blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0998a0eed73dfcda986b11e1d807208cc8ff9813 | [
"self.threads = []\nif thread is not None:\n self.threads.append(thread)\nif threads is not None:\n for t in threads:\n self.threads.append(t)",
"if thread is None:\n thread = Thread()\nself.threads.append(thread)\nreturn thread",
"threads = []\nfor thread in self.threads:\n threads.append(th... | <|body_start_0|>
self.threads = []
if thread is not None:
self.threads.append(thread)
if threads is not None:
for t in threads:
self.threads.append(t)
<|end_body_0|>
<|body_start_1|>
if thread is None:
thread = Thread()
self.th... | Defines a test vector in a testbench | TestVector | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestVector:
"""Defines a test vector in a testbench"""
def __init__(self, thread=None, threads=None):
"""Initializes a TestVector object Args: thread (Thread, optional): Defaults to None. An initial Thread to initialize with threads (Iterable of Threads, optional): Defaults to None. ... | stack_v2_sparse_classes_36k_train_022700 | 20,729 | permissive | [
{
"docstring": "Initializes a TestVector object Args: thread (Thread, optional): Defaults to None. An initial Thread to initialize with threads (Iterable of Threads, optional): Defaults to None. Initialize TestVector with all Threads in this iterable",
"name": "__init__",
"signature": "def __init__(self... | 3 | stack_v2_sparse_classes_30k_train_013183 | Implement the Python class `TestVector` described below.
Class description:
Defines a test vector in a testbench
Method signatures and docstrings:
- def __init__(self, thread=None, threads=None): Initializes a TestVector object Args: thread (Thread, optional): Defaults to None. An initial Thread to initialize with th... | Implement the Python class `TestVector` described below.
Class description:
Defines a test vector in a testbench
Method signatures and docstrings:
- def __init__(self, thread=None, threads=None): Initializes a TestVector object Args: thread (Thread, optional): Defaults to None. An initial Thread to initialize with th... | 99de16dd16d0aa77734584e67263c78a37abef86 | <|skeleton|>
class TestVector:
"""Defines a test vector in a testbench"""
def __init__(self, thread=None, threads=None):
"""Initializes a TestVector object Args: thread (Thread, optional): Defaults to None. An initial Thread to initialize with threads (Iterable of Threads, optional): Defaults to None. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestVector:
"""Defines a test vector in a testbench"""
def __init__(self, thread=None, threads=None):
"""Initializes a TestVector object Args: thread (Thread, optional): Defaults to None. An initial Thread to initialize with threads (Iterable of Threads, optional): Defaults to None. Initialize Te... | the_stack_v2_python_sparse | sonar/testbench.py | Zyk-Hyphen/sonar | train | 0 |
2814fac3fba92e37576e616520bb00f0de005f37 | [
"self.change_password_on_next_logon = change_password_on_next_logon\nself.leave_state_disabled = leave_state_disabled\nself.object_guids = object_guids\nself.organization_unit_path = organization_unit_path\nself.password = password",
"if dictionary is None:\n return None\nchange_password_on_next_logon = dictio... | <|body_start_0|>
self.change_password_on_next_logon = change_password_on_next_logon
self.leave_state_disabled = leave_state_disabled
self.object_guids = object_guids
self.organization_unit_path = organization_unit_path
self.password = password
<|end_body_0|>
<|body_start_1|>
... | Implementation of the 'AdObjectRestoreParameters' model. AdObjectRestoreParameters are the parameters to restore AD objects from recycle bin or from a mounted AD snapshot database. Attributes: change_password_on_next_logon (bool): Specifies the option for AD 'user' type of objects to change password when they next logo... | AdObjectRestoreParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdObjectRestoreParameters:
"""Implementation of the 'AdObjectRestoreParameters' model. AdObjectRestoreParameters are the parameters to restore AD objects from recycle bin or from a mounted AD snapshot database. Attributes: change_password_on_next_logon (bool): Specifies the option for AD 'user' t... | stack_v2_sparse_classes_36k_train_022701 | 4,435 | permissive | [
{
"docstring": "Constructor for the AdObjectRestoreParameters class",
"name": "__init__",
"signature": "def __init__(self, change_password_on_next_logon=None, leave_state_disabled=None, object_guids=None, organization_unit_path=None, password=None)"
},
{
"docstring": "Creates an instance of this... | 2 | stack_v2_sparse_classes_30k_train_004176 | Implement the Python class `AdObjectRestoreParameters` described below.
Class description:
Implementation of the 'AdObjectRestoreParameters' model. AdObjectRestoreParameters are the parameters to restore AD objects from recycle bin or from a mounted AD snapshot database. Attributes: change_password_on_next_logon (bool... | Implement the Python class `AdObjectRestoreParameters` described below.
Class description:
Implementation of the 'AdObjectRestoreParameters' model. AdObjectRestoreParameters are the parameters to restore AD objects from recycle bin or from a mounted AD snapshot database. Attributes: change_password_on_next_logon (bool... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class AdObjectRestoreParameters:
"""Implementation of the 'AdObjectRestoreParameters' model. AdObjectRestoreParameters are the parameters to restore AD objects from recycle bin or from a mounted AD snapshot database. Attributes: change_password_on_next_logon (bool): Specifies the option for AD 'user' t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdObjectRestoreParameters:
"""Implementation of the 'AdObjectRestoreParameters' model. AdObjectRestoreParameters are the parameters to restore AD objects from recycle bin or from a mounted AD snapshot database. Attributes: change_password_on_next_logon (bool): Specifies the option for AD 'user' type of object... | the_stack_v2_python_sparse | cohesity_management_sdk/models/ad_object_restore_parameters.py | cohesity/management-sdk-python | train | 24 |
22c719006d20e68b90015539ff215c79185d0ba6 | [
"self.level_vectors = level_vectors\nself.labels = labels\nself.pairs_df = pairs_df\nself.weights = np.ones(level_vectors.shape[1])\nself.best_weights = np.ones(level_vectors.shape[1])\nself.least_diff = -1\nself.comparator = comparator.Comparator(self.level_vectors, self.labels, self.pairs_df)",
"print('Optimizi... | <|body_start_0|>
self.level_vectors = level_vectors
self.labels = labels
self.pairs_df = pairs_df
self.weights = np.ones(level_vectors.shape[1])
self.best_weights = np.ones(level_vectors.shape[1])
self.least_diff = -1
self.comparator = comparator.Comparator(self.l... | WeightOptimizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeightOptimizer:
def __init__(self, level_vectors, labels, pairs_df):
"""Class for optimizing the weights vector for MTS level analysis Args: level_vectors: ndarray containing dense vector representations of all levels labels: ndarray containing labels for respectively indexed vectors pa... | stack_v2_sparse_classes_36k_train_022702 | 3,954 | permissive | [
{
"docstring": "Class for optimizing the weights vector for MTS level analysis Args: level_vectors: ndarray containing dense vector representations of all levels labels: ndarray containing labels for respectively indexed vectors pairs_df: dataframe containing pair indices and respective mean scores",
"name"... | 3 | stack_v2_sparse_classes_30k_train_011611 | Implement the Python class `WeightOptimizer` described below.
Class description:
Implement the WeightOptimizer class.
Method signatures and docstrings:
- def __init__(self, level_vectors, labels, pairs_df): Class for optimizing the weights vector for MTS level analysis Args: level_vectors: ndarray containing dense ve... | Implement the Python class `WeightOptimizer` described below.
Class description:
Implement the WeightOptimizer class.
Method signatures and docstrings:
- def __init__(self, level_vectors, labels, pairs_df): Class for optimizing the weights vector for MTS level analysis Args: level_vectors: ndarray containing dense ve... | cc9b28b8741b41bea1273c8bc9b4d265d79a1dca | <|skeleton|>
class WeightOptimizer:
def __init__(self, level_vectors, labels, pairs_df):
"""Class for optimizing the weights vector for MTS level analysis Args: level_vectors: ndarray containing dense vector representations of all levels labels: ndarray containing labels for respectively indexed vectors pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WeightOptimizer:
def __init__(self, level_vectors, labels, pairs_df):
"""Class for optimizing the weights vector for MTS level analysis Args: level_vectors: ndarray containing dense vector representations of all levels labels: ndarray containing labels for respectively indexed vectors pairs_df: datafr... | the_stack_v2_python_sparse | autoencoder/optimizer.py | xingchen1106/match3-level-similarity | train | 0 | |
b8173d8f3c95d53202e04eb9aeac4ea64e95ce78 | [
"dists = np.array(distance_chunk)\nmin_dist = 1e-12\nmask = dists < min_dist\nif mask.sum() > 0:\n logger.info(f'{np.sum(mask)} of {np.product(mask.shape)} distances are zero.')\ndists[mask] = min_dist\nweights = 1 / dists\nnorm = np.sum(weights, axis=-1)\nout = np.einsum('ijk,jk->ij', values, weights) / norm\nr... | <|body_start_0|>
dists = np.array(distance_chunk)
min_dist = 1e-12
mask = dists < min_dist
if mask.sum() > 0:
logger.info(f'{np.sum(mask)} of {np.product(mask.shape)} distances are zero.')
dists[mask] = min_dist
weights = 1 / dists
norm = np.sum(weight... | Regridder class for mapping list of coordinates to another. Includes weights and indicies used to map from source grid to each point in the new grid | Regridder | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Regridder:
"""Regridder class for mapping list of coordinates to another. Includes weights and indicies used to map from source grid to each point in the new grid"""
def interpolate(distance_chunk, values):
"""Interpolate to a new coordinate based on distances from that coordinate an... | stack_v2_sparse_classes_36k_train_022703 | 29,957 | permissive | [
{
"docstring": "Interpolate to a new coordinate based on distances from that coordinate and the values of the points at those distances Parameters ---------- distance_chunk : ndarray Chunk of the full array of distances where distances[i] gives the list of distances to the source coordinates to be used for inte... | 2 | stack_v2_sparse_classes_30k_train_013839 | Implement the Python class `Regridder` described below.
Class description:
Regridder class for mapping list of coordinates to another. Includes weights and indicies used to map from source grid to each point in the new grid
Method signatures and docstrings:
- def interpolate(distance_chunk, values): Interpolate to a ... | Implement the Python class `Regridder` described below.
Class description:
Regridder class for mapping list of coordinates to another. Includes weights and indicies used to map from source grid to each point in the new grid
Method signatures and docstrings:
- def interpolate(distance_chunk, values): Interpolate to a ... | f3803a823c7bb0afd7ab6064625908dca0be3476 | <|skeleton|>
class Regridder:
"""Regridder class for mapping list of coordinates to another. Includes weights and indicies used to map from source grid to each point in the new grid"""
def interpolate(distance_chunk, values):
"""Interpolate to a new coordinate based on distances from that coordinate an... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Regridder:
"""Regridder class for mapping list of coordinates to another. Includes weights and indicies used to map from source grid to each point in the new grid"""
def interpolate(distance_chunk, values):
"""Interpolate to a new coordinate based on distances from that coordinate and the values ... | the_stack_v2_python_sparse | sup3r/utilities/regridder.py | NREL/sup3r | train | 20 |
9b02c6ec8cc9ca31b86dd9965ad4ac986762edd9 | [
"python_type = cls.omg_types_to_python_types.get(omg_type_name)\nif python_type is None:\n raise UnsupportedTypeOmgError(omg_type_name)\nif value is None:\n return\ncls.ensure_type(prop_name, python_type, omg_type_name, value, action_resolution_chain)",
"omg_type = expected_output.get('type')\nif omg_type !... | <|body_start_0|>
python_type = cls.omg_types_to_python_types.get(omg_type_name)
if python_type is None:
raise UnsupportedTypeOmgError(omg_type_name)
if value is None:
return
cls.ensure_type(prop_name, python_type, omg_type_name, value, action_resolution_chain)
<|e... | Class to verify the output of a service. | ServiceOutputValidator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceOutputValidator:
"""Class to verify the output of a service."""
def raise_for_type_mismatch(cls, prop_name, omg_type_name, value, action_resolution_chain):
"""Ensures that the value matches the expected type as listed on https://microservice.guide/schema/actions/#arguments. Su... | stack_v2_sparse_classes_36k_train_022704 | 3,922 | permissive | [
{
"docstring": "Ensures that the value matches the expected type as listed on https://microservice.guide/schema/actions/#arguments. Supported types: int, float, number, string, list, map, boolean, or any",
"name": "raise_for_type_mismatch",
"signature": "def raise_for_type_mismatch(cls, prop_name, omg_t... | 3 | stack_v2_sparse_classes_30k_test_000060 | Implement the Python class `ServiceOutputValidator` described below.
Class description:
Class to verify the output of a service.
Method signatures and docstrings:
- def raise_for_type_mismatch(cls, prop_name, omg_type_name, value, action_resolution_chain): Ensures that the value matches the expected type as listed on... | Implement the Python class `ServiceOutputValidator` described below.
Class description:
Class to verify the output of a service.
Method signatures and docstrings:
- def raise_for_type_mismatch(cls, prop_name, omg_type_name, value, action_resolution_chain): Ensures that the value matches the expected type as listed on... | b2c9ab9d39e6d16a0116e4cdf7d65fda45dfce8c | <|skeleton|>
class ServiceOutputValidator:
"""Class to verify the output of a service."""
def raise_for_type_mismatch(cls, prop_name, omg_type_name, value, action_resolution_chain):
"""Ensures that the value matches the expected type as listed on https://microservice.guide/schema/actions/#arguments. Su... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServiceOutputValidator:
"""Class to verify the output of a service."""
def raise_for_type_mismatch(cls, prop_name, omg_type_name, value, action_resolution_chain):
"""Ensures that the value matches the expected type as listed on https://microservice.guide/schema/actions/#arguments. Supported types... | the_stack_v2_python_sparse | storyruntime/omg/ServiceOutputValidator.py | wilzbach/platform-engine | train | 0 |
a13ff8321e2ec3565f098d518775e1050daa7090 | [
"self.plugins = []\nif plugins:\n for plugin in plugins:\n self.load_plugin(plugin)",
"if plname == '':\n return\ntrig = NextTrigger()\nmod = import_module(plname)\nif trig.IsSet():\n raise PluginError('Plugin %s has a trigger on outside the function plugin_setup(), which is not allowed' % plname)... | <|body_start_0|>
self.plugins = []
if plugins:
for plugin in plugins:
self.load_plugin(plugin)
<|end_body_0|>
<|body_start_1|>
if plname == '':
return
trig = NextTrigger()
mod = import_module(plname)
if trig.IsSet():
ra... | PluginManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PluginManager:
def __init__(self, plugins=None):
"""Load plugins as default Args: plugins (list): list of plugins given with module, default to None Example:: PluginManager(["screpl.plugins.unit", "screpl.plugins.location"])"""
<|body_0|>
def load_plugin(self, plname):
... | stack_v2_sparse_classes_36k_train_022705 | 3,072 | permissive | [
{
"docstring": "Load plugins as default Args: plugins (list): list of plugins given with module, default to None Example:: PluginManager([\"screpl.plugins.unit\", \"screpl.plugins.location\"])",
"name": "__init__",
"signature": "def __init__(self, plugins=None)"
},
{
"docstring": "Load screpl pl... | 2 | null | Implement the Python class `PluginManager` described below.
Class description:
Implement the PluginManager class.
Method signatures and docstrings:
- def __init__(self, plugins=None): Load plugins as default Args: plugins (list): list of plugins given with module, default to None Example:: PluginManager(["screpl.plug... | Implement the Python class `PluginManager` described below.
Class description:
Implement the PluginManager class.
Method signatures and docstrings:
- def __init__(self, plugins=None): Load plugins as default Args: plugins (list): list of plugins given with module, default to None Example:: PluginManager(["screpl.plug... | 37b4d03069f074ae6b9b1caa3526730b30740de3 | <|skeleton|>
class PluginManager:
def __init__(self, plugins=None):
"""Load plugins as default Args: plugins (list): list of plugins given with module, default to None Example:: PluginManager(["screpl.plugins.unit", "screpl.plugins.location"])"""
<|body_0|>
def load_plugin(self, plname):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PluginManager:
def __init__(self, plugins=None):
"""Load plugins as default Args: plugins (list): list of plugins given with module, default to None Example:: PluginManager(["screpl.plugins.unit", "screpl.plugins.location"])"""
self.plugins = []
if plugins:
for plugin in pl... | the_stack_v2_python_sparse | screpl/plugin.py | mighty1231/screpl | train | 8 | |
f533d650c1b590d5013187cff13577032f0c9519 | [
"super(MatchPublisherThread, self).__init__()\nself.theMatch = theMatch\nself.spectatorURL = spectatorURL",
"try:\n MatchPublisher.publishToSpectatorServer(self.spectatorURL, self.theMatch)\nexcept IOException as e:\n e.printStackTrace()"
] | <|body_start_0|>
super(MatchPublisherThread, self).__init__()
self.theMatch = theMatch
self.spectatorURL = spectatorURL
<|end_body_0|>
<|body_start_1|>
try:
MatchPublisher.publishToSpectatorServer(self.spectatorURL, self.theMatch)
except IOException as e:
... | generated source for class MatchPublisherThread | MatchPublisherThread | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MatchPublisherThread:
"""generated source for class MatchPublisherThread"""
def __init__(self, spectatorURL, theMatch):
"""generated source for method __init__"""
<|body_0|>
def run(self):
"""generated source for method run"""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_36k_train_022706 | 2,784 | permissive | [
{
"docstring": "generated source for method __init__",
"name": "__init__",
"signature": "def __init__(self, spectatorURL, theMatch)"
},
{
"docstring": "generated source for method run",
"name": "run",
"signature": "def run(self)"
}
] | 2 | null | Implement the Python class `MatchPublisherThread` described below.
Class description:
generated source for class MatchPublisherThread
Method signatures and docstrings:
- def __init__(self, spectatorURL, theMatch): generated source for method __init__
- def run(self): generated source for method run | Implement the Python class `MatchPublisherThread` described below.
Class description:
generated source for class MatchPublisherThread
Method signatures and docstrings:
- def __init__(self, spectatorURL, theMatch): generated source for method __init__
- def run(self): generated source for method run
<|skeleton|>
clas... | 4e6e6e876c3a4294cd711647051da2d9c1836b60 | <|skeleton|>
class MatchPublisherThread:
"""generated source for class MatchPublisherThread"""
def __init__(self, spectatorURL, theMatch):
"""generated source for method __init__"""
<|body_0|>
def run(self):
"""generated source for method run"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MatchPublisherThread:
"""generated source for class MatchPublisherThread"""
def __init__(self, spectatorURL, theMatch):
"""generated source for method __init__"""
super(MatchPublisherThread, self).__init__()
self.theMatch = theMatch
self.spectatorURL = spectatorURL
de... | the_stack_v2_python_sparse | ggpy/cruft/autocode/MatchPublisher.py | hobson/ggpy | train | 1 |
93840b41a3b3537419e39eaeeda0fc911ee26c2d | [
"try:\n user = get_user_model().objects.get(username=username)\nexcept ObjectDoesNotExist:\n raise Http404()\nprofile = Profile.objects.get(user=user)\nif not profile.user.pk == request.user.id:\n return Response({'detail': 'You are not allowed to update this user'}, status=status.HTTP_403_FORBIDDEN)\nseri... | <|body_start_0|>
try:
user = get_user_model().objects.get(username=username)
except ObjectDoesNotExist:
raise Http404()
profile = Profile.objects.get(user=user)
if not profile.user.pk == request.user.id:
return Response({'detail': 'You are not allowed ... | View for Updating the user's profile | ProfileRetrieveUpdate | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileRetrieveUpdate:
"""View for Updating the user's profile"""
def put(self, request, username, format=None):
"""get the user object from the passed in username get the profile belonging to the passed in username pass the request data through the serializer check if valid and save... | stack_v2_sparse_classes_36k_train_022707 | 3,909 | permissive | [
{
"docstring": "get the user object from the passed in username get the profile belonging to the passed in username pass the request data through the serializer check if valid and save",
"name": "put",
"signature": "def put(self, request, username, format=None)"
},
{
"docstring": "get the user o... | 2 | null | Implement the Python class `ProfileRetrieveUpdate` described below.
Class description:
View for Updating the user's profile
Method signatures and docstrings:
- def put(self, request, username, format=None): get the user object from the passed in username get the profile belonging to the passed in username pass the re... | Implement the Python class `ProfileRetrieveUpdate` described below.
Class description:
View for Updating the user's profile
Method signatures and docstrings:
- def put(self, request, username, format=None): get the user object from the passed in username get the profile belonging to the passed in username pass the re... | e8438b78b88c52d108520429d0b67cd3d13e0824 | <|skeleton|>
class ProfileRetrieveUpdate:
"""View for Updating the user's profile"""
def put(self, request, username, format=None):
"""get the user object from the passed in username get the profile belonging to the passed in username pass the request data through the serializer check if valid and save... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProfileRetrieveUpdate:
"""View for Updating the user's profile"""
def put(self, request, username, format=None):
"""get the user object from the passed in username get the profile belonging to the passed in username pass the request data through the serializer check if valid and save"""
t... | the_stack_v2_python_sparse | authors/apps/profiles/views.py | andela/ah-sealteam | train | 1 |
d9f02dec76cfd21b957f160dc008a6f2ae24d6a3 | [
"self.conf = conf\nself.model = None\nself.optimizer = None\nself.criterion = None",
"self.model = external.FCN8s(in_channels=1, n_class=2).cuda()\nself.criterion = torch.nn.CrossEntropyLoss().cuda()\nself.optimizer = torch.optim.Adam(self.model.parameters(), self.conf['learning_rate'])\ncudnn.benchmark = True",
... | <|body_start_0|>
self.conf = conf
self.model = None
self.optimizer = None
self.criterion = None
<|end_body_0|>
<|body_start_1|>
self.model = external.FCN8s(in_channels=1, n_class=2).cuda()
self.criterion = torch.nn.CrossEntropyLoss().cuda()
self.optimizer = torch... | Wrapper for model that ensures training is done with storing best models, logging results during training for each epoch, | ModelWrapper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelWrapper:
"""Wrapper for model that ensures training is done with storing best models, logging results during training for each epoch,"""
def __init__(self, conf):
""":param dict[str, Any] conf: Configuration file. Should contain keys ["learning_rate", "workers", "batch_size", "e... | stack_v2_sparse_classes_36k_train_022708 | 5,426 | no_license | [
{
"docstring": ":param dict[str, Any] conf: Configuration file. Should contain keys [\"learning_rate\", \"workers\", \"batch_size\", \"epochs\"]",
"name": "__init__",
"signature": "def __init__(self, conf)"
},
{
"docstring": "Defines used model, loss function and optimizer",
"name": "get_mod... | 6 | stack_v2_sparse_classes_30k_train_002392 | Implement the Python class `ModelWrapper` described below.
Class description:
Wrapper for model that ensures training is done with storing best models, logging results during training for each epoch,
Method signatures and docstrings:
- def __init__(self, conf): :param dict[str, Any] conf: Configuration file. Should c... | Implement the Python class `ModelWrapper` described below.
Class description:
Wrapper for model that ensures training is done with storing best models, logging results during training for each epoch,
Method signatures and docstrings:
- def __init__(self, conf): :param dict[str, Any] conf: Configuration file. Should c... | 5bc2e0f95af605d88c97dc8ed41490bc6964cdb2 | <|skeleton|>
class ModelWrapper:
"""Wrapper for model that ensures training is done with storing best models, logging results during training for each epoch,"""
def __init__(self, conf):
""":param dict[str, Any] conf: Configuration file. Should contain keys ["learning_rate", "workers", "batch_size", "e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelWrapper:
"""Wrapper for model that ensures training is done with storing best models, logging results during training for each epoch,"""
def __init__(self, conf):
""":param dict[str, Any] conf: Configuration file. Should contain keys ["learning_rate", "workers", "batch_size", "epochs"]"""
... | the_stack_v2_python_sparse | ventricle_segmentation/model_wrapper.py | tomasprinda/ventricle_segmentation | train | 0 |
994759d9e670c492143de7d01e73649296e47679 | [
"self.models = models\nself.coord = coord\nself.orig_coord = deepcopy(coord)",
"T, R, pivot = fit_to_mean(models=self.models, coord=self.coord, centroid=params, verbosity=0)\nval = atomic_rmsd(self.coord)\nself.coord = deepcopy(self.orig_coord)\nreturn val"
] | <|body_start_0|>
self.models = models
self.coord = coord
self.orig_coord = deepcopy(coord)
<|end_body_0|>
<|body_start_1|>
T, R, pivot = fit_to_mean(models=self.models, coord=self.coord, centroid=params, verbosity=0)
val = atomic_rmsd(self.coord)
self.coord = deepcopy(se... | Class for finding the optimal pivot point for motions between the given models. | Pivot_finder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pivot_finder:
"""Class for finding the optimal pivot point for motions between the given models."""
def __init__(self, models, coord):
"""Set up the class for pivot point optimisation for an ensemble of structures. @keyword models: The list of models to use. If set to None, then all ... | stack_v2_sparse_classes_36k_train_022709 | 3,384 | no_license | [
{
"docstring": "Set up the class for pivot point optimisation for an ensemble of structures. @keyword models: The list of models to use. If set to None, then all models will be used. @type models: list of int or None @keyword coord: The array of molecular coordinates. The first dimension corresponds to the mode... | 2 | null | Implement the Python class `Pivot_finder` described below.
Class description:
Class for finding the optimal pivot point for motions between the given models.
Method signatures and docstrings:
- def __init__(self, models, coord): Set up the class for pivot point optimisation for an ensemble of structures. @keyword mod... | Implement the Python class `Pivot_finder` described below.
Class description:
Class for finding the optimal pivot point for motions between the given models.
Method signatures and docstrings:
- def __init__(self, models, coord): Set up the class for pivot point optimisation for an ensemble of structures. @keyword mod... | c317326ddeacd1a1c608128769676899daeae531 | <|skeleton|>
class Pivot_finder:
"""Class for finding the optimal pivot point for motions between the given models."""
def __init__(self, models, coord):
"""Set up the class for pivot point optimisation for an ensemble of structures. @keyword models: The list of models to use. If set to None, then all ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Pivot_finder:
"""Class for finding the optimal pivot point for motions between the given models."""
def __init__(self, models, coord):
"""Set up the class for pivot point optimisation for an ensemble of structures. @keyword models: The list of models to use. If set to None, then all models will b... | the_stack_v2_python_sparse | target_functions/ens_pivot_finder.py | jlec/relax | train | 4 |
20a5f6a70f8cfff97b42bfca47adc83319c0195a | [
"Thread.__init__(self)\nself.tasks = tasks\nself.daemon = True\nself.start()",
"while 1:\n func, args, kargs = self.tasks.get()\n try:\n func(*args, **kargs)\n except Exception as e:\n print(e)\n finally:\n self.tasks.task_done()"
] | <|body_start_0|>
Thread.__init__(self)
self.tasks = tasks
self.daemon = True
self.start()
<|end_body_0|>
<|body_start_1|>
while 1:
func, args, kargs = self.tasks.get()
try:
func(*args, **kargs)
except Exception as e:
... | Thread executing tasks from a given tasks queue | Worker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Worker:
"""Thread executing tasks from a given tasks queue"""
def __init__(self, tasks):
"""Constructor :param tasks: queue containing tasks to execute"""
<|body_0|>
def run(self):
"""Run the worker thread"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_022710 | 2,523 | permissive | [
{
"docstring": "Constructor :param tasks: queue containing tasks to execute",
"name": "__init__",
"signature": "def __init__(self, tasks)"
},
{
"docstring": "Run the worker thread",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000922 | Implement the Python class `Worker` described below.
Class description:
Thread executing tasks from a given tasks queue
Method signatures and docstrings:
- def __init__(self, tasks): Constructor :param tasks: queue containing tasks to execute
- def run(self): Run the worker thread | Implement the Python class `Worker` described below.
Class description:
Thread executing tasks from a given tasks queue
Method signatures and docstrings:
- def __init__(self, tasks): Constructor :param tasks: queue containing tasks to execute
- def run(self): Run the worker thread
<|skeleton|>
class Worker:
"""T... | 09692f8d2300172c41ce25331361875c56d0ba4a | <|skeleton|>
class Worker:
"""Thread executing tasks from a given tasks queue"""
def __init__(self, tasks):
"""Constructor :param tasks: queue containing tasks to execute"""
<|body_0|>
def run(self):
"""Run the worker thread"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Worker:
"""Thread executing tasks from a given tasks queue"""
def __init__(self, tasks):
"""Constructor :param tasks: queue containing tasks to execute"""
Thread.__init__(self)
self.tasks = tasks
self.daemon = True
self.start()
def run(self):
"""Run th... | the_stack_v2_python_sparse | DEVS Modelling and Simulation/pythonpdevs/src/pypdevs/threadpool.py | baturayo/Modeling-of-Software-Intensive-Systems | train | 2 |
b6fd5d32b0168cd5333d304423e1bf3ad90d25a8 | [
"gt_labels = self.data_infos[idx]['gt_label']\ncat_ids = np.where(gt_labels == 1)[0].tolist()\nreturn cat_ids",
"if metric_options is None or metric_options == {}:\n metric_options = {'thr': 0.5}\nif isinstance(metric, str):\n metrics = [metric]\nelse:\n metrics = metric\nallowed_metrics = ['mAP', 'CP', ... | <|body_start_0|>
gt_labels = self.data_infos[idx]['gt_label']
cat_ids = np.where(gt_labels == 1)[0].tolist()
return cat_ids
<|end_body_0|>
<|body_start_1|>
if metric_options is None or metric_options == {}:
metric_options = {'thr': 0.5}
if isinstance(metric, str):
... | Multi-label Dataset. | MultiLabelDataset | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiLabelDataset:
"""Multi-label Dataset."""
def get_cat_ids(self, idx: int) -> List[int]:
"""Get category ids by index. Args: idx (int): Index of data. Returns: cat_ids (List[int]): Image categories of specified index."""
<|body_0|>
def evaluate(self, results, metric='... | stack_v2_sparse_classes_36k_train_022711 | 2,802 | permissive | [
{
"docstring": "Get category ids by index. Args: idx (int): Index of data. Returns: cat_ids (List[int]): Image categories of specified index.",
"name": "get_cat_ids",
"signature": "def get_cat_ids(self, idx: int) -> List[int]"
},
{
"docstring": "Evaluate the dataset. Args: results (list): Testin... | 2 | stack_v2_sparse_classes_30k_train_000784 | Implement the Python class `MultiLabelDataset` described below.
Class description:
Multi-label Dataset.
Method signatures and docstrings:
- def get_cat_ids(self, idx: int) -> List[int]: Get category ids by index. Args: idx (int): Index of data. Returns: cat_ids (List[int]): Image categories of specified index.
- def ... | Implement the Python class `MultiLabelDataset` described below.
Class description:
Multi-label Dataset.
Method signatures and docstrings:
- def get_cat_ids(self, idx: int) -> List[int]: Get category ids by index. Args: idx (int): Index of data. Returns: cat_ids (List[int]): Image categories of specified index.
- def ... | 2b8882b2da41d4e175fe49a33fcefad1423216f4 | <|skeleton|>
class MultiLabelDataset:
"""Multi-label Dataset."""
def get_cat_ids(self, idx: int) -> List[int]:
"""Get category ids by index. Args: idx (int): Index of data. Returns: cat_ids (List[int]): Image categories of specified index."""
<|body_0|>
def evaluate(self, results, metric='... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiLabelDataset:
"""Multi-label Dataset."""
def get_cat_ids(self, idx: int) -> List[int]:
"""Get category ids by index. Args: idx (int): Index of data. Returns: cat_ids (List[int]): Image categories of specified index."""
gt_labels = self.data_infos[idx]['gt_label']
cat_ids = np... | the_stack_v2_python_sparse | mmcls/datasets/multi_label.py | ChenhongyiYang/GPViT | train | 78 |
4680d7ec4bc549f26190f435f836c40f67c7d3ce | [
"from CortexCoreIR import handle_prevalence_command, Client\nmock_client = Client(base_url=f'{Core_URL}/xsiam/', headers={})\nmock_res = load_test_data('./test_data/prevalence_response.json')\nmocker.patch.object(mock_client, 'get_prevalence', return_value=mock_res.get('domain'))\nres = handle_prevalence_command(mo... | <|body_start_0|>
from CortexCoreIR import handle_prevalence_command, Client
mock_client = Client(base_url=f'{Core_URL}/xsiam/', headers={})
mock_res = load_test_data('./test_data/prevalence_response.json')
mocker.patch.object(mock_client, 'get_prevalence', return_value=mock_res.get('doma... | TestPrevalenceCommands | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPrevalenceCommands:
def test_get_domain_analytics(self, mocker):
"""Given: - A domain name. When: - Calling handle_prevalence_command as part of core-get-domain-analytics-prevalence command. Then: - Verify response is as expected."""
<|body_0|>
def test_get_ip_analytics(... | stack_v2_sparse_classes_36k_train_022712 | 3,844 | permissive | [
{
"docstring": "Given: - A domain name. When: - Calling handle_prevalence_command as part of core-get-domain-analytics-prevalence command. Then: - Verify response is as expected.",
"name": "test_get_domain_analytics",
"signature": "def test_get_domain_analytics(self, mocker)"
},
{
"docstring": "... | 3 | stack_v2_sparse_classes_30k_train_014136 | Implement the Python class `TestPrevalenceCommands` described below.
Class description:
Implement the TestPrevalenceCommands class.
Method signatures and docstrings:
- def test_get_domain_analytics(self, mocker): Given: - A domain name. When: - Calling handle_prevalence_command as part of core-get-domain-analytics-pr... | Implement the Python class `TestPrevalenceCommands` described below.
Class description:
Implement the TestPrevalenceCommands class.
Method signatures and docstrings:
- def test_get_domain_analytics(self, mocker): Given: - A domain name. When: - Calling handle_prevalence_command as part of core-get-domain-analytics-pr... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestPrevalenceCommands:
def test_get_domain_analytics(self, mocker):
"""Given: - A domain name. When: - Calling handle_prevalence_command as part of core-get-domain-analytics-prevalence command. Then: - Verify response is as expected."""
<|body_0|>
def test_get_ip_analytics(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestPrevalenceCommands:
def test_get_domain_analytics(self, mocker):
"""Given: - A domain name. When: - Calling handle_prevalence_command as part of core-get-domain-analytics-prevalence command. Then: - Verify response is as expected."""
from CortexCoreIR import handle_prevalence_command, Clie... | the_stack_v2_python_sparse | Packs/Core/Integrations/CortexCoreIR/CortexCoreIR_test.py | demisto/content | train | 1,023 | |
8a9de19a2119078c81cba6df4f4827a60f1dbd3e | [
"if category.prevent_custom_triggers_default:\n kwargs['initial'] = {'prevent_custom_triggers': True}\nsuper().__init__(*args, **kwargs)\nqs = Goal.objects.packages(categories=category)\nself.fields['packaged_goals'].queryset = qs\nif not category.display_prevent_custom_triggers_option:\n self.fields['prevent... | <|body_start_0|>
if category.prevent_custom_triggers_default:
kwargs['initial'] = {'prevent_custom_triggers': True}
super().__init__(*args, **kwargs)
qs = Goal.objects.packages(categories=category)
self.fields['packaged_goals'].queryset = qs
if not category.display_pr... | Allows input of email addresses (in a text box) and the selection of one or more Categories--those of which have been designated as packaged content. Requires that it's first argument is a Category, the parent (or package) of the goals to be selected. | PackageEnrollmentForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PackageEnrollmentForm:
"""Allows input of email addresses (in a text box) and the selection of one or more Categories--those of which have been designated as packaged content. Requires that it's first argument is a Category, the parent (or package) of the goals to be selected."""
def __init_... | stack_v2_sparse_classes_36k_train_022713 | 33,751 | permissive | [
{
"docstring": "Provide a specific category for this for in order to enroll users in it's set of Goals.",
"name": "__init__",
"signature": "def __init__(self, category, *args, **kwargs)"
},
{
"docstring": "Returns a list of email addresses.",
"name": "clean_email_addresses",
"signature":... | 2 | stack_v2_sparse_classes_30k_test_000451 | Implement the Python class `PackageEnrollmentForm` described below.
Class description:
Allows input of email addresses (in a text box) and the selection of one or more Categories--those of which have been designated as packaged content. Requires that it's first argument is a Category, the parent (or package) of the go... | Implement the Python class `PackageEnrollmentForm` described below.
Class description:
Allows input of email addresses (in a text box) and the selection of one or more Categories--those of which have been designated as packaged content. Requires that it's first argument is a Category, the parent (or package) of the go... | 3d22179c581ab3da18900483930d5ecc0a5fca73 | <|skeleton|>
class PackageEnrollmentForm:
"""Allows input of email addresses (in a text box) and the selection of one or more Categories--those of which have been designated as packaged content. Requires that it's first argument is a Category, the parent (or package) of the goals to be selected."""
def __init_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PackageEnrollmentForm:
"""Allows input of email addresses (in a text box) and the selection of one or more Categories--those of which have been designated as packaged content. Requires that it's first argument is a Category, the parent (or package) of the goals to be selected."""
def __init__(self, categ... | the_stack_v2_python_sparse | tndata_backend/goals/forms.py | tndatacommons/tndata_backend | train | 1 |
b4f70da76591db28efa93b379092294c8fd09fc5 | [
"self._check_permission(Permissions.users_view)\nusers = await User.all()\nreturn ResponseUsers(users)",
"self._check_permission(Permissions.users_edit)\ndata = await self.get_json()\nrequest_model = RequestUser(**data)\nkwargs = {}\nif request_model.password:\n kwargs['pass_hash'] = User.get_pass_hash(request... | <|body_start_0|>
self._check_permission(Permissions.users_view)
users = await User.all()
return ResponseUsers(users)
<|end_body_0|>
<|body_start_1|>
self._check_permission(Permissions.users_edit)
data = await self.get_json()
request_model = RequestUser(**data)
kw... | UsersView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UsersView:
async def get(self):
"""--- description: Get list of users tags: - users responses: '200': description: ok content: application/json: schema: $ref: '#/components/schemas/ResponseUsers' '400': description: Bad request content: application/json: schema: $ref: '#/components/schem... | stack_v2_sparse_classes_36k_train_022714 | 5,428 | no_license | [
{
"docstring": "--- description: Get list of users tags: - users responses: '200': description: ok content: application/json: schema: $ref: '#/components/schemas/ResponseUsers' '400': description: Bad request content: application/json: schema: $ref: '#/components/schemas/ResponseError' '401': description: Unaut... | 2 | stack_v2_sparse_classes_30k_train_004141 | Implement the Python class `UsersView` described below.
Class description:
Implement the UsersView class.
Method signatures and docstrings:
- async def get(self): --- description: Get list of users tags: - users responses: '200': description: ok content: application/json: schema: $ref: '#/components/schemas/ResponseU... | Implement the Python class `UsersView` described below.
Class description:
Implement the UsersView class.
Method signatures and docstrings:
- async def get(self): --- description: Get list of users tags: - users responses: '200': description: ok content: application/json: schema: $ref: '#/components/schemas/ResponseU... | d4abeb5b87ab00c4b371d501f3d117feb5e4d72c | <|skeleton|>
class UsersView:
async def get(self):
"""--- description: Get list of users tags: - users responses: '200': description: ok content: application/json: schema: $ref: '#/components/schemas/ResponseUsers' '400': description: Bad request content: application/json: schema: $ref: '#/components/schem... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UsersView:
async def get(self):
"""--- description: Get list of users tags: - users responses: '200': description: ok content: application/json: schema: $ref: '#/components/schemas/ResponseUsers' '400': description: Bad request content: application/json: schema: $ref: '#/components/schemas/ResponseErr... | the_stack_v2_python_sparse | app/services/web/views/users.py | Ravillatypov/asterisk-integration-api | train | 2 | |
1f359129b560510dff37ed267cdf4862d8cc925c | [
"self.created_time_msecs = created_time_msecs\nself.description = description\nself.is_custom_role = is_custom_role\nself.label = label\nself.last_updated_time_msecs = last_updated_time_msecs\nself.name = name\nself.privileges = privileges\nself.tenant_id = tenant_id\nself.tenant_ids = tenant_ids",
"if dictionary... | <|body_start_0|>
self.created_time_msecs = created_time_msecs
self.description = description
self.is_custom_role = is_custom_role
self.label = label
self.last_updated_time_msecs = last_updated_time_msecs
self.name = name
self.privileges = privileges
self.t... | Implementation of the 'Role' model. Specifies information about role such as the category, privileges, description, etc. A role can be a default system role or a custom role. Custom roles are user-defined roles that are created using the Cohesity Dashboard, the REST API or the CLI. System roles are provided by default ... | Role | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Role:
"""Implementation of the 'Role' model. Specifies information about role such as the category, privileges, description, etc. A role can be a default system role or a custom role. Custom roles are user-defined roles that are created using the Cohesity Dashboard, the REST API or the CLI. Syste... | stack_v2_sparse_classes_36k_train_022715 | 4,509 | permissive | [
{
"docstring": "Constructor for the Role class",
"name": "__init__",
"signature": "def __init__(self, created_time_msecs=None, description=None, is_custom_role=None, label=None, last_updated_time_msecs=None, name=None, privileges=None, tenant_id=None, tenant_ids=None)"
},
{
"docstring": "Creates... | 2 | null | Implement the Python class `Role` described below.
Class description:
Implementation of the 'Role' model. Specifies information about role such as the category, privileges, description, etc. A role can be a default system role or a custom role. Custom roles are user-defined roles that are created using the Cohesity Da... | Implement the Python class `Role` described below.
Class description:
Implementation of the 'Role' model. Specifies information about role such as the category, privileges, description, etc. A role can be a default system role or a custom role. Custom roles are user-defined roles that are created using the Cohesity Da... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class Role:
"""Implementation of the 'Role' model. Specifies information about role such as the category, privileges, description, etc. A role can be a default system role or a custom role. Custom roles are user-defined roles that are created using the Cohesity Dashboard, the REST API or the CLI. Syste... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Role:
"""Implementation of the 'Role' model. Specifies information about role such as the category, privileges, description, etc. A role can be a default system role or a custom role. Custom roles are user-defined roles that are created using the Cohesity Dashboard, the REST API or the CLI. System roles are p... | the_stack_v2_python_sparse | cohesity_management_sdk/models/role.py | cohesity/management-sdk-python | train | 24 |
9b1b60a94c34ff4b295439abdff7378bfeabbe87 | [
"self.file_data = []\nself.header = {}\ntot_filepath = 'Data/WDCGG-SurfaceData/' + country + '/'\ntot_filepath += load_filename + '.dat'\nwith open(tot_filepath, 'rb') as file:\n for row in file:\n string_row = row.decode()\n if string_row[0] == 'C':\n try:\n key, value = ... | <|body_start_0|>
self.file_data = []
self.header = {}
tot_filepath = 'Data/WDCGG-SurfaceData/' + country + '/'
tot_filepath += load_filename + '.dat'
with open(tot_filepath, 'rb') as file:
for row in file:
string_row = row.decode()
if s... | Defines a child class of AtmosGasTS, with methods used to read in and parse the .dat files used by the WDCGG: http://ds.data.jma.go.jp/gmd/wdcgg/wdcgg.html | WDCGG_TS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WDCGG_TS:
"""Defines a child class of AtmosGasTS, with methods used to read in and parse the .dat files used by the WDCGG: http://ds.data.jma.go.jp/gmd/wdcgg/wdcgg.html"""
def __init__(self, country, load_filename):
"""Initialises the class based on data found in the .dat files. coun... | stack_v2_sparse_classes_36k_train_022716 | 28,351 | no_license | [
{
"docstring": "Initialises the class based on data found in the .dat files. country -- string; the nation where the data came from, this will be used in filepaths and plot titles; so make sure the folders exit before run time. load_filename -- string; the file name/file path + file name where the .dat file is ... | 2 | stack_v2_sparse_classes_30k_train_015396 | Implement the Python class `WDCGG_TS` described below.
Class description:
Defines a child class of AtmosGasTS, with methods used to read in and parse the .dat files used by the WDCGG: http://ds.data.jma.go.jp/gmd/wdcgg/wdcgg.html
Method signatures and docstrings:
- def __init__(self, country, load_filename): Initiali... | Implement the Python class `WDCGG_TS` described below.
Class description:
Defines a child class of AtmosGasTS, with methods used to read in and parse the .dat files used by the WDCGG: http://ds.data.jma.go.jp/gmd/wdcgg/wdcgg.html
Method signatures and docstrings:
- def __init__(self, country, load_filename): Initiali... | 69c3beb334cb64b257c4496607a9b70dd220098b | <|skeleton|>
class WDCGG_TS:
"""Defines a child class of AtmosGasTS, with methods used to read in and parse the .dat files used by the WDCGG: http://ds.data.jma.go.jp/gmd/wdcgg/wdcgg.html"""
def __init__(self, country, load_filename):
"""Initialises the class based on data found in the .dat files. coun... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WDCGG_TS:
"""Defines a child class of AtmosGasTS, with methods used to read in and parse the .dat files used by the WDCGG: http://ds.data.jma.go.jp/gmd/wdcgg/wdcgg.html"""
def __init__(self, country, load_filename):
"""Initialises the class based on data found in the .dat files. country -- string... | the_stack_v2_python_sparse | ScriptsMisc/AtmosGasTSclass (old).py | tmed2/Atmos2016 | train | 0 |
ad043916760f147af32ec349d478ca7f3ed6a06c | [
"Parametre.__init__(self, 'détruire', 'destroy')\nself.schema = '<element_observable>'\nself.aide_courte = 'détruit votre bonhomme de neige'\nself.aide_longue = 'Cette commande permet de détruire un bonhomme de neige dont vous êtes le créateur. Vous ne pouvez utiliser cette commande pour détruire les bonhommes des ... | <|body_start_0|>
Parametre.__init__(self, 'détruire', 'destroy')
self.schema = '<element_observable>'
self.aide_courte = 'détruit votre bonhomme de neige'
self.aide_longue = 'Cette commande permet de détruire un bonhomme de neige dont vous êtes le créateur. Vous ne pouvez utiliser cette ... | Commande 'neige détruire' | PrmDetruire | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmDetruire:
"""Commande 'neige détruire'"""
def __init__(self):
"""Constructeur du paramètre."""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Méthode d'interprétation de commande"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022717 | 3,697 | permissive | [
{
"docstring": "Constructeur du paramètre.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Méthode d'interprétation de commande",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018172 | Implement the Python class `PrmDetruire` described below.
Class description:
Commande 'neige détruire'
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre.
- def interpreter(self, personnage, dic_masques): Méthode d'interprétation de commande | Implement the Python class `PrmDetruire` described below.
Class description:
Commande 'neige détruire'
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre.
- def interpreter(self, personnage, dic_masques): Méthode d'interprétation de commande
<|skeleton|>
class PrmDetruire:
"""Comma... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmDetruire:
"""Commande 'neige détruire'"""
def __init__(self):
"""Constructeur du paramètre."""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Méthode d'interprétation de commande"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrmDetruire:
"""Commande 'neige détruire'"""
def __init__(self):
"""Constructeur du paramètre."""
Parametre.__init__(self, 'détruire', 'destroy')
self.schema = '<element_observable>'
self.aide_courte = 'détruit votre bonhomme de neige'
self.aide_longue = 'Cette com... | the_stack_v2_python_sparse | src/primaires/salle/commandes/neige/detruire.py | vincent-lg/tsunami | train | 5 |
a01b187426a4943e961f3ee5147b9f65bdcd16a2 | [
"scores = tf.linalg.matmul(user_embeddings, candidate_embeddings, transpose_b=True)\nscores = tf.math.reduce_max(scores, axis=1)\nbatch_size = tf.shape(scores)[0]\nnum_candidates = tf.shape(scores)[-1]\nlabels = tf.eye(batch_size, num_candidates)\nif self._temperature is not None:\n scores = scores / self._tempe... | <|body_start_0|>
scores = tf.linalg.matmul(user_embeddings, candidate_embeddings, transpose_b=True)
scores = tf.math.reduce_max(scores, axis=1)
batch_size = tf.shape(scores)[0]
num_candidates = tf.shape(scores)[-1]
labels = tf.eye(batch_size, num_candidates)
if self._temp... | Extends the tfrs retrieval task to support multiple user representation (MUR). This class modifies the call function to support MUR. See base class for more details. For details on MUR see http://shortn/_PO6OdvUuAs. | MultiShotRetrievalTask | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiShotRetrievalTask:
"""Extends the tfrs retrieval task to support multiple user representation (MUR). This class modifies the call function to support MUR. See base class for more details. For details on MUR see http://shortn/_PO6OdvUuAs."""
def call(self, user_embeddings, candidate_embe... | stack_v2_sparse_classes_36k_train_022718 | 10,488 | permissive | [
{
"docstring": "Computes the loss function for next-item prediction. While computing the loss, the next-item's embedding is used as positive, while remaining items in the batch are negatives (in-batch negatives). Args: user_embeddings: User Embeddings [B, H, D] from the user tower, where H corresponds to the nu... | 2 | null | Implement the Python class `MultiShotRetrievalTask` described below.
Class description:
Extends the tfrs retrieval task to support multiple user representation (MUR). This class modifies the call function to support MUR. See base class for more details. For details on MUR see http://shortn/_PO6OdvUuAs.
Method signatu... | Implement the Python class `MultiShotRetrievalTask` described below.
Class description:
Extends the tfrs retrieval task to support multiple user representation (MUR). This class modifies the call function to support MUR. See base class for more details. For details on MUR see http://shortn/_PO6OdvUuAs.
Method signatu... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class MultiShotRetrievalTask:
"""Extends the tfrs retrieval task to support multiple user representation (MUR). This class modifies the call function to support MUR. See base class for more details. For details on MUR see http://shortn/_PO6OdvUuAs."""
def call(self, user_embeddings, candidate_embe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiShotRetrievalTask:
"""Extends the tfrs retrieval task to support multiple user representation (MUR). This class modifies the call function to support MUR. See base class for more details. For details on MUR see http://shortn/_PO6OdvUuAs."""
def call(self, user_embeddings, candidate_embeddings, sampl... | the_stack_v2_python_sparse | multiple_user_representations/models/task.py | Jimmy-INL/google-research | train | 1 |
0cbb2057d014f5c58a1cc4fd64588a9067d597ab | [
"data = '{\"sex\":\"S01\",\"isFather\":\"F04\",\"attributeValue\":\"V00\",\"grade\":\"G07\",\"belongSchoolId\":24,\"intentLevel\":\"I02\",\"businessType\":\"B01\",\"custStatus\":\"S01\",\"custType\":\"T00\",\"custName\":\"%s\",\"schoolId\":\"33\",\"schoolName\":\"四基初级中学\",\"infoId\":1073,\"infoType\":\"T01\",\"info... | <|body_start_0|>
data = '{"sex":"S01","isFather":"F04","attributeValue":"V00","grade":"G07","belongSchoolId":24,"intentLevel":"I02","businessType":"B01","custStatus":"S01","custType":"T00","custName":"%s","schoolId":"33","schoolName":"四基初级中学","infoId":1073,"infoType":"T01","infoName":"高分云信息单","phoneInfo":"13800... | CrmRequest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CrmRequest:
def save_customer_info(customer_name):
"""输入客户名称生成客户信息 @param customer_name: @return:"""
<|body_0|>
def allot_order(customer_id):
"""将客户id分单给高分云顾问2 @param customer_id: @return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = '{"se... | stack_v2_sparse_classes_36k_train_022719 | 1,384 | no_license | [
{
"docstring": "输入客户名称生成客户信息 @param customer_name: @return:",
"name": "save_customer_info",
"signature": "def save_customer_info(customer_name)"
},
{
"docstring": "将客户id分单给高分云顾问2 @param customer_id: @return:",
"name": "allot_order",
"signature": "def allot_order(customer_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013717 | Implement the Python class `CrmRequest` described below.
Class description:
Implement the CrmRequest class.
Method signatures and docstrings:
- def save_customer_info(customer_name): 输入客户名称生成客户信息 @param customer_name: @return:
- def allot_order(customer_id): 将客户id分单给高分云顾问2 @param customer_id: @return: | Implement the Python class `CrmRequest` described below.
Class description:
Implement the CrmRequest class.
Method signatures and docstrings:
- def save_customer_info(customer_name): 输入客户名称生成客户信息 @param customer_name: @return:
- def allot_order(customer_id): 将客户id分单给高分云顾问2 @param customer_id: @return:
<|skeleton|>
c... | 16bd1ecf5d1c7afa02a3721effb8a0bf078aed67 | <|skeleton|>
class CrmRequest:
def save_customer_info(customer_name):
"""输入客户名称生成客户信息 @param customer_name: @return:"""
<|body_0|>
def allot_order(customer_id):
"""将客户id分单给高分云顾问2 @param customer_id: @return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CrmRequest:
def save_customer_info(customer_name):
"""输入客户名称生成客户信息 @param customer_name: @return:"""
data = '{"sex":"S01","isFather":"F04","attributeValue":"V00","grade":"G07","belongSchoolId":24,"intentLevel":"I02","businessType":"B01","custStatus":"S01","custType":"T00","custName":"%s","scho... | the_stack_v2_python_sparse | func/api_request.py | quanbanno2/new_crm_poium | train | 0 | |
0164f46ccddbd5226c11e19a91b49259827a35e3 | [
"n = len(array)\nif k > n:\n return []\nresult = []\nfor i in range(n - k + 1):\n window = set()\n for j in range(i, i + k):\n window.add(array[j])\n result.append(len(window))\nreturn result",
"n = len(array)\nif k > n:\n return []\nwindow = dict()\nfor i in range(k):\n window[array[i]] ... | <|body_start_0|>
n = len(array)
if k > n:
return []
result = []
for i in range(n - k + 1):
window = set()
for j in range(i, i + k):
window.add(array[j])
result.append(len(window))
return result
<|end_body_0|>
<|body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def count_distinct_brute(self, array, k):
"""Brute force algorithm. Time complexity: O(n * k). Space complexity: O(k), n is len(array)."""
<|body_0|>
def count_distinct(self, array, k):
"""Improved algorithm using dictionary. Time complexity: O(n). Space co... | stack_v2_sparse_classes_36k_train_022720 | 2,318 | no_license | [
{
"docstring": "Brute force algorithm. Time complexity: O(n * k). Space complexity: O(k), n is len(array).",
"name": "count_distinct_brute",
"signature": "def count_distinct_brute(self, array, k)"
},
{
"docstring": "Improved algorithm using dictionary. Time complexity: O(n). Space complexity: O(... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def count_distinct_brute(self, array, k): Brute force algorithm. Time complexity: O(n * k). Space complexity: O(k), n is len(array).
- def count_distinct(self, array, k): Improve... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def count_distinct_brute(self, array, k): Brute force algorithm. Time complexity: O(n * k). Space complexity: O(k), n is len(array).
- def count_distinct(self, array, k): Improve... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def count_distinct_brute(self, array, k):
"""Brute force algorithm. Time complexity: O(n * k). Space complexity: O(k), n is len(array)."""
<|body_0|>
def count_distinct(self, array, k):
"""Improved algorithm using dictionary. Time complexity: O(n). Space co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def count_distinct_brute(self, array, k):
"""Brute force algorithm. Time complexity: O(n * k). Space complexity: O(k), n is len(array)."""
n = len(array)
if k > n:
return []
result = []
for i in range(n - k + 1):
window = set()
... | the_stack_v2_python_sparse | Hashing/distinct_numbers_in_window.py | vladn90/Algorithms | train | 0 | |
ef8eb5e374ad0d9bd213a7d745fa9d6a90801a0e | [
"script_dir = os.path.dirname(__file__)\nprint('Training faces. It will take a few seconds.') if config.DEBUG else None\nself.__image_paths = [os.path.join(script_dir, 'Images/1.jpg'), os.path.join(script_dir, 'Images/2.jpg'), os.path.join(script_dir, 'Images/3.jpg'), os.path.join(script_dir, 'Images/4.jpg'), os.pa... | <|body_start_0|>
script_dir = os.path.dirname(__file__)
print('Training faces. It will take a few seconds.') if config.DEBUG else None
self.__image_paths = [os.path.join(script_dir, 'Images/1.jpg'), os.path.join(script_dir, 'Images/2.jpg'), os.path.join(script_dir, 'Images/3.jpg'), os.path.join(... | FaceTraining | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaceTraining:
def __init__(self):
"""init the model for training and init the images path."""
<|body_0|>
def __train_images_and_labels(self):
"""get the faces from the image & set the id of a face [we set it to 1]"""
<|body_1|>
def __save_train_data(self... | stack_v2_sparse_classes_36k_train_022721 | 2,254 | no_license | [
{
"docstring": "init the model for training and init the images path.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "get the faces from the image & set the id of a face [we set it to 1]",
"name": "__train_images_and_labels",
"signature": "def __train_images_an... | 3 | stack_v2_sparse_classes_30k_train_005464 | Implement the Python class `FaceTraining` described below.
Class description:
Implement the FaceTraining class.
Method signatures and docstrings:
- def __init__(self): init the model for training and init the images path.
- def __train_images_and_labels(self): get the faces from the image & set the id of a face [we s... | Implement the Python class `FaceTraining` described below.
Class description:
Implement the FaceTraining class.
Method signatures and docstrings:
- def __init__(self): init the model for training and init the images path.
- def __train_images_and_labels(self): get the faces from the image & set the id of a face [we s... | 607e459d737ac689d6974bf05f452abf89cbdfe2 | <|skeleton|>
class FaceTraining:
def __init__(self):
"""init the model for training and init the images path."""
<|body_0|>
def __train_images_and_labels(self):
"""get the faces from the image & set the id of a face [we set it to 1]"""
<|body_1|>
def __save_train_data(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FaceTraining:
def __init__(self):
"""init the model for training and init the images path."""
script_dir = os.path.dirname(__file__)
print('Training faces. It will take a few seconds.') if config.DEBUG else None
self.__image_paths = [os.path.join(script_dir, 'Images/1.jpg'), os... | the_stack_v2_python_sparse | Measurements/FaceRecognition/faceTraining.py | alexshachor/TheBackEye | train | 0 | |
59042286e6ae0651a423c76820fd3678c5ad77ed | [
"m, n = (len(s), len(t))\nres = 0\nfor i in range(m):\n for j in range(n):\n k = 0\n diff = 0\n while i + k < m and j + k < n:\n if s[i + k] != t[j + k]:\n diff += 1\n if diff >= 2:\n break\n if diff == 1:\n res +=... | <|body_start_0|>
m, n = (len(s), len(t))
res = 0
for i in range(m):
for j in range(n):
k = 0
diff = 0
while i + k < m and j + k < n:
if s[i + k] != t[j + k]:
diff += 1
if d... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countSubstrings(self, s: str, t: str) -> int:
"""只有一个字符不同的子串对数"""
<|body_0|>
def countSubstrings2(self, s: str, t: str) -> int:
"""不同字符=相同前缀+不同字符+相同后缀 因此需要处理出前后缀的lcp(最长公共前缀)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
m, n = (len(s... | stack_v2_sparse_classes_36k_train_022722 | 2,414 | no_license | [
{
"docstring": "只有一个字符不同的子串对数",
"name": "countSubstrings",
"signature": "def countSubstrings(self, s: str, t: str) -> int"
},
{
"docstring": "不同字符=相同前缀+不同字符+相同后缀 因此需要处理出前后缀的lcp(最长公共前缀)",
"name": "countSubstrings2",
"signature": "def countSubstrings2(self, s: str, t: str) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubstrings(self, s: str, t: str) -> int: 只有一个字符不同的子串对数
- def countSubstrings2(self, s: str, t: str) -> int: 不同字符=相同前缀+不同字符+相同后缀 因此需要处理出前后缀的lcp(最长公共前缀) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubstrings(self, s: str, t: str) -> int: 只有一个字符不同的子串对数
- def countSubstrings2(self, s: str, t: str) -> int: 不同字符=相同前缀+不同字符+相同后缀 因此需要处理出前后缀的lcp(最长公共前缀)
<|skeleton|>
clas... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def countSubstrings(self, s: str, t: str) -> int:
"""只有一个字符不同的子串对数"""
<|body_0|>
def countSubstrings2(self, s: str, t: str) -> int:
"""不同字符=相同前缀+不同字符+相同后缀 因此需要处理出前后缀的lcp(最长公共前缀)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countSubstrings(self, s: str, t: str) -> int:
"""只有一个字符不同的子串对数"""
m, n = (len(s), len(t))
res = 0
for i in range(m):
for j in range(n):
k = 0
diff = 0
while i + k < m and j + k < n:
if... | the_stack_v2_python_sparse | 22_专题/枚举/1638. 统计只差一个字符的子串数目-枚举起点.py | 981377660LMT/algorithm-study | train | 225 | |
da4755eb92e28f2125378c1a23502faca25d19e2 | [
"specs_adhesion_flex: AdhesionFlexPlugin = self.specs.adhesion_flex\nmolecules = specs_adhesion_flex.molecules\nfor idx1 in range(len(molecules)):\n for idx2 in range(idx1, len(molecules)):\n m1, m2 = (molecules[idx1], molecules[idx2])\n self.add_steering_param(name=f'{m1}-{m2}', val=specs_adhesion... | <|body_start_0|>
specs_adhesion_flex: AdhesionFlexPlugin = self.specs.adhesion_flex
molecules = specs_adhesion_flex.molecules
for idx1 in range(len(molecules)):
for idx2 in range(idx1, len(molecules)):
m1, m2 = (molecules[idx1], molecules[idx2])
self.a... | AdhesionDemoSteppable | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdhesionDemoSteppable:
def add_steering_panel(self):
"""Adds a steering panel and populates with available data in AdhesionFlex plugin for changing parameters on-the-fly by the user during simulation execution."""
<|body_0|>
def process_steering_panel_data(self):
"""... | stack_v2_sparse_classes_36k_train_022723 | 4,321 | permissive | [
{
"docstring": "Adds a steering panel and populates with available data in AdhesionFlex plugin for changing parameters on-the-fly by the user during simulation execution.",
"name": "add_steering_panel",
"signature": "def add_steering_panel(self)"
},
{
"docstring": "Updates AdhesionFlex plugin da... | 2 | null | Implement the Python class `AdhesionDemoSteppable` described below.
Class description:
Implement the AdhesionDemoSteppable class.
Method signatures and docstrings:
- def add_steering_panel(self): Adds a steering panel and populates with available data in AdhesionFlex plugin for changing parameters on-the-fly by the u... | Implement the Python class `AdhesionDemoSteppable` described below.
Class description:
Implement the AdhesionDemoSteppable class.
Method signatures and docstrings:
- def add_steering_panel(self): Adds a steering panel and populates with available data in AdhesionFlex plugin for changing parameters on-the-fly by the u... | 65a65eaa693a6d2b3aab303f9b41e71819f4eed4 | <|skeleton|>
class AdhesionDemoSteppable:
def add_steering_panel(self):
"""Adds a steering panel and populates with available data in AdhesionFlex plugin for changing parameters on-the-fly by the user during simulation execution."""
<|body_0|>
def process_steering_panel_data(self):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdhesionDemoSteppable:
def add_steering_panel(self):
"""Adds a steering panel and populates with available data in AdhesionFlex plugin for changing parameters on-the-fly by the user during simulation execution."""
specs_adhesion_flex: AdhesionFlexPlugin = self.specs.adhesion_flex
molec... | the_stack_v2_python_sparse | CompuCell3D/core/Demos/PyCoreSpecs/AdhesionDemo/Simulation/AdhesionDemo.py | CompuCell3D/CompuCell3D | train | 51 | |
6023e48a5387ae6c1ee868f7b9d784c25b6d5513 | [
"self.base_uri = clean_url.clean_url(app_server, self.BASE_PATH)\nself.app_server = app_server\nself.header_factory = header_factory",
"endpoint = 'applicationLogs/search'\nuri = f'{self.base_uri}/{endpoint}'\nparams = {'expand': expand, 'level': level, 'loginId': loginid, 'machineName': machine_name, 'orderBy': ... | <|body_start_0|>
self.base_uri = clean_url.clean_url(app_server, self.BASE_PATH)
self.app_server = app_server
self.header_factory = header_factory
<|end_body_0|>
<|body_start_1|>
endpoint = 'applicationLogs/search'
uri = f'{self.base_uri}/{endpoint}'
params = {'expand': ... | This operation returns application logs, based on the data passed in the request. | ApplicationLogs | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApplicationLogs:
"""This operation returns application logs, based on the data passed in the request."""
def __init__(self, app_server, header_factory):
"""Parameters ---------- app_server: str, optional This is the FQDN of the target QNXT app server header_factory: qnxt.authenticati... | stack_v2_sparse_classes_36k_train_022724 | 33,787 | no_license | [
{
"docstring": "Parameters ---------- app_server: str, optional This is the FQDN of the target QNXT app server header_factory: qnxt.authentication.RequestHeader, required This is a callable that generates the appropriate authentication headers for QNXT API requests",
"name": "__init__",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_test_001134 | Implement the Python class `ApplicationLogs` described below.
Class description:
This operation returns application logs, based on the data passed in the request.
Method signatures and docstrings:
- def __init__(self, app_server, header_factory): Parameters ---------- app_server: str, optional This is the FQDN of the... | Implement the Python class `ApplicationLogs` described below.
Class description:
This operation returns application logs, based on the data passed in the request.
Method signatures and docstrings:
- def __init__(self, app_server, header_factory): Parameters ---------- app_server: str, optional This is the FQDN of the... | 711b83a8091a50f86c09e0ed414c0fefceb39f36 | <|skeleton|>
class ApplicationLogs:
"""This operation returns application logs, based on the data passed in the request."""
def __init__(self, app_server, header_factory):
"""Parameters ---------- app_server: str, optional This is the FQDN of the target QNXT app server header_factory: qnxt.authenticati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApplicationLogs:
"""This operation returns application logs, based on the data passed in the request."""
def __init__(self, app_server, header_factory):
"""Parameters ---------- app_server: str, optional This is the FQDN of the target QNXT app server header_factory: qnxt.authentication.RequestHea... | the_stack_v2_python_sparse | qnxt/api/PlanIntegration.py | agenovia/QNXT-API | train | 0 |
c5aee47b26e10a6e78da39850cca9d7be94dbc94 | [
"word_set = set(wordDict)\ncache = {}\nreturn self.ans_1(s, word_set, cache)",
"if not s:\n return True\nfor i in range(len(s)):\n word = s[:i + 1]\n if word in word_set:\n tmp = self.ans_basic(s[i + 1:], word_set)\n if tmp is True:\n return True\nreturn False",
"if not s:\n ... | <|body_start_0|>
word_set = set(wordDict)
cache = {}
return self.ans_1(s, word_set, cache)
<|end_body_0|>
<|body_start_1|>
if not s:
return True
for i in range(len(s)):
word = s[:i + 1]
if word in word_set:
tmp = self.ans_basic... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_0|>
def ans_basic(self, s, word_set):
"""brute force :param s: :param word_set: :return:"""
<|body_1|>
def ans(self, s, word_set, cache):
... | stack_v2_sparse_classes_36k_train_022725 | 4,334 | no_license | [
{
"docstring": ":type s: str :type wordDict: List[str] :rtype: bool",
"name": "wordBreak",
"signature": "def wordBreak(self, s, wordDict)"
},
{
"docstring": "brute force :param s: :param word_set: :return:",
"name": "ans_basic",
"signature": "def ans_basic(self, s, word_set)"
},
{
... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- def ans_basic(self, s, word_set): brute force :param s: :param word_set: :return:
- def an... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordBreak(self, s, wordDict): :type s: str :type wordDict: List[str] :rtype: bool
- def ans_basic(self, s, word_set): brute force :param s: :param word_set: :return:
- def an... | cf4235170db3629b65790fd0855a8a72ac5886f7 | <|skeleton|>
class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
<|body_0|>
def ans_basic(self, s, word_set):
"""brute force :param s: :param word_set: :return:"""
<|body_1|>
def ans(self, s, word_set, cache):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def wordBreak(self, s, wordDict):
""":type s: str :type wordDict: List[str] :rtype: bool"""
word_set = set(wordDict)
cache = {}
return self.ans_1(s, word_set, cache)
def ans_basic(self, s, word_set):
"""brute force :param s: :param word_set: :return:"""
... | the_stack_v2_python_sparse | word_break.py | buxizhizhoum/leetcode | train | 1 | |
074f616a41123d13a08d584651f97c99aad3f450 | [
"self._filename: str = filename\nself._seen_so_far: float = 0\nself._lock = threading.Lock()\nself._size: float = 0\nif bucket and client:\n if not version_id:\n self._size = client.head_object(Bucket=bucket, Key=filename).get('ContentLength')\n else:\n self._size = client.head_object(Bucket=buc... | <|body_start_0|>
self._filename: str = filename
self._seen_so_far: float = 0
self._lock = threading.Lock()
self._size: float = 0
if bucket and client:
if not version_id:
self._size = client.head_object(Bucket=bucket, Key=filename).get('ContentLength')
... | The progress bar for s3 transfering. Helper class for displaying s3 upload/download/copy percentage. Upload: spcify the filename only. Download/Copy: require a bucket and client parameter as well as the filename. This class should be used within the callback of the S3Transfer class from boto. references: https://boto3.... | S3Progress | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S3Progress:
"""The progress bar for s3 transfering. Helper class for displaying s3 upload/download/copy percentage. Upload: spcify the filename only. Download/Copy: require a bucket and client parameter as well as the filename. This class should be used within the callback of the S3Transfer class... | stack_v2_sparse_classes_36k_train_022726 | 3,490 | permissive | [
{
"docstring": "Construct the progress bar instance.",
"name": "__init__",
"signature": "def __init__(self, filename: str, bucket: str=None, client=None, version_id: str=None) -> None"
},
{
"docstring": "Create the bar. Locking the thread to a single file.",
"name": "__call__",
"signatur... | 3 | stack_v2_sparse_classes_30k_train_020730 | Implement the Python class `S3Progress` described below.
Class description:
The progress bar for s3 transfering. Helper class for displaying s3 upload/download/copy percentage. Upload: spcify the filename only. Download/Copy: require a bucket and client parameter as well as the filename. This class should be used with... | Implement the Python class `S3Progress` described below.
Class description:
The progress bar for s3 transfering. Helper class for displaying s3 upload/download/copy percentage. Upload: spcify the filename only. Download/Copy: require a bucket and client parameter as well as the filename. This class should be used with... | 4abefb2301f7b489b11ed3f0b303faafa5941d5b | <|skeleton|>
class S3Progress:
"""The progress bar for s3 transfering. Helper class for displaying s3 upload/download/copy percentage. Upload: spcify the filename only. Download/Copy: require a bucket and client parameter as well as the filename. This class should be used within the callback of the S3Transfer class... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class S3Progress:
"""The progress bar for s3 transfering. Helper class for displaying s3 upload/download/copy percentage. Upload: spcify the filename only. Download/Copy: require a bucket and client parameter as well as the filename. This class should be used within the callback of the S3Transfer class from boto. r... | the_stack_v2_python_sparse | fzfaws/s3/helper/s3progress.py | kazhala/fzf.aws | train | 68 |
390da47d77e1ccf961ac44f2f4ed5033cad2d1e7 | [
"if browser is None:\n self._browser_type = settings.DEFAULT_BROWSER\nelse:\n self._browser_type = browser\nself._driver = None",
"if self._browser_type.lower() == 'chrome':\n self._driver = webdriver.Chrome()\nelif self._browser_type.lower() == 'firefox':\n self._driver = webdriver.Firefox()\nelif se... | <|body_start_0|>
if browser is None:
self._browser_type = settings.DEFAULT_BROWSER
else:
self._browser_type = browser
self._driver = None
<|end_body_0|>
<|body_start_1|>
if self._browser_type.lower() == 'chrome':
self._driver = webdriver.Chrome()
... | BrowserEngine | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrowserEngine:
def __init__(self, browser=None):
"""初始化浏览器类型 :param browser:"""
<|body_0|>
def init_driver(self):
"""初始化驱动器 :return: 返回驱动器"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if browser is None:
self._browser_type = settings.... | stack_v2_sparse_classes_36k_train_022727 | 1,198 | permissive | [
{
"docstring": "初始化浏览器类型 :param browser:",
"name": "__init__",
"signature": "def __init__(self, browser=None)"
},
{
"docstring": "初始化驱动器 :return: 返回驱动器",
"name": "init_driver",
"signature": "def init_driver(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016193 | Implement the Python class `BrowserEngine` described below.
Class description:
Implement the BrowserEngine class.
Method signatures and docstrings:
- def __init__(self, browser=None): 初始化浏览器类型 :param browser:
- def init_driver(self): 初始化驱动器 :return: 返回驱动器 | Implement the Python class `BrowserEngine` described below.
Class description:
Implement the BrowserEngine class.
Method signatures and docstrings:
- def __init__(self, browser=None): 初始化浏览器类型 :param browser:
- def init_driver(self): 初始化驱动器 :return: 返回驱动器
<|skeleton|>
class BrowserEngine:
def __init__(self, bro... | ed360d5aa7f733991fbbc8ab5af96e739c9e1142 | <|skeleton|>
class BrowserEngine:
def __init__(self, browser=None):
"""初始化浏览器类型 :param browser:"""
<|body_0|>
def init_driver(self):
"""初始化驱动器 :return: 返回驱动器"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrowserEngine:
def __init__(self, browser=None):
"""初始化浏览器类型 :param browser:"""
if browser is None:
self._browser_type = settings.DEFAULT_BROWSER
else:
self._browser_type = browser
self._driver = None
def init_driver(self):
"""初始化驱动器 :return... | the_stack_v2_python_sparse | automated_testing/selenium_unittest_test/app/ui/base/browser_engine.py | tzytammy/requests_unittest | train | 0 | |
54cc47145c7dbb42c270432a4dbb8f12c5b962fe | [
"limit = request.GET.get('limit', 0)\npage = request.GET.get('page', 0)\nread = request.GET.get('read')\nevent_types = request.GET.getlist('eventTypes')\nquery_params = {}\nif read is not None:\n query_params['read'] = read\nif event_types:\n notifs = Notification.objects.filter(event_type__in=event_types, de... | <|body_start_0|>
limit = request.GET.get('limit', 0)
page = request.GET.get('page', 0)
read = request.GET.get('read')
event_types = request.GET.getlist('eventTypes')
query_params = {}
if read is not None:
query_params['read'] = read
if event_types:
... | ManageNotificationsView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManageNotificationsView:
def get(self, request, *args, **kwargs):
"""List all notifications of a certain event type."""
<|body_0|>
def patch(self, request, *args, **kwargs):
"""Mark notifications as read."""
<|body_1|>
def delete(self, request, pk, *args... | stack_v2_sparse_classes_36k_train_022728 | 3,880 | no_license | [
{
"docstring": "List all notifications of a certain event type.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Mark notifications as read.",
"name": "patch",
"signature": "def patch(self, request, *args, **kwargs)"
},
{
"docstring": "Ma... | 3 | null | Implement the Python class `ManageNotificationsView` described below.
Class description:
Implement the ManageNotificationsView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): List all notifications of a certain event type.
- def patch(self, request, *args, **kwargs): Mark notificat... | Implement the Python class `ManageNotificationsView` described below.
Class description:
Implement the ManageNotificationsView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): List all notifications of a certain event type.
- def patch(self, request, *args, **kwargs): Mark notificat... | 83f452436d5586b99ef2a9f327aab833ee794d1e | <|skeleton|>
class ManageNotificationsView:
def get(self, request, *args, **kwargs):
"""List all notifications of a certain event type."""
<|body_0|>
def patch(self, request, *args, **kwargs):
"""Mark notifications as read."""
<|body_1|>
def delete(self, request, pk, *args... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManageNotificationsView:
def get(self, request, *args, **kwargs):
"""List all notifications of a certain event type."""
limit = request.GET.get('limit', 0)
page = request.GET.get('page', 0)
read = request.GET.get('read')
event_types = request.GET.getlist('eventTypes')
... | the_stack_v2_python_sparse | server/portal/apps/notifications/views.py | Avila0000/Core-Portal | train | 0 | |
74e5c00dc399a0e241c416a4322a12f8a3d93523 | [
"self.assertEqual(Hit.objects.count(), 0)\ndata = {'id': -1, 'name': 'New York'}\nadd_or_create_from_uiselect(Hit, 'name', data)\nself.assertEqual(Hit.objects.count(), 1)\ntry:\n hit = Hit.objects.get(name='New York')\nexcept Hit.DoesNotExist:\n self.fail('Hit was not properly created by add_or_create_from_ui... | <|body_start_0|>
self.assertEqual(Hit.objects.count(), 0)
data = {'id': -1, 'name': 'New York'}
add_or_create_from_uiselect(Hit, 'name', data)
self.assertEqual(Hit.objects.count(), 1)
try:
hit = Hit.objects.get(name='New York')
except Hit.DoesNotExist:
... | HitFormTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HitFormTests:
def test_add_or_create_ui_select_new(self):
"""If the data from a UI Select form is -1, this means no model was selected. A new model should be created"""
<|body_0|>
def test_add_or_create_ui_select_get(self):
"""if passed a different id, it should fetc... | stack_v2_sparse_classes_36k_train_022729 | 11,225 | permissive | [
{
"docstring": "If the data from a UI Select form is -1, this means no model was selected. A new model should be created",
"name": "test_add_or_create_ui_select_new",
"signature": "def test_add_or_create_ui_select_new(self)"
},
{
"docstring": "if passed a different id, it should fetch that objec... | 2 | null | Implement the Python class `HitFormTests` described below.
Class description:
Implement the HitFormTests class.
Method signatures and docstrings:
- def test_add_or_create_ui_select_new(self): If the data from a UI Select form is -1, this means no model was selected. A new model should be created
- def test_add_or_cre... | Implement the Python class `HitFormTests` described below.
Class description:
Implement the HitFormTests class.
Method signatures and docstrings:
- def test_add_or_create_ui_select_new(self): If the data from a UI Select form is -1, this means no model was selected. A new model should be created
- def test_add_or_cre... | 07455a660fb2cb8bc91a54f7f12d150923678157 | <|skeleton|>
class HitFormTests:
def test_add_or_create_ui_select_new(self):
"""If the data from a UI Select form is -1, this means no model was selected. A new model should be created"""
<|body_0|>
def test_add_or_create_ui_select_get(self):
"""if passed a different id, it should fetc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HitFormTests:
def test_add_or_create_ui_select_new(self):
"""If the data from a UI Select form is -1, this means no model was selected. A new model should be created"""
self.assertEqual(Hit.objects.count(), 0)
data = {'id': -1, 'name': 'New York'}
add_or_create_from_uiselect(Hi... | the_stack_v2_python_sparse | otcore/hit/tests.py | NYULibraries/dlts-enm-tct-backend | train | 0 | |
a7a143974d7e072629cb0c492ede1794dad54509 | [
"n = len(array)\nleft = [1] * n\nfor i in range(1, n):\n left[i] = left[i - 1] * array[i - 1]\nright = [1] * n\nfor i in range(n - 2, -1, -1):\n right[i] = right[i + 1] * array[i + 1]\nreturn [left[i] * right[i] for i in range(n)]",
"n = len(array)\nresult = [1] * n\nfor i in range(1, n):\n result[i] = r... | <|body_start_0|>
n = len(array)
left = [1] * n
for i in range(1, n):
left[i] = left[i - 1] * array[i - 1]
right = [1] * n
for i in range(n - 2, -1, -1):
right[i] = right[i + 1] * array[i + 1]
return [left[i] * right[i] for i in range(n)]
<|end_body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def product_except_self_1(self, array):
"""Time complexity: O(n). Space complexity: O(n), n is len(array)."""
<|body_0|>
def product_except_self_2(self, array):
"""Time complexity: O(n). Space complexity: O(1), n is len(array). Output array isn't included i... | stack_v2_sparse_classes_36k_train_022730 | 2,824 | no_license | [
{
"docstring": "Time complexity: O(n). Space complexity: O(n), n is len(array).",
"name": "product_except_self_1",
"signature": "def product_except_self_1(self, array)"
},
{
"docstring": "Time complexity: O(n). Space complexity: O(1), n is len(array). Output array isn't included in space complex... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def product_except_self_1(self, array): Time complexity: O(n). Space complexity: O(n), n is len(array).
- def product_except_self_2(self, array): Time complexity: O(n). Space com... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def product_except_self_1(self, array): Time complexity: O(n). Space complexity: O(n), n is len(array).
- def product_except_self_2(self, array): Time complexity: O(n). Space com... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def product_except_self_1(self, array):
"""Time complexity: O(n). Space complexity: O(n), n is len(array)."""
<|body_0|>
def product_except_self_2(self, array):
"""Time complexity: O(n). Space complexity: O(1), n is len(array). Output array isn't included i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def product_except_self_1(self, array):
"""Time complexity: O(n). Space complexity: O(n), n is len(array)."""
n = len(array)
left = [1] * n
for i in range(1, n):
left[i] = left[i - 1] * array[i - 1]
right = [1] * n
for i in range(n - 2, -1,... | the_stack_v2_python_sparse | Arrays/product_array_except_self.py | vladn90/Algorithms | train | 0 | |
b1d88b1b73c3eac45e4a80b8428c5aeaec4aae90 | [
"has_cycle = False\none_step = head\ntwo_step = head\nwhile two_step and two_step.next:\n one_step = one_step.next\n two_step = two_step.next.next\n if one_step == two_step:\n has_cycle = True\n break\nif not has_cycle:\n return None\np = head\nstart = one_step.next\nwhile start:\n if s... | <|body_start_0|>
has_cycle = False
one_step = head
two_step = head
while two_step and two_step.next:
one_step = one_step.next
two_step = two_step.next.next
if one_step == two_step:
has_cycle = True
break
if not h... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def detectCycle1(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
has_cycle = False
one_step =... | stack_v2_sparse_classes_36k_train_022731 | 1,566 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "detectCycle1",
"signature": "def detectCycle1(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "detectCycle",
"signature": "def detectCycle(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013796 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def detectCycle1(self, head): :type head: ListNode :rtype: ListNode
- def detectCycle(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def detectCycle1(self, head): :type head: ListNode :rtype: ListNode
- def detectCycle(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def de... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def detectCycle1(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def detectCycle1(self, head):
""":type head: ListNode :rtype: ListNode"""
has_cycle = False
one_step = head
two_step = head
while two_step and two_step.next:
one_step = one_step.next
two_step = two_step.next.next
if one_step... | the_stack_v2_python_sparse | py/leetcode/142.py | wfeng1991/learnpy | train | 0 | |
593d7b30c5101b1b2c6f40305679d16a06bdd81f | [
"version = version.strip()\nself.repo.get_ready()\nmessage = ''\nif version == '0.17':\n message += f'There are {self.repo.number_of_016_files}'\nelif version == '0.16':\n message += f'There are {self.repo.number_of_017_files}'\nelse:\n num_016 = self.repo.number_of_016_files\n num_017 = self.repo.numbe... | <|body_start_0|>
version = version.strip()
self.repo.get_ready()
message = ''
if version == '0.17':
message += f'There are {self.repo.number_of_016_files}'
elif version == '0.16':
message += f'There are {self.repo.number_of_017_files}'
else:
... | ElmExtensions | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElmExtensions:
def elm_progress(self, channel: str, version: str) -> ChannelMessages:
"""give a version of elm to get me to tell you how many number files are on master"""
<|body_0|>
def elm_progress_on(self, channel: str, branch_name: str) -> ChannelMessages:
"""giv... | stack_v2_sparse_classes_36k_train_022732 | 17,998 | permissive | [
{
"docstring": "give a version of elm to get me to tell you how many number files are on master",
"name": "elm_progress",
"signature": "def elm_progress(self, channel: str, version: str) -> ChannelMessages"
},
{
"docstring": "give a version of elm to get me to tell you how many number files are ... | 4 | stack_v2_sparse_classes_30k_train_013385 | Implement the Python class `ElmExtensions` described below.
Class description:
Implement the ElmExtensions class.
Method signatures and docstrings:
- def elm_progress(self, channel: str, version: str) -> ChannelMessages: give a version of elm to get me to tell you how many number files are on master
- def elm_progres... | Implement the Python class `ElmExtensions` described below.
Class description:
Implement the ElmExtensions class.
Method signatures and docstrings:
- def elm_progress(self, channel: str, version: str) -> ChannelMessages: give a version of elm to get me to tell you how many number files are on master
- def elm_progres... | 3db3d5eaedc8d7a1aa6d4adfff79385988717eec | <|skeleton|>
class ElmExtensions:
def elm_progress(self, channel: str, version: str) -> ChannelMessages:
"""give a version of elm to get me to tell you how many number files are on master"""
<|body_0|>
def elm_progress_on(self, channel: str, branch_name: str) -> ChannelMessages:
"""giv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElmExtensions:
def elm_progress(self, channel: str, version: str) -> ChannelMessages:
"""give a version of elm to get me to tell you how many number files are on master"""
version = version.strip()
self.repo.get_ready()
message = ''
if version == '0.17':
mes... | the_stack_v2_python_sparse | slack_today_i_did/extensions.py | eeue56/slack-today-i-did | train | 3 | |
e60364b51f045bc9254cc9b1ad0d7b9a90fb3113 | [
"if not already_authorized(request):\n response = self.wrap_json_response(code=ReturnCode.UNAUTHORIZED)\n return JsonResponse(response, safe=False)\nopen_id = request.session.get('open_id')\nuser = User.objects.get(open_id=open_id)\ndata = {}\ndata['open_id'] = user.open_id\ndata['focus'] = {}\ndata['focus'][... | <|body_start_0|>
if not already_authorized(request):
response = self.wrap_json_response(code=ReturnCode.UNAUTHORIZED)
return JsonResponse(response, safe=False)
open_id = request.session.get('open_id')
user = User.objects.get(open_id=open_id)
data = {}
data... | 关注的城市、股票和星座 | UserView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserView:
"""关注的城市、股票和星座"""
def get(self, request):
"""获取用户的数据"""
<|body_0|>
def post(self, request):
"""修改用户的数据"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not already_authorized(request):
response = self.wrap_json_response(c... | stack_v2_sparse_classes_36k_train_022733 | 5,687 | no_license | [
{
"docstring": "获取用户的数据",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "修改用户的数据",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002670 | Implement the Python class `UserView` described below.
Class description:
关注的城市、股票和星座
Method signatures and docstrings:
- def get(self, request): 获取用户的数据
- def post(self, request): 修改用户的数据 | Implement the Python class `UserView` described below.
Class description:
关注的城市、股票和星座
Method signatures and docstrings:
- def get(self, request): 获取用户的数据
- def post(self, request): 修改用户的数据
<|skeleton|>
class UserView:
"""关注的城市、股票和星座"""
def get(self, request):
"""获取用户的数据"""
<|body_0|>
de... | 9d0d27e6e29671bd5d38305dac828a61b01095cb | <|skeleton|>
class UserView:
"""关注的城市、股票和星座"""
def get(self, request):
"""获取用户的数据"""
<|body_0|>
def post(self, request):
"""修改用户的数据"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserView:
"""关注的城市、股票和星座"""
def get(self, request):
"""获取用户的数据"""
if not already_authorized(request):
response = self.wrap_json_response(code=ReturnCode.UNAUTHORIZED)
return JsonResponse(response, safe=False)
open_id = request.session.get('open_id')
... | the_stack_v2_python_sparse | backend_ch3_sec1/authorization/views.py | liuwenwen163/django_wx_mini_program | train | 0 |
4e4b1a7ff5ce756e7f2fee2ea11ec8f8bd3d1408 | [
"self.params = params\nself.task_labels = task_labels\nself.cache_dir = tempfile.gettempdir()",
"tf.compat.v1.reset_default_graph()\nconfig = transformers.BertConfig.from_pretrained(os.path.join(self.params.bert_path, 'config.json'), cache_dir=self.cache_dir)\nmodel = transformers.TFBertModel.from_pretrained(os.p... | <|body_start_0|>
self.params = params
self.task_labels = task_labels
self.cache_dir = tempfile.gettempdir()
<|end_body_0|>
<|body_start_1|>
tf.compat.v1.reset_default_graph()
config = transformers.BertConfig.from_pretrained(os.path.join(self.params.bert_path, 'config.json'), cac... | Classifier can be single-task, or multi-task. | Classifier | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Classifier:
"""Classifier can be single-task, or multi-task."""
def __init__(self, params, task_labels='majority'):
"""Creates a Classifier instance for predicting task_labels. Args: params: a Params instance which includes the hyperparameters of the model task_labels: list of label ... | stack_v2_sparse_classes_36k_train_022734 | 7,260 | permissive | [
{
"docstring": "Creates a Classifier instance for predicting task_labels. Args: params: a Params instance which includes the hyperparameters of the model task_labels: list of label names to be predicted from text.",
"name": "__init__",
"signature": "def __init__(self, params, task_labels='majority')"
... | 5 | stack_v2_sparse_classes_30k_train_003865 | Implement the Python class `Classifier` described below.
Class description:
Classifier can be single-task, or multi-task.
Method signatures and docstrings:
- def __init__(self, params, task_labels='majority'): Creates a Classifier instance for predicting task_labels. Args: params: a Params instance which includes the... | Implement the Python class `Classifier` described below.
Class description:
Classifier can be single-task, or multi-task.
Method signatures and docstrings:
- def __init__(self, params, task_labels='majority'): Creates a Classifier instance for predicting task_labels. Args: params: a Params instance which includes the... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class Classifier:
"""Classifier can be single-task, or multi-task."""
def __init__(self, params, task_labels='majority'):
"""Creates a Classifier instance for predicting task_labels. Args: params: a Params instance which includes the hyperparameters of the model task_labels: list of label ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Classifier:
"""Classifier can be single-task, or multi-task."""
def __init__(self, params, task_labels='majority'):
"""Creates a Classifier instance for predicting task_labels. Args: params: a Params instance which includes the hyperparameters of the model task_labels: list of label names to be p... | the_stack_v2_python_sparse | multi_annotator/classifier.py | Jimmy-INL/google-research | train | 1 |
a47f9498120a29e4f16877eea28280dd4f216978 | [
"if self.INDEX_NAME is None:\n raise Exception('Name of the index cannot be empty.Redefine index name in child class')\nif self.FIELDS is None:\n raise Exception('Fields cannot be empty. Redefine fields in child class')",
"if ES_CLIENT is None:\n logging.warning('Elasticsearch is disabled. In order to pr... | <|body_start_0|>
if self.INDEX_NAME is None:
raise Exception('Name of the index cannot be empty.Redefine index name in child class')
if self.FIELDS is None:
raise Exception('Fields cannot be empty. Redefine fields in child class')
<|end_body_0|>
<|body_start_1|>
if ES_CL... | Base service for searching. | SearchService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchService:
"""Base service for searching."""
def __init__(self):
"""Initialize instance. Raise exception if index name or index fields are empty."""
<|body_0|>
def find(self, query_string, *companies):
"""Search by given string."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k_train_022735 | 1,536 | no_license | [
{
"docstring": "Initialize instance. Raise exception if index name or index fields are empty.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Search by given string.",
"name": "find",
"signature": "def find(self, query_string, *companies)"
}
] | 2 | null | Implement the Python class `SearchService` described below.
Class description:
Base service for searching.
Method signatures and docstrings:
- def __init__(self): Initialize instance. Raise exception if index name or index fields are empty.
- def find(self, query_string, *companies): Search by given string. | Implement the Python class `SearchService` described below.
Class description:
Base service for searching.
Method signatures and docstrings:
- def __init__(self): Initialize instance. Raise exception if index name or index fields are empty.
- def find(self, query_string, *companies): Search by given string.
<|skelet... | 252b0ebd77eefbcc945a0efc3068cc3421f46d5f | <|skeleton|>
class SearchService:
"""Base service for searching."""
def __init__(self):
"""Initialize instance. Raise exception if index name or index fields are empty."""
<|body_0|>
def find(self, query_string, *companies):
"""Search by given string."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SearchService:
"""Base service for searching."""
def __init__(self):
"""Initialize instance. Raise exception if index name or index fields are empty."""
if self.INDEX_NAME is None:
raise Exception('Name of the index cannot be empty.Redefine index name in child class')
... | the_stack_v2_python_sparse | common/services/search_service.py | vsokoltsov/Interview360Server | train | 2 |
7a801e9acdcc8f475f7c970f255d822778380653 | [
"self.logger = logger\nself.is_trained = False\nself.supported_formats = ['pkl', 'onnx', 'pmml']\nself.name = 'DSVM'\nself.centroids = None\nself.weights = None\nself.sigma = None",
"NP = X_b.shape[0]\nNC = self.centroids.shape[0]\nXC2 = -2 * np.dot(X_b, self.centroids.T)\nXC2 += np.sum(np.multiply(X_b, X_b), axi... | <|body_start_0|>
self.logger = logger
self.is_trained = False
self.supported_formats = ['pkl', 'onnx', 'pmml']
self.name = 'DSVM'
self.centroids = None
self.weights = None
self.sigma = None
<|end_body_0|>
<|body_start_1|>
NP = X_b.shape[0]
NC = se... | This class contains the Distributed SVM model. | DSVM_model | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DSVM_model:
"""This class contains the Distributed SVM model."""
def __init__(self, logger):
"""Create a :class:`DSVM_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance."""
<|body_0|>
def predict(self, X_b):
"""Use th... | stack_v2_sparse_classes_36k_train_022736 | 19,645 | permissive | [
{
"docstring": "Create a :class:`DSVM_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance.",
"name": "__init__",
"signature": "def __init__(self, logger)"
},
{
"docstring": "Use the model to predict new outputs given for an unlabeled dataset. Paramete... | 2 | stack_v2_sparse_classes_30k_train_011192 | Implement the Python class `DSVM_model` described below.
Class description:
This class contains the Distributed SVM model.
Method signatures and docstrings:
- def __init__(self, logger): Create a :class:`DSVM_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance.
- def predi... | Implement the Python class `DSVM_model` described below.
Class description:
This class contains the Distributed SVM model.
Method signatures and docstrings:
- def __init__(self, logger): Create a :class:`DSVM_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance.
- def predi... | ccc0a7674a04ae0d00bedc38893b33184c5f68c6 | <|skeleton|>
class DSVM_model:
"""This class contains the Distributed SVM model."""
def __init__(self, logger):
"""Create a :class:`DSVM_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance."""
<|body_0|>
def predict(self, X_b):
"""Use th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DSVM_model:
"""This class contains the Distributed SVM model."""
def __init__(self, logger):
"""Create a :class:`DSVM_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance."""
self.logger = logger
self.is_trained = False
self.supp... | the_stack_v2_python_sparse | MMLL/models/POM1/DSVM/DSVM.py | Musketeer-H2020/MMLL-Robust | train | 0 |
41d20cd35e9631d277dae0697dec0164458843dd | [
"_sorted = [0] * len(_list)\nc_length = max(_list) + 1\nc_list = [0] * c_length\n' Populate c list from provided unsorted list'\nfor number in _list:\n c_list[number] += 1\nc_list = self.run_c_prime(c_list)\n' Populate sorted list'\nfor each in _list:\n _sorted[c_list[each] - 1] = each\n c_list[each] -= 1\... | <|body_start_0|>
_sorted = [0] * len(_list)
c_length = max(_list) + 1
c_list = [0] * c_length
' Populate c list from provided unsorted list'
for number in _list:
c_list[number] += 1
c_list = self.run_c_prime(c_list)
' Populate sorted list'
for ... | countSort | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class countSort:
def run_sort(self, _list):
"""Sort list of positive integers using the countSort Algorithm"""
<|body_0|>
def run_c_prime(self, c_list):
"""Build C` list by summing the x and x-1 elements of the list"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_022737 | 1,107 | no_license | [
{
"docstring": "Sort list of positive integers using the countSort Algorithm",
"name": "run_sort",
"signature": "def run_sort(self, _list)"
},
{
"docstring": "Build C` list by summing the x and x-1 elements of the list",
"name": "run_c_prime",
"signature": "def run_c_prime(self, c_list)"... | 2 | stack_v2_sparse_classes_30k_train_009400 | Implement the Python class `countSort` described below.
Class description:
Implement the countSort class.
Method signatures and docstrings:
- def run_sort(self, _list): Sort list of positive integers using the countSort Algorithm
- def run_c_prime(self, c_list): Build C` list by summing the x and x-1 elements of the ... | Implement the Python class `countSort` described below.
Class description:
Implement the countSort class.
Method signatures and docstrings:
- def run_sort(self, _list): Sort list of positive integers using the countSort Algorithm
- def run_c_prime(self, c_list): Build C` list by summing the x and x-1 elements of the ... | ea03e60b111423fb2c88a2ea4034560ea7318d51 | <|skeleton|>
class countSort:
def run_sort(self, _list):
"""Sort list of positive integers using the countSort Algorithm"""
<|body_0|>
def run_c_prime(self, c_list):
"""Build C` list by summing the x and x-1 elements of the list"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class countSort:
def run_sort(self, _list):
"""Sort list of positive integers using the countSort Algorithm"""
_sorted = [0] * len(_list)
c_length = max(_list) + 1
c_list = [0] * c_length
' Populate c list from provided unsorted list'
for number in _list:
... | the_stack_v2_python_sparse | countSort/Python/countSort.py | johncanthony/sorts | train | 0 | |
98d1d8a708a1b16ac650b4e544af3495781d7e19 | [
"tenant_id = request.user.tenant_id\nvpnservices = api.vpn.vpnservice_list(request, tenant_id=tenant_id)\nreturn {'items': [u.to_dict() for u in vpnservices]}",
"new_vpnservice = api.vpn.vpnservice_create(request, **request.DATA)\nif new_vpnservice:\n new_vpnservice = api.vpn.vpnservice_get(request, new_vpnser... | <|body_start_0|>
tenant_id = request.user.tenant_id
vpnservices = api.vpn.vpnservice_list(request, tenant_id=tenant_id)
return {'items': [u.to_dict() for u in vpnservices]}
<|end_body_0|>
<|body_start_1|>
new_vpnservice = api.vpn.vpnservice_create(request, **request.DATA)
if new... | API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html | VPNServices | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VPNServices:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of ikepolicies for a project The listing result is an object with property "items". Each item is a network."""
<|body_0|>
def post(... | stack_v2_sparse_classes_36k_train_022738 | 11,907 | permissive | [
{
"docstring": "Get a list of ikepolicies for a project The listing result is an object with property \"items\". Each item is a network.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create VPNService :param request: request context :param admin_state_up: admin state ... | 2 | stack_v2_sparse_classes_30k_test_000499 | Implement the Python class `VPNServices` described below.
Class description:
API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html
Method signatures and docstrings:
- def get(self, request): Get a list of ikepolicies for a project The listing result is an object with property "items". Eac... | Implement the Python class `VPNServices` described below.
Class description:
API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html
Method signatures and docstrings:
- def get(self, request): Get a list of ikepolicies for a project The listing result is an object with property "items". Eac... | 9524f1952461c83db485d5d1702c350b158d7ce0 | <|skeleton|>
class VPNServices:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of ikepolicies for a project The listing result is an object with property "items". Each item is a network."""
<|body_0|>
def post(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VPNServices:
"""API for Neutron Networks http://developer.openstack.org/api-ref-networking-v2.html"""
def get(self, request):
"""Get a list of ikepolicies for a project The listing result is an object with property "items". Each item is a network."""
tenant_id = request.user.tenant_id
... | the_stack_v2_python_sparse | easystack_dashboard/api/rest/vpn.py | oksbsb/horizon-acc | train | 0 |
f6b1e71ade3babfa4e6a0ca4f0478177dddbdc0a | [
"self.div = float(div)\nself.offset = float(offset)\nself.mult = float(mult)\nsuper(rt_sensor, self).__init__(var, bad_val)",
"if abs(self.variable) >= 6999:\n self.result = self.bad_value\n return\nself.result = (self.variable / self.div + self.offset) / self.mult"
] | <|body_start_0|>
self.div = float(div)
self.offset = float(offset)
self.mult = float(mult)
super(rt_sensor, self).__init__(var, bad_val)
<|end_body_0|>
<|body_start_1|>
if abs(self.variable) >= 6999:
self.result = self.bad_value
return
self.result... | This class represnts a sensor calibration given by the function processed value = ( ( data_element / val_a ) + val_b ) / val_c | rt_sensor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class rt_sensor:
"""This class represnts a sensor calibration given by the function processed value = ( ( data_element / val_a ) + val_b ) / val_c"""
def __init__(self, var, div, offset, mult, bad_val=6999):
"""Class initializer Arguments: var: (convertible to float) the domain value div: ... | stack_v2_sparse_classes_36k_train_022739 | 17,830 | no_license | [
{
"docstring": "Class initializer Arguments: var: (convertible to float) the domain value div: (convertible to float) a divisor offset: (convertible to float) an offset mult: (convertible to float) a multiplier bad_val: (convertible to int) the value to indicate a bad data item",
"name": "__init__",
"si... | 2 | stack_v2_sparse_classes_30k_train_019842 | Implement the Python class `rt_sensor` described below.
Class description:
This class represnts a sensor calibration given by the function processed value = ( ( data_element / val_a ) + val_b ) / val_c
Method signatures and docstrings:
- def __init__(self, var, div, offset, mult, bad_val=6999): Class initializer Argu... | Implement the Python class `rt_sensor` described below.
Class description:
This class represnts a sensor calibration given by the function processed value = ( ( data_element / val_a ) + val_b ) / val_c
Method signatures and docstrings:
- def __init__(self, var, div, offset, mult, bad_val=6999): Class initializer Argu... | 95d0c102d649c5b028d262f5254106f997a7c77a | <|skeleton|>
class rt_sensor:
"""This class represnts a sensor calibration given by the function processed value = ( ( data_element / val_a ) + val_b ) / val_c"""
def __init__(self, var, div, offset, mult, bad_val=6999):
"""Class initializer Arguments: var: (convertible to float) the domain value div: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class rt_sensor:
"""This class represnts a sensor calibration given by the function processed value = ( ( data_element / val_a ) + val_b ) / val_c"""
def __init__(self, var, div, offset, mult, bad_val=6999):
"""Class initializer Arguments: var: (convertible to float) the domain value div: (convertible ... | the_stack_v2_python_sparse | csv_lib/equations.py | rwspicer/csv_utilities | train | 1 |
e4f73538a2c1bbb67fdf791e80a2fd5589b38d54 | [
"self.interpreter = tf.lite.Interpreter(model_path=model_path)\nself.interpreter.allocate_tensors()\nself.input_index = self.interpreter.get_input_details()[0]['index']\nself.output_index = self.interpreter.get_output_details()[0]['index']",
"self.interpreter.set_tensor(self.input_index, image)\nself.interpreter.... | <|body_start_0|>
self.interpreter = tf.lite.Interpreter(model_path=model_path)
self.interpreter.allocate_tensors()
self.input_index = self.interpreter.get_input_details()[0]['index']
self.output_index = self.interpreter.get_output_details()[0]['index']
<|end_body_0|>
<|body_start_1|>
... | Wrapper to run TFLite model. | TFLiteRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TFLiteRunner:
"""Wrapper to run TFLite model."""
def __init__(self, model_path):
"""Init. Args: model_path: str, path to tflite model."""
<|body_0|>
def run(self, image):
"""Run inference on a single images. Args: image: numpy.ndarray of shape [1, H, W, C]. Retur... | stack_v2_sparse_classes_36k_train_022740 | 3,244 | permissive | [
{
"docstring": "Init. Args: model_path: str, path to tflite model.",
"name": "__init__",
"signature": "def __init__(self, model_path)"
},
{
"docstring": "Run inference on a single images. Args: image: numpy.ndarray of shape [1, H, W, C]. Returns: prediction: numpy.ndarray of shape [1, num_detect... | 2 | stack_v2_sparse_classes_30k_train_004526 | Implement the Python class `TFLiteRunner` described below.
Class description:
Wrapper to run TFLite model.
Method signatures and docstrings:
- def __init__(self, model_path): Init. Args: model_path: str, path to tflite model.
- def run(self, image): Run inference on a single images. Args: image: numpy.ndarray of shap... | Implement the Python class `TFLiteRunner` described below.
Class description:
Wrapper to run TFLite model.
Method signatures and docstrings:
- def __init__(self, model_path): Init. Args: model_path: str, path to tflite model.
- def run(self, image): Run inference on a single images. Args: image: numpy.ndarray of shap... | c7392f2bab3165244d1c565b66409fa11fa82367 | <|skeleton|>
class TFLiteRunner:
"""Wrapper to run TFLite model."""
def __init__(self, model_path):
"""Init. Args: model_path: str, path to tflite model."""
<|body_0|>
def run(self, image):
"""Run inference on a single images. Args: image: numpy.ndarray of shape [1, H, W, C]. Retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TFLiteRunner:
"""Wrapper to run TFLite model."""
def __init__(self, model_path):
"""Init. Args: model_path: str, path to tflite model."""
self.interpreter = tf.lite.Interpreter(model_path=model_path)
self.interpreter.allocate_tensors()
self.input_index = self.interpreter.g... | the_stack_v2_python_sparse | efficientdet/run_tflite.py | google/automl | train | 6,415 |
aa7b06d4c33494cafd7a746fa40b3329c1105c38 | [
"nn.Module.__init__(self)\nself.params = {'side': side, 'scale': scale}\nvoxels = torch.zeros((1, 4, side, side, side), dtype=torch.float32)\nself.voxels = nn.Parameter(voxels)\nbias = torch.zeros(4, dtype=torch.float32)\nbias[:3] = torch.logit(torch.FloatTensor([1e-05, 1e-05, 1e-05]))\nbias[3] = -2\nself.bias = nn... | <|body_start_0|>
nn.Module.__init__(self)
self.params = {'side': side, 'scale': scale}
voxels = torch.zeros((1, 4, side, side, side), dtype=torch.float32)
self.voxels = nn.Parameter(voxels)
bias = torch.zeros(4, dtype=torch.float32)
bias[:3] = torch.logit(torch.FloatTenso... | A voxel based radiance field model. | Voxels | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Voxels:
"""A voxel based radiance field model."""
def __init__(self, side: int, scale: float):
"""Constructor. Args: side (int): The number of voxels on one side of a cube. scale (float): The scale of the voxel volume, equivalent to half of one side of the volume, i.e. a scale of 1 i... | stack_v2_sparse_classes_36k_train_022741 | 17,353 | no_license | [
{
"docstring": "Constructor. Args: side (int): The number of voxels on one side of a cube. scale (float): The scale of the voxel volume, equivalent to half of one side of the volume, i.e. a scale of 1 indicates a volume of size 2x2x2.",
"name": "__init__",
"signature": "def __init__(self, side: int, sca... | 3 | null | Implement the Python class `Voxels` described below.
Class description:
A voxel based radiance field model.
Method signatures and docstrings:
- def __init__(self, side: int, scale: float): Constructor. Args: side (int): The number of voxels on one side of a cube. scale (float): The scale of the voxel volume, equivale... | Implement the Python class `Voxels` described below.
Class description:
A voxel based radiance field model.
Method signatures and docstrings:
- def __init__(self, side: int, scale: float): Constructor. Args: side (int): The number of voxels on one side of a cube. scale (float): The scale of the voxel volume, equivale... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class Voxels:
"""A voxel based radiance field model."""
def __init__(self, side: int, scale: float):
"""Constructor. Args: side (int): The number of voxels on one side of a cube. scale (float): The scale of the voxel volume, equivalent to half of one side of the volume, i.e. a scale of 1 i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Voxels:
"""A voxel based radiance field model."""
def __init__(self, side: int, scale: float):
"""Constructor. Args: side (int): The number of voxels on one side of a cube. scale (float): The scale of the voxel volume, equivalent to half of one side of the volume, i.e. a scale of 1 indicates a vo... | the_stack_v2_python_sparse | generated/test_matajoh_fourier_feature_nets.py | jansel/pytorch-jit-paritybench | train | 35 |
184a439cb9211ffe1c6a0a9cbd78e290bb067ddb | [
"self.defaultElementWidth, self.defaultElementHeight = (50, 50)\nself.defaultLabelWidth, self.defaultLabelHeight = (30, 10)\nself.context = context\nself.context.new_path()",
"if alpha is None:\n context.set_source_rgb(float(r) / 255.0, float(g) / 255.0, float(b) / 255.0)\nelse:\n context.set_source_rgba(fl... | <|body_start_0|>
self.defaultElementWidth, self.defaultElementHeight = (50, 50)
self.defaultLabelWidth, self.defaultLabelHeight = (30, 10)
self.context = context
self.context.new_path()
<|end_body_0|>
<|body_start_1|>
if alpha is None:
context.set_source_rgb(float(r)... | Base class for drawing objects | CBaseDrawing | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CBaseDrawing:
"""Base class for drawing objects"""
def __init__(self, context):
"""Constructor @type context: CairoContext @param context: cairo context, will be painted on this context"""
<|body_0|>
def ChangeColor(self, context, r, g, b, alpha=None):
"""Change ... | stack_v2_sparse_classes_36k_train_022742 | 1,264 | no_license | [
{
"docstring": "Constructor @type context: CairoContext @param context: cairo context, will be painted on this context",
"name": "__init__",
"signature": "def __init__(self, context)"
},
{
"docstring": "Change color on given context @type context: CairoContext @param context: cairo context on wh... | 2 | stack_v2_sparse_classes_30k_train_019161 | Implement the Python class `CBaseDrawing` described below.
Class description:
Base class for drawing objects
Method signatures and docstrings:
- def __init__(self, context): Constructor @type context: CairoContext @param context: cairo context, will be painted on this context
- def ChangeColor(self, context, r, g, b,... | Implement the Python class `CBaseDrawing` described below.
Class description:
Base class for drawing objects
Method signatures and docstrings:
- def __init__(self, context): Constructor @type context: CairoContext @param context: cairo context, will be painted on this context
- def ChangeColor(self, context, r, g, b,... | eb050a93ef955b8fbc184a437cb0e6fae54264cd | <|skeleton|>
class CBaseDrawing:
"""Base class for drawing objects"""
def __init__(self, context):
"""Constructor @type context: CairoContext @param context: cairo context, will be painted on this context"""
<|body_0|>
def ChangeColor(self, context, r, g, b, alpha=None):
"""Change ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CBaseDrawing:
"""Base class for drawing objects"""
def __init__(self, context):
"""Constructor @type context: CairoContext @param context: cairo context, will be painted on this context"""
self.defaultElementWidth, self.defaultElementHeight = (50, 50)
self.defaultLabelWidth, self.... | the_stack_v2_python_sparse | plugin/gui/BaseDrawing.py | umlfri-old/addon_team | train | 0 |
1785389d5818d508743bd63d5053077ab499dba3 | [
"super(LstmSeqClassificationModel, self).__init__()\nself.padding_idx = padding_idx\nself.embedder = nn.Embedding(vocab_size, emb_dim, padding_idx=padding_idx)\nself.layer_norm = nn.LayerNorm(normalized_shape=emb_dim, epsilon=epsilon)\nself.dropout = nn.Dropout(p=dropout_rate)\ndirection = 'bidirectional' if is_bid... | <|body_start_0|>
super(LstmSeqClassificationModel, self).__init__()
self.padding_idx = padding_idx
self.embedder = nn.Embedding(vocab_size, emb_dim, padding_idx=padding_idx)
self.layer_norm = nn.LayerNorm(normalized_shape=emb_dim, epsilon=epsilon)
self.dropout = nn.Dropout(p=drop... | Lstm model for seq classification task. | LstmSeqClassificationModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LstmSeqClassificationModel:
"""Lstm model for seq classification task."""
def __init__(self, vocab_size, num_class, emb_dim=512, hidden_size=512, n_lstm_layer=3, is_bidirectory=True, padding_idx=0, epsilon=1e-05, dropout_rate=0.1):
"""Init model Args: vocab_size (int): vocab size. nu... | stack_v2_sparse_classes_36k_train_022743 | 10,112 | permissive | [
{
"docstring": "Init model Args: vocab_size (int): vocab size. num_class (int): num of classes. emb_dim (int, optional): embedding dimmension. Defaults to 512. hidden_size (int, optional): hidden size. Defaults to 512. n_lstm_layer (int, optional): number of lstm layer. Defaults to 3. is_bidirectory (bool, opti... | 4 | stack_v2_sparse_classes_30k_val_000400 | Implement the Python class `LstmSeqClassificationModel` described below.
Class description:
Lstm model for seq classification task.
Method signatures and docstrings:
- def __init__(self, vocab_size, num_class, emb_dim=512, hidden_size=512, n_lstm_layer=3, is_bidirectory=True, padding_idx=0, epsilon=1e-05, dropout_rat... | Implement the Python class `LstmSeqClassificationModel` described below.
Class description:
Lstm model for seq classification task.
Method signatures and docstrings:
- def __init__(self, vocab_size, num_class, emb_dim=512, hidden_size=512, n_lstm_layer=3, is_bidirectory=True, padding_idx=0, epsilon=1e-05, dropout_rat... | 1c84ea6d51625d2d66b3eef1d9a7cc9a87c99e0e | <|skeleton|>
class LstmSeqClassificationModel:
"""Lstm model for seq classification task."""
def __init__(self, vocab_size, num_class, emb_dim=512, hidden_size=512, n_lstm_layer=3, is_bidirectory=True, padding_idx=0, epsilon=1e-05, dropout_rate=0.1):
"""Init model Args: vocab_size (int): vocab size. nu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LstmSeqClassificationModel:
"""Lstm model for seq classification task."""
def __init__(self, vocab_size, num_class, emb_dim=512, hidden_size=512, n_lstm_layer=3, is_bidirectory=True, padding_idx=0, epsilon=1e-05, dropout_rate=0.1):
"""Init model Args: vocab_size (int): vocab size. num_class (int)... | the_stack_v2_python_sparse | apps/pretrained_protein/tape_dynamic/protein_sequence_model_dynamic.py | RuikangSun/PaddleHelix | train | 0 |
da6597fde34803c359fcf0a6b6d46bba2acfe257 | [
"response = self.client.post('/users/signup', {'email': self.email, 'password': self.password, 'confirm_password': self.password, 'firstname': 'Andrew', 'phone': self.phone})\ndata = response.content\ndata = loads(data)\nreturn data",
"response = self.client.post('/users/signin', {'email': self.email, 'password':... | <|body_start_0|>
response = self.client.post('/users/signup', {'email': self.email, 'password': self.password, 'confirm_password': self.password, 'firstname': 'Andrew', 'phone': self.phone})
data = response.content
data = loads(data)
return data
<|end_body_0|>
<|body_start_1|>
r... | Products test. Tests for . | TestProductsView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestProductsView:
"""Products test. Tests for ."""
def signUp_user(self):
"""Signup fixture. A fixture that signs up a user first"""
<|body_0|>
def logs_user_in(self, signUp_user):
"""Log a user in."""
<|body_1|>
def test_empty_productName(self, logs... | stack_v2_sparse_classes_36k_train_022744 | 3,468 | permissive | [
{
"docstring": "Signup fixture. A fixture that signs up a user first",
"name": "signUp_user",
"signature": "def signUp_user(self)"
},
{
"docstring": "Log a user in.",
"name": "logs_user_in",
"signature": "def logs_user_in(self, signUp_user)"
},
{
"docstring": "Tests an empty prod... | 6 | stack_v2_sparse_classes_30k_train_013356 | Implement the Python class `TestProductsView` described below.
Class description:
Products test. Tests for .
Method signatures and docstrings:
- def signUp_user(self): Signup fixture. A fixture that signs up a user first
- def logs_user_in(self, signUp_user): Log a user in.
- def test_empty_productName(self, logs_use... | Implement the Python class `TestProductsView` described below.
Class description:
Products test. Tests for .
Method signatures and docstrings:
- def signUp_user(self): Signup fixture. A fixture that signs up a user first
- def logs_user_in(self, signUp_user): Log a user in.
- def test_empty_productName(self, logs_use... | a5f5b3df935d35c7d874b41bffb57069239dcdfd | <|skeleton|>
class TestProductsView:
"""Products test. Tests for ."""
def signUp_user(self):
"""Signup fixture. A fixture that signs up a user first"""
<|body_0|>
def logs_user_in(self, signUp_user):
"""Log a user in."""
<|body_1|>
def test_empty_productName(self, logs... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestProductsView:
"""Products test. Tests for ."""
def signUp_user(self):
"""Signup fixture. A fixture that signs up a user first"""
response = self.client.post('/users/signup', {'email': self.email, 'password': self.password, 'confirm_password': self.password, 'firstname': 'Andrew', 'pho... | the_stack_v2_python_sparse | items/tests.py | Njaya2019/Store | train | 0 |
fa1427fa9a6d84ce1a50449404e9fe79792ff85a | [
"def gcd(a, b):\n while b != 0:\n tmp = b\n b = a % b\n a = tmp\n return a\nif x + y < z:\n return False\nif x == z or y == z or x + y == z:\n return True\nreturn z % gcd(x, y) == 0",
"import collections\nvisited = collections.defaultdict(dict)\nq = collections.deque([(0, 0)])\nwh... | <|body_start_0|>
def gcd(a, b):
while b != 0:
tmp = b
b = a % b
a = tmp
return a
if x + y < z:
return False
if x == z or y == z or x + y == z:
return True
return z % gcd(x, y) == 0
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canMeasureWater(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
<|body_0|>
def canMeasureWater_BFS(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_022745 | 2,358 | no_license | [
{
"docstring": ":type x: int :type y: int :type z: int :rtype: bool",
"name": "canMeasureWater",
"signature": "def canMeasureWater(self, x, y, z)"
},
{
"docstring": ":type x: int :type y: int :type z: int :rtype: bool",
"name": "canMeasureWater_BFS",
"signature": "def canMeasureWater_BFS... | 2 | stack_v2_sparse_classes_30k_train_008026 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canMeasureWater(self, x, y, z): :type x: int :type y: int :type z: int :rtype: bool
- def canMeasureWater_BFS(self, x, y, z): :type x: int :type y: int :type z: int :rtype: b... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canMeasureWater(self, x, y, z): :type x: int :type y: int :type z: int :rtype: bool
- def canMeasureWater_BFS(self, x, y, z): :type x: int :type y: int :type z: int :rtype: b... | 0a7aa09a2b95e4caca5b5123fb735ceb5c01e992 | <|skeleton|>
class Solution:
def canMeasureWater(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
<|body_0|>
def canMeasureWater_BFS(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canMeasureWater(self, x, y, z):
""":type x: int :type y: int :type z: int :rtype: bool"""
def gcd(a, b):
while b != 0:
tmp = b
b = a % b
a = tmp
return a
if x + y < z:
return False
... | the_stack_v2_python_sparse | water-and-jug-problem.py | onestarshang/leetcode | train | 0 | |
0e8cbfb84dec57524f22488932eaf20f592fc9d5 | [
"with tf.variable_scope(name, reuse=tf.AUTO_REUSE):\n self.wa = tf.get_variable('Wa', shape=[hidden_dim, hidden_dim])\n self.ba = tf.get_variable('ba', shape=[hidden_dim], initializer=tf.zeros_initializer())\n self.wx = tf.get_variable('Wx', shape=[input_dim, hidden_dim])\n self.T = T\n self.input_di... | <|body_start_0|>
with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
self.wa = tf.get_variable('Wa', shape=[hidden_dim, hidden_dim])
self.ba = tf.get_variable('ba', shape=[hidden_dim], initializer=tf.zeros_initializer())
self.wx = tf.get_variable('Wx', shape=[input_dim, hidden... | RNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNN:
def __init__(self, T=40, input_dim=1000, hidden_dim=512, name='rnn'):
""":param T:how many steps :param input_dim: :param hidden_dim: :param name: variable scope name :return NOne :define Wa,Wx,Ba,with shape[hidde,hidden],[input,hidden],[hidde]"""
<|body_0|>
def _rnnCel... | stack_v2_sparse_classes_36k_train_022746 | 1,501 | no_license | [
{
"docstring": ":param T:how many steps :param input_dim: :param hidden_dim: :param name: variable scope name :return NOne :define Wa,Wx,Ba,with shape[hidde,hidden],[input,hidden],[hidde]",
"name": "__init__",
"signature": "def __init__(self, T=40, input_dim=1000, hidden_dim=512, name='rnn')"
},
{
... | 3 | null | Implement the Python class `RNN` described below.
Class description:
Implement the RNN class.
Method signatures and docstrings:
- def __init__(self, T=40, input_dim=1000, hidden_dim=512, name='rnn'): :param T:how many steps :param input_dim: :param hidden_dim: :param name: variable scope name :return NOne :define Wa,... | Implement the Python class `RNN` described below.
Class description:
Implement the RNN class.
Method signatures and docstrings:
- def __init__(self, T=40, input_dim=1000, hidden_dim=512, name='rnn'): :param T:how many steps :param input_dim: :param hidden_dim: :param name: variable scope name :return NOne :define Wa,... | 24e60f24b6e442db22507adddd6bf3e2c343c013 | <|skeleton|>
class RNN:
def __init__(self, T=40, input_dim=1000, hidden_dim=512, name='rnn'):
""":param T:how many steps :param input_dim: :param hidden_dim: :param name: variable scope name :return NOne :define Wa,Wx,Ba,with shape[hidde,hidden],[input,hidden],[hidde]"""
<|body_0|>
def _rnnCel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNN:
def __init__(self, T=40, input_dim=1000, hidden_dim=512, name='rnn'):
""":param T:how many steps :param input_dim: :param hidden_dim: :param name: variable scope name :return NOne :define Wa,Wx,Ba,with shape[hidde,hidden],[input,hidden],[hidde]"""
with tf.variable_scope(name, reuse=tf.AUT... | the_stack_v2_python_sparse | daily/8/DeepLearning/project/rnn/Rnn.py | mckjzhangxk/deepAI | train | 1 | |
1f48ed023f0819fd5b96a6281bfa6273d7c8204f | [
"try:\n import netifaces\nexcept ImportError:\n raise ImportError('netifaces must be installed to configure WiFi')\nself.wifi_port = None\nnet_device_list = netifaces.interfaces()\nif interface in net_device_list:\n self.wifi_port = interface\nelse:\n for net_device in net_device_list:\n if net_d... | <|body_start_0|>
try:
import netifaces
except ImportError:
raise ImportError('netifaces must be installed to configure WiFi')
self.wifi_port = None
net_device_list = netifaces.interfaces()
if interface in net_device_list:
self.wifi_port = inter... | This class controls the WiFi connection. For USB WiFi, RALink RT5370 devices are recommended. Note ---- Administrator rights are necessary to create network interface file Attributes ---------- wifi_port : str string identifier of the wireless network device | Wifi | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Wifi:
"""This class controls the WiFi connection. For USB WiFi, RALink RT5370 devices are recommended. Note ---- Administrator rights are necessary to create network interface file Attributes ---------- wifi_port : str string identifier of the wireless network device"""
def __init__(self, in... | stack_v2_sparse_classes_36k_train_022747 | 6,783 | permissive | [
{
"docstring": "Initializes the wireless connection and assign devices identifier. Network devices are checked to find wireless components. Program will first try the default wireless interface name `wlan0`; if not found, it will look for interface name starting from `wl`. Parameters ---------- interface : str ... | 4 | stack_v2_sparse_classes_30k_train_004105 | Implement the Python class `Wifi` described below.
Class description:
This class controls the WiFi connection. For USB WiFi, RALink RT5370 devices are recommended. Note ---- Administrator rights are necessary to create network interface file Attributes ---------- wifi_port : str string identifier of the wireless netwo... | Implement the Python class `Wifi` described below.
Class description:
This class controls the WiFi connection. For USB WiFi, RALink RT5370 devices are recommended. Note ---- Administrator rights are necessary to create network interface file Attributes ---------- wifi_port : str string identifier of the wireless netwo... | 38e9fcee46f0839e83e123cf22af76b13671a574 | <|skeleton|>
class Wifi:
"""This class controls the WiFi connection. For USB WiFi, RALink RT5370 devices are recommended. Note ---- Administrator rights are necessary to create network interface file Attributes ---------- wifi_port : str string identifier of the wireless network device"""
def __init__(self, in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Wifi:
"""This class controls the WiFi connection. For USB WiFi, RALink RT5370 devices are recommended. Note ---- Administrator rights are necessary to create network interface file Attributes ---------- wifi_port : str string identifier of the wireless network device"""
def __init__(self, interface='wlan... | the_stack_v2_python_sparse | pynq/lib/wifi.py | yunqu/PYNQ | train | 8 |
ae2ea5c8d15cdc3752b837d279f94b4e5b1a7ad8 | [
"self.utils = utils.SearchUtils()\nself.logger = self.utils.logger\nself._coordinate = coordinate_search_handler.CoordinateSearch()\nself._geplaces = geplaces_search_handler.PlacesSearch()\nself._style = self._geplaces.style",
"search_results = ''\nsearch_status = False\nparameters = self.utils.GetParameters(envi... | <|body_start_0|>
self.utils = utils.SearchUtils()
self.logger = self.utils.logger
self._coordinate = coordinate_search_handler.CoordinateSearch()
self._geplaces = geplaces_search_handler.PlacesSearch()
self._style = self._geplaces.style
<|end_body_0|>
<|body_start_1|>
se... | Class for performing the Federated search. We initially submit the search against the CoordinateSearch, stopping there if any positive results are returned. If not, we issue our search against the GEPlacesSearch. If there is a valid response from any of the searches, we use it. If not, then we can assume that 'location... | FederatedSearch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FederatedSearch:
"""Class for performing the Federated search. We initially submit the search against the CoordinateSearch, stopping there if any positive results are returned. If not, we issue our search against the GEPlacesSearch. If there is a valid response from any of the searches, we use it... | stack_v2_sparse_classes_36k_train_022748 | 5,027 | permissive | [
{
"docstring": "Inits FederatedSearch. Initializes the logger \"ge_search\".",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Fetches the search tokens from form and performs the federated search. Args: environ: A list of environment variables as supplied by the WSGI in... | 3 | stack_v2_sparse_classes_30k_train_018656 | Implement the Python class `FederatedSearch` described below.
Class description:
Class for performing the Federated search. We initially submit the search against the CoordinateSearch, stopping there if any positive results are returned. If not, we issue our search against the GEPlacesSearch. If there is a valid respo... | Implement the Python class `FederatedSearch` described below.
Class description:
Class for performing the Federated search. We initially submit the search against the CoordinateSearch, stopping there if any positive results are returned. If not, we issue our search against the GEPlacesSearch. If there is a valid respo... | f7ea83f769485d9c28021b951fec8f15f641b16c | <|skeleton|>
class FederatedSearch:
"""Class for performing the Federated search. We initially submit the search against the CoordinateSearch, stopping there if any positive results are returned. If not, we issue our search against the GEPlacesSearch. If there is a valid response from any of the searches, we use it... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FederatedSearch:
"""Class for performing the Federated search. We initially submit the search against the CoordinateSearch, stopping there if any positive results are returned. If not, we issue our search against the GEPlacesSearch. If there is a valid response from any of the searches, we use it. If not, the... | the_stack_v2_python_sparse | earth_enterprise/src/server/wsgi/search/plugin/federated_search_handler.py | tst-ccamp/earthenterprise | train | 2 |
9fe18658a43d2b99dd84819b1e9aa2b603f41a22 | [
"super(Mixer, self).__init__()\nself.n_agents = agent_num\nself.state_dim = state_dim\nself.embed_dim = mixing_embed_dim\nself.hyper_w_1 = nn.Sequential(nn.Linear(self.state_dim, hypernet_embed), nn.ReLU(), nn.Linear(hypernet_embed, self.embed_dim * self.n_agents))\nself.hyper_w_final = nn.Sequential(nn.Linear(self... | <|body_start_0|>
super(Mixer, self).__init__()
self.n_agents = agent_num
self.state_dim = state_dim
self.embed_dim = mixing_embed_dim
self.hyper_w_1 = nn.Sequential(nn.Linear(self.state_dim, hypernet_embed), nn.ReLU(), nn.Linear(hypernet_embed, self.embed_dim * self.n_agents))
... | Overview: mixer network in QMIX, which mix up the independent q_value of each agent to a total q_value Interface: __init__, forward | Mixer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mixer:
"""Overview: mixer network in QMIX, which mix up the independent q_value of each agent to a total q_value Interface: __init__, forward"""
def __init__(self, agent_num, state_dim, mixing_embed_dim, hypernet_embed=64):
"""Overview: initialize pymarl mixer network Arguments: - ag... | stack_v2_sparse_classes_36k_train_022749 | 27,383 | permissive | [
{
"docstring": "Overview: initialize pymarl mixer network Arguments: - agent_num (:obj:`int`): the number of agent - state_dim(:obj:`int`): the dimension of global observation state - mixing_embed_dim (:obj:`int`): the dimension of mixing state emdedding - hypernet_embed (:obj:`int`): the dimension of hypernet ... | 2 | stack_v2_sparse_classes_30k_train_007528 | Implement the Python class `Mixer` described below.
Class description:
Overview: mixer network in QMIX, which mix up the independent q_value of each agent to a total q_value Interface: __init__, forward
Method signatures and docstrings:
- def __init__(self, agent_num, state_dim, mixing_embed_dim, hypernet_embed=64): ... | Implement the Python class `Mixer` described below.
Class description:
Overview: mixer network in QMIX, which mix up the independent q_value of each agent to a total q_value Interface: __init__, forward
Method signatures and docstrings:
- def __init__(self, agent_num, state_dim, mixing_embed_dim, hypernet_embed=64): ... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class Mixer:
"""Overview: mixer network in QMIX, which mix up the independent q_value of each agent to a total q_value Interface: __init__, forward"""
def __init__(self, agent_num, state_dim, mixing_embed_dim, hypernet_embed=64):
"""Overview: initialize pymarl mixer network Arguments: - ag... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mixer:
"""Overview: mixer network in QMIX, which mix up the independent q_value of each agent to a total q_value Interface: __init__, forward"""
def __init__(self, agent_num, state_dim, mixing_embed_dim, hypernet_embed=64):
"""Overview: initialize pymarl mixer network Arguments: - agent_num (:obj... | the_stack_v2_python_sparse | ding/model/template/qmix.py | shengxuesun/DI-engine | train | 1 |
0e696fdedb301998bdb810f81561e5c587b8e6c2 | [
"f = 1.0\nr = 0\nwhile i > 0:\n f = f / b\n r = r + f * (i % b)\n i = floor(i / float(b))\nreturn r",
"self.npart = npart\nself.ndim = ndim\nself.bounds = bounds\nself.k = k\nself.jitter = jitter\nself.primes = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 9... | <|body_start_0|>
f = 1.0
r = 0
while i > 0:
f = f / b
r = r + f * (i % b)
i = floor(i / float(b))
return r
<|end_body_0|>
<|body_start_1|>
self.npart = npart
self.ndim = ndim
self.bounds = bounds
self.k = k
self... | Initialize a swarm quasirandomly | QuasirandomInitializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuasirandomInitializer:
"""Initialize a swarm quasirandomly"""
def Halton(self, i, b):
"""Return i-th Halton number for the given base"""
<|body_0|>
def __init__(self, npart=10, ndim=3, bounds=None, k=1, jitter=0.0):
"""Constructor"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_022750 | 2,701 | permissive | [
{
"docstring": "Return i-th Halton number for the given base",
"name": "Halton",
"signature": "def Halton(self, i, b)"
},
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, npart=10, ndim=3, bounds=None, k=1, jitter=0.0)"
},
{
"docstring": "Return ... | 3 | stack_v2_sparse_classes_30k_train_013724 | Implement the Python class `QuasirandomInitializer` described below.
Class description:
Initialize a swarm quasirandomly
Method signatures and docstrings:
- def Halton(self, i, b): Return i-th Halton number for the given base
- def __init__(self, npart=10, ndim=3, bounds=None, k=1, jitter=0.0): Constructor
- def Init... | Implement the Python class `QuasirandomInitializer` described below.
Class description:
Initialize a swarm quasirandomly
Method signatures and docstrings:
- def Halton(self, i, b): Return i-th Halton number for the given base
- def __init__(self, npart=10, ndim=3, bounds=None, k=1, jitter=0.0): Constructor
- def Init... | 5445b6f90ab49339ca0fdb71e98d44e6827c95a8 | <|skeleton|>
class QuasirandomInitializer:
"""Initialize a swarm quasirandomly"""
def Halton(self, i, b):
"""Return i-th Halton number for the given base"""
<|body_0|>
def __init__(self, npart=10, ndim=3, bounds=None, k=1, jitter=0.0):
"""Constructor"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuasirandomInitializer:
"""Initialize a swarm quasirandomly"""
def Halton(self, i, b):
"""Return i-th Halton number for the given base"""
f = 1.0
r = 0
while i > 0:
f = f / b
r = r + f * (i % b)
i = floor(i / float(b))
return r
... | the_stack_v2_python_sparse | QuasirandomInitializer.py | dayoladejo/SwarmOptimization | train | 0 |
876d1d26635d85f2f94a706ea78757ce80e3824d | [
"if 'odd' == 'odd':\n arrayextension = 5\nelse:\n arrayextension = 0\narraylength = 96 + arrayextension\nMaxVal = 255\nMinVal = 0\nself.gentest = bytearray([MaxVal // 2] * arraylength)",
"with self.assertRaises(TypeError):\n result = bytesfunc.bmin(1)\nwith self.assertRaises(TypeError):\n result = min... | <|body_start_0|>
if 'odd' == 'odd':
arrayextension = 5
else:
arrayextension = 0
arraylength = 96 + arrayextension
MaxVal = 255
MinVal = 0
self.gentest = bytearray([MaxVal // 2] * arraylength)
<|end_body_0|>
<|body_start_1|>
with self.asser... | Test bmin for basic parameter tests. op_template_params | bmin_parameter_odd_arraysize_with_simd_bytearray | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class bmin_parameter_odd_arraysize_with_simd_bytearray:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
<|body_0|>
def test_bmin_param_function_01(self):
"""Test bmin - Sequence type bytearray. Test invalid parameter typ... | stack_v2_sparse_classes_36k_train_022751 | 49,998 | permissive | [
{
"docstring": "Initialise.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test bmin - Sequence type bytearray. Test invalid parameter type odd length array with SIMD.",
"name": "test_bmin_param_function_01",
"signature": "def test_bmin_param_function_01(self)"
},... | 5 | stack_v2_sparse_classes_30k_train_014711 | Implement the Python class `bmin_parameter_odd_arraysize_with_simd_bytearray` described below.
Class description:
Test bmin for basic parameter tests. op_template_params
Method signatures and docstrings:
- def setUp(self): Initialise.
- def test_bmin_param_function_01(self): Test bmin - Sequence type bytearray. Test ... | Implement the Python class `bmin_parameter_odd_arraysize_with_simd_bytearray` described below.
Class description:
Test bmin for basic parameter tests. op_template_params
Method signatures and docstrings:
- def setUp(self): Initialise.
- def test_bmin_param_function_01(self): Test bmin - Sequence type bytearray. Test ... | 28fe0705fc59b0646a4d44e539c919173e8e8b99 | <|skeleton|>
class bmin_parameter_odd_arraysize_with_simd_bytearray:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
<|body_0|>
def test_bmin_param_function_01(self):
"""Test bmin - Sequence type bytearray. Test invalid parameter typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class bmin_parameter_odd_arraysize_with_simd_bytearray:
"""Test bmin for basic parameter tests. op_template_params"""
def setUp(self):
"""Initialise."""
if 'odd' == 'odd':
arrayextension = 5
else:
arrayextension = 0
arraylength = 96 + arrayextension
... | the_stack_v2_python_sparse | unittest/test_bmin.py | m1griffin/bytesfunc | train | 2 |
fba92b565b0b80e6da232dba71044d76188fa657 | [
"user = self.request.user\nif not user.profile.has_backdated:\n backdate_user(user.profile)\nreturn user",
"user = self.request.user\ncontext = super().get_context_data(**kwargs)\nif not user.profile.has_backdated:\n backdate_user(user.profile)\nmemberships = user.membership_set.all().order_by('group__name'... | <|body_start_0|>
user = self.request.user
if not user.profile.has_backdated:
backdate_user(user.profile)
return user
<|end_body_0|>
<|body_start_1|>
user = self.request.user
context = super().get_context_data(**kwargs)
if not user.profile.has_backdated:
... | View for a user's dashboard. | UserDetailView | [
"MIT",
"AGPL-3.0-only",
"ISC",
"LGPL-2.1-or-later",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserDetailView:
"""View for a user's dashboard."""
def get_object(self):
"""Get object for template."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Get additional context data for template."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022752 | 16,961 | permissive | [
{
"docstring": "Get object for template.",
"name": "get_object",
"signature": "def get_object(self)"
},
{
"docstring": "Get additional context data for template.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
] | 2 | null | Implement the Python class `UserDetailView` described below.
Class description:
View for a user's dashboard.
Method signatures and docstrings:
- def get_object(self): Get object for template.
- def get_context_data(self, **kwargs): Get additional context data for template. | Implement the Python class `UserDetailView` described below.
Class description:
View for a user's dashboard.
Method signatures and docstrings:
- def get_object(self): Get object for template.
- def get_context_data(self, **kwargs): Get additional context data for template.
<|skeleton|>
class UserDetailView:
"""V... | 5b668eb66449e2ebaeb2177237b9a55a14d69efb | <|skeleton|>
class UserDetailView:
"""View for a user's dashboard."""
def get_object(self):
"""Get object for template."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Get additional context data for template."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserDetailView:
"""View for a user's dashboard."""
def get_object(self):
"""Get object for template."""
user = self.request.user
if not user.profile.has_backdated:
backdate_user(user.profile)
return user
def get_context_data(self, **kwargs):
"""Get... | the_stack_v2_python_sparse | codewof/users/views.py | uccser/codewof | train | 7 |
c1c91c5e57ec59ebc0286711031602876e1e37e7 | [
"actions = self._default_attribute_actions.copy()\nactions['href'] = 'must'\nactions['title'] = 'drop'\nactions['class'] = 'keep'\nconverted = self._visit_open(node, children, actions)\nattrs = converted.attributes.attrs\nif 'href' in attrs:\n href = attrs['href'].value\n if href and href[0] == '/':\n ... | <|body_start_0|>
actions = self._default_attribute_actions.copy()
actions['href'] = 'must'
actions['title'] = 'drop'
actions['class'] = 'keep'
converted = self._visit_open(node, children, actions)
attrs = converted.attributes.attrs
if 'href' in attrs:
... | Extract HTML structure from a MDN Kuma raw fragment. Include extra policy for scraping pages for the importer: - Converts <span>content</span> to "content", with issues - Validate and cleanup <a> tags - Keeps <div id="foo">, for detecting compat divs - Keeps <td colspan=# rowspan=#>, for detecting spanning compat cells... | KumaVisitor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KumaVisitor:
"""Extract HTML structure from a MDN Kuma raw fragment. Include extra policy for scraping pages for the importer: - Converts <span>content</span> to "content", with issues - Validate and cleanup <a> tags - Keeps <div id="foo">, for detecting compat divs - Keeps <td colspan=# rowspan=... | stack_v2_sparse_classes_36k_train_022753 | 38,117 | no_license | [
{
"docstring": "Validate and cleanup <a> open tags.",
"name": "visit_a_open",
"signature": "def visit_a_open(self, node, children)"
},
{
"docstring": "Retain id attribute of <div> tags.",
"name": "visit_div_open",
"signature": "def visit_div_open(self, node, children)"
},
{
"docs... | 5 | stack_v2_sparse_classes_30k_train_019831 | Implement the Python class `KumaVisitor` described below.
Class description:
Extract HTML structure from a MDN Kuma raw fragment. Include extra policy for scraping pages for the importer: - Converts <span>content</span> to "content", with issues - Validate and cleanup <a> tags - Keeps <div id="foo">, for detecting com... | Implement the Python class `KumaVisitor` described below.
Class description:
Extract HTML structure from a MDN Kuma raw fragment. Include extra policy for scraping pages for the importer: - Converts <span>content</span> to "content", with issues - Validate and cleanup <a> tags - Keeps <div id="foo">, for detecting com... | bc092964153b03381aaff74a4d80f43a2b2dec19 | <|skeleton|>
class KumaVisitor:
"""Extract HTML structure from a MDN Kuma raw fragment. Include extra policy for scraping pages for the importer: - Converts <span>content</span> to "content", with issues - Validate and cleanup <a> tags - Keeps <div id="foo">, for detecting compat divs - Keeps <td colspan=# rowspan=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KumaVisitor:
"""Extract HTML structure from a MDN Kuma raw fragment. Include extra policy for scraping pages for the importer: - Converts <span>content</span> to "content", with issues - Validate and cleanup <a> tags - Keeps <div id="foo">, for detecting compat divs - Keeps <td colspan=# rowspan=#>, for detec... | the_stack_v2_python_sparse | browsercompat/mdn/kumascript.py | WeilerWebServices/MDN-Web-Docs | train | 1 |
790b4ef362190da006623b1aa1a5ce396ecd9608 | [
"self._build_info_path = control.get('build_info_path')\nself._build_label_pattern = control.get('build_label_pattern')\nself._build_version_pattern = control.get('build_version_pattern')\nself._capture_groups = control.get('capture_groups')\nself._fallback_build_label = control.get('fallback_build_label') or None\... | <|body_start_0|>
self._build_info_path = control.get('build_info_path')
self._build_label_pattern = control.get('build_label_pattern')
self._build_version_pattern = control.get('build_version_pattern')
self._capture_groups = control.get('capture_groups')
self._fallback_build_labe... | Implements the core functionality of the versioning tool. | VersionTool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VersionTool:
"""Implements the core functionality of the versioning tool."""
def __init__(self, control):
"""Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the tool. Please see the moduledoc for a description of the fo... | stack_v2_sparse_classes_36k_train_022754 | 9,887 | permissive | [
{
"docstring": "Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the tool. Please see the moduledoc for a description of the format of this dictionary.",
"name": "__init__",
"signature": "def __init__(self, control)"
},
{
"docstring... | 4 | stack_v2_sparse_classes_30k_train_015864 | Implement the Python class `VersionTool` described below.
Class description:
Implements the core functionality of the versioning tool.
Method signatures and docstrings:
- def __init__(self, control): Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the t... | Implement the Python class `VersionTool` described below.
Class description:
Implements the core functionality of the versioning tool.
Method signatures and docstrings:
- def __init__(self, control): Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the t... | 55cf5c2bec04b05b9ab435e24174834c5681be12 | <|skeleton|>
class VersionTool:
"""Implements the core functionality of the versioning tool."""
def __init__(self, control):
"""Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the tool. Please see the moduledoc for a description of the fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VersionTool:
"""Implements the core functionality of the versioning tool."""
def __init__(self, control):
"""Initializes VersionTool with the given control options. Args: control: The dictionary of options used to control the tool. Please see the moduledoc for a description of the format of this ... | the_stack_v2_python_sparse | tools/versiontool/versiontool.py | bazelbuild/rules_apple | train | 449 |
f0f2f4cbeecaf0caed9ee83525a021dd4d2d591e | [
"self.editable = editable\nself.verbose = verbose\nself.install_dev_sh = f'{T_SYSTEM_PATH}/../install-dev.sh'\nself.install_sh = f'{T_SYSTEM_PATH}/../install.sh'\nif self.editable:\n self.last_hash = self.__get_hash_of(self.install_dev_sh)\nelse:\n self.last_hash = self.__get_hash_of(self.install_sh)",
"if ... | <|body_start_0|>
self.editable = editable
self.verbose = verbose
self.install_dev_sh = f'{T_SYSTEM_PATH}/../install-dev.sh'
self.install_sh = f'{T_SYSTEM_PATH}/../install.sh'
if self.editable:
self.last_hash = self.__get_hash_of(self.install_dev_sh)
else:
... | Class to define an installer of tracking system itself. This class provides necessary initiations and functions named :func:`t_system.updation.Installer.install` as the install point for the changed install scripts and named :func:`t_system.updation.Installer.__get_hash_of` for creating SHA-256 hash of the given file. | Installer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Installer:
"""Class to define an installer of tracking system itself. This class provides necessary initiations and functions named :func:`t_system.updation.Installer.install` as the install point for the changed install scripts and named :func:`t_system.updation.Installer.__get_hash_of` for crea... | stack_v2_sparse_classes_36k_train_022755 | 26,721 | permissive | [
{
"docstring": "Initialization method of :class:`t_system.updation.Installer` class. Args: editable: Editable updation mode flag. verbose: Verbosity flag about printing debug messages.",
"name": "__init__",
"signature": "def __init__(self, editable, verbose)"
},
{
"docstring": "Method to install... | 3 | stack_v2_sparse_classes_30k_train_021408 | Implement the Python class `Installer` described below.
Class description:
Class to define an installer of tracking system itself. This class provides necessary initiations and functions named :func:`t_system.updation.Installer.install` as the install point for the changed install scripts and named :func:`t_system.upd... | Implement the Python class `Installer` described below.
Class description:
Class to define an installer of tracking system itself. This class provides necessary initiations and functions named :func:`t_system.updation.Installer.install` as the install point for the changed install scripts and named :func:`t_system.upd... | 4cf34572b8f8eac54d6c339f37aa72b6a13d8934 | <|skeleton|>
class Installer:
"""Class to define an installer of tracking system itself. This class provides necessary initiations and functions named :func:`t_system.updation.Installer.install` as the install point for the changed install scripts and named :func:`t_system.updation.Installer.__get_hash_of` for crea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Installer:
"""Class to define an installer of tracking system itself. This class provides necessary initiations and functions named :func:`t_system.updation.Installer.install` as the install point for the changed install scripts and named :func:`t_system.updation.Installer.__get_hash_of` for creating SHA-256 ... | the_stack_v2_python_sparse | t_system/updation.py | LookAtMe-Genius-Cameraman/T_System | train | 9 |
ca3e6c50ee6c12dfed3588318923f3633bf9dc9a | [
"try:\n verify_token(request.headers)\nexcept Exception as err:\n ns.abort(401, message=err)\ntry:\n obs = observaciones_ires_cytg.read(id)\nexcept psycopg2.Error as err:\n ns.abort(400, message=get_msg_pgerror(err))\nexcept EmptySetError:\n ns.abort(404, message=ObservacionCyTG.obs_not_found)\nexcep... | <|body_start_0|>
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
try:
obs = observaciones_ires_cytg.read(id)
except psycopg2.Error as err:
ns.abort(400, message=get_msg_pgerror(err))
except Emp... | ObservacionCyTG | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObservacionCyTG:
def get(self, id):
"""To fetch an observation (CyTG (resultados))"""
<|body_0|>
def put(self, id):
"""To update an observation (CyTG (resultados))"""
<|body_1|>
def delete(self, id):
"""To delete an observation (CyTG (resultados)... | stack_v2_sparse_classes_36k_train_022756 | 18,120 | no_license | [
{
"docstring": "To fetch an observation (CyTG (resultados))",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "To update an observation (CyTG (resultados))",
"name": "put",
"signature": "def put(self, id)"
},
{
"docstring": "To delete an observation (CyTG (resul... | 3 | stack_v2_sparse_classes_30k_train_011871 | Implement the Python class `ObservacionCyTG` described below.
Class description:
Implement the ObservacionCyTG class.
Method signatures and docstrings:
- def get(self, id): To fetch an observation (CyTG (resultados))
- def put(self, id): To update an observation (CyTG (resultados))
- def delete(self, id): To delete a... | Implement the Python class `ObservacionCyTG` described below.
Class description:
Implement the ObservacionCyTG class.
Method signatures and docstrings:
- def get(self, id): To fetch an observation (CyTG (resultados))
- def put(self, id): To update an observation (CyTG (resultados))
- def delete(self, id): To delete a... | e00610fac26ef3ca078fd037c0649b70fa0e9a09 | <|skeleton|>
class ObservacionCyTG:
def get(self, id):
"""To fetch an observation (CyTG (resultados))"""
<|body_0|>
def put(self, id):
"""To update an observation (CyTG (resultados))"""
<|body_1|>
def delete(self, id):
"""To delete an observation (CyTG (resultados)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObservacionCyTG:
def get(self, id):
"""To fetch an observation (CyTG (resultados))"""
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
try:
obs = observaciones_ires_cytg.read(id)
except psycopg2.E... | the_stack_v2_python_sparse | DOS/soa/service/genl/endpoints/observaciones_ires_cytg.py | Telematica/knight-rider | train | 1 | |
4e24d5ac9f01c88edc528b55b9773936cea181b6 | [
"def is_palindrone(i, j):\n return s[i:j + 1] == s[i:j + 1][::-1]\nn = len(s)\nresult = 0\nfor i in range(n):\n for j in range(i, n):\n if is_palindrone(i, j):\n result += 1\nreturn result",
"@lru_cache(None)\ndef is_palindrone(i, j):\n if j <= i:\n return True\n return s[i] =... | <|body_start_0|>
def is_palindrone(i, j):
return s[i:j + 1] == s[i:j + 1][::-1]
n = len(s)
result = 0
for i in range(n):
for j in range(i, n):
if is_palindrone(i, j):
result += 1
return result
<|end_body_0|>
<|body_star... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countSubstrings(self, s: str) -> int:
"""Brute Force, Time: O(n^3), Space: O(1)"""
<|body_0|>
def countSubstrings(self, s: str) -> int:
"""Top-Down DP for is_palindrone, Time: O(n^2), Space: O(n^2)"""
<|body_1|>
def countSubstrings(self, s:... | stack_v2_sparse_classes_36k_train_022757 | 1,729 | no_license | [
{
"docstring": "Brute Force, Time: O(n^3), Space: O(1)",
"name": "countSubstrings",
"signature": "def countSubstrings(self, s: str) -> int"
},
{
"docstring": "Top-Down DP for is_palindrone, Time: O(n^2), Space: O(n^2)",
"name": "countSubstrings",
"signature": "def countSubstrings(self, s... | 3 | stack_v2_sparse_classes_30k_train_002504 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubstrings(self, s: str) -> int: Brute Force, Time: O(n^3), Space: O(1)
- def countSubstrings(self, s: str) -> int: Top-Down DP for is_palindrone, Time: O(n^2), Space: O... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubstrings(self, s: str) -> int: Brute Force, Time: O(n^3), Space: O(1)
- def countSubstrings(self, s: str) -> int: Top-Down DP for is_palindrone, Time: O(n^2), Space: O... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def countSubstrings(self, s: str) -> int:
"""Brute Force, Time: O(n^3), Space: O(1)"""
<|body_0|>
def countSubstrings(self, s: str) -> int:
"""Top-Down DP for is_palindrone, Time: O(n^2), Space: O(n^2)"""
<|body_1|>
def countSubstrings(self, s:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countSubstrings(self, s: str) -> int:
"""Brute Force, Time: O(n^3), Space: O(1)"""
def is_palindrone(i, j):
return s[i:j + 1] == s[i:j + 1][::-1]
n = len(s)
result = 0
for i in range(n):
for j in range(i, n):
if is_p... | the_stack_v2_python_sparse | python/647-Palindromic Substrings.py | cwza/leetcode | train | 0 | |
be040a6c45b0b0e208208e836746cab345f81f3c | [
"if not isinstance(query, SearchQueryBuilder):\n raise ImapInvalidArgument('query', query)\nself.__search_query = query\nself.__charset = charset",
"typ, data = imap_obj.search(self.__charset, str(self.__search_query))\nself.check_response(typ, data)\nif not data:\n return []\nfor uid in data[0].split(b' ')... | <|body_start_0|>
if not isinstance(query, SearchQueryBuilder):
raise ImapInvalidArgument('query', query)
self.__search_query = query
self.__charset = charset
<|end_body_0|>
<|body_start_1|>
typ, data = imap_obj.search(self.__charset, str(self.__search_query))
self.ch... | Executes IMAP SEARCH cammand | ImapSearchCommand | [
"WTFPL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImapSearchCommand:
"""Executes IMAP SEARCH cammand"""
def __init__(self, query: SearchQueryBuilder, charset=None):
"""Creates instance of SEARCH IMAP command Raises: ImapRuntimeError - if :param query is not instance of SearchQueryBuilder :param query: FetchQueryBuilder :param charse... | stack_v2_sparse_classes_36k_train_022758 | 1,437 | permissive | [
{
"docstring": "Creates instance of SEARCH IMAP command Raises: ImapRuntimeError - if :param query is not instance of SearchQueryBuilder :param query: FetchQueryBuilder :param charset: Any :return:",
"name": "__init__",
"signature": "def __init__(self, query: SearchQueryBuilder, charset=None)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_016568 | Implement the Python class `ImapSearchCommand` described below.
Class description:
Executes IMAP SEARCH cammand
Method signatures and docstrings:
- def __init__(self, query: SearchQueryBuilder, charset=None): Creates instance of SEARCH IMAP command Raises: ImapRuntimeError - if :param query is not instance of SearchQ... | Implement the Python class `ImapSearchCommand` described below.
Class description:
Executes IMAP SEARCH cammand
Method signatures and docstrings:
- def __init__(self, query: SearchQueryBuilder, charset=None): Creates instance of SEARCH IMAP command Raises: ImapRuntimeError - if :param query is not instance of SearchQ... | 002a916494591e31ec9a0c2dbef66427a72bc036 | <|skeleton|>
class ImapSearchCommand:
"""Executes IMAP SEARCH cammand"""
def __init__(self, query: SearchQueryBuilder, charset=None):
"""Creates instance of SEARCH IMAP command Raises: ImapRuntimeError - if :param query is not instance of SearchQueryBuilder :param query: FetchQueryBuilder :param charse... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImapSearchCommand:
"""Executes IMAP SEARCH cammand"""
def __init__(self, query: SearchQueryBuilder, charset=None):
"""Creates instance of SEARCH IMAP command Raises: ImapRuntimeError - if :param query is not instance of SearchQueryBuilder :param query: FetchQueryBuilder :param charset: Any :retur... | the_stack_v2_python_sparse | pymaillib/imap/commands/search.py | pussbb/pymaillib | train | 0 |
475b3f7924f7eb75612dd97a0062976ab35630fd | [
"self.buf = buf\nself.ptr = ptr\nself.endian = endian\nself._cache = {}",
"pkst = self._cache.get(fmt)\nif pkst is None:\n if self.endian is None or fmt[0] in _ENDIAN_CODES:\n pkst = Struct(fmt)\n else:\n endian_fmt = self.endian + fmt\n pkst = Struct(endian_fmt)\n self._cache[en... | <|body_start_0|>
self.buf = buf
self.ptr = ptr
self.endian = endian
self._cache = {}
<|end_body_0|>
<|body_start_1|>
pkst = self._cache.get(fmt)
if pkst is None:
if self.endian is None or fmt[0] in _ENDIAN_CODES:
pkst = Struct(fmt)
... | Class to unpack values from buffer object The buffer object is usually a string. Caches compiled :mod:`struct` format strings so that repeated unpacking with the same format string should be faster than using ``struct.unpack`` directly. Examples -------- >>> a = b'1234567890' >>> upk = Unpacker(a) >>> upk.unpack('2s') ... | Unpacker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Unpacker:
"""Class to unpack values from buffer object The buffer object is usually a string. Caches compiled :mod:`struct` format strings so that repeated unpacking with the same format string should be faster than using ``struct.unpack`` directly. Examples -------- >>> a = b'1234567890' >>> upk... | stack_v2_sparse_classes_36k_train_022759 | 3,580 | permissive | [
{
"docstring": "Initialize unpacker Parameters ---------- buf : buffer object implementing buffer protocol (e.g. str) ptr : int, optional offset at which to begin reads from `buf` endian : None or str, optional endian code to prepend to format, as for ``unpack`` endian codes. None (the default) corresponds to t... | 3 | stack_v2_sparse_classes_30k_train_018365 | Implement the Python class `Unpacker` described below.
Class description:
Class to unpack values from buffer object The buffer object is usually a string. Caches compiled :mod:`struct` format strings so that repeated unpacking with the same format string should be faster than using ``struct.unpack`` directly. Examples... | Implement the Python class `Unpacker` described below.
Class description:
Class to unpack values from buffer object The buffer object is usually a string. Caches compiled :mod:`struct` format strings so that repeated unpacking with the same format string should be faster than using ``struct.unpack`` directly. Examples... | 3c3acc55de8ba741e673063378e6cbaf10b64c7a | <|skeleton|>
class Unpacker:
"""Class to unpack values from buffer object The buffer object is usually a string. Caches compiled :mod:`struct` format strings so that repeated unpacking with the same format string should be faster than using ``struct.unpack`` directly. Examples -------- >>> a = b'1234567890' >>> upk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Unpacker:
"""Class to unpack values from buffer object The buffer object is usually a string. Caches compiled :mod:`struct` format strings so that repeated unpacking with the same format string should be faster than using ``struct.unpack`` directly. Examples -------- >>> a = b'1234567890' >>> upk = Unpacker(a... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/nibabel/nicom/structreader.py | Raniac/NEURO-LEARN | train | 9 |
c3e0ec8e769fac78c27f034ae5662ddd58b220d0 | [
"super().__init__(parent, store)\nself.frame1_label = tk.Label(self.frame1, text='Login with password', font=('Arial', 20, 'bold'))\nself.password_label = tk.Label(self.frame1, text='Password: ')\nself.password_field = tk.StringVar()\nself.password_entry = tk.Entry(self.frame1, textvariable=self.password_field, sho... | <|body_start_0|>
super().__init__(parent, store)
self.frame1_label = tk.Label(self.frame1, text='Login with password', font=('Arial', 20, 'bold'))
self.password_label = tk.Label(self.frame1, text='Password: ')
self.password_field = tk.StringVar()
self.password_entry = tk.Entry(se... | The second screen when the app opens. It has 2 frame, the left frame is for login normally, and the right frame is for login with face. User can click on the open cam button to use this feature. Attributes: ---------- frame1 : tkinter frame The container for the left page frame2 : tkinter frame The container for the ri... | Screen2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Screen2:
"""The second screen when the app opens. It has 2 frame, the left frame is for login normally, and the right frame is for login with face. User can click on the open cam button to use this feature. Attributes: ---------- frame1 : tkinter frame The container for the left page frame2 : tki... | stack_v2_sparse_classes_36k_train_022760 | 8,263 | permissive | [
{
"docstring": "Init the screen 2 with 2 frame on. The first frame is for login with password and the second frame is for login with face. This only load the recognizer and pca if the user has the face added and the device has camera. Params: ------- parent: tkinter frame or tk() The parent frame attach to this... | 4 | stack_v2_sparse_classes_30k_train_011533 | Implement the Python class `Screen2` described below.
Class description:
The second screen when the app opens. It has 2 frame, the left frame is for login normally, and the right frame is for login with face. User can click on the open cam button to use this feature. Attributes: ---------- frame1 : tkinter frame The c... | Implement the Python class `Screen2` described below.
Class description:
The second screen when the app opens. It has 2 frame, the left frame is for login normally, and the right frame is for login with face. User can click on the open cam button to use this feature. Attributes: ---------- frame1 : tkinter frame The c... | e4478a6ca8ca15ab99fc251b40e64307302bffeb | <|skeleton|>
class Screen2:
"""The second screen when the app opens. It has 2 frame, the left frame is for login normally, and the right frame is for login with face. User can click on the open cam button to use this feature. Attributes: ---------- frame1 : tkinter frame The container for the left page frame2 : tki... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Screen2:
"""The second screen when the app opens. It has 2 frame, the left frame is for login normally, and the right frame is for login with face. User can click on the open cam button to use this feature. Attributes: ---------- frame1 : tkinter frame The container for the left page frame2 : tkinter frame Th... | the_stack_v2_python_sparse | screen2.py | athan37/LoginSystemWithFace | train | 1 |
52199d5344bb74983cb53ee0493b9ae79490b3d4 | [
"username = request.user.get_username()\nserializer = RepoSerializer(username, repo_base, request)\nif username == repo_base:\n return Response(serializer.user_owned_repos())\nelse:\n return Response(serializer.specific_collab_repos(repo_base))",
"username = request.user.get_username()\nserializer = RepoSer... | <|body_start_0|>
username = request.user.get_username()
serializer = RepoSerializer(username, repo_base, request)
if username == repo_base:
return Response(serializer.user_owned_repos())
else:
return Response(serializer.specific_collab_repos(repo_base))
<|end_body... | Repos of the specified user. | ReposForUser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReposForUser:
"""Repos of the specified user."""
def get(self, request, repo_base, format=None):
"""Repos of the specified user that are visible to the logged in user"""
<|body_0|>
def post(self, request, repo_base, format=None):
"""Create a repo for the specifie... | stack_v2_sparse_classes_36k_train_022761 | 31,465 | permissive | [
{
"docstring": "Repos of the specified user that are visible to the logged in user",
"name": "get",
"signature": "def get(self, request, repo_base, format=None)"
},
{
"docstring": "Create a repo for the specified user. --- omit_serializer: true parameters: - name: repo_name in: body type: string... | 2 | stack_v2_sparse_classes_30k_train_002611 | Implement the Python class `ReposForUser` described below.
Class description:
Repos of the specified user.
Method signatures and docstrings:
- def get(self, request, repo_base, format=None): Repos of the specified user that are visible to the logged in user
- def post(self, request, repo_base, format=None): Create a ... | Implement the Python class `ReposForUser` described below.
Class description:
Repos of the specified user.
Method signatures and docstrings:
- def get(self, request, repo_base, format=None): Repos of the specified user that are visible to the logged in user
- def post(self, request, repo_base, format=None): Create a ... | f066b472c2b66cc3b868bbe433aed2d4557aea32 | <|skeleton|>
class ReposForUser:
"""Repos of the specified user."""
def get(self, request, repo_base, format=None):
"""Repos of the specified user that are visible to the logged in user"""
<|body_0|>
def post(self, request, repo_base, format=None):
"""Create a repo for the specifie... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReposForUser:
"""Repos of the specified user."""
def get(self, request, repo_base, format=None):
"""Repos of the specified user that are visible to the logged in user"""
username = request.user.get_username()
serializer = RepoSerializer(username, repo_base, request)
if use... | the_stack_v2_python_sparse | src/api/views.py | datahuborg/datahub | train | 199 |
4ac97982e032778ca48dd1c6a1bf82b7696eb07b | [
"N, H = (len(needle), len(haystack))\nif N == 0:\n return 0\npH = 0\nwhile pH < H - N + 1:\n while pH < H - N + 1 and haystack[pH] != needle[0]:\n pH += 1\n pN = 0\n while pN < N and pH < H and (haystack[pH] == needle[pN]):\n pN += 1\n pH += 1\n if pN == N:\n return pH - N... | <|body_start_0|>
N, H = (len(needle), len(haystack))
if N == 0:
return 0
pH = 0
while pH < H - N + 1:
while pH < H - N + 1 and haystack[pH] != needle[0]:
pH += 1
pN = 0
while pN < N and pH < H and (haystack[pH] == needle[pN]... | Strstr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Strstr:
def get_needle_index_(self, haystack: str, needle: str) -> int:
"""Approach: Two Pointers - Linear Time Slice Time Complexity: O((N - H) N) Space Complexity: O(1) :param haystack: :param needle: :return:"""
<|body_0|>
def get_needle_index__(self, haystack: str, needl... | stack_v2_sparse_classes_36k_train_022762 | 1,717 | no_license | [
{
"docstring": "Approach: Two Pointers - Linear Time Slice Time Complexity: O((N - H) N) Space Complexity: O(1) :param haystack: :param needle: :return:",
"name": "get_needle_index_",
"signature": "def get_needle_index_(self, haystack: str, needle: str) -> int"
},
{
"docstring": "Approach: Subst... | 2 | null | Implement the Python class `Strstr` described below.
Class description:
Implement the Strstr class.
Method signatures and docstrings:
- def get_needle_index_(self, haystack: str, needle: str) -> int: Approach: Two Pointers - Linear Time Slice Time Complexity: O((N - H) N) Space Complexity: O(1) :param haystack: :para... | Implement the Python class `Strstr` described below.
Class description:
Implement the Strstr class.
Method signatures and docstrings:
- def get_needle_index_(self, haystack: str, needle: str) -> int: Approach: Two Pointers - Linear Time Slice Time Complexity: O((N - H) N) Space Complexity: O(1) :param haystack: :para... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Strstr:
def get_needle_index_(self, haystack: str, needle: str) -> int:
"""Approach: Two Pointers - Linear Time Slice Time Complexity: O((N - H) N) Space Complexity: O(1) :param haystack: :param needle: :return:"""
<|body_0|>
def get_needle_index__(self, haystack: str, needl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Strstr:
def get_needle_index_(self, haystack: str, needle: str) -> int:
"""Approach: Two Pointers - Linear Time Slice Time Complexity: O((N - H) N) Space Complexity: O(1) :param haystack: :param needle: :return:"""
N, H = (len(needle), len(haystack))
if N == 0:
return 0
... | the_stack_v2_python_sparse | revisited/math_and_strings/strings/str_str.py | Shiv2157k/leet_code | train | 1 | |
91dacf26f4827d2e5dca7d9bf3ed15454aafedf7 | [
"self.n = n\nself.discount = discount\nself.prices = {k: v for k, v in zip(products, prices)}\nself.c = 1",
"s = 0\nfor p, c in zip(product, amount):\n s += self.prices[p] * c\nif self.c == self.n:\n s *= 1 - self.discount / 100.0\n self.c = 1\nelse:\n self.c += 1\nreturn s"
] | <|body_start_0|>
self.n = n
self.discount = discount
self.prices = {k: v for k, v in zip(products, prices)}
self.c = 1
<|end_body_0|>
<|body_start_1|>
s = 0
for p, c in zip(product, amount):
s += self.prices[p] * c
if self.c == self.n:
s *... | Cashier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
<|body_0|>
def getBill(self, product, amount):
""":type product: List[int] :type amount: List[int] :rtype: float"""
... | stack_v2_sparse_classes_36k_train_022763 | 3,686 | no_license | [
{
"docstring": ":type n: int :type discount: int :type products: List[int] :type prices: List[int]",
"name": "__init__",
"signature": "def __init__(self, n, discount, products, prices)"
},
{
"docstring": ":type product: List[int] :type amount: List[int] :rtype: float",
"name": "getBill",
... | 2 | stack_v2_sparse_classes_30k_train_013432 | Implement the Python class `Cashier` described below.
Class description:
Implement the Cashier class.
Method signatures and docstrings:
- def __init__(self, n, discount, products, prices): :type n: int :type discount: int :type products: List[int] :type prices: List[int]
- def getBill(self, product, amount): :type pr... | Implement the Python class `Cashier` described below.
Class description:
Implement the Cashier class.
Method signatures and docstrings:
- def __init__(self, n, discount, products, prices): :type n: int :type discount: int :type products: List[int] :type prices: List[int]
- def getBill(self, product, amount): :type pr... | f2bf9b13508cd01c8f383789569e55a438f77202 | <|skeleton|>
class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
<|body_0|>
def getBill(self, product, amount):
""":type product: List[int] :type amount: List[int] :rtype: float"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
self.n = n
self.discount = discount
self.prices = {k: v for k, v in zip(products, prices)}
self.c = 1
def getBill(se... | the_stack_v2_python_sparse | version1/1357_Apply_Discount_Every_n_Orders.py | moontree/leetcode | train | 1 | |
daf7ce02d1a3d3a275d7e2a771f708388619e0df | [
"self.log.info('login from GitHub')\ncode = context.get('code')\nif not code:\n return None\naccess_token = self.get_token(code)\nself.log.info('Successfully get access token from github using code %s' % code)\nuser_info = self.get_user_info(access_token)\nemail_list = self.get_emails(access_token)\nself.log.inf... | <|body_start_0|>
self.log.info('login from GitHub')
code = context.get('code')
if not code:
return None
access_token = self.get_token(code)
self.log.info('Successfully get access token from github using code %s' % code)
user_info = self.get_user_info(access_to... | Sign in with github docs: https://developer.github.com/apps/building-oauth-apps/authorizing-oauth-apps/#web-application-flow .. notes:: | GithubLogin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GithubLogin:
"""Sign in with github docs: https://developer.github.com/apps/building-oauth-apps/authorizing-oauth-apps/#web-application-flow .. notes::"""
def login(self, context):
"""github Login :type context: Context :param context: :rtype: dict :return: token and instance of user... | stack_v2_sparse_classes_36k_train_022764 | 17,886 | permissive | [
{
"docstring": "github Login :type context: Context :param context: :rtype: dict :return: token and instance of user",
"name": "login",
"signature": "def login(self, context)"
},
{
"docstring": "Get github access token :type code: str :param code: :rtype: str :return: access token",
"name": ... | 4 | stack_v2_sparse_classes_30k_train_014582 | Implement the Python class `GithubLogin` described below.
Class description:
Sign in with github docs: https://developer.github.com/apps/building-oauth-apps/authorizing-oauth-apps/#web-application-flow .. notes::
Method signatures and docstrings:
- def login(self, context): github Login :type context: Context :param ... | Implement the Python class `GithubLogin` described below.
Class description:
Sign in with github docs: https://developer.github.com/apps/building-oauth-apps/authorizing-oauth-apps/#web-application-flow .. notes::
Method signatures and docstrings:
- def login(self, context): github Login :type context: Context :param ... | 945c4fd2755f5b0dea11e54eb649eeb37ec93d01 | <|skeleton|>
class GithubLogin:
"""Sign in with github docs: https://developer.github.com/apps/building-oauth-apps/authorizing-oauth-apps/#web-application-flow .. notes::"""
def login(self, context):
"""github Login :type context: Context :param context: :rtype: dict :return: token and instance of user... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GithubLogin:
"""Sign in with github docs: https://developer.github.com/apps/building-oauth-apps/authorizing-oauth-apps/#web-application-flow .. notes::"""
def login(self, context):
"""github Login :type context: Context :param context: :rtype: dict :return: token and instance of user"""
s... | the_stack_v2_python_sparse | open-hackathon-server/src/hackathon/user/oauth_login.py | kaiyuanshe/open-hackathon | train | 46 |
199df07e13b13d9b2b855b8205e71c1ffdabe5e3 | [
"batch_size = input.shape[2]\noutput = np.dsplit(input, batch_size)\nfor i in range(batch_size):\n output[i] = output[i][:, :, 0]\nreturn output",
"batch_size = len(input)\nfor i in range(batch_size):\n input[i] = input[i][..., None]\noutput = np.dstack(input)\nreturn output"
] | <|body_start_0|>
batch_size = input.shape[2]
output = np.dsplit(input, batch_size)
for i in range(batch_size):
output[i] = output[i][:, :, 0]
return output
<|end_body_0|>
<|body_start_1|>
batch_size = len(input)
for i in range(batch_size):
input[i... | Module is an abstract class. It handles numpy array data. Assumes working with consistent data format for all inputs and outputs: mxnxb numpy array b refers to batch m,n are arbitrary | Module | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Module:
"""Module is an abstract class. It handles numpy array data. Assumes working with consistent data format for all inputs and outputs: mxnxb numpy array b refers to batch m,n are arbitrary"""
def __unbatch__(self, input):
"""Takes a mxnxb numpy array and returns a list of b mxn... | stack_v2_sparse_classes_36k_train_022765 | 1,100 | no_license | [
{
"docstring": "Takes a mxnxb numpy array and returns a list of b mxn numpy arrays. This is useful for separating the 3-d numpy array into a list of 2-d arrays to perform some operation on each 2-d array. Args: input: mxnxb numpy array Returns: list of b mxn numpy arrays",
"name": "__unbatch__",
"signat... | 2 | stack_v2_sparse_classes_30k_train_007898 | Implement the Python class `Module` described below.
Class description:
Module is an abstract class. It handles numpy array data. Assumes working with consistent data format for all inputs and outputs: mxnxb numpy array b refers to batch m,n are arbitrary
Method signatures and docstrings:
- def __unbatch__(self, inpu... | Implement the Python class `Module` described below.
Class description:
Module is an abstract class. It handles numpy array data. Assumes working with consistent data format for all inputs and outputs: mxnxb numpy array b refers to batch m,n are arbitrary
Method signatures and docstrings:
- def __unbatch__(self, inpu... | 9d964dceadb0f5182f456886eaa5476e185dd818 | <|skeleton|>
class Module:
"""Module is an abstract class. It handles numpy array data. Assumes working with consistent data format for all inputs and outputs: mxnxb numpy array b refers to batch m,n are arbitrary"""
def __unbatch__(self, input):
"""Takes a mxnxb numpy array and returns a list of b mxn... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Module:
"""Module is an abstract class. It handles numpy array data. Assumes working with consistent data format for all inputs and outputs: mxnxb numpy array b refers to batch m,n are arbitrary"""
def __unbatch__(self, input):
"""Takes a mxnxb numpy array and returns a list of b mxn numpy arrays... | the_stack_v2_python_sparse | assignment2/module.py | mqtlam/osu-cs519-006 | train | 4 |
7188f4eb39c5c7021e91919d10da159d2f547c47 | [
"kw = super(ProjectTaskView, self).get_form_kwargs()\nkw.update({'organization': self.request.user.organization})\nreturn kw",
"context = super(ProjectTaskView, self).get_context_data(**kwargs)\nproject = get_object_or_404(Project, id=self.kwargs['pk'])\ntasks = project.task_set.all()\ncount = tasks.count()\niden... | <|body_start_0|>
kw = super(ProjectTaskView, self).get_form_kwargs()
kw.update({'organization': self.request.user.organization})
return kw
<|end_body_0|>
<|body_start_1|>
context = super(ProjectTaskView, self).get_context_data(**kwargs)
project = get_object_or_404(Project, id=se... | Create a project task. | ProjectTaskView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectTaskView:
"""Create a project task."""
def get_form_kwargs(self):
"""Pass organization to form."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Return tasks belonging to the story."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
kw... | stack_v2_sparse_classes_36k_train_022766 | 11,257 | permissive | [
{
"docstring": "Pass organization to form.",
"name": "get_form_kwargs",
"signature": "def get_form_kwargs(self)"
},
{
"docstring": "Return tasks belonging to the story.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001021 | Implement the Python class `ProjectTaskView` described below.
Class description:
Create a project task.
Method signatures and docstrings:
- def get_form_kwargs(self): Pass organization to form.
- def get_context_data(self, **kwargs): Return tasks belonging to the story. | Implement the Python class `ProjectTaskView` described below.
Class description:
Create a project task.
Method signatures and docstrings:
- def get_form_kwargs(self): Pass organization to form.
- def get_context_data(self, **kwargs): Return tasks belonging to the story.
<|skeleton|>
class ProjectTaskView:
"""Cre... | dc6bc79d450f7e2bdf59cfbcd306d05a736e4db9 | <|skeleton|>
class ProjectTaskView:
"""Create a project task."""
def get_form_kwargs(self):
"""Pass organization to form."""
<|body_0|>
def get_context_data(self, **kwargs):
"""Return tasks belonging to the story."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectTaskView:
"""Create a project task."""
def get_form_kwargs(self):
"""Pass organization to form."""
kw = super(ProjectTaskView, self).get_form_kwargs()
kw.update({'organization': self.request.user.organization})
return kw
def get_context_data(self, **kwargs):
... | the_stack_v2_python_sparse | project/editorial/views/tasks.py | ProjectFacet/facet | train | 25 |
ff83553c0628dee449bfe723f6d0cbc7698c1a00 | [
"context = super().get_context_data()\ncontext['datasource'] = models.DataSource.objects.get(pk=self.kwargs['pk'])\nreturn context",
"self.datasource = models.DataSource.objects.get(pk=self.kwargs['pk'])\nuser = self.request.user\nif self.request.user == self.datasource.owner or self.request.user.is_superuser:\n ... | <|body_start_0|>
context = super().get_context_data()
context['datasource'] = models.DataSource.objects.get(pk=self.kwargs['pk'])
return context
<|end_body_0|>
<|body_start_1|>
self.datasource = models.DataSource.objects.get(pk=self.kwargs['pk'])
user = self.request.user
... | Request access to a data source, or request changes to an existing permission. Provides a form view to edit permission requests, but permissions may also be requested using an AJAX POST request. | DataSourceAccessRequestView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataSourceAccessRequestView:
"""Request access to a data source, or request changes to an existing permission. Provides a form view to edit permission requests, but permissions may also be requested using an AJAX POST request."""
def get_context_data(self, **kwargs):
"""Add data sour... | stack_v2_sparse_classes_36k_train_022767 | 7,233 | permissive | [
{
"docstring": "Add data source to the context.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstring": "Get or create a permission object for the relevant user.",
"name": "get_object",
"signature": "def get_object(self, queryset=None)"
},
... | 5 | stack_v2_sparse_classes_30k_train_003781 | Implement the Python class `DataSourceAccessRequestView` described below.
Class description:
Request access to a data source, or request changes to an existing permission. Provides a form view to edit permission requests, but permissions may also be requested using an AJAX POST request.
Method signatures and docstrin... | Implement the Python class `DataSourceAccessRequestView` described below.
Class description:
Request access to a data source, or request changes to an existing permission. Provides a form view to edit permission requests, but permissions may also be requested using an AJAX POST request.
Method signatures and docstrin... | 25a111ac7cf4b23fee50ad8eac6ea21564954859 | <|skeleton|>
class DataSourceAccessRequestView:
"""Request access to a data source, or request changes to an existing permission. Provides a form view to edit permission requests, but permissions may also be requested using an AJAX POST request."""
def get_context_data(self, **kwargs):
"""Add data sour... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataSourceAccessRequestView:
"""Request access to a data source, or request changes to an existing permission. Provides a form view to edit permission requests, but permissions may also be requested using an AJAX POST request."""
def get_context_data(self, **kwargs):
"""Add data source to the con... | the_stack_v2_python_sparse | datasources/views/user_permission_link.py | PEDASI/PEDASI | train | 0 |
30d30150ac10063ee1a4e816b3ba2661930c94c1 | [
"checksum = crc(path, content)\ntry:\n fobj = File.objects.get(path=path)\nexcept File.DoesNotExist:\n return True\nelse:\n return str(fobj.checksum) != checksum",
"checksum = crc(path, content)\ntry:\n fobj = File.objects.get(path=path)\nexcept File.DoesNotExist:\n fobj = File(path=path)\nfobj.che... | <|body_start_0|>
checksum = crc(path, content)
try:
fobj = File.objects.get(path=path)
except File.DoesNotExist:
return True
else:
return str(fobj.checksum) != checksum
<|end_body_0|>
<|body_start_1|>
checksum = crc(path, content)
try:... | FileManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileManager:
def is_changed(self, path, content=None):
"""Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file is stored in DB."""
<|body_0|>
def save_file(self, path, content=None):
"""Save ... | stack_v2_sparse_classes_36k_train_022768 | 1,644 | no_license | [
{
"docstring": "Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file is stored in DB.",
"name": "is_changed",
"signature": "def is_changed(self, path, content=None)"
},
{
"docstring": "Save checksum of the file.",
"n... | 2 | null | Implement the Python class `FileManager` described below.
Class description:
Implement the FileManager class.
Method signatures and docstrings:
- def is_changed(self, path, content=None): Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file i... | Implement the Python class `FileManager` described below.
Class description:
Implement the FileManager class.
Method signatures and docstrings:
- def is_changed(self, path, content=None): Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file i... | 40313d4b413a219ff2f7dfc9775258f23608b2cc | <|skeleton|>
class FileManager:
def is_changed(self, path, content=None):
"""Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file is stored in DB."""
<|body_0|>
def save_file(self, path, content=None):
"""Save ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileManager:
def is_changed(self, path, content=None):
"""Compare checksum of the file stored in DB and the actual file on the disk. `is_changed` is always true if no info about the file is stored in DB."""
checksum = crc(path, content)
try:
fobj = File.objects.get(path=pat... | the_stack_v2_python_sparse | parser/models.py | govtrack/govtrack.us-web | train | 310 | |
41c90b097d5e3d50c2e8234ba740ef99038953b2 | [
"self.driver = driver\nself.comp_name = comp_name\nself.element = self.get_component()",
"self.hide_activity_box()\nself.element.click()\nreturn self.find_elems('select[name=\"' + self.comp_name + '\"] option')",
"self.hide_activity_box()\ndeptlist = self.get_department_list()\nif deptlist:\n deptlist[num].c... | <|body_start_0|>
self.driver = driver
self.comp_name = comp_name
self.element = self.get_component()
<|end_body_0|>
<|body_start_1|>
self.hide_activity_box()
self.element.click()
return self.find_elems('select[name="' + self.comp_name + '"] option')
<|end_body_1|>
<|bod... | 部门选择框控件 | DepartmentPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DepartmentPage:
"""部门选择框控件"""
def __init__(self, driver, comp_name):
"""类初始化执行"""
<|body_0|>
def get_department_list(self):
"""获取部门选择框的选项"""
<|body_1|>
def select_department_num(self, num):
"""获取某个部门的选择值"""
<|body_2|>
def get_dep... | stack_v2_sparse_classes_36k_train_022769 | 2,660 | no_license | [
{
"docstring": "类初始化执行",
"name": "__init__",
"signature": "def __init__(self, driver, comp_name)"
},
{
"docstring": "获取部门选择框的选项",
"name": "get_department_list",
"signature": "def get_department_list(self)"
},
{
"docstring": "获取某个部门的选择值",
"name": "select_department_num",
"... | 5 | stack_v2_sparse_classes_30k_train_014936 | Implement the Python class `DepartmentPage` described below.
Class description:
部门选择框控件
Method signatures and docstrings:
- def __init__(self, driver, comp_name): 类初始化执行
- def get_department_list(self): 获取部门选择框的选项
- def select_department_num(self, num): 获取某个部门的选择值
- def get_department_list_name(self): 获取部门选择框的选项
- de... | Implement the Python class `DepartmentPage` described below.
Class description:
部门选择框控件
Method signatures and docstrings:
- def __init__(self, driver, comp_name): 类初始化执行
- def get_department_list(self): 获取部门选择框的选项
- def select_department_num(self, num): 获取某个部门的选择值
- def get_department_list_name(self): 获取部门选择框的选项
- de... | 78768989a79a14013b983024cf6e4838d51ed595 | <|skeleton|>
class DepartmentPage:
"""部门选择框控件"""
def __init__(self, driver, comp_name):
"""类初始化执行"""
<|body_0|>
def get_department_list(self):
"""获取部门选择框的选项"""
<|body_1|>
def select_department_num(self, num):
"""获取某个部门的选择值"""
<|body_2|>
def get_dep... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DepartmentPage:
"""部门选择框控件"""
def __init__(self, driver, comp_name):
"""类初始化执行"""
self.driver = driver
self.comp_name = comp_name
self.element = self.get_component()
def get_department_list(self):
"""获取部门选择框的选项"""
self.hide_activity_box()
self.... | the_stack_v2_python_sparse | test_case/page_obj/form/department_page.py | pylk/pythonSelenium | train | 0 |
e216afe13dbbfdfda64a40e22bb733a09002e788 | [
"super(MultiAgentEnvironment, self).__init__(environment)\nself._agent_name = agent_name\nself._other_agents = other_agents",
"obs = self.observation()\naction_dict = {k: agent.step(obs) for k, agent in self._other_agents.items()}\naction_dict[self._agent_name] = action\nreturn self._environment.step(action_dict)... | <|body_start_0|>
super(MultiAgentEnvironment, self).__init__(environment)
self._agent_name = agent_name
self._other_agents = other_agents
<|end_body_0|>
<|body_start_1|>
obs = self.observation()
action_dict = {k: agent.step(obs) for k, agent in self._other_agents.items()}
... | Environment class for converting multi-agent into single-agent task. | MultiAgentEnvironment | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiAgentEnvironment:
"""Environment class for converting multi-agent into single-agent task."""
def __init__(self, environment, agent_name, **other_agents):
"""Constructor. Args: environment: Instance of ../moog/environment.Environment. Should have a Composite action space. agent_n... | stack_v2_sparse_classes_36k_train_022770 | 1,972 | permissive | [
{
"docstring": "Constructor. Args: environment: Instance of ../moog/environment.Environment. Should have a Composite action space. agent_name: Name of the agent being controlled by the player's joystick in the demo. Specifically, this is the key used for the joystick action value when passed into the Composite ... | 2 | stack_v2_sparse_classes_30k_train_007565 | Implement the Python class `MultiAgentEnvironment` described below.
Class description:
Environment class for converting multi-agent into single-agent task.
Method signatures and docstrings:
- def __init__(self, environment, agent_name, **other_agents): Constructor. Args: environment: Instance of ../moog/environment.E... | Implement the Python class `MultiAgentEnvironment` described below.
Class description:
Environment class for converting multi-agent into single-agent task.
Method signatures and docstrings:
- def __init__(self, environment, agent_name, **other_agents): Constructor. Args: environment: Instance of ../moog/environment.E... | 3e89e46a5918d59475851f9d4f1558956c110d38 | <|skeleton|>
class MultiAgentEnvironment:
"""Environment class for converting multi-agent into single-agent task."""
def __init__(self, environment, agent_name, **other_agents):
"""Constructor. Args: environment: Instance of ../moog/environment.Environment. Should have a Composite action space. agent_n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiAgentEnvironment:
"""Environment class for converting multi-agent into single-agent task."""
def __init__(self, environment, agent_name, **other_agents):
"""Constructor. Args: environment: Instance of ../moog/environment.Environment. Should have a Composite action space. agent_name: Name of ... | the_stack_v2_python_sparse | moog/env_wrappers/multi_agent.py | hokysung/moog.github.io | train | 0 |
7c1050fd1d624f8ab51e1d2319a4add9fb590816 | [
"if not root:\n return '-1001'\nreturn str(root.val) + ',' + self.serialize(root.left) + ',' + self.serialize(root.right)",
"def helper(dq):\n value = dq.popleft()\n if value == -1001:\n return None\n node = TreeNode(value)\n node.left = helper(dq)\n node.right = helper(dq)\n return no... | <|body_start_0|>
if not root:
return '-1001'
return str(root.val) + ',' + self.serialize(root.left) + ',' + self.serialize(root.right)
<|end_body_0|>
<|body_start_1|>
def helper(dq):
value = dq.popleft()
if value == -1001:
return None
... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_022771 | 1,962 | permissive | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_011860 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 08f3bd22923b652f9d676ffa2af3dc037eed6d73 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return '-1001'
return str(root.val) + ',' + self.serialize(root.left) + ',' + self.serialize(root.right)
def deserialize(self, data):
"""Dec... | the_stack_v2_python_sparse | LeetCode/Serialize-Deserialize-Binary-Tree.py | sethmh82/SethDevelopment | train | 0 | |
18214815ed8c9b59de74f43bef956f828b735b9f | [
"base.Action.__init__(self, self.__openNotebooks)\nself.enabled = ENABLED\nself.__overlayList = overlayList\nself.__displayCtx = displayCtx\nself.__frame = frame\nself.__kernel = None\nself.__server = None",
"if self.__kernel is not None and (not self.__kernel.is_alive()):\n self.__kernel = None\nif self.__ser... | <|body_start_0|>
base.Action.__init__(self, self.__openNotebooks)
self.enabled = ENABLED
self.__overlayList = overlayList
self.__displayCtx = displayCtx
self.__frame = frame
self.__kernel = None
self.__server = None
<|end_body_0|>
<|body_start_1|>
if self... | The ``NotebookAction`` is an :class:`.Action` which (if necessary) starts an embedded IPython kernel and a jupyter notebook server, and opens the server home page in a web browser allowing the user to interact with FSLeyes via notebooks. | NotebookAction | [
"BSD-3-Clause",
"CC-BY-3.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotebookAction:
"""The ``NotebookAction`` is an :class:`.Action` which (if necessary) starts an embedded IPython kernel and a jupyter notebook server, and opens the server home page in a web browser allowing the user to interact with FSLeyes via notebooks."""
def __init__(self, overlayList, ... | stack_v2_sparse_classes_36k_train_022772 | 22,260 | permissive | [
{
"docstring": "Create a ``NotebookAction``. :arg overlayList: The :class:`.OverlayList`. :arg displayCtx: The master :class:`.DisplayContext`. :arg frame: The :class:`.FSLeyesFrame`.",
"name": "__init__",
"signature": "def __init__(self, overlayList, displayCtx, frame)"
},
{
"docstring": "Calle... | 5 | null | Implement the Python class `NotebookAction` described below.
Class description:
The ``NotebookAction`` is an :class:`.Action` which (if necessary) starts an embedded IPython kernel and a jupyter notebook server, and opens the server home page in a web browser allowing the user to interact with FSLeyes via notebooks.
... | Implement the Python class `NotebookAction` described below.
Class description:
The ``NotebookAction`` is an :class:`.Action` which (if necessary) starts an embedded IPython kernel and a jupyter notebook server, and opens the server home page in a web browser allowing the user to interact with FSLeyes via notebooks.
... | 46ccb4fe2b2346eb57576247f49714032b61307a | <|skeleton|>
class NotebookAction:
"""The ``NotebookAction`` is an :class:`.Action` which (if necessary) starts an embedded IPython kernel and a jupyter notebook server, and opens the server home page in a web browser allowing the user to interact with FSLeyes via notebooks."""
def __init__(self, overlayList, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotebookAction:
"""The ``NotebookAction`` is an :class:`.Action` which (if necessary) starts an embedded IPython kernel and a jupyter notebook server, and opens the server home page in a web browser allowing the user to interact with FSLeyes via notebooks."""
def __init__(self, overlayList, displayCtx, f... | the_stack_v2_python_sparse | fsleyes/actions/notebook.py | sanjayankur31/fsleyes | train | 1 |
283c6f90c1997c7114004350326be1de7b6141d9 | [
"parameters = json_parameters(optional=True)\nestimate_ttc = param_get(parameters, 'estimate_ttc', default=False)\nif estimate_ttc:\n return generate_http_error_flask(501, 'NotImplemented', exc_msg='estimate_ttc is not implemented!')\ntry:\n rule = get_replication_rule(rule_id, issuer=request.environ.get('iss... | <|body_start_0|>
parameters = json_parameters(optional=True)
estimate_ttc = param_get(parameters, 'estimate_ttc', default=False)
if estimate_ttc:
return generate_http_error_flask(501, 'NotImplemented', exc_msg='estimate_ttc is not implemented!')
try:
rule = get_re... | REST APIs for replication rules. | Rule | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rule:
"""REST APIs for replication rules."""
def get(self, rule_id):
"""--- summary: Return a Rule tags: - Rule parameters: - name: rule_id in: path description: The id of the replication rule. schema: type: string style: simple responses: 200: description: OK content: application/js... | stack_v2_sparse_classes_36k_train_022773 | 31,808 | permissive | [
{
"docstring": "--- summary: Return a Rule tags: - Rule parameters: - name: rule_id in: path description: The id of the replication rule. schema: type: string style: simple responses: 200: description: OK content: application/json: schema: type: string 406: description: Not Acceptable 401: description: Invalid ... | 3 | null | Implement the Python class `Rule` described below.
Class description:
REST APIs for replication rules.
Method signatures and docstrings:
- def get(self, rule_id): --- summary: Return a Rule tags: - Rule parameters: - name: rule_id in: path description: The id of the replication rule. schema: type: string style: simpl... | Implement the Python class `Rule` described below.
Class description:
REST APIs for replication rules.
Method signatures and docstrings:
- def get(self, rule_id): --- summary: Return a Rule tags: - Rule parameters: - name: rule_id in: path description: The id of the replication rule. schema: type: string style: simpl... | 7f0d229ac0b3bc7dec12c6e158bea2b82d414a3b | <|skeleton|>
class Rule:
"""REST APIs for replication rules."""
def get(self, rule_id):
"""--- summary: Return a Rule tags: - Rule parameters: - name: rule_id in: path description: The id of the replication rule. schema: type: string style: simple responses: 200: description: OK content: application/js... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Rule:
"""REST APIs for replication rules."""
def get(self, rule_id):
"""--- summary: Return a Rule tags: - Rule parameters: - name: rule_id in: path description: The id of the replication rule. schema: type: string style: simple responses: 200: description: OK content: application/json: schema: t... | the_stack_v2_python_sparse | lib/rucio/web/rest/flaskapi/v1/rules.py | rucio/rucio | train | 232 |
df2a3038d307c16f6c7ea0ef1ccd4e11876e461a | [
"self.face_cascade = cv.CascadeClassifier(cascade_file_path)\nif self.face_cascade.empty():\n print(\"Classifier failed to load '{}' filepath\".format(cascade_file_path))\n raise",
"rows, cols = frame.shape[:2]\nself.all_faces = self.face_cascade.detectMultiScale(frame, scaleFactor=1.3, minNeighbors=5)\nif ... | <|body_start_0|>
self.face_cascade = cv.CascadeClassifier(cascade_file_path)
if self.face_cascade.empty():
print("Classifier failed to load '{}' filepath".format(cascade_file_path))
raise
<|end_body_0|>
<|body_start_1|>
rows, cols = frame.shape[:2]
self.all_faces... | Wrapper for the OpenCV program for detecting faces. Calling the 'detect_faces(...)' method on an image will get the information on the faces in the image. This class allows for an implementation agnostic way of detecting faces. | FaceDetector | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaceDetector:
"""Wrapper for the OpenCV program for detecting faces. Calling the 'detect_faces(...)' method on an image will get the information on the faces in the image. This class allows for an implementation agnostic way of detecting faces."""
def __init__(self, cascade_file_path=default... | stack_v2_sparse_classes_36k_train_022774 | 3,297 | permissive | [
{
"docstring": "Loads the image classifier and raises an exception if the classifier fails to load the xml classifier file. When using a different classifier xml, make sure to take into account relative file paths to avoid raising an exception.",
"name": "__init__",
"signature": "def __init__(self, casc... | 2 | stack_v2_sparse_classes_30k_train_007996 | Implement the Python class `FaceDetector` described below.
Class description:
Wrapper for the OpenCV program for detecting faces. Calling the 'detect_faces(...)' method on an image will get the information on the faces in the image. This class allows for an implementation agnostic way of detecting faces.
Method signa... | Implement the Python class `FaceDetector` described below.
Class description:
Wrapper for the OpenCV program for detecting faces. Calling the 'detect_faces(...)' method on an image will get the information on the faces in the image. This class allows for an implementation agnostic way of detecting faces.
Method signa... | c9cf67c7c502406465d647d013f0d98cad2d4c44 | <|skeleton|>
class FaceDetector:
"""Wrapper for the OpenCV program for detecting faces. Calling the 'detect_faces(...)' method on an image will get the information on the faces in the image. This class allows for an implementation agnostic way of detecting faces."""
def __init__(self, cascade_file_path=default... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FaceDetector:
"""Wrapper for the OpenCV program for detecting faces. Calling the 'detect_faces(...)' method on an image will get the information on the faces in the image. This class allows for an implementation agnostic way of detecting faces."""
def __init__(self, cascade_file_path=default_cascade_file... | the_stack_v2_python_sparse | ComputerVisionServer/moedx/facial_detection/face_detector.py | mobiledgex/edge-cloud-sampleapps | train | 12 |
43521002cadebc97931bef20f52c89d39e0106af | [
"if not genre:\n return random.choice(VIDEOS)\nelse:\n songs = [song for song in VIDEOS if genre.casefold() in song['genre']]\n try:\n return random.choice(songs)\n except IndexError:\n log.info('No videos for that genre.')",
"anthem = self.get_video(genre)\nif anthem:\n await ctx.sen... | <|body_start_0|>
if not genre:
return random.choice(VIDEOS)
else:
songs = [song for song in VIDEOS if genre.casefold() in song['genre']]
try:
return random.choice(songs)
except IndexError:
log.info('No videos for that genre.... | Embed a random youtube video for a gay anthem! | PrideAnthem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrideAnthem:
"""Embed a random youtube video for a gay anthem!"""
def get_video(self, genre: Optional[str]=None) -> dict:
"""Picks a random anthem from the list. If `genre` is supplied, it will pick from videos attributed with that genre. If none can be found, it will log this as wel... | stack_v2_sparse_classes_36k_train_022775 | 1,572 | permissive | [
{
"docstring": "Picks a random anthem from the list. If `genre` is supplied, it will pick from videos attributed with that genre. If none can be found, it will log this as well as provide that information to the user.",
"name": "get_video",
"signature": "def get_video(self, genre: Optional[str]=None) ->... | 2 | stack_v2_sparse_classes_30k_train_009603 | Implement the Python class `PrideAnthem` described below.
Class description:
Embed a random youtube video for a gay anthem!
Method signatures and docstrings:
- def get_video(self, genre: Optional[str]=None) -> dict: Picks a random anthem from the list. If `genre` is supplied, it will pick from videos attributed with ... | Implement the Python class `PrideAnthem` described below.
Class description:
Embed a random youtube video for a gay anthem!
Method signatures and docstrings:
- def get_video(self, genre: Optional[str]=None) -> dict: Picks a random anthem from the list. If `genre` is supplied, it will pick from videos attributed with ... | 7aaf8f406fcb6cbe89e4b6742eff6c3efa754993 | <|skeleton|>
class PrideAnthem:
"""Embed a random youtube video for a gay anthem!"""
def get_video(self, genre: Optional[str]=None) -> dict:
"""Picks a random anthem from the list. If `genre` is supplied, it will pick from videos attributed with that genre. If none can be found, it will log this as wel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrideAnthem:
"""Embed a random youtube video for a gay anthem!"""
def get_video(self, genre: Optional[str]=None) -> dict:
"""Picks a random anthem from the list. If `genre` is supplied, it will pick from videos attributed with that genre. If none can be found, it will log this as well as provide ... | the_stack_v2_python_sparse | bot/exts/pride/pride_anthem.py | Lynchly/sir-lancebot | train | 1 |
ea97491740fdb756629ae14602b1db028a3c93fa | [
"leoTkinterDialog.__init__(self, 'Enter unique id', resizeable=False, canClose=False)\nself.id_entry = None\nself.answer = None\nself.createTopFrame()\nself.top.bind('<Key>', self.onKey)\nmessage = 'leoID.txt not found\\n\\n' + 'Please enter an id that identifies you uniquely.\\n' + 'Your cvs login name is a good c... | <|body_start_0|>
leoTkinterDialog.__init__(self, 'Enter unique id', resizeable=False, canClose=False)
self.id_entry = None
self.answer = None
self.createTopFrame()
self.top.bind('<Key>', self.onKey)
message = 'leoID.txt not found\n\n' + 'Please enter an id that identifies... | A class that creates the Tkinter About Leo dialog. | tkinterAskLeoID | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class tkinterAskLeoID:
"""A class that creates the Tkinter About Leo dialog."""
def __init__(self):
"""Create the Leo Id dialog."""
<|body_0|>
def createFrame(self, message):
"""Create the frame for the Leo Id dialog."""
<|body_1|>
def onButton(self):
... | stack_v2_sparse_classes_36k_train_022776 | 25,997 | no_license | [
{
"docstring": "Create the Leo Id dialog.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create the frame for the Leo Id dialog.",
"name": "createFrame",
"signature": "def createFrame(self, message)"
},
{
"docstring": "Handle clicks in the Leo Id close... | 4 | stack_v2_sparse_classes_30k_test_000852 | Implement the Python class `tkinterAskLeoID` described below.
Class description:
A class that creates the Tkinter About Leo dialog.
Method signatures and docstrings:
- def __init__(self): Create the Leo Id dialog.
- def createFrame(self, message): Create the frame for the Leo Id dialog.
- def onButton(self): Handle c... | Implement the Python class `tkinterAskLeoID` described below.
Class description:
A class that creates the Tkinter About Leo dialog.
Method signatures and docstrings:
- def __init__(self): Create the Leo Id dialog.
- def createFrame(self, message): Create the frame for the Leo Id dialog.
- def onButton(self): Handle c... | 28c22721e1bc313c120a8a6c288893bc566a5c67 | <|skeleton|>
class tkinterAskLeoID:
"""A class that creates the Tkinter About Leo dialog."""
def __init__(self):
"""Create the Leo Id dialog."""
<|body_0|>
def createFrame(self, message):
"""Create the frame for the Leo Id dialog."""
<|body_1|>
def onButton(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class tkinterAskLeoID:
"""A class that creates the Tkinter About Leo dialog."""
def __init__(self):
"""Create the Leo Id dialog."""
leoTkinterDialog.__init__(self, 'Enter unique id', resizeable=False, canClose=False)
self.id_entry = None
self.answer = None
self.createTop... | the_stack_v2_python_sparse | Projects/jyleo/src/leoTkinterDialog.py | leo-editor/leo-editor-contrib | train | 6 |
a39b52fc67acb608709f1f240e28d2c48e34a1c6 | [
"if not root:\n return []\nstack, res = ([], [])\nstack.append(root)\nlevel = 0\nwhile stack:\n row, next_stack = ([], [])\n for node in stack:\n row.append(node.val)\n if node.left:\n next_stack.append(node.left)\n if node.right:\n next_stack.append(node.right)\n... | <|body_start_0|>
if not root:
return []
stack, res = ([], [])
stack.append(root)
level = 0
while stack:
row, next_stack = ([], [])
for node in stack:
row.append(node.val)
if node.left:
next_st... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrderBottom(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def levelOrderBottom_reverse_102(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i... | stack_v2_sparse_classes_36k_train_022777 | 1,479 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "levelOrderBottom",
"signature": "def levelOrderBottom(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "levelOrderBottom_reverse_102",
"signature": "def levelOrderBottom_reverse_... | 2 | stack_v2_sparse_classes_30k_train_006390 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrderBottom(self, root): :type root: TreeNode :rtype: List[List[int]]
- def levelOrderBottom_reverse_102(self, root): :type root: TreeNode :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrderBottom(self, root): :type root: TreeNode :rtype: List[List[int]]
- def levelOrderBottom_reverse_102(self, root): :type root: TreeNode :rtype: List[List[int]]
<|ske... | 1a3c1f4d6e9d3444039f087763b93241f4ba7892 | <|skeleton|>
class Solution:
def levelOrderBottom(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def levelOrderBottom_reverse_102(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrderBottom(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
if not root:
return []
stack, res = ([], [])
stack.append(root)
level = 0
while stack:
row, next_stack = ([], [])
for node in stack... | the_stack_v2_python_sparse | Algorithm/107_Binary_Tree_Level_Order_Traversal_II.py | Gi1ia/TechNoteBook | train | 7 | |
c06e86f717ba1f7db12ca21f7a94919476c21298 | [
"self.api_version = api_version or DEFAULT_VERSION\nself.client = apis.GetClientInstance(API_NAME, self.api_version)\nself.messages = apis.GetMessagesModule(API_NAME, self.api_version)",
"occurrence_iter = list_pager.YieldFromList(self.client.projects_notes_occurrences, request=self.messages.ContaineranalysisProj... | <|body_start_0|>
self.api_version = api_version or DEFAULT_VERSION
self.client = apis.GetClientInstance(API_NAME, self.api_version)
self.messages = apis.GetMessagesModule(API_NAME, self.api_version)
<|end_body_0|>
<|body_start_1|>
occurrence_iter = list_pager.YieldFromList(self.client.p... | A client to access containeranalysis for binauthz purposes. | Client | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Client:
"""A client to access containeranalysis for binauthz purposes."""
def __init__(self, api_version=None):
"""Creates a ContainerAnalysisClient. Args: api_version: The containeranalysis API version to use."""
<|body_0|>
def YieldAttestations(self, note_ref, artifact... | stack_v2_sparse_classes_36k_train_022778 | 9,068 | permissive | [
{
"docstring": "Creates a ContainerAnalysisClient. Args: api_version: The containeranalysis API version to use.",
"name": "__init__",
"signature": "def __init__(self, api_version=None)"
},
{
"docstring": "Yields occurrences associated with given AA Note. Args: note_ref: The Note reference that w... | 5 | null | Implement the Python class `Client` described below.
Class description:
A client to access containeranalysis for binauthz purposes.
Method signatures and docstrings:
- def __init__(self, api_version=None): Creates a ContainerAnalysisClient. Args: api_version: The containeranalysis API version to use.
- def YieldAttes... | Implement the Python class `Client` described below.
Class description:
A client to access containeranalysis for binauthz purposes.
Method signatures and docstrings:
- def __init__(self, api_version=None): Creates a ContainerAnalysisClient. Args: api_version: The containeranalysis API version to use.
- def YieldAttes... | 85bb264e273568b5a0408f733b403c56373e2508 | <|skeleton|>
class Client:
"""A client to access containeranalysis for binauthz purposes."""
def __init__(self, api_version=None):
"""Creates a ContainerAnalysisClient. Args: api_version: The containeranalysis API version to use."""
<|body_0|>
def YieldAttestations(self, note_ref, artifact... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Client:
"""A client to access containeranalysis for binauthz purposes."""
def __init__(self, api_version=None):
"""Creates a ContainerAnalysisClient. Args: api_version: The containeranalysis API version to use."""
self.api_version = api_version or DEFAULT_VERSION
self.client = api... | the_stack_v2_python_sparse | google-cloud-sdk/lib/googlecloudsdk/api_lib/container/binauthz/containeranalysis.py | bopopescu/socialliteapp | train | 0 |
36d005638c04e322a358545e4258028c2e388bcc | [
"errors = []\nif not HAS_TEXTFSM:\n errors.append(missing_required_lib('textfsm'))\nreturn {'errors': errors}",
"cli_output = self._task_args.get('text')\nres = self._check_reqs()\nif res.get('errors'):\n return {'errors': res.get('errors')}\ntry:\n template = open(self._task_args.get('parser').get('temp... | <|body_start_0|>
errors = []
if not HAS_TEXTFSM:
errors.append(missing_required_lib('textfsm'))
return {'errors': errors}
<|end_body_0|>
<|body_start_1|>
cli_output = self._task_args.get('text')
res = self._check_reqs()
if res.get('errors'):
retur... | The textfsm parser class Convert raw text to structured data using textfsm | CliParser | [
"GPL-3.0-or-later",
"GPL-3.0-only",
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CliParser:
"""The textfsm parser class Convert raw text to structured data using textfsm"""
def _check_reqs():
"""Check the prerequisites for the textfsm parser :return dict: A dict with errors or a template_path"""
<|body_0|>
def parse(self, *_args, **_kwargs):
... | stack_v2_sparse_classes_36k_train_022779 | 2,009 | permissive | [
{
"docstring": "Check the prerequisites for the textfsm parser :return dict: A dict with errors or a template_path",
"name": "_check_reqs",
"signature": "def _check_reqs()"
},
{
"docstring": "Std entry point for a cli_parse parse execution :return: Errors or parsed text as structured data :rtype... | 2 | null | Implement the Python class `CliParser` described below.
Class description:
The textfsm parser class Convert raw text to structured data using textfsm
Method signatures and docstrings:
- def _check_reqs(): Check the prerequisites for the textfsm parser :return dict: A dict with errors or a template_path
- def parse(se... | Implement the Python class `CliParser` described below.
Class description:
The textfsm parser class Convert raw text to structured data using textfsm
Method signatures and docstrings:
- def _check_reqs(): Check the prerequisites for the textfsm parser :return dict: A dict with errors or a template_path
- def parse(se... | 2ea7d4f00212f502bc684ac257371ada73da1ca9 | <|skeleton|>
class CliParser:
"""The textfsm parser class Convert raw text to structured data using textfsm"""
def _check_reqs():
"""Check the prerequisites for the textfsm parser :return dict: A dict with errors or a template_path"""
<|body_0|>
def parse(self, *_args, **_kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CliParser:
"""The textfsm parser class Convert raw text to structured data using textfsm"""
def _check_reqs():
"""Check the prerequisites for the textfsm parser :return dict: A dict with errors or a template_path"""
errors = []
if not HAS_TEXTFSM:
errors.append(missing... | the_stack_v2_python_sparse | intro-ansible/venv3/lib/python3.8/site-packages/ansible_collections/ansible/netcommon/plugins/cli_parsers/textfsm_parser.py | SimonFangCisco/dne-dna-code | train | 0 |
a639412340c7c976da22e0ae2f1cb875ddf94df8 | [
"r = Round.query.get(round_id)\nif r is not None:\n return r.progress_data()\nabort(404, 'Unknown round_id')",
"previous_round = Round.query.get(round_id)\nif previous_round is not None:\n r = Round()\n r.type = api.payload['type']\n r.set_marks(api.payload['min_marks'], api.payload['max_marks'])\n ... | <|body_start_0|>
r = Round.query.get(round_id)
if r is not None:
return r.progress_data()
abort(404, 'Unknown round_id')
<|end_body_0|>
<|body_start_1|>
previous_round = Round.query.get(round_id)
if previous_round is not None:
r = Round()
r.ty... | RoundAPIProgress | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoundAPIProgress:
def get(self, round_id):
"""Get progress data"""
<|body_0|>
def post(self, round_id):
"""Create the next round"""
<|body_1|>
def patch(self, round_id):
"""Create the next round after a general look"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_022780 | 25,303 | no_license | [
{
"docstring": "Get progress data",
"name": "get",
"signature": "def get(self, round_id)"
},
{
"docstring": "Create the next round",
"name": "post",
"signature": "def post(self, round_id)"
},
{
"docstring": "Create the next round after a general look",
"name": "patch",
"s... | 3 | null | Implement the Python class `RoundAPIProgress` described below.
Class description:
Implement the RoundAPIProgress class.
Method signatures and docstrings:
- def get(self, round_id): Get progress data
- def post(self, round_id): Create the next round
- def patch(self, round_id): Create the next round after a general lo... | Implement the Python class `RoundAPIProgress` described below.
Class description:
Implement the RoundAPIProgress class.
Method signatures and docstrings:
- def get(self, round_id): Get progress data
- def post(self, round_id): Create the next round
- def patch(self, round_id): Create the next round after a general lo... | 079b109fd13683a31d1d632faa5ab72cf0e78ddf | <|skeleton|>
class RoundAPIProgress:
def get(self, round_id):
"""Get progress data"""
<|body_0|>
def post(self, round_id):
"""Create the next round"""
<|body_1|>
def patch(self, round_id):
"""Create the next round after a general look"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoundAPIProgress:
def get(self, round_id):
"""Get progress data"""
r = Round.query.get(round_id)
if r is not None:
return r.progress_data()
abort(404, 'Unknown round_id')
def post(self, round_id):
"""Create the next round"""
previous_round = Rou... | the_stack_v2_python_sparse | backend/apis/round/apis.py | AlenAlic/DANCE | train | 0 | |
3814f2821dcb4975da508bac93a117dce594b283 | [
"if m == 1 or n == 1:\n return 1\ndp = [[0] * (n + 1) for i in range(m + 1)]\ndp[1][2] = 1\ndp[2][1] = 1\nfor i in range(1, m + 1):\n for j in range(1, n + 1):\n if dp[i][j] != 0:\n continue\n dp[i][j] = dp[i - 1][j] + dp[i][j - 1]\nreturn dp[m][n]",
"direct = [[1, 0], [0, 1]]\nx, y... | <|body_start_0|>
if m == 1 or n == 1:
return 1
dp = [[0] * (n + 1) for i in range(m + 1)]
dp[1][2] = 1
dp[2][1] = 1
for i in range(1, m + 1):
for j in range(1, n + 1):
if dp[i][j] != 0:
continue
dp[i][j] ... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_0|>
def uniquePaths1(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if m == 1 or n == 1:
ret... | stack_v2_sparse_classes_36k_train_022781 | 1,083 | permissive | [
{
"docstring": ":type m: int :type n: int :rtype: int",
"name": "uniquePaths",
"signature": "def uniquePaths(self, m, n)"
},
{
"docstring": ":type m: int :type n: int :rtype: int",
"name": "uniquePaths1",
"signature": "def uniquePaths1(self, m, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m, n): :type m: int :type n: int :rtype: int
- def uniquePaths1(self, m, n): :type m: int :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m, n): :type m: int :type n: int :rtype: int
- def uniquePaths1(self, m, n): :type m: int :type n: int :rtype: int
<|skeleton|>
class Solution:
def un... | 64847cbb1adcaca4561b949e8acc52e8e031a6cb | <|skeleton|>
class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_0|>
def uniquePaths1(self, m, n):
""":type m: int :type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def uniquePaths(self, m, n):
""":type m: int :type n: int :rtype: int"""
if m == 1 or n == 1:
return 1
dp = [[0] * (n + 1) for i in range(m + 1)]
dp[1][2] = 1
dp[2][1] = 1
for i in range(1, m + 1):
for j in range(1, n + 1):
... | the_stack_v2_python_sparse | UniquePaths62.py | Bit64L/LeetCode-Python- | train | 0 | |
1b359b11eba1efb9e4f787f074d9e7165a756920 | [
"self.matrix = matrix\nrow = len(matrix)\nif row:\n col = len(matrix[0])\n for i in range(0, row):\n for j in range(0, col):\n if i > 0 and j > 0:\n matrix[i][j] = matrix[i][j - 1] + matrix[i - 1][j] + matrix[i][j] - matrix[i - 1][j - 1]\n if i == 0 and j > 0:\n ... | <|body_start_0|>
self.matrix = matrix
row = len(matrix)
if row:
col = len(matrix[0])
for i in range(0, row):
for j in range(0, col):
if i > 0 and j > 0:
matrix[i][j] = matrix[i][j - 1] + matrix[i - 1][j] + matrix... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :type row2: int :type col2: int :rtype: ... | stack_v2_sparse_classes_36k_train_022782 | 1,417 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": "sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
... | 2 | stack_v2_sparse_classes_30k_train_017185 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1... | 4599634f31d78a0372cf0ff6fb7935d054d5ecb5 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
"""sum of elements matrix[(row1,col1)..(row2,col2)], inclusive. :type row1: int :type col1: int :type row2: int :type col2: int :rtype: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
self.matrix = matrix
row = len(matrix)
if row:
col = len(matrix[0])
for i in range(0, row):
for j in range(0, col):
if i > 0 and j > 0:
... | the_stack_v2_python_sparse | medium/range_sum_query_2d.py | jhgdike/leetCode | train | 3 | |
82f1aa672511dbda1c943d39236384025f773ffc | [
"jane = Player(name='Jane')\nself.assertIsNotNone(jane)\nself.assertEqual(str(jane), 'Jane')\nphil = Player(name='Phil')\nself.assertIsNotNone(phil)\nself.assertEqual(str(phil), 'Phil')",
"player = Player(name='Bob')\nself.assertIsNotNone(player)\nself.assertEqual(str(player), 'Bob')\nself.assertTrue(player.is_si... | <|body_start_0|>
jane = Player(name='Jane')
self.assertIsNotNone(jane)
self.assertEqual(str(jane), 'Jane')
phil = Player(name='Phil')
self.assertIsNotNone(phil)
self.assertEqual(str(phil), 'Phil')
<|end_body_0|>
<|body_start_1|>
player = Player(name='Bob')
... | TestSequenceFunctions | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSequenceFunctions:
def test_new_Player(self):
"""Test basic Player construction."""
<|body_0|>
def test_Player(self):
"""Test Player class"""
<|body_1|>
def test_deal_card(self):
"""Test Player.deal_card() method"""
<|body_2|>
de... | stack_v2_sparse_classes_36k_train_022783 | 5,537 | no_license | [
{
"docstring": "Test basic Player construction.",
"name": "test_new_Player",
"signature": "def test_new_Player(self)"
},
{
"docstring": "Test Player class",
"name": "test_Player",
"signature": "def test_Player(self)"
},
{
"docstring": "Test Player.deal_card() method",
"name":... | 6 | stack_v2_sparse_classes_30k_train_021600 | Implement the Python class `TestSequenceFunctions` described below.
Class description:
Implement the TestSequenceFunctions class.
Method signatures and docstrings:
- def test_new_Player(self): Test basic Player construction.
- def test_Player(self): Test Player class
- def test_deal_card(self): Test Player.deal_card(... | Implement the Python class `TestSequenceFunctions` described below.
Class description:
Implement the TestSequenceFunctions class.
Method signatures and docstrings:
- def test_new_Player(self): Test basic Player construction.
- def test_Player(self): Test Player class
- def test_deal_card(self): Test Player.deal_card(... | 3176f59c665d87afe5bf4bed68ec8afa44fddf6c | <|skeleton|>
class TestSequenceFunctions:
def test_new_Player(self):
"""Test basic Player construction."""
<|body_0|>
def test_Player(self):
"""Test Player class"""
<|body_1|>
def test_deal_card(self):
"""Test Player.deal_card() method"""
<|body_2|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSequenceFunctions:
def test_new_Player(self):
"""Test basic Player construction."""
jane = Player(name='Jane')
self.assertIsNotNone(jane)
self.assertEqual(str(jane), 'Jane')
phil = Player(name='Phil')
self.assertIsNotNone(phil)
self.assertEqual(str(p... | the_stack_v2_python_sparse | unittests/test-Player.py | von/pyPoker | train | 4 | |
3a051a1c4ce25e982c280ef41be418ccf49fc96c | [
"if '.' not in encoder:\n encoder = '.'.join(__name__.split('.')[:-1]) + '.' + encoder.capitalize() + 'Encoder'\nreturn Resolver()(encoder)",
"if encoder is True:\n return Encoder()\nreturn EncoderFactory.get(encoder)()"
] | <|body_start_0|>
if '.' not in encoder:
encoder = '.'.join(__name__.split('.')[:-1]) + '.' + encoder.capitalize() + 'Encoder'
return Resolver()(encoder)
<|end_body_0|>
<|body_start_1|>
if encoder is True:
return Encoder()
return EncoderFactory.get(encoder)()
<|en... | Encoder factory. Creates new Encoder instances. | EncoderFactory | [
"Apache-2.0",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderFactory:
"""Encoder factory. Creates new Encoder instances."""
def get(encoder):
"""Gets a new instance of encoder class. Args: encoder: Encoder instance class Returns: Encoder class"""
<|body_0|>
def create(encoder):
"""Creates a new Encoder instance. Arg... | stack_v2_sparse_classes_36k_train_022784 | 1,001 | permissive | [
{
"docstring": "Gets a new instance of encoder class. Args: encoder: Encoder instance class Returns: Encoder class",
"name": "get",
"signature": "def get(encoder)"
},
{
"docstring": "Creates a new Encoder instance. Args: encoder: Encoder instance class Returns: Encoder",
"name": "create",
... | 2 | null | Implement the Python class `EncoderFactory` described below.
Class description:
Encoder factory. Creates new Encoder instances.
Method signatures and docstrings:
- def get(encoder): Gets a new instance of encoder class. Args: encoder: Encoder instance class Returns: Encoder class
- def create(encoder): Creates a new ... | Implement the Python class `EncoderFactory` described below.
Class description:
Encoder factory. Creates new Encoder instances.
Method signatures and docstrings:
- def get(encoder): Gets a new instance of encoder class. Args: encoder: Encoder instance class Returns: Encoder class
- def create(encoder): Creates a new ... | 789a4555cb60ee9cdfa69afae5a5236d197e2b07 | <|skeleton|>
class EncoderFactory:
"""Encoder factory. Creates new Encoder instances."""
def get(encoder):
"""Gets a new instance of encoder class. Args: encoder: Encoder instance class Returns: Encoder class"""
<|body_0|>
def create(encoder):
"""Creates a new Encoder instance. Arg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderFactory:
"""Encoder factory. Creates new Encoder instances."""
def get(encoder):
"""Gets a new instance of encoder class. Args: encoder: Encoder instance class Returns: Encoder class"""
if '.' not in encoder:
encoder = '.'.join(__name__.split('.')[:-1]) + '.' + encoder.... | the_stack_v2_python_sparse | src/python/txtai/database/encoder/factory.py | neuml/txtai | train | 4,804 |
bae3ebeb2007b1032f63180a2691e26875352db5 | [
"DataFrame.__init__(self, rows=rows, list_x_min=list_x_min, list_x_max=list_x_max, list_x_delta=list_x_delta)\nself.listXDelta = list_x_delta\nsum_probs = 0\nfor row in rows:\n sum_probs += row[-1]\nif sum_probs < 0.99999 or sum_probs > 1.000001:\n raise ValueError('Sum of probabilities should add to 1.')",
... | <|body_start_0|>
DataFrame.__init__(self, rows=rows, list_x_min=list_x_min, list_x_max=list_x_max, list_x_delta=list_x_delta)
self.listXDelta = list_x_delta
sum_probs = 0
for row in rows:
sum_probs += row[-1]
if sum_probs < 0.99999 or sum_probs > 1.000001:
... | example: age, sex, probability 0, 0, 0.1, 0, 1, 0.2, 5, 0, 0.3, 5, 1, 0.4, | DataFrameWithEmpiricalDist | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataFrameWithEmpiricalDist:
"""example: age, sex, probability 0, 0, 0.1, 0, 1, 0.2, 5, 0, 0.3, 5, 1, 0.4,"""
def __init__(self, rows, list_x_min, list_x_max, list_x_delta):
""":param rows: (list of list) the table above :param list_x_min: list of minimum value of x (in example above:... | stack_v2_sparse_classes_36k_train_022785 | 22,072 | no_license | [
{
"docstring": ":param rows: (list of list) the table above :param list_x_min: list of minimum value of x (in example above: [0, 0]) :param list_x_max: list of maximum value of x (in example above: [10, 1]) :param list_x_delta: list of interval between break points of x if set to 'int', x is treated as categori... | 2 | stack_v2_sparse_classes_30k_train_019893 | Implement the Python class `DataFrameWithEmpiricalDist` described below.
Class description:
example: age, sex, probability 0, 0, 0.1, 0, 1, 0.2, 5, 0, 0.3, 5, 1, 0.4,
Method signatures and docstrings:
- def __init__(self, rows, list_x_min, list_x_max, list_x_delta): :param rows: (list of list) the table above :param ... | Implement the Python class `DataFrameWithEmpiricalDist` described below.
Class description:
example: age, sex, probability 0, 0, 0.1, 0, 1, 0.2, 5, 0, 0.3, 5, 1, 0.4,
Method signatures and docstrings:
- def __init__(self, rows, list_x_min, list_x_max, list_x_delta): :param rows: (list of list) the table above :param ... | 2c456d92741ba751af6bc90c49608b49f524182d | <|skeleton|>
class DataFrameWithEmpiricalDist:
"""example: age, sex, probability 0, 0, 0.1, 0, 1, 0.2, 5, 0, 0.3, 5, 1, 0.4,"""
def __init__(self, rows, list_x_min, list_x_max, list_x_delta):
""":param rows: (list of list) the table above :param list_x_min: list of minimum value of x (in example above:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataFrameWithEmpiricalDist:
"""example: age, sex, probability 0, 0, 0.1, 0, 1, 0.2, 5, 0, 0.3, 5, 1, 0.4,"""
def __init__(self, rows, list_x_min, list_x_max, list_x_delta):
""":param rows: (list of list) the table above :param list_x_min: list of minimum value of x (in example above: [0, 0]) :par... | the_stack_v2_python_sparse | SimPy/DataFrames.py | yaesoubilab/SimPy | train | 6 |
5603fa9f26469a0df0856bed53f1b25e7cd9403e | [
"super(Net, self).__init__()\nself.cfgs = cfgs\nself.embedding = nn.Embedding(num_embeddings=token_size, embedding_dim=cfgs.word_emb_size)\nif cfgs.pretrained_emb['name']:\n self.embedding.weight.data.copy_(torch.from_numpy(pretrained_emb))\nself.encode_lang = nn.GRU(input_size=cfgs.word_emb_size, hidden_size=cf... | <|body_start_0|>
super(Net, self).__init__()
self.cfgs = cfgs
self.embedding = nn.Embedding(num_embeddings=token_size, embedding_dim=cfgs.word_emb_size)
if cfgs.pretrained_emb['name']:
self.embedding.weight.data.copy_(torch.from_numpy(pretrained_emb))
self.encode_lang... | Net | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Net:
def __init__(self, cfgs, pretrained_emb, token_size):
""":param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table."""
<|body_0|>
def forward(self, que_ix, opt_ix, dia, dia_node_ix, ins_dia, cp_ix):
""":param que... | stack_v2_sparse_classes_36k_train_022786 | 3,745 | no_license | [
{
"docstring": ":param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table.",
"name": "__init__",
"signature": "def __init__(self, cfgs, pretrained_emb, token_size)"
},
{
"docstring": ":param que_ix: the index of questions :param opt_ix: the index... | 2 | stack_v2_sparse_classes_30k_train_001685 | Implement the Python class `Net` described below.
Class description:
Implement the Net class.
Method signatures and docstrings:
- def __init__(self, cfgs, pretrained_emb, token_size): :param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table.
- def forward(self, que_i... | Implement the Python class `Net` described below.
Class description:
Implement the Net class.
Method signatures and docstrings:
- def __init__(self, cfgs, pretrained_emb, token_size): :param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table.
- def forward(self, que_i... | fca8f4ef64752f48dd73a98be48e99a21a933049 | <|skeleton|>
class Net:
def __init__(self, cfgs, pretrained_emb, token_size):
""":param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table."""
<|body_0|>
def forward(self, que_ix, opt_ix, dia, dia_node_ix, ins_dia, cp_ix):
""":param que... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Net:
def __init__(self, cfgs, pretrained_emb, token_size):
""":param cfgs: configurations of XTQA. :param pretrained_emb: :param token_size: the size of vocabulary table."""
super(Net, self).__init__()
self.cfgs = cfgs
self.embedding = nn.Embedding(num_embeddings=token_size, em... | the_stack_v2_python_sparse | opentqa/models/dqa/mutan/net.py | TrellixVulnTeam/opentqa_DYRZ | train | 0 | |
97eb4b976a8690d4f30bdd3946dbcf022ccdb28d | [
"global url\nsess = session()\nparams = {'parameter': {'recognize_class': 'update', 'rate_grade': '高', 'update_propertiy': {'cn_id': 'true', 'cn_bank': 'true', 'cn_email': 'true', 'cn_date': 'false', 'cn_telephone': 'true', 'cn_passport': 'false'}}}\ns_get = sess.put(url, json=params)\njson_data = json.loads(s_get.... | <|body_start_0|>
global url
sess = session()
params = {'parameter': {'recognize_class': 'update', 'rate_grade': '高', 'update_propertiy': {'cn_id': 'true', 'cn_bank': 'true', 'cn_email': 'true', 'cn_date': 'false', 'cn_telephone': 'true', 'cn_passport': 'false'}}}
s_get = sess.put(url, js... | TestApiPorpertySensitive | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestApiPorpertySensitive:
def test_update_property(self):
"""参数: 修改类别为update，id和bank为true，其他为false 期望结果： 返回的识别信息列表有两个信息cn_id和cn_bank"""
<|body_0|>
def test_default_property(self):
"""参数: 修改类别为defalut， 期望结果： 返回的识别信息列表有四个信息cn_id、cn_bank、cn_email、cn_telephon"""
... | stack_v2_sparse_classes_36k_train_022787 | 2,846 | no_license | [
{
"docstring": "参数: 修改类别为update，id和bank为true，其他为false 期望结果： 返回的识别信息列表有两个信息cn_id和cn_bank",
"name": "test_update_property",
"signature": "def test_update_property(self)"
},
{
"docstring": "参数: 修改类别为defalut， 期望结果： 返回的识别信息列表有四个信息cn_id、cn_bank、cn_email、cn_telephon",
"name": "test_default_property... | 2 | stack_v2_sparse_classes_30k_train_017293 | Implement the Python class `TestApiPorpertySensitive` described below.
Class description:
Implement the TestApiPorpertySensitive class.
Method signatures and docstrings:
- def test_update_property(self): 参数: 修改类别为update，id和bank为true，其他为false 期望结果： 返回的识别信息列表有两个信息cn_id和cn_bank
- def test_default_property(self): 参数: 修改类... | Implement the Python class `TestApiPorpertySensitive` described below.
Class description:
Implement the TestApiPorpertySensitive class.
Method signatures and docstrings:
- def test_update_property(self): 参数: 修改类别为update，id和bank为true，其他为false 期望结果： 返回的识别信息列表有两个信息cn_id和cn_bank
- def test_default_property(self): 参数: 修改类... | fb268cf7901322bb16b8b295f2c791628665bfb8 | <|skeleton|>
class TestApiPorpertySensitive:
def test_update_property(self):
"""参数: 修改类别为update，id和bank为true，其他为false 期望结果： 返回的识别信息列表有两个信息cn_id和cn_bank"""
<|body_0|>
def test_default_property(self):
"""参数: 修改类别为defalut， 期望结果： 返回的识别信息列表有四个信息cn_id、cn_bank、cn_email、cn_telephon"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestApiPorpertySensitive:
def test_update_property(self):
"""参数: 修改类别为update，id和bank为true，其他为false 期望结果： 返回的识别信息列表有两个信息cn_id和cn_bank"""
global url
sess = session()
params = {'parameter': {'recognize_class': 'update', 'rate_grade': '高', 'update_propertiy': {'cn_id': 'true', 'cn_... | the_stack_v2_python_sparse | aladdin-cas/unit_test/test_api_property_privacy.py | ARES3366/aladdin | train | 0 | |
7716ee073940c81c419afe2f163e081402a256c9 | [
"if dungeon is None or len(dungeon) == 0:\n return 0\nm = len(dungeon)\nn = len(dungeon[0])\nhp = [[0 for j in range(n)] for i in range(m)]\nhp[m - 1][n - 1] = abs(dungeon[m - 1][n - 1]) + 1 if dungeon[m - 1][n - 1] < 0 else 1\nfor j in range(n - 2, -1, -1):\n need = hp[m - 1][j + 1] - dungeon[m - 1][j]\n ... | <|body_start_0|>
if dungeon is None or len(dungeon) == 0:
return 0
m = len(dungeon)
n = len(dungeon[0])
hp = [[0 for j in range(n)] for i in range(m)]
hp[m - 1][n - 1] = abs(dungeon[m - 1][n - 1]) + 1 if dungeon[m - 1][n - 1] < 0 else 1
for j in range(n - 2, -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_0|>
def calculateMinimumHP2(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if dun... | stack_v2_sparse_classes_36k_train_022788 | 2,309 | no_license | [
{
"docstring": ":type dungeon: List[List[int]] :rtype: int",
"name": "calculateMinimumHP",
"signature": "def calculateMinimumHP(self, dungeon)"
},
{
"docstring": ":type dungeon: List[List[int]] :rtype: int",
"name": "calculateMinimumHP2",
"signature": "def calculateMinimumHP2(self, dunge... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calculateMinimumHP(self, dungeon): :type dungeon: List[List[int]] :rtype: int
- def calculateMinimumHP2(self, dungeon): :type dungeon: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calculateMinimumHP(self, dungeon): :type dungeon: List[List[int]] :rtype: int
- def calculateMinimumHP2(self, dungeon): :type dungeon: List[List[int]] :rtype: int
<|skeleton... | 54d3d9530b25272d4a2e5dc33e7035c44f506dc5 | <|skeleton|>
class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_0|>
def calculateMinimumHP2(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
if dungeon is None or len(dungeon) == 0:
return 0
m = len(dungeon)
n = len(dungeon[0])
hp = [[0 for j in range(n)] for i in range(m)]
hp[m - 1][n - 1] =... | the_stack_v2_python_sparse | old/DungeonGame.py | MaxIakovliev/algorithms | train | 0 | |
857000e92d7ad62ebd5760e74541e080c926b205 | [
"weightValue = {}\nfor i in range(len(weight)):\n key = weight[i]\n if key not in weightValue.keys():\n weightValue[key] = value[i]\n elif value[i] > weightValue[key]:\n weightValue[key] = value[i]\n else:\n continue\nprint('物品体积价值对应比：', weightValue, list(weightValue.items()))\nweig... | <|body_start_0|>
weightValue = {}
for i in range(len(weight)):
key = weight[i]
if key not in weightValue.keys():
weightValue[key] = value[i]
elif value[i] > weightValue[key]:
weightValue[key] = value[i]
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getdict(self, weight, value):
"""0-1背包转为完全背包问题：有限变无限"""
<|body_0|>
def BagMaxValue(self, num, WeightLimit, weight, value):
"""完全背包问题"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
weightValue = {}
for i in range(len(weight)):
... | stack_v2_sparse_classes_36k_train_022789 | 3,707 | no_license | [
{
"docstring": "0-1背包转为完全背包问题：有限变无限",
"name": "getdict",
"signature": "def getdict(self, weight, value)"
},
{
"docstring": "完全背包问题",
"name": "BagMaxValue",
"signature": "def BagMaxValue(self, num, WeightLimit, weight, value)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getdict(self, weight, value): 0-1背包转为完全背包问题：有限变无限
- def BagMaxValue(self, num, WeightLimit, weight, value): 完全背包问题 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getdict(self, weight, value): 0-1背包转为完全背包问题：有限变无限
- def BagMaxValue(self, num, WeightLimit, weight, value): 完全背包问题
<|skeleton|>
class Solution:
def getdict(self, weight... | 4e4f739402b95691f6c91411da26d7d3bfe042b6 | <|skeleton|>
class Solution:
def getdict(self, weight, value):
"""0-1背包转为完全背包问题：有限变无限"""
<|body_0|>
def BagMaxValue(self, num, WeightLimit, weight, value):
"""完全背包问题"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def getdict(self, weight, value):
"""0-1背包转为完全背包问题：有限变无限"""
weightValue = {}
for i in range(len(weight)):
key = weight[i]
if key not in weightValue.keys():
weightValue[key] = value[i]
elif value[i] > weightValue[key]:
... | the_stack_v2_python_sparse | other_code_programe/16.完全背包问题.py | hugechuanqi/Algorithms-and-Data-Structures | train | 3 | |
9b1cd2e0ddb85a6749c2e37c5a725f0fc527879d | [
"if n < 3:\n return 0\noutput = [1] * n\noutput[0], output[1] = (0, 0)\nfor i in range(2, int(n ** 0.5) + 1):\n if output[i] == 1:\n print(i ** 2, n, i)\n output[i ** 2:n:i] = [0] * len(output[i ** 2:n:i])\nreturn sum(output)",
"if n <= 2:\n return 0\nprime_list = [2]\nfor i in range(3, n):... | <|body_start_0|>
if n < 3:
return 0
output = [1] * n
output[0], output[1] = (0, 0)
for i in range(2, int(n ** 0.5) + 1):
if output[i] == 1:
print(i ** 2, n, i)
output[i ** 2:n:i] = [0] * len(output[i ** 2:n:i])
return sum(ou... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countPrimes(self, n: int) -> int:
"""这题搜到一个非常牛逼的算法,叫做厄拉多塞筛法. 比如说求20以内质数的个数,首先0,1不是质数.2是第一个质数,然后把20以内所有2的倍数划去. 2后面紧跟的数即为下一个质数3,然后把3所有的倍数划去.3后面紧跟的数即为下一个质数5,再把5所有的倍数划去.以此类推. 在上面遍历索引的时候用到了一个非常好的技巧. 即i是从(2,int(n**0.5)+1)而非(2,n).这个技巧是可以验证的,比如说求9以内的质数个数, 那么只要划掉sqrt(9)以内的质数倍数,剩下的即全... | stack_v2_sparse_classes_36k_train_022790 | 2,396 | no_license | [
{
"docstring": "这题搜到一个非常牛逼的算法,叫做厄拉多塞筛法. 比如说求20以内质数的个数,首先0,1不是质数.2是第一个质数,然后把20以内所有2的倍数划去. 2后面紧跟的数即为下一个质数3,然后把3所有的倍数划去.3后面紧跟的数即为下一个质数5,再把5所有的倍数划去.以此类推. 在上面遍历索引的时候用到了一个非常好的技巧. 即i是从(2,int(n**0.5)+1)而非(2,n).这个技巧是可以验证的,比如说求9以内的质数个数, 那么只要划掉sqrt(9)以内的质数倍数,剩下的即全为质数. 所以在划去倍数的时候也是从i*i开始划掉,而不是i+i. 代码的实现上用了非常好的技巧: :param n:... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n: int) -> int: 这题搜到一个非常牛逼的算法,叫做厄拉多塞筛法. 比如说求20以内质数的个数,首先0,1不是质数.2是第一个质数,然后把20以内所有2的倍数划去. 2后面紧跟的数即为下一个质数3,然后把3所有的倍数划去.3后面紧跟的数即为下一个质数5,再把5所有的倍数划去.以此类推. 在上面遍历索... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n: int) -> int: 这题搜到一个非常牛逼的算法,叫做厄拉多塞筛法. 比如说求20以内质数的个数,首先0,1不是质数.2是第一个质数,然后把20以内所有2的倍数划去. 2后面紧跟的数即为下一个质数3,然后把3所有的倍数划去.3后面紧跟的数即为下一个质数5,再把5所有的倍数划去.以此类推. 在上面遍历索... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def countPrimes(self, n: int) -> int:
"""这题搜到一个非常牛逼的算法,叫做厄拉多塞筛法. 比如说求20以内质数的个数,首先0,1不是质数.2是第一个质数,然后把20以内所有2的倍数划去. 2后面紧跟的数即为下一个质数3,然后把3所有的倍数划去.3后面紧跟的数即为下一个质数5,再把5所有的倍数划去.以此类推. 在上面遍历索引的时候用到了一个非常好的技巧. 即i是从(2,int(n**0.5)+1)而非(2,n).这个技巧是可以验证的,比如说求9以内的质数个数, 那么只要划掉sqrt(9)以内的质数倍数,剩下的即全... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countPrimes(self, n: int) -> int:
"""这题搜到一个非常牛逼的算法,叫做厄拉多塞筛法. 比如说求20以内质数的个数,首先0,1不是质数.2是第一个质数,然后把20以内所有2的倍数划去. 2后面紧跟的数即为下一个质数3,然后把3所有的倍数划去.3后面紧跟的数即为下一个质数5,再把5所有的倍数划去.以此类推. 在上面遍历索引的时候用到了一个非常好的技巧. 即i是从(2,int(n**0.5)+1)而非(2,n).这个技巧是可以验证的,比如说求9以内的质数个数, 那么只要划掉sqrt(9)以内的质数倍数,剩下的即全为质数. 所以在划去倍数的时... | the_stack_v2_python_sparse | 204_计数质数.py | lovehhf/LeetCode | train | 0 | |
48b6bfdf3841c55d1521e60891df82f07dde1335 | [
"n = len(nums)\n\ndef dfs(a, cur):\n nonlocal res\n if a == (1 << n) - 1:\n res.append(cur)\n for i in range(n):\n if a & 1 << i:\n continue\n dfs(a | 1 << i, cur + [nums[i]])\nres = []\ndfs(0, [])\nreturn res",
"n = len(nums)\n\ndef dfs(start):\n nonlocal res\n if s... | <|body_start_0|>
n = len(nums)
def dfs(a, cur):
nonlocal res
if a == (1 << n) - 1:
res.append(cur)
for i in range(n):
if a & 1 << i:
continue
dfs(a | 1 << i, cur + [nums[i]])
res = []
... | [46. 全排列](https://leetcode-cn.com/problems/permutations/) | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""[46. 全排列](https://leetcode-cn.com/problems/permutations/)"""
def permute(self, nums: List[int]) -> List[List[int]]:
"""思路：回溯算法，由于没有重复的数字，每次传一个值，用二进制代表哪个位置被选过"""
<|body_0|>
def permute2(self, nums: List[int]) -> List[List[int]]:
"""思路：回溯算法，大佬的交换法，可以随递... | stack_v2_sparse_classes_36k_train_022791 | 1,469 | no_license | [
{
"docstring": "思路：回溯算法，由于没有重复的数字，每次传一个值，用二进制代表哪个位置被选过",
"name": "permute",
"signature": "def permute(self, nums: List[int]) -> List[List[int]]"
},
{
"docstring": "思路：回溯算法，大佬的交换法，可以随递归深度缩小遍历次数",
"name": "permute2",
"signature": "def permute2(self, nums: List[int]) -> List[List[int]]"
}... | 2 | stack_v2_sparse_classes_30k_train_017964 | Implement the Python class `Solution` described below.
Class description:
[46. 全排列](https://leetcode-cn.com/problems/permutations/)
Method signatures and docstrings:
- def permute(self, nums: List[int]) -> List[List[int]]: 思路：回溯算法，由于没有重复的数字，每次传一个值，用二进制代表哪个位置被选过
- def permute2(self, nums: List[int]) -> List[List[int]]... | Implement the Python class `Solution` described below.
Class description:
[46. 全排列](https://leetcode-cn.com/problems/permutations/)
Method signatures and docstrings:
- def permute(self, nums: List[int]) -> List[List[int]]: 思路：回溯算法，由于没有重复的数字，每次传一个值，用二进制代表哪个位置被选过
- def permute2(self, nums: List[int]) -> List[List[int]]... | dbe8eb449e5b112a71bc1cd4eabfd138304de4a3 | <|skeleton|>
class Solution:
"""[46. 全排列](https://leetcode-cn.com/problems/permutations/)"""
def permute(self, nums: List[int]) -> List[List[int]]:
"""思路：回溯算法，由于没有重复的数字，每次传一个值，用二进制代表哪个位置被选过"""
<|body_0|>
def permute2(self, nums: List[int]) -> List[List[int]]:
"""思路：回溯算法，大佬的交换法，可以随递... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""[46. 全排列](https://leetcode-cn.com/problems/permutations/)"""
def permute(self, nums: List[int]) -> List[List[int]]:
"""思路：回溯算法，由于没有重复的数字，每次传一个值，用二进制代表哪个位置被选过"""
n = len(nums)
def dfs(a, cur):
nonlocal res
if a == (1 << n) - 1:
... | the_stack_v2_python_sparse | leetcode/1-300/46.py | Rivarrl/leetcode_python | train | 3 |
e37c7a2b403a5ea08a4c4dca7671bbb891921288 | [
"super(Encoder, self).__init__()\nself.attention = Attention(hidden_size, num_attention_heads, attention_dropout_ratio, hidden_dropout_ratio)\nself.latent = LatentModule(hidden_size, interm_size)\nself.output = Output(interm_size, hidden_size, hidden_dropout_ratio)",
"attention_temp = self.attention(hidden_states... | <|body_start_0|>
super(Encoder, self).__init__()
self.attention = Attention(hidden_size, num_attention_heads, attention_dropout_ratio, hidden_dropout_ratio)
self.latent = LatentModule(hidden_size, interm_size)
self.output = Output(interm_size, hidden_size, hidden_dropout_ratio)
<|end_bod... | Encoder | Encoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
"""Encoder"""
def __init__(self, hidden_size, interm_size, num_attention_heads, attention_dropout_ratio, hidden_dropout_ratio):
"""Initialization"""
<|body_0|>
def forward(self, hidden_states, attention_mask):
"""Encoder block"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k_train_022792 | 12,741 | permissive | [
{
"docstring": "Initialization",
"name": "__init__",
"signature": "def __init__(self, hidden_size, interm_size, num_attention_heads, attention_dropout_ratio, hidden_dropout_ratio)"
},
{
"docstring": "Encoder block",
"name": "forward",
"signature": "def forward(self, hidden_states, attent... | 2 | null | Implement the Python class `Encoder` described below.
Class description:
Encoder
Method signatures and docstrings:
- def __init__(self, hidden_size, interm_size, num_attention_heads, attention_dropout_ratio, hidden_dropout_ratio): Initialization
- def forward(self, hidden_states, attention_mask): Encoder block | Implement the Python class `Encoder` described below.
Class description:
Encoder
Method signatures and docstrings:
- def __init__(self, hidden_size, interm_size, num_attention_heads, attention_dropout_ratio, hidden_dropout_ratio): Initialization
- def forward(self, hidden_states, attention_mask): Encoder block
<|ske... | e6ab0261eb719c21806bbadfd94001ecfe27de45 | <|skeleton|>
class Encoder:
"""Encoder"""
def __init__(self, hidden_size, interm_size, num_attention_heads, attention_dropout_ratio, hidden_dropout_ratio):
"""Initialization"""
<|body_0|>
def forward(self, hidden_states, attention_mask):
"""Encoder block"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder:
"""Encoder"""
def __init__(self, hidden_size, interm_size, num_attention_heads, attention_dropout_ratio, hidden_dropout_ratio):
"""Initialization"""
super(Encoder, self).__init__()
self.attention = Attention(hidden_size, num_attention_heads, attention_dropout_ratio, hidde... | the_stack_v2_python_sparse | apps/drug_target_interaction/moltrans_dti/double_towers.py | PaddlePaddle/PaddleHelix | train | 771 |
a976c960d4ceeda54ce5e50459a71e4ede2e46b6 | [
"if 'formatter' not in overrides:\n overrides['formatter'] = ScalarFormatter()\nsuper().__init__(**overrides)",
"start, end = (self.start, self.end)\ndomain = abs(end - start)\nmajor_step = self.major_step\nif major_step is UNDEF:\n major_step = step_size(domain, self.major_count, self.major_splits)\nminor_... | <|body_start_0|>
if 'formatter' not in overrides:
overrides['formatter'] = ScalarFormatter()
super().__init__(**overrides)
<|end_body_0|>
<|body_start_1|>
start, end = (self.start, self.end)
domain = abs(end - start)
major_step = self.major_step
if major_step... | This type of ticker generates nice looking ticks and labels according to linear scale. The major and the minor steps are calculated automatically according to current range, however, both can be specified if needed. The label 'formatter' is by default set to pero.ScalarFormatter, but can be changed if needed. Propertie... | LinTicker | [
"LicenseRef-scancode-philippe-de-muyter",
"LicenseRef-scancode-commercial-license",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinTicker:
"""This type of ticker generates nice looking ticks and labels according to linear scale. The major and the minor steps are calculated automatically according to current range, however, both can be specified if needed. The label 'formatter' is by default set to pero.ScalarFormatter, bu... | stack_v2_sparse_classes_36k_train_022793 | 4,293 | permissive | [
{
"docstring": "Initializes a new instance of LinTicker.",
"name": "__init__",
"signature": "def __init__(self, **overrides)"
},
{
"docstring": "Generates ticks according to current settings. Returns: (float,), (float,) Generated major and minor ticks.",
"name": "make_ticks",
"signature"... | 3 | stack_v2_sparse_classes_30k_train_018823 | Implement the Python class `LinTicker` described below.
Class description:
This type of ticker generates nice looking ticks and labels according to linear scale. The major and the minor steps are calculated automatically according to current range, however, both can be specified if needed. The label 'formatter' is by ... | Implement the Python class `LinTicker` described below.
Class description:
This type of ticker generates nice looking ticks and labels according to linear scale. The major and the minor steps are calculated automatically according to current range, however, both can be specified if needed. The label 'formatter' is by ... | d59b1bc056f3037b7b7ab635b6deb41120612965 | <|skeleton|>
class LinTicker:
"""This type of ticker generates nice looking ticks and labels according to linear scale. The major and the minor steps are calculated automatically according to current range, however, both can be specified if needed. The label 'formatter' is by default set to pero.ScalarFormatter, bu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinTicker:
"""This type of ticker generates nice looking ticks and labels according to linear scale. The major and the minor steps are calculated automatically according to current range, however, both can be specified if needed. The label 'formatter' is by default set to pero.ScalarFormatter, but can be chan... | the_stack_v2_python_sparse | pero/tickers/linear.py | xxao/pero | train | 31 |
a1a9ba52b07d22412429f349408fae2f564274e2 | [
"if not filename:\n raise ValueError(f'{filename} is not a valid file')\nwith open(filename, encoding='utf8') as fname:\n try:\n self.profile = yaml.safe_load(fname)\n except yaml.YAMLError as ex:\n raise ValueError('f{filename} is not a valid YAML file: {ex}') from ex\n if self.profile is... | <|body_start_0|>
if not filename:
raise ValueError(f'{filename} is not a valid file')
with open(filename, encoding='utf8') as fname:
try:
self.profile = yaml.safe_load(fname)
except yaml.YAMLError as ex:
raise ValueError('f{filename} is... | Manages which scan levels are run for packages. | Profile | [
"CC0-1.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Profile:
"""Manages which scan levels are run for packages."""
def __init__(self, filename: str) -> None:
"""Initialize profile."""
<|body_0|>
def get_package_level(self, package: Package) -> Union[str, Any]:
"""Get which scan level to use for a given package."""... | stack_v2_sparse_classes_36k_train_022794 | 1,305 | permissive | [
{
"docstring": "Initialize profile.",
"name": "__init__",
"signature": "def __init__(self, filename: str) -> None"
},
{
"docstring": "Get which scan level to use for a given package.",
"name": "get_package_level",
"signature": "def get_package_level(self, package: Package) -> Union[str, ... | 2 | stack_v2_sparse_classes_30k_train_016498 | Implement the Python class `Profile` described below.
Class description:
Manages which scan levels are run for packages.
Method signatures and docstrings:
- def __init__(self, filename: str) -> None: Initialize profile.
- def get_package_level(self, package: Package) -> Union[str, Any]: Get which scan level to use fo... | Implement the Python class `Profile` described below.
Class description:
Manages which scan levels are run for packages.
Method signatures and docstrings:
- def __init__(self, filename: str) -> None: Initialize profile.
- def get_package_level(self, package: Package) -> Union[str, Any]: Get which scan level to use fo... | 25225188b04dbdebb04674d0b3c8af886ccf87c3 | <|skeleton|>
class Profile:
"""Manages which scan levels are run for packages."""
def __init__(self, filename: str) -> None:
"""Initialize profile."""
<|body_0|>
def get_package_level(self, package: Package) -> Union[str, Any]:
"""Get which scan level to use for a given package."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Profile:
"""Manages which scan levels are run for packages."""
def __init__(self, filename: str) -> None:
"""Initialize profile."""
if not filename:
raise ValueError(f'{filename} is not a valid file')
with open(filename, encoding='utf8') as fname:
try:
... | the_stack_v2_python_sparse | statick_tool/profile.py | sscpac/statick | train | 73 |
f875997e46b97d8657a0dc76d3f9cfda6612767a | [
"if None is gpb_msg_class:\n raise AttributeError('No GPB message class specified')\nif gpb_msg_class not in [t_ItApiRpdMessage, t_ItApiServiceSuiteMessage]:\n raise AttributeError('Unknown GPB message class passed')\nif None is rx_cb:\n raise AttributeError('No rx_cb specified')\nif None is disp:\n sel... | <|body_start_0|>
if None is gpb_msg_class:
raise AttributeError('No GPB message class specified')
if gpb_msg_class not in [t_ItApiRpdMessage, t_ItApiServiceSuiteMessage]:
raise AttributeError('Unknown GPB message class passed')
if None is rx_cb:
raise Attribut... | Implements server side of the IT (Integration Testing) API. | ItApiServer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItApiServer:
"""Implements server side of the IT (Integration Testing) API."""
def __init__(self, gpb_msg_class, rx_cb, disp=None):
"""Opens socket on the IT API port and listen for GPB messages. :param gpb_msg_class: A class of GPB messages which will be exchanged. :param rx_cb: Use... | stack_v2_sparse_classes_36k_train_022795 | 10,996 | permissive | [
{
"docstring": "Opens socket on the IT API port and listen for GPB messages. :param gpb_msg_class: A class of GPB messages which will be exchanged. :param rx_cb: User's RX callback which is called when some GPB message was received. The callback expects the GPB message as argument. :param disp: Dispatcher. New ... | 5 | null | Implement the Python class `ItApiServer` described below.
Class description:
Implements server side of the IT (Integration Testing) API.
Method signatures and docstrings:
- def __init__(self, gpb_msg_class, rx_cb, disp=None): Opens socket on the IT API port and listen for GPB messages. :param gpb_msg_class: A class o... | Implement the Python class `ItApiServer` described below.
Class description:
Implements server side of the IT (Integration Testing) API.
Method signatures and docstrings:
- def __init__(self, gpb_msg_class, rx_cb, disp=None): Opens socket on the IT API port and listen for GPB messages. :param gpb_msg_class: A class o... | 70cf84df92347aba0493f506c0d059c0c041cba8 | <|skeleton|>
class ItApiServer:
"""Implements server side of the IT (Integration Testing) API."""
def __init__(self, gpb_msg_class, rx_cb, disp=None):
"""Opens socket on the IT API port and listen for GPB messages. :param gpb_msg_class: A class of GPB messages which will be exchanged. :param rx_cb: Use... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ItApiServer:
"""Implements server side of the IT (Integration Testing) API."""
def __init__(self, gpb_msg_class, rx_cb, disp=None):
"""Opens socket on the IT API port and listen for GPB messages. :param gpb_msg_class: A class of GPB messages which will be exchanged. :param rx_cb: User's RX callba... | the_stack_v2_python_sparse | openrpd/rpd/it_api/it_api.py | hujiangyi/or | train | 0 |
d3632ebd40241fda99094287aabf6db9336f438c | [
"super(LeNet1, self).__init__()\nself.conv1 = paddle.nn.Conv2D(in_channels=1, out_channels=16, kernel_size=3, stride=1, padding=1)\nself.max_pool1 = paddle.nn.MaxPool2D(kernel_size=2, stride=2)\nself.conv2 = paddle.nn.Conv2D(in_channels=16, out_channels=16, kernel_size=3, stride=1, padding=1)\nself.max_pool2 = padd... | <|body_start_0|>
super(LeNet1, self).__init__()
self.conv1 = paddle.nn.Conv2D(in_channels=1, out_channels=16, kernel_size=3, stride=1, padding=1)
self.max_pool1 = paddle.nn.MaxPool2D(kernel_size=2, stride=2)
self.conv2 = paddle.nn.Conv2D(in_channels=16, out_channels=16, kernel_size=3, st... | simple nn layers | LeNet1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LeNet1:
"""simple nn layers"""
def __init__(self):
"""init"""
<|body_0|>
def forward(self, x):
"""forward"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(LeNet1, self).__init__()
self.conv1 = paddle.nn.Conv2D(in_channels=1, out_cha... | stack_v2_sparse_classes_36k_train_022796 | 1,728 | no_license | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "forward",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | null | Implement the Python class `LeNet1` described below.
Class description:
simple nn layers
Method signatures and docstrings:
- def __init__(self): init
- def forward(self, x): forward | Implement the Python class `LeNet1` described below.
Class description:
simple nn layers
Method signatures and docstrings:
- def __init__(self): init
- def forward(self, x): forward
<|skeleton|>
class LeNet1:
"""simple nn layers"""
def __init__(self):
"""init"""
<|body_0|>
def forward(s... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class LeNet1:
"""simple nn layers"""
def __init__(self):
"""init"""
<|body_0|>
def forward(self, x):
"""forward"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LeNet1:
"""simple nn layers"""
def __init__(self):
"""init"""
super(LeNet1, self).__init__()
self.conv1 = paddle.nn.Conv2D(in_channels=1, out_channels=16, kernel_size=3, stride=1, padding=1)
self.max_pool1 = paddle.nn.MaxPool2D(kernel_size=2, stride=2)
self.conv2 =... | the_stack_v2_python_sparse | framework/e2e/jit_legacy/scene/test_jit_script_in_forward.py | PaddlePaddle/PaddleTest | train | 42 |
19a3fb49a3261e81ee80235a04f0ffb8c5232c29 | [
"if all((e in elements_tl for e in comp)):\n return np.array([comp[e] if e in comp else 0 for e in elements_tl], np.float32)\nelse:\n return None",
"if 'composition' in kwargs and datapoint is None:\n datapoint = kwargs.get('composition')\n raise DeprecationWarning('Composition is being phased out as ... | <|body_start_0|>
if all((e in elements_tl for e in comp)):
return np.array([comp[e] if e in comp else 0 for e in elements_tl], np.float32)
else:
return None
<|end_body_0|>
<|body_start_1|>
if 'composition' in kwargs and datapoint is None:
datapoint = kwargs.g... | Fixed size vector of length 86 containing raw fractional elemental compositions in the compound. The 86 chosen elements are based on the original implementation at https://github.com/NU-CUCIS/ElemNet. Returns a vector containing fractional compositions of each element in the compound. References ---------- .. [1] Jha, ... | ElemNetFeaturizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElemNetFeaturizer:
"""Fixed size vector of length 86 containing raw fractional elemental compositions in the compound. The 86 chosen elements are based on the original implementation at https://github.com/NU-CUCIS/ElemNet. Returns a vector containing fractional compositions of each element in the... | stack_v2_sparse_classes_36k_train_022797 | 3,232 | permissive | [
{
"docstring": "Converts a dictionary containing element names and corresponding compositional fractions into a vector of fractions. Parameters ---------- comp: collections.defaultdict object Dictionary mapping element names to fractional compositions. Returns ------- fractions: np.ndarray Vector of fractional ... | 2 | stack_v2_sparse_classes_30k_train_002533 | Implement the Python class `ElemNetFeaturizer` described below.
Class description:
Fixed size vector of length 86 containing raw fractional elemental compositions in the compound. The 86 chosen elements are based on the original implementation at https://github.com/NU-CUCIS/ElemNet. Returns a vector containing fractio... | Implement the Python class `ElemNetFeaturizer` described below.
Class description:
Fixed size vector of length 86 containing raw fractional elemental compositions in the compound. The 86 chosen elements are based on the original implementation at https://github.com/NU-CUCIS/ElemNet. Returns a vector containing fractio... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class ElemNetFeaturizer:
"""Fixed size vector of length 86 containing raw fractional elemental compositions in the compound. The 86 chosen elements are based on the original implementation at https://github.com/NU-CUCIS/ElemNet. Returns a vector containing fractional compositions of each element in the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElemNetFeaturizer:
"""Fixed size vector of length 86 containing raw fractional elemental compositions in the compound. The 86 chosen elements are based on the original implementation at https://github.com/NU-CUCIS/ElemNet. Returns a vector containing fractional compositions of each element in the compound. Re... | the_stack_v2_python_sparse | deepchem/feat/material_featurizers/elemnet_featurizer.py | deepchem/deepchem | train | 4,876 |
79c893f627e0d13b1f25f704bfb18d46ec378a3c | [
"super(ArcBiaffine, self).__init__()\nself.U = nn.Parameter(torch.Tensor(hidden_size, hidden_size), requires_grad=True)\nself.has_bias = bias\nif self.has_bias:\n self.bias = nn.Parameter(torch.Tensor(hidden_size), requires_grad=True)\nelse:\n self.register_parameter('bias', None)\ninitial_parameter(self)",
... | <|body_start_0|>
super(ArcBiaffine, self).__init__()
self.U = nn.Parameter(torch.Tensor(hidden_size, hidden_size), requires_grad=True)
self.has_bias = bias
if self.has_bias:
self.bias = nn.Parameter(torch.Tensor(hidden_size), requires_grad=True)
else:
self... | Biaffine Dependency Parser 的子模块, 用于构建预测边的图 | ArcBiaffine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArcBiaffine:
"""Biaffine Dependency Parser 的子模块, 用于构建预测边的图"""
def __init__(self, hidden_size, bias=True):
""":param hidden_size: 输入的特征维度 :param bias: 是否使用bias. Default: ``True``"""
<|body_0|>
def forward(self, head, dep):
""":param head: arc-head tensor [batch, l... | stack_v2_sparse_classes_36k_train_022798 | 22,013 | permissive | [
{
"docstring": ":param hidden_size: 输入的特征维度 :param bias: 是否使用bias. Default: ``True``",
"name": "__init__",
"signature": "def __init__(self, hidden_size, bias=True)"
},
{
"docstring": ":param head: arc-head tensor [batch, length, hidden] :param dep: arc-dependent tensor [batch, length, hidden] :r... | 2 | null | Implement the Python class `ArcBiaffine` described below.
Class description:
Biaffine Dependency Parser 的子模块, 用于构建预测边的图
Method signatures and docstrings:
- def __init__(self, hidden_size, bias=True): :param hidden_size: 输入的特征维度 :param bias: 是否使用bias. Default: ``True``
- def forward(self, head, dep): :param head: arc-... | Implement the Python class `ArcBiaffine` described below.
Class description:
Biaffine Dependency Parser 的子模块, 用于构建预测边的图
Method signatures and docstrings:
- def __init__(self, hidden_size, bias=True): :param hidden_size: 输入的特征维度 :param bias: 是否使用bias. Default: ``True``
- def forward(self, head, dep): :param head: arc-... | dffc7a06cdbff2671a3ca73d2398159d91a4a7db | <|skeleton|>
class ArcBiaffine:
"""Biaffine Dependency Parser 的子模块, 用于构建预测边的图"""
def __init__(self, hidden_size, bias=True):
""":param hidden_size: 输入的特征维度 :param bias: 是否使用bias. Default: ``True``"""
<|body_0|>
def forward(self, head, dep):
""":param head: arc-head tensor [batch, l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArcBiaffine:
"""Biaffine Dependency Parser 的子模块, 用于构建预测边的图"""
def __init__(self, hidden_size, bias=True):
""":param hidden_size: 输入的特征维度 :param bias: 是否使用bias. Default: ``True``"""
super(ArcBiaffine, self).__init__()
self.U = nn.Parameter(torch.Tensor(hidden_size, hidden_size), re... | the_stack_v2_python_sparse | phenobert/utils/fastNLP/models/biaffine_parser.py | TianlabTech/PhenoBERT | train | 2 |
1a1285cdf97102f4eb1974aa61e0ee258ecd3193 | [
"super(Transformer, self).__init__()\nself.encoder = Encoder(N, dm, h, hidden, input_vocab, max_seq_input, drop_rate)\nself.decoder = Decoder(N, dm, h, hidden, target_vocab, max_seq_target, drop_rate)\nself.linear = tf.keras.layers.Dense(target_vocab)",
"enc_output = self.encoder(inputs, training, encoder_mask)\n... | <|body_start_0|>
super(Transformer, self).__init__()
self.encoder = Encoder(N, dm, h, hidden, input_vocab, max_seq_input, drop_rate)
self.decoder = Decoder(N, dm, h, hidden, target_vocab, max_seq_target, drop_rate)
self.linear = tf.keras.layers.Dense(target_vocab)
<|end_body_0|>
<|body_... | Transformer class | Transformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transformer:
"""Transformer class"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the model :param h: number of heads :param h... | stack_v2_sparse_classes_36k_train_022799 | 2,460 | no_license | [
{
"docstring": "Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the model :param h: number of heads :param hidden: number of hidden units in the fully connected layers :param input_vocab: size of the input vocabulary :param target_vocab: size of the target vocabulary :pa... | 2 | stack_v2_sparse_classes_30k_train_021273 | Implement the Python class `Transformer` described below.
Class description:
Transformer class
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1): Class constructor :param N: number of blocks in the encoder :param dm: dimen... | Implement the Python class `Transformer` described below.
Class description:
Transformer class
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1): Class constructor :param N: number of blocks in the encoder :param dm: dimen... | f83a60babb1d2a510a4a0e0f58aa3880fd9f93a7 | <|skeleton|>
class Transformer:
"""Transformer class"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the model :param h: number of heads :param h... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Transformer:
"""Transformer class"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""Class constructor :param N: number of blocks in the encoder :param dm: dimensionality of the model :param h: number of heads :param hidden: number... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/11-transformer.py | jalondono/holbertonschool-machine_learning | train | 2 |
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