nwo stringlengths 5 106 | sha stringlengths 40 40 | path stringlengths 4 174 | language stringclasses 1
value | identifier stringlengths 1 140 | parameters stringlengths 0 87.7k | argument_list stringclasses 1
value | return_statement stringlengths 0 426k | docstring stringlengths 0 64.3k | docstring_summary stringlengths 0 26.3k | docstring_tokens list | function stringlengths 18 4.83M | function_tokens list | url stringlengths 83 304 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PaddlePaddle/PaddleX | 2bab73f81ab54e328204e7871e6ae4a82e719f5d | paddlex/tools/dataset_conversion/x2coco.py | python | LabelMe2COCO.generate_images_field | (self, json_info, image_file, image_id) | return image | [] | def generate_images_field(self, json_info, image_file, image_id):
image = {}
image["height"] = json_info["imageHeight"]
image["width"] = json_info["imageWidth"]
image["id"] = image_id + 1
json_img_path = path_normalization(json_info["imagePath"])
json_info["imagePath"] = osp.join(
osp.split(json_img_path)[0], image_file)
image["file_name"] = osp.split(json_info["imagePath"])[-1]
return image | [
"def",
"generate_images_field",
"(",
"self",
",",
"json_info",
",",
"image_file",
",",
"image_id",
")",
":",
"image",
"=",
"{",
"}",
"image",
"[",
"\"height\"",
"]",
"=",
"json_info",
"[",
"\"imageHeight\"",
"]",
"image",
"[",
"\"width\"",
"]",
"=",
"json_... | https://github.com/PaddlePaddle/PaddleX/blob/2bab73f81ab54e328204e7871e6ae4a82e719f5d/paddlex/tools/dataset_conversion/x2coco.py#L99-L108 | |||
solarwinds/orionsdk-python | 97168451ddbc68db1773717f592a42f78be0eefe | orionsdk/solarwinds.py | python | SolarWinds.get_node_uri | (self, node_name) | Returns the NodeURI for the given NodeName. Uses a SWIS query to the SolarWinds database to retrieve this
information.
Args:
node_name(string): A node name which should equal the caption used in SolarWinds for the node object.
Returns:
node_id (string): The node URI that corresponds to the specified node name. | Returns the NodeURI for the given NodeName. Uses a SWIS query to the SolarWinds database to retrieve this
information. | [
"Returns",
"the",
"NodeURI",
"for",
"the",
"given",
"NodeName",
".",
"Uses",
"a",
"SWIS",
"query",
"to",
"the",
"SolarWinds",
"database",
"to",
"retrieve",
"this",
"information",
"."
] | def get_node_uri(self, node_name):
""" Returns the NodeURI for the given NodeName. Uses a SWIS query to the SolarWinds database to retrieve this
information.
Args:
node_name(string): A node name which should equal the caption used in SolarWinds for the node object.
Returns:
node_id (string): The node URI that corresponds to the specified node name.
"""
node_uri = self.swis.query("SELECT Caption, Uri FROM Orion.Nodes WHERE Caption = @caption",
caption=node_name)
self.logger.info("get_node_uri - node uri query results: %s.", node_uri)
if node_uri['results']:
return node_uri['results'][0]['Uri']
else:
return "" | [
"def",
"get_node_uri",
"(",
"self",
",",
"node_name",
")",
":",
"node_uri",
"=",
"self",
".",
"swis",
".",
"query",
"(",
"\"SELECT Caption, Uri FROM Orion.Nodes WHERE Caption = @caption\"",
",",
"caption",
"=",
"node_name",
")",
"self",
".",
"logger",
".",
"info",... | https://github.com/solarwinds/orionsdk-python/blob/97168451ddbc68db1773717f592a42f78be0eefe/orionsdk/solarwinds.py#L63-L82 | ||
dropbox/changes | 37e23c3141b75e4785cf398d015e3dbca41bdd56 | changes/lib/mesos_lib.py | python | _update_maintenance_schedule | (master, maint_data) | Overwrite maintenance schedule on a Mesos master | Overwrite maintenance schedule on a Mesos master | [
"Overwrite",
"maintenance",
"schedule",
"on",
"a",
"Mesos",
"master"
] | def _update_maintenance_schedule(master, maint_data):
"""
Overwrite maintenance schedule on a Mesos master
"""
_master_api_request(master, SCHEDULE_ENDPOINT, post_data=json.dumps(maint_data)) | [
"def",
"_update_maintenance_schedule",
"(",
"master",
",",
"maint_data",
")",
":",
"_master_api_request",
"(",
"master",
",",
"SCHEDULE_ENDPOINT",
",",
"post_data",
"=",
"json",
".",
"dumps",
"(",
"maint_data",
")",
")"
] | https://github.com/dropbox/changes/blob/37e23c3141b75e4785cf398d015e3dbca41bdd56/changes/lib/mesos_lib.py#L92-L96 | ||
statsmodels/statsmodels | debbe7ea6ba28fe5bdb78f09f8cac694bef98722 | statsmodels/duration/hazard_regression.py | python | PHRegResults.martingale_residuals | (self) | return mart_resid | The martingale residuals. | The martingale residuals. | [
"The",
"martingale",
"residuals",
"."
] | def martingale_residuals(self):
"""
The martingale residuals.
"""
surv = self.model.surv
# Initialize at NaN since rows that belong to strata with no
# events have undefined residuals.
mart_resid = np.nan*np.ones(len(self.model.endog), dtype=np.float64)
cumhaz_f_list = self.baseline_cumulative_hazard_function
# Loop over strata
for stx in range(surv.nstrat):
cumhaz_f = cumhaz_f_list[stx]
exog_s = surv.exog_s[stx]
time_s = surv.time_s[stx]
linpred = np.dot(exog_s, self.params)
if surv.offset_s is not None:
linpred += surv.offset_s[stx]
e_linpred = np.exp(linpred)
ii = surv.stratum_rows[stx]
chaz = cumhaz_f(time_s)
mart_resid[ii] = self.model.status[ii] - e_linpred * chaz
return mart_resid | [
"def",
"martingale_residuals",
"(",
"self",
")",
":",
"surv",
"=",
"self",
".",
"model",
".",
"surv",
"# Initialize at NaN since rows that belong to strata with no",
"# events have undefined residuals.",
"mart_resid",
"=",
"np",
".",
"nan",
"*",
"np",
".",
"ones",
"("... | https://github.com/statsmodels/statsmodels/blob/debbe7ea6ba28fe5bdb78f09f8cac694bef98722/statsmodels/duration/hazard_regression.py#L1541-L1571 | |
python/cpython | e13cdca0f5224ec4e23bdd04bb3120506964bc8b | Lib/string.py | python | capwords | (s, sep=None) | return (sep or ' ').join(map(str.capitalize, s.split(sep))) | capwords(s [,sep]) -> string
Split the argument into words using split, capitalize each
word using capitalize, and join the capitalized words using
join. If the optional second argument sep is absent or None,
runs of whitespace characters are replaced by a single space
and leading and trailing whitespace are removed, otherwise
sep is used to split and join the words. | capwords(s [,sep]) -> string | [
"capwords",
"(",
"s",
"[",
"sep",
"]",
")",
"-",
">",
"string"
] | def capwords(s, sep=None):
"""capwords(s [,sep]) -> string
Split the argument into words using split, capitalize each
word using capitalize, and join the capitalized words using
join. If the optional second argument sep is absent or None,
runs of whitespace characters are replaced by a single space
and leading and trailing whitespace are removed, otherwise
sep is used to split and join the words.
"""
return (sep or ' ').join(map(str.capitalize, s.split(sep))) | [
"def",
"capwords",
"(",
"s",
",",
"sep",
"=",
"None",
")",
":",
"return",
"(",
"sep",
"or",
"' '",
")",
".",
"join",
"(",
"map",
"(",
"str",
".",
"capitalize",
",",
"s",
".",
"split",
"(",
"sep",
")",
")",
")"
] | https://github.com/python/cpython/blob/e13cdca0f5224ec4e23bdd04bb3120506964bc8b/Lib/string.py#L37-L48 | |
OpenMDAO/OpenMDAO | f47eb5485a0bb5ea5d2ae5bd6da4b94dc6b296bd | openmdao/jacobians/jacobian.py | python | Jacobian._randomize_subjac | (self, subjac, key) | return r | Return a subjac that is the given subjac filled with random values.
Parameters
----------
subjac : ndarray or csc_matrix
Sub-jacobian to be randomized.
key : tuple (of, wrt)
Key for subjac within the jacobian.
Returns
-------
ndarray or csc_matrix
Randomized version of the subjac. | Return a subjac that is the given subjac filled with random values. | [
"Return",
"a",
"subjac",
"that",
"is",
"the",
"given",
"subjac",
"filled",
"with",
"random",
"values",
"."
] | def _randomize_subjac(self, subjac, key):
"""
Return a subjac that is the given subjac filled with random values.
Parameters
----------
subjac : ndarray or csc_matrix
Sub-jacobian to be randomized.
key : tuple (of, wrt)
Key for subjac within the jacobian.
Returns
-------
ndarray or csc_matrix
Randomized version of the subjac.
"""
if isinstance(subjac, sparse_types): # sparse
sparse = subjac.copy()
sparse.data = rand(sparse.data.size)
sparse.data += 1.0
return sparse
# if a subsystem has computed a dynamic partial or semi-total coloring,
# we use that sparsity information to set the sparsity of the randomized
# subjac. Otherwise all subjacs that didn't have sparsity declared by the
# user will appear completely dense, which will lead to a total jacobian that
# is more dense than it should be, causing any total coloring that we compute
# to be overly conservative.
subjac_info = self._subjacs_info[key]
if 'sparsity' in subjac_info:
assert subjac_info['rows'] is None
rows, cols, shape = subjac_info['sparsity']
r = np.zeros(shape)
val = rand(len(rows))
val += 1.0
r[rows, cols] = val
else:
r = rand(*subjac.shape)
r += 1.0
return r | [
"def",
"_randomize_subjac",
"(",
"self",
",",
"subjac",
",",
"key",
")",
":",
"if",
"isinstance",
"(",
"subjac",
",",
"sparse_types",
")",
":",
"# sparse",
"sparse",
"=",
"subjac",
".",
"copy",
"(",
")",
"sparse",
".",
"data",
"=",
"rand",
"(",
"sparse... | https://github.com/OpenMDAO/OpenMDAO/blob/f47eb5485a0bb5ea5d2ae5bd6da4b94dc6b296bd/openmdao/jacobians/jacobian.py#L260-L299 | |
JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/views/decorators/cache.py | python | cache_control | (**kwargs) | return _cache_controller | [] | def cache_control(**kwargs):
def _cache_controller(viewfunc):
@wraps(viewfunc, assigned=available_attrs(viewfunc))
def _cache_controlled(request, *args, **kw):
response = viewfunc(request, *args, **kw)
patch_cache_control(response, **kwargs)
return response
return _cache_controlled
return _cache_controller | [
"def",
"cache_control",
"(",
"*",
"*",
"kwargs",
")",
":",
"def",
"_cache_controller",
"(",
"viewfunc",
")",
":",
"@",
"wraps",
"(",
"viewfunc",
",",
"assigned",
"=",
"available_attrs",
"(",
"viewfunc",
")",
")",
"def",
"_cache_controlled",
"(",
"request",
... | https://github.com/JaniceWuo/MovieRecommend/blob/4c86db64ca45598917d304f535413df3bc9fea65/movierecommend/venv1/Lib/site-packages/django/views/decorators/cache.py#L39-L47 | |||
barseghyanartur/django-elasticsearch-dsl-drf | 8fe35265d44501269b2603570773be47f20fa471 | examples/simple/settings/core.py | python | project_dir | (base) | return os.path.abspath(
os.path.join(os.path.dirname(__file__), base).replace('\\', '/')
) | Absolute path to a file from current directory. | Absolute path to a file from current directory. | [
"Absolute",
"path",
"to",
"a",
"file",
"from",
"current",
"directory",
"."
] | def project_dir(base):
"""Absolute path to a file from current directory."""
return os.path.abspath(
os.path.join(os.path.dirname(__file__), base).replace('\\', '/')
) | [
"def",
"project_dir",
"(",
"base",
")",
":",
"return",
"os",
".",
"path",
".",
"abspath",
"(",
"os",
".",
"path",
".",
"join",
"(",
"os",
".",
"path",
".",
"dirname",
"(",
"__file__",
")",
",",
"base",
")",
".",
"replace",
"(",
"'\\\\'",
",",
"'/... | https://github.com/barseghyanartur/django-elasticsearch-dsl-drf/blob/8fe35265d44501269b2603570773be47f20fa471/examples/simple/settings/core.py#L10-L14 | |
tahoe-lafs/tahoe-lafs | 766a53b5208c03c45ca0a98e97eee76870276aa1 | src/allmydata/frontends/sftpd.py | python | _convert_error | (res, request) | If res is not a Failure, return it, otherwise reraise the appropriate
SFTPError. | If res is not a Failure, return it, otherwise reraise the appropriate
SFTPError. | [
"If",
"res",
"is",
"not",
"a",
"Failure",
"return",
"it",
"otherwise",
"reraise",
"the",
"appropriate",
"SFTPError",
"."
] | def _convert_error(res, request):
"""If res is not a Failure, return it, otherwise reraise the appropriate
SFTPError."""
if not isinstance(res, Failure):
logged_res = res
if isinstance(res, (bytes, str)): logged_res = "<data of length %r>" % (len(res),)
logmsg("SUCCESS %r %r" % (request, logged_res,), level=OPERATIONAL)
return res
err = res
logmsg("RAISE %r %r" % (request, err.value), level=OPERATIONAL)
try:
if noisy: logmsg(traceback.format_exc(err.value), level=NOISY)
except Exception: # pragma: no cover
pass
# The message argument to SFTPError must not reveal information that
# might compromise anonymity, if we are running over an anonymous network.
if err.check(SFTPError):
# original raiser of SFTPError has responsibility to ensure anonymity
raise err
if err.check(NoSuchChildError):
childname = _utf8(err.value.args[0])
raise createSFTPError(FX_NO_SUCH_FILE, childname)
if err.check(NotWriteableError) or err.check(ChildOfWrongTypeError):
msg = _utf8(err.value.args[0])
raise createSFTPError(FX_PERMISSION_DENIED, msg)
if err.check(ExistingChildError):
# Versions of SFTP after v3 (which is what twisted.conch implements)
# define a specific error code for this case: FX_FILE_ALREADY_EXISTS.
# However v3 doesn't; instead, other servers such as sshd return
# FX_FAILURE. The gvfs SFTP backend, for example, depends on this
# to translate the error to the equivalent of POSIX EEXIST, which is
# necessary for some picky programs (such as gedit).
msg = _utf8(err.value.args[0])
raise createSFTPError(FX_FAILURE, msg)
if err.check(NotImplementedError):
raise createSFTPError(FX_OP_UNSUPPORTED, _utf8(err.value))
if err.check(EOFError):
raise createSFTPError(FX_EOF, "end of file reached")
if err.check(defer.FirstError):
_convert_error(err.value.subFailure, request)
# We assume that the error message is not anonymity-sensitive.
raise createSFTPError(FX_FAILURE, _utf8(err.value)) | [
"def",
"_convert_error",
"(",
"res",
",",
"request",
")",
":",
"if",
"not",
"isinstance",
"(",
"res",
",",
"Failure",
")",
":",
"logged_res",
"=",
"res",
"if",
"isinstance",
"(",
"res",
",",
"(",
"bytes",
",",
"str",
")",
")",
":",
"logged_res",
"=",... | https://github.com/tahoe-lafs/tahoe-lafs/blob/766a53b5208c03c45ca0a98e97eee76870276aa1/src/allmydata/frontends/sftpd.py#L92-L138 | ||
GoogleCloudPlatform/gsutil | 5be882803e76608e2fd29cf8c504ccd1fe0a7746 | gslib/commands/acl.py | python | AclCommand.ApplyAclChanges | (self, name_expansion_result, thread_state=None) | Applies the changes in self.changes to the provided URL.
Args:
name_expansion_result: NameExpansionResult describing the target object.
thread_state: If present, gsutil Cloud API instance to apply the changes. | Applies the changes in self.changes to the provided URL. | [
"Applies",
"the",
"changes",
"in",
"self",
".",
"changes",
"to",
"the",
"provided",
"URL",
"."
] | def ApplyAclChanges(self, name_expansion_result, thread_state=None):
"""Applies the changes in self.changes to the provided URL.
Args:
name_expansion_result: NameExpansionResult describing the target object.
thread_state: If present, gsutil Cloud API instance to apply the changes.
"""
if thread_state:
gsutil_api = thread_state
else:
gsutil_api = self.gsutil_api
url = name_expansion_result.expanded_storage_url
if url.IsBucket():
bucket = gsutil_api.GetBucket(url.bucket_name,
provider=url.scheme,
fields=['acl', 'metageneration'])
current_acl = bucket.acl
elif url.IsObject():
gcs_object = encoding.JsonToMessage(apitools_messages.Object,
name_expansion_result.expanded_result)
current_acl = gcs_object.acl
if not current_acl:
self._RaiseForAccessDenied(url)
if self._ApplyAclChangesAndReturnChangeCount(url, current_acl) == 0:
self.logger.info('No changes to %s', url)
return
try:
if url.IsBucket():
preconditions = Preconditions(meta_gen_match=bucket.metageneration)
bucket_metadata = apitools_messages.Bucket(acl=current_acl)
gsutil_api.PatchBucket(url.bucket_name,
bucket_metadata,
preconditions=preconditions,
provider=url.scheme,
fields=['id'])
else: # Object
preconditions = Preconditions(gen_match=gcs_object.generation,
meta_gen_match=gcs_object.metageneration)
object_metadata = apitools_messages.Object(acl=current_acl)
try:
gsutil_api.PatchObjectMetadata(url.bucket_name,
url.object_name,
object_metadata,
preconditions=preconditions,
provider=url.scheme,
generation=url.generation,
fields=['id'])
except PreconditionException as e:
# Special retry case where we want to do an additional step, the read
# of the read-modify-write cycle, to fetch the correct object
# metadata before reattempting ACL changes.
self._RefetchObjectMetadataAndApplyAclChanges(url, gsutil_api)
self.logger.info('Updated ACL on %s', url)
except BadRequestException as e:
# Don't retry on bad requests, e.g. invalid email address.
raise CommandException('Received bad request from server: %s' % str(e))
except AccessDeniedException:
self._RaiseForAccessDenied(url)
except PreconditionException as e:
# For objects, retry attempts should have already been handled.
if url.IsObject():
raise CommandException(str(e))
# For buckets, raise PreconditionException and continue to next retry.
raise e | [
"def",
"ApplyAclChanges",
"(",
"self",
",",
"name_expansion_result",
",",
"thread_state",
"=",
"None",
")",
":",
"if",
"thread_state",
":",
"gsutil_api",
"=",
"thread_state",
"else",
":",
"gsutil_api",
"=",
"self",
".",
"gsutil_api",
"url",
"=",
"name_expansion_... | https://github.com/GoogleCloudPlatform/gsutil/blob/5be882803e76608e2fd29cf8c504ccd1fe0a7746/gslib/commands/acl.py#L426-L493 | ||
buke/GreenOdoo | 3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df | runtime/python/lib/python2.7/site-packages/_xmlplus/parsers/xmlproc/xmldtd.py | python | FNDABuilder.new_transition_cur2rem | (self,label) | Adds a new transition from the current state to the last remembered
state. | Adds a new transition from the current state to the last remembered
state. | [
"Adds",
"a",
"new",
"transition",
"from",
"the",
"current",
"state",
"to",
"the",
"last",
"remembered",
"state",
"."
] | def new_transition_cur2rem(self,label):
"""Adds a new transition from the current state to the last remembered
state."""
self.__transitions[self.__current].append((self.__mem[-1],label)) | [
"def",
"new_transition_cur2rem",
"(",
"self",
",",
"label",
")",
":",
"self",
".",
"__transitions",
"[",
"self",
".",
"__current",
"]",
".",
"append",
"(",
"(",
"self",
".",
"__mem",
"[",
"-",
"1",
"]",
",",
"label",
")",
")"
] | https://github.com/buke/GreenOdoo/blob/3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df/runtime/python/lib/python2.7/site-packages/_xmlplus/parsers/xmlproc/xmldtd.py#L571-L574 | ||
out0fmemory/GoAgent-Always-Available | c4254984fea633ce3d1893fe5901debd9f22c2a9 | server/lib/google/appengine/ext/ndb/query.py | python | Query._fetch_page_async | (self, page_size, **q_options) | Internal version of fetch_page_async(). | Internal version of fetch_page_async(). | [
"Internal",
"version",
"of",
"fetch_page_async",
"()",
"."
] | def _fetch_page_async(self, page_size, **q_options):
"""Internal version of fetch_page_async()."""
q_options.setdefault('batch_size', page_size)
q_options.setdefault('produce_cursors', True)
it = self.iter(limit=page_size + 1, **q_options)
results = []
while (yield it.has_next_async()):
results.append(it.next())
if len(results) >= page_size:
break
try:
cursor = it.cursor_after()
except datastore_errors.BadArgumentError:
cursor = None
raise tasklets.Return(results, cursor, it.probably_has_next()) | [
"def",
"_fetch_page_async",
"(",
"self",
",",
"page_size",
",",
"*",
"*",
"q_options",
")",
":",
"q_options",
".",
"setdefault",
"(",
"'batch_size'",
",",
"page_size",
")",
"q_options",
".",
"setdefault",
"(",
"'produce_cursors'",
",",
"True",
")",
"it",
"="... | https://github.com/out0fmemory/GoAgent-Always-Available/blob/c4254984fea633ce3d1893fe5901debd9f22c2a9/server/lib/google/appengine/ext/ndb/query.py#L1359-L1373 | ||
holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/sympy/polys/polyclasses.py | python | DMP.compose | (f, g) | return per(dmp_compose(F, G, lev, dom)) | Computes functional composition of ``f`` and ``g``. | Computes functional composition of ``f`` and ``g``. | [
"Computes",
"functional",
"composition",
"of",
"f",
"and",
"g",
"."
] | def compose(f, g):
"""Computes functional composition of ``f`` and ``g``. """
lev, dom, per, F, G = f.unify(g)
return per(dmp_compose(F, G, lev, dom)) | [
"def",
"compose",
"(",
"f",
",",
"g",
")",
":",
"lev",
",",
"dom",
",",
"per",
",",
"F",
",",
"G",
"=",
"f",
".",
"unify",
"(",
"g",
")",
"return",
"per",
"(",
"dmp_compose",
"(",
"F",
",",
"G",
",",
"lev",
",",
"dom",
")",
")"
] | https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/sympy/polys/polyclasses.py#L723-L726 | |
Ledger-Donjon/lascar | 7a1fc2187a9b642efcdda5d9177f86ec2345d7ba | lascar/engine/engine.py | python | Engine.__init__ | (self, name) | :param name: the name chosen for the Engine | :param name: the name chosen for the Engine | [
":",
"param",
"name",
":",
"the",
"name",
"chosen",
"for",
"the",
"Engine"
] | def __init__(self, name):
"""
:param name: the name chosen for the Engine
"""
if name is None:
name = hex(id(self))[2:]
self.name = name
self.logger = logging.getLogger(__name__)
self.size_in_memory = 0
self.result = {}
self.finalize_step = []
self.is_initialized = False
self.output_parser_mode = "basic" | [
"def",
"__init__",
"(",
"self",
",",
"name",
")",
":",
"if",
"name",
"is",
"None",
":",
"name",
"=",
"hex",
"(",
"id",
"(",
"self",
")",
")",
"[",
"2",
":",
"]",
"self",
".",
"name",
"=",
"name",
"self",
".",
"logger",
"=",
"logging",
".",
"g... | https://github.com/Ledger-Donjon/lascar/blob/7a1fc2187a9b642efcdda5d9177f86ec2345d7ba/lascar/engine/engine.py#L39-L55 | ||
josiah-wolf-oberholtzer/supriya | 5ca725a6b97edfbe016a75666d420ecfdf49592f | dev/etc/pending_ugens/DynKlank.py | python | DynKlank.specifications_array_ref | (self) | return self._inputs[index] | Gets `specifications_array_ref` input of DynKlank.
::
>>> dyn_klank = supriya.ugens.DynKlank.ar(
... decayscale=1,
... freqoffset=0,
... freqscale=1,
... input=input,
... specifications_array_ref=specifications_array_ref,
... )
>>> dyn_klank.specifications_array_ref
Returns ugen input. | Gets `specifications_array_ref` input of DynKlank. | [
"Gets",
"specifications_array_ref",
"input",
"of",
"DynKlank",
"."
] | def specifications_array_ref(self):
"""
Gets `specifications_array_ref` input of DynKlank.
::
>>> dyn_klank = supriya.ugens.DynKlank.ar(
... decayscale=1,
... freqoffset=0,
... freqscale=1,
... input=input,
... specifications_array_ref=specifications_array_ref,
... )
>>> dyn_klank.specifications_array_ref
Returns ugen input.
"""
index = self._ordered_input_names.index('specifications_array_ref')
return self._inputs[index] | [
"def",
"specifications_array_ref",
"(",
"self",
")",
":",
"index",
"=",
"self",
".",
"_ordered_input_names",
".",
"index",
"(",
"'specifications_array_ref'",
")",
"return",
"self",
".",
"_inputs",
"[",
"index",
"]"
] | https://github.com/josiah-wolf-oberholtzer/supriya/blob/5ca725a6b97edfbe016a75666d420ecfdf49592f/dev/etc/pending_ugens/DynKlank.py#L226-L244 | |
google-research/language | 61fa7260ac7d690d11ef72ca863e45a37c0bdc80 | language/templama/sling2facts.py | python | SlingExtractor.as_string | (self, x) | Return a string based on x.id or x.id[x.name]. | Return a string based on x.id or x.id[x.name]. | [
"Return",
"a",
"string",
"based",
"on",
"x",
".",
"id",
"or",
"x",
".",
"id",
"[",
"x",
".",
"name",
"]",
"."
] | def as_string(self, x):
"""Return a string based on x.id or x.id[x.name]."""
x_name = self.get_name(x)
if x is None:
x_str = 'None'
elif isinstance(x, sling.Frame) and 'id' in x:
x_str = x.id
else:
try:
x_str = str(x)
except UnicodeDecodeError:
x_str = 'None'
if FLAGS.show_names:
return ('%s[%s]' % (x_str, x_name)) if x_name else ('%s[]' % x_str)
else:
return x_str | [
"def",
"as_string",
"(",
"self",
",",
"x",
")",
":",
"x_name",
"=",
"self",
".",
"get_name",
"(",
"x",
")",
"if",
"x",
"is",
"None",
":",
"x_str",
"=",
"'None'",
"elif",
"isinstance",
"(",
"x",
",",
"sling",
".",
"Frame",
")",
"and",
"'id'",
"in"... | https://github.com/google-research/language/blob/61fa7260ac7d690d11ef72ca863e45a37c0bdc80/language/templama/sling2facts.py#L370-L385 | ||
mozillazg/pypy | 2ff5cd960c075c991389f842c6d59e71cf0cb7d0 | pypy/module/cpyext/stubs.py | python | _PyImport_FindExtension | (space, name, filename) | For internal use only. | For internal use only. | [
"For",
"internal",
"use",
"only",
"."
] | def _PyImport_FindExtension(space, name, filename):
"""For internal use only."""
raise NotImplementedError | [
"def",
"_PyImport_FindExtension",
"(",
"space",
",",
"name",
",",
"filename",
")",
":",
"raise",
"NotImplementedError"
] | https://github.com/mozillazg/pypy/blob/2ff5cd960c075c991389f842c6d59e71cf0cb7d0/pypy/module/cpyext/stubs.py#L654-L656 | ||
rhinstaller/anaconda | 63edc8680f1b05cbfe11bef28703acba808c5174 | pyanaconda/input_checking.py | python | CheckResult.error_message | (self) | return self._error_message | Optional error message describing why the input is not valid.
:returns: why the input is bad (provided it is bad) or None
:rtype: str or None | Optional error message describing why the input is not valid. | [
"Optional",
"error",
"message",
"describing",
"why",
"the",
"input",
"is",
"not",
"valid",
"."
] | def error_message(self):
"""Optional error message describing why the input is not valid.
:returns: why the input is bad (provided it is bad) or None
:rtype: str or None
"""
return self._error_message | [
"def",
"error_message",
"(",
"self",
")",
":",
"return",
"self",
".",
"_error_message"
] | https://github.com/rhinstaller/anaconda/blob/63edc8680f1b05cbfe11bef28703acba808c5174/pyanaconda/input_checking.py#L218-L224 | |
pypr/pysph | 9cb9a859934939307c65a25cbf73e4ecc83fea4a | pysph/sph/integrator_cython_helper.py | python | IntegratorCythonHelper._check_arrays_for_properties | (self, dest, args) | Given a particle array name and a set of arguments used by an
integrator stepper method, check if the particle array has the
required props. | Given a particle array name and a set of arguments used by an
integrator stepper method, check if the particle array has the
required props. | [
"Given",
"a",
"particle",
"array",
"name",
"and",
"a",
"set",
"of",
"arguments",
"used",
"by",
"an",
"integrator",
"stepper",
"method",
"check",
"if",
"the",
"particle",
"array",
"has",
"the",
"required",
"props",
"."
] | def _check_arrays_for_properties(self, dest, args):
"""Given a particle array name and a set of arguments used by an
integrator stepper method, check if the particle array has the
required props.
"""
pa = self._particle_arrays[dest]
# Remove the 's_' or 'd_'
props = set([x[2:] for x in args])
available_props = set(pa.properties.keys()).union(pa.constants.keys())
if not props.issubset(available_props):
diff = props.difference(available_props)
integrator_name = self.object.steppers[dest].__class__.__name__
names = ', '.join([x for x in sorted(diff)])
msg = "ERROR: {integrator_name} requires the following "\
"properties:\n\t{names}\n"\
"Please add them to the particle array '{dest}'.".format(
integrator_name=integrator_name, names=names, dest=dest
)
self._runtime_error(msg) | [
"def",
"_check_arrays_for_properties",
"(",
"self",
",",
"dest",
",",
"args",
")",
":",
"pa",
"=",
"self",
".",
"_particle_arrays",
"[",
"dest",
"]",
"# Remove the 's_' or 'd_'",
"props",
"=",
"set",
"(",
"[",
"x",
"[",
"2",
":",
"]",
"for",
"x",
"in",
... | https://github.com/pypr/pysph/blob/9cb9a859934939307c65a25cbf73e4ecc83fea4a/pysph/sph/integrator_cython_helper.py#L189-L208 | ||
openstack/octavia | 27e5b27d31c695ba72fb6750de2bdafd76e0d7d9 | octavia/db/repositories.py | python | ListenerRepository.create | (self, session, **model_kwargs) | return model.to_data_model() | Creates a new Listener with some validation. | Creates a new Listener with some validation. | [
"Creates",
"a",
"new",
"Listener",
"with",
"some",
"validation",
"."
] | def create(self, session, **model_kwargs):
"""Creates a new Listener with some validation."""
with session.begin(subtransactions=True):
listener_id = model_kwargs.get('id')
allowed_cidrs = set(model_kwargs.pop('allowed_cidrs', []) or [])
model_kwargs['allowed_cidrs'] = [
models.ListenerCidr(listener_id=listener_id, cidr=cidr)
for cidr in allowed_cidrs]
model = self.model_class(**model_kwargs)
if model.default_pool_id:
model.default_pool = self._pool_check(
session, model.default_pool_id,
lb_id=model.load_balancer_id)
if model.peer_port is None:
model.peer_port = self._find_next_peer_port(
session, lb_id=model.load_balancer_id)
session.add(model)
return model.to_data_model() | [
"def",
"create",
"(",
"self",
",",
"session",
",",
"*",
"*",
"model_kwargs",
")",
":",
"with",
"session",
".",
"begin",
"(",
"subtransactions",
"=",
"True",
")",
":",
"listener_id",
"=",
"model_kwargs",
".",
"get",
"(",
"'id'",
")",
"allowed_cidrs",
"=",... | https://github.com/openstack/octavia/blob/27e5b27d31c695ba72fb6750de2bdafd76e0d7d9/octavia/db/repositories.py#L1188-L1205 | |
saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/modules/rh_ip.py | python | get_network_settings | () | return _read_file(_RH_NETWORK_FILE) | Return the contents of the global network script.
CLI Example:
.. code-block:: bash
salt '*' ip.get_network_settings | Return the contents of the global network script. | [
"Return",
"the",
"contents",
"of",
"the",
"global",
"network",
"script",
"."
] | def get_network_settings():
"""
Return the contents of the global network script.
CLI Example:
.. code-block:: bash
salt '*' ip.get_network_settings
"""
return _read_file(_RH_NETWORK_FILE) | [
"def",
"get_network_settings",
"(",
")",
":",
"return",
"_read_file",
"(",
"_RH_NETWORK_FILE",
")"
] | https://github.com/saltstack/salt/blob/fae5bc757ad0f1716483ce7ae180b451545c2058/salt/modules/rh_ip.py#L1205-L1215 | |
Komodo/KomodoEdit | 61edab75dce2bdb03943b387b0608ea36f548e8e | src/codeintel/play/core.py | python | NotifyEvent.Veto | (*args, **kwargs) | return _core.NotifyEvent_Veto(*args, **kwargs) | Veto() | Veto() | [
"Veto",
"()"
] | def Veto(*args, **kwargs):
"""Veto()"""
return _core.NotifyEvent_Veto(*args, **kwargs) | [
"def",
"Veto",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"_core",
".",
"NotifyEvent_Veto",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] | https://github.com/Komodo/KomodoEdit/blob/61edab75dce2bdb03943b387b0608ea36f548e8e/src/codeintel/play/core.py#L3180-L3182 | |
canonical/cloud-init | dc1aabfca851e520693c05322f724bd102c76364 | cloudinit/sources/helpers/openstack.py | python | ConfigDriveReader.read_v1 | (self) | return results | Reads a version 1 formatted location.
Return a dict with metadata, userdata, dsmode, files and version (1).
If not a valid path, raise a NonReadable exception. | Reads a version 1 formatted location. | [
"Reads",
"a",
"version",
"1",
"formatted",
"location",
"."
] | def read_v1(self):
"""Reads a version 1 formatted location.
Return a dict with metadata, userdata, dsmode, files and version (1).
If not a valid path, raise a NonReadable exception.
"""
found = {}
for name in FILES_V1.keys():
path = self._path_join(self.base_path, name)
if os.path.exists(path):
found[name] = path
if len(found) == 0:
raise NonReadable("%s: no files found" % (self.base_path))
md = {}
for (name, (key, translator, default)) in FILES_V1.items():
if name in found:
path = found[name]
try:
contents = self._path_read(path)
except IOError as e:
raise BrokenMetadata("Failed to read: %s" % path) from e
try:
# Disable not-callable pylint check; pylint isn't able to
# determine that every member of FILES_V1 has a callable in
# the appropriate position
md[key] = translator(contents) # pylint: disable=E1102
except Exception as e:
raise BrokenMetadata(
"Failed to process path %s: %s" % (path, e)
) from e
else:
md[key] = copy.deepcopy(default)
keydata = md["authorized_keys"]
meta_js = md["meta_js"]
# keydata in meta_js is preferred over "injected"
keydata = meta_js.get("public-keys", keydata)
if keydata:
lines = keydata.splitlines()
md["public-keys"] = [
line
for line in lines
if len(line) and not line.startswith("#")
]
# config-drive-v1 has no way for openstack to provide the instance-id
# so we copy that into metadata from the user input
if "instance-id" in meta_js:
md["instance-id"] = meta_js["instance-id"]
results = {
"version": 1,
"metadata": md,
}
# allow the user to specify 'dsmode' in a meta tag
if "dsmode" in meta_js:
results["dsmode"] = meta_js["dsmode"]
# config-drive-v1 has no way of specifying user-data, so the user has
# to cheat and stuff it in a meta tag also.
results["userdata"] = meta_js.get("user-data", "")
# this implementation does not support files other than
# network/interfaces and authorized_keys...
results["files"] = {}
return results | [
"def",
"read_v1",
"(",
"self",
")",
":",
"found",
"=",
"{",
"}",
"for",
"name",
"in",
"FILES_V1",
".",
"keys",
"(",
")",
":",
"path",
"=",
"self",
".",
"_path_join",
"(",
"self",
".",
"base_path",
",",
"name",
")",
"if",
"os",
".",
"path",
".",
... | https://github.com/canonical/cloud-init/blob/dc1aabfca851e520693c05322f724bd102c76364/cloudinit/sources/helpers/openstack.py#L394-L465 | |
hasanirtiza/Pedestron | 3bdcf8476edc0741f28a80dd4cb161ac532507ee | tools/ECPB/eval.py | python | evaluate_detection | (results_path, det_path, gt_path, det_method_name, eval_type='pedestrian') | [] | def evaluate_detection(results_path, det_path, gt_path, det_method_name, eval_type='pedestrian'):
# print ('Start evaluation for {}'.format(det_method_name))
results = []
for difficulty in ['reasonable', 'small', 'occluded', 'all']:
# False is the default case used by the benchmark server,
# use [True, False] if you want to compare the enforce with the ignore setting
for ignore_other_vru in [True,]:
result = evaluate(difficulty, ignore_other_vru, results_path, det_path, gt_path, det_method_name,
use_cache=False, eval_type=eval_type)
results.append(result)
print(['reasonable', 'small', 'occluded', 'all'], results) | [
"def",
"evaluate_detection",
"(",
"results_path",
",",
"det_path",
",",
"gt_path",
",",
"det_method_name",
",",
"eval_type",
"=",
"'pedestrian'",
")",
":",
"# print ('Start evaluation for {}'.format(det_method_name))",
"results",
"=",
"[",
"]",
"for",
"difficulty",
"in"... | https://github.com/hasanirtiza/Pedestron/blob/3bdcf8476edc0741f28a80dd4cb161ac532507ee/tools/ECPB/eval.py#L111-L121 | ||||
kerlomz/captcha_trainer | 72b0cd02c66a9b44073820098155b3278c8bde61 | optimizer/AdaBound.py | python | AdaBoundOptimizer._resource_apply_sparse | (self, grad, var, indices) | return self._apply_sparse_shared(
grad, var, indices, self._resource_scatter_add) | [] | def _resource_apply_sparse(self, grad, var, indices):
return self._apply_sparse_shared(
grad, var, indices, self._resource_scatter_add) | [
"def",
"_resource_apply_sparse",
"(",
"self",
",",
"grad",
",",
"var",
",",
"indices",
")",
":",
"return",
"self",
".",
"_apply_sparse_shared",
"(",
"grad",
",",
"var",
",",
"indices",
",",
"self",
".",
"_resource_scatter_add",
")"
] | https://github.com/kerlomz/captcha_trainer/blob/72b0cd02c66a9b44073820098155b3278c8bde61/optimizer/AdaBound.py#L240-L242 | |||
romanz/amodem | 883ecb433415a7f8398e903acbd1e2bb537bf822 | amodem/levinson.py | python | solver | (t, y) | return x | Solve Mx = y for x, where M[i,j] = t[|i-j|], in O(N^2) steps.
See http://en.wikipedia.org/wiki/Levinson_recursion for details. | Solve Mx = y for x, where M[i,j] = t[|i-j|], in O(N^2) steps.
See http://en.wikipedia.org/wiki/Levinson_recursion for details. | [
"Solve",
"Mx",
"=",
"y",
"for",
"x",
"where",
"M",
"[",
"i",
"j",
"]",
"=",
"t",
"[",
"|i",
"-",
"j|",
"]",
"in",
"O",
"(",
"N^2",
")",
"steps",
".",
"See",
"http",
":",
"//",
"en",
".",
"wikipedia",
".",
"org",
"/",
"wiki",
"/",
"Levinson_... | def solver(t, y):
""" Solve Mx = y for x, where M[i,j] = t[|i-j|], in O(N^2) steps.
See http://en.wikipedia.org/wiki/Levinson_recursion for details.
"""
N = len(t)
assert len(y) == N
t0 = np.array([1.0 / t[0]])
f = [t0] # forward vectors
b = [t0] # backward vectors
for n in range(1, N):
prev_f = f[-1]
prev_b = b[-1]
ef = sum(t[n-i] * prev_f[i] for i in range(n))
eb = sum(t[i+1] * prev_b[i] for i in range(n))
f_ = np.concatenate([prev_f, [0]])
b_ = np.concatenate([[0], prev_b])
det = 1.0 - ef * eb
f.append((f_ - ef * b_) / det)
b.append((b_ - eb * f_) / det)
x = []
for n in range(N):
x = np.concatenate([x, [0]])
ef = sum(t[n-i] * x[i] for i in range(n))
x = x + (y[n] - ef) * b[n]
return x | [
"def",
"solver",
"(",
"t",
",",
"y",
")",
":",
"N",
"=",
"len",
"(",
"t",
")",
"assert",
"len",
"(",
"y",
")",
"==",
"N",
"t0",
"=",
"np",
".",
"array",
"(",
"[",
"1.0",
"/",
"t",
"[",
"0",
"]",
"]",
")",
"f",
"=",
"[",
"t0",
"]",
"# ... | https://github.com/romanz/amodem/blob/883ecb433415a7f8398e903acbd1e2bb537bf822/amodem/levinson.py#L4-L30 | |
mesalock-linux/mesapy | ed546d59a21b36feb93e2309d5c6b75aa0ad95c9 | lib-python/2.7/logging/__init__.py | python | Handler.close | (self) | Tidy up any resources used by the handler.
This version removes the handler from an internal map of handlers,
_handlers, which is used for handler lookup by name. Subclasses
should ensure that this gets called from overridden close()
methods. | Tidy up any resources used by the handler. | [
"Tidy",
"up",
"any",
"resources",
"used",
"by",
"the",
"handler",
"."
] | def close(self):
"""
Tidy up any resources used by the handler.
This version removes the handler from an internal map of handlers,
_handlers, which is used for handler lookup by name. Subclasses
should ensure that this gets called from overridden close()
methods.
"""
#get the module data lock, as we're updating a shared structure.
_acquireLock()
try: #unlikely to raise an exception, but you never know...
if self._name and self._name in _handlers:
del _handlers[self._name]
finally:
_releaseLock() | [
"def",
"close",
"(",
"self",
")",
":",
"#get the module data lock, as we're updating a shared structure.",
"_acquireLock",
"(",
")",
"try",
":",
"#unlikely to raise an exception, but you never know...",
"if",
"self",
".",
"_name",
"and",
"self",
".",
"_name",
"in",
"_hand... | https://github.com/mesalock-linux/mesapy/blob/ed546d59a21b36feb93e2309d5c6b75aa0ad95c9/lib-python/2.7/logging/__init__.py#L792-L807 | ||
spesmilo/electrum | bdbd59300fbd35b01605e66145458e5f396108e8 | electrum/lnpeer.py | python | can_send_shutdown | (self, chan: Channel) | return False | [] | def can_send_shutdown(self, chan: Channel):
if chan.get_state() >= ChannelState.OPENING:
return True
if chan.constraints.is_initiator and chan.channel_id in self.funding_created_sent:
return True
if not chan.constraints.is_initiator and chan.channel_id in self.funding_signed_sent:
return True
return False | [
"def",
"can_send_shutdown",
"(",
"self",
",",
"chan",
":",
"Channel",
")",
":",
"if",
"chan",
".",
"get_state",
"(",
")",
">=",
"ChannelState",
".",
"OPENING",
":",
"return",
"True",
"if",
"chan",
".",
"constraints",
".",
"is_initiator",
"and",
"chan",
"... | https://github.com/spesmilo/electrum/blob/bdbd59300fbd35b01605e66145458e5f396108e8/electrum/lnpeer.py#L1729-L1736 | |||
log2timeline/plaso | fe2e316b8c76a0141760c0f2f181d84acb83abc2 | plaso/engine/worker.py | python | EventExtractionWorker._AnalyzeDataStream | (
self, file_entry, data_stream_name, display_name, event_data_stream) | Analyzes the contents of a specific data stream of a file entry.
The results of the analyzers are set in the event data stream as
attributes that are added to produced event objects. Note that some
file systems allow directories to have data streams, such as NTFS.
Args:
file_entry (dfvfs.FileEntry): file entry whose data stream is to be
analyzed.
data_stream_name (str): name of the data stream.
display_name (str): human readable representation of the file entry
currently being analyzed.
event_data_stream (EventDataStream): event data stream attribute
container.
Raises:
RuntimeError: if the file-like object cannot be retrieved from
the file entry. | Analyzes the contents of a specific data stream of a file entry. | [
"Analyzes",
"the",
"contents",
"of",
"a",
"specific",
"data",
"stream",
"of",
"a",
"file",
"entry",
"."
] | def _AnalyzeDataStream(
self, file_entry, data_stream_name, display_name, event_data_stream):
"""Analyzes the contents of a specific data stream of a file entry.
The results of the analyzers are set in the event data stream as
attributes that are added to produced event objects. Note that some
file systems allow directories to have data streams, such as NTFS.
Args:
file_entry (dfvfs.FileEntry): file entry whose data stream is to be
analyzed.
data_stream_name (str): name of the data stream.
display_name (str): human readable representation of the file entry
currently being analyzed.
event_data_stream (EventDataStream): event data stream attribute
container.
Raises:
RuntimeError: if the file-like object cannot be retrieved from
the file entry.
"""
logger.debug('[AnalyzeDataStream] analyzing file: {0:s}'.format(
display_name))
if self._processing_profiler:
self._processing_profiler.StartTiming('analyzing')
try:
file_object = file_entry.GetFileObject(data_stream_name=data_stream_name)
if not file_object:
raise RuntimeError((
'Unable to retrieve file-like object for file entry: '
'{0:s}.').format(display_name))
self._AnalyzeFileObject(file_object, display_name, event_data_stream)
finally:
if self._processing_profiler:
self._processing_profiler.StopTiming('analyzing')
logger.debug('[AnalyzeDataStream] completed analyzing file: {0:s}'.format(
display_name)) | [
"def",
"_AnalyzeDataStream",
"(",
"self",
",",
"file_entry",
",",
"data_stream_name",
",",
"display_name",
",",
"event_data_stream",
")",
":",
"logger",
".",
"debug",
"(",
"'[AnalyzeDataStream] analyzing file: {0:s}'",
".",
"format",
"(",
"display_name",
")",
")",
"... | https://github.com/log2timeline/plaso/blob/fe2e316b8c76a0141760c0f2f181d84acb83abc2/plaso/engine/worker.py#L129-L170 | ||
wxWidgets/Phoenix | b2199e299a6ca6d866aa6f3d0888499136ead9d6 | wx/lib/agw/aui/framemanager.py | python | AuiCenterDockingGuide.HitTest | (self, x, y) | return -1 | Checks if the mouse position is inside the target windows rect.
:param integer `x`: the `x` mouse position;
:param integer `y`: the `y` mouse position. | Checks if the mouse position is inside the target windows rect. | [
"Checks",
"if",
"the",
"mouse",
"position",
"is",
"inside",
"the",
"target",
"windows",
"rect",
"."
] | def HitTest(self, x, y):
"""
Checks if the mouse position is inside the target windows rect.
:param integer `x`: the `x` mouse position;
:param integer `y`: the `y` mouse position.
"""
if not self._useAero:
if self.targetLeft.GetScreenRect().Contains((x, y)):
return wx.LEFT
if self.targetTop.GetScreenRect().Contains((x, y)):
return wx.UP
if self.targetRight.GetScreenRect().Contains((x, y)):
return wx.RIGHT
if self.targetBottom.GetScreenRect().Contains((x, y)):
return wx.DOWN
if self.targetCenter.IsValid() and self.targetCenter.GetScreenRect().Contains((x, y)):
return wx.CENTER
else:
constants = [wx.LEFT, wx.UP, wx.RIGHT, wx.DOWN, wx.CENTER]
lenRects = len(self._aeroRects)
for indx, rect in enumerate(self._aeroRects):
if rect.Contains((x, y)):
if indx < lenRects or (indx == lenRects - 1 and self._valid):
return constants[indx]
return -1 | [
"def",
"HitTest",
"(",
"self",
",",
"x",
",",
"y",
")",
":",
"if",
"not",
"self",
".",
"_useAero",
":",
"if",
"self",
".",
"targetLeft",
".",
"GetScreenRect",
"(",
")",
".",
"Contains",
"(",
"(",
"x",
",",
"y",
")",
")",
":",
"return",
"wx",
".... | https://github.com/wxWidgets/Phoenix/blob/b2199e299a6ca6d866aa6f3d0888499136ead9d6/wx/lib/agw/aui/framemanager.py#L2411-L2438 | |
pygae/clifford | 0b6cffb9a6d44ecb7a666f6b08b1788fc94a0ab6 | clifford/tools/g3c/__init__.py | python | get_radius_from_sphere | (sphere) | return math.sqrt(abs(dual_sphere * dual_sphere)) | Returns the radius of a sphere | Returns the radius of a sphere | [
"Returns",
"the",
"radius",
"of",
"a",
"sphere"
] | def get_radius_from_sphere(sphere):
"""
Returns the radius of a sphere
"""
dual_sphere = sphere * I5
dual_sphere = dual_sphere / (-dual_sphere | ninf)[()]
return math.sqrt(abs(dual_sphere * dual_sphere)) | [
"def",
"get_radius_from_sphere",
"(",
"sphere",
")",
":",
"dual_sphere",
"=",
"sphere",
"*",
"I5",
"dual_sphere",
"=",
"dual_sphere",
"/",
"(",
"-",
"dual_sphere",
"|",
"ninf",
")",
"[",
"(",
")",
"]",
"return",
"math",
".",
"sqrt",
"(",
"abs",
"(",
"d... | https://github.com/pygae/clifford/blob/0b6cffb9a6d44ecb7a666f6b08b1788fc94a0ab6/clifford/tools/g3c/__init__.py#L992-L998 | |
twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/verify/v2/service/rate_limit/bucket.py | python | BucketContext.update | (self, max=values.unset, interval=values.unset) | return BucketInstance(
self._version,
payload,
service_sid=self._solution['service_sid'],
rate_limit_sid=self._solution['rate_limit_sid'],
sid=self._solution['sid'],
) | Update the BucketInstance
:param unicode max: Max number of requests.
:param unicode interval: Number of seconds that the rate limit will be enforced over.
:returns: The updated BucketInstance
:rtype: twilio.rest.verify.v2.service.rate_limit.bucket.BucketInstance | Update the BucketInstance | [
"Update",
"the",
"BucketInstance"
] | def update(self, max=values.unset, interval=values.unset):
"""
Update the BucketInstance
:param unicode max: Max number of requests.
:param unicode interval: Number of seconds that the rate limit will be enforced over.
:returns: The updated BucketInstance
:rtype: twilio.rest.verify.v2.service.rate_limit.bucket.BucketInstance
"""
data = values.of({'Max': max, 'Interval': interval, })
payload = self._version.update(method='POST', uri=self._uri, data=data, )
return BucketInstance(
self._version,
payload,
service_sid=self._solution['service_sid'],
rate_limit_sid=self._solution['rate_limit_sid'],
sid=self._solution['sid'],
) | [
"def",
"update",
"(",
"self",
",",
"max",
"=",
"values",
".",
"unset",
",",
"interval",
"=",
"values",
".",
"unset",
")",
":",
"data",
"=",
"values",
".",
"of",
"(",
"{",
"'Max'",
":",
"max",
",",
"'Interval'",
":",
"interval",
",",
"}",
")",
"pa... | https://github.com/twilio/twilio-python/blob/6e1e811ea57a1edfadd5161ace87397c563f6915/twilio/rest/verify/v2/service/rate_limit/bucket.py#L241-L261 | |
grow/grow | 97fc21730b6a674d5d33948d94968e79447ce433 | grow/translations/catalog_holder.py | python | Catalogs.init | (self, locales, include_header=None) | [] | def init(self, locales, include_header=None):
_, _, include_header, _ = \
self.get_extract_config(include_header=include_header)
for locale in locales:
catalog = self.get(locale)
catalog.init(template_path=self.template_path,
include_header=include_header) | [
"def",
"init",
"(",
"self",
",",
"locales",
",",
"include_header",
"=",
"None",
")",
":",
"_",
",",
"_",
",",
"include_header",
",",
"_",
"=",
"self",
".",
"get_extract_config",
"(",
"include_header",
"=",
"include_header",
")",
"for",
"locale",
"in",
"l... | https://github.com/grow/grow/blob/97fc21730b6a674d5d33948d94968e79447ce433/grow/translations/catalog_holder.py#L154-L160 | ||||
nortikin/sverchok | 7b460f01317c15f2681bfa3e337c5e7346f3711b | data_structure.py | python | socket_id | (socket) | return socket.socket_id | return an usable and semi stable hash | return an usable and semi stable hash | [
"return",
"an",
"usable",
"and",
"semi",
"stable",
"hash"
] | def socket_id(socket):
"""return an usable and semi stable hash"""
return socket.socket_id | [
"def",
"socket_id",
"(",
"socket",
")",
":",
"return",
"socket",
".",
"socket_id"
] | https://github.com/nortikin/sverchok/blob/7b460f01317c15f2681bfa3e337c5e7346f3711b/data_structure.py#L1446-L1448 | |
mjwestcott/Goodrich | dc2516591bd28488516c0337a62e64248debe47c | ch10/sorted_table_map.py | python | SortedTableMap._find_index | (self, k, low, high) | Return index of the leftmost item with key greater than or equal to k.
Return high + 1 if no such item qualifies.
That is, j will be returned such that:
all items of slice table[low:j] have key < k
all items of slice table[j:high+1] have key >= k | Return index of the leftmost item with key greater than or equal to k. | [
"Return",
"index",
"of",
"the",
"leftmost",
"item",
"with",
"key",
"greater",
"than",
"or",
"equal",
"to",
"k",
"."
] | def _find_index(self, k, low, high):
"""Return index of the leftmost item with key greater than or equal to k.
Return high + 1 if no such item qualifies.
That is, j will be returned such that:
all items of slice table[low:j] have key < k
all items of slice table[j:high+1] have key >= k
"""
if high < low:
return high + 1 # no element qualifies
else:
mid = (low + high) // 2
if k == self._table[mid]._key:
return mid # found exact match
elif k < self._table[mid]._key:
return self._find_index(k, low, mid - 1) # Note: may return mid
else:
return self._find_index(k, mid + 1, high) | [
"def",
"_find_index",
"(",
"self",
",",
"k",
",",
"low",
",",
"high",
")",
":",
"if",
"high",
"<",
"low",
":",
"return",
"high",
"+",
"1",
"# no element qualifies",
"else",
":",
"mid",
"=",
"(",
"low",
"+",
"high",
")",
"//",
"2",
"if",
"k",
"=="... | https://github.com/mjwestcott/Goodrich/blob/dc2516591bd28488516c0337a62e64248debe47c/ch10/sorted_table_map.py#L28-L46 | ||
MTG/freesound | 72f234a656ce31f5f625f0bba5376dd4160b478d | sounds/models.py | python | BulkUploadProgress.has_global_validation_errors | (self) | return False | Returns True if the validation finished with global errors | Returns True if the validation finished with global errors | [
"Returns",
"True",
"if",
"the",
"validation",
"finished",
"with",
"global",
"errors"
] | def has_global_validation_errors(self):
"""
Returns True if the validation finished with global errors
"""
if self.validation_output is not None:
return len(self.validation_output['global_errors']) > 0
return False | [
"def",
"has_global_validation_errors",
"(",
"self",
")",
":",
"if",
"self",
".",
"validation_output",
"is",
"not",
"None",
":",
"return",
"len",
"(",
"self",
".",
"validation_output",
"[",
"'global_errors'",
"]",
")",
">",
"0",
"return",
"False"
] | https://github.com/MTG/freesound/blob/72f234a656ce31f5f625f0bba5376dd4160b478d/sounds/models.py#L262-L268 | |
fandoghpaas/fandogh-cli | 8bb3e4e49ebcfea3a3defb1db1b1831e27ba8af7 | fandogh_cli/service_commands.py | python | service_destroy | (service_name, archived) | Destroy service | Destroy service | [
"Destroy",
"service"
] | def service_destroy(service_name, archived):
"""Destroy service"""
click.echo(
'you are about to destroy service with name {}.'.format(service_name))
click.echo('It might take a while!')
message = present(lambda: destroy_service(service_name, archived))
click.echo(message) | [
"def",
"service_destroy",
"(",
"service_name",
",",
"archived",
")",
":",
"click",
".",
"echo",
"(",
"'you are about to destroy service with name {}.'",
".",
"format",
"(",
"service_name",
")",
")",
"click",
".",
"echo",
"(",
"'It might take a while!'",
")",
"messag... | https://github.com/fandoghpaas/fandogh-cli/blob/8bb3e4e49ebcfea3a3defb1db1b1831e27ba8af7/fandogh_cli/service_commands.py#L135-L141 | ||
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/modular/hecke/module.py | python | HeckeModule_free_module.system_of_eigenvalues | (self, n, name='alpha') | return [self.eigenvalue(m, name=name) for m in range(1, n + 1)] | r"""
Assuming that ``self`` is a simple space of modular symbols, return the
eigenvalues `[a_1, \ldots, a_nmax]` of the Hecke
operators on self. See ``self.eigenvalue(n)`` for more
details.
INPUT:
- ``n`` - number of eigenvalues
- ``alpha`` - name of generate for eigenvalue field
EXAMPLES:
The outputs of the following tests are very unstable. The algorithms
are randomized and depend on cached results. A slight change in the
sequence of pseudo-random numbers or a modification in caching is
likely to modify the results. We reset the random number generator and
clear some caches for reproducibility::
sage: set_random_seed(0)
sage: ModularSymbols_clear_cache()
We compute eigenvalues for newforms of level 62::
sage: M = ModularSymbols(62,2,sign=-1)
sage: S = M.cuspidal_submodule().new_submodule()
sage: [[o.minpoly() for o in A.system_of_eigenvalues(3)] for A in S.decomposition()]
[[x - 1, x - 1, x], [x - 1, x + 1, x^2 - 2*x - 2]]
Next we define a function that does the above::
sage: def b(N,k=2):
....: t=cputime()
....: S = ModularSymbols(N,k,sign=-1).cuspidal_submodule().new_submodule()
....: for A in S.decomposition():
....: print("{} {}".format(N, A.system_of_eigenvalues(5)))
::
sage: b(63)
63 [1, 1, 0, -1, 2]
63 [1, alpha, 0, 1, -2*alpha]
This example illustrates finding field over which the eigenvalues
are defined::
sage: M = ModularSymbols(23,2,sign=1).cuspidal_submodule().new_submodule()
sage: v = M.system_of_eigenvalues(10); v
[1, alpha, -2*alpha - 1, -alpha - 1, 2*alpha, alpha - 2, 2*alpha + 2, -2*alpha - 1, 2, -2*alpha + 2]
sage: v[0].parent()
Number Field in alpha with defining polynomial x^2 + x - 1
This example illustrates setting the print name of the eigenvalue
field.
::
sage: A = ModularSymbols(125,sign=1).new_subspace()[0]
sage: A.system_of_eigenvalues(10)
[1, alpha, -alpha - 2, -alpha - 1, 0, -alpha - 1, -3, -2*alpha - 1, 3*alpha + 2, 0]
sage: A.system_of_eigenvalues(10,'x')
[1, x, -x - 2, -x - 1, 0, -x - 1, -3, -2*x - 1, 3*x + 2, 0] | r"""
Assuming that ``self`` is a simple space of modular symbols, return the
eigenvalues `[a_1, \ldots, a_nmax]` of the Hecke
operators on self. See ``self.eigenvalue(n)`` for more
details. | [
"r",
"Assuming",
"that",
"self",
"is",
"a",
"simple",
"space",
"of",
"modular",
"symbols",
"return",
"the",
"eigenvalues",
"[",
"a_1",
"\\",
"ldots",
"a_nmax",
"]",
"of",
"the",
"Hecke",
"operators",
"on",
"self",
".",
"See",
"self",
".",
"eigenvalue",
"... | def system_of_eigenvalues(self, n, name='alpha'):
r"""
Assuming that ``self`` is a simple space of modular symbols, return the
eigenvalues `[a_1, \ldots, a_nmax]` of the Hecke
operators on self. See ``self.eigenvalue(n)`` for more
details.
INPUT:
- ``n`` - number of eigenvalues
- ``alpha`` - name of generate for eigenvalue field
EXAMPLES:
The outputs of the following tests are very unstable. The algorithms
are randomized and depend on cached results. A slight change in the
sequence of pseudo-random numbers or a modification in caching is
likely to modify the results. We reset the random number generator and
clear some caches for reproducibility::
sage: set_random_seed(0)
sage: ModularSymbols_clear_cache()
We compute eigenvalues for newforms of level 62::
sage: M = ModularSymbols(62,2,sign=-1)
sage: S = M.cuspidal_submodule().new_submodule()
sage: [[o.minpoly() for o in A.system_of_eigenvalues(3)] for A in S.decomposition()]
[[x - 1, x - 1, x], [x - 1, x + 1, x^2 - 2*x - 2]]
Next we define a function that does the above::
sage: def b(N,k=2):
....: t=cputime()
....: S = ModularSymbols(N,k,sign=-1).cuspidal_submodule().new_submodule()
....: for A in S.decomposition():
....: print("{} {}".format(N, A.system_of_eigenvalues(5)))
::
sage: b(63)
63 [1, 1, 0, -1, 2]
63 [1, alpha, 0, 1, -2*alpha]
This example illustrates finding field over which the eigenvalues
are defined::
sage: M = ModularSymbols(23,2,sign=1).cuspidal_submodule().new_submodule()
sage: v = M.system_of_eigenvalues(10); v
[1, alpha, -2*alpha - 1, -alpha - 1, 2*alpha, alpha - 2, 2*alpha + 2, -2*alpha - 1, 2, -2*alpha + 2]
sage: v[0].parent()
Number Field in alpha with defining polynomial x^2 + x - 1
This example illustrates setting the print name of the eigenvalue
field.
::
sage: A = ModularSymbols(125,sign=1).new_subspace()[0]
sage: A.system_of_eigenvalues(10)
[1, alpha, -alpha - 2, -alpha - 1, 0, -alpha - 1, -3, -2*alpha - 1, 3*alpha + 2, 0]
sage: A.system_of_eigenvalues(10,'x')
[1, x, -x - 2, -x - 1, 0, -x - 1, -3, -2*x - 1, 3*x + 2, 0]
"""
return [self.eigenvalue(m, name=name) for m in range(1, n + 1)] | [
"def",
"system_of_eigenvalues",
"(",
"self",
",",
"n",
",",
"name",
"=",
"'alpha'",
")",
":",
"return",
"[",
"self",
".",
"eigenvalue",
"(",
"m",
",",
"name",
"=",
"name",
")",
"for",
"m",
"in",
"range",
"(",
"1",
",",
"n",
"+",
"1",
")",
"]"
] | https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/modular/hecke/module.py#L1664-L1729 | |
edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/requests/packages/urllib3/connectionpool.py | python | HTTPSConnectionPool._prepare_conn | (self, conn) | return conn | Prepare the ``connection`` for :meth:`urllib3.util.ssl_wrap_socket`
and establish the tunnel if proxy is used. | Prepare the ``connection`` for :meth:`urllib3.util.ssl_wrap_socket`
and establish the tunnel if proxy is used. | [
"Prepare",
"the",
"connection",
"for",
":",
"meth",
":",
"urllib3",
".",
"util",
".",
"ssl_wrap_socket",
"and",
"establish",
"the",
"tunnel",
"if",
"proxy",
"is",
"used",
"."
] | def _prepare_conn(self, conn):
"""
Prepare the ``connection`` for :meth:`urllib3.util.ssl_wrap_socket`
and establish the tunnel if proxy is used.
"""
if isinstance(conn, VerifiedHTTPSConnection):
conn.set_cert(key_file=self.key_file,
cert_file=self.cert_file,
cert_reqs=self.cert_reqs,
ca_certs=self.ca_certs,
ca_cert_dir=self.ca_cert_dir,
assert_hostname=self.assert_hostname,
assert_fingerprint=self.assert_fingerprint)
conn.ssl_version = self.ssl_version
return conn | [
"def",
"_prepare_conn",
"(",
"self",
",",
"conn",
")",
":",
"if",
"isinstance",
"(",
"conn",
",",
"VerifiedHTTPSConnection",
")",
":",
"conn",
".",
"set_cert",
"(",
"key_file",
"=",
"self",
".",
"key_file",
",",
"cert_file",
"=",
"self",
".",
"cert_file",
... | https://github.com/edisonlz/fastor/blob/342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3/base/site-packages/requests/packages/urllib3/connectionpool.py#L716-L732 | |
chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/pip/vcs/__init__.py | python | VersionControl.get_src_requirement | (self, dist, location) | Return a string representing the requirement needed to
redownload the files currently present in location, something
like:
{repository_url}@{revision}#egg={project_name}-{version_identifier} | Return a string representing the requirement needed to
redownload the files currently present in location, something
like:
{repository_url} | [
"Return",
"a",
"string",
"representing",
"the",
"requirement",
"needed",
"to",
"redownload",
"the",
"files",
"currently",
"present",
"in",
"location",
"something",
"like",
":",
"{",
"repository_url",
"}"
] | def get_src_requirement(self, dist, location):
"""
Return a string representing the requirement needed to
redownload the files currently present in location, something
like:
{repository_url}@{revision}#egg={project_name}-{version_identifier}
"""
raise NotImplementedError | [
"def",
"get_src_requirement",
"(",
"self",
",",
"dist",
",",
"location",
")",
":",
"raise",
"NotImplementedError"
] | https://github.com/chribsen/simple-machine-learning-examples/blob/dc94e52a4cebdc8bb959ff88b81ff8cfeca25022/venv/lib/python2.7/site-packages/pip/vcs/__init__.py#L288-L295 | ||
PaddlePaddle/PaddleX | 2bab73f81ab54e328204e7871e6ae4a82e719f5d | paddlex/ppdet/data/transform/keypoint_operators.py | python | register_keypointop | (cls) | return serializable(cls) | [] | def register_keypointop(cls):
return serializable(cls) | [
"def",
"register_keypointop",
"(",
"cls",
")",
":",
"return",
"serializable",
"(",
"cls",
")"
] | https://github.com/PaddlePaddle/PaddleX/blob/2bab73f81ab54e328204e7871e6ae4a82e719f5d/paddlex/ppdet/data/transform/keypoint_operators.py#L55-L56 | |||
csu/quora-api | 59c8bac0016a29cca1236c39410298a036341e02 | server.py | python | user_upvotes_route | (user) | return jsonify({'items': Quora.get_activity(user).upvotes}) | [] | def user_upvotes_route(user):
return jsonify({'items': Quora.get_activity(user).upvotes}) | [
"def",
"user_upvotes_route",
"(",
"user",
")",
":",
"return",
"jsonify",
"(",
"{",
"'items'",
":",
"Quora",
".",
"get_activity",
"(",
"user",
")",
".",
"upvotes",
"}",
")"
] | https://github.com/csu/quora-api/blob/59c8bac0016a29cca1236c39410298a036341e02/server.py#L85-L86 | |||
holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/sympy/polys/densearith.py | python | dmp_rr_div | (f, g, u, K) | return q, r | Multivariate division with remainder over a ring.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_rr_div(x**2 + x*y, 2*x + 2)
(0, x**2 + x*y) | Multivariate division with remainder over a ring. | [
"Multivariate",
"division",
"with",
"remainder",
"over",
"a",
"ring",
"."
] | def dmp_rr_div(f, g, u, K):
"""
Multivariate division with remainder over a ring.
Examples
========
>>> from sympy.polys import ring, ZZ
>>> R, x,y = ring("x,y", ZZ)
>>> R.dmp_rr_div(x**2 + x*y, 2*x + 2)
(0, x**2 + x*y)
"""
if not u:
return dup_rr_div(f, g, K)
df = dmp_degree(f, u)
dg = dmp_degree(g, u)
if dg < 0:
raise ZeroDivisionError("polynomial division")
q, r, dr = dmp_zero(u), f, df
if df < dg:
return q, r
lc_g, v = dmp_LC(g, K), u - 1
while True:
lc_r = dmp_LC(r, K)
c, R = dmp_rr_div(lc_r, lc_g, v, K)
if not dmp_zero_p(R, v):
break
j = dr - dg
q = dmp_add_term(q, c, j, u, K)
h = dmp_mul_term(g, c, j, u, K)
r = dmp_sub(r, h, u, K)
_dr, dr = dr, dmp_degree(r, u)
if dr < dg:
break
elif not (dr < _dr):
raise PolynomialDivisionFailed(f, g, K)
return q, r | [
"def",
"dmp_rr_div",
"(",
"f",
",",
"g",
",",
"u",
",",
"K",
")",
":",
"if",
"not",
"u",
":",
"return",
"dup_rr_div",
"(",
"f",
",",
"g",
",",
"K",
")",
"df",
"=",
"dmp_degree",
"(",
"f",
",",
"u",
")",
"dg",
"=",
"dmp_degree",
"(",
"g",
",... | https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/sympy/polys/densearith.py#L1359-L1409 | |
tensorflow/datasets | 2e496976d7d45550508395fb2f35cf958c8a3414 | tensorflow_datasets/audio/savee.py | python | Savee._generate_examples | (self, file_names) | Yields examples. | Yields examples. | [
"Yields",
"examples",
"."
] | def _generate_examples(self, file_names):
"""Yields examples."""
for fname in file_names:
folder, wavname = os.path.split(fname)
_, speaker_id = os.path.split(folder)
label_abbrev = re.match('^([a-zA-Z]+)', wavname).group(1) # pytype: disable=attribute-error
label = LABEL_MAP[label_abbrev]
key = '{}_{}'.format(speaker_id, wavname.split('.')[0])
yield key, {'audio': fname, 'label': label, 'speaker_id': speaker_id} | [
"def",
"_generate_examples",
"(",
"self",
",",
"file_names",
")",
":",
"for",
"fname",
"in",
"file_names",
":",
"folder",
",",
"wavname",
"=",
"os",
".",
"path",
".",
"split",
"(",
"fname",
")",
"_",
",",
"speaker_id",
"=",
"os",
".",
"path",
".",
"s... | https://github.com/tensorflow/datasets/blob/2e496976d7d45550508395fb2f35cf958c8a3414/tensorflow_datasets/audio/savee.py#L189-L197 | ||
gevent/gevent | ae2cb5aeb2aea8987efcb90a4c50ca4e1ee12c31 | src/gevent/_waiter.py | python | Waiter.throw | (self, *throw_args) | Switch to the greenlet with the exception. If there's no greenlet, store the exception. | Switch to the greenlet with the exception. If there's no greenlet, store the exception. | [
"Switch",
"to",
"the",
"greenlet",
"with",
"the",
"exception",
".",
"If",
"there",
"s",
"no",
"greenlet",
"store",
"the",
"exception",
"."
] | def throw(self, *throw_args):
"""Switch to the greenlet with the exception. If there's no greenlet, store the exception."""
greenlet = self.greenlet
if greenlet is None:
self._exception = throw_args
else:
if getcurrent() is not self.hub: # pylint:disable=undefined-variable
raise AssertionError("Can only use Waiter.switch method from the Hub greenlet")
throw = greenlet.throw
try:
throw(*throw_args)
except: # pylint:disable=bare-except
self.hub.handle_error(throw, *sys.exc_info()) | [
"def",
"throw",
"(",
"self",
",",
"*",
"throw_args",
")",
":",
"greenlet",
"=",
"self",
".",
"greenlet",
"if",
"greenlet",
"is",
"None",
":",
"self",
".",
"_exception",
"=",
"throw_args",
"else",
":",
"if",
"getcurrent",
"(",
")",
"is",
"not",
"self",
... | https://github.com/gevent/gevent/blob/ae2cb5aeb2aea8987efcb90a4c50ca4e1ee12c31/src/gevent/_waiter.py#L129-L141 | ||
minio/minio-py | b3ba3bf99fe6b9ff2b28855550d6ab5345c134e3 | minio/datatypes.py | python | ListMultipartUploadsResult.key_marker | (self) | return self._key_marker | Get key marker. | Get key marker. | [
"Get",
"key",
"marker",
"."
] | def key_marker(self):
"""Get key marker."""
return self._key_marker | [
"def",
"key_marker",
"(",
"self",
")",
":",
"return",
"self",
".",
"_key_marker"
] | https://github.com/minio/minio-py/blob/b3ba3bf99fe6b9ff2b28855550d6ab5345c134e3/minio/datatypes.py#L591-L593 | |
tmulc18/Distributed-TensorFlow-Guide | 8e7fec757112a3ab5dccff93e848e7617ef7ed3e | DOWNPOUR/DOWNPOUR.py | python | add_global_variables_to_local_collection | () | return r | Adds all variables from the global collection
to the local collection.
Returns the list of variables added. | Adds all variables from the global collection
to the local collection. | [
"Adds",
"all",
"variables",
"from",
"the",
"global",
"collection",
"to",
"the",
"local",
"collection",
"."
] | def add_global_variables_to_local_collection():
"""Adds all variables from the global collection
to the local collection.
Returns the list of variables added.
"""
r =[]
for var in tf.get_default_graph()._collections[tf.GraphKeys.GLOBAL_VARIABLES]:
tf.add_to_collection(tf.GraphKeys.LOCAL_VARIABLES,var)
r.append(var)
return r | [
"def",
"add_global_variables_to_local_collection",
"(",
")",
":",
"r",
"=",
"[",
"]",
"for",
"var",
"in",
"tf",
".",
"get_default_graph",
"(",
")",
".",
"_collections",
"[",
"tf",
".",
"GraphKeys",
".",
"GLOBAL_VARIABLES",
"]",
":",
"tf",
".",
"add_to_collec... | https://github.com/tmulc18/Distributed-TensorFlow-Guide/blob/8e7fec757112a3ab5dccff93e848e7617ef7ed3e/DOWNPOUR/DOWNPOUR.py#L216-L226 | |
securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/whoosh/src/whoosh/matching/binary.py | python | DisjunctionMaxMatcher.skip_to_quality | (self, minquality) | return skipped | [] | def skip_to_quality(self, minquality):
a = self.a
b = self.b
# Short circuit if one matcher is inactive
if not a.is_active():
sk = b.skip_to_quality(minquality)
return sk
elif not b.is_active():
return a.skip_to_quality(minquality)
skipped = 0
aq = a.block_quality()
bq = b.block_quality()
while a.is_active() and b.is_active() and max(aq, bq) <= minquality:
if aq <= minquality:
skipped += a.skip_to_quality(minquality)
aq = a.block_quality()
if bq <= minquality:
skipped += b.skip_to_quality(minquality)
bq = b.block_quality()
return skipped | [
"def",
"skip_to_quality",
"(",
"self",
",",
"minquality",
")",
":",
"a",
"=",
"self",
".",
"a",
"b",
"=",
"self",
".",
"b",
"# Short circuit if one matcher is inactive",
"if",
"not",
"a",
".",
"is_active",
"(",
")",
":",
"sk",
"=",
"b",
".",
"skip_to_qua... | https://github.com/securesystemslab/zippy/blob/ff0e84ac99442c2c55fe1d285332cfd4e185e089/zippy/benchmarks/src/benchmarks/whoosh/src/whoosh/matching/binary.py#L390-L411 | |||
tdamdouni/Pythonista | 3e082d53b6b9b501a3c8cf3251a8ad4c8be9c2ad | stash/pep8.py | python | Checker.report_invalid_syntax | (self) | Check if the syntax is valid. | Check if the syntax is valid. | [
"Check",
"if",
"the",
"syntax",
"is",
"valid",
"."
] | def report_invalid_syntax(self):
"""Check if the syntax is valid."""
(exc_type, exc) = sys.exc_info()[:2]
if len(exc.args) > 1:
offset = exc.args[1]
if len(offset) > 2:
offset = offset[1:3]
else:
offset = (1, 0)
self.report_error(offset[0], offset[1] or 0,
'E901 %s: %s' % (exc_type.__name__, exc.args[0]),
self.report_invalid_syntax) | [
"def",
"report_invalid_syntax",
"(",
"self",
")",
":",
"(",
"exc_type",
",",
"exc",
")",
"=",
"sys",
".",
"exc_info",
"(",
")",
"[",
":",
"2",
"]",
"if",
"len",
"(",
"exc",
".",
"args",
")",
">",
"1",
":",
"offset",
"=",
"exc",
".",
"args",
"["... | https://github.com/tdamdouni/Pythonista/blob/3e082d53b6b9b501a3c8cf3251a8ad4c8be9c2ad/stash/pep8.py#L1425-L1436 | ||
caiiiac/Machine-Learning-with-Python | 1a26c4467da41ca4ebc3d5bd789ea942ef79422f | MachineLearning/venv/lib/python3.5/site-packages/sklearn/decomposition/pca.py | python | PCA.score_samples | (self, X) | return log_like | Return the log-likelihood of each sample.
See. "Pattern Recognition and Machine Learning"
by C. Bishop, 12.2.1 p. 574
or http://www.miketipping.com/papers/met-mppca.pdf
Parameters
----------
X: array, shape(n_samples, n_features)
The data.
Returns
-------
ll: array, shape (n_samples,)
Log-likelihood of each sample under the current model | Return the log-likelihood of each sample. | [
"Return",
"the",
"log",
"-",
"likelihood",
"of",
"each",
"sample",
"."
] | def score_samples(self, X):
"""Return the log-likelihood of each sample.
See. "Pattern Recognition and Machine Learning"
by C. Bishop, 12.2.1 p. 574
or http://www.miketipping.com/papers/met-mppca.pdf
Parameters
----------
X: array, shape(n_samples, n_features)
The data.
Returns
-------
ll: array, shape (n_samples,)
Log-likelihood of each sample under the current model
"""
check_is_fitted(self, 'mean_')
X = check_array(X)
Xr = X - self.mean_
n_features = X.shape[1]
log_like = np.zeros(X.shape[0])
precision = self.get_precision()
log_like = -.5 * (Xr * (np.dot(Xr, precision))).sum(axis=1)
log_like -= .5 * (n_features * log(2. * np.pi) -
fast_logdet(precision))
return log_like | [
"def",
"score_samples",
"(",
"self",
",",
"X",
")",
":",
"check_is_fitted",
"(",
"self",
",",
"'mean_'",
")",
"X",
"=",
"check_array",
"(",
"X",
")",
"Xr",
"=",
"X",
"-",
"self",
".",
"mean_",
"n_features",
"=",
"X",
".",
"shape",
"[",
"1",
"]",
... | https://github.com/caiiiac/Machine-Learning-with-Python/blob/1a26c4467da41ca4ebc3d5bd789ea942ef79422f/MachineLearning/venv/lib/python3.5/site-packages/sklearn/decomposition/pca.py#L485-L512 | |
NVIDIA/NeMo | 5b0c0b4dec12d87d3cd960846de4105309ce938e | nemo/collections/asr/data/audio_to_text_dataset.py | python | get_bpe_dataset | (
config: dict, tokenizer: 'TokenizerSpec', augmentor: Optional['AudioAugmentor'] = None
) | return dataset | Instantiates a Byte Pair Encoding / Word Piece Encoding based AudioToBPEDataset.
Args:
config: Config of the AudioToBPEDataset.
tokenizer: An instance of a TokenizerSpec object.
augmentor: Optional AudioAugmentor object for augmentations on audio data.
Returns:
An instance of AudioToBPEDataset. | Instantiates a Byte Pair Encoding / Word Piece Encoding based AudioToBPEDataset. | [
"Instantiates",
"a",
"Byte",
"Pair",
"Encoding",
"/",
"Word",
"Piece",
"Encoding",
"based",
"AudioToBPEDataset",
"."
] | def get_bpe_dataset(
config: dict, tokenizer: 'TokenizerSpec', augmentor: Optional['AudioAugmentor'] = None
) -> audio_to_text.AudioToBPEDataset:
"""
Instantiates a Byte Pair Encoding / Word Piece Encoding based AudioToBPEDataset.
Args:
config: Config of the AudioToBPEDataset.
tokenizer: An instance of a TokenizerSpec object.
augmentor: Optional AudioAugmentor object for augmentations on audio data.
Returns:
An instance of AudioToBPEDataset.
"""
dataset = audio_to_text.AudioToBPEDataset(
manifest_filepath=config['manifest_filepath'],
tokenizer=tokenizer,
sample_rate=config['sample_rate'],
int_values=config.get('int_values', False),
augmentor=augmentor,
max_duration=config.get('max_duration', None),
min_duration=config.get('min_duration', None),
max_utts=config.get('max_utts', 0),
trim=config.get('trim_silence', False),
use_start_end_token=config.get('use_start_end_token', True),
return_sample_id=config.get('return_sample_id', False),
)
return dataset | [
"def",
"get_bpe_dataset",
"(",
"config",
":",
"dict",
",",
"tokenizer",
":",
"'TokenizerSpec'",
",",
"augmentor",
":",
"Optional",
"[",
"'AudioAugmentor'",
"]",
"=",
"None",
")",
"->",
"audio_to_text",
".",
"AudioToBPEDataset",
":",
"dataset",
"=",
"audio_to_tex... | https://github.com/NVIDIA/NeMo/blob/5b0c0b4dec12d87d3cd960846de4105309ce938e/nemo/collections/asr/data/audio_to_text_dataset.py#L104-L131 | |
bendmorris/static-python | 2e0f8c4d7ed5b359dc7d8a75b6fb37e6b6c5c473 | Lib/pydoc.py | python | TextDoc.docdata | (self, object, name=None, mod=None, cl=None) | return self._docdescriptor(name, object, mod) | Produce text documentation for a data descriptor. | Produce text documentation for a data descriptor. | [
"Produce",
"text",
"documentation",
"for",
"a",
"data",
"descriptor",
"."
] | def docdata(self, object, name=None, mod=None, cl=None):
"""Produce text documentation for a data descriptor."""
return self._docdescriptor(name, object, mod) | [
"def",
"docdata",
"(",
"self",
",",
"object",
",",
"name",
"=",
"None",
",",
"mod",
"=",
"None",
",",
"cl",
"=",
"None",
")",
":",
"return",
"self",
".",
"_docdescriptor",
"(",
"name",
",",
"object",
",",
"mod",
")"
] | https://github.com/bendmorris/static-python/blob/2e0f8c4d7ed5b359dc7d8a75b6fb37e6b6c5c473/Lib/pydoc.py#L1354-L1356 | |
twisted/twisted | dee676b040dd38b847ea6fb112a712cb5e119490 | src/twisted/protocols/ftp.py | python | DTPFactory.__init__ | (self, pi, peerHost=None, reactor=None) | Constructor
@param pi: this factory's protocol interpreter
@param peerHost: if peerCheck is True, this is the tuple that the
generated instance will use to perform security checks | Constructor | [
"Constructor"
] | def __init__(self, pi, peerHost=None, reactor=None):
"""
Constructor
@param pi: this factory's protocol interpreter
@param peerHost: if peerCheck is True, this is the tuple that the
generated instance will use to perform security checks
"""
self.pi = pi
self.peerHost = peerHost # from FTP.transport.peerHost()
# deferred will fire when instance is connected
self.deferred = defer.Deferred()
self.delayedCall = None
if reactor is None:
from twisted.internet import reactor
self._reactor = reactor | [
"def",
"__init__",
"(",
"self",
",",
"pi",
",",
"peerHost",
"=",
"None",
",",
"reactor",
"=",
"None",
")",
":",
"self",
".",
"pi",
"=",
"pi",
"self",
".",
"peerHost",
"=",
"peerHost",
"# from FTP.transport.peerHost()",
"# deferred will fire when instance is conn... | https://github.com/twisted/twisted/blob/dee676b040dd38b847ea6fb112a712cb5e119490/src/twisted/protocols/ftp.py#L590-L605 | ||
riptideio/pymodbus | c5772b35ae3f29d1947f3ab453d8d00df846459f | pymodbus/client/sync.py | python | BaseModbusClient.debug_enabled | (self) | return self._debug | Returns a boolean indicating if debug is enabled. | Returns a boolean indicating if debug is enabled. | [
"Returns",
"a",
"boolean",
"indicating",
"if",
"debug",
"is",
"enabled",
"."
] | def debug_enabled(self):
"""
Returns a boolean indicating if debug is enabled.
"""
return self._debug | [
"def",
"debug_enabled",
"(",
"self",
")",
":",
"return",
"self",
".",
"_debug"
] | https://github.com/riptideio/pymodbus/blob/c5772b35ae3f29d1947f3ab453d8d00df846459f/pymodbus/client/sync.py#L136-L140 | |
openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.9.40/roles/lib_openshift/src/class/oc_label.py | python | OCLabel.any_label_exists | (self) | return False | return whether any single label already exists | return whether any single label already exists | [
"return",
"whether",
"any",
"single",
"label",
"already",
"exists"
] | def any_label_exists(self):
''' return whether any single label already exists '''
for current_host_labels in self.current_labels:
for label in self.labels:
if label['key'] in current_host_labels:
return True
return False | [
"def",
"any_label_exists",
"(",
"self",
")",
":",
"for",
"current_host_labels",
"in",
"self",
".",
"current_labels",
":",
"for",
"label",
"in",
"self",
".",
"labels",
":",
"if",
"label",
"[",
"'key'",
"]",
"in",
"current_host_labels",
":",
"return",
"True",
... | https://github.com/openshift/openshift-tools/blob/1188778e728a6e4781acf728123e5b356380fe6f/openshift/installer/vendored/openshift-ansible-3.9.40/roles/lib_openshift/src/class/oc_label.py#L59-L66 | |
cognitect-labs/transducers-python | 11ac3e5c78a5a9dd30719d3aba91bf333c249a94 | transducers/transducers.py | python | take | (n) | return _take_xducer | Takes n values from a collection. | Takes n values from a collection. | [
"Takes",
"n",
"values",
"from",
"a",
"collection",
"."
] | def take(n):
"""Takes n values from a collection."""
def _take_xducer(step):
outer_vars = {"counter": n}
def _take_step(r=Missing, x=Missing):
if r is Missing: return step()
if x is Missing:
return step(r)
n = outer_vars["counter"]
outer_vars["counter"] -= 1
r = step(r, x) if n > 0 else r
return ensure_reduced(r) if outer_vars["counter"] <= 0 else r
return _take_step
return _take_xducer | [
"def",
"take",
"(",
"n",
")",
":",
"def",
"_take_xducer",
"(",
"step",
")",
":",
"outer_vars",
"=",
"{",
"\"counter\"",
":",
"n",
"}",
"def",
"_take_step",
"(",
"r",
"=",
"Missing",
",",
"x",
"=",
"Missing",
")",
":",
"if",
"r",
"is",
"Missing",
... | https://github.com/cognitect-labs/transducers-python/blob/11ac3e5c78a5a9dd30719d3aba91bf333c249a94/transducers/transducers.py#L123-L136 | |
lisa-lab/pylearn2 | af81e5c362f0df4df85c3e54e23b2adeec026055 | pylearn2/models/dbm/dbm.py | python | DBM.get_weights | (self) | return self.hidden_layers[0].get_weights() | .. todo::
WRITEME | .. todo:: | [
"..",
"todo",
"::"
] | def get_weights(self):
"""
.. todo::
WRITEME
"""
return self.hidden_layers[0].get_weights() | [
"def",
"get_weights",
"(",
"self",
")",
":",
"return",
"self",
".",
"hidden_layers",
"[",
"0",
"]",
".",
"get_weights",
"(",
")"
] | https://github.com/lisa-lab/pylearn2/blob/af81e5c362f0df4df85c3e54e23b2adeec026055/pylearn2/models/dbm/dbm.py#L391-L397 | |
jparkhill/TensorMol | d52104dc7ee46eec8301d332a95d672270ac0bd1 | TensorMol/ForceModifiers/Periodic.py | python | PeriodicForce.BindForce | (self, lf_, rng_) | Adds a local force to be computed when the PeriodicForce is called.
Args:
lf_: a function which takes z,x and returns atom energies, atom forces. | Adds a local force to be computed when the PeriodicForce is called. | [
"Adds",
"a",
"local",
"force",
"to",
"be",
"computed",
"when",
"the",
"PeriodicForce",
"is",
"called",
"."
] | def BindForce(self, lf_, rng_):
"""
Adds a local force to be computed when the PeriodicForce is called.
Args:
lf_: a function which takes z,x and returns atom energies, atom forces.
"""
self.LocalForces.append(LocalForce(lf_,rng_)) | [
"def",
"BindForce",
"(",
"self",
",",
"lf_",
",",
"rng_",
")",
":",
"self",
".",
"LocalForces",
".",
"append",
"(",
"LocalForce",
"(",
"lf_",
",",
"rng_",
")",
")"
] | https://github.com/jparkhill/TensorMol/blob/d52104dc7ee46eec8301d332a95d672270ac0bd1/TensorMol/ForceModifiers/Periodic.py#L368-L375 | ||
eirannejad/pyRevit | 49c0b7eb54eb343458ce1365425e6552d0c47d44 | site-packages/requests/packages/urllib3/fields.py | python | RequestField._render_part | (self, name, value) | return format_header_param(name, value) | Overridable helper function to format a single header parameter.
:param name:
The name of the parameter, a string expected to be ASCII only.
:param value:
The value of the parameter, provided as a unicode string. | Overridable helper function to format a single header parameter. | [
"Overridable",
"helper",
"function",
"to",
"format",
"a",
"single",
"header",
"parameter",
"."
] | def _render_part(self, name, value):
"""
Overridable helper function to format a single header parameter.
:param name:
The name of the parameter, a string expected to be ASCII only.
:param value:
The value of the parameter, provided as a unicode string.
"""
return format_header_param(name, value) | [
"def",
"_render_part",
"(",
"self",
",",
"name",
",",
"value",
")",
":",
"return",
"format_header_param",
"(",
"name",
",",
"value",
")"
] | https://github.com/eirannejad/pyRevit/blob/49c0b7eb54eb343458ce1365425e6552d0c47d44/site-packages/requests/packages/urllib3/fields.py#L105-L114 | |
CedricGuillemet/Imogen | ee417b42747ed5b46cb11b02ef0c3630000085b3 | bin/Lib/asyncio/events.py | python | _get_running_loop | () | Return the running event loop or None.
This is a low-level function intended to be used by event loops.
This function is thread-specific. | Return the running event loop or None. | [
"Return",
"the",
"running",
"event",
"loop",
"or",
"None",
"."
] | def _get_running_loop():
"""Return the running event loop or None.
This is a low-level function intended to be used by event loops.
This function is thread-specific.
"""
# NOTE: this function is implemented in C (see _asynciomodule.c)
running_loop, pid = _running_loop.loop_pid
if running_loop is not None and pid == os.getpid():
return running_loop | [
"def",
"_get_running_loop",
"(",
")",
":",
"# NOTE: this function is implemented in C (see _asynciomodule.c)",
"running_loop",
",",
"pid",
"=",
"_running_loop",
".",
"loop_pid",
"if",
"running_loop",
"is",
"not",
"None",
"and",
"pid",
"==",
"os",
".",
"getpid",
"(",
... | https://github.com/CedricGuillemet/Imogen/blob/ee417b42747ed5b46cb11b02ef0c3630000085b3/bin/Lib/asyncio/events.py#L693-L702 | ||
roglew/guppy-proxy | 01df16be71dd9f23d7de415a315821659c29bc63 | guppyproxy/macros.py | python | ActiveMacroWidget.browse_macro | (self) | [] | def browse_macro(self):
fname = open_dialog(self, filter_string="Python File (*.py)")
if not fname:
return
self.tableModel.add_macro(fname) | [
"def",
"browse_macro",
"(",
"self",
")",
":",
"fname",
"=",
"open_dialog",
"(",
"self",
",",
"filter_string",
"=",
"\"Python File (*.py)\"",
")",
"if",
"not",
"fname",
":",
"return",
"self",
".",
"tableModel",
".",
"add_macro",
"(",
"fname",
")"
] | https://github.com/roglew/guppy-proxy/blob/01df16be71dd9f23d7de415a315821659c29bc63/guppyproxy/macros.py#L666-L670 | ||||
JinpengLI/deep_ocr | 450148c0c51b3565a96ac2f3c94ee33022e55307 | deep_ocr/ocrolib/common.py | python | RegionExtractor.x1 | (self,i) | return self.bbox(i)[3] | Return x0 (column) for the end of the box. | Return x0 (column) for the end of the box. | [
"Return",
"x0",
"(",
"column",
")",
"for",
"the",
"end",
"of",
"the",
"box",
"."
] | def x1(self,i):
"""Return x0 (column) for the end of the box."""
return self.bbox(i)[3] | [
"def",
"x1",
"(",
"self",
",",
"i",
")",
":",
"return",
"self",
".",
"bbox",
"(",
"i",
")",
"[",
"3",
"]"
] | https://github.com/JinpengLI/deep_ocr/blob/450148c0c51b3565a96ac2f3c94ee33022e55307/deep_ocr/ocrolib/common.py#L351-L353 | |
learningequality/ka-lite | 571918ea668013dcf022286ea85eff1c5333fb8b | kalite/packages/bundled/django/contrib/comments/moderation.py | python | CommentModerator.moderate | (self, comment, content_object, request) | return False | Determine whether a given comment on a given object should be
allowed to show up immediately, or should be marked non-public
and await approval.
Return ``True`` if the comment should be moderated (marked
non-public), ``False`` otherwise. | Determine whether a given comment on a given object should be
allowed to show up immediately, or should be marked non-public
and await approval. | [
"Determine",
"whether",
"a",
"given",
"comment",
"on",
"a",
"given",
"object",
"should",
"be",
"allowed",
"to",
"show",
"up",
"immediately",
"or",
"should",
"be",
"marked",
"non",
"-",
"public",
"and",
"await",
"approval",
"."
] | def moderate(self, comment, content_object, request):
"""
Determine whether a given comment on a given object should be
allowed to show up immediately, or should be marked non-public
and await approval.
Return ``True`` if the comment should be moderated (marked
non-public), ``False`` otherwise.
"""
if self.auto_moderate_field and self.moderate_after is not None:
moderate_after_date = getattr(content_object, self.auto_moderate_field)
if moderate_after_date is not None and self._get_delta(timezone.now(), moderate_after_date).days >= self.moderate_after:
return True
return False | [
"def",
"moderate",
"(",
"self",
",",
"comment",
",",
"content_object",
",",
"request",
")",
":",
"if",
"self",
".",
"auto_moderate_field",
"and",
"self",
".",
"moderate_after",
"is",
"not",
"None",
":",
"moderate_after_date",
"=",
"getattr",
"(",
"content_obje... | https://github.com/learningequality/ka-lite/blob/571918ea668013dcf022286ea85eff1c5333fb8b/kalite/packages/bundled/django/contrib/comments/moderation.py#L215-L229 | |
jadore801120/attention-is-all-you-need-pytorch | 132907dd272e2cc92e3c10e6c4e783a87ff8893d | learn_bpe.py | python | replace_pair | (pair, vocab, indices) | return changes | Replace all occurrences of a symbol pair ('A', 'B') with a new symbol 'AB | Replace all occurrences of a symbol pair ('A', 'B') with a new symbol 'AB | [
"Replace",
"all",
"occurrences",
"of",
"a",
"symbol",
"pair",
"(",
"A",
"B",
")",
"with",
"a",
"new",
"symbol",
"AB"
] | def replace_pair(pair, vocab, indices):
"""Replace all occurrences of a symbol pair ('A', 'B') with a new symbol 'AB'"""
first, second = pair
pair_str = ''.join(pair)
pair_str = pair_str.replace('\\','\\\\')
changes = []
pattern = re.compile(r'(?<!\S)' + re.escape(first + ' ' + second) + r'(?!\S)')
if sys.version_info < (3, 0):
iterator = indices[pair].iteritems()
else:
iterator = indices[pair].items()
for j, freq in iterator:
if freq < 1:
continue
word, freq = vocab[j]
new_word = ' '.join(word)
new_word = pattern.sub(pair_str, new_word)
new_word = tuple(new_word.split(' '))
vocab[j] = (new_word, freq)
changes.append((j, new_word, word, freq))
return changes | [
"def",
"replace_pair",
"(",
"pair",
",",
"vocab",
",",
"indices",
")",
":",
"first",
",",
"second",
"=",
"pair",
"pair_str",
"=",
"''",
".",
"join",
"(",
"pair",
")",
"pair_str",
"=",
"pair_str",
".",
"replace",
"(",
"'\\\\'",
",",
"'\\\\\\\\'",
")",
... | https://github.com/jadore801120/attention-is-all-you-need-pytorch/blob/132907dd272e2cc92e3c10e6c4e783a87ff8893d/learn_bpe.py#L125-L147 | |
XuezheMax/flowseq | 8cb4ae00c26fbeb3e1459e3b3b90e7e9a84c3d2b | flownmt/data/dataloader.py | python | DataIterator.get_batch | (self, batch_size) | return self.process_batch(batch) | [] | def get_batch(self, batch_size):
batch = random.sample(self.data, batch_size)
return self.process_batch(batch) | [
"def",
"get_batch",
"(",
"self",
",",
"batch_size",
")",
":",
"batch",
"=",
"random",
".",
"sample",
"(",
"self",
".",
"data",
",",
"batch_size",
")",
"return",
"self",
".",
"process_batch",
"(",
"batch",
")"
] | https://github.com/XuezheMax/flowseq/blob/8cb4ae00c26fbeb3e1459e3b3b90e7e9a84c3d2b/flownmt/data/dataloader.py#L458-L460 | |||
mozilla/MozDef | d7d4dd1cd898bb4eeb59d014bd5bcfe96554a10f | mq/plugins/parse_su.py | python | message.__init__ | (self) | takes an incoming su message
and parses it to extract data points | takes an incoming su message
and parses it to extract data points | [
"takes",
"an",
"incoming",
"su",
"message",
"and",
"parses",
"it",
"to",
"extract",
"data",
"points"
] | def __init__(self):
'''
takes an incoming su message
and parses it to extract data points
'''
self.registration = ['sshd']
self.priority = 5 | [
"def",
"__init__",
"(",
"self",
")",
":",
"self",
".",
"registration",
"=",
"[",
"'sshd'",
"]",
"self",
".",
"priority",
"=",
"5"
] | https://github.com/mozilla/MozDef/blob/d7d4dd1cd898bb4eeb59d014bd5bcfe96554a10f/mq/plugins/parse_su.py#L11-L18 | ||
landlab/landlab | a5dd80b8ebfd03d1ba87ef6c4368c409485f222c | landlab/graph/graph.py | python | NetworkGraph.angle_of_link | (self) | return get_angle_of_link(self) | Get the angle of each link.
Examples
--------
>>> import numpy as np
>>> from landlab.graph import Graph
>>> node_x, node_y = ([0, 1, 2, 0, 1, 2],
... [0, 0, 0, 1, 1, 1])
>>> links = ((0, 1), (1, 2),
... (0, 3), (1, 4), (2, 5),
... (3, 4), (4, 5))
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.angle_of_link * 180. / np.pi
array([ 0., 0., 90., 90., 90., 0., 0.])
LLCATS: LINF | Get the angle of each link. | [
"Get",
"the",
"angle",
"of",
"each",
"link",
"."
] | def angle_of_link(self):
"""Get the angle of each link.
Examples
--------
>>> import numpy as np
>>> from landlab.graph import Graph
>>> node_x, node_y = ([0, 1, 2, 0, 1, 2],
... [0, 0, 0, 1, 1, 1])
>>> links = ((0, 1), (1, 2),
... (0, 3), (1, 4), (2, 5),
... (3, 4), (4, 5))
>>> graph = Graph((node_y, node_x), links=links)
>>> graph.angle_of_link * 180. / np.pi
array([ 0., 0., 90., 90., 90., 0., 0.])
LLCATS: LINF
"""
return get_angle_of_link(self) | [
"def",
"angle_of_link",
"(",
"self",
")",
":",
"return",
"get_angle_of_link",
"(",
"self",
")"
] | https://github.com/landlab/landlab/blob/a5dd80b8ebfd03d1ba87ef6c4368c409485f222c/landlab/graph/graph.py#L566-L585 | |
securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/sympy/sympy/polys/domains/old_polynomialring.py | python | GeneralizedPolynomialRing.to_sympy | (self, a) | return (basic_from_dict(a.numer().to_sympy_dict(), *self.gens) /
basic_from_dict(a.denom().to_sympy_dict(), *self.gens)) | Convert `a` to a SymPy object. | Convert `a` to a SymPy object. | [
"Convert",
"a",
"to",
"a",
"SymPy",
"object",
"."
] | def to_sympy(self, a):
"""Convert `a` to a SymPy object. """
return (basic_from_dict(a.numer().to_sympy_dict(), *self.gens) /
basic_from_dict(a.denom().to_sympy_dict(), *self.gens)) | [
"def",
"to_sympy",
"(",
"self",
",",
"a",
")",
":",
"return",
"(",
"basic_from_dict",
"(",
"a",
".",
"numer",
"(",
")",
".",
"to_sympy_dict",
"(",
")",
",",
"*",
"self",
".",
"gens",
")",
"/",
"basic_from_dict",
"(",
"a",
".",
"denom",
"(",
")",
... | https://github.com/securesystemslab/zippy/blob/ff0e84ac99442c2c55fe1d285332cfd4e185e089/zippy/benchmarks/src/benchmarks/sympy/sympy/polys/domains/old_polynomialring.py#L309-L312 | |
chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/pandas/core/categorical.py | python | Categorical.memory_usage | (self, deep=False) | return self._codes.nbytes + self._categories.memory_usage(deep=deep) | Memory usage of my values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False
See Also
--------
numpy.ndarray.nbytes | Memory usage of my values | [
"Memory",
"usage",
"of",
"my",
"values"
] | def memory_usage(self, deep=False):
"""
Memory usage of my values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False
See Also
--------
numpy.ndarray.nbytes
"""
return self._codes.nbytes + self._categories.memory_usage(deep=deep) | [
"def",
"memory_usage",
"(",
"self",
",",
"deep",
"=",
"False",
")",
":",
"return",
"self",
".",
"_codes",
".",
"nbytes",
"+",
"self",
".",
"_categories",
".",
"memory_usage",
"(",
"deep",
"=",
"deep",
")"
] | https://github.com/chribsen/simple-machine-learning-examples/blob/dc94e52a4cebdc8bb959ff88b81ff8cfeca25022/venv/lib/python2.7/site-packages/pandas/core/categorical.py#L1054-L1077 | |
google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/client/grr_response_client/client_actions/memory.py | python | UnprivilegedYaraWrapper.Open | (self) | [] | def Open(self) -> None:
with contextlib.ExitStack() as stack:
file_descriptors = []
for psutil_process in self._psutil_processes:
try:
process = stack.enter_context(
client_utils.OpenProcessForMemoryAccess(psutil_process.pid))
except Exception as e: # pylint: disable=broad-except
# OpenProcessForMemoryAccess can raise any exception upon error.
self._pid_to_exception[psutil_process.pid] = e
continue
self._pid_to_serializable_file_descriptor[
psutil_process.pid] = process.serialized_file_descriptor
file_descriptors.append(
communication.FileDescriptor.FromSerialized(
process.serialized_file_descriptor, communication.Mode.READ))
self._server = memory_server.CreateMemoryServer(file_descriptors)
self._server.Start()
self._client = memory_client.Client(self._server.Connect()) | [
"def",
"Open",
"(",
"self",
")",
"->",
"None",
":",
"with",
"contextlib",
".",
"ExitStack",
"(",
")",
"as",
"stack",
":",
"file_descriptors",
"=",
"[",
"]",
"for",
"psutil_process",
"in",
"self",
".",
"_psutil_processes",
":",
"try",
":",
"process",
"=",... | https://github.com/google/grr/blob/8ad8a4d2c5a93c92729206b7771af19d92d4f915/grr/client/grr_response_client/client_actions/memory.py#L220-L238 | ||||
GRAAL-Research/poutyne | f46e5fe610d175b96a490db24ef2d22b49cc594b | poutyne/framework/model_bundle.py | python | ModelBundle.infer_dataset | (self, dataset, **kwargs) | return self._predict(self.model.predict_dataset, dataset, **kwargs) | Returns the inferred predictions of the network given a dataset, where the tensors are
converted into Numpy arrays.
Args:
dataset (~torch.utils.data.Dataset): Dataset. Must not return ``y``, just ``x``.
checkpoint (Union[str, int]): Which model checkpoint weights to load for the prediction.
- If 'best', will load the best weights according to ``monitor_metric`` and ``monitor_mode``.
- If 'last', will load the last model checkpoint.
- If int, will load the checkpoint of the specified epoch.
- If a path (str), will load the model pickled state_dict weights (for instance, saved as
``torch.save(a_pytorch_network.state_dict(), "./a_path.p")``).
This argument has no effect when logging is disabled. (Default value = 'best')
kwargs: Any keyword arguments to pass to :func:`~Model.predict_dataset()`.
Returns:
Return the predictions in the format outputted by the model. | Returns the inferred predictions of the network given a dataset, where the tensors are
converted into Numpy arrays. | [
"Returns",
"the",
"inferred",
"predictions",
"of",
"the",
"network",
"given",
"a",
"dataset",
"where",
"the",
"tensors",
"are",
"converted",
"into",
"Numpy",
"arrays",
"."
] | def infer_dataset(self, dataset, **kwargs) -> Any:
"""
Returns the inferred predictions of the network given a dataset, where the tensors are
converted into Numpy arrays.
Args:
dataset (~torch.utils.data.Dataset): Dataset. Must not return ``y``, just ``x``.
checkpoint (Union[str, int]): Which model checkpoint weights to load for the prediction.
- If 'best', will load the best weights according to ``monitor_metric`` and ``monitor_mode``.
- If 'last', will load the last model checkpoint.
- If int, will load the checkpoint of the specified epoch.
- If a path (str), will load the model pickled state_dict weights (for instance, saved as
``torch.save(a_pytorch_network.state_dict(), "./a_path.p")``).
This argument has no effect when logging is disabled. (Default value = 'best')
kwargs: Any keyword arguments to pass to :func:`~Model.predict_dataset()`.
Returns:
Return the predictions in the format outputted by the model.
"""
return self._predict(self.model.predict_dataset, dataset, **kwargs) | [
"def",
"infer_dataset",
"(",
"self",
",",
"dataset",
",",
"*",
"*",
"kwargs",
")",
"->",
"Any",
":",
"return",
"self",
".",
"_predict",
"(",
"self",
".",
"model",
".",
"predict_dataset",
",",
"dataset",
",",
"*",
"*",
"kwargs",
")"
] | https://github.com/GRAAL-Research/poutyne/blob/f46e5fe610d175b96a490db24ef2d22b49cc594b/poutyne/framework/model_bundle.py#L1122-L1143 | |
postgres/pgadmin4 | 374c5e952fa594d749fadf1f88076c1cba8c5f64 | web/pgadmin/authenticate/__init__.py | python | get_auth_sources | (type) | return auth_source | Get the authenticated source object from the registry | Get the authenticated source object from the registry | [
"Get",
"the",
"authenticated",
"source",
"object",
"from",
"the",
"registry"
] | def get_auth_sources(type):
"""Get the authenticated source object from the registry"""
auth_sources = getattr(current_app, '_pgadmin_auth_sources', None)
if auth_sources is None or not isinstance(auth_sources, dict):
auth_sources = dict()
if type in auth_sources:
return auth_sources[type]
auth_source = AuthSourceRegistry.get(type)
if auth_source is not None:
auth_sources[type] = auth_source
setattr(current_app, '_pgadmin_auth_sources', auth_sources)
return auth_source | [
"def",
"get_auth_sources",
"(",
"type",
")",
":",
"auth_sources",
"=",
"getattr",
"(",
"current_app",
",",
"'_pgadmin_auth_sources'",
",",
"None",
")",
"if",
"auth_sources",
"is",
"None",
"or",
"not",
"isinstance",
"(",
"auth_sources",
",",
"dict",
")",
":",
... | https://github.com/postgres/pgadmin4/blob/374c5e952fa594d749fadf1f88076c1cba8c5f64/web/pgadmin/authenticate/__init__.py#L258-L275 | |
demisto/content | 5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07 | Packs/PAN-OS/Integrations/Panorama/Panorama.py | python | panorama_create_edl_command | (args: Dict[str, str]) | Create an edl object | Create an edl object | [
"Create",
"an",
"edl",
"object"
] | def panorama_create_edl_command(args: Dict[str, str]):
"""
Create an edl object
"""
edl_name = args.get('name')
url = args.get('url', '').replace(' ', '%20')
type_ = args.get('type')
recurring = args.get('recurring')
certificate_profile = args.get('certificate_profile')
description = args.get('description')
edl = panorama_create_edl(edl_name, url, type_, recurring, certificate_profile, description)
edl_output = {
'Name': edl_name,
'URL': url,
'Type': type_,
'Recurring': recurring
}
if DEVICE_GROUP:
edl_output['DeviceGroup'] = DEVICE_GROUP
if description:
edl_output['Description'] = description
if certificate_profile:
edl_output['CertificateProfile'] = certificate_profile
return_results({
'Type': entryTypes['note'],
'ContentsFormat': formats['json'],
'Contents': edl,
'ReadableContentsFormat': formats['text'],
'HumanReadable': 'External Dynamic List was created successfully.',
'EntryContext': {
"Panorama.EDL(val.Name == obj.Name)": edl_output
}
}) | [
"def",
"panorama_create_edl_command",
"(",
"args",
":",
"Dict",
"[",
"str",
",",
"str",
"]",
")",
":",
"edl_name",
"=",
"args",
".",
"get",
"(",
"'name'",
")",
"url",
"=",
"args",
".",
"get",
"(",
"'url'",
",",
"''",
")",
".",
"replace",
"(",
"' '"... | https://github.com/demisto/content/blob/5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07/Packs/PAN-OS/Integrations/Panorama/Panorama.py#L3579-L3615 | ||
lspvic/CopyNet | 2cc44dd672115fe88a2d76bd59b76fb2d7389bb4 | nmt/nmt/scripts/rouge.py | python | _get_word_ngrams | (n, sentences) | return _get_ngrams(n, words) | Calculates word n-grams for multiple sentences. | Calculates word n-grams for multiple sentences. | [
"Calculates",
"word",
"n",
"-",
"grams",
"for",
"multiple",
"sentences",
"."
] | def _get_word_ngrams(n, sentences):
"""Calculates word n-grams for multiple sentences.
"""
assert len(sentences) > 0
assert n > 0
words = _split_into_words(sentences)
return _get_ngrams(n, words) | [
"def",
"_get_word_ngrams",
"(",
"n",
",",
"sentences",
")",
":",
"assert",
"len",
"(",
"sentences",
")",
">",
"0",
"assert",
"n",
">",
"0",
"words",
"=",
"_split_into_words",
"(",
"sentences",
")",
"return",
"_get_ngrams",
"(",
"n",
",",
"words",
")"
] | https://github.com/lspvic/CopyNet/blob/2cc44dd672115fe88a2d76bd59b76fb2d7389bb4/nmt/nmt/scripts/rouge.py#L42-L49 | |
Fallen-Breath/MCDReforged | fdb1d2520b35f916123f265dbd94603981bb2b0c | mcdreforged/plugin/plugin_thread.py | python | PluginThread.run | (self) | [] | def run(self):
try:
while True:
try:
if self.task is not None:
task_data = self.task
self.task = None
else:
task_data = self.thread_pool.task_queue.get(timeout=0.01) # type: TaskData
except queue.Empty:
pass
else:
plugin = task_data.plugin # type: AbstractPlugin
with plugin.plugin_manager.with_plugin_context(plugin):
self.setName('{}@{}'.format(self, plugin.get_id()))
self.thread_pool.working_count += 1
try:
task_data.callback()
except:
self.thread_pool.mcdr_server.logger.exception('Exception in thread created by {}'.format(plugin))
finally:
self.thread_pool.working_count -= 1
self.setName(self.original_name)
finally:
if self.flag_interrupt:
break
finally:
with self.thread_pool.threads_write_lock:
self.thread_pool.threads.remove(self) | [
"def",
"run",
"(",
"self",
")",
":",
"try",
":",
"while",
"True",
":",
"try",
":",
"if",
"self",
".",
"task",
"is",
"not",
"None",
":",
"task_data",
"=",
"self",
".",
"task",
"self",
".",
"task",
"=",
"None",
"else",
":",
"task_data",
"=",
"self"... | https://github.com/Fallen-Breath/MCDReforged/blob/fdb1d2520b35f916123f265dbd94603981bb2b0c/mcdreforged/plugin/plugin_thread.py#L31-L59 | ||||
riptideio/pymodbus | c5772b35ae3f29d1947f3ab453d8d00df846459f | pymodbus/server/async_io.py | python | StartTlsServer | (context=None, identity=None, address=None,
sslctx=None,
certfile=None, keyfile=None,
allow_reuse_address=False,
allow_reuse_port=False,
custom_functions=[],
defer_start=True, **kwargs) | return server | A factory to start and run a tls modbus server
:param context: The ModbusServerContext datastore
:param identity: An optional identify structure
:param address: An optional (interface, port) to bind to.
:param sslctx: The SSLContext to use for TLS (default None and auto create)
:param certfile: The cert file path for TLS (used if sslctx is None)
:param keyfile: The key file path for TLS (used if sslctx is None)
:param allow_reuse_address: Whether the server will allow the reuse of an
address.
:param allow_reuse_port: Whether the server will allow the reuse of a port.
:param custom_functions: An optional list of custom function classes
supported by server instance.
:param defer_start: if set, a coroutine which can be started and stopped
will be returned. Otherwise, the server will be immediately spun
up without the ability to shut it off from within the asyncio loop
:param ignore_missing_slaves: True to not send errors on a request to a
missing slave
:return: an initialized but inactive server object coroutine | A factory to start and run a tls modbus server | [
"A",
"factory",
"to",
"start",
"and",
"run",
"a",
"tls",
"modbus",
"server"
] | async def StartTlsServer(context=None, identity=None, address=None,
sslctx=None,
certfile=None, keyfile=None,
allow_reuse_address=False,
allow_reuse_port=False,
custom_functions=[],
defer_start=True, **kwargs):
""" A factory to start and run a tls modbus server
:param context: The ModbusServerContext datastore
:param identity: An optional identify structure
:param address: An optional (interface, port) to bind to.
:param sslctx: The SSLContext to use for TLS (default None and auto create)
:param certfile: The cert file path for TLS (used if sslctx is None)
:param keyfile: The key file path for TLS (used if sslctx is None)
:param allow_reuse_address: Whether the server will allow the reuse of an
address.
:param allow_reuse_port: Whether the server will allow the reuse of a port.
:param custom_functions: An optional list of custom function classes
supported by server instance.
:param defer_start: if set, a coroutine which can be started and stopped
will be returned. Otherwise, the server will be immediately spun
up without the ability to shut it off from within the asyncio loop
:param ignore_missing_slaves: True to not send errors on a request to a
missing slave
:return: an initialized but inactive server object coroutine
"""
framer = kwargs.pop("framer", ModbusTlsFramer)
server = ModbusTlsServer(context, framer, identity, address, sslctx,
certfile, keyfile,
allow_reuse_address=allow_reuse_address,
allow_reuse_port=allow_reuse_port, **kwargs)
for f in custom_functions:
server.decoder.register(f) # pragma: no cover
if not defer_start:
await server.serve_forever()
return server | [
"async",
"def",
"StartTlsServer",
"(",
"context",
"=",
"None",
",",
"identity",
"=",
"None",
",",
"address",
"=",
"None",
",",
"sslctx",
"=",
"None",
",",
"certfile",
"=",
"None",
",",
"keyfile",
"=",
"None",
",",
"allow_reuse_address",
"=",
"False",
","... | https://github.com/riptideio/pymodbus/blob/c5772b35ae3f29d1947f3ab453d8d00df846459f/pymodbus/server/async_io.py#L851-L890 | |
lisa-lab/pylearn2 | af81e5c362f0df4df85c3e54e23b2adeec026055 | pylearn2/datasets/utlc.py | python | load_ndarray_dataset | (name, normalize=True, transfer=False,
normalize_on_the_fly=False, randomize_valid=False,
randomize_test=False) | Load the train,valid,test data for the dataset `name` and return it in
ndarray format.
We suppose the data was created with ift6266h11/pretraitement/to_npy.py
that shuffle the train. So the train should already be shuffled.
Parameters
----------
name : 'avicenna', 'harry', 'rita', 'sylvester' or 'ule'
Which dataset to load
normalize : bool
If True, we normalize the train dataset before returning it
transfer : bool
If True also return the transfer labels
normalize_on_the_fly : bool
If True, we return a Theano Variable that will give as output the
normalized value. If the user only take a subtensor of that variable,
Theano optimization should make that we will only have in memory the
subtensor portion that is computed in normalized form. We store the
original data in shared memory in its original dtype. This is usefull
to have the original data in its original dtype in memory to same
memory. Especialy usefull to be able to use rita and harry with 1G per
jobs.
randomize_valid : bool
Do we randomize the order of the valid set? We always use the same
random order If False, return in the same order as downloaded on the
web
randomize_test : bool
Do we randomize the order of the test set? We always use the same
random order If False, return in the same order as downloaded on the
web
Returns
-------
train, valid, test : ndarrays
Datasets returned if transfer = False
train, valid, test, transfer : ndarrays
Datasets returned if transfer = False | Load the train,valid,test data for the dataset `name` and return it in
ndarray format. | [
"Load",
"the",
"train",
"valid",
"test",
"data",
"for",
"the",
"dataset",
"name",
"and",
"return",
"it",
"in",
"ndarray",
"format",
"."
] | def load_ndarray_dataset(name, normalize=True, transfer=False,
normalize_on_the_fly=False, randomize_valid=False,
randomize_test=False):
"""
Load the train,valid,test data for the dataset `name` and return it in
ndarray format.
We suppose the data was created with ift6266h11/pretraitement/to_npy.py
that shuffle the train. So the train should already be shuffled.
Parameters
----------
name : 'avicenna', 'harry', 'rita', 'sylvester' or 'ule'
Which dataset to load
normalize : bool
If True, we normalize the train dataset before returning it
transfer : bool
If True also return the transfer labels
normalize_on_the_fly : bool
If True, we return a Theano Variable that will give as output the
normalized value. If the user only take a subtensor of that variable,
Theano optimization should make that we will only have in memory the
subtensor portion that is computed in normalized form. We store the
original data in shared memory in its original dtype. This is usefull
to have the original data in its original dtype in memory to same
memory. Especialy usefull to be able to use rita and harry with 1G per
jobs.
randomize_valid : bool
Do we randomize the order of the valid set? We always use the same
random order If False, return in the same order as downloaded on the
web
randomize_test : bool
Do we randomize the order of the test set? We always use the same
random order If False, return in the same order as downloaded on the
web
Returns
-------
train, valid, test : ndarrays
Datasets returned if transfer = False
train, valid, test, transfer : ndarrays
Datasets returned if transfer = False
"""
assert not (normalize and normalize_on_the_fly), \
"Can't normalize in 2 way at the same time!"
assert name in ['avicenna', 'harry', 'rita', 'sylvester', 'ule']
common = os.path.join(
preprocess('${PYLEARN2_DATA_PATH}'), 'UTLC', 'filetensor', name + '_')
trname, vname, tename = [
common + subset + '.ft' for subset in ['train', 'valid', 'test']]
train = load_filetensor(trname)
valid = load_filetensor(vname)
test = load_filetensor(tename)
if randomize_valid:
rng = make_np_rng(None, [1, 2, 3, 4], which_method='permutation')
perm = rng.permutation(valid.shape[0])
valid = valid[perm]
if randomize_test:
rng = make_np_rng(None, [1, 2, 3, 4], which_method='permutation')
perm = rng.permutation(test.shape[0])
test = test[perm]
if normalize or normalize_on_the_fly:
if normalize_on_the_fly:
# Shared variables of the original type
train = theano.shared(train, borrow=True, name=name + "_train")
valid = theano.shared(valid, borrow=True, name=name + "_valid")
test = theano.shared(test, borrow=True, name=name + "_test")
# Symbolic variables cast into floatX
train = theano.tensor.cast(train, theano.config.floatX)
valid = theano.tensor.cast(valid, theano.config.floatX)
test = theano.tensor.cast(test, theano.config.floatX)
else:
train = numpy.asarray(train, theano.config.floatX)
valid = numpy.asarray(valid, theano.config.floatX)
test = numpy.asarray(test, theano.config.floatX)
if name == "ule":
train /= 255
valid /= 255
test /= 255
elif name in ["avicenna", "sylvester"]:
if name == "avicenna":
train_mean = 514.62154022835455
train_std = 6.829096494224145
else:
train_mean = 403.81889927027686
train_std = 96.43841050784053
train -= train_mean
valid -= train_mean
test -= train_mean
train /= train_std
valid /= train_std
test /= train_std
elif name == "harry":
std = 0.69336046033925791 # train.std()slow to compute
train /= std
valid /= std
test /= std
elif name == "rita":
v = numpy.asarray(230, dtype=theano.config.floatX)
train /= v
valid /= v
test /= v
else:
raise Exception(
"This dataset don't have its normalization defined")
if transfer:
transfer = load_ndarray_transfer(name)
return train, valid, test, transfer
else:
return train, valid, test | [
"def",
"load_ndarray_dataset",
"(",
"name",
",",
"normalize",
"=",
"True",
",",
"transfer",
"=",
"False",
",",
"normalize_on_the_fly",
"=",
"False",
",",
"randomize_valid",
"=",
"False",
",",
"randomize_test",
"=",
"False",
")",
":",
"assert",
"not",
"(",
"n... | https://github.com/lisa-lab/pylearn2/blob/af81e5c362f0df4df85c3e54e23b2adeec026055/pylearn2/datasets/utlc.py#L21-L140 | ||
Ericsson/codechecker | c4e43f62dc3acbf71d3109b337db7c97f7852f43 | tools/report-converter/codechecker_report_converter/analyzers/spotbugs/analyzer_result.py | python | AnalyzerResult.__event_from_method | (self, element) | return BugPathEvent(
message,
get_or_create_file(source_path, self.__file_cache),
line,
col) | Creates event from a Method element. | Creates event from a Method element. | [
"Creates",
"event",
"from",
"a",
"Method",
"element",
"."
] | def __event_from_method(self, element) -> Optional[BugPathEvent]:
""" Creates event from a Method element. """
message = element.find('Message').text
source_line = element.find('SourceLine')
if source_line is None:
return None
source_path = source_line.attrib.get('sourcepath')
source_path = self.__get_abs_path(source_path)
if not source_path:
return None
line = int(source_line.attrib.get('start', 0))
col = 0
return BugPathEvent(
message,
get_or_create_file(source_path, self.__file_cache),
line,
col) | [
"def",
"__event_from_method",
"(",
"self",
",",
"element",
")",
"->",
"Optional",
"[",
"BugPathEvent",
"]",
":",
"message",
"=",
"element",
".",
"find",
"(",
"'Message'",
")",
".",
"text",
"source_line",
"=",
"element",
".",
"find",
"(",
"'SourceLine'",
")... | https://github.com/Ericsson/codechecker/blob/c4e43f62dc3acbf71d3109b337db7c97f7852f43/tools/report-converter/codechecker_report_converter/analyzers/spotbugs/analyzer_result.py#L168-L188 | |
0vercl0k/stuffz | 2ff82f4739d7e215c6140d4987efa8310db39d55 | transmissionrpc.py | python | Client.start | (self, ids, bypass_queue=False, timeout=None) | .. WARNING::
Deprecated, please use start_torrent. | [] | def start(self, ids, bypass_queue=False, timeout=None):
"""
.. WARNING::
Deprecated, please use start_torrent.
"""
warnings.warn('start has been deprecated, please use start_torrent instead.', DeprecationWarning)
self.start_torrent(ids, bypass_queue, timeout) | [
"def",
"start",
"(",
"self",
",",
"ids",
",",
"bypass_queue",
"=",
"False",
",",
"timeout",
"=",
"None",
")",
":",
"warnings",
".",
"warn",
"(",
"'start has been deprecated, please use start_torrent instead.'",
",",
"DeprecationWarning",
")",
"self",
".",
"start_t... | https://github.com/0vercl0k/stuffz/blob/2ff82f4739d7e215c6140d4987efa8310db39d55/transmissionrpc.py#L1676-L1683 | |||
exaile/exaile | a7b58996c5c15b3aa7b9975ac13ee8f784ef4689 | xlgui/widgets/playlist.py | python | PlaylistModel._compute_row_params | (self, rowidx) | return pixbuf, sensitive, weight | :returns: pixbuf, sensitive, weight | :returns: pixbuf, sensitive, weight | [
":",
"returns",
":",
"pixbuf",
"sensitive",
"weight"
] | def _compute_row_params(self, rowidx):
"""
:returns: pixbuf, sensitive, weight
"""
pixbuf = self.clear_pixbuf.pixbuf
weight = Pango.Weight.NORMAL
sensitive = True
playlist = self.playlist
spatpos = playlist.spat_position
spat = spatpos == rowidx
if spat:
pixbuf = self.stop_pixbuf.pixbuf
if playlist is self.player.queue.current_playlist:
if (
playlist.current_position == rowidx
and playlist[rowidx] == self.player.current
):
# this row is the current track, set a special icon
state = self.player.get_state()
weight = Pango.Weight.HEAVY
if state == 'playing':
if spat:
pixbuf = self.play_stop_pixbuf.pixbuf
else:
pixbuf = self.play_pixbuf.pixbuf
elif state == 'paused':
if spat:
pixbuf = self.pause_stop_pixbuf.pixbuf
else:
pixbuf = self.pause_pixbuf.pixbuf
if spatpos == -1 or spatpos > rowidx:
sensitive = True
else:
sensitive = False
return pixbuf, sensitive, weight | [
"def",
"_compute_row_params",
"(",
"self",
",",
"rowidx",
")",
":",
"pixbuf",
"=",
"self",
".",
"clear_pixbuf",
".",
"pixbuf",
"weight",
"=",
"Pango",
".",
"Weight",
".",
"NORMAL",
"sensitive",
"=",
"True",
"playlist",
"=",
"self",
".",
"playlist",
"spatpo... | https://github.com/exaile/exaile/blob/a7b58996c5c15b3aa7b9975ac13ee8f784ef4689/xlgui/widgets/playlist.py#L1934-L1979 | |
jiangxinyang227/NLP-Project | b11f67d8962f40e17990b4fc4551b0ea5496881c | multi_label_classifier/data_helpers/train_data.py | python | TrainData.gen_vocab | (self, words, labels) | return word_to_index, label_to_index | 生成词汇，标签等映射表
:param words: 训练集所含有的单词
:param labels: 标签
:return: | 生成词汇，标签等映射表
:param words: 训练集所含有的单词
:param labels: 标签
:return: | [
"生成词汇，标签等映射表",
":",
"param",
"words",
":",
"训练集所含有的单词",
":",
"param",
"labels",
":",
"标签",
":",
"return",
":"
] | def gen_vocab(self, words, labels):
"""
生成词汇，标签等映射表
:param words: 训练集所含有的单词
:param labels: 标签
:return:
"""
# 如果不是第一次处理，则可以直接加载生成好的词汇表和词向量
if os.path.exists(os.path.join(self._output_path, "word_vectors.npy")):
print("load word_vectors")
self.word_vectors = np.load(os.path.join(self._output_path, "word_vectors.npy"))
if os.path.exists(os.path.join(self._output_path, "word_to_index.pkl")) and \
os.path.exists(os.path.join(self._output_path, "label_to_index.pkl")):
print("load word_to_index")
with open(os.path.join(self._output_path, "word_to_index.pkl"), "rb") as f:
word_to_index = pickle.load(f)
with open(os.path.join(self._output_path, "label_to_index.pkl"), "rb") as f:
label_to_index = pickle.load(f)
self.vocab_size = len(word_to_index)
return word_to_index, label_to_index
words = ["<PAD>", "<UNK>"] + words
vocab = words[:self.vocab_size]
# 若vocab的长读小于设置的vocab_size，则选择vocab的长度作为真实的vocab_size
self.vocab_size = len(vocab)
if self._word_vectors_path:
word_vectors = self.get_word_vectors(vocab)
self.word_vectors = word_vectors
# 将本项目的词向量保存起来
np.save(os.path.join(self._output_path, "word_vectors.npy"), self.word_vectors)
word_to_index = dict(zip(vocab, list(range(len(vocab)))))
# 将词汇-索引映射表保存为pkl数据，之后做inference时直接加载来处理数据
with open(os.path.join(self._output_path, "word_to_index.pkl"), "wb") as f:
pickle.dump(word_to_index, f)
# 将标签-索引映射表保存为pkl数据
unique_labels = list(set(chain(*labels)))
label_to_index = dict(zip(unique_labels, list(range(len(unique_labels)))))
with open(os.path.join(self._output_path, "label_to_index.pkl"), "wb") as f:
pickle.dump(label_to_index, f)
return word_to_index, label_to_index | [
"def",
"gen_vocab",
"(",
"self",
",",
"words",
",",
"labels",
")",
":",
"# 如果不是第一次处理，则可以直接加载生成好的词汇表和词向量",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"self",
".",
"_output_path",
",",
"\"word_vectors.npy\"",
")",
")",
... | https://github.com/jiangxinyang227/NLP-Project/blob/b11f67d8962f40e17990b4fc4551b0ea5496881c/multi_label_classifier/data_helpers/train_data.py#L94-L143 | |
DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | linkerd/datadog_checks/linkerd/config_models/defaults.py | python | instance_metrics | (field, value) | return get_default_field_value(field, value) | [] | def instance_metrics(field, value):
return get_default_field_value(field, value) | [
"def",
"instance_metrics",
"(",
"field",
",",
"value",
")",
":",
"return",
"get_default_field_value",
"(",
"field",
",",
"value",
")"
] | https://github.com/DataDog/integrations-core/blob/934674b29d94b70ccc008f76ea172d0cdae05e1e/linkerd/datadog_checks/linkerd/config_models/defaults.py#L193-L194 | |||
PaddlePaddle/Research | 2da0bd6c72d60e9df403aff23a7802779561c4a1 | NLP/ACL2019-KTNET/reading_comprehension/src/model/bert.py | python | BertModel.get_pooled_output | (self) | return next_sent_feat | Get the first feature of each sequence for classification | Get the first feature of each sequence for classification | [
"Get",
"the",
"first",
"feature",
"of",
"each",
"sequence",
"for",
"classification"
] | def get_pooled_output(self):
"""Get the first feature of each sequence for classification"""
next_sent_feat = fluid.layers.slice(
input=self._enc_out, axes=[1], starts=[0], ends=[1])
next_sent_feat = fluid.layers.fc(
input=next_sent_feat,
size=self._emb_size,
act="tanh",
param_attr=fluid.ParamAttr(
name="pooled_fc.w_0", initializer=self._param_initializer),
bias_attr="pooled_fc.b_0")
return next_sent_feat | [
"def",
"get_pooled_output",
"(",
"self",
")",
":",
"next_sent_feat",
"=",
"fluid",
".",
"layers",
".",
"slice",
"(",
"input",
"=",
"self",
".",
"_enc_out",
",",
"axes",
"=",
"[",
"1",
"]",
",",
"starts",
"=",
"[",
"0",
"]",
",",
"ends",
"=",
"[",
... | https://github.com/PaddlePaddle/Research/blob/2da0bd6c72d60e9df403aff23a7802779561c4a1/NLP/ACL2019-KTNET/reading_comprehension/src/model/bert.py#L151-L163 | |
oracle/oci-python-sdk | 3c1604e4e212008fb6718e2f68cdb5ef71fd5793 | src/oci/core/virtual_network_client_composite_operations.py | python | VirtualNetworkClientCompositeOperations.delete_local_peering_gateway_and_wait_for_state | (self, local_peering_gateway_id, wait_for_states=[], operation_kwargs={}, waiter_kwargs={}) | Calls :py:func:`~oci.core.VirtualNetworkClient.delete_local_peering_gateway` and waits for the :py:class:`~oci.core.models.LocalPeeringGateway` acted upon
to enter the given state(s).
:param str local_peering_gateway_id: (required)
The `OCID`__ of the local peering gateway.
__ https://docs.cloud.oracle.com/Content/General/Concepts/identifiers.htm
:param list[str] wait_for_states:
An array of states to wait on. These should be valid values for :py:attr:`~oci.core.models.LocalPeeringGateway.lifecycle_state`
:param dict operation_kwargs:
A dictionary of keyword arguments to pass to :py:func:`~oci.core.VirtualNetworkClient.delete_local_peering_gateway`
:param dict waiter_kwargs:
A dictionary of keyword arguments to pass to the :py:func:`oci.wait_until` function. For example, you could pass ``max_interval_seconds`` or ``max_interval_seconds``
as dictionary keys to modify how long the waiter function will wait between retries and the maximum amount of time it will wait | Calls :py:func:`~oci.core.VirtualNetworkClient.delete_local_peering_gateway` and waits for the :py:class:`~oci.core.models.LocalPeeringGateway` acted upon
to enter the given state(s). | [
"Calls",
":",
"py",
":",
"func",
":",
"~oci",
".",
"core",
".",
"VirtualNetworkClient",
".",
"delete_local_peering_gateway",
"and",
"waits",
"for",
"the",
":",
"py",
":",
"class",
":",
"~oci",
".",
"core",
".",
"models",
".",
"LocalPeeringGateway",
"acted",
... | def delete_local_peering_gateway_and_wait_for_state(self, local_peering_gateway_id, wait_for_states=[], operation_kwargs={}, waiter_kwargs={}):
"""
Calls :py:func:`~oci.core.VirtualNetworkClient.delete_local_peering_gateway` and waits for the :py:class:`~oci.core.models.LocalPeeringGateway` acted upon
to enter the given state(s).
:param str local_peering_gateway_id: (required)
The `OCID`__ of the local peering gateway.
__ https://docs.cloud.oracle.com/Content/General/Concepts/identifiers.htm
:param list[str] wait_for_states:
An array of states to wait on. These should be valid values for :py:attr:`~oci.core.models.LocalPeeringGateway.lifecycle_state`
:param dict operation_kwargs:
A dictionary of keyword arguments to pass to :py:func:`~oci.core.VirtualNetworkClient.delete_local_peering_gateway`
:param dict waiter_kwargs:
A dictionary of keyword arguments to pass to the :py:func:`oci.wait_until` function. For example, you could pass ``max_interval_seconds`` or ``max_interval_seconds``
as dictionary keys to modify how long the waiter function will wait between retries and the maximum amount of time it will wait
"""
initial_get_result = self.client.get_local_peering_gateway(local_peering_gateway_id)
operation_result = None
try:
operation_result = self.client.delete_local_peering_gateway(local_peering_gateway_id, **operation_kwargs)
except oci.exceptions.ServiceError as e:
if e.status == 404:
return WAIT_RESOURCE_NOT_FOUND
else:
raise e
if not wait_for_states:
return operation_result
lowered_wait_for_states = [w.lower() for w in wait_for_states]
try:
waiter_result = oci.wait_until(
self.client,
initial_get_result,
evaluate_response=lambda r: getattr(r.data, 'lifecycle_state') and getattr(r.data, 'lifecycle_state').lower() in lowered_wait_for_states,
succeed_on_not_found=True,
**waiter_kwargs
)
result_to_return = waiter_result
return result_to_return
except Exception as e:
raise oci.exceptions.CompositeOperationError(partial_results=[operation_result], cause=e) | [
"def",
"delete_local_peering_gateway_and_wait_for_state",
"(",
"self",
",",
"local_peering_gateway_id",
",",
"wait_for_states",
"=",
"[",
"]",
",",
"operation_kwargs",
"=",
"{",
"}",
",",
"waiter_kwargs",
"=",
"{",
"}",
")",
":",
"initial_get_result",
"=",
"self",
... | https://github.com/oracle/oci-python-sdk/blob/3c1604e4e212008fb6718e2f68cdb5ef71fd5793/src/oci/core/virtual_network_client_composite_operations.py#L1792-L1839 | ||
mpatacchiola/dissecting-reinforcement-learning | 38660b0a0d5aed077a46acb4bcb2013565304d9c | src/5/genetic_algorithm_policy_estimation.py | python | return_mutated_population | (population, gene_set, mutation_rate, elite=0) | return population | Returns a mutated population
It applies the point-mutation mechanism to each value
contained in the chromosomes.
@param population numpy array containing the chromosomes
@param gene_set a numpy array with the value to pick
@parma mutation_rate a float repesenting the probaiblity
of mutation for each gene (e.g. 0.02=2%)
@return the mutated population | Returns a mutated population | [
"Returns",
"a",
"mutated",
"population"
] | def return_mutated_population(population, gene_set, mutation_rate, elite=0):
'''Returns a mutated population
It applies the point-mutation mechanism to each value
contained in the chromosomes.
@param population numpy array containing the chromosomes
@param gene_set a numpy array with the value to pick
@parma mutation_rate a float repesenting the probaiblity
of mutation for each gene (e.g. 0.02=2%)
@return the mutated population
'''
for x in np.nditer(population[elite:,:], op_flags=['readwrite']):
if(np.random.uniform(0,1) < mutation_rate):
x[...] = np.random.choice(gene_set, 1)
return population | [
"def",
"return_mutated_population",
"(",
"population",
",",
"gene_set",
",",
"mutation_rate",
",",
"elite",
"=",
"0",
")",
":",
"for",
"x",
"in",
"np",
".",
"nditer",
"(",
"population",
"[",
"elite",
":",
",",
":",
"]",
",",
"op_flags",
"=",
"[",
"'rea... | https://github.com/mpatacchiola/dissecting-reinforcement-learning/blob/38660b0a0d5aed077a46acb4bcb2013565304d9c/src/5/genetic_algorithm_policy_estimation.py#L74-L88 | |
kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python3-alpha/python-libs/gdata/apps/emailsettings/data.py | python | EmailSettingsVacationResponder.GetSubject | (self) | return self._GetProperty(VACATION_RESPONDER_SUBJECT) | Get the Subject value of the Vacation Responder object.
Returns:
The Subject value of this Vacation Responder object as a string or None. | Get the Subject value of the Vacation Responder object. | [
"Get",
"the",
"Subject",
"value",
"of",
"the",
"Vacation",
"Responder",
"object",
"."
] | def GetSubject(self):
"""Get the Subject value of the Vacation Responder object.
Returns:
The Subject value of this Vacation Responder object as a string or None.
"""
return self._GetProperty(VACATION_RESPONDER_SUBJECT) | [
"def",
"GetSubject",
"(",
"self",
")",
":",
"return",
"self",
".",
"_GetProperty",
"(",
"VACATION_RESPONDER_SUBJECT",
")"
] | https://github.com/kuri65536/python-for-android/blob/26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891/python3-alpha/python-libs/gdata/apps/emailsettings/data.py#L837-L844 | |
filerock/FileRock-Client | 37214f701666e76e723595f8f9ed238a42f6eb06 | filerockclient/osconfig/PlatformSettingsOSX.py | python | PlatformSettingsOSX._get_launch_agent_content | (self, enable) | return doc.toxml(encoding='utf-8') | Returns XML content of launch agent plist file | Returns XML content of launch agent plist file | [
"Returns",
"XML",
"content",
"of",
"launch",
"agent",
"plist",
"file"
] | def _get_launch_agent_content(self, enable):
"""
Returns XML content of launch agent plist file
"""
imp = getDOMImplementation()
doctype = imp.createDocumentType("plist", "-//Apple//DTD PLIST 1.0//EN", "http://www.apple.com/DTDs/PropertyList-1.0.dtd")
doc = imp.createDocument(None,"plist",doctype)
doc.documentElement.setAttribute("version","1.0")
dict_elem = doc.createElement("dict")
label_key_elem = doc.createElement("key")
label_key_elem.appendChild(doc.createTextNode("Label"))
label_string_elem = doc.createElement("string")
label_string_elem.appendChild(doc.createTextNode(self.LAUNCH_AGENT_BUNDLE_ID))
prog_args_key_elem = doc.createElement("key")
prog_args_key_elem.appendChild(doc.createTextNode("ProgramArguments"))
args_array_elem = doc.createElement("array")
for argument in self._filter_cmd_line_args(self.cmdline_args):
arg_string_elem = doc.createElement("string")
arg_string_elem.appendChild(doc.createTextNode(argument))
args_array_elem.appendChild(arg_string_elem)
run_at_load_key = doc.createElement("key")
run_at_load_key.appendChild(doc.createTextNode("RunAtLoad"))
run_at_load_true = doc.createElement(str(enable).lower())
dict_elem.appendChild(label_key_elem)
dict_elem.appendChild(label_string_elem)
dict_elem.appendChild(prog_args_key_elem)
dict_elem.appendChild(args_array_elem)
dict_elem.appendChild(run_at_load_key)
dict_elem.appendChild(run_at_load_true)
doc.documentElement.appendChild(dict_elem)
return doc.toxml(encoding='utf-8') | [
"def",
"_get_launch_agent_content",
"(",
"self",
",",
"enable",
")",
":",
"imp",
"=",
"getDOMImplementation",
"(",
")",
"doctype",
"=",
"imp",
".",
"createDocumentType",
"(",
"\"plist\"",
",",
"\"-//Apple//DTD PLIST 1.0//EN\"",
",",
"\"http://www.apple.com/DTDs/Property... | https://github.com/filerock/FileRock-Client/blob/37214f701666e76e723595f8f9ed238a42f6eb06/filerockclient/osconfig/PlatformSettingsOSX.py#L91-L136 | |
CoinAlpha/hummingbot | 36f6149c1644c07cd36795b915f38b8f49b798e7 | hummingbot/connector/exchange/ndax/ndax_exchange.py | python | NdaxExchange._api_request | (self,
method: str,
path_url: str,
params: Optional[Dict[str, Any]] = None,
data: Optional[Dict[str, Any]] = None,
is_auth_required: bool = False,
limit_id: Optional[str] = None) | return parsed_response | Sends an aiohttp request and waits for a response.
:param method: The HTTP method, e.g. get or post
:param path_url: The path url or the API end point
:param params: The query parameters of the API request
:param params: The body parameters of the API request
:param is_auth_required: Whether an authentication is required, when True the function will add encrypted
signature to the request.
:param limit_id: The id used for the API throttler. If not supplied, the `path_url` is used instead.
:returns A response in json format. | Sends an aiohttp request and waits for a response.
:param method: The HTTP method, e.g. get or post
:param path_url: The path url or the API end point
:param params: The query parameters of the API request
:param params: The body parameters of the API request
:param is_auth_required: Whether an authentication is required, when True the function will add encrypted
signature to the request.
:param limit_id: The id used for the API throttler. If not supplied, the `path_url` is used instead.
:returns A response in json format. | [
"Sends",
"an",
"aiohttp",
"request",
"and",
"waits",
"for",
"a",
"response",
".",
":",
"param",
"method",
":",
"The",
"HTTP",
"method",
"e",
".",
"g",
".",
"get",
"or",
"post",
":",
"param",
"path_url",
":",
"The",
"path",
"url",
"or",
"the",
"API",
... | async def _api_request(self,
method: str,
path_url: str,
params: Optional[Dict[str, Any]] = None,
data: Optional[Dict[str, Any]] = None,
is_auth_required: bool = False,
limit_id: Optional[str] = None) -> Union[Dict[str, Any], List[Any]]:
"""
Sends an aiohttp request and waits for a response.
:param method: The HTTP method, e.g. get or post
:param path_url: The path url or the API end point
:param params: The query parameters of the API request
:param params: The body parameters of the API request
:param is_auth_required: Whether an authentication is required, when True the function will add encrypted
signature to the request.
:param limit_id: The id used for the API throttler. If not supplied, the `path_url` is used instead.
:returns A response in json format.
"""
url = ndax_utils.rest_api_url(self._domain) + path_url
try:
if is_auth_required:
headers = self._auth.get_auth_headers()
else:
headers = self._auth.get_headers()
limit_id = limit_id or path_url
if method == "GET":
async with self._throttler.execute_task(limit_id):
response = await self._shared_client.get(url, headers=headers, params=params)
elif method == "POST":
async with self._throttler.execute_task(limit_id):
response = await self._shared_client.post(url, headers=headers, data=ujson.dumps(data))
else:
raise NotImplementedError(f"{method} HTTP Method not implemented. ")
data = await response.text()
if data == CONSTANTS.API_LIMIT_REACHED_ERROR_MESSAGE:
raise Exception(f"The exchange API request limit has been reached (original error '{data}')")
parsed_response = await response.json()
except ValueError as e:
self.logger().error(f"{str(e)}")
raise ValueError(f"Error authenticating request {method} {url}. Error: {str(e)}")
except Exception as e:
raise IOError(f"Error parsing data from {url}. Error: {str(e)}")
if response.status != 200 or (isinstance(parsed_response, dict) and not parsed_response.get("result", True)):
self.logger().error(f"Error fetching data from {url}. HTTP status is {response.status}. "
f"Message: {parsed_response} "
f"Params: {params} "
f"Data: {data}")
raise Exception(f"Error fetching data from {url}. HTTP status is {response.status}. "
f"Message: {parsed_response} "
f"Params: {params} "
f"Data: {data}")
return parsed_response | [
"async",
"def",
"_api_request",
"(",
"self",
",",
"method",
":",
"str",
",",
"path_url",
":",
"str",
",",
"params",
":",
"Optional",
"[",
"Dict",
"[",
"str",
",",
"Any",
"]",
"]",
"=",
"None",
",",
"data",
":",
"Optional",
"[",
"Dict",
"[",
"str",
... | https://github.com/CoinAlpha/hummingbot/blob/36f6149c1644c07cd36795b915f38b8f49b798e7/hummingbot/connector/exchange/ndax/ndax_exchange.py#L299-L356 | |
syang1993/gst-tacotron | f28635c539d6a3a9ceece7be2acf8aa2fe3477b0 | models/gmm_attention_wrapper.py | python | GMMAttentionWrapper._get_params | (self, cell_out, prev_kappa) | return alpha, beta, kappa | Compute window parameters
In GMM-based attention, the location parameters kappa are defined
as offsets from the previous locations, and that the size of the
offset is constrained to be greater than zero. Then we get:
alpha: the importance of the window within the mixture.
beta: the width of the window.
kappa: the location of the window. | Compute window parameters
In GMM-based attention, the location parameters kappa are defined
as offsets from the previous locations, and that the size of the
offset is constrained to be greater than zero. Then we get: | [
"Compute",
"window",
"parameters",
"In",
"GMM",
"-",
"based",
"attention",
"the",
"location",
"parameters",
"kappa",
"are",
"defined",
"as",
"offsets",
"from",
"the",
"previous",
"locations",
"and",
"that",
"the",
"size",
"of",
"the",
"offset",
"is",
"constrai... | def _get_params(self, cell_out, prev_kappa):
"""Compute window parameters
In GMM-based attention, the location parameters kappa are defined
as offsets from the previous locations, and that the size of the
offset is constrained to be greater than zero. Then we get:
alpha: the importance of the window within the mixture.
beta: the width of the window.
kappa: the location of the window.
"""
window_params = tf.layers.dense(cell_out, units=3*self._num_attn_mixture)
alpha, beta, kappa = tf.split(tf.exp(window_params), 3, axis=1)
kappa = kappa + prev_kappa
return alpha, beta, kappa | [
"def",
"_get_params",
"(",
"self",
",",
"cell_out",
",",
"prev_kappa",
")",
":",
"window_params",
"=",
"tf",
".",
"layers",
".",
"dense",
"(",
"cell_out",
",",
"units",
"=",
"3",
"*",
"self",
".",
"_num_attn_mixture",
")",
"alpha",
",",
"beta",
",",
"k... | https://github.com/syang1993/gst-tacotron/blob/f28635c539d6a3a9ceece7be2acf8aa2fe3477b0/models/gmm_attention_wrapper.py#L71-L85 | |
openstack/tempest | fe0ac89a5a1c43fa908a76759cd99eea3b1f9853 | tempest/lib/services/compute/servers_client.py | python | ServersClient.create_server | (self, **kwargs) | return rest_client.ResponseBody(resp, body) | Create server.
For a full list of available parameters, please refer to the official
API reference:
https://docs.openstack.org/api-ref/compute/#create-server
:param name: Server name
:param imageRef: Image reference (UUID)
:param flavorRef: Flavor reference (UUID or full URL)
Most parameters except the following are passed to the API without
any changes.
:param disk_config: The name is changed to OS-DCF:diskConfig
:param scheduler_hints: The name is changed to os:scheduler_hints and
the parameter is set in the same level as the parameter 'server'. | Create server. | [
"Create",
"server",
"."
] | def create_server(self, **kwargs):
"""Create server.
For a full list of available parameters, please refer to the official
API reference:
https://docs.openstack.org/api-ref/compute/#create-server
:param name: Server name
:param imageRef: Image reference (UUID)
:param flavorRef: Flavor reference (UUID or full URL)
Most parameters except the following are passed to the API without
any changes.
:param disk_config: The name is changed to OS-DCF:diskConfig
:param scheduler_hints: The name is changed to os:scheduler_hints and
the parameter is set in the same level as the parameter 'server'.
"""
body = copy.deepcopy(kwargs)
if body.get('disk_config'):
body['OS-DCF:diskConfig'] = body.pop('disk_config')
hints = None
if body.get('scheduler_hints'):
hints = {'os:scheduler_hints': body.pop('scheduler_hints')}
post_body = {'server': body}
if hints:
post_body.update(hints)
post_body = json.dumps(post_body)
resp, body = self.post('servers', post_body)
body = json.loads(body)
# NOTE(maurosr): this deals with the case of multiple server create
# with return reservation id set True
if 'reservation_id' in body:
return rest_client.ResponseBody(resp, body)
if self.enable_instance_password:
create_schema = schema.create_server_with_admin_pass
else:
create_schema = schema.create_server
self.validate_response(create_schema, resp, body)
return rest_client.ResponseBody(resp, body) | [
"def",
"create_server",
"(",
"self",
",",
"*",
"*",
"kwargs",
")",
":",
"body",
"=",
"copy",
".",
"deepcopy",
"(",
"kwargs",
")",
"if",
"body",
".",
"get",
"(",
"'disk_config'",
")",
":",
"body",
"[",
"'OS-DCF:diskConfig'",
"]",
"=",
"body",
".",
"po... | https://github.com/openstack/tempest/blob/fe0ac89a5a1c43fa908a76759cd99eea3b1f9853/tempest/lib/services/compute/servers_client.py#L80-L123 | |
numba/numba | bf480b9e0da858a65508c2b17759a72ee6a44c51 | numba/core/boxing.py | python | unbox_pyobject | (typ, obj, c) | return NativeValue(obj) | [] | def unbox_pyobject(typ, obj, c):
return NativeValue(obj) | [
"def",
"unbox_pyobject",
"(",
"typ",
",",
"obj",
",",
"c",
")",
":",
"return",
"NativeValue",
"(",
"obj",
")"
] | https://github.com/numba/numba/blob/bf480b9e0da858a65508c2b17759a72ee6a44c51/numba/core/boxing.py#L1009-L1010 | |||
CLUEbenchmark/CLUE | 5bd39732734afecb490cf18a5212e692dbf2c007 | baselines/models/albert/modeling.py | python | gelu | (x) | return x * cdf | Gaussian Error Linear Unit.
This is a smoother version of the RELU.
Original paper: https://arxiv.org/abs/1606.08415
Args:
x: float Tensor to perform activation.
Returns:
`x` with the GELU activation applied. | Gaussian Error Linear Unit. | [
"Gaussian",
"Error",
"Linear",
"Unit",
"."
] | def gelu(x):
"""Gaussian Error Linear Unit.
This is a smoother version of the RELU.
Original paper: https://arxiv.org/abs/1606.08415
Args:
x: float Tensor to perform activation.
Returns:
`x` with the GELU activation applied.
"""
cdf = 0.5 * (1.0 + tf.tanh(
(np.sqrt(2 / np.pi) * (x + 0.044715 * tf.pow(x, 3)))))
return x * cdf | [
"def",
"gelu",
"(",
"x",
")",
":",
"cdf",
"=",
"0.5",
"*",
"(",
"1.0",
"+",
"tf",
".",
"tanh",
"(",
"(",
"np",
".",
"sqrt",
"(",
"2",
"/",
"np",
".",
"pi",
")",
"*",
"(",
"x",
"+",
"0.044715",
"*",
"tf",
".",
"pow",
"(",
"x",
",",
"3",
... | https://github.com/CLUEbenchmark/CLUE/blob/5bd39732734afecb490cf18a5212e692dbf2c007/baselines/models/albert/modeling.py#L286-L299 | |
TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/zj/v20190121/models.py | python | DescribeSmsSignListRequest.__init__ | (self) | r"""
:param License: 商户证书
:type License: str
:param SignIdSet: 签名ID数组
:type SignIdSet: list of int non-negative
:param International: 是否国际/港澳台短信：
0：表示国内短信。
1：表示国际/港澳台短信。
:type International: int | r"""
:param License: 商户证书
:type License: str
:param SignIdSet: 签名ID数组
:type SignIdSet: list of int non-negative
:param International: 是否国际/港澳台短信：
0：表示国内短信。
1：表示国际/港澳台短信。
:type International: int | [
"r",
":",
"param",
"License",
":",
"商户证书",
":",
"type",
"License",
":",
"str",
":",
"param",
"SignIdSet",
":",
"签名ID数组",
":",
"type",
"SignIdSet",
":",
"list",
"of",
"int",
"non",
"-",
"negative",
":",
"param",
"International",
":",
"是否国际",
"/",
"港澳台短信... | def __init__(self):
r"""
:param License: 商户证书
:type License: str
:param SignIdSet: 签名ID数组
:type SignIdSet: list of int non-negative
:param International: 是否国际/港澳台短信：
0：表示国内短信。
1：表示国际/港澳台短信。
:type International: int
"""
self.License = None
self.SignIdSet = None
self.International = None | [
"def",
"__init__",
"(",
"self",
")",
":",
"self",
".",
"License",
"=",
"None",
"self",
".",
"SignIdSet",
"=",
"None",
"self",
".",
"International",
"=",
"None"
] | https://github.com/TencentCloud/tencentcloud-sdk-python/blob/3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2/tencentcloud/zj/v20190121/models.py#L975-L988 | ||
stoq/stoq | c26991644d1affcf96bc2e0a0434796cabdf8448 | stoqlib/domain/workorder.py | python | WorkOrderPackageItem.send | (self, user: LoginUser) | Send the item to the :attr:`WorkOrderPackage.destination_branch`
This will mark the package as sent. Note that it's only possible
to call this on the same branch as :attr:`.source_branch`.
When calling this, the work orders' :attr:`WorkOrder.current_branch`
will be ``None``, since they are on a package and not on any branch. | Send the item to the :attr:`WorkOrderPackage.destination_branch` | [
"Send",
"the",
"item",
"to",
"the",
":",
"attr",
":",
"WorkOrderPackage",
".",
"destination_branch"
] | def send(self, user: LoginUser):
"""Send the item to the :attr:`WorkOrderPackage.destination_branch`
This will mark the package as sent. Note that it's only possible
to call this on the same branch as :attr:`.source_branch`.
When calling this, the work orders' :attr:`WorkOrder.current_branch`
will be ``None``, since they are on a package and not on any branch.
"""
if self.package.destination_branch != self.order.branch:
old_execution_branch = self.order.execution_branch
self.order.execution_branch = self.package.destination_branch
WorkOrderHistory.add_entry(
self.store, self.order, _(u"Execution branch"), user=user,
old_value=(old_execution_branch and
old_execution_branch.get_description()),
new_value=self.package.destination_branch.get_description()) | [
"def",
"send",
"(",
"self",
",",
"user",
":",
"LoginUser",
")",
":",
"if",
"self",
".",
"package",
".",
"destination_branch",
"!=",
"self",
".",
"order",
".",
"branch",
":",
"old_execution_branch",
"=",
"self",
".",
"order",
".",
"execution_branch",
"self"... | https://github.com/stoq/stoq/blob/c26991644d1affcf96bc2e0a0434796cabdf8448/stoqlib/domain/workorder.py#L103-L119 | ||
jupyter/nbformat | dee3e4f0e97084009f8a8abc34104ad45b9b9896 | nbformat/_struct.py | python | Struct.__isub__ | (self, other) | return self | Inplace remove keys from self that are in other.
Examples
--------
>>> s1 = Struct(a=10,b=30)
>>> s2 = Struct(a=40)
>>> s1 -= s2
>>> s1
{'b': 30} | Inplace remove keys from self that are in other. | [
"Inplace",
"remove",
"keys",
"from",
"self",
"that",
"are",
"in",
"other",
"."
] | def __isub__(self, other):
"""Inplace remove keys from self that are in other.
Examples
--------
>>> s1 = Struct(a=10,b=30)
>>> s2 = Struct(a=40)
>>> s1 -= s2
>>> s1
{'b': 30}
"""
for k in other.keys():
if k in self:
del self[k]
return self | [
"def",
"__isub__",
"(",
"self",
",",
"other",
")",
":",
"for",
"k",
"in",
"other",
".",
"keys",
"(",
")",
":",
"if",
"k",
"in",
"self",
":",
"del",
"self",
"[",
"k",
"]",
"return",
"self"
] | https://github.com/jupyter/nbformat/blob/dee3e4f0e97084009f8a8abc34104ad45b9b9896/nbformat/_struct.py#L189-L204 | |
IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/pickle.py | python | _Unpickler.load_long4 | (self) | [] | def load_long4(self):
n, = unpack('<i', self.read(4))
if n < 0:
# Corrupt or hostile pickle -- we never write one like this
raise UnpicklingError("LONG pickle has negative byte count")
data = self.read(n)
self.append(decode_long(data)) | [
"def",
"load_long4",
"(",
"self",
")",
":",
"n",
",",
"=",
"unpack",
"(",
"'<i'",
",",
"self",
".",
"read",
"(",
"4",
")",
")",
"if",
"n",
"<",
"0",
":",
"# Corrupt or hostile pickle -- we never write one like this",
"raise",
"UnpicklingError",
"(",
"\"LONG ... | https://github.com/IronLanguages/ironpython3/blob/7a7bb2a872eeab0d1009fc8a6e24dca43f65b693/Src/StdLib/Lib/pickle.py#L1135-L1141 | ||||
mongodb/mongo-python-driver | c760f900f2e4109a247c2ffc8ad3549362007772 | gridfs/grid_file.py | python | GridOut.__exit__ | (self, exc_type, exc_val, exc_tb) | return False | Makes it possible to use :class:`GridOut` files
with the context manager protocol. | Makes it possible to use :class:`GridOut` files
with the context manager protocol. | [
"Makes",
"it",
"possible",
"to",
"use",
":",
"class",
":",
"GridOut",
"files",
"with",
"the",
"context",
"manager",
"protocol",
"."
] | def __exit__(self, exc_type, exc_val, exc_tb):
"""Makes it possible to use :class:`GridOut` files
with the context manager protocol.
"""
self.close()
return False | [
"def",
"__exit__",
"(",
"self",
",",
"exc_type",
",",
"exc_val",
",",
"exc_tb",
")",
":",
"self",
".",
"close",
"(",
")",
"return",
"False"
] | https://github.com/mongodb/mongo-python-driver/blob/c760f900f2e4109a247c2ffc8ad3549362007772/gridfs/grid_file.py#L694-L699 | |
meduza-corp/interstellar | 40a801ccd7856491726f5a126621d9318cabe2e1 | gsutil/third_party/httplib2/python2/httplib2/__init__.py | python | safename | (filename) | return ",".join((filename, filemd5)) | Return a filename suitable for the cache.
Strips dangerous and common characters to create a filename we
can use to store the cache in. | Return a filename suitable for the cache. | [
"Return",
"a",
"filename",
"suitable",
"for",
"the",
"cache",
"."
] | def safename(filename):
"""Return a filename suitable for the cache.
Strips dangerous and common characters to create a filename we
can use to store the cache in.
"""
try:
if re_url_scheme.match(filename):
if isinstance(filename,str):
filename = filename.decode('utf-8')
filename = filename.encode('idna')
else:
filename = filename.encode('idna')
except UnicodeError:
pass
if isinstance(filename,unicode):
filename=filename.encode('utf-8')
filemd5 = _md5(filename).hexdigest()
filename = re_url_scheme.sub("", filename)
filename = re_slash.sub(",", filename)
# limit length of filename
if len(filename)>200:
filename=filename[:200]
return ",".join((filename, filemd5)) | [
"def",
"safename",
"(",
"filename",
")",
":",
"try",
":",
"if",
"re_url_scheme",
".",
"match",
"(",
"filename",
")",
":",
"if",
"isinstance",
"(",
"filename",
",",
"str",
")",
":",
"filename",
"=",
"filename",
".",
"decode",
"(",
"'utf-8'",
")",
"filen... | https://github.com/meduza-corp/interstellar/blob/40a801ccd7856491726f5a126621d9318cabe2e1/gsutil/third_party/httplib2/python2/httplib2/__init__.py#L235-L260 | |
XX-net/XX-Net | a9898cfcf0084195fb7e69b6bc834e59aecdf14f | python3.8.2/Lib/asyncio/base_events.py | python | BaseEventLoop.run_forever | (self) | Run until stop() is called. | Run until stop() is called. | [
"Run",
"until",
"stop",
"()",
"is",
"called",
"."
] | def run_forever(self):
"""Run until stop() is called."""
self._check_closed()
self._check_running()
self._set_coroutine_origin_tracking(self._debug)
self._thread_id = threading.get_ident()
old_agen_hooks = sys.get_asyncgen_hooks()
sys.set_asyncgen_hooks(firstiter=self._asyncgen_firstiter_hook,
finalizer=self._asyncgen_finalizer_hook)
try:
events._set_running_loop(self)
while True:
self._run_once()
if self._stopping:
break
finally:
self._stopping = False
self._thread_id = None
events._set_running_loop(None)
self._set_coroutine_origin_tracking(False)
sys.set_asyncgen_hooks(*old_agen_hooks) | [
"def",
"run_forever",
"(",
"self",
")",
":",
"self",
".",
"_check_closed",
"(",
")",
"self",
".",
"_check_running",
"(",
")",
"self",
".",
"_set_coroutine_origin_tracking",
"(",
"self",
".",
"_debug",
")",
"self",
".",
"_thread_id",
"=",
"threading",
".",
... | https://github.com/XX-net/XX-Net/blob/a9898cfcf0084195fb7e69b6bc834e59aecdf14f/python3.8.2/Lib/asyncio/base_events.py#L557-L578 | ||
uber/causalml | ebf265156f23bba4939a7db0f635c35408324708 | causalml/optimize/utils.py | python | get_actual_value | (treatment, observed_outcome, conversion_value,
conditions, conversion_cost, impression_cost) | return actual_value | Set the conversion and impression costs based on a dict of parameters.
Calculate the actual value of targeting a user with the actual treatment group
using the above parameters.
Params
------
treatment : array, shape = (num_samples, )
Treatment array.
observed_outcome : array, shape = (num_samples, )
Observed outcome array, aka y.
conversion_value : array, shape = (num_samples, )
The value of converting a given user.
conditions : list, len = len(set(treatment))
List of treatment conditions.
conversion_cost : array, shape = (num_samples, num_treatment)
Array of conversion costs for each unit in each treatment.
impression_cost : array, shape = (num_samples, num_treatment)
Array of impression costs for each unit in each treatment.
Returns
-------
actual_value : array, shape = (num_samples, )
Array of actual values of havng a user in their actual treatment group.
conversion_value : array, shape = (num_samples, )
Array of payoffs from converting a user. | Set the conversion and impression costs based on a dict of parameters. | [
"Set",
"the",
"conversion",
"and",
"impression",
"costs",
"based",
"on",
"a",
"dict",
"of",
"parameters",
"."
] | def get_actual_value(treatment, observed_outcome, conversion_value,
conditions, conversion_cost, impression_cost):
'''
Set the conversion and impression costs based on a dict of parameters.
Calculate the actual value of targeting a user with the actual treatment group
using the above parameters.
Params
------
treatment : array, shape = (num_samples, )
Treatment array.
observed_outcome : array, shape = (num_samples, )
Observed outcome array, aka y.
conversion_value : array, shape = (num_samples, )
The value of converting a given user.
conditions : list, len = len(set(treatment))
List of treatment conditions.
conversion_cost : array, shape = (num_samples, num_treatment)
Array of conversion costs for each unit in each treatment.
impression_cost : array, shape = (num_samples, num_treatment)
Array of impression costs for each unit in each treatment.
Returns
-------
actual_value : array, shape = (num_samples, )
Array of actual values of havng a user in their actual treatment group.
conversion_value : array, shape = (num_samples, )
Array of payoffs from converting a user.
'''
cost_filter = [actual_group == possible_group
for actual_group in treatment
for possible_group in conditions]
conversion_cost_flat = conversion_cost.flatten()
actual_cc = conversion_cost_flat[cost_filter]
impression_cost_flat = impression_cost.flatten()
actual_ic = impression_cost_flat[cost_filter]
# Calculate the actual value of having a user in their actual treatment
actual_value = (conversion_value - actual_cc) * \
observed_outcome - actual_ic
return actual_value | [
"def",
"get_actual_value",
"(",
"treatment",
",",
"observed_outcome",
",",
"conversion_value",
",",
"conditions",
",",
"conversion_cost",
",",
"impression_cost",
")",
":",
"cost_filter",
"=",
"[",
"actual_group",
"==",
"possible_group",
"for",
"actual_group",
"in",
... | https://github.com/uber/causalml/blob/ebf265156f23bba4939a7db0f635c35408324708/causalml/optimize/utils.py#L56-L106 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.