body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
|---|---|---|---|---|---|---|---|
def apply_bbox_cutout(image, bboxes, pad_fraction):
'Applies cutout to a single bounding box within image.'
random_index = tf.random_uniform(shape=[], maxval=tf.shape(bboxes)[0], dtype=tf.int32)
chosen_bbox = tf.gather(bboxes, random_index)
(mask, mean) = _cutout_inside_bbox(image, chosen_bbox, pad_frac... | -3,658,342,878,226,009,000 | Applies cutout to a single bounding box within image. | efficientdet/aug/autoaugment.py | apply_bbox_cutout | datawowio/automl | python | def apply_bbox_cutout(image, bboxes, pad_fraction):
random_index = tf.random_uniform(shape=[], maxval=tf.shape(bboxes)[0], dtype=tf.int32)
chosen_bbox = tf.gather(bboxes, random_index)
(mask, mean) = _cutout_inside_bbox(image, chosen_bbox, pad_fraction)
replace = (mean if replace_with_mean else 128... |
@badpenny.periodic_task(seconds=TASK_TIME_OUT)
def cleanup_old_tasks(job_status):
'delete any tracker task if it is older than the time a task can live for.'
session = current_app.db.session('relengapi')
expiry_cutoff = (now() - datetime.timedelta(seconds=TASK_TIME_OUT))
table = tables.ArchiverTask
... | -4,374,379,887,311,869,400 | delete any tracker task if it is older than the time a task can live for. | relengapi/blueprints/archiver/__init__.py | cleanup_old_tasks | lundjordan/build-relengapi | python | @badpenny.periodic_task(seconds=TASK_TIME_OUT)
def cleanup_old_tasks(job_status):
session = current_app.db.session('relengapi')
expiry_cutoff = (now() - datetime.timedelta(seconds=TASK_TIME_OUT))
table = tables.ArchiverTask
for tracker in session.query(table).order_by(table.created_at):
if ... |
@bp.route('/status/<task_id>')
@api.apimethod(MozharnessArchiveTask, unicode)
def task_status(task_id):
"\n Check and return the current state of the create_and_upload_archive celery task with task id\n of <task_id>.\n\n If the task is unknown, state will be PENDING. Once the task starts it will be updated... | 2,060,864,171,519,897,900 | Check and return the current state of the create_and_upload_archive celery task with task id
of <task_id>.
If the task is unknown, state will be PENDING. Once the task starts it will be updated to
STARTED and finally, if it completes, it will be either SUCCESS (no exceptions), or FAILURE.
See update_state() within cr... | relengapi/blueprints/archiver/__init__.py | task_status | lundjordan/build-relengapi | python | @bp.route('/status/<task_id>')
@api.apimethod(MozharnessArchiveTask, unicode)
def task_status(task_id):
"\n Check and return the current state of the create_and_upload_archive celery task with task id\n of <task_id>.\n\n If the task is unknown, state will be PENDING. Once the task starts it will be updated... |
@bp.route('/hgmo/<path:repo>/<rev>')
@api.apimethod(None, unicode, unicode, unicode, unicode, unicode, status_code=302)
def get_hgmo_archive(repo, rev, subdir=None, suffix='tar.gz', preferred_region=None):
'\n An archiver for hg.mozilla.org related requests. Uses relengapi.blueprints.archiver.get_archive\n\n ... | -5,873,509,484,656,335,000 | An archiver for hg.mozilla.org related requests. Uses relengapi.blueprints.archiver.get_archive
:param repo: the repo location off of hg.mozilla.org/
:param rev: the rev associated with the repo
:param subdir: optional subdir path to only archive a portion of the repo
:param suffix: the archive extension type. default... | relengapi/blueprints/archiver/__init__.py | get_hgmo_archive | lundjordan/build-relengapi | python | @bp.route('/hgmo/<path:repo>/<rev>')
@api.apimethod(None, unicode, unicode, unicode, unicode, unicode, status_code=302)
def get_hgmo_archive(repo, rev, subdir=None, suffix='tar.gz', preferred_region=None):
'\n An archiver for hg.mozilla.org related requests. Uses relengapi.blueprints.archiver.get_archive\n\n ... |
def get_archive(src_url, key, preferred_region):
'\n A generic getter for retrieving an s3 location of an archive where the archive is based off a\n src_url.\n\n sub-dir: hg.mozilla.org supports archives of sub directories within a repository. This\n flexibility allows for creating archives of only a po... | -6,013,747,439,112,581,000 | A generic getter for retrieving an s3 location of an archive where the archive is based off a
src_url.
sub-dir: hg.mozilla.org supports archives of sub directories within a repository. This
flexibility allows for creating archives of only a portion of what would normally be an entire
repo archive.
logic flow:
If the... | relengapi/blueprints/archiver/__init__.py | get_archive | lundjordan/build-relengapi | python | def get_archive(src_url, key, preferred_region):
'\n A generic getter for retrieving an s3 location of an archive where the archive is based off a\n src_url.\n\n sub-dir: hg.mozilla.org supports archives of sub directories within a repository. This\n flexibility allows for creating archives of only a po... |
def test_exists() -> None:
' Program exists '
assert os.path.isfile(PRG) | -4,827,572,837,640,662,000 | Program exists | 09_grph/tests/grph_test.py | test_exists | BioPeterson/biofx_python | python | def test_exists() -> None:
' '
assert os.path.isfile(PRG) |
def test_usage() -> None:
' Usage '
(rv, out) = getstatusoutput(RUN)
assert (rv > 0)
assert out.lower().startswith('usage:') | 9,113,665,449,928,071,000 | Usage | 09_grph/tests/grph_test.py | test_usage | BioPeterson/biofx_python | python | def test_usage() -> None:
' '
(rv, out) = getstatusoutput(RUN)
assert (rv > 0)
assert out.lower().startswith('usage:') |
def test_bad_k() -> None:
' Dies on bad k '
k = random.choice(range((- 10), 1))
(rv, out) = getstatusoutput(f'{RUN} -k {k} {SAMPLE1}')
assert (rv != 0)
assert out.lower().startswith('usage:')
assert re.search(f'-k "{k}" must be > 0', out) | -1,136,513,366,063,022,600 | Dies on bad k | 09_grph/tests/grph_test.py | test_bad_k | BioPeterson/biofx_python | python | def test_bad_k() -> None:
' '
k = random.choice(range((- 10), 1))
(rv, out) = getstatusoutput(f'{RUN} -k {k} {SAMPLE1}')
assert (rv != 0)
assert out.lower().startswith('usage:')
assert re.search(f'-k "{k}" must be > 0', out) |
def test_bad_file() -> None:
' Dies on bad file '
bad = random_string()
(rv, out) = getstatusoutput('{} {}'.format(RUN, bad))
assert (rv != 0)
assert out.lower().startswith('usage:')
assert re.search(f"No such file or directory: '{bad}'", out) | 3,688,796,799,715,212,300 | Dies on bad file | 09_grph/tests/grph_test.py | test_bad_file | BioPeterson/biofx_python | python | def test_bad_file() -> None:
' '
bad = random_string()
(rv, out) = getstatusoutput('{} {}'.format(RUN, bad))
assert (rv != 0)
assert out.lower().startswith('usage:')
assert re.search(f"No such file or directory: '{bad}'", out) |
def run(in_file: str, k: int) -> None:
' Run with args '
out_file = '.'.join([in_file, str(k), 'out'])
assert os.path.isfile(out_file)
expected = open(out_file).read().rstrip()
cmd = '{} -k {} {} | sort'.format(RUN, k, in_file)
(rv, out) = getstatusoutput(cmd)
assert (rv == 0)
assert (ou... | 2,782,652,345,295,144,400 | Run with args | 09_grph/tests/grph_test.py | run | BioPeterson/biofx_python | python | def run(in_file: str, k: int) -> None:
' '
out_file = '.'.join([in_file, str(k), 'out'])
assert os.path.isfile(out_file)
expected = open(out_file).read().rstrip()
cmd = '{} -k {} {} | sort'.format(RUN, k, in_file)
(rv, out) = getstatusoutput(cmd)
assert (rv == 0)
assert (out.rstrip() ==... |
def test_01():
' Runs OK '
run(SAMPLE1, 3) | 4,297,253,423,442,003,500 | Runs OK | 09_grph/tests/grph_test.py | test_01 | BioPeterson/biofx_python | python | def test_01():
' '
run(SAMPLE1, 3) |
def test_02() -> None:
' Runs OK '
run(SAMPLE1, 4) | 8,518,686,450,370,489,000 | Runs OK | 09_grph/tests/grph_test.py | test_02 | BioPeterson/biofx_python | python | def test_02() -> None:
' '
run(SAMPLE1, 4) |
def test_03() -> None:
' Runs OK '
run(SAMPLE1, 5) | 7,497,294,204,659,460,000 | Runs OK | 09_grph/tests/grph_test.py | test_03 | BioPeterson/biofx_python | python | def test_03() -> None:
' '
run(SAMPLE1, 5) |
def test_04() -> None:
' Runs OK '
run(SAMPLE2, 3) | -278,510,080,884,287,400 | Runs OK | 09_grph/tests/grph_test.py | test_04 | BioPeterson/biofx_python | python | def test_04() -> None:
' '
run(SAMPLE2, 3) |
def test_05() -> None:
' Runs OK '
run(SAMPLE2, 4) | -451,182,995,679,305,300 | Runs OK | 09_grph/tests/grph_test.py | test_05 | BioPeterson/biofx_python | python | def test_05() -> None:
' '
run(SAMPLE2, 4) |
def test_06() -> None:
' Runs OK '
run(SAMPLE2, 5) | -4,800,970,842,889,804,000 | Runs OK | 09_grph/tests/grph_test.py | test_06 | BioPeterson/biofx_python | python | def test_06() -> None:
' '
run(SAMPLE2, 5) |
def test_07() -> None:
' Runs OK '
run(SAMPLE3, 3) | 5,923,181,508,090,840,000 | Runs OK | 09_grph/tests/grph_test.py | test_07 | BioPeterson/biofx_python | python | def test_07() -> None:
' '
run(SAMPLE3, 3) |
def test_08() -> None:
' Runs OK '
run(SAMPLE3, 4) | -9,171,916,681,065,659,000 | Runs OK | 09_grph/tests/grph_test.py | test_08 | BioPeterson/biofx_python | python | def test_08() -> None:
' '
run(SAMPLE3, 4) |
def test_09() -> None:
' Runs OK '
run(SAMPLE3, 5) | -4,117,453,768,972,889,000 | Runs OK | 09_grph/tests/grph_test.py | test_09 | BioPeterson/biofx_python | python | def test_09() -> None:
' '
run(SAMPLE3, 5) |
def random_string() -> str:
'Generate a random string'
return ''.join(random.sample((string.ascii_letters + string.digits), k=random.randint(5, 10))) | -4,268,000,723,444,968,400 | Generate a random string | 09_grph/tests/grph_test.py | random_string | BioPeterson/biofx_python | python | def random_string() -> str:
return .join(random.sample((string.ascii_letters + string.digits), k=random.randint(5, 10))) |
def create_pipeline() -> pipeline_pb2.Pipeline:
'Creates an async pipeline for testing.'
example_gen = _example_gen().with_id('my_example_gen')
transform = _transform(examples=example_gen.outputs['examples'], a_param=10).with_id('my_transform')
trainer = _trainer(examples=example_gen.outputs['examples']... | -8,291,859,342,785,953,000 | Creates an async pipeline for testing. | tfx/orchestration/experimental/core/testing/test_async_pipeline.py | create_pipeline | Avnish327030/tfx | python | def create_pipeline() -> pipeline_pb2.Pipeline:
example_gen = _example_gen().with_id('my_example_gen')
transform = _transform(examples=example_gen.outputs['examples'], a_param=10).with_id('my_transform')
trainer = _trainer(examples=example_gen.outputs['examples'], transform_graph=transform.outputs['tra... |
def is_absolute_uri(url: ParseResult) -> bool:
'\n Returns True if the parsed result is an "absolute URI".\n\n We define an "absolute URI" as containing at mimimum a **scheme** and an\n **host** (a.k.a., an authority).\n\n It must contain SH according to the nomenclature defined in this proposal:\n h... | -397,197,891,575,155,200 | Returns True if the parsed result is an "absolute URI".
We define an "absolute URI" as containing at mimimum a **scheme** and an
**host** (a.k.a., an authority).
It must contain SH according to the nomenclature defined in this proposal:
https://gist.github.com/andrewdotn/eebeaa60d48c3c0f6f9fc75f0ede8d03#proposal
Exa... | src/CreeDictionary/CreeDictionary/templatetags/url_extras.py | is_absolute_uri | Madoshakalaka/morphodict | python | def is_absolute_uri(url: ParseResult) -> bool:
'\n Returns True if the parsed result is an "absolute URI".\n\n We define an "absolute URI" as containing at mimimum a **scheme** and an\n **host** (a.k.a., an authority).\n\n It must contain SH according to the nomenclature defined in this proposal:\n h... |
def to_pf_url(url: ParseResult):
'\n Returns *P*ath and *F*ile as defined here:\n https://gist.github.com/andrewdotn/eebeaa60d48c3c0f6f9fc75f0ede8d03#proposal\n '
return urlunparse(url._replace(scheme='', netloc='')) | 249,949,858,676,596,380 | Returns *P*ath and *F*ile as defined here:
https://gist.github.com/andrewdotn/eebeaa60d48c3c0f6f9fc75f0ede8d03#proposal | src/CreeDictionary/CreeDictionary/templatetags/url_extras.py | to_pf_url | Madoshakalaka/morphodict | python | def to_pf_url(url: ParseResult):
'\n Returns *P*ath and *F*ile as defined here:\n https://gist.github.com/andrewdotn/eebeaa60d48c3c0f6f9fc75f0ede8d03#proposal\n '
return urlunparse(url._replace(scheme=, netloc=)) |
@register.tag
def abstatic(parser, token):
'\n Given a relative path to a static asset, return the absolute path to the\n asset.\n\n Derived from: https://github.com/django/django/blob/635d53a86a36cde7866b9caefeb64d809e6bfcd9/django/templatetags/static.py#L143-L159\n '
return AbstaticNode.handle_tok... | -6,947,781,304,580,890,000 | Given a relative path to a static asset, return the absolute path to the
asset.
Derived from: https://github.com/django/django/blob/635d53a86a36cde7866b9caefeb64d809e6bfcd9/django/templatetags/static.py#L143-L159 | src/CreeDictionary/CreeDictionary/templatetags/url_extras.py | abstatic | Madoshakalaka/morphodict | python | @register.tag
def abstatic(parser, token):
'\n Given a relative path to a static asset, return the absolute path to the\n asset.\n\n Derived from: https://github.com/django/django/blob/635d53a86a36cde7866b9caefeb64d809e6bfcd9/django/templatetags/static.py#L143-L159\n '
return AbstaticNode.handle_tok... |
def _get_path(self, subpath: str) -> str:
'get full subpath'
return f"engagements/v{(self.options.get('version') or ENGAGEMENTS_API_VERSION)}/{subpath}" | -5,392,205,939,925,482,000 | get full subpath | hubspot3/engagements.py | _get_path | benaduggan/hubspot3 | python | def _get_path(self, subpath: str) -> str:
return f"engagements/v{(self.options.get('version') or ENGAGEMENTS_API_VERSION)}/{subpath}" |
def get(self, engagement_id, **options):
'Get a HubSpot engagement.'
return self._call(f'engagements/{engagement_id}', method='GET', **options) | -5,515,921,273,092,089,000 | Get a HubSpot engagement. | hubspot3/engagements.py | get | benaduggan/hubspot3 | python | def get(self, engagement_id, **options):
return self._call(f'engagements/{engagement_id}', method='GET', **options) |
def get_associated(self, object_type, object_id, **options) -> List[Dict]:
'\n get all engagements associated with the given object\n :param object_type: type of object to get associations on [CONTACT, COMPANY, DEAL]\n :param object_id: ID of the object to get associations on\n '
fin... | 892,432,714,481,501,600 | get all engagements associated with the given object
:param object_type: type of object to get associations on [CONTACT, COMPANY, DEAL]
:param object_id: ID of the object to get associations on | hubspot3/engagements.py | get_associated | benaduggan/hubspot3 | python | def get_associated(self, object_type, object_id, **options) -> List[Dict]:
'\n get all engagements associated with the given object\n :param object_type: type of object to get associations on [CONTACT, COMPANY, DEAL]\n :param object_id: ID of the object to get associations on\n '
fin... |
def get_all(self, **options) -> List[Dict]:
'get all engagements'
finished = False
output = []
query_limit = 250
offset = 0
while (not finished):
batch = self._call('engagements/paged', method='GET', params={'limit': query_limit, 'offset': offset}, **options)
output.extend(batch[... | -8,089,323,220,531,312,000 | get all engagements | hubspot3/engagements.py | get_all | benaduggan/hubspot3 | python | def get_all(self, **options) -> List[Dict]:
finished = False
output = []
query_limit = 250
offset = 0
while (not finished):
batch = self._call('engagements/paged', method='GET', params={'limit': query_limit, 'offset': offset}, **options)
output.extend(batch['results'])
f... |
def get_recently_modified(self, since, **options) -> List[Dict]:
'get recently modified engagements'
finished = False
output = []
query_limit = 100
offset = 0
while (not finished):
batch = self._call('engagements/recent/modified', method='GET', params={'limit': query_limit, 'offset': off... | 2,372,618,434,490,447,400 | get recently modified engagements | hubspot3/engagements.py | get_recently_modified | benaduggan/hubspot3 | python | def get_recently_modified(self, since, **options) -> List[Dict]:
finished = False
output = []
query_limit = 100
offset = 0
while (not finished):
batch = self._call('engagements/recent/modified', method='GET', params={'limit': query_limit, 'offset': offset, 'since': since}, **options)
... |
def __init__(self, batch_token=None):
'\n V1ListItemsRequest - a model defined in Swagger\n\n :param dict swaggerTypes: The key is attribute name\n and the value is attribute type.\n :param dict attributeMap: The key is attribute name\n ... | 8,804,516,505,985,339,000 | V1ListItemsRequest - a model defined in Swagger
:param dict swaggerTypes: The key is attribute name
and the value is attribute type.
:param dict attributeMap: The key is attribute name
and the value is json key in definition. | squareconnect/models/v1_list_items_request.py | __init__ | reduceus/connect-python-sdk | python | def __init__(self, batch_token=None):
'\n V1ListItemsRequest - a model defined in Swagger\n\n :param dict swaggerTypes: The key is attribute name\n and the value is attribute type.\n :param dict attributeMap: The key is attribute name\n ... |
@property
def batch_token(self):
'\n Gets the batch_token of this V1ListItemsRequest.\n A pagination cursor to retrieve the next set of results for your original query to the endpoint.\n\n :return: The batch_token of this V1ListItemsRequest.\n :rtype: str\n '
return self._batc... | -8,642,177,761,913,007,000 | Gets the batch_token of this V1ListItemsRequest.
A pagination cursor to retrieve the next set of results for your original query to the endpoint.
:return: The batch_token of this V1ListItemsRequest.
:rtype: str | squareconnect/models/v1_list_items_request.py | batch_token | reduceus/connect-python-sdk | python | @property
def batch_token(self):
'\n Gets the batch_token of this V1ListItemsRequest.\n A pagination cursor to retrieve the next set of results for your original query to the endpoint.\n\n :return: The batch_token of this V1ListItemsRequest.\n :rtype: str\n '
return self._batc... |
@batch_token.setter
def batch_token(self, batch_token):
'\n Sets the batch_token of this V1ListItemsRequest.\n A pagination cursor to retrieve the next set of results for your original query to the endpoint.\n\n :param batch_token: The batch_token of this V1ListItemsRequest.\n :type: str... | -956,991,087,329,217,000 | Sets the batch_token of this V1ListItemsRequest.
A pagination cursor to retrieve the next set of results for your original query to the endpoint.
:param batch_token: The batch_token of this V1ListItemsRequest.
:type: str | squareconnect/models/v1_list_items_request.py | batch_token | reduceus/connect-python-sdk | python | @batch_token.setter
def batch_token(self, batch_token):
'\n Sets the batch_token of this V1ListItemsRequest.\n A pagination cursor to retrieve the next set of results for your original query to the endpoint.\n\n :param batch_token: The batch_token of this V1ListItemsRequest.\n :type: str... |
def to_dict(self):
'\n Returns the model properties as a dict\n '
result = {}
for (attr, _) in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), v... | 2,191,974,537,531,847,000 | Returns the model properties as a dict | squareconnect/models/v1_list_items_request.py | to_dict | reduceus/connect-python-sdk | python | def to_dict(self):
'\n \n '
result = {}
for (attr, _) in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map((lambda x: (x.to_dict() if hasattr(x, 'to_dict') else x)), value))
elif hasattr(value, 'to... |
def to_str(self):
'\n Returns the string representation of the model\n '
return pformat(self.to_dict()) | -3,531,024,894,346,511,000 | Returns the string representation of the model | squareconnect/models/v1_list_items_request.py | to_str | reduceus/connect-python-sdk | python | def to_str(self):
'\n \n '
return pformat(self.to_dict()) |
def __repr__(self):
'\n For `print` and `pprint`\n '
return self.to_str() | 5,853,962,500,611,353,000 | For `print` and `pprint` | squareconnect/models/v1_list_items_request.py | __repr__ | reduceus/connect-python-sdk | python | def __repr__(self):
'\n \n '
return self.to_str() |
def __eq__(self, other):
'\n Returns true if both objects are equal\n '
return (self.__dict__ == other.__dict__) | 3,599,733,221,149,238,300 | Returns true if both objects are equal | squareconnect/models/v1_list_items_request.py | __eq__ | reduceus/connect-python-sdk | python | def __eq__(self, other):
'\n \n '
return (self.__dict__ == other.__dict__) |
def __ne__(self, other):
'\n Returns true if both objects are not equal\n '
return (not (self == other)) | 3,600,423,175,817,510,400 | Returns true if both objects are not equal | squareconnect/models/v1_list_items_request.py | __ne__ | reduceus/connect-python-sdk | python | def __ne__(self, other):
'\n \n '
return (not (self == other)) |
def make_instance(self, include_optional):
'Test Queue\n include_option is a boolean, when False only required\n params are included, when True both required and\n optional params are included '
if include_optional:
return Queue(_class='', items=[openapi_client.models.qu... | -8,577,424,846,062,078,000 | Test Queue
include_option is a boolean, when False only required
params are included, when True both required and
optional params are included | clients/python-legacy/generated/test/test_queue.py | make_instance | cliffano/jenkins-api-clients-generator | python | def make_instance(self, include_optional):
'Test Queue\n include_option is a boolean, when False only required\n params are included, when True both required and\n optional params are included '
if include_optional:
return Queue(_class=, items=[openapi_client.models.queu... |
def testQueue(self):
'Test Queue'
inst_req_only = self.make_instance(include_optional=False)
inst_req_and_optional = self.make_instance(include_optional=True) | -1,662,886,051,552,567,000 | Test Queue | clients/python-legacy/generated/test/test_queue.py | testQueue | cliffano/jenkins-api-clients-generator | python | def testQueue(self):
inst_req_only = self.make_instance(include_optional=False)
inst_req_and_optional = self.make_instance(include_optional=True) |
def index_of_masked_word(sentence, bert):
"Return index of the masked word in `sentence` using `bert`'s' tokenizer.\n\n We use this function to calculate the linear distance between the target\n and controller as BERT sees it.\n\n Parameters\n ----------\n sentence : str\n\n Returns\n -------\n... | -5,210,766,759,479,877,000 | Return index of the masked word in `sentence` using `bert`'s' tokenizer.
We use this function to calculate the linear distance between the target
and controller as BERT sees it.
Parameters
----------
sentence : str
Returns
-------
int | src/experiment.py | index_of_masked_word | geoffbacon/does-bert-agree | python | def index_of_masked_word(sentence, bert):
"Return index of the masked word in `sentence` using `bert`'s' tokenizer.\n\n We use this function to calculate the linear distance between the target\n and controller as BERT sees it.\n\n Parameters\n ----------\n sentence : str\n\n Returns\n -------\n... |
def run(language, force_multilingual=False, fold_case=True, gpu=True):
'Run the experiment for `language`.\n\n Parameters\n ----------\n language : str\n force_multilingual : bool\n Whether to use the multilingual model even on English\n fold_case : bool\n Whether to ignore caseing diff... | -3,874,926,264,927,106,000 | Run the experiment for `language`.
Parameters
----------
language : str
force_multilingual : bool
Whether to use the multilingual model even on English
fold_case : bool
Whether to ignore caseing differences after making predictions
gpu : bool
Whether to run on GPU or not (useful for debugging)
Returns
---... | src/experiment.py | run | geoffbacon/does-bert-agree | python | def run(language, force_multilingual=False, fold_case=True, gpu=True):
'Run the experiment for `language`.\n\n Parameters\n ----------\n language : str\n force_multilingual : bool\n Whether to use the multilingual model even on English\n fold_case : bool\n Whether to ignore caseing diff... |
def plot_confusion_matrix(cm, classes, normalize=False, title='Confusion matrix', cmap=plt.cm.Blues):
'\n This function prints and plots the confusion matrix.\n Normalization can be applied by setting `normalize=True`.\n '
plt.imshow(cm, interpolation='nearest', cmap=cmap)
plt.title(title)
plt.... | -5,036,289,120,716,576,000 | This function prints and plots the confusion matrix.
Normalization can be applied by setting `normalize=True`. | TrainValue/multiclass_svm.py | plot_confusion_matrix | xuanthuong/DOU-SI | python | def plot_confusion_matrix(cm, classes, normalize=False, title='Confusion matrix', cmap=plt.cm.Blues):
'\n This function prints and plots the confusion matrix.\n Normalization can be applied by setting `normalize=True`.\n '
plt.imshow(cm, interpolation='nearest', cmap=cmap)
plt.title(title)
plt.... |
def heading_deg(self):
' Calculate heading in degrees of vector from origin '
heading_rad = math.atan2(self.x, self.y)
heading_deg_normalised = ((math.degrees(heading_rad) + 360) % 360)
return heading_deg_normalised | 4,203,066,159,195,690,500 | Calculate heading in degrees of vector from origin | gym_jsbsim/properties.py | heading_deg | songhyonkim/gym-ai-pilot | python | def heading_deg(self):
' '
heading_rad = math.atan2(self.x, self.y)
heading_deg_normalised = ((math.degrees(heading_rad) + 360) % 360)
return heading_deg_normalised |
def heading_deg_to(self, destination: 'GeodeticPosition') -> float:
' Determines heading in degrees of course between self and destination '
difference_vector = (destination - self)
return difference_vector.heading_deg() | 662,026,814,692,946,400 | Determines heading in degrees of course between self and destination | gym_jsbsim/properties.py | heading_deg_to | songhyonkim/gym-ai-pilot | python | def heading_deg_to(self, destination: 'GeodeticPosition') -> float:
' '
difference_vector = (destination - self)
return difference_vector.heading_deg() |
@staticmethod
def from_sim(sim: 'simulation.Simulation') -> 'GeodeticPosition':
' Return a GeodeticPosition object with lat and lon from simulation '
lat_deg = sim[lat_geod_deg]
lon_deg = sim[lng_geoc_deg]
return GeodeticPosition(lat_deg, lon_deg) | 6,759,532,399,933,314,000 | Return a GeodeticPosition object with lat and lon from simulation | gym_jsbsim/properties.py | from_sim | songhyonkim/gym-ai-pilot | python | @staticmethod
def from_sim(sim: 'simulation.Simulation') -> 'GeodeticPosition':
' '
lat_deg = sim[lat_geod_deg]
lon_deg = sim[lng_geoc_deg]
return GeodeticPosition(lat_deg, lon_deg) |
def __sub__(self, other) -> Vector2:
' Returns difference between two coords as (delta_lat, delta_long) '
return Vector2((self.lon - other.lon), (self.lat - other.lat)) | -3,347,112,684,996,750,300 | Returns difference between two coords as (delta_lat, delta_long) | gym_jsbsim/properties.py | __sub__ | songhyonkim/gym-ai-pilot | python | def __sub__(self, other) -> Vector2:
' '
return Vector2((self.lon - other.lon), (self.lat - other.lat)) |
@pytest.fixture
def mock_publish(hass):
'Initialize components.'
(yield hass.loop.run_until_complete(async_mock_mqtt_component(hass))) | 3,935,108,766,096,235,000 | Initialize components. | tests/components/mqtt/test_switch.py | mock_publish | BobbyBleacher/home-assistant | python | @pytest.fixture
def mock_publish(hass):
(yield hass.loop.run_until_complete(async_mock_mqtt_component(hass))) |
async def test_controlling_state_via_topic(hass, mock_publish):
'Test the controlling state via topic.'
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'payload_on': 1, 'payload_off': 0}... | 8,155,222,178,456,217,000 | Test the controlling state via topic. | tests/components/mqtt/test_switch.py | test_controlling_state_via_topic | BobbyBleacher/home-assistant | python | async def test_controlling_state_via_topic(hass, mock_publish):
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'payload_on': 1, 'payload_off': 0}}))
state = hass.states.get('switch... |
async def test_sending_mqtt_commands_and_optimistic(hass, mock_publish):
'Test the sending MQTT commands in optimistic mode.'
fake_state = ha.State('switch.test', 'on')
with patch('homeassistant.helpers.restore_state.RestoreEntity.async_get_last_state', return_value=mock_coro(fake_state)):
assert (a... | -1,817,929,223,250,078,200 | Test the sending MQTT commands in optimistic mode. | tests/components/mqtt/test_switch.py | test_sending_mqtt_commands_and_optimistic | BobbyBleacher/home-assistant | python | async def test_sending_mqtt_commands_and_optimistic(hass, mock_publish):
fake_state = ha.State('switch.test', 'on')
with patch('homeassistant.helpers.restore_state.RestoreEntity.async_get_last_state', return_value=mock_coro(fake_state)):
assert (await async_setup_component(hass, switch.DOMAIN, {swi... |
async def test_controlling_state_via_topic_and_json_message(hass, mock_publish):
'Test the controlling state via topic and JSON message.'
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', ... | -2,006,936,702,478,254,000 | Test the controlling state via topic and JSON message. | tests/components/mqtt/test_switch.py | test_controlling_state_via_topic_and_json_message | BobbyBleacher/home-assistant | python | async def test_controlling_state_via_topic_and_json_message(hass, mock_publish):
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'payload_on': 'beer on', 'payload_off': 'beer off', 'val... |
async def test_default_availability_payload(hass, mock_publish):
'Test the availability payload.'
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'availability_topic': 'availability_topi... | -3,038,129,219,349,842,400 | Test the availability payload. | tests/components/mqtt/test_switch.py | test_default_availability_payload | BobbyBleacher/home-assistant | python | async def test_default_availability_payload(hass, mock_publish):
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'availability_topic': 'availability_topic', 'payload_on': 1, 'payload_of... |
async def test_custom_availability_payload(hass, mock_publish):
'Test the availability payload.'
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'availability_topic': 'availability_topic... | 2,127,276,169,409,135,600 | Test the availability payload. | tests/components/mqtt/test_switch.py | test_custom_availability_payload | BobbyBleacher/home-assistant | python | async def test_custom_availability_payload(hass, mock_publish):
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'availability_topic': 'availability_topic', 'payload_on': 1, 'payload_off... |
async def test_custom_state_payload(hass, mock_publish):
'Test the state payload.'
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'payload_on': 1, 'payload_off': 0, 'state_on': 'HIGH', ... | -7,688,893,017,872,148,000 | Test the state payload. | tests/components/mqtt/test_switch.py | test_custom_state_payload | BobbyBleacher/home-assistant | python | async def test_custom_state_payload(hass, mock_publish):
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'state_topic': 'state-topic', 'command_topic': 'command-topic', 'payload_on': 1, 'payload_off': 0, 'state_on': 'HIGH', 'state_off': 'LOW'}}))
... |
async def test_setting_attribute_via_mqtt_json_message(hass, mqtt_mock):
'Test the setting of attribute via MQTT with JSON payload.'
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'command_topic': 'test-topic', 'json_attributes_topic': 'attr-topic'}... | 177,271,805,859,749,000 | Test the setting of attribute via MQTT with JSON payload. | tests/components/mqtt/test_switch.py | test_setting_attribute_via_mqtt_json_message | BobbyBleacher/home-assistant | python | async def test_setting_attribute_via_mqtt_json_message(hass, mqtt_mock):
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'command_topic': 'test-topic', 'json_attributes_topic': 'attr-topic'}}))
async_fire_mqtt_message(hass, 'attr-topic', '{ "val... |
async def test_update_with_json_attrs_not_dict(hass, mqtt_mock, caplog):
'Test attributes get extracted from a JSON result.'
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'command_topic': 'test-topic', 'json_attributes_topic': 'attr-topic'}}))
... | -1,280,874,276,873,739,300 | Test attributes get extracted from a JSON result. | tests/components/mqtt/test_switch.py | test_update_with_json_attrs_not_dict | BobbyBleacher/home-assistant | python | async def test_update_with_json_attrs_not_dict(hass, mqtt_mock, caplog):
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'command_topic': 'test-topic', 'json_attributes_topic': 'attr-topic'}}))
async_fire_mqtt_message(hass, 'attr-topic', '[ "lis... |
async def test_update_with_json_attrs_bad_JSON(hass, mqtt_mock, caplog):
'Test attributes get extracted from a JSON result.'
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'command_topic': 'test-topic', 'json_attributes_topic': 'attr-topic'}}))
... | 586,962,458,147,496,800 | Test attributes get extracted from a JSON result. | tests/components/mqtt/test_switch.py | test_update_with_json_attrs_bad_JSON | BobbyBleacher/home-assistant | python | async def test_update_with_json_attrs_bad_JSON(hass, mqtt_mock, caplog):
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: {'platform': 'mqtt', 'name': 'test', 'command_topic': 'test-topic', 'json_attributes_topic': 'attr-topic'}}))
async_fire_mqtt_message(hass, 'attr-topic', 'This i... |
async def test_discovery_update_attr(hass, mqtt_mock, caplog):
'Test update of discovered MQTTAttributes.'
entry = MockConfigEntry(domain=mqtt.DOMAIN)
(await async_start(hass, 'homeassistant', {}, entry))
data1 = '{ "name": "Beer", "command_topic": "test_topic", "json_attributes_topic": "attr-topic1" ... | -5,929,376,502,707,091,000 | Test update of discovered MQTTAttributes. | tests/components/mqtt/test_switch.py | test_discovery_update_attr | BobbyBleacher/home-assistant | python | async def test_discovery_update_attr(hass, mqtt_mock, caplog):
entry = MockConfigEntry(domain=mqtt.DOMAIN)
(await async_start(hass, 'homeassistant', {}, entry))
data1 = '{ "name": "Beer", "command_topic": "test_topic", "json_attributes_topic": "attr-topic1" }'
data2 = '{ "name": "Beer", "command... |
async def test_unique_id(hass):
'Test unique id option only creates one switch per unique_id.'
(await async_mock_mqtt_component(hass))
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: [{'platform': 'mqtt', 'name': 'Test 1', 'state_topic': 'test-topic', 'command_topic': 'command-topic... | 5,170,561,312,111,095,000 | Test unique id option only creates one switch per unique_id. | tests/components/mqtt/test_switch.py | test_unique_id | BobbyBleacher/home-assistant | python | async def test_unique_id(hass):
(await async_mock_mqtt_component(hass))
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: [{'platform': 'mqtt', 'name': 'Test 1', 'state_topic': 'test-topic', 'command_topic': 'command-topic', 'unique_id': 'TOTALLY_UNIQUE'}, {'platform': 'mqtt', 'name'... |
async def test_discovery_removal_switch(hass, mqtt_mock, caplog):
'Test removal of discovered switch.'
entry = MockConfigEntry(domain=mqtt.DOMAIN)
(await async_start(hass, 'homeassistant', {}, entry))
data = '{ "name": "Beer", "state_topic": "test_topic", "command_topic": "test_topic" }'
async_fir... | 1,035,768,021,042,002,600 | Test removal of discovered switch. | tests/components/mqtt/test_switch.py | test_discovery_removal_switch | BobbyBleacher/home-assistant | python | async def test_discovery_removal_switch(hass, mqtt_mock, caplog):
entry = MockConfigEntry(domain=mqtt.DOMAIN)
(await async_start(hass, 'homeassistant', {}, entry))
data = '{ "name": "Beer", "state_topic": "test_topic", "command_topic": "test_topic" }'
async_fire_mqtt_message(hass, 'homeassistant/... |
async def test_discovery_update_switch(hass, mqtt_mock, caplog):
'Test update of discovered switch.'
entry = MockConfigEntry(domain=mqtt.DOMAIN)
(await async_start(hass, 'homeassistant', {}, entry))
data1 = '{ "name": "Beer", "state_topic": "test_topic", "command_topic": "test_topic" }'
data2 = '{... | -1,301,209,773,686,279,000 | Test update of discovered switch. | tests/components/mqtt/test_switch.py | test_discovery_update_switch | BobbyBleacher/home-assistant | python | async def test_discovery_update_switch(hass, mqtt_mock, caplog):
entry = MockConfigEntry(domain=mqtt.DOMAIN)
(await async_start(hass, 'homeassistant', {}, entry))
data1 = '{ "name": "Beer", "state_topic": "test_topic", "command_topic": "test_topic" }'
data2 = '{ "name": "Milk", "state_topic": "t... |
async def test_discovery_broken(hass, mqtt_mock, caplog):
'Test handling of bad discovery message.'
entry = MockConfigEntry(domain=mqtt.DOMAIN)
(await async_start(hass, 'homeassistant', {}, entry))
data1 = '{ "name": "Beer" }'
data2 = '{ "name": "Milk", "state_topic": "test_topic", "command_topic"... | 959,381,512,160,867,500 | Test handling of bad discovery message. | tests/components/mqtt/test_switch.py | test_discovery_broken | BobbyBleacher/home-assistant | python | async def test_discovery_broken(hass, mqtt_mock, caplog):
entry = MockConfigEntry(domain=mqtt.DOMAIN)
(await async_start(hass, 'homeassistant', {}, entry))
data1 = '{ "name": "Beer" }'
data2 = '{ "name": "Milk", "state_topic": "test_topic", "command_topic": "test_topic" }'
async_fire_mqtt_mes... |
async def test_entity_device_info_with_identifier(hass, mqtt_mock):
'Test MQTT switch device registry integration.'
entry = MockConfigEntry(domain=mqtt.DOMAIN)
entry.add_to_hass(hass)
(await async_start(hass, 'homeassistant', {}, entry))
registry = (await hass.helpers.device_registry.async_get_regis... | 9,132,497,107,045,344,000 | Test MQTT switch device registry integration. | tests/components/mqtt/test_switch.py | test_entity_device_info_with_identifier | BobbyBleacher/home-assistant | python | async def test_entity_device_info_with_identifier(hass, mqtt_mock):
entry = MockConfigEntry(domain=mqtt.DOMAIN)
entry.add_to_hass(hass)
(await async_start(hass, 'homeassistant', {}, entry))
registry = (await hass.helpers.device_registry.async_get_registry())
data = json.dumps({'platform': 'mqtt... |
async def test_entity_device_info_update(hass, mqtt_mock):
'Test device registry update.'
entry = MockConfigEntry(domain=mqtt.DOMAIN)
entry.add_to_hass(hass)
(await async_start(hass, 'homeassistant', {}, entry))
registry = (await hass.helpers.device_registry.async_get_registry())
config = {'plat... | 1,981,086,579,315,102,700 | Test device registry update. | tests/components/mqtt/test_switch.py | test_entity_device_info_update | BobbyBleacher/home-assistant | python | async def test_entity_device_info_update(hass, mqtt_mock):
entry = MockConfigEntry(domain=mqtt.DOMAIN)
entry.add_to_hass(hass)
(await async_start(hass, 'homeassistant', {}, entry))
registry = (await hass.helpers.device_registry.async_get_registry())
config = {'platform': 'mqtt', 'name': 'Test 1... |
async def test_entity_id_update(hass, mqtt_mock):
'Test MQTT subscriptions are managed when entity_id is updated.'
registry = mock_registry(hass, {})
mock_mqtt = (await async_mock_mqtt_component(hass))
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: [{'platform': 'mqtt', 'name':... | 2,420,902,222,189,967,000 | Test MQTT subscriptions are managed when entity_id is updated. | tests/components/mqtt/test_switch.py | test_entity_id_update | BobbyBleacher/home-assistant | python | async def test_entity_id_update(hass, mqtt_mock):
registry = mock_registry(hass, {})
mock_mqtt = (await async_mock_mqtt_component(hass))
assert (await async_setup_component(hass, switch.DOMAIN, {switch.DOMAIN: [{'platform': 'mqtt', 'name': 'beer', 'state_topic': 'test-topic', 'command_topic': 'command-... |
def greedy_feedback(distmat, q_pids, g_pids, positive_indices, negative_indices, inplace=True):
'\n Update positive_indices, negative_indices with one round of feedback. Provide feedback for top-ranked gallery.\n Note that distmat is corrupted if inplace=True.\n\n :param distmat: q x g Tensor (adjusted que... | 4,714,801,363,259,745,000 | Update positive_indices, negative_indices with one round of feedback. Provide feedback for top-ranked gallery.
Note that distmat is corrupted if inplace=True.
:param distmat: q x g Tensor (adjusted query to gallery)
:param q_pids: q
:param g_pids: g
:param positive_indices: q x g
:param negative_indices: q x g
:return... | hitl/feedback.py | greedy_feedback | itsnamgyu/reid-metric | python | def greedy_feedback(distmat, q_pids, g_pids, positive_indices, negative_indices, inplace=True):
'\n Update positive_indices, negative_indices with one round of feedback. Provide feedback for top-ranked gallery.\n Note that distmat is corrupted if inplace=True.\n\n :param distmat: q x g Tensor (adjusted que... |
def naive_round(qf, gf, q_pids, g_pids, positive_indices=None, negative_indices=None, inplace=True, previous_distmat=None, device=None):
'\n qf: q x m\n gf: g x m\n q_pids: q\n g_pids: g\n positive_indices: q x g\n negative_indices: q x g\n previous_distmat: adjusted distmat (== compute_distmat... | -8,445,332,685,900,629,000 | qf: q x m
gf: g x m
q_pids: q
g_pids: g
positive_indices: q x g
negative_indices: q x g
previous_distmat: adjusted distmat (== compute_distmat(qf, gf) only at init) | hitl/feedback.py | naive_round | itsnamgyu/reid-metric | python | def naive_round(qf, gf, q_pids, g_pids, positive_indices=None, negative_indices=None, inplace=True, previous_distmat=None, device=None):
'\n qf: q x m\n gf: g x m\n q_pids: q\n g_pids: g\n positive_indices: q x g\n negative_indices: q x g\n previous_distmat: adjusted distmat (== compute_distmat... |
@staticmethod
def _read_image_and_resize(img_entry: Union[(str, 'numpy.array')], img_width: int, img_height: int, should_resize: bool, num_channels: int, resize_method: str, user_specified_num_channels: int):
"\n :param img_entry Union[str, 'numpy.array']: if str file path to the\n image else ... | 3,679,320,613,820,813,300 | :param img_entry Union[str, 'numpy.array']: if str file path to the
image else numpy.array of the image itself
:param img_width: expected width of the image
:param img_height: expected height of the image
:param should_resize: Should the image be resized?
:param resize_method: type of resizing method
:param num... | ludwig/features/image_feature.py | _read_image_and_resize | Yard1/ludwig | python | @staticmethod
def _read_image_and_resize(img_entry: Union[(str, 'numpy.array')], img_width: int, img_height: int, should_resize: bool, num_channels: int, resize_method: str, user_specified_num_channels: int):
"\n :param img_entry Union[str, 'numpy.array']: if str file path to the\n image else ... |
@staticmethod
def _finalize_preprocessing_parameters(preprocessing_parameters: dict, first_img_entry: Union[(str, 'numpy.array')], src_path: str, input_feature_col: np.array):
'\n Helper method to determine the height, width and number of channels for\n preprocessing the image data. This is achieved b... | 6,889,128,509,968,942,000 | Helper method to determine the height, width and number of channels for
preprocessing the image data. This is achieved by looking at the
parameters provided by the user. When there are some missing parameters,
we fall back on to the first image in the dataset. The assumption being
that all the images in the data are ex... | ludwig/features/image_feature.py | _finalize_preprocessing_parameters | Yard1/ludwig | python | @staticmethod
def _finalize_preprocessing_parameters(preprocessing_parameters: dict, first_img_entry: Union[(str, 'numpy.array')], src_path: str, input_feature_col: np.array):
'\n Helper method to determine the height, width and number of channels for\n preprocessing the image data. This is achieved b... |
@lD.log((logBase + '.getAllData'))
def getAllData(logger, query, values=None, dbName=None):
'query data from the database\n \n Query the data over here. If there is a problem with the data, it is going \n to return the value of None, and log the error. Your program needs to check \n whether there was a... | -2,191,366,141,799,859,500 | query data from the database
Query the data over here. If there is a problem with the data, it is going
to return the value of None, and log the error. Your program needs to check
whether there was an error with the query by checking for a None return
value. Note that the location of the dataabses are assumed to b... | src/lib/databaseIO/sqLiteIO.py | getAllData | madelinelimm/newcookiectest | python | @lD.log((logBase + '.getAllData'))
def getAllData(logger, query, values=None, dbName=None):
'query data from the database\n \n Query the data over here. If there is a problem with the data, it is going \n to return the value of None, and log the error. Your program needs to check \n whether there was a... |
@lD.log((logBase + '.getDataIterator'))
def getDataIterator(logger, query, values=None, chunks=100, dbName=None):
'Create an iterator from a largish query\n \n This is a generator that returns values in chunks of chunksize ``chunks``.\n \n Parameters\n ----------\n logger : {logging.logger}\n ... | 4,075,178,327,135,300,000 | Create an iterator from a largish query
This is a generator that returns values in chunks of chunksize ``chunks``.
Parameters
----------
logger : {logging.logger}
logging element
query : {str}
The query to be made to the databse
values : {tuple or list-like}, optional
Additional values to be passed to th... | src/lib/databaseIO/sqLiteIO.py | getDataIterator | madelinelimm/newcookiectest | python | @lD.log((logBase + '.getDataIterator'))
def getDataIterator(logger, query, values=None, chunks=100, dbName=None):
'Create an iterator from a largish query\n \n This is a generator that returns values in chunks of chunksize ``chunks``.\n \n Parameters\n ----------\n logger : {logging.logger}\n ... |
@lD.log((logBase + '.getSingleDataIterator'))
def getSingleDataIterator(logger, query, values=None, dbName=None):
'Create an iterator from a largish query\n \n This is a generator that returns values in chunks of chunksize 1.\n \n Parameters\n ----------\n logger : {logging.logger}\n loggin... | 1,734,528,024,462,529,000 | Create an iterator from a largish query
This is a generator that returns values in chunks of chunksize 1.
Parameters
----------
logger : {logging.logger}
logging element
query : {str}
The query to be made to the databse
values : {tuple or list-like}, optional
Additional values to be passed to the query (... | src/lib/databaseIO/sqLiteIO.py | getSingleDataIterator | madelinelimm/newcookiectest | python | @lD.log((logBase + '.getSingleDataIterator'))
def getSingleDataIterator(logger, query, values=None, dbName=None):
'Create an iterator from a largish query\n \n This is a generator that returns values in chunks of chunksize 1.\n \n Parameters\n ----------\n logger : {logging.logger}\n loggin... |
@lD.log((logBase + '.commitData'))
def commitData(logger, query, values=None, dbName=None):
'query data from the database\n \n Query the data over here. If there is a problem with\n the data, it is going to return the value of ``None``, and\n log the error. Your program needs to check whether \n ther... | 5,148,623,577,417,340,000 | query data from the database
Query the data over here. If there is a problem with
the data, it is going to return the value of ``None``, and
log the error. Your program needs to check whether
there was an error with the query by checking for a ``None``
return value
Parameters
----------
logger : {logging.logger}
... | src/lib/databaseIO/sqLiteIO.py | commitData | madelinelimm/newcookiectest | python | @lD.log((logBase + '.commitData'))
def commitData(logger, query, values=None, dbName=None):
'query data from the database\n \n Query the data over here. If there is a problem with\n the data, it is going to return the value of ``None``, and\n log the error. Your program needs to check whether \n ther... |
@lD.log((logBase + '.commitDataList'))
def commitDataList(logger, query, values, dbName=None):
'query data from the database\n \n Query the data over here. If there is a problem with\n the data, it is going to return the value of None, and\n log the error. Your program needs to check whether \n there... | 4,836,143,481,288,761,000 | query data from the database
Query the data over here. If there is a problem with
the data, it is going to return the value of None, and
log the error. Your program needs to check whether
there was an error with the query by checking for a ``None``
return value
Parameters
----------
logger : {logging.logger}
log... | src/lib/databaseIO/sqLiteIO.py | commitDataList | madelinelimm/newcookiectest | python | @lD.log((logBase + '.commitDataList'))
def commitDataList(logger, query, values, dbName=None):
'query data from the database\n \n Query the data over here. If there is a problem with\n the data, it is going to return the value of None, and\n log the error. Your program needs to check whether \n there... |
def a_vector_OLS_and_LP(m_dict, bounds, boundedness, term_limit, term_lower_bound, fit_method, alpha, diff_error=0.001, diff_step=0.001):
" Main workhorse function of pymetalog package.\n Called during metalog.__init__ method call.\n\n Args:\n m_dict (:obj:`dict` with keys ['params', 'dataValues', ... | 6,141,652,472,069,626,000 | Main workhorse function of pymetalog package.
Called during metalog.__init__ method call.
Args:
m_dict (:obj:`dict` with keys ['params', 'dataValues', 'Y']): Initialized output_dict variable from metalog class.
- m_dict['params']: (:obj:`dict` with keys ['bounds', 'boundedness', 'term_limit', 'term_low... | pymetalog/a_vector.py | a_vector_OLS_and_LP | sives5/pymetalog | python | def a_vector_OLS_and_LP(m_dict, bounds, boundedness, term_limit, term_lower_bound, fit_method, alpha, diff_error=0.001, diff_step=0.001):
" Main workhorse function of pymetalog package.\n Called during metalog.__init__ method call.\n\n Args:\n m_dict (:obj:`dict` with keys ['params', 'dataValues', ... |
def a_vector_LP(m_dict, term_limit, term_lower_bound, diff_error=0.001, diff_step=0.001):
'TODO: write docstring\n\n '
cnames = np.array([])
for i in range(term_lower_bound, (term_limit + 1)):
Y = m_dict['Y'].iloc[:, 0:i]
z = m_dict['dataValues']['z']
Y_neg = (- Y)
new_Y =... | -768,892,783,951,292,000 | TODO: write docstring | pymetalog/a_vector.py | a_vector_LP | sives5/pymetalog | python | def a_vector_LP(m_dict, term_limit, term_lower_bound, diff_error=0.001, diff_step=0.001):
'\n\n '
cnames = np.array([])
for i in range(term_lower_bound, (term_limit + 1)):
Y = m_dict['Y'].iloc[:, 0:i]
z = m_dict['dataValues']['z']
Y_neg = (- Y)
new_Y = pd.DataFrame({'y1': ... |
def a_vector_MLE(a, y, term, m_dict, bounds, boundedness):
'TODO: write docstring\n\n '
ym = [newtons_method_metalog(a, xi, term, bounds, boundedness) for xi in m_dict['dataValues']['x']]
def MLE_quantile_constraints(x):
M = [quantileMetalog(x[:term], yi, term, bounds=bounds, boundedness=bounded... | 7,889,138,763,662,265,000 | TODO: write docstring | pymetalog/a_vector.py | a_vector_MLE | sives5/pymetalog | python | def a_vector_MLE(a, y, term, m_dict, bounds, boundedness):
'\n\n '
ym = [newtons_method_metalog(a, xi, term, bounds, boundedness) for xi in m_dict['dataValues']['x']]
def MLE_quantile_constraints(x):
M = [quantileMetalog(x[:term], yi, term, bounds=bounds, boundedness=boundedness) for yi in x[ter... |
def test_alap_pass(self):
'Test ALAP scheduling.'
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.u2(3.14, 1.57, q[0])
qc.u2(0.5, 0.25, q[1])
qc.barrier(q[1])
qc.u2(0.5, 0.25, q[1])
qc.barrier(q[0], q[1])
qc.cx(q[0], q[1])
qc.measure(q, c)
sch... | -1,342,313,367,346,715,600 | Test ALAP scheduling. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_alap_pass | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_alap_pass(self):
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.u2(3.14, 1.57, q[0])
qc.u2(0.5, 0.25, q[1])
qc.barrier(q[1])
qc.u2(0.5, 0.25, q[1])
qc.barrier(q[0], q[1])
qc.cx(q[0], q[1])
qc.measure(q, c)
sched = schedule(qc, self.... |
def test_alap_with_barriers(self):
'Test that ALAP respects barriers on new qubits.'
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.u2(0, 0, q[0])
qc.barrier(q[0], q[1])
qc.u2(0, 0, q[1])
sched = schedule(qc, self.backend, method='alap')
expected = Sched... | -8,490,361,027,831,596,000 | Test that ALAP respects barriers on new qubits. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_alap_with_barriers | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_alap_with_barriers(self):
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.u2(0, 0, q[0])
qc.barrier(q[0], q[1])
qc.u2(0, 0, q[1])
sched = schedule(qc, self.backend, method='alap')
expected = Schedule(self.cmd_def.get('u2', [0], 0, 0), (28, self.... |
def test_alap_aligns_end(self):
'Test that ALAP always acts as though there is a final global barrier.'
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.u3(0, 0, 0, q[0])
qc.u2(0, 0, q[1])
sched = schedule(qc, self.backend, method='alap')
expected_sched = Sche... | 7,536,511,695,377,579,000 | Test that ALAP always acts as though there is a final global barrier. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_alap_aligns_end | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_alap_aligns_end(self):
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.u3(0, 0, 0, q[0])
qc.u2(0, 0, q[1])
sched = schedule(qc, self.backend, method='alap')
expected_sched = Schedule(self.cmd_def.get('u2', [1], 0, 0), (26, self.cmd_def.get('u3', [0]... |
def test_asap_pass(self):
'Test ASAP scheduling.'
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.u2(3.14, 1.57, q[0])
qc.u2(0.5, 0.25, q[1])
qc.barrier(q[1])
qc.u2(0.5, 0.25, q[1])
qc.barrier(q[0], q[1])
qc.cx(q[0], q[1])
qc.measure(q, c)
sch... | -1,838,080,591,864,963,300 | Test ASAP scheduling. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_asap_pass | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_asap_pass(self):
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.u2(3.14, 1.57, q[0])
qc.u2(0.5, 0.25, q[1])
qc.barrier(q[1])
qc.u2(0.5, 0.25, q[1])
qc.barrier(q[0], q[1])
qc.cx(q[0], q[1])
qc.measure(q, c)
sched = schedule(qc, self.... |
def test_alap_resource_respecting(self):
"Test that the ALAP pass properly respects busy resources when backwards scheduling.\n For instance, a CX on 0 and 1 followed by an X on only 1 must respect both qubits'\n timeline."
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircui... | -4,846,775,682,320,039,000 | Test that the ALAP pass properly respects busy resources when backwards scheduling.
For instance, a CX on 0 and 1 followed by an X on only 1 must respect both qubits'
timeline. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_alap_resource_respecting | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_alap_resource_respecting(self):
"Test that the ALAP pass properly respects busy resources when backwards scheduling.\n For instance, a CX on 0 and 1 followed by an X on only 1 must respect both qubits'\n timeline."
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircui... |
def test_cmd_def_schedules_unaltered(self):
"Test that forward scheduling doesn't change relative timing with a command."
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.cx(q[0], q[1])
sched1 = schedule(qc, self.backend, method='as_soon_as_possible')
sched2 = sch... | 6,633,446,773,433,102,000 | Test that forward scheduling doesn't change relative timing with a command. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_cmd_def_schedules_unaltered | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_cmd_def_schedules_unaltered(self):
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.cx(q[0], q[1])
sched1 = schedule(qc, self.backend, method='as_soon_as_possible')
sched2 = schedule(qc, self.backend, method='as_late_as_possible')
self.assertEqual(sc... |
def test_measure_combined(self):
'\n Test to check for measure on the same qubit which generated another measure schedule.\n\n The measures on different qubits are combined, but measures on the same qubit\n adds another measure to the schedule.\n '
q = QuantumRegister(2)
c = Clas... | -8,182,329,726,274,524,000 | Test to check for measure on the same qubit which generated another measure schedule.
The measures on different qubits are combined, but measures on the same qubit
adds another measure to the schedule. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_measure_combined | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_measure_combined(self):
'\n Test to check for measure on the same qubit which generated another measure schedule.\n\n The measures on different qubits are combined, but measures on the same qubit\n adds another measure to the schedule.\n '
q = QuantumRegister(2)
c = Clas... |
def test_3q_schedule(self):
'Test a schedule that was recommended by David McKay :D '
backend = FakeOpenPulse3Q()
cmd_def = backend.defaults().build_cmd_def()
q = QuantumRegister(3)
c = ClassicalRegister(3)
qc = QuantumCircuit(q, c)
qc.cx(q[0], q[1])
qc.u2(0.778, 0.122, q[2])
qc.u3(3... | -2,168,647,660,574,186,000 | Test a schedule that was recommended by David McKay :D | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_3q_schedule | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_3q_schedule(self):
' '
backend = FakeOpenPulse3Q()
cmd_def = backend.defaults().build_cmd_def()
q = QuantumRegister(3)
c = ClassicalRegister(3)
qc = QuantumCircuit(q, c)
qc.cx(q[0], q[1])
qc.u2(0.778, 0.122, q[2])
qc.u3(3.14, 1.57, 0.0, q[0])
qc.u2(3.14, 1.57, q[1])
... |
def test_schedule_multi(self):
'Test scheduling multiple circuits at once.'
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc0 = QuantumCircuit(q, c)
qc0.cx(q[0], q[1])
qc1 = QuantumCircuit(q, c)
qc1.cx(q[0], q[1])
schedules = schedule([qc0, qc1], self.backend)
expected_insts = sche... | 2,331,117,832,550,685,000 | Test scheduling multiple circuits at once. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_schedule_multi | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_schedule_multi(self):
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc0 = QuantumCircuit(q, c)
qc0.cx(q[0], q[1])
qc1 = QuantumCircuit(q, c)
qc1.cx(q[0], q[1])
schedules = schedule([qc0, qc1], self.backend)
expected_insts = schedule(qc0, self.backend).instructions
sel... |
def test_circuit_name_kept(self):
'Test that the new schedule gets its name from the circuit.'
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c, name='CIRCNAME')
qc.cx(q[0], q[1])
sched = schedule(qc, self.backend, method='asap')
self.assertEqual(sched.name, qc.name)
... | 4,632,417,592,669,203,000 | Test that the new schedule gets its name from the circuit. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_circuit_name_kept | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_circuit_name_kept(self):
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c, name='CIRCNAME')
qc.cx(q[0], q[1])
sched = schedule(qc, self.backend, method='asap')
self.assertEqual(sched.name, qc.name)
sched = schedule(qc, self.backend, method='alap')
se... |
def test_can_add_gates_into_free_space(self):
'The scheduler does some time bookkeeping to know when qubits are free to be\n scheduled. Make sure this works for qubits that are used in the future. This was\n a bug, uncovered by this example:\n\n q0 = - - - - |X|\n q1 = |X| |u2| |X... | -2,730,611,971,349,152,300 | The scheduler does some time bookkeeping to know when qubits are free to be
scheduled. Make sure this works for qubits that are used in the future. This was
a bug, uncovered by this example:
q0 = - - - - |X|
q1 = |X| |u2| |X|
In ALAP scheduling, the next operation on qubit 0 would be added at t=0 rather
than i... | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_can_add_gates_into_free_space | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_can_add_gates_into_free_space(self):
'The scheduler does some time bookkeeping to know when qubits are free to be\n scheduled. Make sure this works for qubits that are used in the future. This was\n a bug, uncovered by this example:\n\n q0 = - - - - |X|\n q1 = |X| |u2| |X... |
def test_barriers_in_middle(self):
'As a follow on to `test_can_add_gates_into_free_space`, similar issues\n arose for barriers, specifically.\n '
qr = QuantumRegister(2)
qc = QuantumCircuit(qr)
for i in range(2):
qc.u2(0, 0, [qr[i]])
qc.barrier(qr[i])
qc.u1(3.14, [... | -3,675,416,939,452,719,600 | As a follow on to `test_can_add_gates_into_free_space`, similar issues
arose for barriers, specifically. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_barriers_in_middle | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_barriers_in_middle(self):
'As a follow on to `test_can_add_gates_into_free_space`, similar issues\n arose for barriers, specifically.\n '
qr = QuantumRegister(2)
qc = QuantumCircuit(qr)
for i in range(2):
qc.u2(0, 0, [qr[i]])
qc.barrier(qr[i])
qc.u1(3.14, [... |
def test_only_needed_measures(self):
'Test that `MeasureChannel`s are only added for measured qubits.'
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.measure(q[1], c[1])
sched_all_channels = schedule(qc, self.backend, method='as_soon_as_possible').channels
delet... | -2,662,223,638,239,911,000 | Test that `MeasureChannel`s are only added for measured qubits. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_only_needed_measures | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_only_needed_measures(self):
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.measure(q[1], c[1])
sched_all_channels = schedule(qc, self.backend, method='as_soon_as_possible').channels
deleted_channels = [MeasureChannel(0)]
self.assertNotIn(sched_all_... |
def test_user_mapping_for_memslots(self):
'\n Test that the new schedule only has required `MeasureChannel`s and that the\n `MemorySlot`s are mapped according to the input circuit.\n '
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.measure(q[0], c[1... | -4,664,338,327,747,616,000 | Test that the new schedule only has required `MeasureChannel`s and that the
`MemorySlot`s are mapped according to the input circuit. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_user_mapping_for_memslots | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_user_mapping_for_memslots(self):
'\n Test that the new schedule only has required `MeasureChannel`s and that the\n `MemorySlot`s are mapped according to the input circuit.\n '
q = QuantumRegister(2)
c = ClassicalRegister(2)
qc = QuantumCircuit(q, c)
qc.measure(q[0], c[1... |
def test_user_mapping_for_memslots_3Q(self):
'Test measuring two of three qubits.'
backend = FakeOpenPulse3Q()
cmd_def = backend.defaults().build_cmd_def()
q = QuantumRegister(3)
c = ClassicalRegister(3)
qc = QuantumCircuit(q, c)
qc.measure(q[1], c[2])
qc.measure(q[2], c[0])
sched = ... | 5,272,640,111,508,526,000 | Test measuring two of three qubits. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_user_mapping_for_memslots_3Q | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_user_mapping_for_memslots_3Q(self):
backend = FakeOpenPulse3Q()
cmd_def = backend.defaults().build_cmd_def()
q = QuantumRegister(3)
c = ClassicalRegister(3)
qc = QuantumCircuit(q, c)
qc.measure(q[1], c[2])
qc.measure(q[2], c[0])
sched = schedule(qc, backend)
expected = ... |
def test_multiple_measure_in_3Q(self):
'Test multiple measure, user memslot mapping, 3Q.'
backend = FakeOpenPulse3Q()
cmd_def = backend.defaults().build_cmd_def()
q = QuantumRegister(3)
c = ClassicalRegister(5)
qc = QuantumCircuit(q, c)
qc.measure(q[0], c[2])
qc.measure(q[0], c[4])
s... | 2,211,987,329,034,881,300 | Test multiple measure, user memslot mapping, 3Q. | artifacts/old_dataset_versions/minimal_commits/qiskit-terra/qiskit-terra#2704/after/test_basic_scheduler.py | test_multiple_measure_in_3Q | MattePalte/Bugs-Quantum-Computing-Platforms | python | def test_multiple_measure_in_3Q(self):
backend = FakeOpenPulse3Q()
cmd_def = backend.defaults().build_cmd_def()
q = QuantumRegister(3)
c = ClassicalRegister(5)
qc = QuantumCircuit(q, c)
qc.measure(q[0], c[2])
qc.measure(q[0], c[4])
sched = schedule(qc, backend)
expected = Schedu... |
def dav_index(context, data):
'List files in a WebDAV directory.'
url = data.get('url')
context.log.info(('Fetching WebDAV path: %s' % url))
result = context.http.request('PROPFIND', url)
for resp in result.xml.findall('./{DAV:}response'):
href = resp.findtext('./{DAV:}href')
if (hre... | 8,402,320,049,363,877,000 | List files in a WebDAV directory. | memorious/operations/webdav.py | dav_index | Rosencrantz/memorious | python | def dav_index(context, data):
url = data.get('url')
context.log.info(('Fetching WebDAV path: %s' % url))
result = context.http.request('PROPFIND', url)
for resp in result.xml.findall('./{DAV:}response'):
href = resp.findtext('./{DAV:}href')
if (href is None):
continue
... |
def default_data_collator(features: List[InputDataClass]) -> Dict[(str, torch.Tensor)]:
"\n Very simple data collator that simply collates batches of dict-like objects and performs special handling for\n potential keys named:\n\n - ``label``: handles a single value (int or float) per object\n - ... | -5,154,268,821,003,138,000 | Very simple data collator that simply collates batches of dict-like objects and performs special handling for
potential keys named:
- ``label``: handles a single value (int or float) per object
- ``label_ids``: handles a list of values per object
Does not do any additional preprocessing: property names of the... | src/transformers/data/data_collator.py | default_data_collator | 21jun/transformers | python | def default_data_collator(features: List[InputDataClass]) -> Dict[(str, torch.Tensor)]:
"\n Very simple data collator that simply collates batches of dict-like objects and performs special handling for\n potential keys named:\n\n - ``label``: handles a single value (int or float) per object\n - ... |
def _collate_batch(examples, tokenizer, pad_to_multiple_of: Optional[int]=None):
'Collate `examples` into a batch, using the information in `tokenizer` for padding if necessary.'
if isinstance(examples[0], (list, tuple)):
examples = [torch.tensor(e, dtype=torch.long) for e in examples]
length_of_fir... | 9,111,441,324,026,435,000 | Collate `examples` into a batch, using the information in `tokenizer` for padding if necessary. | src/transformers/data/data_collator.py | _collate_batch | 21jun/transformers | python | def _collate_batch(examples, tokenizer, pad_to_multiple_of: Optional[int]=None):
if isinstance(examples[0], (list, tuple)):
examples = [torch.tensor(e, dtype=torch.long) for e in examples]
length_of_first = examples[0].size(0)
are_tensors_same_length = all(((x.size(0) == length_of_first) for x ... |
def mask_tokens(self, inputs: torch.Tensor, special_tokens_mask: Optional[torch.Tensor]=None) -> Tuple[(torch.Tensor, torch.Tensor)]:
'\n Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original.\n '
labels = inputs.clone()
probability_matrix = torch... | -6,466,449,275,945,545,000 | Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. | src/transformers/data/data_collator.py | mask_tokens | 21jun/transformers | python | def mask_tokens(self, inputs: torch.Tensor, special_tokens_mask: Optional[torch.Tensor]=None) -> Tuple[(torch.Tensor, torch.Tensor)]:
'\n \n '
labels = inputs.clone()
probability_matrix = torch.full(labels.shape, self.mlm_probability)
if (special_tokens_mask is None):
special_token... |
def _whole_word_mask(self, input_tokens: List[str], max_predictions=512):
'\n Get 0/1 labels for masked tokens with whole word mask proxy\n '
if (not isinstance(self.tokenizer, (BertTokenizer, BertTokenizerFast))):
warnings.warn('DataCollatorForWholeWordMask is only suitable for BertTokeni... | -4,265,430,114,033,264,000 | Get 0/1 labels for masked tokens with whole word mask proxy | src/transformers/data/data_collator.py | _whole_word_mask | 21jun/transformers | python | def _whole_word_mask(self, input_tokens: List[str], max_predictions=512):
'\n \n '
if (not isinstance(self.tokenizer, (BertTokenizer, BertTokenizerFast))):
warnings.warn('DataCollatorForWholeWordMask is only suitable for BertTokenizer-like tokenizers.Please refer to the documentation for m... |
def mask_tokens(self, inputs: torch.Tensor, mask_labels: torch.Tensor) -> Tuple[(torch.Tensor, torch.Tensor)]:
"\n Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. Set\n 'mask_labels' means we use whole word mask (wwm), we directly mask idxs accordi... | -6,416,139,270,136,281,000 | Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. Set
'mask_labels' means we use whole word mask (wwm), we directly mask idxs according to it's ref. | src/transformers/data/data_collator.py | mask_tokens | 21jun/transformers | python | def mask_tokens(self, inputs: torch.Tensor, mask_labels: torch.Tensor) -> Tuple[(torch.Tensor, torch.Tensor)]:
"\n Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. Set\n 'mask_labels' means we use whole word mask (wwm), we directly mask idxs accordi... |
def mask_tokens(self, inputs: torch.Tensor) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor)]:
'\n Prepare masked tokens inputs/labels/attention_mask for masked language modeling: 80% MASK, 10% random, 10%\n original. N-gram not applied yet.\n '
if (self.tokenizer.mask_token is None):
... | 6,151,136,398,149,454,000 | Prepare masked tokens inputs/labels/attention_mask for masked language modeling: 80% MASK, 10% random, 10%
original. N-gram not applied yet. | src/transformers/data/data_collator.py | mask_tokens | 21jun/transformers | python | def mask_tokens(self, inputs: torch.Tensor) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor)]:
'\n Prepare masked tokens inputs/labels/attention_mask for masked language modeling: 80% MASK, 10% random, 10%\n original. N-gram not applied yet.\n '
if (self.tokenizer.mask_token is None):
... |
def mask_tokens(self, inputs: torch.Tensor) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor)]:
'\n The masked tokens to be predicted for a particular sequence are determined by the following algorithm:\n\n 0. Start from the beginning of the sequence by setting ``cur_len = 0`` (num... | -8,821,713,950,774,863,000 | The masked tokens to be predicted for a particular sequence are determined by the following algorithm:
0. Start from the beginning of the sequence by setting ``cur_len = 0`` (number of tokens processed so far).
1. Sample a ``span_length`` from the interval ``[1, max_span_length]`` (length of span of tokens to ... | src/transformers/data/data_collator.py | mask_tokens | 21jun/transformers | python | def mask_tokens(self, inputs: torch.Tensor) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor)]:
'\n The masked tokens to be predicted for a particular sequence are determined by the following algorithm:\n\n 0. Start from the beginning of the sequence by setting ``cur_len = 0`` (num... |
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