 303 | 14 | 75 | Fillr/libpostal | scripts/geodata/address_expansions/equivalence.py | Python | equivalent | equivalent | 24 | 56 | 24 | 24 | 2748bacec80604aace9be170c27cb8e9cd782e5b | bigcode/the-stack | train |
7e1cde9401f3571b3d74f4c6 | train | function | def swap_case_string(str1):
result_str = ""
for item in str1:
if item.isupper():
result_str += item.lower()
else:
result_str += item.upper()
return result_str
| def swap_case_string(str1):
| result_str = ""
for item in str1:
if item.isupper():
result_str += item.lower()
else:
result_str += item.upper()
return result_str
| """
Write a Python program to swap cases of a given string.
Sample Output:
pYTHON eXERCISES
jAVA
nUMpy
"""
def swap_case_string(str1):
| 40 | 64 | 47 | 7 | 33 | CodedLadiesInnovateTech/-python-challenge-solutions | Aniyom Ebenezer/Phase 2/STRINGS/Day_37_Challenge_Solution/Question 4 Solution.py | Python | swap_case_string | swap_case_string | 8 | 15 | 8 | 8 | a71e57b4faff1cdd7d34996c33469482b77b0e66 | bigcode/the-stack | train |
2dfdb815f9b59aa86b617e2f | train | function | def update_button(idx, pressed):
curr_btns[idx] = pressed
if curr_btns[idx] and not prev_btns[idx]:
print("Exit menu")
return True
prev_btns[idx] = curr_btns[idx]
return False
| def update_button(idx, pressed):
| curr_btns[idx] = pressed
if curr_btns[idx] and not prev_btns[idx]:
print("Exit menu")
return True
prev_btns[idx] = curr_btns[idx]
return False
| , 0.5),
)
# Button management
curr_btns = [False] * 4
prev_btns = [False] * 4
BTN_A = 0
BTN_B = 1
BTN_C = 2
BTN_D = 3
def update_button(idx, pressed):
| 64 | 64 | 56 | 7 | 56 | albinger/Adafruit_Learning_System_Guides | MagTag_Flashcards/chapters/code.py | Python | update_button | update_button | 87 | 93 | 87 | 87 | 92d7b6b887a0989573d87d13e8760bb3f1ba0248 | bigcode/the-stack | train |
7997f36c5af6fcd504329c07 | train | class | class writer:
def __init__(self):
self.queue = []
self.max_queue_size = 1000
self.mutex = thread.allocate_lock()
thread.start_new_thread(self.looper, ())
#
# Writing thread
#
def looper(self):
logger.dump('writer.looper() started!', 'info')
while... | class writer:
| def __init__(self):
self.queue = []
self.max_queue_size = 1000
self.mutex = thread.allocate_lock()
thread.start_new_thread(self.looper, ())
#
# Writing thread
#
def looper(self):
logger.dump('writer.looper() started!', 'info')
while True:
... | #!/usr/bin/python3
import os
import sys
import time
try:
import thread
except BaseException:
import _thread as thread
__DIR__ = os.path.dirname(os.path.realpath(__file__))
sys.path.insert(0, __DIR__)
sys.path.insert(0, __DIR__ + '/../')
import logger
class writer:
| 73 | 134 | 448 | 3 | 69 | dpanic/honeypot | modules/writer.py | Python | writer | writer | 20 | 99 | 20 | 21 | d1e165fe045eb0f7ac5bb9b050ed2dab49351454 | bigcode/the-stack | train |
c8df2acca85ec424f47212a6 | train | function | def get_environment_variable(key, default=sentinel, coerce=str):
try:
value = os.environ[key]
return coerce(value)
except KeyError:
if default != sentinel:
return default
raise ValueError(
"You must specify '{}' environment variable.".format(key))
exce... | def get_environment_variable(key, default=sentinel, coerce=str):
| try:
value = os.environ[key]
return coerce(value)
except KeyError:
if default != sentinel:
return default
raise ValueError(
"You must specify '{}' environment variable.".format(key))
except Exception as e:
raise ValueError(
"Error w... | import os
sentinel = object()
def get_environment_variable(key, default=sentinel, coerce=str):
| 23 | 64 | 95 | 15 | 8 | sreekaransrinath/TearDrops | bot/utils.py | Python | get_environment_variable | get_environment_variable | 6 | 18 | 6 | 6 | 3e3d30e67eb927e9162b3a2627898d2e4c5565a9 | bigcode/the-stack | train |
081cea8eb0fdef53b6b1a1c0 | train | class | class Migration(migrations.Migration):
dependencies = [
('datapoint', '0002_auto_20160203_1929'),
]
operations = [
migrations.AddField(
model_name='datapoint',
name='collected_at',
field=models.DateTimeField(default=datetime.datetime(2016, 2, 3, 19, 43, ... | class Migration(migrations.Migration):
| dependencies = [
('datapoint', '0002_auto_20160203_1929'),
]
operations = [
migrations.AddField(
model_name='datapoint',
name='collected_at',
field=models.DateTimeField(default=datetime.datetime(2016, 2, 3, 19, 43, 23, 995365, tzinfo=utc)),
pr... | -*- coding: utf-8 -*-
# Generated by Django 1.9.1 on 2016-02-03 19:43
from __future__ import unicode_literals
import datetime
from django.db import migrations, models
from django.utils.timezone import utc
class Migration(migrations.Migration):
| 64 | 64 | 129 | 7 | 56 | p-v-o-s/hydro | Hydro/datapoint/migrations/0003_auto_20160203_1943.py | Python | Migration | Migration | 10 | 28 | 10 | 11 | 5b8b48c47a2516bfff97af45394e13f4ec25ed03 | bigcode/the-stack | train |
981e5a437bdd831dcb85a2ed | train | class | class AsstesHelper(Helper):
"""Helper class for the unit test cases."""
@staticmethod
def mock_request(*args, **kwargs):
"""To mock the requests method for unit test."""
if kwargs.get("auth")[0] == "wrong":
return MockResponse(401, data={})
if kwargs.get("auth")[1] == "w... | class AsstesHelper(Helper):
| """Helper class for the unit test cases."""
@staticmethod
def mock_request(*args, **kwargs):
"""To mock the requests method for unit test."""
if kwargs.get("auth")[0] == "wrong":
return MockResponse(401, data={})
if kwargs.get("auth")[1] == "wrong":
return Mo... | from urllib.parse import urlparse
from insightconnect_plugin_runtime.exceptions import PluginException
from icon_ibm_qradar.util.constants.constant import SUCCESS_RESPONSE_CODES
from unit_test.helpers.helper import Helper, MockResponse
class AsstesHelper(Helper):
| 50 | 64 | 205 | 7 | 42 | lukaszlaszuk/insightconnect-plugins | plugins/ibm_qradar/unit_test/helpers/assets.py | Python | AsstesHelper | AsstesHelper | 9 | 33 | 9 | 9 | a046873840c427cb5989d1cd32d93a6b3a344909 | bigcode/the-stack | train |
6447fee19786cafc829626fd | train | function | def read_out_file(file, success=True):
if success:
with open(file) as f:
lines = f.readlines()
value = lines[-1].split()[1]
return value
else:
return float("NaN")
| def read_out_file(file, success=True):
| if success:
with open(file) as f:
lines = f.readlines()
value = lines[-1].split()[1]
return value
else:
return float("NaN")
| if os.path.isfile(im_csv_fname):
# print_header = False
# result_df = result_df.append(value_dict, ignore_index=True)
# print(result_df)
result_df.to_csv(im_csv_fname, header=print_header, columns=cols)
def read_out_file(file, success=True):
| 64 | 64 | 52 | 9 | 55 | ucgmsim/IM_calculation | IM_calculation/Advanced_IM/Models/Spear_3D_Model/run.py | Python | read_out_file | read_out_file | 273 | 283 | 273 | 273 | 79e86ab0b593428a2693738d7183604ec9bdd491 | bigcode/the-stack | train |
acd2dee7d1780f0823b8271c | train | function | def main(comp_000, comp_090, output_dir, OpenSees_path):
if not os.path.exists(output_dir):
os.makedirs(args.output_dir)
script = [
OpenSees_path,
os.path.join(model_dir, "Run_script.tcl"),
comp_000,
comp_090,
output_dir,
]
print(" ".join(script))
... | def main(comp_000, comp_090, output_dir, OpenSees_path):
| if not os.path.exists(output_dir):
os.makedirs(args.output_dir)
script = [
OpenSees_path,
os.path.join(model_dir, "Run_script.tcl"),
comp_000,
comp_090,
output_dir,
]
print(" ".join(script))
subprocess.run(script)
im_name = "Spear_3D_Model"
... | import argparse
import glob
import os
import subprocess
import numpy as np
import pandas as pd
from IM_calculation.Advanced_IM import runlibs_2d
model_dir = os.path.dirname(__file__)
def main(comp_000, comp_090, output_dir, OpenSees_path):
| 63 | 78 | 262 | 18 | 45 | ucgmsim/IM_calculation | IM_calculation/Advanced_IM/Models/Spear_3D_Model/run.py | Python | main | main | 14 | 51 | 14 | 15 | 2cab9b57f3f03d95363648813b7b3d24da172cd2 | bigcode/the-stack | train |
ef46890b7a00bae57e159f31 | train | function | def calculate_geom(output_dir, im_name):
"""
generates geom by globing results from 000 and 090
output_dir: folder that contains adv_im_comp.csv. used to grab data from 000, 090.
im_name: adv_im model name
"""
df_000 = pd.read_csv(
os.path.join(output_dir, f"{im_name}_000.csv"), dtype={"... | def calculate_geom(output_dir, im_name):
| """
generates geom by globing results from 000 and 090
output_dir: folder that contains adv_im_comp.csv. used to grab data from 000, 090.
im_name: adv_im model name
"""
df_000 = pd.read_csv(
os.path.join(output_dir, f"{im_name}_000.csv"), dtype={"component": str}
)
df_090 = pd.re... | _df = pd.DataFrame.from_dict(value_dict, orient="index")
cols = list(result_df.columns)
cols.sort()
# test if file exist, if exist, no header
if os.path.isfile(im_csv_fname):
print_header = False
result_df.to_csv(im_csv_fname, mode="a", header=print_header, columns=cols)
def calculate_geo... | 85 | 85 | 285 | 9 | 76 | ucgmsim/IM_calculation | IM_calculation/Advanced_IM/Models/Spear_3D_Model/run.py | Python | calculate_geom | calculate_geom | 143 | 170 | 143 | 143 | 1462ac3d01950d1b1a090530204070f09bca2c9b | bigcode/the-stack | train |
79de2235d722d4bdf9556e3b | train | function | def create_im_csv(
output_dir,
im_name,
component,
component_dir,
check_converge=True,
print_header=True,
remove_gravity=True,
):
"""
create a csv file for each single component/analysis
"""
if check_converge:
success_glob = os.path.join(component_dir, "Analysis_*")
... | def create_im_csv(
output_dir,
im_name,
component,
component_dir,
check_converge=True,
print_header=True,
remove_gravity=True,
):
| """
create a csv file for each single component/analysis
"""
if check_converge:
success_glob = os.path.join(component_dir, "Analysis_*")
success_files = glob.glob(success_glob)
model_converged = False
for f in success_files:
with open(f) as fp:
... | csv that contains multiple rows
000,090, geom, norm
"""
# read all df
# im_csv_glob = os.path.join(output_dir, im_name + "_*" + ".csv")
df = pd.DataFrame()
df.index.name = "component"
for component in ["000", "090", "geom", "norm"]:
component_csv_fname = os.path.join(output_dir, f"{... | 224 | 224 | 749 | 39 | 184 | ucgmsim/IM_calculation | IM_calculation/Advanced_IM/Models/Spear_3D_Model/run.py | Python | create_im_csv | create_im_csv | 195 | 270 | 195 | 203 | 392df2ae7caf10ca8a6459b4824353dc031cba51 | bigcode/the-stack | train |
e5a8d296eea52193320d6bd0 | train | function | def calculate_norm(im_name, output_dir, print_header=True):
# get 000 and 090 dir
dir_000 = os.path.join(output_dir, "000")
dir_090 = os.path.join(output_dir, "090")
component = "norm"
im_csv_fname = os.path.join(output_dir, f"{im_name}_{component}.csv")
value_dict = {}
# read data from r... | def calculate_norm(im_name, output_dir, print_header=True):
# get 000 and 090 dir
| dir_000 = os.path.join(output_dir, "000")
dir_090 = os.path.join(output_dir, "090")
component = "norm"
im_csv_fname = os.path.join(output_dir, f"{im_name}_{component}.csv")
value_dict = {}
# read data from recordings
for recorder_name in ["disp", "drift", "accl"]:
# find recorder ... | os.path.exists(im_gravity_recorder):
gr_value = float(read_out_file(im_gravity_recorder))
else:
gr_value = 0
im_recorder = os.path.join(
direction_dir, os.path.join(recorder_name, im_recorder_fname)
)
with open(im_recorder) as f_im_recorder:
im_records_list_tmp = [floa... | 159 | 159 | 531 | 23 | 135 | ucgmsim/IM_calculation | IM_calculation/Advanced_IM/Models/Spear_3D_Model/run.py | Python | calculate_norm | calculate_norm | 80 | 140 | 80 | 81 | 8f91370078862295a69b8d46feaf2333a9efbe6e | bigcode/the-stack | train |
b7f2588825c3b6069e400555 | train | function | def agg_csv(output_dir, im_name, print_header=True):
"""
aggregate all data into one huge csv that contains multiple rows
000,090, geom, norm
"""
# read all df
# im_csv_glob = os.path.join(output_dir, im_name + "_*" + ".csv")
df = pd.DataFrame()
df.index.name = "component"
for compon... | def agg_csv(output_dir, im_name, print_header=True):
| """
aggregate all data into one huge csv that contains multiple rows
000,090, geom, norm
"""
# read all df
# im_csv_glob = os.path.join(output_dir, im_name + "_*" + ".csv")
df = pd.DataFrame()
df.index.name = "component"
for component in ["000", "090", "geom", "norm"]:
compon... | "))
cols = list(im_geom.columns)
cols.sort()
im_csv_fname = os.path.join(output_dir, f"{im_name}_geom.csv")
im_geom.to_csv(im_csv_fname, columns=cols, index=True, header=True)
def agg_csv(output_dir, im_name, print_header=True):
| 64 | 64 | 200 | 13 | 51 | ucgmsim/IM_calculation | IM_calculation/Advanced_IM/Models/Spear_3D_Model/run.py | Python | agg_csv | agg_csv | 173 | 191 | 173 | 173 | fd81d2674b826ad5a52825a92698f65854bf934c | bigcode/the-stack | train |
6c14ae516e0804c90df7ff6b | train | function | def read_recorder_all(direction_dir, recorder_name, im_recorder_fname):
# find corrosponding gravity file
im_gravity_dir = os.path.join(direction_dir, f"gravity_{recorder_name}")
im_gravity_recorder = os.path.join(im_gravity_dir, f"gr_{im_recorder_fname}")
if os.path.exists(im_gravity_recorder):
... | def read_recorder_all(direction_dir, recorder_name, im_recorder_fname):
# find corrosponding gravity file
| im_gravity_dir = os.path.join(direction_dir, f"gravity_{recorder_name}")
im_gravity_recorder = os.path.join(im_gravity_dir, f"gr_{im_recorder_fname}")
if os.path.exists(im_gravity_recorder):
gr_value = float(read_out_file(im_gravity_recorder))
else:
gr_value = 0
im_recorder = os.pa... | # calculate the disp&drift Norm from records from 000 and 090
calculate_norm(im_name, output_dir)
agg_csv(output_dir, im_name)
# calc norm
def read_recorder_all(direction_dir, recorder_name, im_recorder_fname):
# find corrosponding gravity file
| 64 | 64 | 207 | 25 | 38 | ucgmsim/IM_calculation | IM_calculation/Advanced_IM/Models/Spear_3D_Model/run.py | Python | read_recorder_all | read_recorder_all | 55 | 77 | 55 | 57 | 4354e5109c2a8fbdb92768acdd1e2fdd92217999 | bigcode/the-stack | train |
b606945f5f0654c6adb940ed | train | function | def select_loss_fnc(loss_type,use_probabilities=False):
"""
Selects the type of loss function to use. Choices are currently Cross-entropy or Mean-Square-Estimate.
:param loss_type: 'CE' or 'MSE'
:param use_probabilities:
:return:
"""
if loss_type == 'CE':
if use_probabilities:
... | def select_loss_fnc(loss_type,use_probabilities=False):
| """
Selects the type of loss function to use. Choices are currently Cross-entropy or Mean-Square-Estimate.
:param loss_type: 'CE' or 'MSE'
:param use_probabilities:
:return:
"""
if loss_type == 'CE':
if use_probabilities:
loss_fnc = cross_entropy_probabilities(reduction='... | import torch
import torch.nn as nn
import torch.nn.functional as F
def select_loss_fnc(loss_type,use_probabilities=False):
| 28 | 64 | 158 | 12 | 15 | tueboesen/Active-Learning | src/losses.py | Python | select_loss_fnc | select_loss_fnc | 5 | 22 | 5 | 5 | 2adc1f2813c770ffa44a1933045fb6e822508a0e | bigcode/the-stack | train |
e844f62ba2c324911584950f | train | class | class MSE_custom(torch.nn.Module):
"""
This class works just like the normal MSE loss function, with the extra option of using reduction='sum_to_samples'
which sums over all other dimension and reduce the dimension down to the number of samples. Which is useful if you want to put individual weight on each p... | class MSE_custom(torch.nn.Module):
| """
This class works just like the normal MSE loss function, with the extra option of using reduction='sum_to_samples'
which sums over all other dimension and reduce the dimension down to the number of samples. Which is useful if you want to put individual weight on each point.
"""
def __init__(self... | torch.log(F.softmax(input, dim=1))).sum(dim=1))
if self.reduction == 'none':
return loss
elif self.reduction == 'mean':
return loss.mean()
elif self.reduction == 'sum':
return loss.sum()
class MSE_custom(torch.nn.Module):
| 64 | 64 | 155 | 8 | 56 | tueboesen/Active-Learning | src/losses.py | Python | MSE_custom | MSE_custom | 48 | 61 | 48 | 48 | e30c6f840e1eeed3b4cc176d40acd3d8f4b3bf50 | bigcode/the-stack | train |
51a07acef717c7fd4302b002 | train | class | class cross_entropy_probabilities(torch.nn.Module):
"""
Cross entropy function that can handle probability targets
"""
def __init__(self,reduction='none'):
self.reduction = reduction
super(cross_entropy_probabilities,self).__init__()
def forward(self, input, target, point_weight=1)... | class cross_entropy_probabilities(torch.nn.Module):
| """
Cross entropy function that can handle probability targets
"""
def __init__(self,reduction='none'):
self.reduction = reduction
super(cross_entropy_probabilities,self).__init__()
def forward(self, input, target, point_weight=1):
assert input.size() == target.size()
... | EntropyLoss(ignore_index=-1,reduction='none')
elif loss_type == 'MSE':
loss_fnc = MSE_custom(reduction='sum_to_samples')
else:
raise ValueError("Undefined loss_fnc selected")
return loss_fnc
class cross_entropy_probabilities(torch.nn.Module):
| 64 | 64 | 214 | 9 | 54 | tueboesen/Active-Learning | src/losses.py | Python | cross_entropy_probabilities | cross_entropy_probabilities | 25 | 46 | 25 | 25 | db20fa853ede96ea48c001cf04b4ecb129e6212b | bigcode/the-stack | train |
0e065a3c21a85900d0770f62 | train | function | def save_xml(data, xml_file):
output = codecs.open(xml_file, 'w', 'utf-8')
root = etree.Element('root')
city_xml = etree.ElementTree(root)
city = etree.SubElement(root, 'city')
city.append(etree.Comment('城市信息'))
city.text = str(data)
output.write(etree.tounicode(city_xml.getroot()))
outp... | def save_xml(data, xml_file):
| output = codecs.open(xml_file, 'w', 'utf-8')
root = etree.Element('root')
city_xml = etree.ElementTree(root)
city = etree.SubElement(root, 'city')
city.append(etree.Comment('城市信息'))
city.text = str(data)
output.write(etree.tounicode(city_xml.getroot()))
output.close()
| rd.open_workbook(xlsx_file)
table = data.sheets()[0]
c = OrderedDict()
for i in range(table.nrows):
c[table.cell(i, 0).value] = table.row_values(i)[1:]
return c
def save_xml(data, xml_file):
| 64 | 64 | 86 | 8 | 55 | feikon/Python_learning | show_me_the_code/problem_0018.py | Python | save_xml | save_xml | 36 | 44 | 36 | 36 | 59871f1ee2388cf2567da0df709943004d598fb6 | bigcode/the-stack | train |
324256ac5494645d3c498392 | train | function | def read_xlsx(xlsx_file):
data = xlrd.open_workbook(xlsx_file)
table = data.sheets()[0]
c = OrderedDict()
for i in range(table.nrows):
c[table.cell(i, 0).value] = table.row_values(i)[1:]
return c
| def read_xlsx(xlsx_file):
| data = xlrd.open_workbook(xlsx_file)
table = data.sheets()[0]
c = OrderedDict()
for i in range(table.nrows):
c[table.cell(i, 0).value] = table.row_values(i)[1:]
return c
| 50
"""
# Problem describe:Convert city.xlsx file to city.xml
# Problem solve step:
# 1.Read the city.xlsx;
# 2.Write to city.xml;
import xlrd
import codecs
from lxml import etree
from collections import OrderedDict
def read_xlsx(xlsx_file):
| 64 | 64 | 68 | 8 | 55 | feikon/Python_learning | show_me_the_code/problem_0018.py | Python | read_xlsx | read_xlsx | 27 | 33 | 27 | 27 | 73726de44dfbfdfc499bf29d51b9ac61d6a76943 | bigcode/the-stack | train |
9f740040c7d25d2e8078e0de | train | class | class ServiceAccountCreatePage(BasePage):
def _get_new_service_account_form(self):
return self.find_element_by_class_name("new-service-account-form")
def set_name(self, name):
form = self._get_new_service_account_form()
field = form.find_element_by_name("name")
field.send_keys(n... | class ServiceAccountCreatePage(BasePage):
| def _get_new_service_account_form(self):
return self.find_element_by_class_name("new-service-account-form")
def set_name(self, name):
form = self._get_new_service_account_form()
field = form.find_element_by_name("name")
field.send_keys(name)
def submit(self):
form =... | _enable_button(self):
button = self.find_element_by_class_name("enable-service-account")
button.click()
def get_disable_modal(self):
element = self.find_element_by_id("disableModal")
self.wait_until_visible(element)
return DisableServiceAccountModal(element)
class ServiceAcc... | 64 | 64 | 88 | 8 | 56 | bonniech3n/merou | itests/pages/service_accounts.py | Python | ServiceAccountCreatePage | ServiceAccountCreatePage | 21 | 32 | 21 | 21 | 19e165806bae7ac429f1b04c32edc57f1e11839b | bigcode/the-stack | train |
25c1ededc2809b8dbb490609 | train | class | class ServiceAccountViewPage(BasePage):
def click_disable_button(self):
button = self.find_element_by_class_name("disable-service-account")
button.click()
def click_enable_button(self):
button = self.find_element_by_class_name("enable-service-account")
button.click()
def ge... | class ServiceAccountViewPage(BasePage):
| def click_disable_button(self):
button = self.find_element_by_class_name("disable-service-account")
button.click()
def click_enable_button(self):
button = self.find_element_by_class_name("enable-service-account")
button.click()
def get_disable_modal(self):
element =... | from selenium.webdriver.support.select import Select
from itests.pages.base import BaseModal, BasePage
class ServiceAccountViewPage(BasePage):
| 28 | 64 | 92 | 8 | 19 | bonniech3n/merou | itests/pages/service_accounts.py | Python | ServiceAccountViewPage | ServiceAccountViewPage | 6 | 18 | 6 | 6 | 78d3e1414ddd0ed866294568f6fe2e154ddd688c | bigcode/the-stack | train |
3e2917dba13f7493a4d52dff | train | class | class DisableServiceAccountModal(BaseModal):
pass
| class DisableServiceAccountModal(BaseModal):
| pass
| ):
form = self._get_enable_service_account_form()
owner_select = form.find_element_by_tag_name("select")
Select(owner_select).select_by_visible_text(owner)
def submit(self):
form = self._get_enable_service_account_form()
form.submit()
class DisableServiceAccountModal(BaseMod... | 64 | 64 | 11 | 8 | 56 | bonniech3n/merou | itests/pages/service_accounts.py | Python | DisableServiceAccountModal | DisableServiceAccountModal | 49 | 50 | 49 | 49 | 493025889e37eb4250f8bfc1d805cbfab98395bd | bigcode/the-stack | train |
e42aa5af645ca75deb694ef6 | train | class | class ServiceAccountEnablePage(BasePage):
def _get_enable_service_account_form(self):
return self.find_element_by_class_name("enable-service-account-form")
def select_owner(self, owner):
form = self._get_enable_service_account_form()
owner_select = form.find_element_by_tag_name("select"... | class ServiceAccountEnablePage(BasePage):
| def _get_enable_service_account_form(self):
return self.find_element_by_class_name("enable-service-account-form")
def select_owner(self, owner):
form = self._get_enable_service_account_form()
owner_select = form.find_element_by_tag_name("select")
Select(owner_select).select_by_v... | def set_name(self, name):
form = self._get_new_service_account_form()
field = form.find_element_by_name("name")
field.send_keys(name)
def submit(self):
form = self._get_new_service_account_form()
form.submit()
class ServiceAccountEnablePage(BasePage):
| 64 | 64 | 95 | 8 | 56 | bonniech3n/merou | itests/pages/service_accounts.py | Python | ServiceAccountEnablePage | ServiceAccountEnablePage | 35 | 46 | 35 | 35 | 2e5dc4c72b72912929fa63790e4d3eea4b899058 | bigcode/the-stack | train |
53e02b24c482f9c368855f7f | train | class | class ThrowStmt(Statement):
def __init__(self, kwargs={}):
super(Statement, self).__init__(kwargs)
locs = _import()
# Expression expr;
e = kwargs.get(u'expr', {})
self._expr = locs[e[u'@t']](e) if e else None
self.add_as_parent([self.expr])
@proper... | class ThrowStmt(Statement):
| def __init__(self, kwargs={}):
super(Statement, self).__init__(kwargs)
locs = _import()
# Expression expr;
e = kwargs.get(u'expr', {})
self._expr = locs[e[u'@t']](e) if e else None
self.add_as_parent([self.expr])
@property
def expr(self): retur... | #!/usr/bin/env python
from .statement import Statement
from . import _import
class ThrowStmt(Statement):
| 24 | 64 | 114 | 6 | 17 | natebragg/java-sketch | jskparser/ast/stmt/throwstmt.py | Python | ThrowStmt | ThrowStmt | 7 | 22 | 7 | 7 | 55b088749307837edf4165b9d6c1428ac1e88271 | bigcode/the-stack | train |
c7fc456fd6abf4bb0dbd4c15 | train | class | class ZFSSAApi(object):
"""ZFSSA API proxy class"""
def __init__(self):
self.host = None
self.url = None
self.rclient = None
def __del__(self):
if self.rclient and self.rclient.islogin():
self.rclient.logout()
def _is_pool_owned(self, pdata):
"""Ret... | class ZFSSAApi(object):
| """ZFSSA API proxy class"""
def __init__(self):
self.host = None
self.url = None
self.rclient = None
def __del__(self):
if self.rclient and self.rclient.islogin():
self.rclient.logout()
def _is_pool_owned(self, pdata):
"""Returns True if the pool's ... | 2014, 2015, Oracle and/or its affiliates. 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 re... | 256 | 256 | 8,217 | 7 | 249 | usernameisnull/cinder-explanation | cinder/volume/drivers/zfssa/zfssarest.py | Python | ZFSSAApi | ZFSSAApi | 34 | 999 | 34 | 34 | 1ca408e4ffa6a0436d1d0087a04f1d0e4cac7c8a | bigcode/the-stack | train |
fd200406cd1c9cdc0f272a8c | train | class | class ZFSSANfsApi(ZFSSAApi):
"""ZFSSA API proxy class for NFS driver"""
projects_path = '/api/storage/v1/pools/%s/projects'
project_path = projects_path + '/%s'
shares_path = project_path + '/filesystems'
share_path = shares_path + '/%s'
share_snapshots_path = share_path + '/snapshots'
shar... | class ZFSSANfsApi(ZFSSAApi):
| """ZFSSA API proxy class for NFS driver"""
projects_path = '/api/storage/v1/pools/%s/projects'
project_path = projects_path + '/%s'
shares_path = project_path + '/filesystems'
share_path = shares_path + '/%s'
share_snapshots_path = share_path + '/snapshots'
share_snapshot_path = share_snaps... | '
svc = "%(base)s/%(prop)s" % {'base': base, 'prop': schema['property']}
ret = self.rclient.get(svc)
if ret.status == restclient.Status.OK:
LOG.warning(_LW('Property %s already exists.'), schema['property'])
return
ret = self.rclient.post(base, schema)
i... | 256 | 256 | 2,251 | 12 | 243 | usernameisnull/cinder-explanation | cinder/volume/drivers/zfssa/zfssarest.py | Python | ZFSSANfsApi | ZFSSANfsApi | 1,002 | 1,272 | 1,002 | 1,002 | 713f77223332c8d55ba8b75810d82a619fc7ba14 | bigcode/the-stack | train |
c878f3e1415ec1367c27d58f | train | function | def factory_restclient(url, **kwargs):
return restclient.RestClientURL(url, **kwargs)
| def factory_restclient(url, **kwargs):
| return restclient.RestClientURL(url, **kwargs)
| from cinder import exception
from cinder.i18n import _, _LE, _LW
from cinder.volume.drivers.zfssa import restclient
from cinder.volume.drivers.zfssa import webdavclient
LOG = log.getLogger(__name__)
def factory_restclient(url, **kwargs):
| 64 | 64 | 21 | 9 | 55 | usernameisnull/cinder-explanation | cinder/volume/drivers/zfssa/zfssarest.py | Python | factory_restclient | factory_restclient | 30 | 31 | 30 | 30 | 154fc3192dc3cc3f4329091a8fa15987dd750990 | bigcode/the-stack | train |
dbe63ef8018fd652582ec797 | train | function | def erro(msg='ERRO'):
"""
-> Cria uma mensagem de erro
:param msg:mensagem que será usada no erro (padrão = 'ERRO')
:return:string da mensagem de erro criada criada
"""
return f"\t{color('vermelho')}{msg}{color()}"
| def erro(msg='ERRO'):
| """
-> Cria uma mensagem de erro
:param msg:mensagem que será usada no erro (padrão = 'ERRO')
:return:string da mensagem de erro criada criada
"""
return f"\t{color('vermelho')}{msg}{color()}"
| {color('azul')}{i:<{tam - 6}}"
interface += f"\n\t{color('amarelo')}{'='*tam}{color('azul')}\n\t {pos}{color('verde')}"
return interface
def erro(msg='ERRO'):
| 64 | 64 | 70 | 7 | 56 | Felix-xilef/Curso-de-Python | Desafios/Desafio115Pacote/Menu/__init__.py | Python | erro | erro | 74 | 80 | 74 | 74 | 2b3601e96ab0e8d3a6e56cf7c13337bcac4b0c57 | bigcode/the-stack | train |
bdf4adaf0afb07be2689dacd | train | function | def color(font=''):
"""
-> Fornece o código ANSI para a cor de texto desejada, não forneça entrada para a cor padrão
:param font:nome da cor desejada opções - preto, vermelho, verde, amarelo, azul, magenta, cyan e cinza claro
:return:código ANSI para texto na cor escolhida
"""
font.l... | def color(font=''):
| """
-> Fornece o código ANSI para a cor de texto desejada, não forneça entrada para a cor padrão
:param font:nome da cor desejada opções - preto, vermelho, verde, amarelo, azul, magenta, cyan e cinza claro
:return:código ANSI para texto na cor escolhida
"""
font.lower()
cor = '\0... | def color(font=''):
| 5 | 64 | 213 | 5 | 0 | Felix-xilef/Curso-de-Python | Desafios/Desafio115Pacote/Menu/__init__.py | Python | color | color | 1 | 26 | 1 | 1 | 4ce38a079b37531fd26dc1ef3134222a6cbc9c5e | bigcode/the-stack | train |
60852c64d62c5250f7da0e0c | train | function | def cabecalho(msg=''):
"""
-> Cria um 'cabeçalho' no seguinte formato:
===========
msg
===========
:param msg:mensagem que será usada no cabeçalho do menu (padrão = '')
:return:string cabeçalho criado
"""
tam = 50
if len(msg) > ... | def cabecalho(msg=''):
| """
-> Cria um 'cabeçalho' no seguinte formato:
===========
msg
===========
:param msg:mensagem que será usada no cabeçalho do menu (padrão = '')
:return:string cabeçalho criado
"""
tam = 50
if len(msg) > tam:
tam = len(... | cor += '34'
elif font == 'magenta':
cor += '35'
elif font == 'cyan':
cor += '36'
elif font == 'cinza claro':
cor += '37'
cor += 'm'
return cor
def cabecalho(msg=''):
| 64 | 64 | 146 | 7 | 56 | Felix-xilef/Curso-de-Python | Desafios/Desafio115Pacote/Menu/__init__.py | Python | cabecalho | cabecalho | 29 | 43 | 29 | 29 | ac5f1e6fa4f7e3b8e5ebd24879352fbce32a364e | bigcode/the-stack | train |
e3f58c65e8e6cf5877bfa4a9 | train | function | def menu(msg='Menu', pos='Digite uma opção: ', *op):
"""
-> Cria um 'menu' no seguinte formato:
===========
msg
===========
op1
...
opn
===========
pos
:param msg:... | def menu(msg='Menu', pos='Digite uma opção: ', *op):
| """
-> Cria um 'menu' no seguinte formato:
===========
msg
===========
op1
...
opn
===========
pos
:param msg:mensagem que será usada no cabeçalho do menu (padrão ... | ) + 8
interface = f"\n\t{color('amarelo')}{'='*tam}\n\t{color('azul')}{msg:^{tam}}\n\t{color('amarelo')}{'='*tam}{color()}"
return interface
def menu(msg='Menu', pos='Digite uma opção: ', *op):
| 77 | 77 | 259 | 16 | 60 | Felix-xilef/Curso-de-Python | Desafios/Desafio115Pacote/Menu/__init__.py | Python | menu | menu | 46 | 71 | 46 | 46 | 3330b7a72a17690498ac3be5fddfc0e6bd0758d7 | bigcode/the-stack | train |
43a1c9408ab0699066d3330f | train | class | class Sequencer(SimpleElaboratable):
"""Sequences a 1x1 convolution.
This is the control logic required to calculate all output channel values
for a single input pixel.
Public Interface
---------------
start_run: Signal() in
When the run commences.
in_store_ready: Signal() in
... | class Sequencer(SimpleElaboratable):
| """Sequences a 1x1 convolution.
This is the control logic required to calculate all output channel values
for a single input pixel.
Public Interface
---------------
start_run: Signal() in
When the run commences.
in_store_ready: Signal() in
Input store has data available
... |
---------------
start_run: Signal() in
High for a single cycle when a run is started.
all_output_finished: Signal() in
High when all of the output channels calculations have been started.
in_store_ready: Signal() in
High while input store has data available for read.
fifo_ha... | 244 | 244 | 815 | 8 | 236 | keadwen/CFU-Playground | proj/mnv2_first/gateware/sequencing.py | Python | Sequencer | Sequencer | 101 | 193 | 101 | 101 | b95c9ab950db720fa262b005781ee7b56fc002a1 | bigcode/the-stack | train |
6b6ccbe110347813239f8ec8 | train | class | class UpCounter(SimpleElaboratable):
"""Counts pulses.
Parameters
----------
width: int
Number of bits in counter
Public Interface
---------------
restart: Signal() in
Zero all internal counter, get ready to start again.
en: Signal() in
Count up by one.
done... | class UpCounter(SimpleElaboratable):
| """Counts pulses.
Parameters
----------
width: int
Number of bits in counter
Public Interface
---------------
restart: Signal() in
Zero all internal counter, get ready to start again.
en: Signal() in
Count up by one.
done: Signal() out
Set high for o... | specific language governing permissions and
# limitations under the License.
from nmigen import Signal, Mux
from nmigen_cfu import SimpleElaboratable
from . import config
from .delay import Delayer
from .macc import Madd4Pipeline
from .post_process import PostProcessor
class UpCounter(SimpleElaboratable):
| 69 | 69 | 230 | 8 | 60 | keadwen/CFU-Playground | proj/mnv2_first/gateware/sequencing.py | Python | UpCounter | UpCounter | 26 | 62 | 26 | 26 | 5c5be30d90de6b6f6c7a650241b28feb2bbc2ed0 | bigcode/the-stack | train |
0677c72442ae00079d3b0d39 | train | class | class GateCalculator(SimpleElaboratable):
"""Calcaulates the 'gate' signal
Public Interface
---------------
start_run: Signal() in
High for a single cycle when a run is started.
all_output_finished: Signal() in
High when all of the output channels calculations have been started.
... | class GateCalculator(SimpleElaboratable):
| """Calcaulates the 'gate' signal
Public Interface
---------------
start_run: Signal() in
High for a single cycle when a run is started.
all_output_finished: Signal() in
High when all of the output channels calculations have been started.
in_store_ready: Signal() in
High ... | 1
next_count = Mux(count == last_count, 0, count + 1)
with m.If(self.en):
m.d.sync += count.eq(next_count)
m.d.comb += self.done.eq(count == last_count)
with m.If(self.restart):
m.d.sync += count.eq(0)
class GateCalculator(SimpleElaboratable):
| 77 | 77 | 258 | 8 | 69 | keadwen/CFU-Playground | proj/mnv2_first/gateware/sequencing.py | Python | GateCalculator | GateCalculator | 65 | 98 | 65 | 65 | d234e359df9d0ffc269aaa9c7a27f8a2cd1dfaaf | bigcode/the-stack | train |
d071c682c4f5e439fd30ace4 | train | function | def setup(bot):
bot.add_cog(Screenshare(bot)) | def setup(bot):
| bot.add_cog(Screenshare(bot)) | from .screenshare import Screenshare
__red_end_user_data_statement__ = (
"This cog does not persistently store data or metadata about users."
)
def setup(bot):
| 37 | 64 | 14 | 4 | 33 | pordino/kennnyshiwa-cogs | screenshare/__init__.py | Python | setup | setup | 7 | 8 | 7 | 7 | 34c5b61560206f5fd2dc0de5f694805edcd7de62 | bigcode/the-stack | train |
b538841162abae04fd6f28be | train | function | def resolve_heap_object_factory(obj: Any, options: Options = None) -> HeapObjectFactory:
if isinstance(obj, basic_types):
return BasicHeapObjectFactory(obj, options)
if isinstance(obj, sequence_types):
return SequenceHeapObjectFactory(obj, options)
if isinstance(obj, key_value_types):
... | def resolve_heap_object_factory(obj: Any, options: Options = None) -> HeapObjectFactory:
| if isinstance(obj, basic_types):
return BasicHeapObjectFactory(obj, options)
if isinstance(obj, sequence_types):
return SequenceHeapObjectFactory(obj, options)
if isinstance(obj, key_value_types):
return KvpHeapObjectFactory(obj, options)
if isinstance(obj, named_types):
... | _factory import KvpHeapObjectFactory
from .named_heap_object_factory import NamedHeapObjectFactory
from .sequence_heap_object_factory import SequenceHeapObjectFactory
from .unknown_heap_object_factory import UnknownHeapObjectFactory
def resolve_heap_object_factory(obj: Any, options: Options = None) -> HeapObjectFactory... | 64 | 64 | 155 | 20 | 43 | vincentxavier/nbtutor | nbtutor/ipython/factories/heap_object_factory.py | Python | resolve_heap_object_factory | resolve_heap_object_factory | 16 | 35 | 16 | 16 | d4f4102fd533304b1b1cd8ec35044b04be1dd011 | bigcode/the-stack | train |
0c81922e4b515bbafba9eecb | train | function | def create_heap_object(obj: Any, options: Options = None) -> HeapObject:
return resolve_heap_object_factory(obj, options).create()
| def create_heap_object(obj: Any, options: Options = None) -> HeapObject:
| return resolve_heap_object_factory(obj, options).create()
| return ClassHeapObjectFactory(obj, options)
if isinstance(type(obj), type) and hasattr(obj, '__dict__'):
return InstanceHeapObjectFactory(obj, options)
return UnknownHeapObjectFactory(obj, options)
def create_heap_object(obj: Any, options: Options = None) -> HeapObject:
| 64 | 64 | 30 | 18 | 46 | vincentxavier/nbtutor | nbtutor/ipython/factories/heap_object_factory.py | Python | create_heap_object | create_heap_object | 38 | 39 | 38 | 38 | 6ff69eff4d3ad65d5064908fb9871dd720b6d919 | bigcode/the-stack | train |
81fe693c27fedd044c1b1eeb | train | function | def create_heap_objects(objects: Collection[Any], options: Options = None) -> Dict[str, HeapObject]:
heap: Dict[str, HeapObject] = dict()
reduce_heap_objects(objects, heap, options)
return heap
| def create_heap_objects(objects: Collection[Any], options: Options = None) -> Dict[str, HeapObject]:
| heap: Dict[str, HeapObject] = dict()
reduce_heap_objects(objects, heap, options)
return heap
| ()
objects_to_reduce = factory.get_objects_to_reduce()
if objects_to_reduce is not None and len(objects_to_reduce) > 0:
reduce_heap_objects(objects_to_reduce, heap, options)
def create_heap_objects(objects: Collection[Any], options: Options = None) -> Dict[str, HeapObject]:
| 64 | 64 | 48 | 22 | 42 | vincentxavier/nbtutor | nbtutor/ipython/factories/heap_object_factory.py | Python | create_heap_objects | create_heap_objects | 56 | 59 | 56 | 56 | e2f952674b509226f957b445c369030910700de6 | bigcode/the-stack | train |
d12469902ee4d53eea7f1494 | train | function | def reduce_heap_objects(objects: Collection[Any], heap: Dict[str, HeapObject], options: Options = None) -> None:
for obj in objects:
obj_id = HeapObjectFactory.get_object_id(obj)
if heap.get(obj_id, None) is not None:
continue
factory = resolve_heap_object_factory(obj, options)
... | def reduce_heap_objects(objects: Collection[Any], heap: Dict[str, HeapObject], options: Options = None) -> None:
| for obj in objects:
obj_id = HeapObjectFactory.get_object_id(obj)
if heap.get(obj_id, None) is not None:
continue
factory = resolve_heap_object_factory(obj, options)
heap[obj_id] = factory.create()
objects_to_reduce = factory.get_objects_to_reduce()
if o... | UnknownHeapObjectFactory(obj, options)
def create_heap_object(obj: Any, options: Options = None) -> HeapObject:
return resolve_heap_object_factory(obj, options).create()
def reduce_heap_objects(objects: Collection[Any], heap: Dict[str, HeapObject], options: Options = None) -> None:
| 64 | 64 | 121 | 26 | 38 | vincentxavier/nbtutor | nbtutor/ipython/factories/heap_object_factory.py | Python | reduce_heap_objects | reduce_heap_objects | 42 | 53 | 42 | 42 | d47fca210bac1aeec1d220a33a2a73b471f04423 | bigcode/the-stack | train |
e60d2b69f2d71926814fc621 | train | class | class SQLiteMixin(object):
@property
def dbcur(self):
pid = (os.getpid(), threading.current_thread().ident)
if not (self.conn and pid == self.last_pid):
self.last_pid = pid
self.conn = sqlite3.connect(self.path, isolation_level=None)
return self.conn.cursor()
| class SQLiteMixin(object):
@property
| def dbcur(self):
pid = (os.getpid(), threading.current_thread().ident)
if not (self.conn and pid == self.last_pid):
self.last_pid = pid
self.conn = sqlite3.connect(self.path, isolation_level=None)
return self.conn.cursor()
| import os
import time
import sqlite3
import threading
class SQLiteMixin(object):
@property
| 22 | 64 | 69 | 9 | 12 | rahman-mahmudur/PyART | simplejson_test/testdata/pyspider/database/sqlite/tmp.py | Python | SQLiteMixin | SQLiteMixin | 7 | 15 | 7 | 9 | 39c29ca6cdad0849a9ac15e5ab47a929a81ff150 | bigcode/the-stack | train |
080b462134f204a7f761a99c | train | class | class SplitTableMixin(object):
UPDATE_PROJECTS_TIME = 10 * 60
def _tablename(self, project):
if self.__tablename__:
return '%s_%s' % (self.__tablename__, project)
else:
return project
@property
def projects(self):
if time.time() - getattr(self, '_last_up... | class SplitTableMixin(object):
| UPDATE_PROJECTS_TIME = 10 * 60
def _tablename(self, project):
if self.__tablename__:
return '%s_%s' % (self.__tablename__, project)
else:
return project
@property
def projects(self):
if time.time() - getattr(self, '_last_update_projects', 0) \
... | dbcur(self):
pid = (os.getpid(), threading.current_thread().ident)
if not (self.conn and pid == self.last_pid):
self.last_pid = pid
self.conn = sqlite3.connect(self.path, isolation_level=None)
return self.conn.cursor()
class SplitTableMixin(object):
| 64 | 64 | 214 | 6 | 58 | rahman-mahmudur/PyART | simplejson_test/testdata/pyspider/database/sqlite/tmp.py | Python | SplitTableMixin | SplitTableMixin | 18 | 49 | 18 | 18 | 25bb1af22ceb0c26ddde8d40f549664aa8bf5ed1 | bigcode/the-stack | train |
a4ced511a4aff339d0e518f1 | train | class | class Session:
def __init__(self):
self.__requests_session = requests.Session()
# self.__requests_session.headers.update({"User-Agent": "medex"})
def api_request(self, url, params=None, auth=None, http_call="get"):
if http_call == "get":
response = self.__requests_session.ge... | class Session:
| def __init__(self):
self.__requests_session = requests.Session()
# self.__requests_session.headers.update({"User-Agent": "medex"})
def api_request(self, url, params=None, auth=None, http_call="get"):
if http_call == "get":
response = self.__requests_session.get(url)
... | import requests
import time
class APIResponseError(Exception):
""" Exception raise if the API replies with an HTTP code
not in the 2xx range. """
pass
class Session:
| 41 | 67 | 225 | 3 | 37 | SiahaanBernard/python-indodax | indodax/common.py | Python | Session | Session | 9 | 36 | 9 | 9 | 09d6ef4f195c04bb7f2e71e748d0bb66acb8aead | bigcode/the-stack | train |
5b837200823bc8ad37d34cb4 | train | class | class APIResponseError(Exception):
""" Exception raise if the API replies with an HTTP code
not in the 2xx range. """
pass
| class APIResponseError(Exception):
| """ Exception raise if the API replies with an HTTP code
not in the 2xx range. """
pass
| import requests
import time
class APIResponseError(Exception):
| 12 | 64 | 32 | 6 | 5 | SiahaanBernard/python-indodax | indodax/common.py | Python | APIResponseError | APIResponseError | 4 | 7 | 4 | 4 | 527dfcda3c69e416e50105267862c2529965b485 | bigcode/the-stack | train |
7442fbd262a349d70b0e5936 | train | function | def threshold_choose(scores, threshold):
mask = scores.gt(threshold)
topk_scores = scores[mask]
topk_inds = torch.arange(0, scores.numel())[mask.squeeze().flatten()]
topk_inds = topk_inds.cuda().to(torch.int64)
batch, cat, height, width = scores.size()
topk_inds = topk_inds % (height * width)
... | def threshold_choose(scores, threshold):
| mask = scores.gt(threshold)
topk_scores = scores[mask]
topk_inds = torch.arange(0, scores.numel())[mask.squeeze().flatten()]
topk_inds = topk_inds.cuda().to(torch.int64)
batch, cat, height, width = scores.size()
topk_inds = topk_inds % (height * width)
topk_ys = (topk_inds / width).int().fl... | (topk_ys.view(batch, -1, 1), topk_ind).view(batch, K)
topk_xs = _gather_feat(topk_xs.view(batch, -1, 1), topk_ind).view(batch, K)
return topk_score, topk_inds, topk_clses, topk_ys, topk_xs
def threshold_choose(scores, threshold):
| 86 | 86 | 288 | 7 | 78 | chenjun2hao/facemask | facemask/model/decode.py | Python | threshold_choose | threshold_choose | 33 | 52 | 33 | 33 | 5e7d4305684a2e9cf5ed4dd1493414b90dca2caa | bigcode/the-stack | train |
ff2c4133098a60a3b0d31b51 | train | function | def _nms(heat, kernel=3):
pad = (kernel - 1) // 2
hmax = nn.functional.max_pool2d(
heat, (kernel, kernel), stride=1, padding=pad)
keep = (hmax == heat).float()
return heat * keep
| def _nms(heat, kernel=3):
| pad = (kernel - 1) // 2
hmax = nn.functional.max_pool2d(
heat, (kernel, kernel), stride=1, padding=pad)
keep = (hmax == heat).float()
return heat * keep
| import torch
import torch.nn as nn
from ..utils.util import _gather_feat,_tranpose_and_gather_feat
def _nms(heat, kernel=3):
| 37 | 64 | 68 | 11 | 25 | chenjun2hao/facemask | facemask/model/decode.py | Python | _nms | _nms | 5 | 11 | 5 | 5 | 9cd4a0e682298ebb81e1182fa725e8839228d828 | bigcode/the-stack | train |
6498536ca14299a826e4ced0 | train | function | def ctdet_decode(heat, wh, reg=None, cat_spec_wh=False, K=100):
batch, cat, height, width = heat.size()
heat = _nms(heat)
scores, inds, clses, ys, xs = _topk(heat, K=K)
# scores, inds, clses, ys, xs, K = threshold_choose(heat, threshold=threshold)
if reg is not None:
... | def ctdet_decode(heat, wh, reg=None, cat_spec_wh=False, K=100):
| batch, cat, height, width = heat.size()
heat = _nms(heat)
scores, inds, clses, ys, xs = _topk(heat, K=K)
# scores, inds, clses, ys, xs, K = threshold_choose(heat, threshold=threshold)
if reg is not None:
reg = _tranpose_and_gather_feat(reg, inds)
reg = reg.view... | -1, 1), topk_ind).view(batch, K)
topk_ys = _gather_feat(topk_ys.view(batch, -1, 1), topk_ind).view(batch, K)
topk_xs = _gather_feat(topk_xs.view(batch, -1, 1), topk_ind).view(batch, K)
return topk_score, topk_inds, topk_clses, topk_ys, topk_xs, K
def ctdet_decode(heat, wh, reg=None, cat_spec_wh=False, K=1... | 128 | 128 | 427 | 22 | 105 | chenjun2hao/facemask | facemask/model/decode.py | Python | ctdet_decode | ctdet_decode | 55 | 84 | 55 | 55 | 28d23bb11eceff0909ad5ba855971d1b5c77530d | bigcode/the-stack | train |
1e105055da02e77878ea6a8e | train | function | def _topk(scores, K=40):
batch, cat, height, width = scores.size()
topk_scores, topk_inds = torch.topk(scores.view(batch, cat, -1), K) # 前100个点
topk_inds = topk_inds % (height * width)
topk_ys = (topk_inds / width).int().float()
topk_xs = (topk_inds % width).int().float()
... | def _topk(scores, K=40):
| batch, cat, height, width = scores.size()
topk_scores, topk_inds = torch.topk(scores.view(batch, cat, -1), K) # 前100个点
topk_inds = topk_inds % (height * width)
topk_ys = (topk_inds / width).int().float()
topk_xs = (topk_inds % width).int().float()
topk_score, topk_... | def _nms(heat, kernel=3):
pad = (kernel - 1) // 2
hmax = nn.functional.max_pool2d(
heat, (kernel, kernel), stride=1, padding=pad)
keep = (hmax == heat).float()
return heat * keep
def _topk(scores, K=40):
| 78 | 78 | 263 | 10 | 67 | chenjun2hao/facemask | facemask/model/decode.py | Python | _topk | _topk | 14 | 30 | 14 | 14 | 6eac754fbf1a64aa12c7da95d13a6adf3d83de04 | bigcode/the-stack | train |
f9ddf30cbb62e91c1c5943ee | train | class | class FakeElasticsearch(Elasticsearch):
__documents_dict = None
def __init__(self, hosts=None, transport_class=None, **kwargs):
self.__documents_dict = {}
self.__scrolls = {}
@query_params()
def ping(self, params=None):
return True
@query_params()
def info(self, params... | class FakeElasticsearch(Elasticsearch):
| __documents_dict = None
def __init__(self, hosts=None, transport_class=None, **kwargs):
self.__documents_dict = {}
self.__scrolls = {}
@query_params()
def ping(self, params=None):
return True
@query_params()
def info(self, params=None):
return {
'st... | # -*- coding: utf-8 -*-
import json
import sys
from elasticsearch import Elasticsearch
from elasticsearch.client.utils import query_params
from elasticsearch.exceptions import NotFoundError
from elasticmock.utilities import get_random_id, get_random_scroll_id
PY3 = sys.version_info[0] == 3
if PY3:
unicode = str... | 82 | 256 | 2,236 | 8 | 73 | AdamGold/elasticmock | elasticmock/fake_elasticsearch.py | Python | FakeElasticsearch | FakeElasticsearch | 17 | 297 | 17 | 17 | ff1b3e19488d4267394c3b6c9d788a33ff176b46 | bigcode/the-stack | train |
bda5a5f39e701077315554e1 | train | function | def square_error(x, y):
return (x-y).pow(2).sum()
| def square_error(x, y):
| return (x-y).pow(2).sum()
| import torch
def square_error(x, y):
| 10 | 64 | 19 | 7 | 2 | nirvguy/annpy | annpy/metrics.py | Python | square_error | square_error | 3 | 4 | 3 | 3 | 52877427c93a78878102ff6994f844962bfb892c | bigcode/the-stack | train |
660e46d7b122e9d757197d44 | train | function | def count_fails(x, y):
return (x!=y).sum()
| def count_fails(x, y):
| return (x!=y).sum()
| import torch
def square_error(x, y):
return (x-y).pow(2).sum()
def count_fails(x, y):
| 30 | 64 | 17 | 8 | 22 | nirvguy/annpy | annpy/metrics.py | Python | count_fails | count_fails | 6 | 7 | 6 | 6 | 357e12631672f223a6f64a608181df6beaffec22 | bigcode/the-stack | train |
9b99633cc42ba2e301fe7c58 | train | class | class DateTimeEncoder(JSONEncoder):
#Override the default method
def default(self, obj):
if isinstance(obj, (datetime.date, datetime.datetime)):
return obj.isoformat()
| class DateTimeEncoder(JSONEncoder):
#Override the default method
| def default(self, obj):
if isinstance(obj, (datetime.date, datetime.datetime)):
return obj.isoformat()
| datetime
from json import JSONEncoder
employee = {
"id": 456,
"name": "William Smith",
"salary": 8000,
"joindate": datetime.datetime.now()
}
# subclass JSONEncoder
class DateTimeEncoder(JSONEncoder):
#Override the default method
| 64 | 64 | 39 | 14 | 49 | PatrickVienne/PythonAssessment | answers/q8.py | Python | DateTimeEncoder | DateTimeEncoder | 17 | 21 | 17 | 18 | 02cd71aa919159c7379de49b15806552f7deab1d | bigcode/the-stack | train |
ab5439960f4b65498bb283a5 | train | function | def _add_learning_rate_args(parser):
group = parser.add_argument_group(title='learning rate')
group.add_argument('--lr', type=float, default=None,
help='Initial learning rate. Depending on decay style '
'and initial warmup, the learing rate at each '
... | def _add_learning_rate_args(parser):
| group = parser.add_argument_group(title='learning rate')
group.add_argument('--lr', type=float, default=None,
help='Initial learning rate. Depending on decay style '
'and initial warmup, the learing rate at each '
'iteration would be differen... | group.add_argument('--codecarbon-dir', type=str, default=None,
help='Write CodeCarbon logs to this directory.')
return parser
def _add_initialization_args(parser):
group = parser.add_argument_group(title='initialization')
group.add_argument('--seed', type=int, default=1234,
... | 160 | 160 | 535 | 8 | 151 | adammoody/Megatron-DeepSpeed | megatron/arguments.py | Python | _add_learning_rate_args | _add_learning_rate_args | 481 | 524 | 481 | 481 | 8598b39d54939b8140d996c45f18c3fab74f8a17 | bigcode/the-stack | train |
31861221e7bd156ab26c612e | train | function | def _add_zero_args(parser):
"""Text generate arguments."""
group = parser.add_argument_group('ZeRO configurations', 'configurations')
group.add_argument("--zero-stage", type=int, default=1.0)
group.add_argument('--zero-reduce-scatter', action='store_true',
help='Use reduce scatte... | def _add_zero_args(parser):
| """Text generate arguments."""
group = parser.add_argument_group('ZeRO configurations', 'configurations')
group.add_argument("--zero-stage", type=int, default=1.0)
group.add_argument('--zero-reduce-scatter', action='store_true',
help='Use reduce scatter if specified')
group.a... | task')
group.add_argument('--num-channels', type=int, default=3,
help='Number of channels in input image data')
group.add_argument('--patch-dim', type=int, default=16,
help='patch dimension used in vit')
return parser
def _add_zero_args(parser):
| 65 | 65 | 217 | 7 | 57 | adammoody/Megatron-DeepSpeed | megatron/arguments.py | Python | _add_zero_args | _add_zero_args | 790 | 805 | 790 | 790 | f4199caba48bf2940136fcf826f57966f676a619 | bigcode/the-stack | train |
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