hybrid-diff-ar/stack-v2-sparse-classes-10k

36bea736905f0277ad12805247592c226c75f683

[ "if not root:\n return ''\ncur_list = [root]\nval_list = [str(root.val)]\nwhile len(cur_list):\n pointer = cur_list.pop(0)\n if pointer.left:\n cur_list.append(pointer.left)\n val_list.append(str(pointer.left.val))\n else:\n val_list.append('NA')\n if pointer.right:\n cur_...

<|body_start_0|> if not root: return '' cur_list = [root] val_list = [str(root.val)] while len(cur_list): pointer = cur_list.pop(0) if pointer.left: cur_list.append(pointer.left) val_list.append(str(pointer.left.val)) ...

Codec

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002300

3,830

no_license

[ { "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_004143

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:...

9387c1cbf1cac2db1aebf5ad196230705ab0fcc7

stack_v2_sparse_classes_10k

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 '' cur_list = [root] val_list = [str(root.val)] while len(cur_list): pointer = cur_list.pop(0) if pointer....

the_stack_v2_python_sparse

serialize_and_deserialize_binary_tree.py

lightening0907/algorithm

train

0

28ba5d0174603e0b7b01a65286129057f3deb4c8

[ "try:\n parsed_url = urlparse(url)\nexcept Exception as e:\n logging.error('Failed to parse url: ' + str(e))\n raise FailedDownloadingFileException('The provided url is not in a recognized format.')\nif not parsed_url.path.lower().split('?')[0].endswith(schema_generator.SchemaGenerator.valid_extensions):\n...

<|body_start_0|> try: parsed_url = urlparse(url) except Exception as e: logging.error('Failed to parse url: ' + str(e)) raise FailedDownloadingFileException('The provided url is not in a recognized format.') if not parsed_url.path.lower().split('?')[0].endswit...

This class functionality is to read supported file types into temporary files.

FileDownloader

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class FileDownloader: """This class functionality is to read supported file types into temporary files.""" def download_temp(url, sftp_username=None, sftp_password=None): """Parses the url and downloads the file into a temporary file.""" <|body_0|> def __https_file_downloader(...

stack_v2_sparse_classes_10k_train_002301

4,953

no_license

[ { "docstring": "Parses the url and downloads the file into a temporary file.", "name": "download_temp", "signature": "def download_temp(url, sftp_username=None, sftp_password=None)" }, { "docstring": "Takes in a given https url and downloads the file into a temporary file.", "name": "__https...

3

stack_v2_sparse_classes_30k_train_006497

Implement the Python class `FileDownloader` described below. Class description: This class functionality is to read supported file types into temporary files. Method signatures and docstrings: - def download_temp(url, sftp_username=None, sftp_password=None): Parses the url and downloads the file into a temporary file...

873c96bdf5fd07ddc986d3944a90c5bcfa898b2d

<|skeleton|> class FileDownloader: """This class functionality is to read supported file types into temporary files.""" def download_temp(url, sftp_username=None, sftp_password=None): """Parses the url and downloads the file into a temporary file.""" <|body_0|> def __https_file_downloader(...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class FileDownloader: """This class functionality is to read supported file types into temporary files.""" def download_temp(url, sftp_username=None, sftp_password=None): """Parses the url and downloads the file into a temporary file.""" try: parsed_url = urlparse(url) excep...

the_stack_v2_python_sparse

cataloger/utilities/file_downloader.py

timeonator/opendatapdx

train

1

c296f2751865c7f5f948a68ae90e26f5e00985b4

[ "self.max_read_iops = max_read_iops\nself.max_write_iops = max_write_iops\nself.read_iops_samples = read_iops_samples\nself.write_iops_samples = write_iops_samples", "if dictionary is None:\n return None\nmax_read_iops = dictionary.get('maxReadIops')\nmax_write_iops = dictionary.get('maxWriteIops')\nread_iops_...

Implementation of the 'IopsTile' model. IOPs information for dashboard. Attributes: max_read_iops (long|int): Maximum Read IOs per second in last 24 hours. max_write_iops (long|int): Maximum number of Write IOs per second in last 24 hours. read_iops_samples (list of Sample): Read IOs per second samples taken for the pa...

IopsTile

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class IopsTile: """Implementation of the 'IopsTile' model. IOPs information for dashboard. Attributes: max_read_iops (long|int): Maximum Read IOs per second in last 24 hours. max_write_iops (long|int): Maximum number of Write IOs per second in last 24 hours. read_iops_samples (list of Sample): Read IOs...

stack_v2_sparse_classes_10k_train_002302

3,022

permissive

[ { "docstring": "Constructor for the IopsTile class", "name": "__init__", "signature": "def __init__(self, max_read_iops=None, max_write_iops=None, read_iops_samples=None, write_iops_samples=None)" }, { "docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary...

2

stack_v2_sparse_classes_30k_train_000192

Implement the Python class `IopsTile` described below. Class description: Implementation of the 'IopsTile' model. IOPs information for dashboard. Attributes: max_read_iops (long|int): Maximum Read IOs per second in last 24 hours. max_write_iops (long|int): Maximum number of Write IOs per second in last 24 hours. read_...

e4973dfeb836266904d0369ea845513c7acf261e

<|skeleton|> class IopsTile: """Implementation of the 'IopsTile' model. IOPs information for dashboard. Attributes: max_read_iops (long|int): Maximum Read IOs per second in last 24 hours. max_write_iops (long|int): Maximum number of Write IOs per second in last 24 hours. read_iops_samples (list of Sample): Read IOs...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class IopsTile: """Implementation of the 'IopsTile' model. IOPs information for dashboard. Attributes: max_read_iops (long|int): Maximum Read IOs per second in last 24 hours. max_write_iops (long|int): Maximum number of Write IOs per second in last 24 hours. read_iops_samples (list of Sample): Read IOs per second s...

the_stack_v2_python_sparse

cohesity_management_sdk/models/iops_tile.py

cohesity/management-sdk-python

train

24

364a476317899eda3709d936233f29175071eaaa

[ "if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn BrowserSharedCookieHistory()", "from .browser_shared_cookie_source_environment import BrowserSharedCookieSourceEnvironment\nfrom .identity_set import IdentitySet\nfrom .browser_shared_cookie_source_environment import BrowserSharedCooki...

BrowserSharedCookieHistory

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class BrowserSharedCookieHistory: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSharedCookieHistory: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and...

stack_v2_sparse_classes_10k_train_002303

4,881

permissive

[ { "docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: BrowserSharedCookieHistory", "name": "create_from_discriminator_value", "signature": "def create_from_discri...

3

stack_v2_sparse_classes_30k_train_003835

Implement the Python class `BrowserSharedCookieHistory` described below. Class description: Implement the BrowserSharedCookieHistory class. Method signatures and docstrings: - def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSharedCookieHistory: Creates a new instance of the appropr...

27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949

<|skeleton|> class BrowserSharedCookieHistory: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSharedCookieHistory: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class BrowserSharedCookieHistory: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> BrowserSharedCookieHistory: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ob...

the_stack_v2_python_sparse

msgraph/generated/models/browser_shared_cookie_history.py

microsoftgraph/msgraph-sdk-python

train

135

d8edef84a12d610f1752cfb28d7e7095e32b6a8f

[ "self.ar_coeffs = ar_coeffs\nself.ma_coeffs = ma_coeffs\nself.arma_process = sm.tsa.ArmaProcess.from_coeffs(self.ar_coeffs, self.ma_coeffs)", "if seed is None:\n seed = 0\nnp.random.seed(seed)\nindex = pd.date_range(**date_range_kwargs)\nnsample = index.size\ndata = self.arma_process.generate_sample(nsample=ns...

A thin wrapper around statsmodels `ArmaProcess`, with Pandas support.

ArmaProcess

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ArmaProcess: """A thin wrapper around statsmodels `ArmaProcess`, with Pandas support.""" def __init__(self, ar_coeffs: List[float], ma_coeffs: List[float]) -> None: """Initialize `arma_process` using given coefficients. Useful properties include - arroots - isinvertible - isstationar...

stack_v2_sparse_classes_10k_train_002304

14,310

permissive

[ { "docstring": "Initialize `arma_process` using given coefficients. Useful properties include - arroots - isinvertible - isstationary - maroots Further details are available at - https://www.statsmodels.org/stable/generated/statsmodels.tsa.arima_process.ArmaProcess.html # pylint: disable=line-too-long", "na...

2

stack_v2_sparse_classes_30k_train_002395

Implement the Python class `ArmaProcess` described below. Class description: A thin wrapper around statsmodels `ArmaProcess`, with Pandas support. Method signatures and docstrings: - def __init__(self, ar_coeffs: List[float], ma_coeffs: List[float]) -> None: Initialize `arma_process` using given coefficients. Useful ...

363c59fa29df2ba2719cbad2f8a19ae12cc54a92

<|skeleton|> class ArmaProcess: """A thin wrapper around statsmodels `ArmaProcess`, with Pandas support.""" def __init__(self, ar_coeffs: List[float], ma_coeffs: List[float]) -> None: """Initialize `arma_process` using given coefficients. Useful properties include - arroots - isinvertible - isstationar...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ArmaProcess: """A thin wrapper around statsmodels `ArmaProcess`, with Pandas support.""" def __init__(self, ar_coeffs: List[float], ma_coeffs: List[float]) -> None: """Initialize `arma_process` using given coefficients. Useful properties include - arroots - isinvertible - isstationary - maroots F...

the_stack_v2_python_sparse

core/artificial_signal_generators.py

srlindemann/amp

train

0

a388a3252656e046f945c827b53f38990382404e

[ "def encode_extra_types(obj):\n \"\"\"MessagePack hook to serialize extra types.\n\n The recipe took from the MessagePack for Python docs:\n https://github.com/msgpack/msgpack-python#packingunpacking-of-custom-data-type\n\n Supported types:\n - Django models (through `...

<|body_start_0|> def encode_extra_types(obj): """MessagePack hook to serialize extra types. The recipe took from the MessagePack for Python docs: https://github.com/msgpack/msgpack-python#packingunpacking-of-custom-data-type Supported typ...

Serialize/deserialize Python collection with Django models. Serialize/deserialize the data with the MessagePack like Redis Channels layer backend does. If `data` contains Django models, then it is serialized by the Django serialization utilities. For details see: Django serialization: https://docs.djangoproject.com/en/...

Serializer

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Serializer: """Serialize/deserialize Python collection with Django models. Serialize/deserialize the data with the MessagePack like Redis Channels layer backend does. If `data` contains Django models, then it is serialized by the Django serialization utilities. For details see: Django serializati...

stack_v2_sparse_classes_10k_train_002305

3,850

permissive

[ { "docstring": "Serialize the `data`.", "name": "serialize", "signature": "def serialize(data)" }, { "docstring": "Deserialize the `data`.", "name": "deserialize", "signature": "def deserialize(data)" } ]

2

stack_v2_sparse_classes_30k_train_004171

Implement the Python class `Serializer` described below. Class description: Serialize/deserialize Python collection with Django models. Serialize/deserialize the data with the MessagePack like Redis Channels layer backend does. If `data` contains Django models, then it is serialized by the Django serialization utiliti...

09a2ffdde45a1553abd09b5b3e595402b6e6c9b1

<|skeleton|> class Serializer: """Serialize/deserialize Python collection with Django models. Serialize/deserialize the data with the MessagePack like Redis Channels layer backend does. If `data` contains Django models, then it is serialized by the Django serialization utilities. For details see: Django serializati...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Serializer: """Serialize/deserialize Python collection with Django models. Serialize/deserialize the data with the MessagePack like Redis Channels layer backend does. If `data` contains Django models, then it is serialized by the Django serialization utilities. For details see: Django serialization: https://d...

the_stack_v2_python_sparse

channels_graphql_ws/serializer.py

datadvance/DjangoChannelsGraphqlWs

train

295

9ea014162748b92664743cf57ecc1f484e34447a

[ "self.Wh = np.random.normal(size=(h + i, h))\nself.Wy = np.random.normal(size=(h, o))\nself.bh = np.zeros((1, h))\nself.by = np.zeros((1, o))", "xMax = np.max(x, axis=-1, keepdims=True)\ne_x = np.exp(x - xMax)\nreturn e_x / e_x.sum(axis=-1, keepdims=True)", "hidden_con = np.concatenate((h_prev.T, x_t.T), axis=0...

RNNCell

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class RNNCell: def __init__(self, i, h, o): """class condtructor :param i: dim of the data :param h: dim of hidden state :param o: dim of outputs Note: create public attributes Wh, Wy, bh, by Note: Wh and bh: for the concatenated Hidden state and input Wy and by: for the output Note: Weights: ...

stack_v2_sparse_classes_10k_train_002306

1,817

no_license

[ { "docstring": "class condtructor :param i: dim of the data :param h: dim of hidden state :param o: dim of outputs Note: create public attributes Wh, Wy, bh, by Note: Wh and bh: for the concatenated Hidden state and input Wy and by: for the output Note: Weights: initialized using fandom normal distribution in l...

3

stack_v2_sparse_classes_30k_train_001243

Implement the Python class `RNNCell` described below. Class description: Implement the RNNCell class. Method signatures and docstrings: - def __init__(self, i, h, o): class condtructor :param i: dim of the data :param h: dim of hidden state :param o: dim of outputs Note: create public attributes Wh, Wy, bh, by Note: ...

4ac942126918c7acaa9ef88d18efe299b2f726fe

<|skeleton|> class RNNCell: def __init__(self, i, h, o): """class condtructor :param i: dim of the data :param h: dim of hidden state :param o: dim of outputs Note: create public attributes Wh, Wy, bh, by Note: Wh and bh: for the concatenated Hidden state and input Wy and by: for the output Note: Weights: ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class RNNCell: def __init__(self, i, h, o): """class condtructor :param i: dim of the data :param h: dim of hidden state :param o: dim of outputs Note: create public attributes Wh, Wy, bh, by Note: Wh and bh: for the concatenated Hidden state and input Wy and by: for the output Note: Weights: initialized us...

the_stack_v2_python_sparse

supervised_learning/0x0D-RNNs/0-rnn_cell.py

DracoMindz/holbertonschool-machine_learning

train

2

ece1d797a3b98dc341b9b1e116a2373ea328ba2d

[ "number_frequency_map = {}\nfor num in arr:\n number_frequency_map[num] = number_frequency_map.get(num, 0) + 1\nlucky_number = -1\nfor key, value in number_frequency_map.items():\n if key == value:\n lucky_number = max(value, lucky_number)\nreturn lucky_number", "lucky_list = []\nfor i in arr:\n i...

<|body_start_0|> number_frequency_map = {} for num in arr: number_frequency_map[num] = number_frequency_map.get(num, 0) + 1 lucky_number = -1 for key, value in number_frequency_map.items(): if key == value: lucky_number = max(value, lucky_number) ...

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def findLucky(self, arr: List[int]) -> int: """Time: O(N) Space: O(N)""" <|body_0|> def findLucky_2(self, arr: List[int]) -> int: """Time: O(N^2) Space: O(N)""" <|body_1|> <|end_skeleton|> <|body_start_0|> number_frequency_map = {} ...

stack_v2_sparse_classes_10k_train_002307

2,039

no_license

[ { "docstring": "Time: O(N) Space: O(N)", "name": "findLucky", "signature": "def findLucky(self, arr: List[int]) -> int" }, { "docstring": "Time: O(N^2) Space: O(N)", "name": "findLucky_2", "signature": "def findLucky_2(self, arr: List[int]) -> int" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def findLucky(self, arr: List[int]) -> int: Time: O(N) Space: O(N) - def findLucky_2(self, arr: List[int]) -> int: Time: O(N^2) Space: O(N)

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def findLucky(self, arr: List[int]) -> int: Time: O(N) Space: O(N) - def findLucky_2(self, arr: List[int]) -> int: Time: O(N^2) Space: O(N) <|skeleton|> class Solution: def...

57534898c17d058ef1dba2b1cb8cdcd8d1d2a41c

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def findLucky(self, arr: List[int]) -> int: """Time: O(N) Space: O(N)""" number_frequency_map = {} for num in arr: number_frequency_map[num] = number_frequency_map.get(num, 0) + 1 lucky_number = -1 for key, value in number_frequency_map.items(): ...

the_stack_v2_python_sparse

leetcode/leetcode_question_bank/problems/1394_find_lucky_integer_in_an_array/lucky_integer.py

arivolispark/datastructuresandalgorithms

train

0

26db360cbafd14ccfdb0466d616245d11efd3415

[ "self.api = api\nself.station = station\nsuper().__init__(hass, _LOGGER, name=name, update_interval=MIN_TIME_BETWEEN_UPDATES)", "try:\n return await self.api.async_get_station_measurements(self.station.uuid)\nexcept CONNECT_ERRORS as err:\n raise UpdateFailed(f'Failed to communicate with API: {err}') from e...

DataUpdateCoordinator for the pegel_online integration.

PegelOnlineDataUpdateCoordinator

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class PegelOnlineDataUpdateCoordinator: """DataUpdateCoordinator for the pegel_online integration.""" def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None: """Initialize the PegelOnlineDataUpdateCoordinator.""" <|body_0|> async def _as...

stack_v2_sparse_classes_10k_train_002308

1,227

permissive

[ { "docstring": "Initialize the PegelOnlineDataUpdateCoordinator.", "name": "__init__", "signature": "def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None" }, { "docstring": "Fetch data from API endpoint.", "name": "_async_update_data", "signature...

2

null

Implement the Python class `PegelOnlineDataUpdateCoordinator` described below. Class description: DataUpdateCoordinator for the pegel_online integration. Method signatures and docstrings: - def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None: Initialize the PegelOnlineDataUp...

80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743

<|skeleton|> class PegelOnlineDataUpdateCoordinator: """DataUpdateCoordinator for the pegel_online integration.""" def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None: """Initialize the PegelOnlineDataUpdateCoordinator.""" <|body_0|> async def _as...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class PegelOnlineDataUpdateCoordinator: """DataUpdateCoordinator for the pegel_online integration.""" def __init__(self, hass: HomeAssistant, name: str, api: PegelOnline, station: Station) -> None: """Initialize the PegelOnlineDataUpdateCoordinator.""" self.api = api self.station = stat...

the_stack_v2_python_sparse

homeassistant/components/pegel_online/coordinator.py

home-assistant/core

train

35,501

77346fe559d546712187956ec4b5f3bb8f842a2e

[ "sample = list(self.fetch_samples(sample_id=sample_id))\nif len(sample) > 0:\n LOG.info('Deleting sample %s from database', sample[0].id)\n self.delete_commit(sample)", "LOG.info('Deleting entire group %s from database', group_id)\nsamples = self.fetch_samples(group_id=group_id)\nfor sample in samples:\n ...

Methods for deleting samples from database

DeleteMixin

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002309

807

permissive

[ { "docstring": "Delete single sample from database", "name": "delete_sample", "signature": "def delete_sample(self, sample_id)" }, { "docstring": "Delete entire group from database", "name": "delete_group", "signature": "def delete_group(self, group_id)" } ]

2

stack_v2_sparse_classes_30k_train_004629

Implement the Python class `DeleteMixin` described below. Class description: Methods for deleting samples from database Method signatures and docstrings: - def delete_sample(self, sample_id): Delete single sample from database - def delete_group(self, group_id): Delete entire group from database

Implement the Python class `DeleteMixin` described below. Class description: Methods for deleting samples from database Method signatures and docstrings: - def delete_sample(self, sample_id): Delete single sample from database - def delete_group(self, group_id): Delete entire group from database <|skeleton|> class D...

13f80c592ade1693590992bc66af31b8c0600210

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class DeleteMixin: """Methods for deleting samples from database""" def delete_sample(self, sample_id): """Delete single sample from database""" sample = list(self.fetch_samples(sample_id=sample_id)) if len(sample) > 0: LOG.info('Deleting sample %s from database', sample[0]....

the_stack_v2_python_sparse

chanjo/store/delete.py

Clinical-Genomics/chanjo

train

10

8d5b41c37cb068490bb3cafe719cea9e64cb1d21

[ "self.linha = int(linha)\nself.coluna = int(coluna)\nself.robo = robo\nself.arena = []\nself.robo.posicao = 0\nfor i in range(linha):\n entrada = input()\n line = []\n for j in range(coluna):\n line.append(entrada[j])\n if not self.robo.posicao != 0:\n self.encontraPos(entrada[j], ...

<|body_start_0|> self.linha = int(linha) self.coluna = int(coluna) self.robo = robo self.arena = [] self.robo.posicao = 0 for i in range(linha): entrada = input() line = [] for j in range(coluna): line.append(entrada[j])...

Classe Arena.

Arena

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002310

3,220

no_license

[ { "docstring": "Construtor.", "name": "__init__", "signature": "def __init__(self, linha, coluna, robo)" }, { "docstring": "Plota arena.", "name": "__repr__", "signature": "def __repr__(self)" }, { "docstring": "Enc.", "name": "encontraPos", "signature": "def encontraPos(...

6

stack_v2_sparse_classes_30k_train_002015

Implement the Python class `Arena` described below. Class description: Classe Arena. Method signatures and docstrings: - def __init__(self, linha, coluna, robo): Construtor. - def __repr__(self): Plota arena. - def encontraPos(self, entrada, x, y): Enc. - def posAnteior(self): Altera na Arena a posicao anterior. - de...

e79b79c8b78693bf1d5d8843f7b0121be70bca70

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Arena: """Classe Arena.""" def __init__(self, linha, coluna, robo): """Construtor.""" self.linha = int(linha) self.coluna = int(coluna) self.robo = robo self.arena = [] self.robo.posicao = 0 for i in range(linha): entrada = input() ...

the_stack_v2_python_sparse

roboColecionadorOO.py

jonathasfsilva/lab-jfs-20181

train

0

4e839ba3808743ba8c8785079521bbfa02a0e34f

[ "id = request.GET.get('id', None)\nif id is None:\n offering_courses = OfferingCourse.objects.all()\n serializer = OfferingCourseSerializer(offering_courses, many=True)\n return JsonResponse({'offering_courses': serializer.data}, safe=False)\nelse:\n offering_course = get_object_or_404(OfferingCourse, i...

<|body_start_0|> id = request.GET.get('id', None) if id is None: offering_courses = OfferingCourse.objects.all() serializer = OfferingCourseSerializer(offering_courses, many=True) return JsonResponse({'offering_courses': serializer.data}, safe=False) else: ...

开设课程view

OfferingCourses

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002311

15,061

permissive

[ { "docstring": "查询开设课程", "name": "get", "signature": "def get(self, request)" }, { "docstring": "修改开设课程", "name": "put", "signature": "def put(self, request)" }, { "docstring": "增加开设课程", "name": "post", "signature": "def post(self, request)" }, { "docstring": "删除开...

4

stack_v2_sparse_classes_30k_train_003092

Implement the Python class `OfferingCourses` described below. Class description: 开设课程view Method signatures and docstrings: - def get(self, request): 查询开设课程 - def put(self, request): 修改开设课程 - def post(self, request): 增加开设课程 - def delete(self, request): 删除开设课程

Implement the Python class `OfferingCourses` described below. Class description: 开设课程view Method signatures and docstrings: - def get(self, request): 查询开设课程 - def put(self, request): 修改开设课程 - def post(self, request): 增加开设课程 - def delete(self, request): 删除开设课程 <|skeleton|> class OfferingCourses: """开设课程view""" ...

7aaa1be773718de1beb3ce0080edca7c4114b7ad

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class OfferingCourses: """开设课程view""" def get(self, request): """查询开设课程""" id = request.GET.get('id', None) if id is None: offering_courses = OfferingCourse.objects.all() serializer = OfferingCourseSerializer(offering_courses, many=True) return JsonRe...

the_stack_v2_python_sparse

plan/views.py

MIXISAMA/MIS-backend

train

0

89f95e76da8855e7c66229e30d32b041b0dbc7c5

[ "items = []\nif info.line.strip().startswith(('import ', 'from ')) and info.is_python_like:\n items += module_completion(info.line, [info.filename])\nelif info.obj:\n base = info.obj\n tokens = set(info.split_words(-1))\n items = [item for item in tokens if item.startswith(base) and len(item) > len(base...

<|body_start_0|> items = [] if info.line.strip().startswith(('import ', 'from ')) and info.is_python_like: items += module_completion(info.line, [info.filename]) elif info.obj: base = info.obj tokens = set(info.split_words(-1)) items = [item for it...

Basic Introspection Plugin for Spyder

FallbackPlugin

[ "Python-2.0", "Apache-2.0", "BSD-3-Clause", "LicenseRef-scancode-unknown" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class FallbackPlugin: """Basic Introspection Plugin for Spyder""" def get_completions(self, info): """Return a list of completion strings Simple completion based on python-like identifiers and whitespace""" <|body_0|> def get_definition(self, info): """Find the definit...

stack_v2_sparse_classes_10k_train_002312

13,005

permissive

[ { "docstring": "Return a list of completion strings Simple completion based on python-like identifiers and whitespace", "name": "get_completions", "signature": "def get_completions(self, info)" }, { "docstring": "Find the definition for an object within a set of source code This is used to find ...

2

stack_v2_sparse_classes_30k_train_007095

Implement the Python class `FallbackPlugin` described below. Class description: Basic Introspection Plugin for Spyder Method signatures and docstrings: - def get_completions(self, info): Return a list of completion strings Simple completion based on python-like identifiers and whitespace - def get_definition(self, in...

2c9002f16bb5c265e0d14f4a2314c86eeaa35cb6

<|skeleton|> class FallbackPlugin: """Basic Introspection Plugin for Spyder""" def get_completions(self, info): """Return a list of completion strings Simple completion based on python-like identifiers and whitespace""" <|body_0|> def get_definition(self, info): """Find the definit...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class FallbackPlugin: """Basic Introspection Plugin for Spyder""" def get_completions(self, info): """Return a list of completion strings Simple completion based on python-like identifiers and whitespace""" items = [] if info.line.strip().startswith(('import ', 'from ')) and info.is_pyt...

the_stack_v2_python_sparse

lib/python2.7/site-packages/spyderlib/utils/introspection/fallback_plugin.py

wangyum/Anaconda

train

11

d4e64a98de5a58c7fd5ddbd72b6e1516adfe6f4b

[ "if Singleton.__instance == None:\n Singleton()\nreturn Singleton.__instance", "if Singleton.__instance != None:\n raise Exception('This class is a singleton!')\nelse:\n Singleton.__instance = self" ]

Singleton

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002313

1,319

no_license

[ { "docstring": "Static access method.", "name": "getInstance", "signature": "def getInstance()" }, { "docstring": "Virtually private constructor.", "name": "__init__", "signature": "def __init__(self)" } ]

2

stack_v2_sparse_classes_30k_train_000709

Implement the Python class `Singleton` described below. Class description: Implement the Singleton class. Method signatures and docstrings: - def getInstance(): Static access method. - def __init__(self): Virtually private constructor.

Implement the Python class `Singleton` described below. Class description: Implement the Singleton class. Method signatures and docstrings: - def getInstance(): Static access method. - def __init__(self): Virtually private constructor. <|skeleton|> class Singleton: def getInstance(): """Static access me...

ed5f232f6737bc9f750d704455442f239d4f0561

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Singleton: def getInstance(): """Static access method.""" if Singleton.__instance == None: Singleton() return Singleton.__instance def __init__(self): """Virtually private constructor.""" if Singleton.__instance != None: raise Exception('Thi...

the_stack_v2_python_sparse

codes/design_pattern/02_singleton.py

Ziaeemehr/workshop_scripting

train

4

e05c94385259b4a27a8898fd11c194dd761a9f6f

[ "if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn SharedInsight()", "from .entity import Entity\nfrom .resource_reference import ResourceReference\nfrom .resource_visualization import ResourceVisualization\nfrom .sharing_detail import SharingDetail\nfrom .entity import Entity\nfrom .r...

SharedInsight

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SharedInsight: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharedInsight: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns...

stack_v2_sparse_classes_10k_train_002314

4,000

permissive

[ { "docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: SharedInsight", "name": "create_from_discriminator_value", "signature": "def create_from_discriminator_value...

3

null

Implement the Python class `SharedInsight` described below. Class description: Implement the SharedInsight class. Method signatures and docstrings: - def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharedInsight: Creates a new instance of the appropriate class based on discriminator value...

27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949

<|skeleton|> class SharedInsight: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharedInsight: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class SharedInsight: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SharedInsight: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: SharedInsigh...

the_stack_v2_python_sparse

msgraph/generated/models/shared_insight.py

microsoftgraph/msgraph-sdk-python

train

135

9dffa748bf4130da477d2e19d7e1e1a4fb6a5bfb

[ "assert len(sep) == 1\nself._sep = sep\nsuper().__init__(*args, **kwargs)", "if value is None:\n return None\nelif not isinstance(value, list) or set(map(type, value)) != {str}:\n raise ValueError('ListField stores lists of strings.')\nif any((self._sep in item for item in value)):\n raise ValueError(f'L...

<|body_start_0|> assert len(sep) == 1 self._sep = sep super().__init__(*args, **kwargs) <|end_body_0|> <|body_start_1|> if value is None: return None elif not isinstance(value, list) or set(map(type, value)) != {str}: raise ValueError('ListField stores li...

A field to facilitate storing lists of strings as a textfield.

ListField

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ListField: """A field to facilitate storing lists of strings as a textfield.""" def __init__(self, sep: str=',', *args: T.Any, **kwargs: T.Any) -> None: """init. Args: sep: What separator to use to separate fields. *args: Passed to pw.CharField. *kwargs: Passed to pw.CharField.""" ...

stack_v2_sparse_classes_10k_train_002315

9,976

no_license

[ { "docstring": "init. Args: sep: What separator to use to separate fields. *args: Passed to pw.CharField. *kwargs: Passed to pw.CharField.", "name": "__init__", "signature": "def __init__(self, sep: str=',', *args: T.Any, **kwargs: T.Any) -> None" }, { "docstring": "Validate and convert to strin...

3

stack_v2_sparse_classes_30k_train_001977

Implement the Python class `ListField` described below. Class description: A field to facilitate storing lists of strings as a textfield. Method signatures and docstrings: - def __init__(self, sep: str=',', *args: T.Any, **kwargs: T.Any) -> None: init. Args: sep: What separator to use to separate fields. *args: Passe...

46a5fee829c6e722afced0a3bc93cc41ded8c68e

<|skeleton|> class ListField: """A field to facilitate storing lists of strings as a textfield.""" def __init__(self, sep: str=',', *args: T.Any, **kwargs: T.Any) -> None: """init. Args: sep: What separator to use to separate fields. *args: Passed to pw.CharField. *kwargs: Passed to pw.CharField.""" ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ListField: """A field to facilitate storing lists of strings as a textfield.""" def __init__(self, sep: str=',', *args: T.Any, **kwargs: T.Any) -> None: """init. Args: sep: What separator to use to separate fields. *args: Passed to pw.CharField. *kwargs: Passed to pw.CharField.""" assert ...

the_stack_v2_python_sparse

services/web/backend/flask_app/database/models.py

arenabox/openFraming

train

0

7170a4a385d109166c0a985d85f7ccca6c99e23d

[ "if not head or not head.next:\n return head\np = head\nq = head.next\nhead.next = None\nwhile q:\n r = q.next\n q.next = p\n p = q\n q = r\nreturn p", "if not head or not head.next:\n return head\np = head.next\nnewHead = self.reverseList(p)\np.next = head\nhead.next = None\nreturn newHead" ]

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002316

868

no_license

[ { "docstring": "迭代 :param head: :return:", "name": "reverseList1", "signature": "def reverseList1(self, head)" }, { "docstring": "递归 :param head: :return:", "name": "reverseList", "signature": "def reverseList(self, head: ListNode) -> ListNode" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def reverseList1(self, head): 迭代 :param head: :return: - def reverseList(self, head: ListNode) -> ListNode: 递归 :param head: :return:

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def reverseList1(self, head): 迭代 :param head: :return: - def reverseList(self, head: ListNode) -> ListNode: 递归 :param head: :return: <|skeleton|> class Solution: def revers...

5d3574ccd282d0146c83c286ae28d8baaabd4910

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def reverseList1(self, head): """迭代 :param head: :return:""" if not head or not head.next: return head p = head q = head.next head.next = None while q: r = q.next q.next = p p = q q = r ...

the_stack_v2_python_sparse

206_反转链表.py

lovehhf/LeetCode

train

0

ed94486254899116b94770c0259e0fb6dc50c06d

[ "date_formatter = date.getLocaleFormatter(self.request, 'date', 'long')\n\ndef _q_data_item(q):\n item = {}\n item['qid'] = 'q_%s' % q.question_id\n if q.question_number:\n item['subject'] = u'Q %s %s' % (q.question_number, q.short_name)\n else:\n item['subject'] = q.short_name\n item['...

<|body_start_0|> date_formatter = date.getLocaleFormatter(self.request, 'date', 'long') def _q_data_item(q): item = {} item['qid'] = 'q_%s' % q.question_id if q.question_number: item['subject'] = u'Q %s %s' % (q.question_number, q.short_name) ...

QuestionInStateViewlet

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002317

27,657

no_license

[ { "docstring": "return the data of the query", "name": "_setData", "signature": "def _setData(self)" }, { "docstring": "refresh the query", "name": "update", "signature": "def update(self)" } ]

2

stack_v2_sparse_classes_30k_train_001156

Implement the Python class `QuestionInStateViewlet` described below. Class description: Implement the QuestionInStateViewlet class. Method signatures and docstrings: - def _setData(self): return the data of the query - def update(self): refresh the query

Implement the Python class `QuestionInStateViewlet` described below. Class description: Implement the QuestionInStateViewlet class. Method signatures and docstrings: - def _setData(self): return the data of the query - def update(self): refresh the query <|skeleton|> class QuestionInStateViewlet: def _setData(s...

5cf0ba31dfbff8d2c1b4aa8ab6f69c7a0ae9870d

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class QuestionInStateViewlet: def _setData(self): """return the data of the query""" date_formatter = date.getLocaleFormatter(self.request, 'date', 'long') def _q_data_item(q): item = {} item['qid'] = 'q_%s' % q.question_id if q.question_number: ...

the_stack_v2_python_sparse

bungeni.main/branches/mr/bungeni/ui/viewlets/workspace.py

malangalanga/bungeni-portal

train

0

a5048a5623ff03a9a7e278c717148999e69b8549

[ "lines = make_model()\nlog = get_logger(level='warning', encoding='utf-8')\nmodel = read_abaqus(lines, log=log, debug=False)\nmodel.write('spike.inp')\nos.remove('spike.inp')\nabaqus_filename = os.path.join(MODEL_PATH, 'abaqus.inp')\nwith open(abaqus_filename, 'w') as abaqus_file:\n abaqus_file.writelines('\\n'....

<|body_start_0|> lines = make_model() log = get_logger(level='warning', encoding='utf-8') model = read_abaqus(lines, log=log, debug=False) model.write('spike.inp') os.remove('spike.inp') abaqus_filename = os.path.join(MODEL_PATH, 'abaqus.inp') with open(abaqus_fil...

TestAbaqus

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002318

3,005

no_license

[ { "docstring": "simple test", "name": "test_abaqus_1", "signature": "def test_abaqus_1(self)" }, { "docstring": "two hex blocks with duplicate node ids", "name": "test_abaqus_2", "signature": "def test_abaqus_2(self)" } ]

2

stack_v2_sparse_classes_30k_train_003884

Implement the Python class `TestAbaqus` described below. Class description: Implement the TestAbaqus class. Method signatures and docstrings: - def test_abaqus_1(self): simple test - def test_abaqus_2(self): two hex blocks with duplicate node ids

Implement the Python class `TestAbaqus` described below. Class description: Implement the TestAbaqus class. Method signatures and docstrings: - def test_abaqus_1(self): simple test - def test_abaqus_2(self): two hex blocks with duplicate node ids <|skeleton|> class TestAbaqus: def test_abaqus_1(self): "...

d9ffdb4ac845b13bcf6aea96ff5d37cc026c5267

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class TestAbaqus: def test_abaqus_1(self): """simple test""" lines = make_model() log = get_logger(level='warning', encoding='utf-8') model = read_abaqus(lines, log=log, debug=False) model.write('spike.inp') os.remove('spike.inp') abaqus_filename = os.path.joi...

the_stack_v2_python_sparse

pyNastran/converters/abaqus/test_unit_abaqus.py

ratalex/pyNastran

train

0

c079ccd79ea0b2e24628d41bb02a42ab6dcae4e2

[ "self.model_type = model_type\nself.model_name = model_name\nself.model_task = model_task\nself.model_description = model_description\nself.model_folder = os.path.join(ROOT_DIR, self.model_type, self.model_task, self.model_name)\nself.bucket = s3.S3Bucket(bucket_name='s3ludos')\nif not os.path.isdir(self.model_fold...

<|body_start_0|> self.model_type = model_type self.model_name = model_name self.model_task = model_task self.model_description = model_description self.model_folder = os.path.join(ROOT_DIR, self.model_type, self.model_task, self.model_name) self.bucket = s3.S3Bucket(bucke...

Base class for the model

BaseModel

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class BaseModel: """Base class for the model""" def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'): """Args: model_type (str): Type of the model, 'models' model_name (str): Name of your model model_task (str): Task o...

stack_v2_sparse_classes_10k_train_002319

3,053

no_license

[ { "docstring": "Args: model_type (str): Type of the model, 'models' model_name (str): Name of your model model_task (str): Task of your model stage (str): training or prediction expname (str): Name of the experiment", "name": "__init__", "signature": "def __init__(self, model_name: str, model_task: str,...

2

stack_v2_sparse_classes_30k_train_000663

Implement the Python class `BaseModel` described below. Class description: Base class for the model Method signatures and docstrings: - def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'): Args: model_type (str): Type of the model, 'models' mode...

fd09eb1bceafe794d8784a21cfd3753cfd371258

<|skeleton|> class BaseModel: """Base class for the model""" def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'): """Args: model_type (str): Type of the model, 'models' model_name (str): Name of your model model_task (str): Task o...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class BaseModel: """Base class for the model""" def __init__(self, model_name: str, model_task: str, model_description: str='', expname: str=None, model_type: str='models'): """Args: model_type (str): Type of the model, 'models' model_name (str): Name of your model model_task (str): Task of your model ...

the_stack_v2_python_sparse

ludos/models/common.py

cthorey/ludos

train

0

eb6fc78df232b9999907f3ff2815886f1ae26f5d

[ "DataUnitSettings.__init__(self, n)\nself.registerCounted('IntensityTransferFunctions', 1)\nself.register('InterpolationTimepoints', 1)\nself.set('Type', 'Adjust')\nself.registerPrivate('ColorTransferFunction', 1)\nself.registerCounted('Source')\nself.register('VoxelSize')\nself.register('Spacing')\nself.register('...

<|body_start_0|> DataUnitSettings.__init__(self, n) self.registerCounted('IntensityTransferFunctions', 1) self.register('InterpolationTimepoints', 1) self.set('Type', 'Adjust') self.registerPrivate('ColorTransferFunction', 1) self.registerCounted('Source') self.re...

Description: Stores settings related to dataset adjustment

AdjustSettings

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class AdjustSettings: """Description: Stores settings related to dataset adjustment""" def __init__(self, n=-1): """Constructor""" <|body_0|> def initialize(self, dataunit, channels, timepoints): """Set initial values for settings based on number of channels and timepo...

stack_v2_sparse_classes_10k_train_002320

2,815

no_license

[ { "docstring": "Constructor", "name": "__init__", "signature": "def __init__(self, n=-1)" }, { "docstring": "Set initial values for settings based on number of channels and timepoints", "name": "initialize", "signature": "def initialize(self, dataunit, channels, timepoints)" } ]

2

stack_v2_sparse_classes_30k_train_005469

Implement the Python class `AdjustSettings` described below. Class description: Description: Stores settings related to dataset adjustment Method signatures and docstrings: - def __init__(self, n=-1): Constructor - def initialize(self, dataunit, channels, timepoints): Set initial values for settings based on number o...

ea8bafa073de5090bd8f83fb4f5ca16669d0211f

<|skeleton|> class AdjustSettings: """Description: Stores settings related to dataset adjustment""" def __init__(self, n=-1): """Constructor""" <|body_0|> def initialize(self, dataunit, channels, timepoints): """Set initial values for settings based on number of channels and timepo...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class AdjustSettings: """Description: Stores settings related to dataset adjustment""" def __init__(self, n=-1): """Constructor""" DataUnitSettings.__init__(self, n) self.registerCounted('IntensityTransferFunctions', 1) self.register('InterpolationTimepoints', 1) self.se...

the_stack_v2_python_sparse

Graphs/LX-2/molecule_otsu = False/BioImageXD-1.0/Modules/Task/Adjust/AdjustSettings.py

giacomo21/Image-analysis

train

1

22797439416b5ec13b2082d3d7d637441f0214c3

[ "self.data_dir = FileOps.download_dataset(data_dir)\nself.batch_size = batch_size\nself.mode = mode\nself.num_parallel_batches = num_parallel_batches\nself.repeat_num = repeat_num\nself.dtype = tf.float16 if fp16 is True else tf.float32\nself.drop_remainder = drop_remainder\nself._include_mask = False\nself._datase...

<|body_start_0|> self.data_dir = FileOps.download_dataset(data_dir) self.batch_size = batch_size self.mode = mode self.num_parallel_batches = num_parallel_batches self.repeat_num = repeat_num self.dtype = tf.float16 if fp16 is True else tf.float32 self.drop_remain...

This is a class for Coco TFRecords dataset. :param data_dir: Coco TFRecords data directory :type data_dir: str :param batch_size: batch size :type batch_size: int :param mode: dataset mode, train or val :type mode: str :param num_parallel_batches: number of parallel batches :type num_parallel_batches: int, default 1 :p...

CocoDataset

[ "Apache-2.0", "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CocoDataset: """This is a class for Coco TFRecords dataset. :param data_dir: Coco TFRecords data directory :type data_dir: str :param batch_size: batch size :type batch_size: int :param mode: dataset mode, train or val :type mode: str :param num_parallel_batches: number of parallel batches :type ...

stack_v2_sparse_classes_10k_train_002321

5,507

permissive

[ { "docstring": "Init CocoTF.", "name": "__init__", "signature": "def __init__(self, data_dir, batch_size, mode, num_parallel_batches=1, repeat_num=5, padding=8, fp16=False, drop_remainder=False)" }, { "docstring": "Coco data files of type TFRecords.", "name": "_file_pattern", "signature"...

4

null

Implement the Python class `CocoDataset` described below. Class description: This is a class for Coco TFRecords dataset. :param data_dir: Coco TFRecords data directory :type data_dir: str :param batch_size: batch size :type batch_size: int :param mode: dataset mode, train or val :type mode: str :param num_parallel_bat...

df51ed9c1d6dbde1deef63f2a037a369f8554406

<|skeleton|> class CocoDataset: """This is a class for Coco TFRecords dataset. :param data_dir: Coco TFRecords data directory :type data_dir: str :param batch_size: batch size :type batch_size: int :param mode: dataset mode, train or val :type mode: str :param num_parallel_batches: number of parallel batches :type ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class CocoDataset: """This is a class for Coco TFRecords dataset. :param data_dir: Coco TFRecords data directory :type data_dir: str :param batch_size: batch size :type batch_size: int :param mode: dataset mode, train or val :type mode: str :param num_parallel_batches: number of parallel batches :type num_parallel_...

the_stack_v2_python_sparse

built-in/TensorFlow/Research/cv/image_classification/Cars_for_TensorFlow/automl/vega/datasets/tensorflow/coco.py

Huawei-Ascend/modelzoo

train

1

d113ebbfe7c02fb786ba4624e88cd009a9ba2598

[ "with open(img_path, 'rb') as f:\n base64_data = base64.b64encode(f.read())\n base64_data = base64_data.decode('utf8')\n return base64_data", "base64_encoding = base64_encoding.encode('utf8')\nimg_data = base64.b64decode(base64_encoding)\nwith open(des_img_path, 'wb') as file:\n file.write(img_data)" ...

ImageTransform

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002322

1,206

no_license

[ { "docstring": ":param img_path: :return:", "name": "img_to_base64", "signature": "def img_to_base64(img_path)" }, { "docstring": ":param des_img_path: :param base64_encoding: :return:", "name": "base64_to_img", "signature": "def base64_to_img(base64_encoding, des_img_path)" } ]

2

stack_v2_sparse_classes_30k_train_005997

Implement the Python class `ImageTransform` described below. Class description: Implement the ImageTransform class. Method signatures and docstrings: - def img_to_base64(img_path): :param img_path: :return: - def base64_to_img(base64_encoding, des_img_path): :param des_img_path: :param base64_encoding: :return:

Implement the Python class `ImageTransform` described below. Class description: Implement the ImageTransform class. Method signatures and docstrings: - def img_to_base64(img_path): :param img_path: :return: - def base64_to_img(base64_encoding, des_img_path): :param des_img_path: :param base64_encoding: :return: <|sk...

ee41eb80d6b8823cfd764920ed8aa4c682d9a013

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ImageTransform: def img_to_base64(img_path): """:param img_path: :return:""" with open(img_path, 'rb') as f: base64_data = base64.b64encode(f.read()) base64_data = base64_data.decode('utf8') return base64_data def base64_to_img(base64_encoding, des_img_...

the_stack_v2_python_sparse

data_custom_backend/llib/cv_utility/image_transform.py

marjeylee/cmdb

train

0

1738ed8d4580f1107dfbee9373698fe766ade0ac

[ "ENFORCER.enforce_call(action='identity:check_grant', build_target=functools.partial(self._build_enforcement_target_attr, role_id=role_id, project_id=project_id, group_id=group_id))\ninherited = self._check_if_inherited()\nPROVIDERS.assignment_api.get_grant(role_id=role_id, group_id=group_id, project_id=project_id,...

<|body_start_0|> ENFORCER.enforce_call(action='identity:check_grant', build_target=functools.partial(self._build_enforcement_target_attr, role_id=role_id, project_id=project_id, group_id=group_id)) inherited = self._check_if_inherited() PROVIDERS.assignment_api.get_grant(role_id=role_id, group_i...

ProjectGroupGrantResource

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ProjectGroupGrantResource: def get(self, project_id, group_id, role_id): """Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{role_id}""" <|body_0|> def put(self, project_id, group_id, role_id): """Grant role for group o...

stack_v2_sparse_classes_10k_train_002323

22,149

permissive

[ { "docstring": "Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{role_id}", "name": "get", "signature": "def get(self, project_id, group_id, role_id)" }, { "docstring": "Grant role for group on project. PUT /v3/projects/{project_id}/groups/{group_i...

3

stack_v2_sparse_classes_30k_train_006296

Implement the Python class `ProjectGroupGrantResource` described below. Class description: Implement the ProjectGroupGrantResource class. Method signatures and docstrings: - def get(self, project_id, group_id, role_id): Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{r...

03a0a8146a78682ede9eca12a5a7fdacde2035c8

<|skeleton|> class ProjectGroupGrantResource: def get(self, project_id, group_id, role_id): """Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{role_id}""" <|body_0|> def put(self, project_id, group_id, role_id): """Grant role for group o...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ProjectGroupGrantResource: def get(self, project_id, group_id, role_id): """Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{role_id}""" ENFORCER.enforce_call(action='identity:check_grant', build_target=functools.partial(self._build_enforcement_t...

the_stack_v2_python_sparse

keystone/api/projects.py

sapcc/keystone

train

0

011241ab57547be3ce8b0ab58fb256e7c80156d2

[ "queryset = Workshop.objects.filter(club=obj, date__gte=date.today()).order_by('date', 'time')\nserializer = WorkshopSerializer(queryset, many=True)\nreturn serializer.data", "queryset = Workshop.objects.filter(club=obj, date__lt=date.today()).order_by('-date', '-time')\nserializer = WorkshopSerializer(queryset, ...

ClubDetailWorkshopSerializer

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002324

18,006

no_license

[ { "docstring": "Active Workshops of the Club", "name": "get_active_workshops", "signature": "def get_active_workshops(self, obj)" }, { "docstring": "Past Workshops of the Club", "name": "get_past_workshops", "signature": "def get_past_workshops(self, obj)" } ]

2

stack_v2_sparse_classes_30k_train_005283

Implement the Python class `ClubDetailWorkshopSerializer` described below. Class description: Implement the ClubDetailWorkshopSerializer class. Method signatures and docstrings: - def get_active_workshops(self, obj): Active Workshops of the Club - def get_past_workshops(self, obj): Past Workshops of the Club

Implement the Python class `ClubDetailWorkshopSerializer` described below. Class description: Implement the ClubDetailWorkshopSerializer class. Method signatures and docstrings: - def get_active_workshops(self, obj): Active Workshops of the Club - def get_past_workshops(self, obj): Past Workshops of the Club <|skele...

7cd4eb5d82917dcc554331d3893108b809468505

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ClubDetailWorkshopSerializer: def get_active_workshops(self, obj): """Active Workshops of the Club""" queryset = Workshop.objects.filter(club=obj, date__gte=date.today()).order_by('date', 'time') serializer = WorkshopSerializer(queryset, many=True) return serializer.data d...

the_stack_v2_python_sparse

workshop/serializers.py

aishwary023/workshops-app-backend

train

0

d4ba1cd917884ee1503fe147fe6bb3ed9493e61f

[ "if not root:\n return 'n'\ns = ''\nstack = [root]\nwhile stack:\n root = stack.pop(0)\n if root:\n s += str(root.val)\n stack.append(root.left)\n stack.append(root.right)\n else:\n s += 'n'\n s += ' '\nreturn s", "if not data:\n return None\ntree = data.split()\nif t...

<|body_start_0|> if not root: return 'n' s = '' stack = [root] while stack: root = stack.pop(0) if root: s += str(root.val) stack.append(root.left) stack.append(root.right) else: ...

Codec

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002325

2,353

no_license

[ { "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_002505

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:...

ce29ea836bd20841d69972180273e4d4ec11514d

stack_v2_sparse_classes_10k

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 'n' s = '' stack = [root] while stack: root = stack.pop(0) if root: s += str(root.val) ...

the_stack_v2_python_sparse

37.py

NeilWangziyu/JZOffer

train

1

2a96946ba686a7a1d5903a949c583e63a1ad9946

[ "self.device = device\nself.max_length = max_length\nself.config = AutoConfig.from_pretrained(model_name_or_path, cache_dir=cache_dir)\nself.tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, cache_dir=cache_dir)\nself.model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path, config=self.config, ...

<|body_start_0|> self.device = device self.max_length = max_length self.config = AutoConfig.from_pretrained(model_name_or_path, cache_dir=cache_dir) self.tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, cache_dir=cache_dir) self.model = AutoModelForSeq2SeqLM.from_pre...

UniEvaluator

[ "BSD-3-Clause", "LicenseRef-scancode-warranty-disclaimer", "Apache-2.0", "BSD-2-Clause", "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class UniEvaluator: def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None): """Set up model""" <|body_0|> def score(self, inputs, task, category, dim, batch_size=8): """Get scores for the given samples. final_score = postive_score / (posti...

stack_v2_sparse_classes_10k_train_002326

4,582

permissive

[ { "docstring": "Set up model", "name": "__init__", "signature": "def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None)" }, { "docstring": "Get scores for the given samples. final_score = postive_score / (postive_score + negative_score)", "name": "score", ...

2

stack_v2_sparse_classes_30k_train_001918

Implement the Python class `UniEvaluator` described below. Class description: Implement the UniEvaluator class. Method signatures and docstrings: - def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None): Set up model - def score(self, inputs, task, category, dim, batch_size=8): Get s...

c7b60f75470f067d1342705708810a660eabd684

<|skeleton|> class UniEvaluator: def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None): """Set up model""" <|body_0|> def score(self, inputs, task, category, dim, batch_size=8): """Get scores for the given samples. final_score = postive_score / (posti...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class UniEvaluator: def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None): """Set up model""" self.device = device self.max_length = max_length self.config = AutoConfig.from_pretrained(model_name_or_path, cache_dir=cache_dir) self.tokenizer ...

the_stack_v2_python_sparse

applications/Chat/evaluate/unieval/scorer.py

hpcaitech/ColossalAI

train

32,044

5e4198dcc9da98e7c4922d426edff324a07f9969

[ "@self.router.get('/info', response_model=Info, response_model_exclude={'minzoom', 'maxzoom', 'center'}, response_model_exclude_none=True, responses={200: {'description': \"Return dataset's basic info or the list of available bands.\"}})\ndef info(src_path=Depends(self.path_dependency), bands_params=Depends(BandsPa...

<|body_start_0|> @self.router.get('/info', response_model=Info, response_model_exclude={'minzoom', 'maxzoom', 'center'}, response_model_exclude_none=True, responses={200: {'description': "Return dataset's basic info or the list of available bands."}}) def info(src_path=Depends(self.path_dependency), ban...

Custom Tiler Factory for MultiBandReader classes. Note: To be able to use the rio_tiler.io.MultiBandReader we need to be able to pass a `bands` argument to most of its methods. By using the `BandsExprParams` for the `layer_dependency`, the .tile(), .point(), .preview() and the .part() methods will receive bands or expr...

MultiBandTilerFactory

[ "LicenseRef-scancode-unknown-license-reference", "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MultiBandTilerFactory: """Custom Tiler Factory for MultiBandReader classes. Note: To be able to use the rio_tiler.io.MultiBandReader we need to be able to pass a `bands` argument to most of its methods. By using the `BandsExprParams` for the `layer_dependency`, the .tile(), .point(), .preview() a...

stack_v2_sparse_classes_10k_train_002327

48,399

permissive

[ { "docstring": "Register /info endpoint.", "name": "info", "signature": "def info(self)" }, { "docstring": "Register /metadata endpoint.", "name": "metadata", "signature": "def metadata(self)" } ]

2

stack_v2_sparse_classes_30k_train_002633

Implement the Python class `MultiBandTilerFactory` described below. Class description: Custom Tiler Factory for MultiBandReader classes. Note: To be able to use the rio_tiler.io.MultiBandReader we need to be able to pass a `bands` argument to most of its methods. By using the `BandsExprParams` for the `layer_dependenc...

2168c9284b39a46c4d1a095542c77addc690a738

<|skeleton|> class MultiBandTilerFactory: """Custom Tiler Factory for MultiBandReader classes. Note: To be able to use the rio_tiler.io.MultiBandReader we need to be able to pass a `bands` argument to most of its methods. By using the `BandsExprParams` for the `layer_dependency`, the .tile(), .point(), .preview() a...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class MultiBandTilerFactory: """Custom Tiler Factory for MultiBandReader classes. Note: To be able to use the rio_tiler.io.MultiBandReader we need to be able to pass a `bands` argument to most of its methods. By using the `BandsExprParams` for the `layer_dependency`, the .tile(), .point(), .preview() and the .part(...

the_stack_v2_python_sparse

src/titiler/core/titiler/core/factory.py

kylebarron/titiler

train

0

a8e6acf38526e16b0a98e994e5692d53285264c5

[ "startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('yufeng72', 'yufeng72')\nurl = 'http://bostonopendata-boston.opendata.arcgis.com/datasets/cbf14bb032ef4bd38e20429f71acb61a_2.csv'\nresponse = urllib.request.urlopen(url)\nr = csv.reader(io.StringIO(respon...

<|body_start_0|> startTime = datetime.datetime.now() client = dml.pymongo.MongoClient() repo = client.repo repo.authenticate('yufeng72', 'yufeng72') url = 'http://bostonopendata-boston.opendata.arcgis.com/datasets/cbf14bb032ef4bd38e20429f71acb61a_2.csv' response = urllib....

RetrieveCollegesUniversities

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class RetrieveCollegesUniversities: def execute(trial=False): """Retrieve some data sets (not using the API here for the sake of simplicity).""" <|body_0|> def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): """Create the provenance document descri...

stack_v2_sparse_classes_10k_train_002328

5,033

no_license

[ { "docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).", "name": "execute", "signature": "def execute(trial=False)" }, { "docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d...

2

stack_v2_sparse_classes_30k_train_000899

Implement the Python class `RetrieveCollegesUniversities` described below. Class description: Implement the RetrieveCollegesUniversities class. Method signatures and docstrings: - def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity). - def provenance(doc=prov.model.Pro...

90284cf3debbac36eead07b8d2339cdd191b86cf

<|skeleton|> class RetrieveCollegesUniversities: def execute(trial=False): """Retrieve some data sets (not using the API here for the sake of simplicity).""" <|body_0|> def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): """Create the provenance document descri...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class RetrieveCollegesUniversities: def execute(trial=False): """Retrieve some data sets (not using the API here for the sake of simplicity).""" startTime = datetime.datetime.now() client = dml.pymongo.MongoClient() repo = client.repo repo.authenticate('yufeng72', 'yufeng72')...

the_stack_v2_python_sparse

yufeng72/RetrieveCollegesUniversities.py

maximega/course-2019-spr-proj

train

2

8e43691036f9dcded320b1e2f45e9f7698c44438

[ "super().__init__(model_dir, *args, **kwargs)\nself.model_dir: str = model_dir\nself.sequence_length = kwargs.pop('sequence_length', 512)\nself.tokenizer = AutoTokenizer.from_pretrained(model_dir, use_fast=True)", "text = data\noutput = self.tokenizer([text], return_tensors='pt')\nreturn {'text': text, 'input_ids...

The relation extraction preprocessor used in normal RE task.

RelationExtractionPreprocessor

[ "Apache-2.0", "BSD-3-Clause", "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class RelationExtractionPreprocessor: """The relation extraction preprocessor used in normal RE task.""" def __init__(self, model_dir: str, *args, **kwargs): """preprocess the data Args: model_dir (str): model path""" <|body_0|> def __call__(self, data: str) -> Dict[str, Any]:...

stack_v2_sparse_classes_10k_train_002329

1,650

permissive

[ { "docstring": "preprocess the data Args: model_dir (str): model path", "name": "__init__", "signature": "def __init__(self, model_dir: str, *args, **kwargs)" }, { "docstring": "process the raw input data Args: data (str): a sentence Example: 'you are so handsome.' Returns: Dict[str, Any]: the p...

2

null

Implement the Python class `RelationExtractionPreprocessor` described below. Class description: The relation extraction preprocessor used in normal RE task. Method signatures and docstrings: - def __init__(self, model_dir: str, *args, **kwargs): preprocess the data Args: model_dir (str): model path - def __call__(sel...

8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6

<|skeleton|> class RelationExtractionPreprocessor: """The relation extraction preprocessor used in normal RE task.""" def __init__(self, model_dir: str, *args, **kwargs): """preprocess the data Args: model_dir (str): model path""" <|body_0|> def __call__(self, data: str) -> Dict[str, Any]:...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class RelationExtractionPreprocessor: """The relation extraction preprocessor used in normal RE task.""" def __init__(self, model_dir: str, *args, **kwargs): """preprocess the data Args: model_dir (str): model path""" super().__init__(model_dir, *args, **kwargs) self.model_dir: str = mo...

the_stack_v2_python_sparse

ai/modelscope/modelscope/preprocessors/nlp/relation_extraction_preprocessor.py

alldatacenter/alldata

train

774

e1e91015a9c30ca44aa92454e15189e1076b821b

[ "self.typology = 'Area'\nself.id = identifier\nself.name = name\nself.trt = trt\nself.geometry = geometry\nself.upper_depth = upper_depth\nself.lower_depth = lower_depth\nself.mag_scale_rel = mag_scale_rel\nself.rupt_aspect_ratio = rupt_aspect_ratio\nself.mfd = mfd\nself.nodal_plane_dist = nodal_plane_dist\nself.hy...

<|body_start_0|> self.typology = 'Area' self.id = identifier self.name = name self.trt = trt self.geometry = geometry self.upper_depth = upper_depth self.lower_depth = lower_depth self.mag_scale_rel = mag_scale_rel self.rupt_aspect_ratio = rupt_asp...

Describes the Area Source :param str identifier: ID code for the source :param str name: Source name :param str trt: Tectonic region type :param geometry: Instance of :class: nhlib.geo.polygon.Polygon class :param float upper_depth: Upper seismogenic depth (km) :param float lower_depth: Lower seismogenic depth (km) :pa...

mtkAreaSource

[ "AGPL-3.0-only", "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class mtkAreaSource: """Describes the Area Source :param str identifier: ID code for the source :param str name: Source name :param str trt: Tectonic region type :param geometry: Instance of :class: nhlib.geo.polygon.Polygon class :param float upper_depth: Upper seismogenic depth (km) :param float lowe...

stack_v2_sparse_classes_10k_train_002330

9,101

permissive

[ { "docstring": "Instantiates class with two essential attributes: identifier and name", "name": "__init__", "signature": "def __init__(self, identifier, name, trt=None, geometry=None, upper_depth=None, lower_depth=None, mag_scale_rel=None, rupt_aspect_ratio=None, mfd=None, nodal_plane_dist=None, hypo_de...

5

stack_v2_sparse_classes_30k_train_005788

Implement the Python class `mtkAreaSource` described below. Class description: Describes the Area Source :param str identifier: ID code for the source :param str name: Source name :param str trt: Tectonic region type :param geometry: Instance of :class: nhlib.geo.polygon.Polygon class :param float upper_depth: Upper s...

0da9ba5a575360081715e8b90c71d4b16c6687c8

<|skeleton|> class mtkAreaSource: """Describes the Area Source :param str identifier: ID code for the source :param str name: Source name :param str trt: Tectonic region type :param geometry: Instance of :class: nhlib.geo.polygon.Polygon class :param float upper_depth: Upper seismogenic depth (km) :param float lowe...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class mtkAreaSource: """Describes the Area Source :param str identifier: ID code for the source :param str name: Source name :param str trt: Tectonic region type :param geometry: Instance of :class: nhlib.geo.polygon.Polygon class :param float upper_depth: Upper seismogenic depth (km) :param float lower_depth: Lowe...

the_stack_v2_python_sparse

openquake/hmtk/sources/area_source.py

GFZ-Centre-for-Early-Warning/shakyground

train

1

4a0521e733d7580ef3eba6519f3e26a369b68637

[ "super().__init__()\nself.spherical_cheb = SphericalChebConv(in_channels, out_channels, lap, kernel_size)\nself.batchnorm = nn.BatchNorm1d(out_channels)", "x = self.spherical_cheb(x)\nx = self.batchnorm(x.permute(0, 2, 1))\nx = F.relu(x.permute(0, 2, 1))\nreturn x" ]

Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation.

SphericalChebBN

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SphericalChebBN: """Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation.""" def __init__(self, in_channels, out_channels, lap, kernel_size): """Initialization. Args: in_channels (int): initial number of channels. out_channels (int): output number of c...

stack_v2_sparse_classes_10k_train_002331

41,403

no_license

[ { "docstring": "Initialization. Args: in_channels (int): initial number of channels. out_channels (int): output number of channels. lap (:obj:`torch.sparse.FloatTensor`): laplacian. kernel_size (int, optional): polynomial degree. Defaults to 3.", "name": "__init__", "signature": "def __init__(self, in_c...

2

null

Implement the Python class `SphericalChebBN` described below. Class description: Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation. Method signatures and docstrings: - def __init__(self, in_channels, out_channels, lap, kernel_size): Initialization. Args: in_channels (int): initial n...

7e55a422588c1d1e00f35a3d3a3ff896cce59e18

<|skeleton|> class SphericalChebBN: """Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation.""" def __init__(self, in_channels, out_channels, lap, kernel_size): """Initialization. Args: in_channels (int): initial number of channels. out_channels (int): output number of c...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class SphericalChebBN: """Building Block with a Chebyshev Convolution, Batchnormalization, and ReLu activation.""" def __init__(self, in_channels, out_channels, lap, kernel_size): """Initialization. Args: in_channels (int): initial number of channels. out_channels (int): output number of channels. lap ...

the_stack_v2_python_sparse

generated/test_deepsphere_deepsphere_pytorch.py

jansel/pytorch-jit-paritybench

train

35

166f1110ae1960c9a1910891171dde528767ece6

[ "params = self.get_set_params(locals())\nresponse = await self.api.request('donut.getFriends', params)\nmodel = donut.GetFriendsResponse\nreturn model(**response).response", "params = self.get_set_params(locals())\nresponse = await self.api.request('donut.getSubscription', params)\nmodel = donut.GetSubscriptionRe...

DonutCategory

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class DonutCategory: async def get_friends(self, owner_id: int, offset: Optional[int]=None, count: Optional[int]=None, fields: Optional[List[str]]=None, **kwargs) -> donut.GetFriendsResponseModel: """donut.getFriends method :param owner_id: :param offset: :param count: :param fields:""" ...

stack_v2_sparse_classes_10k_train_002332

1,897

permissive

[ { "docstring": "donut.getFriends method :param owner_id: :param offset: :param count: :param fields:", "name": "get_friends", "signature": "async def get_friends(self, owner_id: int, offset: Optional[int]=None, count: Optional[int]=None, fields: Optional[List[str]]=None, **kwargs) -> donut.GetFriendsRes...

4

stack_v2_sparse_classes_30k_val_000385

Implement the Python class `DonutCategory` described below. Class description: Implement the DonutCategory class. Method signatures and docstrings: - async def get_friends(self, owner_id: int, offset: Optional[int]=None, count: Optional[int]=None, fields: Optional[List[str]]=None, **kwargs) -> donut.GetFriendsRespons...

dfcedd4023aa170dd7f802ac662f0e2ed9033904

<|skeleton|> class DonutCategory: async def get_friends(self, owner_id: int, offset: Optional[int]=None, count: Optional[int]=None, fields: Optional[List[str]]=None, **kwargs) -> donut.GetFriendsResponseModel: """donut.getFriends method :param owner_id: :param offset: :param count: :param fields:""" ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class DonutCategory: async def get_friends(self, owner_id: int, offset: Optional[int]=None, count: Optional[int]=None, fields: Optional[List[str]]=None, **kwargs) -> donut.GetFriendsResponseModel: """donut.getFriends method :param owner_id: :param offset: :param count: :param fields:""" params = sel...

the_stack_v2_python_sparse

codegen/results/methods/donut.py

ScriptHound/vkbottle-types

train

0

3f3fedc0d4facd3f6b20650ffed04ee9a33d24d8

[ "data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.add_dataStage03QuantificationOtherData(data.data)\ndata.clear_data()", "data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.update_dataStage03QuantificationOtherData(data.data)\ndata.clear_data()" ]

stage03_quantification_otherData_io

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002333

982

permissive

[ { "docstring": "table adds", "name": "import_dataStage03QuantificationOtherData_add", "signature": "def import_dataStage03QuantificationOtherData_add(self, filename)" }, { "docstring": "table adds", "name": "import_dataStage03QuantificationOtherData_update", "signature": "def import_data...

2

stack_v2_sparse_classes_30k_train_006713

Implement the Python class `stage03_quantification_otherData_io` described below. Class description: Implement the stage03_quantification_otherData_io class. Method signatures and docstrings: - def import_dataStage03QuantificationOtherData_add(self, filename): table adds - def import_dataStage03QuantificationOtherDat...

0eeed0191f952ea0226ab8bbc234a30638fb2f9f

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class stage03_quantification_otherData_io: def import_dataStage03QuantificationOtherData_add(self, filename): """table adds""" data = base_importData() data.read_csv(filename) data.format_data() self.add_dataStage03QuantificationOtherData(data.data) data.clear_data() ...

the_stack_v2_python_sparse

SBaaS_thermodynamics/stage03_quantification_otherData_io.py

dmccloskey/SBaaS_thermodynamics

train

0

d416e44660facb07879f2d214c0706e9b0ff04d0

[ "self.number = number\nself.title = title\nself.paragraphs = []\nfor paragraph_lines in paragraphs:\n new_pragraph = Paragraph.Paragraph(paragraph_lines)\n self.paragraphs.append(new_pragraph)", "if paragraph_idx:\n self.paragraphs[paragraph_idx].read()\nelse:\n for paragraph in self.paragraphs:\n ...

Chapter

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002334

676

no_license

[ { "docstring": "A chapter consists of multiple paragraphs.", "name": "__init__", "signature": "def __init__(self, number, title, paragraphs)" }, { "docstring": "A paragraph can be read.", "name": "read", "signature": "def read(self, paragraph_idx=None)" } ]

2

stack_v2_sparse_classes_30k_train_000787

Implement the Python class `Chapter` described below. Class description: Implement the Chapter class. Method signatures and docstrings: - def __init__(self, number, title, paragraphs): A chapter consists of multiple paragraphs. - def read(self, paragraph_idx=None): A paragraph can be read.

Implement the Python class `Chapter` described below. Class description: Implement the Chapter class. Method signatures and docstrings: - def __init__(self, number, title, paragraphs): A chapter consists of multiple paragraphs. - def read(self, paragraph_idx=None): A paragraph can be read. <|skeleton|> class Chapter...

70dac5017980c8f30294f2cbd98e5bfd905bfaa7

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Chapter: def __init__(self, number, title, paragraphs): """A chapter consists of multiple paragraphs.""" self.number = number self.title = title self.paragraphs = [] for paragraph_lines in paragraphs: new_pragraph = Paragraph.Paragraph(paragraph_lines) ...

the_stack_v2_python_sparse

week2/objectOriented/Chapter.py

MalteMagnussen/PythonProjects

train

0

ab8730795161ecb89426f9f0db37c162c2c1f894

[ "self.dic = {}\nfor word in set(dictionary):\n if word:\n if len(word) <= 2:\n if word not in self.dic:\n self.dic[word] = set()\n self.dic[word].add(word)\n else:\n abb = word[0] + str(len(word) - 2) + word[-1]\n if abb in self.dic:\n ...

<|body_start_0|> self.dic = {} for word in set(dictionary): if word: if len(word) <= 2: if word not in self.dic: self.dic[word] = set() self.dic[word].add(word) else: abb =...

ValidWordAbbr

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002335

1,496

no_license

[ { "docstring": "initialize your data structure here. :type dictionary: List[str]", "name": "__init__", "signature": "def __init__(self, dictionary)" }, { "docstring": "check if a word is unique. :type word: str :rtype: bool", "name": "isUnique", "signature": "def isUnique(self, word)" ...

2

stack_v2_sparse_classes_30k_train_002698

Implement the Python class `ValidWordAbbr` described below. Class description: Implement the ValidWordAbbr class. Method signatures and docstrings: - def __init__(self, dictionary): initialize your data structure here. :type dictionary: List[str] - def isUnique(self, word): check if a word is unique. :type word: str ...

f1b85a2bfee024ef3afdf2ca0b223842c2d2d3f3

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ValidWordAbbr: def __init__(self, dictionary): """initialize your data structure here. :type dictionary: List[str]""" self.dic = {} for word in set(dictionary): if word: if len(word) <= 2: if word not in self.dic: ...

the_stack_v2_python_sparse

288-Unique-Word-Abbreviation/solution.py

Xochitlxie/Leetcode

train

0

bbabdd8dcb523a539fc0cba2f95ba346e0000c55

[ "if level != 0:\n image1 = ImageExtender.extend_image(image, int(image.width), int(image.height))\n image2 = GaussianNoiseGenerator.generate_gaussian_noise_by_level(image1, level, image.width)\n return BoundedImageCropper.crop_bounded_image_inverse(image2, (255, 255, 255, 0))\nelse:\n return image", "...

<|body_start_0|> if level != 0: image1 = ImageExtender.extend_image(image, int(image.width), int(image.height)) image2 = GaussianNoiseGenerator.generate_gaussian_noise_by_level(image1, level, image.width) return BoundedImageCropper.crop_bounded_image_inverse(image2, (255, 255...

NoisedImageGenerator

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class NoisedImageGenerator: def generate_noised_image_by_level(image, level): """Blur an image with the intended noise level :param image: the image to modify :param level: the level of the noise (more explanation in gaussian_noise_generator) :type image: an image file :type level: int (prefer...

stack_v2_sparse_classes_10k_train_002336

1,670

permissive

[ { "docstring": "Blur an image with the intended noise level :param image: the image to modify :param level: the level of the noise (more explanation in gaussian_noise_generator) :type image: an image file :type level: int (preferably from 0 to 100)", "name": "generate_noised_image_by_level", "signature"...

2

stack_v2_sparse_classes_30k_train_003701

Implement the Python class `NoisedImageGenerator` described below. Class description: Implement the NoisedImageGenerator class. Method signatures and docstrings: - def generate_noised_image_by_level(image, level): Blur an image with the intended noise level :param image: the image to modify :param level: the level of...

8931c8859878692134f5113d4c6c3e17561f0196

<|skeleton|> class NoisedImageGenerator: def generate_noised_image_by_level(image, level): """Blur an image with the intended noise level :param image: the image to modify :param level: the level of the noise (more explanation in gaussian_noise_generator) :type image: an image file :type level: int (prefer...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class NoisedImageGenerator: def generate_noised_image_by_level(image, level): """Blur an image with the intended noise level :param image: the image to modify :param level: the level of the noise (more explanation in gaussian_noise_generator) :type image: an image file :type level: int (preferably from 0 to...

the_stack_v2_python_sparse

UpdatedSyntheticDataset/SyntheticDataset2/ElementsCreator/noised_image_generator.py

FlintHill/SUAS-Competition

train

5

cdad07f5439fc88c0cf211d88719d8bc2954088d

[ "if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn CountryNamedLocation()", "from .country_lookup_method_type import CountryLookupMethodType\nfrom .named_location import NamedLocation\nfrom .country_lookup_method_type import CountryLookupMethodType\nfrom .named_location import NamedLoc...

CountryNamedLocation

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CountryNamedLocation: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CountryNamedLocation: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ...

stack_v2_sparse_classes_10k_train_002337

3,404

permissive

[ { "docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: CountryNamedLocation", "name": "create_from_discriminator_value", "signature": "def create_from_discriminato...

3

null

Implement the Python class `CountryNamedLocation` described below. Class description: Implement the CountryNamedLocation class. Method signatures and docstrings: - def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CountryNamedLocation: Creates a new instance of the appropriate class based o...

27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949

<|skeleton|> class CountryNamedLocation: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CountryNamedLocation: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class CountryNamedLocation: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CountryNamedLocation: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns...

the_stack_v2_python_sparse

msgraph/generated/models/country_named_location.py

microsoftgraph/msgraph-sdk-python

train

135

7136d4ae62e2ae0b5068ec8bf798387d27d730c3

[ "ObjectManager.__init__(self)\nself.getters.update({'session_template': 'get_foreign_key', 'session_user_role': 'get_foreign_key', 'max': 'get_general', 'min': 'get_general'})\nself.setters.update({'session_template': 'set_foreign_key', 'session_user_role': 'set_foreign_key', 'max': 'set_general', 'min': 'set_gener...

<|body_start_0|> ObjectManager.__init__(self) self.getters.update({'session_template': 'get_foreign_key', 'session_user_role': 'get_foreign_key', 'max': 'get_general', 'min': 'get_general'}) self.setters.update({'session_template': 'set_foreign_key', 'session_user_role': 'set_foreign_key', 'max'...

Manage SessionTemplateUserRoleRequirements in the Power Reg system

SessionTemplateUserRoleRequirementManager

[ "BSD-2-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SessionTemplateUserRoleRequirementManager: """Manage SessionTemplateUserRoleRequirements in the Power Reg system""" def __init__(self): """constructor""" <|body_0|> def create(self, auth_token, session_template_id, session_user_role_id, min, max, credential_type_ids=None...

stack_v2_sparse_classes_10k_train_002338

2,528

permissive

[ { "docstring": "constructor", "name": "__init__", "signature": "def __init__(self)" }, { "docstring": "Create a new SessionTemplateUserRoleRequirement @param session_template_id Primary key for an session_template @param session_user_role_id Primary key for a session_user_role @param min Minimum...

2

stack_v2_sparse_classes_30k_train_003374

Implement the Python class `SessionTemplateUserRoleRequirementManager` described below. Class description: Manage SessionTemplateUserRoleRequirements in the Power Reg system Method signatures and docstrings: - def __init__(self): constructor - def create(self, auth_token, session_template_id, session_user_role_id, mi...

a59457bc37f0501aea1f54d006a6de94ff80511c

<|skeleton|> class SessionTemplateUserRoleRequirementManager: """Manage SessionTemplateUserRoleRequirements in the Power Reg system""" def __init__(self): """constructor""" <|body_0|> def create(self, auth_token, session_template_id, session_user_role_id, min, max, credential_type_ids=None...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class SessionTemplateUserRoleRequirementManager: """Manage SessionTemplateUserRoleRequirements in the Power Reg system""" def __init__(self): """constructor""" ObjectManager.__init__(self) self.getters.update({'session_template': 'get_foreign_key', 'session_user_role': 'get_foreign_key'...

the_stack_v2_python_sparse

pr_services/event_system/session_template_user_role_requirement_manager.py

ninemoreminutes/openassign-server

train

0

331641bf91c540417e5f07c2dfa9a22fe1589517

[ "self.hashMap = {}\nself.upper = N - len(blacklist)\nfor num in blacklist:\n self.hashMap[num] = -1\ni = N - 1\nfor num in blacklist:\n if num >= N - len(blacklist):\n continue\n while i in self.hashMap:\n i -= 1\n self.hashMap[num] = i\n i -= 1", "number = random.randint(0, self.uppe...

<|body_start_0|> self.hashMap = {} self.upper = N - len(blacklist) for num in blacklist: self.hashMap[num] = -1 i = N - 1 for num in blacklist: if num >= N - len(blacklist): continue while i in self.hashMap: i -=...

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def __init__(self, N, blacklist): """:type N: int :type blacklist: List[int]""" <|body_0|> def pick(self): """:rtype: int""" <|body_1|> <|end_skeleton|> <|body_start_0|> self.hashMap = {} self.upper = N - len(blacklist) for...

stack_v2_sparse_classes_10k_train_002339

1,765

no_license

[ { "docstring": ":type N: int :type blacklist: List[int]", "name": "__init__", "signature": "def __init__(self, N, blacklist)" }, { "docstring": ":rtype: int", "name": "pick", "signature": "def pick(self)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def __init__(self, N, blacklist): :type N: int :type blacklist: List[int] - def pick(self): :rtype: int

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def __init__(self, N, blacklist): :type N: int :type blacklist: List[int] - def pick(self): :rtype: int <|skeleton|> class Solution: def __init__(self, N, blacklist): ...

1d8821da01c9c200732a6b7037b8631689e2f7e7

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def __init__(self, N, blacklist): """:type N: int :type blacklist: List[int]""" self.hashMap = {} self.upper = N - len(blacklist) for num in blacklist: self.hashMap[num] = -1 i = N - 1 for num in blacklist: if num >= N - len(bla...

the_stack_v2_python_sparse

Leetcode0710.py

xiaojinghu/Leetcode

train

0

4ced799c2e6370ca55cc2a371541627f77ffaa3d

[ "ls = len(s)\nlp = len(p)\nif ls < lp or lp == 0:\n return []\ndic = dict()\nfor c in p:\n if c in dic:\n dic[c] += 1\n else:\n dic[c] = 1\nimport copy\nr = []\nfor i in range(0, ls - lp + 1):\n t = copy.deepcopy(dic)\n f = True\n for j in range(i, i + lp):\n if s[j] in t and ...

<|body_start_0|> ls = len(s) lp = len(p) if ls < lp or lp == 0: return [] dic = dict() for c in p: if c in dic: dic[c] += 1 else: dic[c] = 1 import copy r = [] for i in range(0, ls - lp + ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002340

1,779

no_license

[ { "docstring": ":type s: str :type p: str :rtype: List[int]", "name": "findAnagrams1", "signature": "def findAnagrams1(self, s, p)" }, { "docstring": ":type s: str :type p: str :rtype: List[int]", "name": "findAnagrams", "signature": "def findAnagrams(self, s, p)" } ]

2

stack_v2_sparse_classes_30k_train_005845

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def findAnagrams1(self, s, p): :type s: str :type p: str :rtype: List[int] - def findAnagrams(self, s, p): :type s: str :type p: str :rtype: List[int]

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def findAnagrams1(self, s, p): :type s: str :type p: str :rtype: List[int] - def findAnagrams(self, s, p): :type s: str :type p: str :rtype: List[int] <|skeleton|> class Solutio...

e5b018493bbd12edcdcd0434f35d9c358106d391

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def findAnagrams1(self, s, p): """:type s: str :type p: str :rtype: List[int]""" ls = len(s) lp = len(p) if ls < lp or lp == 0: return [] dic = dict() for c in p: if c in dic: dic[c] += 1 else: ...

the_stack_v2_python_sparse

py/leetcode/438.py

wfeng1991/learnpy

train

0

205cc4c2ace0f961ed950863bb236ffe9cfe5070

[ "polling_interval = kwargs.pop('_polling_interval', 5)\nsas_parameter = self._models.SASTokenParameter(storage_resource_uri=blob_storage_url, token=sas_token)\ncontinuation_token = kwargs.pop('continuation_token', None)\nstatus_response = None\nif continuation_token:\n status_url = base64.b64decode(continuation_...

<|body_start_0|> polling_interval = kwargs.pop('_polling_interval', 5) sas_parameter = self._models.SASTokenParameter(storage_resource_uri=blob_storage_url, token=sas_token) continuation_token = kwargs.pop('continuation_token', None) status_response = None if continuation_token: ...

Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or Managed HSM resource. See https://aka.ms/azsdk/blog/vault-uri for details. :param crede...

KeyVaultBackupClient

[ "LicenseRef-scancode-generic-cla", "MIT", "LGPL-2.1-or-later" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class KeyVaultBackupClient: """Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or Managed HSM resource. See https://aka.m...

stack_v2_sparse_classes_10k_train_002341

8,780

permissive

[ { "docstring": "Begin a full backup of the Key Vault. :param str blob_storage_url: URL of the blob storage container in which the backup will be stored, for example https://<account>.blob.core.windows.net/backup :param str sas_token: a Shared Access Signature (SAS) token authorizing access to the blob storage r...

2

stack_v2_sparse_classes_30k_train_003087

Implement the Python class `KeyVaultBackupClient` described below. Class description: Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or ...

c2ca191e736bb06bfbbbc9493e8325763ba990bb

<|skeleton|> class KeyVaultBackupClient: """Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or Managed HSM resource. See https://aka.m...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class KeyVaultBackupClient: """Performs Key Vault backup and restore operations. :param str vault_url: URL of the vault on which the client will operate. This is also called the vault's "DNS Name". You should validate that this URL references a valid Key Vault or Managed HSM resource. See https://aka.ms/azsdk/blog/...

the_stack_v2_python_sparse

sdk/keyvault/azure-keyvault-administration/azure/keyvault/administration/_backup_client.py

Azure/azure-sdk-for-python

train

4,046

35ce505d9abbc2926d4ea59da3b1b58ac65d3ac4

[ "bin_path = '/home/cephuser/venv/bin/'\nself.prefix = bin_path + 's3cmd'\nif options is None:\n options = []\nself.operation = operation\nself.options = ' '.join(options)", "if params is None:\n params = []\ncommand_list = [self.prefix, self.options, self.operation] + params\ncmd = list(filter(lambda cmd: l...

S3CMD

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class S3CMD: def __init__(self, operation, options=None): """Constructor for S3CMD class operation(str): S3CMD operation, E.g: ls, mb, etc... options(list): Optional options for the command""" <|body_0|> def command(self, params=None): """Args: params(list): list of params...

stack_v2_sparse_classes_10k_train_002342

1,012

permissive

[ { "docstring": "Constructor for S3CMD class operation(str): S3CMD operation, E.g: ls, mb, etc... options(list): Optional options for the command", "name": "__init__", "signature": "def __init__(self, operation, options=None)" }, { "docstring": "Args: params(list): list of params to be passed in ...

2

stack_v2_sparse_classes_30k_test_000340

Implement the Python class `S3CMD` described below. Class description: Implement the S3CMD class. Method signatures and docstrings: - def __init__(self, operation, options=None): Constructor for S3CMD class operation(str): S3CMD operation, E.g: ls, mb, etc... options(list): Optional options for the command - def comm...

4c3b9b3e8e7f42d43270a9b79299a8b404a76046

<|skeleton|> class S3CMD: def __init__(self, operation, options=None): """Constructor for S3CMD class operation(str): S3CMD operation, E.g: ls, mb, etc... options(list): Optional options for the command""" <|body_0|> def command(self, params=None): """Args: params(list): list of params...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class S3CMD: def __init__(self, operation, options=None): """Constructor for S3CMD class operation(str): S3CMD operation, E.g: ls, mb, etc... options(list): Optional options for the command""" bin_path = '/home/cephuser/venv/bin/' self.prefix = bin_path + 's3cmd' if options is None: ...

the_stack_v2_python_sparse

rgw/v2/lib/s3cmd/resource_op.py

red-hat-storage/ceph-qe-scripts

train

9

6f2301e3e6bd43e8a82926349a880ca4b23fdc3b

[ "mocker.patch.object(demisto, 'command', return_value='xdr-iocs-enable')\nmocker.patch.object(demisto, 'args', return_value={'indicator': '11.11.11.11'})\nmocker.patch('XDR_iocs.Client.http_request', return_value={})\noutputs = mocker.patch('XDR_iocs.return_outputs')\nenable_ioc = mocker.patch('XDR_iocs.prepare_ena...

<|body_start_0|> mocker.patch.object(demisto, 'command', return_value='xdr-iocs-enable') mocker.patch.object(demisto, 'args', return_value={'indicator': '11.11.11.11'}) mocker.patch('XDR_iocs.Client.http_request', return_value={}) outputs = mocker.patch('XDR_iocs.return_outputs') ...

TestIOCSCommand

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TestIOCSCommand: def test_iocs_command_with_enable(self, mocker): """Given: - enable command Then: - Verify enable command is called.""" <|body_0|> def test_iocs_command_with_disable(self, mocker): """Given: - disable command Then: - Verify disable command is called....

stack_v2_sparse_classes_10k_train_002343

41,271

permissive

[ { "docstring": "Given: - enable command Then: - Verify enable command is called.", "name": "test_iocs_command_with_enable", "signature": "def test_iocs_command_with_enable(self, mocker)" }, { "docstring": "Given: - disable command Then: - Verify disable command is called.", "name": "test_ioc...

2

stack_v2_sparse_classes_30k_train_001938

Implement the Python class `TestIOCSCommand` described below. Class description: Implement the TestIOCSCommand class. Method signatures and docstrings: - def test_iocs_command_with_enable(self, mocker): Given: - enable command Then: - Verify enable command is called. - def test_iocs_command_with_disable(self, mocker)...

890def5a0e0ae8d6eaa538148249ddbc851dbb6b

<|skeleton|> class TestIOCSCommand: def test_iocs_command_with_enable(self, mocker): """Given: - enable command Then: - Verify enable command is called.""" <|body_0|> def test_iocs_command_with_disable(self, mocker): """Given: - disable command Then: - Verify disable command is called....

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class TestIOCSCommand: def test_iocs_command_with_enable(self, mocker): """Given: - enable command Then: - Verify enable command is called.""" mocker.patch.object(demisto, 'command', return_value='xdr-iocs-enable') mocker.patch.object(demisto, 'args', return_value={'indicator': '11.11.11.11'...

the_stack_v2_python_sparse

Packs/CortexXDR/Integrations/XDR_iocs/XDR_iocs_test.py

demisto/content

train

1,023

e720d7ab130c3b9c9b948ceec477ecb80dabe8db

[ "diff = [g - c for g, c in zip(gas, cost)]\nif sum(diff) < 0:\n return -1\ntank = 0\nlength = len(gas)\nfor index in range(length):\n tmp_index = index\n while True:\n tank += gas[tmp_index]\n tank -= cost[tmp_index]\n if tank < 0:\n break\n tmp_index = (tmp_index + 1...

<|body_start_0|> diff = [g - c for g, c in zip(gas, cost)] if sum(diff) < 0: return -1 tank = 0 length = len(gas) for index in range(length): tmp_index = index while True: tank += gas[tmp_index] tank -= cost[tmp_...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002344

2,266

no_license

[ { "docstring": ":type gas: List[int] :type cost: List[int] :rtype: int", "name": "canCompleteCircuit", "signature": "def canCompleteCircuit(self, gas, cost)" }, { "docstring": ":type gas: List[int] :type cost: List[int] :rtype: int", "name": "canCompleteCircuit2", "signature": "def canCo...

2

stack_v2_sparse_classes_30k_train_003506

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def canCompleteCircuit(self, gas, cost): :type gas: List[int] :type cost: List[int] :rtype: int - def canCompleteCircuit2(self, gas, cost): :type gas: List[int] :type cost: List[...

a8b59573dc201438ebd5a5ab64e9ac61255a4abd

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def canCompleteCircuit(self, gas, cost): """:type gas: List[int] :type cost: List[int] :rtype: int""" diff = [g - c for g, c in zip(gas, cost)] if sum(diff) < 0: return -1 tank = 0 length = len(gas) for index in range(length): t...

the_stack_v2_python_sparse

summer/2018_07_21/gas-station.py

shaheming/leecode

train

0

838af8ab1f9b343943eea58f3354c3e2c5176188

[ "if n == 1:\n return 0\ndp = [0] * (n + 1)\ndp[2] = 1\nfor i in range(3, n + 1):\n if i % 2:\n dp[i] = min(dp[(i + 1) // 2], dp[(i - 1) // 2]) + 2\n else:\n dp[i] = dp[i // 2] + 1\nreturn dp[n]", "def help(n, mem):\n if n in mem:\n return mem[n]\n if n == 1:\n mem[n] = 0...

<|body_start_0|> if n == 1: return 0 dp = [0] * (n + 1) dp[2] = 1 for i in range(3, n + 1): if i % 2: dp[i] = min(dp[(i + 1) // 2], dp[(i - 1) // 2]) + 2 else: dp[i] = dp[i // 2] + 1 return dp[n] <|end_body_0|> ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002345

846

no_license

[ { "docstring": ":type n: int :rtype: int", "name": "integerReplacement1", "signature": "def integerReplacement1(self, n)" }, { "docstring": ":type n: int :rtype: int", "name": "integerReplacement", "signature": "def integerReplacement(self, n)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def integerReplacement1(self, n): :type n: int :rtype: int - def integerReplacement(self, n): :type n: int :rtype: int

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def integerReplacement1(self, n): :type n: int :rtype: int - def integerReplacement(self, n): :type n: int :rtype: int <|skeleton|> class Solution: def integerReplacement1(...

e5b018493bbd12edcdcd0434f35d9c358106d391

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def integerReplacement1(self, n): """:type n: int :rtype: int""" if n == 1: return 0 dp = [0] * (n + 1) dp[2] = 1 for i in range(3, n + 1): if i % 2: dp[i] = min(dp[(i + 1) // 2], dp[(i - 1) // 2]) + 2 else: ...

the_stack_v2_python_sparse

py/leetcode/397.py

wfeng1991/learnpy

train

0

6b50876f984fb071cf6dddc0a55b801ecd64dd7c

[ "size = 0\ncid = CustomID()\nuser: UserModel = self.current_user\nfn = os.path.join(upload_dir, str(cid.to_hex()))\nm = hashlib.blake2b()\npost = await self.post_data()\nfield: FileField = post.get('file', None)\nif not (field and isinstance(field, FileField)):\n return self.finish(RETCODE.INVALID_POSTDATA, '没有提...

<|body_start_0|> size = 0 cid = CustomID() user: UserModel = self.current_user fn = os.path.join(upload_dir, str(cid.to_hex())) m = hashlib.blake2b() post = await self.post_data() field: FileField = post.get('file', None) if not (field and isinstance(field...

UploadView

[ "Zlib" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002346

3,832

permissive

[ { "docstring": "上传图片随机文件名，上传至指定目录。完成后修改文件名为hash值 :return:", "name": "upload", "signature": "async def upload(self)" }, { "docstring": "获取七牛 token :return:", "name": "qn_token", "signature": "async def qn_token(self)" }, { "docstring": "七牛回调 :return:", "name": "qn_callback", ...

3

stack_v2_sparse_classes_30k_train_002884

Implement the Python class `UploadView` described below. Class description: Implement the UploadView class. Method signatures and docstrings: - async def upload(self): 上传图片随机文件名，上传至指定目录。完成后修改文件名为hash值 :return: - async def qn_token(self): 获取七牛 token :return: - async def qn_callback(self): 七牛回调 :return:

Implement the Python class `UploadView` described below. Class description: Implement the UploadView class. Method signatures and docstrings: - async def upload(self): 上传图片随机文件名，上传至指定目录。完成后修改文件名为hash值 :return: - async def qn_token(self): 获取七牛 token :return: - async def qn_callback(self): 七牛回调 :return: <|skeleton|> ...

c3a4af0f98693a08b850b47ff01091c4e884cc18

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class UploadView: async def upload(self): """上传图片随机文件名，上传至指定目录。完成后修改文件名为hash值 :return:""" size = 0 cid = CustomID() user: UserModel = self.current_user fn = os.path.join(upload_dir, str(cid.to_hex())) m = hashlib.blake2b() post = await self.post_data() ...

the_stack_v2_python_sparse

backend/api/upload.py

LiangTang1993/Icarus

train

1

ba1045b4a133fee2f842f1993b3470169335c839

[ "Parametre.__init__(self, 'hotboot', 'hotboot')\nself.aide_courte = 'permet de redémarrer les modules du MUD'\nself.aide_longue = \"Cette commande permet de redémarrer un ou plusieurs modules pendant l'exécution du MUD. Cela permet de corriger des bugs, intégrer des modifications, ajouter ou retirer des commandes s...

<|body_start_0|> Parametre.__init__(self, 'hotboot', 'hotboot') self.aide_courte = 'permet de redémarrer les modules du MUD' self.aide_longue = "Cette commande permet de redémarrer un ou plusieurs modules pendant l'exécution du MUD. Cela permet de corriger des bugs, intégrer des modifications, a...

Commande 'module hotboot'.

PrmHotboot

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002347

3,062

permissive

[ { "docstring": "Constructeur du paramètre", "name": "__init__", "signature": "def __init__(self)" }, { "docstring": "Interprétation du paramètre", "name": "interpreter", "signature": "def interpreter(self, personnage, dic_masques)" } ]

2

null

Implement the Python class `PrmHotboot` described below. Class description: Commande 'module hotboot'. Method signatures and docstrings: - def __init__(self): Constructeur du paramètre - def interpreter(self, personnage, dic_masques): Interprétation du paramètre

Implement the Python class `PrmHotboot` described below. Class description: Commande 'module hotboot'. Method signatures and docstrings: - def __init__(self): Constructeur du paramètre - def interpreter(self, personnage, dic_masques): Interprétation du paramètre <|skeleton|> class PrmHotboot: """Commande 'module...

7e93bff08cdf891352efba587e89c40f3b4a2301

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class PrmHotboot: """Commande 'module hotboot'.""" def __init__(self): """Constructeur du paramètre""" Parametre.__init__(self, 'hotboot', 'hotboot') self.aide_courte = 'permet de redémarrer les modules du MUD' self.aide_longue = "Cette commande permet de redémarrer un ou plusie...

the_stack_v2_python_sparse

src/primaires/joueur/commandes/module/hotboot.py

vincent-lg/tsunami

train

5

a7b47a5a44788ad09de86c3227d85f8ec52e2ce8

[ "super().__init__(*args, **kwargs)\nself.invite_only = invite_only\nself.show_invisible = show_invisible", "existing_groups: Iterable[Group]\ninput_value: Optional[str]\nif value:\n if not self.multivalued:\n value = [value]\n value = [v for v in value if v]\n input_value = ','.join((force_str(v) ...

A form widget allowing people to select one or more Group objects. This widget offers both the ability to see which groups are already in the list, as well as interactive search and filtering. Version Changed: 5.0.6: * Added an option for enabling specifying invisible review groups. * Added support for Python type hint...

RelatedGroupWidget

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class RelatedGroupWidget: """A form widget allowing people to select one or more Group objects. This widget offers both the ability to see which groups are already in the list, as well as interactive search and filtering. Version Changed: 5.0.6: * Added an option for enabling specifying invisible revie...

stack_v2_sparse_classes_10k_train_002348

16,804

permissive

[ { "docstring": "Initialize the RelatedGroupWidget. Version Changed: 5.0.6: Added the ``show_invisible`` argument. Args: invite_only (bool, optional): Whether or not to limit results to accessible review groups that are invite-only. show_invisible (bool, optional): Whether to include accessible invisible review ...

3

null

Implement the Python class `RelatedGroupWidget` described below. Class description: A form widget allowing people to select one or more Group objects. This widget offers both the ability to see which groups are already in the list, as well as interactive search and filtering. Version Changed: 5.0.6: * Added an option ...

c3a991f1e9d7682239a1ab0e8661cee6da01d537

<|skeleton|> class RelatedGroupWidget: """A form widget allowing people to select one or more Group objects. This widget offers both the ability to see which groups are already in the list, as well as interactive search and filtering. Version Changed: 5.0.6: * Added an option for enabling specifying invisible revie...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class RelatedGroupWidget: """A form widget allowing people to select one or more Group objects. This widget offers both the ability to see which groups are already in the list, as well as interactive search and filtering. Version Changed: 5.0.6: * Added an option for enabling specifying invisible review groups. * A...

the_stack_v2_python_sparse

reviewboard/admin/form_widgets.py

reviewboard/reviewboard

train

1,141

6fc4b746b192a737442735583c4009decb5234d3

[ "if not root:\n return '[]'\nres = []\nqueue = collections.deque()\nqueue.append(root)\nwhile queue:\n node = queue.popleft()\n if node:\n res.append(str(node.val))\n queue.append(node.left)\n queue.append(node.right)\n else:\n res.append('null')\nreturn '[' + ','.join(res) +...

<|body_start_0|> if not root: return '[]' res = [] queue = collections.deque() queue.append(root) while queue: node = queue.popleft() if node: res.append(str(node.val)) queue.append(node.left) que...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002349

2,245

no_license

[ { "docstring": "类似于面试题32 :param root: 传入一棵树 :return: 返回字符串", "name": "serialize", "signature": "def serialize(self, root)" }, { "docstring": ":param data: 是一个字符串 :return: 返回一棵树", "name": "deserialize", "signature": "def deserialize(self, data)" } ]

2

stack_v2_sparse_classes_30k_train_005602

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def serialize(self, root): 类似于面试题32 :param root: 传入一棵树 :return: 返回字符串 - def deserialize(self, data): :param data: 是一个字符串 :return: 返回一棵树

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def serialize(self, root): 类似于面试题32 :param root: 传入一棵树 :return: 返回字符串 - def deserialize(self, data): :param data: 是一个字符串 :return: 返回一棵树 <|skeleton|> class Solution: def ser...

f1bbd6b3197cd9ac4f0d35a37539c11b02272065

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def serialize(self, root): """类似于面试题32 :param root: 传入一棵树 :return: 返回字符串""" if not root: return '[]' res = [] queue = collections.deque() queue.append(root) while queue: node = queue.popleft() if node: ...

the_stack_v2_python_sparse

offer/树/37. 序列化二叉树/Codec.py

guohaoyuan/algorithms-for-work

train

2

2fae4983fba0c3f1e6384fa52990e36b107925d8

[ "self.char = ''\nself.d = {}\nself.end = False", "c, n = (word[0], len(word))\nnode = self.d.get(c)\nif not node:\n self.d[c] = Trie()\n self.d[c].char = c\n node = self.d[c]\nif n == 1:\n node.end = True\nelse:\n node.insert(word[1:])", "node = self\nfor c in word:\n node = node.d.get(c)\n ...

<|body_start_0|> self.char = '' self.d = {} self.end = False <|end_body_0|> <|body_start_1|> c, n = (word[0], len(word)) node = self.d.get(c) if not node: self.d[c] = Trie() self.d[c].char = c node = self.d[c] if n == 1: ...

Trie

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002350

1,311

no_license

[ { "docstring": "Initialize your data structure here.", "name": "__init__", "signature": "def __init__(self)" }, { "docstring": "Inserts a word into the trie.", "name": "insert", "signature": "def insert(self, word: str) -> None" }, { "docstring": "Returns if the word is in the tr...

4

stack_v2_sparse_classes_30k_train_003482

Implement the Python class `Trie` described below. Class description: Implement the Trie class. Method signatures and docstrings: - def __init__(self): Initialize your data structure here. - def insert(self, word: str) -> None: Inserts a word into the trie. - def search(self, word: str) -> bool: Returns if the word i...

12f62a218e827e6be2578b206dee9ce256da8d3d

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Trie: def __init__(self): """Initialize your data structure here.""" self.char = '' self.d = {} self.end = False def insert(self, word: str) -> None: """Inserts a word into the trie.""" c, n = (word[0], len(word)) node = self.d.get(c) if not...

the_stack_v2_python_sparse

Python3/0208_Implement_Trie.py

kiranani/playground

train

0

c793207626c423bbf2cc159ffc8d8a5e88c08c86

[ "super(RateConverter, self).__init__(id=id)\nself.base_currency = base_currency\nself.user = user\nself.key = key", "errors = super(RateConverter, self).add_data(data)\nself.cache_currencies()\nreturn errors", "from .serializers import RateAmountSerializer\nerrors = []\nfor line in data:\n serializer = RateA...

Converter of rates

RateConverter

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class RateConverter: """Converter of rates""" def __init__(self, user: User, id: str=None, key: str=None, base_currency: str=settings.BASE_CURRENCY): """Initialize :param user: Django User :param key: key for user :param base_currency: destination currency""" <|body_0|> def ad...

stack_v2_sparse_classes_10k_train_002351

16,208

permissive

[ { "docstring": "Initialize :param user: Django User :param key: key for user :param base_currency: destination currency", "name": "__init__", "signature": "def __init__(self, user: User, id: str=None, key: str=None, base_currency: str=settings.BASE_CURRENCY)" }, { "docstring": "Check data and ad...

5

stack_v2_sparse_classes_30k_train_007098

Implement the Python class `RateConverter` described below. Class description: Converter of rates Method signatures and docstrings: - def __init__(self, user: User, id: str=None, key: str=None, base_currency: str=settings.BASE_CURRENCY): Initialize :param user: Django User :param key: key for user :param base_currenc...

23cc075377d47ac631634cd71fd0e7d6b0a57bad

<|skeleton|> class RateConverter: """Converter of rates""" def __init__(self, user: User, id: str=None, key: str=None, base_currency: str=settings.BASE_CURRENCY): """Initialize :param user: Django User :param key: key for user :param base_currency: destination currency""" <|body_0|> def ad...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class RateConverter: """Converter of rates""" def __init__(self, user: User, id: str=None, key: str=None, base_currency: str=settings.BASE_CURRENCY): """Initialize :param user: Django User :param key: key for user :param base_currency: destination currency""" super(RateConverter, self).__init__...

the_stack_v2_python_sparse

src/geocurrency/rates/models.py

fmeurou/geocurrency

train

5

122c588d57997f9321217bfeded4ff5641c1fb71

[ "rospy.init_node('mapper')\nself._map = Map()\nrospy.Subscriber('scan', LaserScan, self.scan_callback, queue_size=1)\nself._map_pub = rospy.Publisher('map', OccupancyGrid, latch=True)\nself._map_data_pub = rospy.Publisher('map_metadata', MapMetaData, latch=True)\nrospy.spin()", "self._map.grid[0, 0] = 1.0\nself._...

<|body_start_0|> rospy.init_node('mapper') self._map = Map() rospy.Subscriber('scan', LaserScan, self.scan_callback, queue_size=1) self._map_pub = rospy.Publisher('map', OccupancyGrid, latch=True) self._map_data_pub = rospy.Publisher('map_metadata', MapMetaData, latch=True) ...

The Mapper class creates a map from laser scan data.

Mapper

[ "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002352

5,549

permissive

[ { "docstring": "Start the mapper.", "name": "__init__", "signature": "def __init__(self)" }, { "docstring": "Update the map on every scan callback.", "name": "scan_callback", "signature": "def scan_callback(self, scan)" }, { "docstring": "Publish the map.", "name": "publish_m...

3

stack_v2_sparse_classes_30k_train_000248

Implement the Python class `Mapper` described below. Class description: The Mapper class creates a map from laser scan data. Method signatures and docstrings: - def __init__(self): Start the mapper. - def scan_callback(self, scan): Update the map on every scan callback. - def publish_map(self): Publish the map.

Implement the Python class `Mapper` described below. Class description: The Mapper class creates a map from laser scan data. Method signatures and docstrings: - def __init__(self): Start the mapper. - def scan_callback(self, scan): Update the map on every scan callback. - def publish_map(self): Publish the map. <|sk...

43387024c313e40596dd49f1686d2bb1e7f7e319

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Mapper: """The Mapper class creates a map from laser scan data.""" def __init__(self): """Start the mapper.""" rospy.init_node('mapper') self._map = Map() rospy.Subscriber('scan', LaserScan, self.scan_callback, queue_size=1) self._map_pub = rospy.Publisher('map', O...

the_stack_v2_python_sparse

crazyflie_demo/scripts/mapping/mapper.py

GalBrandwine/crazyflie_ros

train

3

b376105dc380f41b6006b1a698b0c4a0f93540f6

[ "self.config = self.trainer.config\nif vega.is_npu_device():\n count_input = torch.FloatTensor(1, 3, 1024, 1024).npu()\nelse:\n count_input = torch.FloatTensor(1, 3, 1024, 1024).cuda()\nflops_count, params_count = calc_model_flops_params(self.trainer.model, count_input)\nself.flops_count, self.params_count = ...

<|body_start_0|> self.config = self.trainer.config if vega.is_npu_device(): count_input = torch.FloatTensor(1, 3, 1024, 1024).npu() else: count_input = torch.FloatTensor(1, 3, 1024, 1024).cuda() flops_count, params_count = calc_model_flops_params(self.trainer.mode...

Construct the trainer of Adelaide-EA.

SegmentationEATrainerCallback

[ "LicenseRef-scancode-unknown-license-reference", "Apache-2.0", "BSD-3-Clause", "MIT" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002353

1,941

permissive

[ { "docstring": "Be called before the training process.", "name": "before_train", "signature": "def before_train(self, logs=None)" }, { "docstring": "Update flops and params.", "name": "after_epoch", "signature": "def after_epoch(self, epoch, logs=None)" } ]

2

null

Implement the Python class `SegmentationEATrainerCallback` described below. Class description: Construct the trainer of Adelaide-EA. Method signatures and docstrings: - def before_train(self, logs=None): Be called before the training process. - def after_epoch(self, epoch, logs=None): Update flops and params.

Implement the Python class `SegmentationEATrainerCallback` described below. Class description: Construct the trainer of Adelaide-EA. Method signatures and docstrings: - def before_train(self, logs=None): Be called before the training process. - def after_epoch(self, epoch, logs=None): Update flops and params. <|skel...

12e37a1991eb6771a2999fe0a46ddda920c47948

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class SegmentationEATrainerCallback: """Construct the trainer of Adelaide-EA.""" def before_train(self, logs=None): """Be called before the training process.""" self.config = self.trainer.config if vega.is_npu_device(): count_input = torch.FloatTensor(1, 3, 1024, 1024).npu()...

the_stack_v2_python_sparse

vega/algorithms/nas/segmentation_ea/segmentation_ea_trainercallback.py

huawei-noah/vega

train

850

983c79f1d8e645ce3e9c205ccef45fdd7d09fc6c

[ "assert features.is_contiguous()\nassert idx.is_contiguous()\nassert weight.is_contiguous()\nm, c = features.size()\nn = idx.size(0)\nctx.three_interpolate_for_backward = (idx, weight, m)\noutput = torch.cuda.FloatTensor(n, c)\nsparse_interpolate_ext.three_interpolate_wrapper(c, m, n, features, idx, weight, output)...

<|body_start_0|> assert features.is_contiguous() assert idx.is_contiguous() assert weight.is_contiguous() m, c = features.size() n = idx.size(0) ctx.three_interpolate_for_backward = (idx, weight, m) output = torch.cuda.FloatTensor(n, c) sparse_interpolate_...

SparseThreeInterpolate

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SparseThreeInterpolate: def forward(ctx, features: torch.Tensor, idx: torch.Tensor, weight: torch.Tensor) -> torch.Tensor: """Performs weight linear interpolation on 3 features :param ctx: :param features: (M, C) Features descriptors to be interpolated from :param idx: (n, 3) three neare...

stack_v2_sparse_classes_10k_train_002354

3,814

permissive

[ { "docstring": "Performs weight linear interpolation on 3 features :param ctx: :param features: (M, C) Features descriptors to be interpolated from :param idx: (n, 3) three nearest neighbors of the target features in features :param weight: (n, 3) weights :return: output: (N, C) tensor of the interpolated featu...

2

stack_v2_sparse_classes_30k_train_001998

Implement the Python class `SparseThreeInterpolate` described below. Class description: Implement the SparseThreeInterpolate class. Method signatures and docstrings: - def forward(ctx, features: torch.Tensor, idx: torch.Tensor, weight: torch.Tensor) -> torch.Tensor: Performs weight linear interpolation on 3 features ...

9987806185a4e1619bc15ceecb8a1755e764ff68

<|skeleton|> class SparseThreeInterpolate: def forward(ctx, features: torch.Tensor, idx: torch.Tensor, weight: torch.Tensor) -> torch.Tensor: """Performs weight linear interpolation on 3 features :param ctx: :param features: (M, C) Features descriptors to be interpolated from :param idx: (n, 3) three neare...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class SparseThreeInterpolate: def forward(ctx, features: torch.Tensor, idx: torch.Tensor, weight: torch.Tensor) -> torch.Tensor: """Performs weight linear interpolation on 3 features :param ctx: :param features: (M, C) Features descriptors to be interpolated from :param idx: (n, 3) three nearest neighbors o...

the_stack_v2_python_sparse

gorilla3d/ops/sparse_interpolate/sparse_interpolate.py

SijanNeupane49/gorilla-3d

train

0

79c6fd96ee3fa40e17e393494783294e2869252f

[ "if not any(values.values()):\n values['eia860'] = Eia860Settings()\n values['eia861'] = Eia861Settings()\n values['eia923'] = Eia923Settings()\nreturn values", "eia923 = values.get('eia923')\neia860 = values.get('eia860')\nif not eia923 and eia860:\n values['eia923'] = Eia923Settings(years=eia860.yea...

An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings.

EiaSettings

[ "CC-BY-4.0", "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class EiaSettings: """An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings.""" def default_load_all(cls, values): """If no datasets are specified defau...

stack_v2_sparse_classes_10k_train_002355

24,804

permissive

[ { "docstring": "If no datasets are specified default to all. Args: values (Dict[str, BaseModel]): dataset settings. Returns: values (Dict[str, BaseModel]): dataset settings.", "name": "default_load_all", "signature": "def default_load_all(cls, values)" }, { "docstring": "Make sure the dependenci...

2

stack_v2_sparse_classes_30k_train_002863

Implement the Python class `EiaSettings` described below. Class description: An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings. Method signatures and docstrings: - def default_...

6afae8aade053408f23ac4332d5cbb438ab72dc6

<|skeleton|> class EiaSettings: """An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings.""" def default_load_all(cls, values): """If no datasets are specified defau...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class EiaSettings: """An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings.""" def default_load_all(cls, values): """If no datasets are specified default to all. Ar...

the_stack_v2_python_sparse

src/pudl/settings.py

catalyst-cooperative/pudl

train

382

09708350bf3d70b4c8c284e8cb9f8ec62cbe963e

[ "if len(nums) < 3:\n return 0\nfirstBiggest, secondBiggest, thirdBiggest = (float('-inf'), float('-inf'), float('-inf'))\nfirstSmallest, secondSmallest = (float('-inf'), float('-inf'))\nC = Counter(nums)\nfirstBiggest = max(C)\nC[firstBiggest] -= 1\nif not C[firstBiggest]:\n del C[firstBiggest]\nsecondBiggest...

<|body_start_0|> if len(nums) < 3: return 0 firstBiggest, secondBiggest, thirdBiggest = (float('-inf'), float('-inf'), float('-inf')) firstSmallest, secondSmallest = (float('-inf'), float('-inf')) C = Counter(nums) firstBiggest = max(C) C[firstBiggest] -= 1 ...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002356

1,631

no_license

[ { "docstring": ":type nums: List[int] :rtype: int", "name": "maximumProduct", "signature": "def maximumProduct(self, nums)" }, { "docstring": ":type nums: List[int] :rtype: int", "name": "maximumProductFirstSolution", "signature": "def maximumProductFirstSolution(self, nums)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def maximumProduct(self, nums): :type nums: List[int] :rtype: int - def maximumProductFirstSolution(self, nums): :type nums: List[int] :rtype: int

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def maximumProduct(self, nums): :type nums: List[int] :rtype: int - def maximumProductFirstSolution(self, nums): :type nums: List[int] :rtype: int <|skeleton|> class Solution: ...

25e5caf324e25edfdf0a7a3be1e572f5d4c88837

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def maximumProduct(self, nums): """:type nums: List[int] :rtype: int""" if len(nums) < 3: return 0 firstBiggest, secondBiggest, thirdBiggest = (float('-inf'), float('-inf'), float('-inf')) firstSmallest, secondSmallest = (float('-inf'), float('-inf')) ...

the_stack_v2_python_sparse

Arrays/maximum_product_of_three_numbers.py

msraju2009/CodingProblemsPractice

train

0

e6f3b3cfe120ccaa761d3edfa1f2339c4c5846b2

[ "try:\n self.__genre = 'review'\n self.__task_elements_dict = {'priority': self.task.priority, 'level': self.task.level, 'last_updated_time': datetime.strftime(datetime.utcnow(), '%Y-%m-%dT%H:%M:%SZ'), 'pickup_date': datetime.strftime(datetime.utcnow(), '%Y-%m-%dT%H:%M:%SZ'), 'connector_instance_log_id': self...

<|body_start_0|> try: self.__genre = 'review' self.__task_elements_dict = {'priority': self.task.priority, 'level': self.task.level, 'last_updated_time': datetime.strftime(datetime.utcnow(), '%Y-%m-%dT%H:%M:%SZ'), 'pickup_date': datetime.strftime(datetime.utcnow(), '%Y-%m-%dT%H:%M:%SZ'),...

This will fetch the info for Sample uris is http://www.customerservicescoreboard.com/Bank+of+America

CustomerServiceScoreBoardConnector

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CustomerServiceScoreBoardConnector: """This will fetch the info for Sample uris is http://www.customerservicescoreboard.com/Bank+of+America""" def fetch(self): """Fetch of customerservicescoreboard.com""" <|body_0|> def __iteratePosts(self): """It will Iterate Ov...

stack_v2_sparse_classes_10k_train_002357

7,675

no_license

[ { "docstring": "Fetch of customerservicescoreboard.com", "name": "fetch", "signature": "def fetch(self)" }, { "docstring": "It will Iterate Over the links found in the Current URI", "name": "__iteratePosts", "signature": "def __iteratePosts(self)" }, { "docstring": "This will tak...

5

stack_v2_sparse_classes_30k_train_007234

Implement the Python class `CustomerServiceScoreBoardConnector` described below. Class description: This will fetch the info for Sample uris is http://www.customerservicescoreboard.com/Bank+of+America Method signatures and docstrings: - def fetch(self): Fetch of customerservicescoreboard.com - def __iteratePosts(self...

dbd14efb81b28be6340dfd00df9d31cc6a290b08

<|skeleton|> class CustomerServiceScoreBoardConnector: """This will fetch the info for Sample uris is http://www.customerservicescoreboard.com/Bank+of+America""" def fetch(self): """Fetch of customerservicescoreboard.com""" <|body_0|> def __iteratePosts(self): """It will Iterate Ov...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class CustomerServiceScoreBoardConnector: """This will fetch the info for Sample uris is http://www.customerservicescoreboard.com/Bank+of+America""" def fetch(self): """Fetch of customerservicescoreboard.com""" try: self.__genre = 'review' self.__task_elements_dict = {'p...

the_stack_v2_python_sparse

crawler/connectors/customerservicescoreboardconnector.py

jsyadav/CrawlerFramework

train

1

3381a9138c5525d1bf3a77d35b79f4586eafc6b8

[ "startTime = datetime.datetime.now()\nif trial:\n endTime = datetime.datetime.now()\n return {'start': startTime, 'end': endTime}\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate(TEAM_NAME, TEAM_NAME)\ndocument = repo[DEMOGRAPHIC_DATA_COUNTY_NAME].find_one()\nkeys = []\nfor key in do...

<|body_start_0|> startTime = datetime.datetime.now() if trial: endTime = datetime.datetime.now() return {'start': startTime, 'end': endTime} client = dml.pymongo.MongoClient() repo = client.repo repo.authenticate(TEAM_NAME, TEAM_NAME) document = re...

transformationSummaryMetrics

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class transformationSummaryMetrics: def execute(trial=False): """Retrieve summary demographic data for all facts by county and town and insert into collection ex) {'Fact': 'Population estimates, July 1, 2017, (V2017)', 'Town_Min': 'Middleton town, Essex County, Massachusetts', 'Town_Min_Val': ...

stack_v2_sparse_classes_10k_train_002358

7,267

no_license

[ { "docstring": "Retrieve summary demographic data for all facts by county and town and insert into collection ex) {'Fact': 'Population estimates, July 1, 2017, (V2017)', 'Town_Min': 'Middleton town, Essex County, Massachusetts', 'Town_Min_Val': '9,861', 'Town_Max': 'Littleton town, Middlesex County, Massachuset...

2

stack_v2_sparse_classes_30k_train_005701

Implement the Python class `transformationSummaryMetrics` described below. Class description: Implement the transformationSummaryMetrics class. Method signatures and docstrings: - def execute(trial=False): Retrieve summary demographic data for all facts by county and town and insert into collection ex) {'Fact': 'Popu...

90284cf3debbac36eead07b8d2339cdd191b86cf

<|skeleton|> class transformationSummaryMetrics: def execute(trial=False): """Retrieve summary demographic data for all facts by county and town and insert into collection ex) {'Fact': 'Population estimates, July 1, 2017, (V2017)', 'Town_Min': 'Middleton town, Essex County, Massachusetts', 'Town_Min_Val': ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class transformationSummaryMetrics: def execute(trial=False): """Retrieve summary demographic data for all facts by county and town and insert into collection ex) {'Fact': 'Population estimates, July 1, 2017, (V2017)', 'Town_Min': 'Middleton town, Essex County, Massachusetts', 'Town_Min_Val': '9,861', 'Town...

the_stack_v2_python_sparse

ldisalvo_skeesara_vidyaap/transformationSummaryMetrics.py

maximega/course-2019-spr-proj

train

2

6100f1a09996674b67a958a7026ada368ae699fb

[ "nn.Module.__init__(self)\nself.P = P\nself.nu = nu\nself.eps = eps", "dist = torch.sum((input - torch.matmul(self.P, input.transpose(0, 1)).transpose(0, 1)) ** 2, dim=1)\nif self.soft_boundary:\n scores = dist - R ** 2\n loss = R ** 2 + 1 / self.nu * torch.mean(torch.max(torch.zeros_like(scores), scores))\...

Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019) but with the distance of the point projected to the subspace of training samples rather than the hypersphere. It follows the mathematical derivation proposed by Arnout Devos et al. (2019).

DeepSVDDLossSubspace

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class DeepSVDDLossSubspace: """Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019) but with the distance of the point projected to the subspace of training samples rather than the hypersphere. It follows the mathematical derivation proposed by Arnout Devos et al. (2019).""" de...

stack_v2_sparse_classes_10k_train_002359

18,386

permissive

[ { "docstring": "Constructor of the DeepSVDD loss Subspace. ---------- INPUT |---- P (torch.Tensor) The projection matrix to the subspace of normal | sample. P is a MxM matrix where M is the embedding dimension. |---- nu (float) a priory fraction of outliers. |---- eps (float) epsilon to ensure numerical stabili...

2

stack_v2_sparse_classes_30k_train_002904

Implement the Python class `DeepSVDDLossSubspace` described below. Class description: Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019) but with the distance of the point projected to the subspace of training samples rather than the hypersphere. It follows the mathematical derivation proposed by...

850b6195d6290a50eee865b4d5a66f5db5260e8f

<|skeleton|> class DeepSVDDLossSubspace: """Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019) but with the distance of the point projected to the subspace of training samples rather than the hypersphere. It follows the mathematical derivation proposed by Arnout Devos et al. (2019).""" de...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class DeepSVDDLossSubspace: """Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019) but with the distance of the point projected to the subspace of training samples rather than the hypersphere. It follows the mathematical derivation proposed by Arnout Devos et al. (2019).""" def __init__(se...

the_stack_v2_python_sparse

Code/src/models/optim/CustomLosses.py

antoine-spahr/X-ray-Anomaly-Detection

train

3

dc32d9e620f1bec5cb404a7ce702f4b26d02de5e

[ "self.job_id = job_id\nself.cloud_target_type = cloud_target_type\nself.expiry_time_usecs = expiry_time_usecs\nself.target_id = target_id\nself.target_name = target_name\nself.total_snapshots = total_snapshots\nself.mtype = mtype", "if dictionary is None:\n return None\njob_id = dictionary.get('JobId')\ncloud_...

<|body_start_0|> self.job_id = job_id self.cloud_target_type = cloud_target_type self.expiry_time_usecs = expiry_time_usecs self.target_id = target_id self.target_name = target_name self.total_snapshots = total_snapshots self.mtype = mtype <|end_body_0|> <|body_s...

Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type (string): Specifies the cloud deploy target type. For example 'kAzure','kAWS', ...

GdprCopyTask

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class GdprCopyTask: """Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type (string): Specifies the cloud deploy ta...

stack_v2_sparse_classes_10k_train_002360

3,218

permissive

[ { "docstring": "Constructor for the GdprCopyTask class", "name": "__init__", "signature": "def __init__(self, job_id=None, cloud_target_type=None, expiry_time_usecs=None, target_id=None, target_name=None, total_snapshots=None, mtype=None)" }, { "docstring": "Creates an instance of this model fro...

2

stack_v2_sparse_classes_30k_train_001191

Implement the Python class `GdprCopyTask` described below. Class description: Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type ...

e4973dfeb836266904d0369ea845513c7acf261e

<|skeleton|> class GdprCopyTask: """Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type (string): Specifies the cloud deploy ta...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class GdprCopyTask: """Implementation of the 'GdprCopyTask' model. CopyTask defines the copy tasks of a job. Attributes: job_id (long|int): Specifies the job with which this copy task is tied to. Note: this is only used for internal aggregation. cloud_target_type (string): Specifies the cloud deploy target type. Fo...

the_stack_v2_python_sparse

cohesity_management_sdk/models/gdpr_copy_task.py

cohesity/management-sdk-python

train

24

e9b6bf2dd1eb7ddd3c48b9f328ed2be0afecd239

[ "queryset = self.filter_queryset(self.get_queryset())\nuid = force_text(urlsafe_base64_decode(self.kwargs['uid']))\ntoken = self.kwargs['token']\nobj = get_object_or_404(queryset, pk=uid)\nself.check_object_permissions(self.request, obj)\nif not default_token_generator.check_token(user=obj, token=token):\n raise...

<|body_start_0|> queryset = self.filter_queryset(self.get_queryset()) uid = force_text(urlsafe_base64_decode(self.kwargs['uid'])) token = self.kwargs['token'] obj = get_object_or_404(queryset, pk=uid) self.check_object_permissions(self.request, obj) if not default_token_g...

User activate view.

UserActivation

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class UserActivation: """User activate view.""" def get_object(self) -> User: """Get user by uid and check permissions. :return: User.""" <|body_0|> def get(self, request: Request, *args: tuple, **kwargs: dict) -> Response: """Activate user. :param request: :return:"""...

stack_v2_sparse_classes_10k_train_002361

5,061

no_license

[ { "docstring": "Get user by uid and check permissions. :return: User.", "name": "get_object", "signature": "def get_object(self) -> User" }, { "docstring": "Activate user. :param request: :return:", "name": "get", "signature": "def get(self, request: Request, *args: tuple, **kwargs: dict...

2

stack_v2_sparse_classes_30k_train_002270

Implement the Python class `UserActivation` described below. Class description: User activate view. Method signatures and docstrings: - def get_object(self) -> User: Get user by uid and check permissions. :return: User. - def get(self, request: Request, *args: tuple, **kwargs: dict) -> Response: Activate user. :param...

713b9d84ac70d964d46f189ab1f9c7b944b9684b

<|skeleton|> class UserActivation: """User activate view.""" def get_object(self) -> User: """Get user by uid and check permissions. :return: User.""" <|body_0|> def get(self, request: Request, *args: tuple, **kwargs: dict) -> Response: """Activate user. :param request: :return:"""...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class UserActivation: """User activate view.""" def get_object(self) -> User: """Get user by uid and check permissions. :return: User.""" queryset = self.filter_queryset(self.get_queryset()) uid = force_text(urlsafe_base64_decode(self.kwargs['uid'])) token = self.kwargs['token']...

the_stack_v2_python_sparse

jobadvisor/users/views/registration.py

ewgen19892/jobadvisor

train

0

6be363362f51f0d889ac06917a9e911ed094a888

[ "if isinstance(obj, str):\n raise NotImplementedError\nself.converter = obj\nself.N = N\nself.results = None\nself.include_dummy = False\nif to_exclude is None:\n self.to_exclude = []\nelse:\n self.to_exclude = to_exclude\nif to_include is None:\n self.to_include = []\nelse:\n self.to_include = to_in...

<|body_start_0|> if isinstance(obj, str): raise NotImplementedError self.converter = obj self.N = N self.results = None self.include_dummy = False if to_exclude is None: self.to_exclude = [] else: self.to_exclude = to_exclude ...

Convenient class to benchmark several methods for a given converter :: c = Bam2Bed(infile, outfile) b = Benchmark(c, N=5) b.run_methods() b.plot()

Benchmark

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Benchmark: """Convenient class to benchmark several methods for a given converter :: c = Bam2Bed(infile, outfile) b = Benchmark(c, N=5) b.run_methods() b.plot()""" def __init__(self, obj, N=5, to_exclude=None, to_include=None): """.. rubric:: constructor :param obj: can be an instanc...

stack_v2_sparse_classes_10k_train_002362

6,414

permissive

[ { "docstring": ".. rubric:: constructor :param obj: can be an instance of a converter class or a class name :param int N: number of replicates :param list to_exclude: methods to exclude from the benchmark :param list to_include: methods to include ONLY Use one of to_exclude or to_include. If both are provided, ...

3

stack_v2_sparse_classes_30k_train_006901

Implement the Python class `Benchmark` described below. Class description: Convenient class to benchmark several methods for a given converter :: c = Bam2Bed(infile, outfile) b = Benchmark(c, N=5) b.run_methods() b.plot() Method signatures and docstrings: - def __init__(self, obj, N=5, to_exclude=None, to_include=Non...

60a746290e763fd1041732dab0bda123841e5b26

<|skeleton|> class Benchmark: """Convenient class to benchmark several methods for a given converter :: c = Bam2Bed(infile, outfile) b = Benchmark(c, N=5) b.run_methods() b.plot()""" def __init__(self, obj, N=5, to_exclude=None, to_include=None): """.. rubric:: constructor :param obj: can be an instanc...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Benchmark: """Convenient class to benchmark several methods for a given converter :: c = Bam2Bed(infile, outfile) b = Benchmark(c, N=5) b.run_methods() b.plot()""" def __init__(self, obj, N=5, to_exclude=None, to_include=None): """.. rubric:: constructor :param obj: can be an instance of a conver...

the_stack_v2_python_sparse

bioconvert/core/benchmark.py

ddesvillechabrol/bioconvert

train

1

3d2c1538dd30697dabbc21cbf9d9835334a7d8aa

[ "soup = bs(response.text, 'html.parser')\npage_div = soup.find('div', class_='col-md-2 col-xs-3 text-right')\nself.max_page = int(page_div.select('a')[-1].get('href').split('/')[-1]) if page_div.select('a')[-1] else 0\nyield scrapy.Request(response.url, callback=self.parse_get_next_page)", "soup = bs(response.tex...

<|body_start_0|> soup = bs(response.text, 'html.parser') page_div = soup.find('div', class_='col-md-2 col-xs-3 text-right') self.max_page = int(page_div.select('a')[-1].get('href').split('/')[-1]) if page_div.select('a')[-1] else 0 yield scrapy.Request(response.url, callback=self.parse_g...

dprSpider

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002363

4,942

no_license

[ { "docstring": ":param response: :return: 最大页码数", "name": "parse", "signature": "def parse(self, response)" }, { "docstring": ":param response: :return:一级目录链接", "name": "parse_get_next_page", "signature": "def parse_get_next_page(self, response)" }, { "docstring": ":param respons...

3

stack_v2_sparse_classes_30k_test_000193

Implement the Python class `dprSpider` described below. Class description: Implement the dprSpider class. Method signatures and docstrings: - def parse(self, response): :param response: :return: 最大页码数 - def parse_get_next_page(self, response): :param response: :return:一级目录链接 - def get_news_detail(self, response): :pa...

1bcb03a48aff1ebca4e04a5c060be299ca9881d4

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class dprSpider: def parse(self, response): """:param response: :return: 最大页码数""" soup = bs(response.text, 'html.parser') page_div = soup.find('div', class_='col-md-2 col-xs-3 text-right') self.max_page = int(page_div.select('a')[-1].get('href').split('/')[-1]) if page_div.select('a'...

the_stack_v2_python_sparse

crawler/v1/dprgoid.py

AMAtreus/dg_crawler_website

train

0

340ca5d86442dc63c1c4bb8325f9e14a4238ffd1

[ "ROWS = len(A)\nCOLS = len(A[0])\ngrid = [[0 for _ in range(COLS)] for _ in range(2)]\nfor i in range(ROWS - 1, -1, -1):\n for j in range(COLS):\n if i == ROWS - 1:\n grid[i & 1][j] = A[i][j]\n else:\n grid[i & 1][j] = grid[i + 1 & 1][j]\n if j + 1 < COLS:\n ...

<|body_start_0|> ROWS = len(A) COLS = len(A[0]) grid = [[0 for _ in range(COLS)] for _ in range(2)] for i in range(ROWS - 1, -1, -1): for j in range(COLS): if i == ROWS - 1: grid[i & 1][j] = A[i][j] else: ...

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def minFallingPathSumBackwardDP(self, A: List[List[int]]) -> int: """Just save the min falling path (i, j) -> minimum value start from bottom row as base case, build next layer above based on bottom row.""" <|body_0|> def minFallingPathSum(self, A: List[List[int]])...

stack_v2_sparse_classes_10k_train_002364

3,215

no_license

[ { "docstring": "Just save the min falling path (i, j) -> minimum value start from bottom row as base case, build next layer above based on bottom row.", "name": "minFallingPathSumBackwardDP", "signature": "def minFallingPathSumBackwardDP(self, A: List[List[int]]) -> int" }, { "docstring": "Just ...

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def minFallingPathSumBackwardDP(self, A: List[List[int]]) -> int: Just save the min falling path (i, j) -> minimum value start from bottom row as base case, build next layer abov...

483f0c93faca8ccaf038b77ebe2fa712f6b0c6bc

<|skeleton|> class Solution: def minFallingPathSumBackwardDP(self, A: List[List[int]]) -> int: """Just save the min falling path (i, j) -> minimum value start from bottom row as base case, build next layer above based on bottom row.""" <|body_0|> def minFallingPathSum(self, A: List[List[int]])...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def minFallingPathSumBackwardDP(self, A: List[List[int]]) -> int: """Just save the min falling path (i, j) -> minimum value start from bottom row as base case, build next layer above based on bottom row.""" ROWS = len(A) COLS = len(A[0]) grid = [[0 for _ in range(COLS...

the_stack_v2_python_sparse

Algorithms and Data Structures Practice/LeetCode Questions/MOST IMPORTANT PROBLEMS/931. Minimum Falling Path Sum.py

harman666666/Algorithms-Data-Structures-and-Design

train

3

368f6af11c168552220469a2544d8c0b88f0ff25

[ "context = req.environ['nova.context']\nauthorize(context)\nreturn volume_types.get_all_types(context)", "context = req.environ['nova.context']\nauthorize(context)\nif not body or body == '':\n raise exc.HTTPUnprocessableEntity()\nvol_type = body.get('volume_type', None)\nif vol_type is None or vol_type == '':...

The volume types API controller for the Openstack API

VolumeTypesController

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002365

8,791

permissive

[ { "docstring": "Returns the list of volume types", "name": "index", "signature": "def index(self, req)" }, { "docstring": "Creates a new volume type.", "name": "create", "signature": "def create(self, req, body)" }, { "docstring": "Return a single volume type item", "name": "...

5

stack_v2_sparse_classes_30k_train_005099

Implement the Python class `VolumeTypesController` described below. Class description: The volume types API controller for the Openstack API Method signatures and docstrings: - def index(self, req): Returns the list of volume types - def create(self, req, body): Creates a new volume type. - def show(self, req, id): R...

d3de121d6ad35431fb63c20b2185f0f61ceb9e8e

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class VolumeTypesController: """The volume types API controller for the Openstack API""" def index(self, req): """Returns the list of volume types""" context = req.environ['nova.context'] authorize(context) return volume_types.get_all_types(context) def create(self, req, bo...

the_stack_v2_python_sparse

nova/api/openstack/compute/contrib/volumetypes.py

rcbops/nova-buildpackage

train

0

14fb1f79292a79bb569ac8b964e3c211c10be157

[ "essential_keys = ['nvars', 'c', 'freq']\nfor key in essential_keys:\n if key not in problem_params:\n msg = 'need %s to instantiate problem, only got %s' % (key, str(problem_params.keys()))\n raise ParameterError(msg)\nif (problem_params['nvars'] + 1) % 2 != 0:\n raise ProblemError('setup requi...

<|body_start_0|> essential_keys = ['nvars', 'c', 'freq'] for key in essential_keys: if key not in problem_params: msg = 'need %s to instantiate problem, only got %s' % (key, str(problem_params.keys())) raise ParameterError(msg) if (problem_params['nvar...

Example implementing the unforced 1D advection equation with periodic BC in [0,1], discretized using upwinding finite differences Attributes: A: FD discretization of the gradient operator using upwinding dx: distance between two spatial nodes

advection1d_dirichlet

[ "BSD-2-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class advection1d_dirichlet: """Example implementing the unforced 1D advection equation with periodic BC in [0,1], discretized using upwinding finite differences Attributes: A: FD discretization of the gradient operator using upwinding dx: distance between two spatial nodes""" def __init__(self, p...

stack_v2_sparse_classes_10k_train_002366

5,002

permissive

[ { "docstring": "Initialization routine Args: problem_params (dict): custom parameters for the example dtype_u: mesh data type (will be passed parent class) dtype_f: mesh data type (will be passed parent class)", "name": "__init__", "signature": "def __init__(self, problem_params, dtype_u=mesh, dtype_f=m...

5

stack_v2_sparse_classes_30k_train_005919

Implement the Python class `advection1d_dirichlet` described below. Class description: Example implementing the unforced 1D advection equation with periodic BC in [0,1], discretized using upwinding finite differences Attributes: A: FD discretization of the gradient operator using upwinding dx: distance between two spa...

de2cd523411276083355389d7e7993106cedf93d

<|skeleton|> class advection1d_dirichlet: """Example implementing the unforced 1D advection equation with periodic BC in [0,1], discretized using upwinding finite differences Attributes: A: FD discretization of the gradient operator using upwinding dx: distance between two spatial nodes""" def __init__(self, p...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class advection1d_dirichlet: """Example implementing the unforced 1D advection equation with periodic BC in [0,1], discretized using upwinding finite differences Attributes: A: FD discretization of the gradient operator using upwinding dx: distance between two spatial nodes""" def __init__(self, problem_params...

the_stack_v2_python_sparse

pySDC/implementations/problem_classes/AdvectionEquation_1D_FD_dirichlet.py

ruthschoebel/pySDC

train

0

2511a8af35db60015dba0d5b1537075669473edd

[ "ret = []\nfor i in range(numRows):\n row = [1]\n if ret:\n for i in range(len(ret[-1]) - 1):\n row.append(ret[-1][i] + ret[-1][i + 1])\n row.append(1)\n ret.append(row)\nreturn ret", "if numRows == 0:\n return []\nret = [[1]]\nfor i in range(1, numRows):\n row = [1]\n f...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002367

1,597

no_license

[ { "docstring": "07/17/2021 08:17", "name": "generate", "signature": "def generate(self, numRows: int) -> List[List[int]]" }, { "docstring": "07/31/2022 22:48", "name": "generate", "signature": "def generate(self, numRows: int) -> List[List[int]]" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def generate(self, numRows: int) -> List[List[int]]: 07/17/2021 08:17 - def generate(self, numRows: int) -> List[List[int]]: 07/31/2022 22:48

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def generate(self, numRows: int) -> List[List[int]]: 07/17/2021 08:17 - def generate(self, numRows: int) -> List[List[int]]: 07/31/2022 22:48 <|skeleton|> class Solution: d...

1389a009a02e90e8700a7a00e0b7f797c129cdf4

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def generate(self, numRows: int) -> List[List[int]]: """07/17/2021 08:17""" ret = [] for i in range(numRows): row = [1] if ret: for i in range(len(ret[-1]) - 1): row.append(ret[-1][i] + ret[-1][i + 1]) ...

the_stack_v2_python_sparse

leetcode/solved/118_Pascal's_Triangle/solution.py

sungminoh/algorithms

train

0

b3b06e495044b2c5b5889a3f971cb715508a9e68

[ "if not root:\n return ''\nqueue = deque()\nqueue.append(root)\nresult = []\nwhile queue:\n curr = queue.popleft()\n if curr != None:\n result.append(str(curr.val))\n result.append(',')\n queue.append(curr.left)\n queue.append(curr.right)\n else:\n result.append('null'...

<|body_start_0|> if not root: return '' queue = deque() queue.append(root) result = [] while queue: curr = queue.popleft() if curr != None: result.append(str(curr.val)) result.append(',') queue.ap...

Codec

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002368

2,099

no_license

[ { "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_val_000025

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:...

52bf12095996a9137b1ea213ac43e1fe07806956

stack_v2_sparse_classes_10k

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 '' queue = deque() queue.append(root) result = [] while queue: curr = queue.popleft() if curr != N...

the_stack_v2_python_sparse

serialize-and-deserialize-binary-tree/serialize-and-deserialize-binary-tree.py

siva4646/LeetCode_Python

train

0

765f41b4953076d60696f39ed97239d2fe446025

[ "input_tensor = tf.ones([1, 4, 4, 2])\noutput_tensor = cnn_autoencoder_model.encoder(input_tensor, layers_list=(64, 2), pool_list=(2, 2))\nself.assertAllEqual(output_tensor.shape, [1, 2, 2, 2])\nexpected = tf.constant([[[[-0.02436768, -0.27847868], [-0.0774256, -0.5111736]], [[0.50436425, -0.1713084], [0.2803106, -...

<|body_start_0|> input_tensor = tf.ones([1, 4, 4, 2]) output_tensor = cnn_autoencoder_model.encoder(input_tensor, layers_list=(64, 2), pool_list=(2, 2)) self.assertAllEqual(output_tensor.shape, [1, 2, 2, 2]) expected = tf.constant([[[[-0.02436768, -0.27847868], [-0.0774256, -0.5111736]],...

CNNAutoencoderModelTest

[ "Apache-2.0", "CC-BY-4.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002369

4,774

permissive

[ { "docstring": "Tests encoder with default inputs.", "name": "test_encoder_default", "signature": "def test_encoder_default(self)" }, { "docstring": "Tests encoder with default inputs.", "name": "test_encoder_pool_list_values", "signature": "def test_encoder_pool_list_values(self)" }, ...

5

null

Implement the Python class `CNNAutoencoderModelTest` described below. Class description: Implement the CNNAutoencoderModelTest class. Method signatures and docstrings: - def test_encoder_default(self): Tests encoder with default inputs. - def test_encoder_pool_list_values(self): Tests encoder with default inputs. - d...

5573d9c5822f4e866b6692769963ae819cb3f10d

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class CNNAutoencoderModelTest: def test_encoder_default(self): """Tests encoder with default inputs.""" input_tensor = tf.ones([1, 4, 4, 2]) output_tensor = cnn_autoencoder_model.encoder(input_tensor, layers_list=(64, 2), pool_list=(2, 2)) self.assertAllEqual(output_tensor.shape, [1,...

the_stack_v2_python_sparse

simulation_research/next_day_wildfire_spread/models/cnn_autoencoder_model_test.py

Jimmy-INL/google-research

train

1

413973fe2c109f9747000d793dfa108bdbf7a173

[ "self.map_func = map_func\nself.reduce_func = reduce_func\nself.pool = multiprocessing.Pool(num_workers)", "partitioned_data = collections.defaultdict(list)\nfor key, value in mapped_values:\n partitioned_data[key].append(value)\nreturn partitioned_data.items()", "map_responses = self.pool.map(self.map_func,...

SimpleMapReduce

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SimpleMapReduce: def __init__(self, map_func, reduce_func, num_workers=None): """map_func Function to map inputs to intermediate data.Takes as argument one input value and returns a tuple with the key and a value to be reduced. reduce_func Function to reduce partitioned version of interm...

stack_v2_sparse_classes_10k_train_002370

2,086

no_license

[ { "docstring": "map_func Function to map inputs to intermediate data.Takes as argument one input value and returns a tuple with the key and a value to be reduced. reduce_func Function to reduce partitioned version of intermediate data to final output. Takes as argument a key as produced by map_func and a sequen...

3

null

Implement the Python class `SimpleMapReduce` described below. Class description: Implement the SimpleMapReduce class. Method signatures and docstrings: - def __init__(self, map_func, reduce_func, num_workers=None): map_func Function to map inputs to intermediate data.Takes as argument one input value and returns a tu...

c3c554f14b378b487c632e11f22e5e3118be940c

<|skeleton|> class SimpleMapReduce: def __init__(self, map_func, reduce_func, num_workers=None): """map_func Function to map inputs to intermediate data.Takes as argument one input value and returns a tuple with the key and a value to be reduced. reduce_func Function to reduce partitioned version of interm...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class SimpleMapReduce: def __init__(self, map_func, reduce_func, num_workers=None): """map_func Function to map inputs to intermediate data.Takes as argument one input value and returns a tuple with the key and a value to be reduced. reduce_func Function to reduce partitioned version of intermediate data to...

the_stack_v2_python_sparse

Simple_Python/standard/multiprocessing/multiprocessing_24.py

yafeile/Simple_Study

train

0

059e83a3f1c7a999df0f2ab18dc8000302497dbf

[ "main_data = self.get_main_data(imdb_id, api_data)\nratings_data = self.get_ratings_data(imdb_id, api_data)\nif ratings_data and main_data:\n return {'omdb_main': main_data, 'omdb_ratings': ratings_data}\nelse:\n raise GatherException(imdb_id, 'Failed standardise')", "try:\n main_data = [{'imdb_id': imdb...

<|body_start_0|> main_data = self.get_main_data(imdb_id, api_data) ratings_data = self.get_ratings_data(imdb_id, api_data) if ratings_data and main_data: return {'omdb_main': main_data, 'omdb_ratings': ratings_data} else: raise GatherException(imdb_id, 'Failed sta...

This class standardises the response returned from the OMDB API, removing unwanted data, and structuring the remaining data so that it is easier to handle in later processes.

StandardiseResponse

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class StandardiseResponse: """This class standardises the response returned from the OMDB API, removing unwanted data, and structuring the remaining data so that it is easier to handle in later processes.""" def standardise(self, imdb_id, api_data): """Constructs a new dictionary from the ...

stack_v2_sparse_classes_10k_train_002371

5,419

permissive

[ { "docstring": "Constructs a new dictionary from the API data. :param imdb_id: The imdb_id for the requested film :param api_data: The raw response from the OMDB API :return: A standardised dictionary.", "name": "standardise", "signature": "def standardise(self, imdb_id, api_data)" }, { "docstri...

3

stack_v2_sparse_classes_30k_val_000333

Implement the Python class `StandardiseResponse` described below. Class description: This class standardises the response returned from the OMDB API, removing unwanted data, and structuring the remaining data so that it is easier to handle in later processes. Method signatures and docstrings: - def standardise(self, ...

cd6974764f8136529e5d4a3c191ad34865bfe732

<|skeleton|> class StandardiseResponse: """This class standardises the response returned from the OMDB API, removing unwanted data, and structuring the remaining data so that it is easier to handle in later processes.""" def standardise(self, imdb_id, api_data): """Constructs a new dictionary from the ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class StandardiseResponse: """This class standardises the response returned from the OMDB API, removing unwanted data, and structuring the remaining data so that it is easier to handle in later processes.""" def standardise(self, imdb_id, api_data): """Constructs a new dictionary from the API data. :pa...

the_stack_v2_python_sparse

processes/get_omdb.py

kinoreel/kino-gather

train

0

e260482940e11314881315ce489a1aaca5e444f0

[ "course_key = self.course.location.course_key\nbadge_class = BadgeClassFactory.create(course_id=course_key)\nfor dummy in range(3):\n BadgeAssertionFactory.create(user=self.user, badge_class=badge_class)\nfor dummy in range(3):\n BadgeAssertionFactory.create(user=self.user)\nfor dummy in range(6):\n BadgeA...

<|body_start_0|> course_key = self.course.location.course_key badge_class = BadgeClassFactory.create(course_id=course_key) for dummy in range(3): BadgeAssertionFactory.create(user=self.user, badge_class=badge_class) for dummy in range(3): BadgeAssertionFactory.cre...

Test the Badge Assertions view with the course_id filter.

TestUserCourseBadgeAssertions

[ "AGPL-3.0-only", "AGPL-3.0-or-later", "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TestUserCourseBadgeAssertions: """Test the Badge Assertions view with the course_id filter.""" def test_get_assertions(self): """Verify we can get assertions via the course_id and username.""" <|body_0|> def test_assertion_structure(self): """Verify the badge ass...

stack_v2_sparse_classes_10k_train_002372

8,941

permissive

[ { "docstring": "Verify we can get assertions via the course_id and username.", "name": "test_get_assertions", "signature": "def test_get_assertions(self)" }, { "docstring": "Verify the badge assertion structure is as expected when a course is involved.", "name": "test_assertion_structure", ...

2

stack_v2_sparse_classes_30k_train_000824

Implement the Python class `TestUserCourseBadgeAssertions` described below. Class description: Test the Badge Assertions view with the course_id filter. Method signatures and docstrings: - def test_get_assertions(self): Verify we can get assertions via the course_id and username. - def test_assertion_structure(self):...

5809eaca7079a15ee56b0b7fcfea425337046c97

<|skeleton|> class TestUserCourseBadgeAssertions: """Test the Badge Assertions view with the course_id filter.""" def test_get_assertions(self): """Verify we can get assertions via the course_id and username.""" <|body_0|> def test_assertion_structure(self): """Verify the badge ass...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class TestUserCourseBadgeAssertions: """Test the Badge Assertions view with the course_id filter.""" def test_get_assertions(self): """Verify we can get assertions via the course_id and username.""" course_key = self.course.location.course_key badge_class = BadgeClassFactory.create(cour...

the_stack_v2_python_sparse

Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/lms/djangoapps/badges/api/tests.py

luque/better-ways-of-thinking-about-software

train

3

414c7e9dbe1a590259815fb994394a87e1fb9a7b

[ "cls.NETWORK_ATTACHMENT_ARG = flags.NetworkAttachmentArgument()\ncls.NETWORK_ATTACHMENT_ARG.AddArgument(parser, operation_type='create')\ncls.SUBNETWORK_ARG = subnetwork_flags.SubnetworkArgumentForNetworkAttachment()\ncls.SUBNETWORK_ARG.AddArgument(parser)\nparser.display_info.AddFormat(flags.DEFAULT_LIST_FORMAT)\n...

<|body_start_0|> cls.NETWORK_ATTACHMENT_ARG = flags.NetworkAttachmentArgument() cls.NETWORK_ATTACHMENT_ARG.AddArgument(parser, operation_type='create') cls.SUBNETWORK_ARG = subnetwork_flags.SubnetworkArgumentForNetworkAttachment() cls.SUBNETWORK_ARG.AddArgument(parser) parser.dis...

Create a Google Compute Engine network attachment.

Create

[ "Apache-2.0", "LicenseRef-scancode-unknown-license-reference" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Create: """Create a Google Compute Engine network attachment.""" def Args(cls, parser): """Create a Google Compute Engine network attachment. Args: parser: the parser that parses the input from the user.""" <|body_0|> def Run(self, args): """Issue a network attac...

stack_v2_sparse_classes_10k_train_002373

5,014

permissive

[ { "docstring": "Create a Google Compute Engine network attachment. Args: parser: the parser that parses the input from the user.", "name": "Args", "signature": "def Args(cls, parser)" }, { "docstring": "Issue a network attachment INSERT request.", "name": "Run", "signature": "def Run(sel...

2

null

Implement the Python class `Create` described below. Class description: Create a Google Compute Engine network attachment. Method signatures and docstrings: - def Args(cls, parser): Create a Google Compute Engine network attachment. Args: parser: the parser that parses the input from the user. - def Run(self, args): ...

392abf004b16203030e6efd2f0af24db7c8d669e

<|skeleton|> class Create: """Create a Google Compute Engine network attachment.""" def Args(cls, parser): """Create a Google Compute Engine network attachment. Args: parser: the parser that parses the input from the user.""" <|body_0|> def Run(self, args): """Issue a network attac...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Create: """Create a Google Compute Engine network attachment.""" def Args(cls, parser): """Create a Google Compute Engine network attachment. Args: parser: the parser that parses the input from the user.""" cls.NETWORK_ATTACHMENT_ARG = flags.NetworkAttachmentArgument() cls.NETWORK...

the_stack_v2_python_sparse

lib/surface/compute/network_attachments/create.py

google-cloud-sdk-unofficial/google-cloud-sdk

train

9

8cf82579b9009fbccb5335b99d74f667b681244d

[ "super(SubNet, self).__init__()\nself.norm = nn.BatchNorm1d(in_size)\nself.drop = nn.Dropout(p=dropout)\nself.linear_1 = nn.Linear(in_size, hidden_size)\nself.linear_2 = nn.Linear(hidden_size, hidden_size)\nself.linear_3 = nn.Linear(hidden_size, hidden_size)", "normed = self.norm(x)\ndropped = self.drop(normed)\n...

<|body_start_0|> super(SubNet, self).__init__() self.norm = nn.BatchNorm1d(in_size) self.drop = nn.Dropout(p=dropout) self.linear_1 = nn.Linear(in_size, hidden_size) self.linear_2 = nn.Linear(hidden_size, hidden_size) self.linear_3 = nn.Linear(hidden_size, hidden_size) <|...

The subnetwork that is used in TFN for video and audio in the pre-fusion stage

SubNet

[ "GPL-1.0-or-later", "Apache-2.0", "BSD-2-Clause", "MIT", "BSD-3-Clause", "LicenseRef-scancode-generic-cla", "LicenseRef-scancode-unknown-license-reference" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class SubNet: """The subnetwork that is used in TFN for video and audio in the pre-fusion stage""" def __init__(self, in_size, hidden_size, dropout): """Args: in_size: input dimension hidden_size: hidden layer dimension dropout: dropout probability Output: (return value in forward) a tenso...

stack_v2_sparse_classes_10k_train_002374

3,873

permissive

[ { "docstring": "Args: in_size: input dimension hidden_size: hidden layer dimension dropout: dropout probability Output: (return value in forward) a tensor of shape (batch_size, hidden_size)", "name": "__init__", "signature": "def __init__(self, in_size, hidden_size, dropout)" }, { "docstring": "...

2

stack_v2_sparse_classes_30k_train_001841

Implement the Python class `SubNet` described below. Class description: The subnetwork that is used in TFN for video and audio in the pre-fusion stage Method signatures and docstrings: - def __init__(self, in_size, hidden_size, dropout): Args: in_size: input dimension hidden_size: hidden layer dimension dropout: drop...

92acc188d3a0f634de58463b6676e70df83ef808

<|skeleton|> class SubNet: """The subnetwork that is used in TFN for video and audio in the pre-fusion stage""" def __init__(self, in_size, hidden_size, dropout): """Args: in_size: input dimension hidden_size: hidden layer dimension dropout: dropout probability Output: (return value in forward) a tenso...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class SubNet: """The subnetwork that is used in TFN for video and audio in the pre-fusion stage""" def __init__(self, in_size, hidden_size, dropout): """Args: in_size: input dimension hidden_size: hidden layer dimension dropout: dropout probability Output: (return value in forward) a tensor of shape (b...

the_stack_v2_python_sparse

PyTorch/contrib/others/MMSA_ID2979_for_PyTorch/models/subNets/FeatureNets.py

Ascend/ModelZoo-PyTorch

train

23

89ff15bbd2be63a50bc35b21850606205f9fee65

[ "super().__init__()\nself.graph, self.session = parse_tf_model_bytes(model_bytes, device, session_config)\nself.input_image = self.graph.get_tensor_by_name('input:0')\nself.segmented_tensor = self.graph.get_tensor_by_name('output_prediction:0')", "img_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)\nfeed = {self.i...

<|body_start_0|> super().__init__() self.graph, self.session = parse_tf_model_bytes(model_bytes, device, session_config) self.input_image = self.graph.get_tensor_by_name('input:0') self.segmented_tensor = self.graph.get_tensor_by_name('output_prediction:0') <|end_body_0|> <|body_start_1...

Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does not support batch prediction TODO: Is this true?

DepthPredictor

[ "BSD-3-Clause" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class DepthPredictor: """Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does not support batch prediction TODO: Is ...

stack_v2_sparse_classes_10k_train_002375

2,142

permissive

[ { "docstring": ":param model_bytes: Model file data, likely a loaded *.pb file :param device: The device to run the model on :param session_config: Model configuration options", "name": "__init__", "signature": "def __init__(self, model_bytes, device: str=None, session_config: tf.compat.v1.ConfigProto=N...

2

stack_v2_sparse_classes_30k_train_007049

Implement the Python class `DepthPredictor` described below. Class description: Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does...

7412902fed8f91c9c82bd42b0180e07673c38bf1

<|skeleton|> class DepthPredictor: """Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does not support batch prediction TODO: Is ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class DepthPredictor: """Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does not support batch prediction TODO: Is this true?"""...

the_stack_v2_python_sparse

vcap_utils/vcap_utils/backends/depth.py

opencv/open_vision_capsules

train

124

3fce6e554bc2be9ebd9b14f817c77b4e02837152

[ "if cve is None:\n raise ValueError('CVE ID Required')\nmowCVE.__init__(self, cve=cve, **kwargs)\n'\\n self.description = kwargs.get(\"description\", None)\\n self.title = kwargs.get(\"title\", None)\\n self.cvss2 = cvss.CVSS2(kwargs.get(\"cvss2\", None))\\n self.cvss3 = cvss.CVSS3(kw...

<|body_start_0|> if cve is None: raise ValueError('CVE ID Required') mowCVE.__init__(self, cve=cve, **kwargs) '\n self.description = kwargs.get("description", None)\n self.title = kwargs.get("title", None)\n self.cvss2 = cvss.CVSS2(kwargs.get("cvss2", None))\n ...

Red Hat CVE Class that Updates mowCVE with Data from CVE

mowCVERedHat

[ "LicenseRef-scancode-unknown-license-reference", "BSD-2-Clause" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002376

6,606

permissive

[ { "docstring": "Initialze a Holder for CVE Things", "name": "__init__", "signature": "def __init__(self, cve=None, **kwargs)" }, { "docstring": "Reach out, Grab the CVE Data and Parse it", "name": "pull_rh_cve", "signature": "def pull_rh_cve(self)" }, { "docstring": "Takes the pa...

3

stack_v2_sparse_classes_30k_train_005803

Implement the Python class `mowCVERedHat` described below. Class description: Red Hat CVE Class that Updates mowCVE with Data from CVE Method signatures and docstrings: - def __init__(self, cve=None, **kwargs): Initialze a Holder for CVE Things - def pull_rh_cve(self): Reach out, Grab the CVE Data and Parse it - def ...

b9399f32950125ac7bfc48595da1c713544a1dfe

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class mowCVERedHat: """Red Hat CVE Class that Updates mowCVE with Data from CVE""" def __init__(self, cve=None, **kwargs): """Initialze a Holder for CVE Things""" if cve is None: raise ValueError('CVE ID Required') mowCVE.__init__(self, cve=cve, **kwargs) '\n ...

the_stack_v2_python_sparse

audittools/redhat_cve.py

chalbersma/manowar

train

3

5f77c5318a4541c5e746d74d3fe1d3c2d656643a

[ "email_content, receivers_email = self.generate_report(task_id=task_id)\nlogger.info('task task_id:{} has been checked out, hunter will send result to email:{}'.format(task_id, receivers_email))\nif receivers_email is not None and receivers_email.strip() != '':\n EmailUtils().send_mail_with_ssl(receivers_email, ...

<|body_start_0|> email_content, receivers_email = self.generate_report(task_id=task_id) logger.info('task task_id:{} has been checked out, hunter will send result to email:{}'.format(task_id, receivers_email)) if receivers_email is not None and receivers_email.strip() != '': EmailUti...

EmailObserver

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002377

4,435

permissive

[ { "docstring": "发送邮件通知 :return:", "name": "notify", "signature": "def notify(self, task_id)" }, { "docstring": "生成邮件发送报告 :param cls: :param task_id: :return:", "name": "generate_report", "signature": "def generate_report(self, task_id)" } ]

2

stack_v2_sparse_classes_30k_train_003513

Implement the Python class `EmailObserver` described below. Class description: Implement the EmailObserver class. Method signatures and docstrings: - def notify(self, task_id): 发送邮件通知 :return: - def generate_report(self, task_id): 生成邮件发送报告 :param cls: :param task_id: :return:

Implement the Python class `EmailObserver` described below. Class description: Implement the EmailObserver class. Method signatures and docstrings: - def notify(self, task_id): 发送邮件通知 :return: - def generate_report(self, task_id): 生成邮件发送报告 :param cls: :param task_id: :return: <|skeleton|> class EmailObserver: d...

4ee5cca8dc5fc5d7e631e935517bd0f493c30a37

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class EmailObserver: def notify(self, task_id): """发送邮件通知 :return:""" email_content, receivers_email = self.generate_report(task_id=task_id) logger.info('task task_id:{} has been checked out, hunter will send result to email:{}'.format(task_id, receivers_email)) if receivers_email is...

the_stack_v2_python_sparse

HunterCelery/notice/email_observer.py

a1kaid/hunter

train

0

40a96bfe0a1328d123da5121b4fac09389faa053

[ "if token_cache is None:\n token_cache = JSONFileCache(self._SSO_TOKEN_CACHE_DIR)\nself._token_cache = token_cache\nif cache is None:\n cache = {}\nself.cache = cache\nself._load_config = load_config\nself._client_creator = client_creator\nself._profile_name = profile_name", "loaded_config = self._load_conf...

<|body_start_0|> if token_cache is None: token_cache = JSONFileCache(self._SSO_TOKEN_CACHE_DIR) self._token_cache = token_cache if cache is None: cache = {} self.cache = cache self._load_config = load_config self._client_creator = client_creator ...

AWS SSO credential provider.

SSOProvider

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002378

11,021

permissive

[ { "docstring": "Instantiate class.", "name": "__init__", "signature": "def __init__(self, load_config, client_creator, profile_name, cache=None, token_cache=None)" }, { "docstring": "Load sso config.", "name": "_load_sso_config", "signature": "def _load_sso_config(self)" }, { "do...

3

null

Implement the Python class `SSOProvider` described below. Class description: AWS SSO credential provider. Method signatures and docstrings: - def __init__(self, load_config, client_creator, profile_name, cache=None, token_cache=None): Instantiate class. - def _load_sso_config(self): Load sso config. - def load(self):...

0763b06aee07d2cf3f037a49ca0cb81a048c5deb

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class SSOProvider: """AWS SSO credential provider.""" def __init__(self, load_config, client_creator, profile_name, cache=None, token_cache=None): """Instantiate class.""" if token_cache is None: token_cache = JSONFileCache(self._SSO_TOKEN_CACHE_DIR) self._token_cache = toke...

the_stack_v2_python_sparse

runway/aws_sso_botocore/credentials.py

onicagroup/runway

train

156

b1bf98d5a2673a7878b261bdf63093cff0a8f234

[ "cluster = check_obj(Cluster, cluster_id, 'CLUSTER_NOT_FOUND')\nres = cm.api.get_import(cluster)\nreturn Response(res)", "cluster = check_obj(Cluster, cluster_id, 'CLUSTER_NOT_FOUND')\nserializer = self.post_serializer(data=request.data, context={'request': request, 'cluster': cluster})\nif serializer.is_valid():...

ClusterImport

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002379

32,530

permissive

[ { "docstring": "List all imports avaliable for specified cluster", "name": "get", "signature": "def get(self, request, cluster_id)" }, { "docstring": "Update bind for cluster", "name": "post", "signature": "def post(self, request, cluster_id)" } ]

2

stack_v2_sparse_classes_30k_train_000624

Implement the Python class `ClusterImport` described below. Class description: Implement the ClusterImport class. Method signatures and docstrings: - def get(self, request, cluster_id): List all imports avaliable for specified cluster - def post(self, request, cluster_id): Update bind for cluster

Implement the Python class `ClusterImport` described below. Class description: Implement the ClusterImport class. Method signatures and docstrings: - def get(self, request, cluster_id): List all imports avaliable for specified cluster - def post(self, request, cluster_id): Update bind for cluster <|skeleton|> class ...

e1c67e3041437ad9e17dccc6c95c5ac02184eddb

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ClusterImport: def get(self, request, cluster_id): """List all imports avaliable for specified cluster""" cluster = check_obj(Cluster, cluster_id, 'CLUSTER_NOT_FOUND') res = cm.api.get_import(cluster) return Response(res) def post(self, request, cluster_id): """Upd...

the_stack_v2_python_sparse

api/cluster_views.py

amleshkov/adcm

train

0

77757e8284e30c20656b352b994b57920eb5479f

[ "self.cache = {}\nself.frequency = collections.defaultdict(list)\nself.capacity = capacity", "if key not in self.cache:\n return -1\nfor freq in self.frequency:\n if key in self.frequency[freq]:\n self.frequency[freq].remove(key)\n if not self.frequency[freq]:\n self.frequency.pop(f...

<|body_start_0|> self.cache = {} self.frequency = collections.defaultdict(list) self.capacity = capacity <|end_body_0|> <|body_start_1|> if key not in self.cache: return -1 for freq in self.frequency: if key in self.frequency[freq]: self.f...

LFUCache

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002380

1,356

no_license

[ { "docstring": ":type capacity: int", "name": "__init__", "signature": "def __init__(self, capacity)" }, { "docstring": ":type key: int :rtype: int", "name": "get", "signature": "def get(self, key)" }, { "docstring": ":type key: int :type value: int :rtype: None", "name": "pu...

3

stack_v2_sparse_classes_30k_train_000680

Implement the Python class `LFUCache` described below. Class description: Implement the LFUCache class. Method signatures and docstrings: - def __init__(self, capacity): :type capacity: int - def get(self, key): :type key: int :rtype: int - def put(self, key, value): :type key: int :type value: int :rtype: None

Implement the Python class `LFUCache` described below. Class description: Implement the LFUCache class. Method signatures and docstrings: - def __init__(self, capacity): :type capacity: int - def get(self, key): :type key: int :rtype: int - def put(self, key, value): :type key: int :type value: int :rtype: None <|sk...

2fe336e0de336f6d5f67b058ddb5cf50c9f00d4e

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class LFUCache: def __init__(self, capacity): """:type capacity: int""" self.cache = {} self.frequency = collections.defaultdict(list) self.capacity = capacity def get(self, key): """:type key: int :rtype: int""" if key not in self.cache: return -1 ...

the_stack_v2_python_sparse

c++/460. LFU Cache.py

rhzx3519/leetcode

train

3

f1d07364d9b62b14c520ec4de393d84ae86fe86d

[ "total_sum = sum(nums)\nif total_sum % 2 != 0:\n return False\nsub_set_sum = total_sum // 2\ndp = [False] * (sub_set_sum + 1)\ndp[0] = True\nfor num in nums:\n for j in range(sub_set_sum, num - 1, -1):\n dp[j] = dp[j] or dp[j - num]\nreturn dp[sub_set_sum]", "total_sum = sum(nums)\nif total_sum % 2 !...

<|body_start_0|> total_sum = sum(nums) if total_sum % 2 != 0: return False sub_set_sum = total_sum // 2 dp = [False] * (sub_set_sum + 1) dp[0] = True for num in nums: for j in range(sub_set_sum, num - 1, -1): dp[j] = dp[j] or dp[j -...

Array

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Array: def can_partition(self, nums: List[int]) -> bool: """Approach: DP (1D Array) Time Complexity: O(m * n) Space Complexity: O(m) :param nums: :return:""" <|body_0|> def can_partition_(self, nums: List[int]) -> bool: """Approach: DP (2D Array) Time Complexity: O(m...

stack_v2_sparse_classes_10k_train_002381

1,709

no_license

[ { "docstring": "Approach: DP (1D Array) Time Complexity: O(m * n) Space Complexity: O(m) :param nums: :return:", "name": "can_partition", "signature": "def can_partition(self, nums: List[int]) -> bool" }, { "docstring": "Approach: DP (2D Array) Time Complexity: O(m * n) Space Complexity: O(m * n...

2

null

Implement the Python class `Array` described below. Class description: Implement the Array class. Method signatures and docstrings: - def can_partition(self, nums: List[int]) -> bool: Approach: DP (1D Array) Time Complexity: O(m * n) Space Complexity: O(m) :param nums: :return: - def can_partition_(self, nums: List[i...

65cc78b5afa0db064f9fe8f06597e3e120f7363d

<|skeleton|> class Array: def can_partition(self, nums: List[int]) -> bool: """Approach: DP (1D Array) Time Complexity: O(m * n) Space Complexity: O(m) :param nums: :return:""" <|body_0|> def can_partition_(self, nums: List[int]) -> bool: """Approach: DP (2D Array) Time Complexity: O(m...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Array: def can_partition(self, nums: List[int]) -> bool: """Approach: DP (1D Array) Time Complexity: O(m * n) Space Complexity: O(m) :param nums: :return:""" total_sum = sum(nums) if total_sum % 2 != 0: return False sub_set_sum = total_sum // 2 dp = [False] ...

the_stack_v2_python_sparse

revisited_2021/dp/partition_equal_subset_sum.py

Shiv2157k/leet_code

train

1

9927888e9df972509a201241abfe195fb7e16430

[ "assert len(sizes) == 2, 'SSD requires sizes to be (size_min, size_max)'\nanchors = []\nfor i in range(alloc_size[0]):\n for j in range(alloc_size[1]):\n cy = (i + offsets[0]) * step\n cx = (j + offsets[1]) * step\n r = ratios[0]\n anchors.append([cx, cy, sizes[0] / 2, sizes[0] / 2])\...

<|body_start_0|> assert len(sizes) == 2, 'SSD requires sizes to be (size_min, size_max)' anchors = [] for i in range(alloc_size[0]): for j in range(alloc_size[1]): cy = (i + offsets[0]) * step cx = (j + offsets[1]) * step r = ratios[0] ...

Bounding box anchor generator for Single-shot Object Detection, corresponding to anchors structure used in ssd_mobilenet_v1_coco from TF Object Detection API This class inherits SSDAnchorGenerator and uses the same input parameters. Main differences: - First branch is not added with another anchor with size extracted f...

LiteAnchorGenerator

[ "Apache-2.0" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class LiteAnchorGenerator: """Bounding box anchor generator for Single-shot Object Detection, corresponding to anchors structure used in ssd_mobilenet_v1_coco from TF Object Detection API This class inherits SSDAnchorGenerator and uses the same input parameters. Main differences: - First branch is not ...

stack_v2_sparse_classes_10k_train_002382

5,184

permissive

[ { "docstring": "Generate anchors for once. Anchors are stored with (center_x, center_y, w, h) format.", "name": "_generate_anchors", "signature": "def _generate_anchors(self, sizes, ratios, step, alloc_size, offsets)" }, { "docstring": "Number of anchors at each pixel.", "name": "num_depth",...

2

stack_v2_sparse_classes_30k_train_000089

Implement the Python class `LiteAnchorGenerator` described below. Class description: Bounding box anchor generator for Single-shot Object Detection, corresponding to anchors structure used in ssd_mobilenet_v1_coco from TF Object Detection API This class inherits SSDAnchorGenerator and uses the same input parameters. M...

567775619f3b97d47e7c360748912a4fd883ff52

<|skeleton|> class LiteAnchorGenerator: """Bounding box anchor generator for Single-shot Object Detection, corresponding to anchors structure used in ssd_mobilenet_v1_coco from TF Object Detection API This class inherits SSDAnchorGenerator and uses the same input parameters. Main differences: - First branch is not ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class LiteAnchorGenerator: """Bounding box anchor generator for Single-shot Object Detection, corresponding to anchors structure used in ssd_mobilenet_v1_coco from TF Object Detection API This class inherits SSDAnchorGenerator and uses the same input parameters. Main differences: - First branch is not added with an...

the_stack_v2_python_sparse

gluoncv/model_zoo/ssd/anchor.py

dmlc/gluon-cv

train

6,064

e061b8e09f6649ed13e439ca3980e9eda94f5946

[ "endpoint = 'show version '\nPARSER = 'raw/showEdgeVersion'\nEXPECT_PROMPT = ['bytes*', 'NSXEdge>']\nmapped_pydict = utilities.get_mapped_pydict_for_expect(client_object.connection, endpoint, PARSER, EXPECT_PROMPT, ' ')\nclient_object.connection.close()\nget_edge_version_schema_object = show_edge_version_schema.Sho...

<|body_start_0|> endpoint = 'show version ' PARSER = 'raw/showEdgeVersion' EXPECT_PROMPT = ['bytes*', 'NSXEdge>'] mapped_pydict = utilities.get_mapped_pydict_for_expect(client_object.connection, endpoint, PARSER, EXPECT_PROMPT, ' ') client_object.connection.close() get_ed...

Edge70OSImpl

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Edge70OSImpl: def get_os_info(cls, client_object, **kwargs): """Returns the Kernel version, Build number, Name and Version information for given NSX edge NSXEdge>show version ... Name: NSX Edge ... Version: 7.0.0.0.0 ... Build Number: 2252106 ... Kernel: 3.2.62""" <|body_0|> ...

stack_v2_sparse_classes_10k_train_002383

8,973

no_license

[ { "docstring": "Returns the Kernel version, Build number, Name and Version information for given NSX edge NSXEdge>show version ... Name: NSX Edge ... Version: 7.0.0.0.0 ... Build Number: 2252106 ... Kernel: 3.2.62", "name": "get_os_info", "signature": "def get_os_info(cls, client_object, **kwargs)" },...

5

stack_v2_sparse_classes_30k_test_000281

Implement the Python class `Edge70OSImpl` described below. Class description: Implement the Edge70OSImpl class. Method signatures and docstrings: - def get_os_info(cls, client_object, **kwargs): Returns the Kernel version, Build number, Name and Version information for given NSX edge NSXEdge>show version ... Name: NS...

5b55817c050b637e2747084290f6206d2e622938

<|skeleton|> class Edge70OSImpl: def get_os_info(cls, client_object, **kwargs): """Returns the Kernel version, Build number, Name and Version information for given NSX edge NSXEdge>show version ... Name: NSX Edge ... Version: 7.0.0.0.0 ... Build Number: 2252106 ... Kernel: 3.2.62""" <|body_0|> ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Edge70OSImpl: def get_os_info(cls, client_object, **kwargs): """Returns the Kernel version, Build number, Name and Version information for given NSX edge NSXEdge>show version ... Name: NSX Edge ... Version: 7.0.0.0.0 ... Build Number: 2252106 ... Kernel: 3.2.62""" endpoint = 'show version ' ...

the_stack_v2_python_sparse

SystemTesting/pylib/vmware/nsx/edge/cli/edge70_os_impl.py

Cloudxtreme/MyProject

train

0

bd0f1abfcf830758fb58ba5e12d93d44f79d7085

[ "super(Encoder, self).__init__()\nself.layers = clones(layer, N)\nself.norm = LayerNorm(layer.size)\nself.position = position", "if self.position:\n x = self.position(x, mask, indices)\nmask = mask.unsqueeze(-2)\nfor layer in self.layers:\n x = layer(x, mask)\nreturn self.norm(x)" ]

Stack of Transformer encoder blocks with positional encoding.

Encoder

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Encoder: """Stack of Transformer encoder blocks with positional encoding.""" def __init__(self, layer, N, position): """:param layer: single building block to clone :param N: number of copies :param position: positional encoding module""" <|body_0|> def forward(self, x, ...

stack_v2_sparse_classes_10k_train_002384

21,238

no_license

[ { "docstring": ":param layer: single building block to clone :param N: number of copies :param position: positional encoding module", "name": "__init__", "signature": "def __init__(self, layer, N, position)" }, { "docstring": "Forward pass through each block of the Transformer. :param x: input o...

2

null

Implement the Python class `Encoder` described below. Class description: Stack of Transformer encoder blocks with positional encoding. Method signatures and docstrings: - def __init__(self, layer, N, position): :param layer: single building block to clone :param N: number of copies :param position: positional encodin...

7e55a422588c1d1e00f35a3d3a3ff896cce59e18

<|skeleton|> class Encoder: """Stack of Transformer encoder blocks with positional encoding.""" def __init__(self, layer, N, position): """:param layer: single building block to clone :param N: number of copies :param position: positional encoding module""" <|body_0|> def forward(self, x, ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Encoder: """Stack of Transformer encoder blocks with positional encoding.""" def __init__(self, layer, N, position): """:param layer: single building block to clone :param N: number of copies :param position: positional encoding module""" super(Encoder, self).__init__() self.layer...

the_stack_v2_python_sparse

generated/test_allegro_allRank.py

jansel/pytorch-jit-paritybench

train

35

334839b5ccb98cd07b5b6540cb19f92b130228f6

[ "def insert(target):\n left, right = (0, len(res) - 1)\n while left <= right:\n mid = left + (right - left) / 2\n if res[mid] < target:\n left = mid + 1\n else:\n right = mid - 1\n if left == len(res):\n res.append(target)\n else:\n res[left] = ta...

<|body_start_0|> def insert(target): left, right = (0, len(res) - 1) while left <= right: mid = left + (right - left) / 2 if res[mid] < target: left = mid + 1 else: right = mid - 1 if left...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002385

3,342

no_license

[ { "docstring": ":type envelopes: List[List[int]] :rtype: int", "name": "maxEnvelopes", "signature": "def maxEnvelopes(self, envelopes)" }, { "docstring": ":type envelopes: List[List[int]] :rtype: int", "name": "maxEnvelopes2", "signature": "def maxEnvelopes2(self, envelopes)" } ]

2

null

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def maxEnvelopes(self, envelopes): :type envelopes: List[List[int]] :rtype: int - def maxEnvelopes2(self, envelopes): :type envelopes: List[List[int]] :rtype: int

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def maxEnvelopes(self, envelopes): :type envelopes: List[List[int]] :rtype: int - def maxEnvelopes2(self, envelopes): :type envelopes: List[List[int]] :rtype: int <|skeleton|> c...

340ae58fb65b97aa6c6ab2daa8cbd82d1093deae

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def maxEnvelopes(self, envelopes): """:type envelopes: List[List[int]] :rtype: int""" def insert(target): left, right = (0, len(res) - 1) while left <= right: mid = left + (right - left) / 2 if res[mid] < target: ...

the_stack_v2_python_sparse

learnpythonthehardway/russian-doll-envelopes-354.py

dgpllc/leetcode-python

train

0

b43cb61973a4e9d90321c6d69200533dabaacdcb

[ "if not root:\n return ''\npreOrderList = []\n\ndef preOrder(node):\n if not node:\n preOrderList.append('#')\n return\n preOrderList.append(node.val)\n preOrder(node.left)\n preOrder(node.right)\npreOrder(root)\nreturn ' '.join(map(str, preOrderList))", "if not data:\n return None...

<|body_start_0|> if not root: return '' preOrderList = [] def preOrder(node): if not node: preOrderList.append('#') return preOrderList.append(node.val) preOrder(node.left) preOrder(node.right) p...

Codec

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002386

2,238

no_license

[ { "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

null

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:...

63ac5a0921835b1e9d65f71e1346bbb7d66dad9b

stack_v2_sparse_classes_10k

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 '' preOrderList = [] def preOrder(node): if not node: preOrderList.append('#') return ...

the_stack_v2_python_sparse

LeetCode/困难/树/297. 二叉树的序列化与反序列化.py

homezzm/leetcode

train

1

260e8b84b1e48c39c0961a5ee70432922e837ae5

[ "super().__init__(master, **options)\nself.pack()\nself._player_info = player_info\nself._selected_color_bgr = StringVar(self, '顏色未定')\nself._selected_color_bgr.trace('w', self._update_player_color)\nself._previous_selected_color_bgr = self._selected_color_bgr.get()\nself._setup_layout(color_list)", "color_label ...

<|body_start_0|> super().__init__(master, **options) self.pack() self._player_info = player_info self._selected_color_bgr = StringVar(self, '顏色未定') self._selected_color_bgr.trace('w', self._update_player_color) self._previous_selected_color_bgr = self._selected_color_bgr....

The widget for setting and displaying BasicPlayerInfo or its derived class Usage: ``` playerInfoWidget = PlayerInfoWidget(...) playerInfoWidget.pack() playerInfoWidget.refresh() # To reflect the changes in BasicPlayerInfo ``` @var _player_info The object of BasicPlayerInfo or its derived class that binds to this widget...

BasicPlayerInfoWidget

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class BasicPlayerInfoWidget: """The widget for setting and displaying BasicPlayerInfo or its derived class Usage: ``` playerInfoWidget = PlayerInfoWidget(...) playerInfoWidget.pack() playerInfoWidget.refresh() # To reflect the changes in BasicPlayerInfo ``` @var _player_info The object of BasicPlayerIn...

stack_v2_sparse_classes_10k_train_002387

8,055

no_license

[ { "docstring": "Constructor Constructor will invoke BasicPlayerInfoWidget._setup_layout() to setup its layout. @param master Specify he parent widget @param player_info Specify the target player information to be shwon @param color_list Specify he selectable color for this player. It will be a list of string re...

5

stack_v2_sparse_classes_30k_train_006729

Implement the Python class `BasicPlayerInfoWidget` described below. Class description: The widget for setting and displaying BasicPlayerInfo or its derived class Usage: ``` playerInfoWidget = PlayerInfoWidget(...) playerInfoWidget.pack() playerInfoWidget.refresh() # To reflect the changes in BasicPlayerInfo ``` @var _...

dc695322095b2eae4527fcdd33cf6304fbf39600

<|skeleton|> class BasicPlayerInfoWidget: """The widget for setting and displaying BasicPlayerInfo or its derived class Usage: ``` playerInfoWidget = PlayerInfoWidget(...) playerInfoWidget.pack() playerInfoWidget.refresh() # To reflect the changes in BasicPlayerInfo ``` @var _player_info The object of BasicPlayerIn...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class BasicPlayerInfoWidget: """The widget for setting and displaying BasicPlayerInfo or its derived class Usage: ``` playerInfoWidget = PlayerInfoWidget(...) playerInfoWidget.pack() playerInfoWidget.refresh() # To reflect the changes in BasicPlayerInfo ``` @var _player_info The object of BasicPlayerInfo or its der...

the_stack_v2_python_sparse

game_essential/game_widgets.py

LanKuDot/MazeArena-Console

train

0

599ac5d70a03e18ea6841a4f40fd20fa0ac1ebe1

[ "if len(data['changes']):\n if not isinstance(to, (list, set)):\n to = [to]\n if len(to) > 0:\n with transaction.atomic():\n message = Message()\n message.create_message_from_template(template_name=template_name, data=data)\n message.save()\n message.s...

<|body_start_0|> if len(data['changes']): if not isinstance(to, (list, set)): to = [to] if len(to) > 0: with transaction.atomic(): message = Message() message.create_message_from_template(template_name=template_name,...

Миксин для оповещения пользователя, что модератор исправил/изменил материал

MixinSaveModel

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MixinSaveModel: """Миксин для оповещения пользователя, что модератор исправил/изменил материал""" def _send_private_message(template_name, data, to): """Формирование автоматического уведомления с указанием измененных полей""" <|body_0|> def save_model(self, request, obj,...

stack_v2_sparse_classes_10k_train_002388

5,107

no_license

[ { "docstring": "Формирование автоматического уведомления с указанием измененных полей", "name": "_send_private_message", "signature": "def _send_private_message(template_name, data, to)" }, { "docstring": "Метод вызывается при сохранении материала из админки. При изменении полей формирует данные...

2

stack_v2_sparse_classes_30k_train_003564

Implement the Python class `MixinSaveModel` described below. Class description: Миксин для оповещения пользователя, что модератор исправил/изменил материал Method signatures and docstrings: - def _send_private_message(template_name, data, to): Формирование автоматического уведомления с указанием измененных полей - de...

9c46e756e285fba9853dad6c510b1f87968a7092

<|skeleton|> class MixinSaveModel: """Миксин для оповещения пользователя, что модератор исправил/изменил материал""" def _send_private_message(template_name, data, to): """Формирование автоматического уведомления с указанием измененных полей""" <|body_0|> def save_model(self, request, obj,...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class MixinSaveModel: """Миксин для оповещения пользователя, что модератор исправил/изменил материал""" def _send_private_message(template_name, data, to): """Формирование автоматического уведомления с указанием измененных полей""" if len(data['changes']): if not isinstance(to, (lis...

the_stack_v2_python_sparse

main/admin.py

thewebcat/livecamsbay

train

1

da0c4e1077bf059179a43f5ee32eeaa020ff1e03

[ "steps = dict()\n\ndef dfs(root, step):\n if root is None:\n return\n if step not in steps:\n steps[step] = root.val\n else:\n steps[step] = max(steps[step], root.val)\n if root.left:\n dfs(root.left, step + 1)\n if root.right:\n dfs(root.right, step + 1)\ndfs(root,...

<|body_start_0|> steps = dict() def dfs(root, step): if root is None: return if step not in steps: steps[step] = root.val else: steps[step] = max(steps[step], root.val) if root.left: dfs(root...

Solution

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002389

1,886

no_license

[ { "docstring": ":type root: TreeNode :rtype: List[int]", "name": "largestValues", "signature": "def largestValues(self, root)" }, { "docstring": ":type root: TreeNode :rtype: List[int]", "name": "largestValuesBFS", "signature": "def largestValuesBFS(self, root)" } ]

2

stack_v2_sparse_classes_30k_train_002400

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def largestValues(self, root): :type root: TreeNode :rtype: List[int] - def largestValuesBFS(self, root): :type root: TreeNode :rtype: List[int]

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def largestValues(self, root): :type root: TreeNode :rtype: List[int] - def largestValuesBFS(self, root): :type root: TreeNode :rtype: List[int] <|skeleton|> class Solution: ...

1520e1e9bb0c428797a3e5234e5b328110472c20

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def largestValues(self, root): """:type root: TreeNode :rtype: List[int]""" steps = dict() def dfs(root, step): if root is None: return if step not in steps: steps[step] = root.val else: step...

the_stack_v2_python_sparse

Depth-first Search/515. Find Largest Value in Each Tree Row.py

tinkle1129/Leetcode_Solution

train

0

3597588e3098aa04ef38b3a65fa995ed19282795

[ "if not nums2 or not nums1:\n return []\nheap = []\nret = []\nheappush(heap, [nums1[0] + nums2[0], 0, 0])\nwhile len(ret) < k and heap:\n min_of_cur = heappop(heap)\n _, i, j = min_of_cur\n ret.append([nums1[i], nums2[j]])\n if j + 1 < len(nums2):\n heappush(heap, [nums1[i] + nums2[j + 1], i, ...

<|body_start_0|> if not nums2 or not nums1: return [] heap = [] ret = [] heappush(heap, [nums1[0] + nums2[0], 0, 0]) while len(ret) < k and heap: min_of_cur = heappop(heap) _, i, j = min_of_cur ret.append([nums1[i], nums2[j]]) ...

Solution

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class Solution: def kSmallestPairs(self, nums1, nums2, k): """:type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]""" <|body_0|> def kSmallestPairs3(self, nums1, nums2, k): """:type nums1: List[int] :type nums2: List[int] :type k: int :rtype: ...

stack_v2_sparse_classes_10k_train_002390

3,335

no_license

[ { "docstring": ":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]", "name": "kSmallestPairs", "signature": "def kSmallestPairs(self, nums1, nums2, k)" }, { "docstring": ":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]", "nam...

4

stack_v2_sparse_classes_30k_train_005827

Implement the Python class `Solution` described below. Class description: Implement the Solution class. Method signatures and docstrings: - def kSmallestPairs(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]] - def kSmallestPairs3(self, nums1, nums2, k): :type ...

70bdd75b6af2e1811c1beab22050c01d28d7373e

<|skeleton|> class Solution: def kSmallestPairs(self, nums1, nums2, k): """:type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]""" <|body_0|> def kSmallestPairs3(self, nums1, nums2, k): """:type nums1: List[int] :type nums2: List[int] :type k: int :rtype: ...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class Solution: def kSmallestPairs(self, nums1, nums2, k): """:type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[List[int]]""" if not nums2 or not nums1: return [] heap = [] ret = [] heappush(heap, [nums1[0] + nums2[0], 0, 0]) while le...

the_stack_v2_python_sparse

python/leetcode/373_Find_K_Pairs_with_Smallest_Sums.py

bobcaoge/my-code

train

0

abe7cfd8d0733d37bcc78cbca32ae742cf4e858f

[ "if UserProfile.objects.filter(username=username):\n raise serializers.ValidationError(username + ' 账号已存在')\nreturn username", "REGEX_MOBILE = '^1[358]\\\\d{9}$|^147\\\\d{8}$|^176\\\\d{8}$'\nif not re.match(REGEX_MOBILE, mobile):\n raise serializers.ValidationError('手机号码不合法')\nif UserProfile.objects.filter(...

<|body_start_0|> if UserProfile.objects.filter(username=username): raise serializers.ValidationError(username + ' 账号已存在') return username <|end_body_0|> <|body_start_1|> REGEX_MOBILE = '^1[358]\\d{9}$|^147\\d{8}$|^176\\d{8}$' if not re.match(REGEX_MOBILE, mobile): ...

创建用户序列化

UserCreateSerializer

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002391

3,031

no_license

[ { "docstring": "校验用户名是否存在 :param username: :return:", "name": "validate_username", "signature": "def validate_username(self, username)" }, { "docstring": "校验手机号是否合法、是否已被注册 :param mobile: :return:", "name": "validate_mobile", "signature": "def validate_mobile(self, mobile)" } ]

2

stack_v2_sparse_classes_30k_train_005025

Implement the Python class `UserCreateSerializer` described below. Class description: 创建用户序列化 Method signatures and docstrings: - def validate_username(self, username): 校验用户名是否存在 :param username: :return: - def validate_mobile(self, mobile): 校验手机号是否合法、是否已被注册 :param mobile: :return:

Implement the Python class `UserCreateSerializer` described below. Class description: 创建用户序列化 Method signatures and docstrings: - def validate_username(self, username): 校验用户名是否存在 :param username: :return: - def validate_mobile(self, mobile): 校验手机号是否合法、是否已被注册 :param mobile: :return: <|skeleton|> class UserCreateSeria...

db1d7c4eb2d5d229ab54c6d5775f96fc1843716e

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class UserCreateSerializer: """创建用户序列化""" def validate_username(self, username): """校验用户名是否存在 :param username: :return:""" if UserProfile.objects.filter(username=username): raise serializers.ValidationError(username + ' 账号已存在') return username def validate_mobile(self, ...

the_stack_v2_python_sparse

apps/rbac/serializers/user_serializer.py

fengjy96/rest_task

train

0

b551968c9de039248ef33a8d7247a2552d8bef8d

[ "assert is_unwrappable_to(env, DiscreteEnv)\nassert is_unwrappable_to(env, FeatureWrapper)\nsuper(MaxEntIRL, self).__init__(env, expert_trajs, rl_alg_factory, metrics, config)\nself.transition_matrix = get_transition_matrix(self.env)\nself.n_states, self.n_actions, _ = self.transition_matrix.shape\nfeature_wrapper ...

<|body_start_0|> assert is_unwrappable_to(env, DiscreteEnv) assert is_unwrappable_to(env, FeatureWrapper) super(MaxEntIRL, self).__init__(env, expert_trajs, rl_alg_factory, metrics, config) self.transition_matrix = get_transition_matrix(self.env) self.n_states, self.n_actions, _ ...

Maximum Entropy IRL (Ziebart et al., 2008). Not to be confused with Maximum Entropy Deep IRL (Wulfmeier et al., 2016) or Maximum Causal Entropy IRL (Ziebart et al., 2010).

MaxEntIRL

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class MaxEntIRL: """Maximum Entropy IRL (Ziebart et al., 2008). Not to be confused with Maximum Entropy Deep IRL (Wulfmeier et al., 2016) or Maximum Causal Entropy IRL (Ziebart et al., 2010).""" def __init__(self, env: gym.Env, expert_trajs: List[Dict[str, list]], rl_alg_factory: Callable[[gym.Env...

stack_v2_sparse_classes_10k_train_002392

5,210

no_license

[ { "docstring": "See :class:`irl_benchmark.irl.algorithms.base_algorithm.BaseIRLAlgorithm`.", "name": "__init__", "signature": "def __init__(self, env: gym.Env, expert_trajs: List[Dict[str, list]], rl_alg_factory: Callable[[gym.Env], BaseRLAlgorithm], metrics: List[BaseMetric], config: dict)" }, { ...

3

stack_v2_sparse_classes_30k_train_003305

Implement the Python class `MaxEntIRL` described below. Class description: Maximum Entropy IRL (Ziebart et al., 2008). Not to be confused with Maximum Entropy Deep IRL (Wulfmeier et al., 2016) or Maximum Causal Entropy IRL (Ziebart et al., 2010). Method signatures and docstrings: - def __init__(self, env: gym.Env, ex...

8dbf62c79a106e460a542c4008903aec8ec472c6

<|skeleton|> class MaxEntIRL: """Maximum Entropy IRL (Ziebart et al., 2008). Not to be confused with Maximum Entropy Deep IRL (Wulfmeier et al., 2016) or Maximum Causal Entropy IRL (Ziebart et al., 2010).""" def __init__(self, env: gym.Env, expert_trajs: List[Dict[str, list]], rl_alg_factory: Callable[[gym.Env...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class MaxEntIRL: """Maximum Entropy IRL (Ziebart et al., 2008). Not to be confused with Maximum Entropy Deep IRL (Wulfmeier et al., 2016) or Maximum Causal Entropy IRL (Ziebart et al., 2010).""" def __init__(self, env: gym.Env, expert_trajs: List[Dict[str, list]], rl_alg_factory: Callable[[gym.Env], BaseRLAlgo...

the_stack_v2_python_sparse

irl_benchmark/irl/algorithms/me_irl.py

dit7ya/irl-benchmark-1

train

0

ae929564c0ee8bb868cd44fc714185f8709db7ad

[ "if not 'image' in data:\n data['image'] = 'images/no_image.png'\nreturn data", "group = self.Meta.model(**validated_data)\ngroup.save()\nauthor = validated_data['author']\ngroup.members.add(author)\nreturn group" ]

GroupRegisterSerializer

[]

stack_v2_sparse_python_classes_v1

stack_v2_sparse_classes_10k_train_002393

6,287

no_license

[ { "docstring": "Checks to be sure that the received password and confirm_password fields are exactly the same", "name": "validate", "signature": "def validate(self, data)" }, { "docstring": "Creates the user if validation succeeds", "name": "create", "signature": "def create(self, valida...

2

stack_v2_sparse_classes_30k_train_006503

Implement the Python class `GroupRegisterSerializer` described below. Class description: Implement the GroupRegisterSerializer class. Method signatures and docstrings: - def validate(self, data): Checks to be sure that the received password and confirm_password fields are exactly the same - def create(self, validated...

db7582b75f1a3dea4468749912cccd15c9341436

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class GroupRegisterSerializer: def validate(self, data): """Checks to be sure that the received password and confirm_password fields are exactly the same""" if not 'image' in data: data['image'] = 'images/no_image.png' return data def create(self, validated_data): ""...

the_stack_v2_python_sparse

django_app/group/serializer/group.py

jmnghn/chming

train

0

daf7ce02d1a3d3a275d7e2a771f708388619e0df

[ "self.log.info('login from QQ')\ncode = context.get('code')\nredirect_uri = context.get('redirect_uri')\nif not code or not redirect_uri:\n return None\naccess_token = self.get_token(code, redirect_uri)\ninfo = self.get_info(access_token)\nuser_info = self.get_user_info(access_token, info['openid'], info['client...

<|body_start_0|> self.log.info('login from QQ') code = context.get('code') redirect_uri = context.get('redirect_uri') if not code or not redirect_uri: return None access_token = self.get_token(code, redirect_uri) info = self.get_info(access_token) user...

Sign in with QQ :Example: from client.user.login import QQLogin QQLogin() .. notes::

QQLogin

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class QQLogin: """Sign in with QQ :Example: from client.user.login import QQLogin QQLogin() .. notes::""" def login(self, context): """QQ Login :type context: Context :param context: :rtype: dict :return: token and instance of user""" <|body_0|> def get_token(self, code, redir...

stack_v2_sparse_classes_10k_train_002394

17,886

permissive

[ { "docstring": "QQ Login :type context: Context :param context: :rtype: dict :return: token and instance of user", "name": "login", "signature": "def login(self, context)" }, { "docstring": "Get qq access token :type code: str :param code: authorization code :type redirect_uri: str :param redire...

4

stack_v2_sparse_classes_30k_train_001970

Implement the Python class `QQLogin` described below. Class description: Sign in with QQ :Example: from client.user.login import QQLogin QQLogin() .. notes:: Method signatures and docstrings: - def login(self, context): QQ Login :type context: Context :param context: :rtype: dict :return: token and instance of user -...

945c4fd2755f5b0dea11e54eb649eeb37ec93d01

<|skeleton|> class QQLogin: """Sign in with QQ :Example: from client.user.login import QQLogin QQLogin() .. notes::""" def login(self, context): """QQ Login :type context: Context :param context: :rtype: dict :return: token and instance of user""" <|body_0|> def get_token(self, code, redir...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class QQLogin: """Sign in with QQ :Example: from client.user.login import QQLogin QQLogin() .. notes::""" def login(self, context): """QQ Login :type context: Context :param context: :rtype: dict :return: token and instance of user""" self.log.info('login from QQ') code = context.get('c...

the_stack_v2_python_sparse

open-hackathon-server/src/hackathon/user/oauth_login.py

kaiyuanshe/open-hackathon

train

46

79f1f9403e408b557a41330ebb7d2d08d8b3f800

[ "try:\n self.assertEqual(subtract(30, 16), 15)\nexcept Exception as error:\n print(f'Got error in {inspect.stack()[0][3]}, {error}')", "try:\n self.assertEqual(subtract(-18, -5), -13)\nexcept Exception as error:\n print(error)", "try:\n self.assertEqual(subtract(0, -6), 7)\nexcept Exception as er...

<|body_start_0|> try: self.assertEqual(subtract(30, 16), 15) except Exception as error: print(f'Got error in {inspect.stack()[0][3]}, {error}') <|end_body_0|> <|body_start_1|> try: self.assertEqual(subtract(-18, -5), -13) except Exception as error: ...

Test subtract function from calculation.py module.

TestSubtractFunction

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class TestSubtractFunction: """Test subtract function from calculation.py module.""" def test_subtract_all_args_greater_zero(self): """Test subtract function if all arguments are greater than zero.""" <|body_0|> def test_subtract_all_args_less_zero(self): """Test subtr...

stack_v2_sparse_classes_10k_train_002395

1,838

no_license

[ { "docstring": "Test subtract function if all arguments are greater than zero.", "name": "test_subtract_all_args_greater_zero", "signature": "def test_subtract_all_args_greater_zero(self)" }, { "docstring": "Test subtract function if all arguments are less than zero.", "name": "test_subtract...

3

stack_v2_sparse_classes_30k_test_000072

Implement the Python class `TestSubtractFunction` described below. Class description: Test subtract function from calculation.py module. Method signatures and docstrings: - def test_subtract_all_args_greater_zero(self): Test subtract function if all arguments are greater than zero. - def test_subtract_all_args_less_z...

3a500c9d55fecf4032b5faf59a1cbecf64592e9a

<|skeleton|> class TestSubtractFunction: """Test subtract function from calculation.py module.""" def test_subtract_all_args_greater_zero(self): """Test subtract function if all arguments are greater than zero.""" <|body_0|> def test_subtract_all_args_less_zero(self): """Test subtr...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class TestSubtractFunction: """Test subtract function from calculation.py module.""" def test_subtract_all_args_greater_zero(self): """Test subtract function if all arguments are greater than zero.""" try: self.assertEqual(subtract(30, 16), 15) except Exception as error: ...

the_stack_v2_python_sparse

python10/test_calculation.py

maksimok93/Dp-189

train

0

2299156860a1fd49c12de9c00453e6f7735567c6

[ "if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn LearningContent()", "from .entity import Entity\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'additionalTags': lambda n: setattr(self, 'additional_tags', n.get_collection_of_primitive_values(str)), 'contentW...

<|body_start_0|> if not parse_node: raise TypeError('parse_node cannot be null.') return LearningContent() <|end_body_0|> <|body_start_1|> from .entity import Entity from .entity import Entity fields: Dict[str, Callable[[Any], None]] = {'additionalTags': lambda n: se...

LearningContent

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class LearningContent: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningContent: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Ret...

stack_v2_sparse_classes_10k_train_002396

7,407

permissive

[ { "docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: LearningContent", "name": "create_from_discriminator_value", "signature": "def create_from_discriminator_val...

3

stack_v2_sparse_classes_30k_train_003160

Implement the Python class `LearningContent` described below. Class description: Implement the LearningContent class. Method signatures and docstrings: - def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningContent: Creates a new instance of the appropriate class based on discriminator...

27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949

<|skeleton|> class LearningContent: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningContent: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Ret...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class LearningContent: def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LearningContent: """Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Learning...

the_stack_v2_python_sparse

msgraph/generated/models/learning_content.py

microsoftgraph/msgraph-sdk-python

train

135

cb9c86f5e3f00ad8afaa3ec6519bd594a10e3fae

[ "variation_id = variation['_id']\nidentifier = valid_result.identifier\ntoken_type = valid_result.classification_token.token_type\ntoken_type_l = token_type.lower()\nvrs_ref_allele_seq = None\nif 'uncertain' in token_type_l:\n warnings = ['Ambiguous regions cannot be normalized']\nelif 'range' not in token_type_...

<|body_start_0|> variation_id = variation['_id'] identifier = valid_result.identifier token_type = valid_result.classification_token.token_type token_type_l = token_type.lower() vrs_ref_allele_seq = None if 'uncertain' in token_type_l: warnings = ['Ambiguous r...

Class for represnting VRSATILE objects

ToVRSATILE

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ToVRSATILE: """Class for represnting VRSATILE objects""" def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationDescriptor, List]: """Return variation descriptor and warning...

stack_v2_sparse_classes_10k_train_002397

3,637

permissive

[ { "docstring": "Return variation descriptor and warnings :param str label: Initial input query :param Dict variation: VRS variation object :param ValidationResult valid_result: Valid result for query :param str _id: _id field for variation descriptor :param List warnings: List of warnings :param Optional[str] g...

2

stack_v2_sparse_classes_30k_train_000770

Implement the Python class `ToVRSATILE` described below. Class description: Class for represnting VRSATILE objects Method signatures and docstrings: - def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationD...

4614e6dd0b3b5612d48f1e69be4e1476977aafba

<|skeleton|> class ToVRSATILE: """Class for represnting VRSATILE objects""" def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationDescriptor, List]: """Return variation descriptor and warning...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ToVRSATILE: """Class for represnting VRSATILE objects""" def get_variation_descriptor(self, label: str, variation: Dict, valid_result: ValidationResult, _id: str, warnings: List, gene: Optional[str]=None) -> Tuple[VariationDescriptor, List]: """Return variation descriptor and warnings :param str ...

the_stack_v2_python_sparse

variation/to_vrsatile.py

cancervariants/variation-normalization

train

4

a232274be705e3cfa03016d853a3c6eb22b30968

[ "if not spectator_apps.is_enabled('reading'):\n raise ImproperlyConfigured(\"To use the CreatorManager.by_publications() method, 'spectator.reading' must by in INSTALLED_APPS.\")\nqs = self.get_queryset()\nqs = qs.exclude(publications__reading__isnull=True).exclude(publications__reading__is_finished=False).annot...

<|body_start_0|> if not spectator_apps.is_enabled('reading'): raise ImproperlyConfigured("To use the CreatorManager.by_publications() method, 'spectator.reading' must by in INSTALLED_APPS.") qs = self.get_queryset() qs = qs.exclude(publications__reading__isnull=True).exclude(publicat...

CreatorManager

[ "MIT" ]

stack_v2_sparse_python_classes_v1

<|skeleton|> class CreatorManager: def by_publications(self): """The Creators who have been most-read, ordered by number of read publications (ignoring if any of those publicatinos have been read multiple times.) Each Creator will have a `num_publications` attribute.""" <|body_0|> def by_readi...

stack_v2_sparse_classes_10k_train_002398

4,128

permissive

[ { "docstring": "The Creators who have been most-read, ordered by number of read publications (ignoring if any of those publicatinos have been read multiple times.) Each Creator will have a `num_publications` attribute.", "name": "by_publications", "signature": "def by_publications(self)" }, { "d...

4

stack_v2_sparse_classes_30k_train_006379

Implement the Python class `CreatorManager` described below. Class description: Implement the CreatorManager class. Method signatures and docstrings: - def by_publications(self): The Creators who have been most-read, ordered by number of read publications (ignoring if any of those publicatinos have been read multiple...

2d89dcdb624b01452a5b6ca0ee092774fcc0aa52

<|skeleton|> class CreatorManager: def by_publications(self): """The Creators who have been most-read, ordered by number of read publications (ignoring if any of those publicatinos have been read multiple times.) Each Creator will have a `num_publications` attribute.""" <|body_0|> def by_readi...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class CreatorManager: def by_publications(self): """The Creators who have been most-read, ordered by number of read publications (ignoring if any of those publicatinos have been read multiple times.) Each Creator will have a `num_publications` attribute.""" if not spectator_apps.is_enabled('reading'...

the_stack_v2_python_sparse

spectator/core/managers.py

philgyford/django-spectator

train

45

fe1b68be12c5b5606e3c516dd1543be259d091e3

[ "data_list = []\nresults = self.query.all()\nformatter = self.request.locale.dates.getFormatter('date', 'short')\nfor result in results:\n data = {}\n data['qid'] = 'i-' + str(result.parliamentary_item_id)\n if type(result) == domain.AgendaItem:\n g = u' ' + result.group.type + u' ' + result.group.s...

<|body_start_0|> data_list = [] results = self.query.all() formatter = self.request.locale.dates.getFormatter('date', 'short') for result in results: data = {} data['qid'] = 'i-' + str(result.parliamentary_item_id) if type(result) == domain.AgendaItem:...

Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)

ItemInStageViewlet

[]

stack_v2_sparse_python_classes_v1

<|skeleton|> class ItemInStageViewlet: """Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)""" def getData(self): """return the data of the query""" <|body_0|> def update(self): """refresh the query""...

stack_v2_sparse_classes_10k_train_002399

35,739

no_license

[ { "docstring": "return the data of the query", "name": "getData", "signature": "def getData(self)" }, { "docstring": "refresh the query", "name": "update", "signature": "def update(self)" } ]

2

null

Implement the Python class `ItemInStageViewlet` described below. Class description: Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible) Method signatures and docstrings: - def getData(self): return the data of the query - def update(self)...

5cf0ba31dfbff8d2c1b4aa8ab6f69c7a0ae9870d

<|skeleton|> class ItemInStageViewlet: """Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)""" def getData(self): """return the data of the query""" <|body_0|> def update(self): """refresh the query""...

stack_v2_sparse_classes_10k

data/stack_v2_sparse_classes_30k

class ItemInStageViewlet: """Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)""" def getData(self): """return the data of the query""" data_list = [] results = self.query.all() formatter = self.re...

the_stack_v2_python_sparse

bungeni.buildout/branches/bungeni.buildout-refactor-2010-06-02/src/bungeni.main/bungeni/ui/viewlets/workspace.py

malangalanga/bungeni-portal

train

0