blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3d715a9906517175e9b55ec47ae2e3efe802548b | [
"if rowIndex <= 0:\n return []\ncur_row = []\nfor n in range(rowIndex + 1):\n new_row = [None for _ in range(n + 1)]\n new_row[0], new_row[-1] = (1, 1)\n for j in range(1, n):\n new_row[j] = cur_row[j - 1] + cur_row[j]\n cur_row = new_row\nreturn cur_row",
"res = [1]\nfor i in range(1, row_n... | <|body_start_0|>
if rowIndex <= 0:
return []
cur_row = []
for n in range(rowIndex + 1):
new_row = [None for _ in range(n + 1)]
new_row[0], new_row[-1] = (1, 1)
for j in range(1, n):
new_row[j] = cur_row[j - 1] + cur_row[j]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getRow(self, rowIndex: int):
"""根据给定的行数，生成杨辉三角该行元素。 :param rowIndex:杨辉三角的层数。 :return:"""
<|body_0|>
def getRow_2(self, row_nums):
"""根据给定行数返回杨辉三角该行元素。 相比上一方法的改进之处是复用了当前列。 以时间换空间。 :param row_nums: 给定行数 :return: res:list 该行元素"""
<|body_1|>
de... | stack_v2_sparse_classes_36k_train_028400 | 2,416 | no_license | [
{
"docstring": "根据给定的行数，生成杨辉三角该行元素。 :param rowIndex:杨辉三角的层数。 :return:",
"name": "getRow",
"signature": "def getRow(self, rowIndex: int)"
},
{
"docstring": "根据给定行数返回杨辉三角该行元素。 相比上一方法的改进之处是复用了当前列。 以时间换空间。 :param row_nums: 给定行数 :return: res:list 该行元素",
"name": "getRow_2",
"signature": "def g... | 3 | stack_v2_sparse_classes_30k_train_019775 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getRow(self, rowIndex: int): 根据给定的行数，生成杨辉三角该行元素。 :param rowIndex:杨辉三角的层数。 :return:
- def getRow_2(self, row_nums): 根据给定行数返回杨辉三角该行元素。 相比上一方法的改进之处是复用了当前列。 以时间换空间。 :param row_nu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getRow(self, rowIndex: int): 根据给定的行数，生成杨辉三角该行元素。 :param rowIndex:杨辉三角的层数。 :return:
- def getRow_2(self, row_nums): 根据给定行数返回杨辉三角该行元素。 相比上一方法的改进之处是复用了当前列。 以时间换空间。 :param row_nu... | 62ad010a992c031e8c0fe4d1a9b6f9364f96ed4c | <|skeleton|>
class Solution:
def getRow(self, rowIndex: int):
"""根据给定的行数，生成杨辉三角该行元素。 :param rowIndex:杨辉三角的层数。 :return:"""
<|body_0|>
def getRow_2(self, row_nums):
"""根据给定行数返回杨辉三角该行元素。 相比上一方法的改进之处是复用了当前列。 以时间换空间。 :param row_nums: 给定行数 :return: res:list 该行元素"""
<|body_1|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def getRow(self, rowIndex: int):
"""根据给定的行数，生成杨辉三角该行元素。 :param rowIndex:杨辉三角的层数。 :return:"""
if rowIndex <= 0:
return []
cur_row = []
for n in range(rowIndex + 1):
new_row = [None for _ in range(n + 1)]
new_row[0], new_row[-1] = (1,... | the_stack_v2_python_sparse | leetcode/solved/119_.py | usnnu/python_foundation | train | 0 | |
936b76be550bf0940c281e860949bb51e2b1f8ad | [
"self.logger = logger\nself.is_trained = False\nself.supported_formats = ['pkl', 'onnx', 'pmml']\nself.name = 'Kmeans'\nself.centroids = None",
"dists = dists = np.sqrt(np.abs(-2 * np.dot(self.centroids, X_b.T) + np.sum(X_b ** 2, axis=1) + np.sum(self.centroids ** 2, axis=1)[:, np.newaxis]))\nmin_dists = np.min(d... | <|body_start_0|>
self.logger = logger
self.is_trained = False
self.supported_formats = ['pkl', 'onnx', 'pmml']
self.name = 'Kmeans'
self.centroids = None
<|end_body_0|>
<|body_start_1|>
dists = dists = np.sqrt(np.abs(-2 * np.dot(self.centroids, X_b.T) + np.sum(X_b ** 2, ... | This class contains the Kmeans model. | Kmeans_model | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Kmeans_model:
"""This class contains the Kmeans model."""
def __init__(self, logger):
"""Create a :class:`Kmeans_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance."""
<|body_0|>
def predict(self, X_b):
"""Uses the Km... | stack_v2_sparse_classes_36k_train_028401 | 23,712 | permissive | [
{
"docstring": "Create a :class:`Kmeans_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance.",
"name": "__init__",
"signature": "def __init__(self, logger)"
},
{
"docstring": "Uses the Kmeans model to predict new outputs given the inputs. Parameters -... | 2 | stack_v2_sparse_classes_30k_val_000755 | Implement the Python class `Kmeans_model` described below.
Class description:
This class contains the Kmeans model.
Method signatures and docstrings:
- def __init__(self, logger): Create a :class:`Kmeans_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance.
- def predict(se... | Implement the Python class `Kmeans_model` described below.
Class description:
This class contains the Kmeans model.
Method signatures and docstrings:
- def __init__(self, logger): Create a :class:`Kmeans_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance.
- def predict(se... | ccc0a7674a04ae0d00bedc38893b33184c5f68c6 | <|skeleton|>
class Kmeans_model:
"""This class contains the Kmeans model."""
def __init__(self, logger):
"""Create a :class:`Kmeans_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance."""
<|body_0|>
def predict(self, X_b):
"""Uses the Km... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Kmeans_model:
"""This class contains the Kmeans model."""
def __init__(self, logger):
"""Create a :class:`Kmeans_model` instance. Parameters ---------- logger: :class:`mylogging.Logger` Logging object instance."""
self.logger = logger
self.is_trained = False
self.supported... | the_stack_v2_python_sparse | MMLL/models/POM3/Kmeans/Kmeans.py | Musketeer-H2020/MMLL-Robust | train | 0 |
5159b0301198e69b3831e1e7d9e740a5defbcf32 | [
"data = base_importData()\ndata.read_csv(filename)\ndata.format_data()\nself.add_calibratorConcentrations(data.data)\ndata.clear_data()",
"data_O = []\nif met_ids_I:\n met_ids = met_ids_I\nelse:\n met_ids = []\n met_ids = self.get_metIDs_calibratorConcentrations()\nfor met_id in met_ids:\n rows = []\n... | <|body_start_0|>
data = base_importData()
data.read_csv(filename)
data.format_data()
self.add_calibratorConcentrations(data.data)
data.clear_data()
<|end_body_0|>
<|body_start_1|>
data_O = []
if met_ids_I:
met_ids = met_ids_I
else:
... | lims_calibratorsAndMixes_io | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class lims_calibratorsAndMixes_io:
def import_calibratorConcentrations_add(self, filename):
"""table adds"""
<|body_0|>
def export_calibratorConcentrations_csv(self, filename, met_ids_I=[]):
"""export calibrator concentrations"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_028402 | 1,217 | permissive | [
{
"docstring": "table adds",
"name": "import_calibratorConcentrations_add",
"signature": "def import_calibratorConcentrations_add(self, filename)"
},
{
"docstring": "export calibrator concentrations",
"name": "export_calibratorConcentrations_csv",
"signature": "def export_calibratorConce... | 2 | stack_v2_sparse_classes_30k_train_010161 | Implement the Python class `lims_calibratorsAndMixes_io` described below.
Class description:
Implement the lims_calibratorsAndMixes_io class.
Method signatures and docstrings:
- def import_calibratorConcentrations_add(self, filename): table adds
- def export_calibratorConcentrations_csv(self, filename, met_ids_I=[]):... | Implement the Python class `lims_calibratorsAndMixes_io` described below.
Class description:
Implement the lims_calibratorsAndMixes_io class.
Method signatures and docstrings:
- def import_calibratorConcentrations_add(self, filename): table adds
- def export_calibratorConcentrations_csv(self, filename, met_ids_I=[]):... | 5dfd73689674953345d523178a67b8dda10e6d47 | <|skeleton|>
class lims_calibratorsAndMixes_io:
def import_calibratorConcentrations_add(self, filename):
"""table adds"""
<|body_0|>
def export_calibratorConcentrations_csv(self, filename, met_ids_I=[]):
"""export calibrator concentrations"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class lims_calibratorsAndMixes_io:
def import_calibratorConcentrations_add(self, filename):
"""table adds"""
data = base_importData()
data.read_csv(filename)
data.format_data()
self.add_calibratorConcentrations(data.data)
data.clear_data()
def export_calibratorCo... | the_stack_v2_python_sparse | SBaaS_LIMS/lims_calibratorsAndMixes_io.py | dmccloskey/SBaaS_LIMS | train | 0 | |
da3adc973fbca8c76783c53a490c50de6462e53d | [
"self.characters = characters\nself.combinationLength = combinationLength\nself.position = 0\nself.gene = list(combinations(characters, combinationLength))",
"res = self.gene[self.position]\nansw = ''\nfor obj in res:\n answ += obj\nself.position += 1\nreturn answ",
"if self.position <= len(self.gene) - 1:\n... | <|body_start_0|>
self.characters = characters
self.combinationLength = combinationLength
self.position = 0
self.gene = list(combinations(characters, combinationLength))
<|end_body_0|>
<|body_start_1|>
res = self.gene[self.position]
answ = ''
for obj in res:
... | CombinationIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CombinationIterator:
def __init__(self, characters: str, combinationLength: int):
"""A constructor that takes a string characters of sorted distinct lowercase English letters and a number combinationLength as arguments."""
<|body_0|>
def next(self) -> str:
"""A funct... | stack_v2_sparse_classes_36k_train_028403 | 1,447 | no_license | [
{
"docstring": "A constructor that takes a string characters of sorted distinct lowercase English letters and a number combinationLength as arguments.",
"name": "__init__",
"signature": "def __init__(self, characters: str, combinationLength: int)"
},
{
"docstring": "A function next() that return... | 3 | null | Implement the Python class `CombinationIterator` described below.
Class description:
Implement the CombinationIterator class.
Method signatures and docstrings:
- def __init__(self, characters: str, combinationLength: int): A constructor that takes a string characters of sorted distinct lowercase English letters and a... | Implement the Python class `CombinationIterator` described below.
Class description:
Implement the CombinationIterator class.
Method signatures and docstrings:
- def __init__(self, characters: str, combinationLength: int): A constructor that takes a string characters of sorted distinct lowercase English letters and a... | 9a960a9cc193e724696016aebbe5a55bdf5422f4 | <|skeleton|>
class CombinationIterator:
def __init__(self, characters: str, combinationLength: int):
"""A constructor that takes a string characters of sorted distinct lowercase English letters and a number combinationLength as arguments."""
<|body_0|>
def next(self) -> str:
"""A funct... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CombinationIterator:
def __init__(self, characters: str, combinationLength: int):
"""A constructor that takes a string characters of sorted distinct lowercase English letters and a number combinationLength as arguments."""
self.characters = characters
self.combinationLength = combinati... | the_stack_v2_python_sparse | contests2019/Leetcode20191214biweekly/IteratorClass.py | BradleyPelton/Leetcode-Solutions | train | 1 | |
3eb7607bc9f8e763415a3290bcb21389307eaf27 | [
"shell = eii.Parameter('shell')\ndialogCaption = 'Capture rejection reason'\ninitialComment = 'My reason for rejecting the authorization process.'\nreason = acm.UX().Dialogs().GetTextInput(shell, dialogCaption, initialComment)\nif reason and len(reason) > 0:\n parameters = acm.FDictionary()\n parameters.AtPut... | <|body_start_0|>
shell = eii.Parameter('shell')
dialogCaption = 'Capture rejection reason'
initialComment = 'My reason for rejecting the authorization process.'
reason = acm.UX().Dialogs().GetTextInput(shell, dialogCaption, initialComment)
if reason and len(reason) > 0:
... | MenuItem on Business Process Sheet used to view a historical version of a specific breached mandate. | DenyMandateMenuItem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DenyMandateMenuItem:
"""MenuItem on Business Process Sheet used to view a historical version of a specific breached mandate."""
def _Deny(self, eii):
"""Deny the mandate. This method captures the reason why the user denied / rejected the specific mandate. It pops up a display prompti... | stack_v2_sparse_classes_36k_train_028404 | 27,405 | no_license | [
{
"docstring": "Deny the mandate. This method captures the reason why the user denied / rejected the specific mandate. It pops up a display prompting the user to capture a comment. :param eii: FExtensionInvokationInfo",
"name": "_Deny",
"signature": "def _Deny(self, eii)"
},
{
"docstring": "OnCl... | 4 | null | Implement the Python class `DenyMandateMenuItem` described below.
Class description:
MenuItem on Business Process Sheet used to view a historical version of a specific breached mandate.
Method signatures and docstrings:
- def _Deny(self, eii): Deny the mandate. This method captures the reason why the user denied / re... | Implement the Python class `DenyMandateMenuItem` described below.
Class description:
MenuItem on Business Process Sheet used to view a historical version of a specific breached mandate.
Method signatures and docstrings:
- def _Deny(self, eii): Deny the mandate. This method captures the reason why the user denied / re... | 5e7cc7de3495145501ca53deb9efee2233ab7e1c | <|skeleton|>
class DenyMandateMenuItem:
"""MenuItem on Business Process Sheet used to view a historical version of a specific breached mandate."""
def _Deny(self, eii):
"""Deny the mandate. This method captures the reason why the user denied / rejected the specific mandate. It pops up a display prompti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DenyMandateMenuItem:
"""MenuItem on Business Process Sheet used to view a historical version of a specific breached mandate."""
def _Deny(self, eii):
"""Deny the mandate. This method captures the reason why the user denied / rejected the specific mandate. It pops up a display prompting the user t... | the_stack_v2_python_sparse | Extensions/GenericMandates/FPythonCode/GenericMandatesMenu.py | webclinic017/fa-absa-py3 | train | 0 |
eebdc26acca3c256d2e89eda60bb90bbf6538125 | [
"super(AllImageLSTM, self).__init__()\nargs.wrap_model = False\nself.args = args\nself.lstm = nn.LSTM(input_size=args.hidden_dim, hidden_size=args.hidden_dim // 2, num_layers=1, bias=True, batch_first=True, dropout=args.dropout, bidirectional=True)\nself.view_bn = nn.BatchNorm1d(args.hidden_dim * 2)\nself.view_fc =... | <|body_start_0|>
super(AllImageLSTM, self).__init__()
args.wrap_model = False
self.args = args
self.lstm = nn.LSTM(input_size=args.hidden_dim, hidden_size=args.hidden_dim // 2, num_layers=1, bias=True, batch_first=True, dropout=args.dropout, bidirectional=True)
self.view_bn = nn.... | AllImageLSTM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllImageLSTM:
def __init__(self, args):
"""Given some a patch model, add add some FC layers and a shortcut to make whole image prediction"""
<|body_0|>
def forward(self, x):
"""param x: a batch of image tensors, in the order of: [Cu L CC, Pr L CC, Cu L MLO, Pr L MLO,... | stack_v2_sparse_classes_36k_train_028405 | 5,214 | permissive | [
{
"docstring": "Given some a patch model, add add some FC layers and a shortcut to make whole image prediction",
"name": "__init__",
"signature": "def __init__(self, args)"
},
{
"docstring": "param x: a batch of image tensors, in the order of: [Cu L CC, Pr L CC, Cu L MLO, Pr L MLO, Cu R CC, Pr R... | 2 | stack_v2_sparse_classes_30k_train_014167 | Implement the Python class `AllImageLSTM` described below.
Class description:
Implement the AllImageLSTM class.
Method signatures and docstrings:
- def __init__(self, args): Given some a patch model, add add some FC layers and a shortcut to make whole image prediction
- def forward(self, x): param x: a batch of image... | Implement the Python class `AllImageLSTM` described below.
Class description:
Implement the AllImageLSTM class.
Method signatures and docstrings:
- def __init__(self, args): Given some a patch model, add add some FC layers and a shortcut to make whole image prediction
- def forward(self, x): param x: a batch of image... | 12bace8fd6ce9c5bb129fd0d30a46a00a2f7b054 | <|skeleton|>
class AllImageLSTM:
def __init__(self, args):
"""Given some a patch model, add add some FC layers and a shortcut to make whole image prediction"""
<|body_0|>
def forward(self, x):
"""param x: a batch of image tensors, in the order of: [Cu L CC, Pr L CC, Cu L MLO, Pr L MLO,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AllImageLSTM:
def __init__(self, args):
"""Given some a patch model, add add some FC layers and a shortcut to make whole image prediction"""
super(AllImageLSTM, self).__init__()
args.wrap_model = False
self.args = args
self.lstm = nn.LSTM(input_size=args.hidden_dim, hid... | the_stack_v2_python_sparse | onconet/models/aggregate_hiddens.py | yala/Mirai | train | 66 | |
bdf40f88103183110b6408bd9b2b330427601a58 | [
"self.right_now = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')\nself.new_logs_folder_name = 'logs_' + self.right_now\nself.project_logs_folder_path = os.getcwd()\nself.project_root_dir = os.path.abspath(os.pardir)\nself.project_results_folder_path = os.path.join(self.project_root_dir, 'results')\nself.new_logs... | <|body_start_0|>
self.right_now = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
self.new_logs_folder_name = 'logs_' + self.right_now
self.project_logs_folder_path = os.getcwd()
self.project_root_dir = os.path.abspath(os.pardir)
self.project_results_folder_path = os.path.join(... | Class definition | GatherAllLogFiles | [
"LicenseRef-scancode-other-permissive"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GatherAllLogFiles:
"""Class definition"""
def __init__(self):
"""Constructor"""
<|body_0|>
def _copy_result_logs(self, result_root, dst_folder):
"""Helper function for copying"""
<|body_1|>
def populate_lists(self):
"""make lists of the file ... | stack_v2_sparse_classes_36k_train_028406 | 7,726 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Helper function for copying",
"name": "_copy_result_logs",
"signature": "def _copy_result_logs(self, result_root, dst_folder)"
},
{
"docstring": "make lists of the file paths to... | 5 | null | Implement the Python class `GatherAllLogFiles` described below.
Class description:
Class definition
Method signatures and docstrings:
- def __init__(self): Constructor
- def _copy_result_logs(self, result_root, dst_folder): Helper function for copying
- def populate_lists(self): make lists of the file paths to be cop... | Implement the Python class `GatherAllLogFiles` described below.
Class description:
Class definition
Method signatures and docstrings:
- def __init__(self): Constructor
- def _copy_result_logs(self, result_root, dst_folder): Helper function for copying
- def populate_lists(self): make lists of the file paths to be cop... | bc7a05e04c7901f477fe553c59e478a837116d92 | <|skeleton|>
class GatherAllLogFiles:
"""Class definition"""
def __init__(self):
"""Constructor"""
<|body_0|>
def _copy_result_logs(self, result_root, dst_folder):
"""Helper function for copying"""
<|body_1|>
def populate_lists(self):
"""make lists of the file ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GatherAllLogFiles:
"""Class definition"""
def __init__(self):
"""Constructor"""
self.right_now = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
self.new_logs_folder_name = 'logs_' + self.right_now
self.project_logs_folder_path = os.getcwd()
self.project_root_dir... | the_stack_v2_python_sparse | src/CyPhyMasterInterpreter/Resources/gather_all_logfiles.py | metamorph-inc/meta-core | train | 25 |
df2f2f5a5d5565089a18aa43077b99ef08dce518 | [
"self.atr = list(atr)\nself.mask = mask\nif mask is None:\n self.maskedatr = self.atr\nelse:\n if len(self.atr) != len(self.mask):\n raise InvalidATRMaskLengthException(toHexString(mask))\n self.maskedatr = list(map(lambda x, y: x & y, self.atr, self.mask))",
"if len(atr) != len(self.atr):\n re... | <|body_start_0|>
self.atr = list(atr)
self.mask = mask
if mask is None:
self.maskedatr = self.atr
else:
if len(self.atr) != len(self.mask):
raise InvalidATRMaskLengthException(toHexString(mask))
self.maskedatr = list(map(lambda x, y: x ... | The ATRCardType defines a card from an ATR and a mask. | ATRCardType | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ATRCardType:
"""The ATRCardType defines a card from an ATR and a mask."""
def __init__(self, atr, mask=None):
"""ATRCardType constructor. @param atr: the ATR of the CardType @param mask: an optional mask to be applied to the ATR for L{CardType} matching default is None"""
<|b... | stack_v2_sparse_classes_36k_train_028407 | 3,654 | permissive | [
{
"docstring": "ATRCardType constructor. @param atr: the ATR of the CardType @param mask: an optional mask to be applied to the ATR for L{CardType} matching default is None",
"name": "__init__",
"signature": "def __init__(self, atr, mask=None)"
},
{
"docstring": "Returns true if the atr matches ... | 2 | stack_v2_sparse_classes_30k_train_016084 | Implement the Python class `ATRCardType` described below.
Class description:
The ATRCardType defines a card from an ATR and a mask.
Method signatures and docstrings:
- def __init__(self, atr, mask=None): ATRCardType constructor. @param atr: the ATR of the CardType @param mask: an optional mask to be applied to the AT... | Implement the Python class `ATRCardType` described below.
Class description:
The ATRCardType defines a card from an ATR and a mask.
Method signatures and docstrings:
- def __init__(self, atr, mask=None): ATRCardType constructor. @param atr: the ATR of the CardType @param mask: an optional mask to be applied to the AT... | a145345f9bb91bccb2bd67b349af8cfc4ec9e290 | <|skeleton|>
class ATRCardType:
"""The ATRCardType defines a card from an ATR and a mask."""
def __init__(self, atr, mask=None):
"""ATRCardType constructor. @param atr: the ATR of the CardType @param mask: an optional mask to be applied to the ATR for L{CardType} matching default is None"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ATRCardType:
"""The ATRCardType defines a card from an ATR and a mask."""
def __init__(self, atr, mask=None):
"""ATRCardType constructor. @param atr: the ATR of the CardType @param mask: an optional mask to be applied to the ATR for L{CardType} matching default is None"""
self.atr = list(... | the_stack_v2_python_sparse | EnrollmentStation/Binaries/YubikeyManager/pymodules/smartcard/CardType.py | jnsgsbz/EnrollmentStation | train | 2 |
1c2ceb54816dc8b38c3d2bf30b5f3a6eeef95a93 | [
"if len(A) <= 0:\n return 0\nans_max_L = 0\nres_L = {}\nans_max_M = 0\nfor i in range(len(A) - L + 1):\n val = sum(A[i:i + L])\n if val > ans_max_L:\n ans_max_L = val\n res_L[val] = i\nindex_L = res_L.get(ans_max_L)\nA = A[0:index_L] + A[index_L + L:]\nfor j in range(len(A) - M + 1):\n val... | <|body_start_0|>
if len(A) <= 0:
return 0
ans_max_L = 0
res_L = {}
ans_max_M = 0
for i in range(len(A) - L + 1):
val = sum(A[i:i + L])
if val > ans_max_L:
ans_max_L = val
res_L[val] = i
index_L = res_L.ge... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSumTwoNoOverlap(self, A, L, M):
"""wrong--局部最优，要找的是两个子序列的和最优 :type A: List[int] :type L: int :type M: int :rtype: int"""
<|body_0|>
def maxSumTwoNoOverlap1(self, A, L, M):
"""use DP step1:find cursum of A step2:two case about location of maxL & maxM-... | stack_v2_sparse_classes_36k_train_028408 | 1,893 | no_license | [
{
"docstring": "wrong--局部最优，要找的是两个子序列的和最优 :type A: List[int] :type L: int :type M: int :rtype: int",
"name": "maxSumTwoNoOverlap",
"signature": "def maxSumTwoNoOverlap(self, A, L, M)"
},
{
"docstring": "use DP step1:find cursum of A step2:two case about location of maxL & maxM--- one possible ca... | 2 | stack_v2_sparse_classes_30k_train_009782 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSumTwoNoOverlap(self, A, L, M): wrong--局部最优，要找的是两个子序列的和最优 :type A: List[int] :type L: int :type M: int :rtype: int
- def maxSumTwoNoOverlap1(self, A, L, M): use DP step1:f... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSumTwoNoOverlap(self, A, L, M): wrong--局部最优，要找的是两个子序列的和最优 :type A: List[int] :type L: int :type M: int :rtype: int
- def maxSumTwoNoOverlap1(self, A, L, M): use DP step1:f... | 18c06a96bb14688e4a1d5fb6baf235a6b53bd3ae | <|skeleton|>
class Solution:
def maxSumTwoNoOverlap(self, A, L, M):
"""wrong--局部最优，要找的是两个子序列的和最优 :type A: List[int] :type L: int :type M: int :rtype: int"""
<|body_0|>
def maxSumTwoNoOverlap1(self, A, L, M):
"""use DP step1:find cursum of A step2:two case about location of maxL & maxM-... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSumTwoNoOverlap(self, A, L, M):
"""wrong--局部最优，要找的是两个子序列的和最优 :type A: List[int] :type L: int :type M: int :rtype: int"""
if len(A) <= 0:
return 0
ans_max_L = 0
res_L = {}
ans_max_M = 0
for i in range(len(A) - L + 1):
val ... | the_stack_v2_python_sparse | medium/others/maximum-sum-of-two-non-overlapping-subarrays.py | congyingTech/Basic-Algorithm | train | 10 | |
1685004e4fc9ab680723247e09eea555598ad07c | [
"common_templates_dir: Text = os.path.abspath(os.path.dirname(os.path.realpath(__file__)) + os.sep + '..' + os.sep + 'templates')\ntemplates: List = list()\nif isinstance(templates_dir, list):\n templates.extend(templates_dir)\n templates.append(common_templates_dir)\nelse:\n templates.append(templates_dir... | <|body_start_0|>
common_templates_dir: Text = os.path.abspath(os.path.dirname(os.path.realpath(__file__)) + os.sep + '..' + os.sep + 'templates')
templates: List = list()
if isinstance(templates_dir, list):
templates.extend(templates_dir)
templates.append(common_templates... | Class for writing files based on Jinja2 templates. | Jinja2TemplateRenderer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Jinja2TemplateRenderer:
"""Class for writing files based on Jinja2 templates."""
def __init__(self, templates_dir: Union[Text, List]='templates') -> None:
"""Constructor for Jinja2TemplateRenderer. :param templates_dir: The directory containing templates."""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_028409 | 3,297 | permissive | [
{
"docstring": "Constructor for Jinja2TemplateRenderer. :param templates_dir: The directory containing templates.",
"name": "__init__",
"signature": "def __init__(self, templates_dir: Union[Text, List]='templates') -> None"
},
{
"docstring": "Renders and writes html templates. :param template_na... | 2 | stack_v2_sparse_classes_30k_train_003951 | Implement the Python class `Jinja2TemplateRenderer` described below.
Class description:
Class for writing files based on Jinja2 templates.
Method signatures and docstrings:
- def __init__(self, templates_dir: Union[Text, List]='templates') -> None: Constructor for Jinja2TemplateRenderer. :param templates_dir: The dir... | Implement the Python class `Jinja2TemplateRenderer` described below.
Class description:
Class for writing files based on Jinja2 templates.
Method signatures and docstrings:
- def __init__(self, templates_dir: Union[Text, List]='templates') -> None: Constructor for Jinja2TemplateRenderer. :param templates_dir: The dir... | eac1deadc0fe793539e24d5843d4ab552bab833b | <|skeleton|>
class Jinja2TemplateRenderer:
"""Class for writing files based on Jinja2 templates."""
def __init__(self, templates_dir: Union[Text, List]='templates') -> None:
"""Constructor for Jinja2TemplateRenderer. :param templates_dir: The directory containing templates."""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Jinja2TemplateRenderer:
"""Class for writing files based on Jinja2 templates."""
def __init__(self, templates_dir: Union[Text, List]='templates') -> None:
"""Constructor for Jinja2TemplateRenderer. :param templates_dir: The directory containing templates."""
common_templates_dir: Text = o... | the_stack_v2_python_sparse | viya_ark_library/jinja2/sas_jinja2.py | framhc/viya4-ark | train | 0 |
fab05cb37308ede0c4fd5f4b37a5b98ae5487725 | [
"if not str_A:\n return 0\nstr_A = str_A.strip()\nstr_arr = list(str_A)\nres = []\nflag = 1\nfor ind, val in enumerate(str_arr):\n if val == '+' and ind == 0:\n flag = 1\n continue\n if val == '-' and ind == 0:\n flag = -1\n continue\n if val in [str(i) for i in list(range(0,... | <|body_start_0|>
if not str_A:
return 0
str_A = str_A.strip()
str_arr = list(str_A)
res = []
flag = 1
for ind, val in enumerate(str_arr):
if val == '+' and ind == 0:
flag = 1
continue
if val == '-' and in... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def myAtoi(self, str_A):
""":type str: str :rtype: int"""
<|body_0|>
def myAtoi2(self, s):
""":type str: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not str_A:
return 0
str_A = str_A.strip()
... | stack_v2_sparse_classes_36k_train_028410 | 2,304 | no_license | [
{
"docstring": ":type str: str :rtype: int",
"name": "myAtoi",
"signature": "def myAtoi(self, str_A)"
},
{
"docstring": ":type str: str :rtype: int",
"name": "myAtoi2",
"signature": "def myAtoi2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myAtoi(self, str_A): :type str: str :rtype: int
- def myAtoi2(self, s): :type str: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myAtoi(self, str_A): :type str: str :rtype: int
- def myAtoi2(self, s): :type str: str :rtype: int
<|skeleton|>
class Solution:
def myAtoi(self, str_A):
""":typ... | beabfd31379f44ffd767fc676912db5022495b53 | <|skeleton|>
class Solution:
def myAtoi(self, str_A):
""":type str: str :rtype: int"""
<|body_0|>
def myAtoi2(self, s):
""":type str: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def myAtoi(self, str_A):
""":type str: str :rtype: int"""
if not str_A:
return 0
str_A = str_A.strip()
str_arr = list(str_A)
res = []
flag = 1
for ind, val in enumerate(str_arr):
if val == '+' and ind == 0:
... | the_stack_v2_python_sparse | leetCode/top50/008StringtoInteger.py | fatezy/Algorithm | train | 1 | |
c91b5275a9fe06c4aea878982c9309ba23598782 | [
"self.obj = obj\nfor arg in alias_names:\n self.register_key(arg)",
"if isinstance(key, str):\n key = sys.intern(key)\nself[key] = self.obj"
] | <|body_start_0|>
self.obj = obj
for arg in alias_names:
self.register_key(arg)
<|end_body_0|>
<|body_start_1|>
if isinstance(key, str):
key = sys.intern(key)
self[key] = self.obj
<|end_body_1|>
| AliasDict | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AliasDict:
def __init__(self, alias_names: Iterable[Hashable], obj: object) -> None:
"""AliasDict Create a dictionary of pointers to an object Args: alias_names (Iterable[Hashable]): keys to be used, assumed to be immutable i.e. hashable obj (object): object the keys must point to"""
... | stack_v2_sparse_classes_36k_train_028411 | 1,034 | no_license | [
{
"docstring": "AliasDict Create a dictionary of pointers to an object Args: alias_names (Iterable[Hashable]): keys to be used, assumed to be immutable i.e. hashable obj (object): object the keys must point to",
"name": "__init__",
"signature": "def __init__(self, alias_names: Iterable[Hashable], obj: o... | 2 | stack_v2_sparse_classes_30k_train_021432 | Implement the Python class `AliasDict` described below.
Class description:
Implement the AliasDict class.
Method signatures and docstrings:
- def __init__(self, alias_names: Iterable[Hashable], obj: object) -> None: AliasDict Create a dictionary of pointers to an object Args: alias_names (Iterable[Hashable]): keys to... | Implement the Python class `AliasDict` described below.
Class description:
Implement the AliasDict class.
Method signatures and docstrings:
- def __init__(self, alias_names: Iterable[Hashable], obj: object) -> None: AliasDict Create a dictionary of pointers to an object Args: alias_names (Iterable[Hashable]): keys to... | c8690379dd9ca383cf3257a281094e4851677faa | <|skeleton|>
class AliasDict:
def __init__(self, alias_names: Iterable[Hashable], obj: object) -> None:
"""AliasDict Create a dictionary of pointers to an object Args: alias_names (Iterable[Hashable]): keys to be used, assumed to be immutable i.e. hashable obj (object): object the keys must point to"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AliasDict:
def __init__(self, alias_names: Iterable[Hashable], obj: object) -> None:
"""AliasDict Create a dictionary of pointers to an object Args: alias_names (Iterable[Hashable]): keys to be used, assumed to be immutable i.e. hashable obj (object): object the keys must point to"""
self.obj ... | the_stack_v2_python_sparse | pymethods/utils/alias_dict.py | IFF-0303/pymethods | train | 0 | |
2eb0c0e123dd47ece3e80d85d120740c1320289d | [
"study_id = filter_params.pop('study_id', None)\nq = ReadGroupGenomicFile.query.filter_by(**filter_params)\nfrom dataservice.api.participant.models import Participant\nfrom dataservice.api.biospecimen.models import Biospecimen\nfrom dataservice.api.genomic_file.models import GenomicFile\nfrom dataservice.api.biospe... | <|body_start_0|>
study_id = filter_params.pop('study_id', None)
q = ReadGroupGenomicFile.query.filter_by(**filter_params)
from dataservice.api.participant.models import Participant
from dataservice.api.biospecimen.models import Biospecimen
from dataservice.api.genomic_file.models... | ReadGroupGenomicFile List API | ReadGroupGenomicFileListAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadGroupGenomicFileListAPI:
"""ReadGroupGenomicFile List API"""
def get(self, filter_params, after, limit):
"""Get a paginated read_group_genomic_files --- template: path: get_list.yml properties: resource: ReadGroupGenomicFile"""
<|body_0|>
def post(self):
"""C... | stack_v2_sparse_classes_36k_train_028412 | 5,383 | permissive | [
{
"docstring": "Get a paginated read_group_genomic_files --- template: path: get_list.yml properties: resource: ReadGroupGenomicFile",
"name": "get",
"signature": "def get(self, filter_params, after, limit)"
},
{
"docstring": "Create a new read_group_genomic_file --- template: path: new_resource... | 2 | null | Implement the Python class `ReadGroupGenomicFileListAPI` described below.
Class description:
ReadGroupGenomicFile List API
Method signatures and docstrings:
- def get(self, filter_params, after, limit): Get a paginated read_group_genomic_files --- template: path: get_list.yml properties: resource: ReadGroupGenomicFil... | Implement the Python class `ReadGroupGenomicFileListAPI` described below.
Class description:
ReadGroupGenomicFile List API
Method signatures and docstrings:
- def get(self, filter_params, after, limit): Get a paginated read_group_genomic_files --- template: path: get_list.yml properties: resource: ReadGroupGenomicFil... | 36ee3fc3d1ba9d1a177274d051fb175c56dd898e | <|skeleton|>
class ReadGroupGenomicFileListAPI:
"""ReadGroupGenomicFile List API"""
def get(self, filter_params, after, limit):
"""Get a paginated read_group_genomic_files --- template: path: get_list.yml properties: resource: ReadGroupGenomicFile"""
<|body_0|>
def post(self):
"""C... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReadGroupGenomicFileListAPI:
"""ReadGroupGenomicFile List API"""
def get(self, filter_params, after, limit):
"""Get a paginated read_group_genomic_files --- template: path: get_list.yml properties: resource: ReadGroupGenomicFile"""
study_id = filter_params.pop('study_id', None)
q ... | the_stack_v2_python_sparse | dataservice/api/read_group_genomic_file/resources.py | kids-first/kf-api-dataservice | train | 9 |
53db8120db5decfdf113fa370870572bbbbadc84 | [
"ne_ref = [] if ne_ref is None else ne_ref\njson = {'name': name, 'ne_ref': ne_ref, 'operator': operator}\nreturn json",
"sub_expression = [] if sub_expression is None else [sub_expression]\njson = {'name': name, 'operator': operator, 'ne_ref': ne_ref, 'sub_expression': sub_expression, 'comment': comment}\nreturn... | <|body_start_0|>
ne_ref = [] if ne_ref is None else ne_ref
json = {'name': name, 'ne_ref': ne_ref, 'operator': operator}
return json
<|end_body_0|>
<|body_start_1|>
sub_expression = [] if sub_expression is None else [sub_expression]
json = {'name': name, 'operator': operator, 'n... | Expressions are used to build boolean like objects used in policy. For example, if you wanted to create an expression that negates a specific set of network elements to use in a "NOT" rule, an expression would be the element type. For example, adding a rule that negates (network A or network B):: sub_expression = Expre... | Expression | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Expression:
"""Expressions are used to build boolean like objects used in policy. For example, if you wanted to create an expression that negates a specific set of network elements to use in a "NOT" rule, an expression would be the element type. For example, adding a rule that negates (network A ... | stack_v2_sparse_classes_36k_train_028413 | 24,780 | permissive | [
{
"docstring": "Static method to build and return the proper json for a sub-expression. A sub-expression would be the grouping of network elements used as a target match. For example, (network A or network B) would be considered a sub-expression. This can be used to compound sub-expressions before calling creat... | 2 | null | Implement the Python class `Expression` described below.
Class description:
Expressions are used to build boolean like objects used in policy. For example, if you wanted to create an expression that negates a specific set of network elements to use in a "NOT" rule, an expression would be the element type. For example,... | Implement the Python class `Expression` described below.
Class description:
Expressions are used to build boolean like objects used in policy. For example, if you wanted to create an expression that negates a specific set of network elements to use in a "NOT" rule, an expression would be the element type. For example,... | 54386c8a710727cc1acf69334a57b155d2f5408c | <|skeleton|>
class Expression:
"""Expressions are used to build boolean like objects used in policy. For example, if you wanted to create an expression that negates a specific set of network elements to use in a "NOT" rule, an expression would be the element type. For example, adding a rule that negates (network A ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Expression:
"""Expressions are used to build boolean like objects used in policy. For example, if you wanted to create an expression that negates a specific set of network elements to use in a "NOT" rule, an expression would be the element type. For example, adding a rule that negates (network A or network B)... | the_stack_v2_python_sparse | smc/elements/network.py | gabstopper/smc-python | train | 31 |
a3a777a18022111b81a565503bf9a2246dd90bbb | [
"super().__init__()\nself.normalizer = normalizer\nif self.normalizer is None:\n self.fitted = True\nif aggregator is None:\n aggregator = AverageAggregator()\nself.aggregator = aggregator",
"if self.normalizer is not None:\n x = self.normalizer(x)\nx = self.aggregator(x)\nreturn x",
"if self.normalize... | <|body_start_0|>
super().__init__()
self.normalizer = normalizer
if self.normalizer is None:
self.fitted = True
if aggregator is None:
aggregator = AverageAggregator()
self.aggregator = aggregator
<|end_body_0|>
<|body_start_1|>
if self.normalizer... | Ensembler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ensembler:
def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None):
"""An Ensembler applies normalization and aggregation operations to the scores of an ensemble of detectors. Parameters ---------- normalizer `BaseFittedTransformTorch` objec... | stack_v2_sparse_classes_36k_train_028414 | 9,337 | permissive | [
{
"docstring": "An Ensembler applies normalization and aggregation operations to the scores of an ensemble of detectors. Parameters ---------- normalizer `BaseFittedTransformTorch` object to normalize the scores. If ``None`` then no normalization is applied. aggregator `BaseTransformTorch` object to aggregate t... | 3 | stack_v2_sparse_classes_30k_train_009336 | Implement the Python class `Ensembler` described below.
Class description:
Implement the Ensembler class.
Method signatures and docstrings:
- def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None): An Ensembler applies normalization and aggregation operations to the sco... | Implement the Python class `Ensembler` described below.
Class description:
Implement the Ensembler class.
Method signatures and docstrings:
- def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None): An Ensembler applies normalization and aggregation operations to the sco... | 4a1b4f74a8590117965421e86c2295bff0f33e89 | <|skeleton|>
class Ensembler:
def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None):
"""An Ensembler applies normalization and aggregation operations to the scores of an ensemble of detectors. Parameters ---------- normalizer `BaseFittedTransformTorch` objec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ensembler:
def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None):
"""An Ensembler applies normalization and aggregation operations to the scores of an ensemble of detectors. Parameters ---------- normalizer `BaseFittedTransformTorch` object to normalize... | the_stack_v2_python_sparse | alibi_detect/od/pytorch/ensemble.py | SeldonIO/alibi-detect | train | 1,922 | |
0df4bde1b6f4554f89f6ec69b315fe2a45f0786a | [
"self.intent_type = intent_type\nself.domain = domain\nself.service = service\nself.speech = speech",
"hass = intent_obj.hass\nslots = self.async_validate_slots(intent_obj.slots)\nstate = async_match_state(hass, slots['name']['value'])\nawait hass.services.async_call(self.domain, self.service, {ATTR_ENTITY_ID: st... | <|body_start_0|>
self.intent_type = intent_type
self.domain = domain
self.service = service
self.speech = speech
<|end_body_0|>
<|body_start_1|>
hass = intent_obj.hass
slots = self.async_validate_slots(intent_obj.slots)
state = async_match_state(hass, slots['name... | Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id. | ServiceIntentHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceIntentHandler:
"""Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id."""
def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None:
"""Create Service Intent Handler."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_028415 | 8,241 | permissive | [
{
"docstring": "Create Service Intent Handler.",
"name": "__init__",
"signature": "def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None"
},
{
"docstring": "Handle the hass intent.",
"name": "async_handle",
"signature": "async def async_handle(self, intent_... | 2 | stack_v2_sparse_classes_30k_train_013185 | Implement the Python class `ServiceIntentHandler` described below.
Class description:
Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id.
Method signatures and docstrings:
- def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None: C... | Implement the Python class `ServiceIntentHandler` described below.
Class description:
Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id.
Method signatures and docstrings:
- def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None: C... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class ServiceIntentHandler:
"""Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id."""
def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None:
"""Create Service Intent Handler."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServiceIntentHandler:
"""Service Intent handler registration. Service specific intent handler that calls a service by name/entity_id."""
def __init__(self, intent_type: str, domain: str, service: str, speech: str) -> None:
"""Create Service Intent Handler."""
self.intent_type = intent_typ... | the_stack_v2_python_sparse | homeassistant/helpers/intent.py | BenWoodford/home-assistant | train | 11 |
f03ac6f1c5b3195905159d7351005912baf91630 | [
"assert in_channels % 2 == 0, 'in_channels should be divisible by 2'\nsuper().__init__()\nself.half_channels = in_channels // 2\nself.use_only_mean = use_only_mean\nself.input_conv = nn.Conv1D(self.half_channels, hidden_channels, 1)\nself.encoder = WaveNet(in_channels=-1, out_channels=-1, kernel_size=kernel_size, l... | <|body_start_0|>
assert in_channels % 2 == 0, 'in_channels should be divisible by 2'
super().__init__()
self.half_channels = in_channels // 2
self.use_only_mean = use_only_mean
self.input_conv = nn.Conv1D(self.half_channels, hidden_channels, 1)
self.encoder = WaveNet(in_c... | Residual affine coupling layer. | ResidualAffineCouplingLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResidualAffineCouplingLayer:
"""Residual affine coupling layer."""
def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: int=-1, dropout_rate: float=0.0, use_weight_norm: bool=True, bias: bo... | stack_v2_sparse_classes_36k_train_028416 | 9,159 | permissive | [
{
"docstring": "Initialzie ResidualAffineCouplingLayer module. Args: in_channels (int): Number of input channels. hidden_channels (int): Number of hidden channels. kernel_size (int): Kernel size for WaveNet. base_dilation (int): Base dilation factor for WaveNet. layers (int): Number of layers of WaveNet. stacks... | 2 | null | Implement the Python class `ResidualAffineCouplingLayer` described below.
Class description:
Residual affine coupling layer.
Method signatures and docstrings:
- def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: i... | Implement the Python class `ResidualAffineCouplingLayer` described below.
Class description:
Residual affine coupling layer.
Method signatures and docstrings:
- def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: i... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class ResidualAffineCouplingLayer:
"""Residual affine coupling layer."""
def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: int=-1, dropout_rate: float=0.0, use_weight_norm: bool=True, bias: bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResidualAffineCouplingLayer:
"""Residual affine coupling layer."""
def __init__(self, in_channels: int=192, hidden_channels: int=192, kernel_size: int=5, base_dilation: int=1, layers: int=5, stacks: int=1, global_channels: int=-1, dropout_rate: float=0.0, use_weight_norm: bool=True, bias: bool=True, use_... | the_stack_v2_python_sparse | paddlespeech/t2s/models/vits/residual_coupling.py | anniyanvr/DeepSpeech-1 | train | 0 |
67a1c4bd52df576b0ffbb7180ccd00fcc7f6ec34 | [
"if self.singledot is not None and self.doubledot is not None and (self.dotregime is not None):\n return True\nelse:\n return False",
"if self.pinchoff is not None:\n return True\nelse:\n return False"
] | <|body_start_0|>
if self.singledot is not None and self.doubledot is not None and (self.dotregime is not None):
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
if self.pinchoff is not None:
return True
else:
return False
<|e... | Class grouping binary classifiers required for tuning. Parameters: pinchoff (optional nt.Classifier): pre-trained pinch-off classifier. singledot (optional nt.Classifier): pre-trained single dot classifier. doubledot (optional nt.Classifier): pre-trained double dot classifier. dotregime (optional nt.Classifier): pre-tr... | Classifiers | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Classifiers:
"""Class grouping binary classifiers required for tuning. Parameters: pinchoff (optional nt.Classifier): pre-trained pinch-off classifier. singledot (optional nt.Classifier): pre-trained single dot classifier. doubledot (optional nt.Classifier): pre-trained double dot classifier. dot... | stack_v2_sparse_classes_36k_train_028417 | 7,268 | permissive | [
{
"docstring": "Checks if dot classifiers are specified/not None. If so, the `Classifiers` instance can be used in a dot tuning algorithm.",
"name": "is_dot_classifier",
"signature": "def is_dot_classifier(self) -> bool"
},
{
"docstring": "Checks if pinch-off classifier is specified/not None. If... | 2 | stack_v2_sparse_classes_30k_train_012730 | Implement the Python class `Classifiers` described below.
Class description:
Class grouping binary classifiers required for tuning. Parameters: pinchoff (optional nt.Classifier): pre-trained pinch-off classifier. singledot (optional nt.Classifier): pre-trained single dot classifier. doubledot (optional nt.Classifier):... | Implement the Python class `Classifiers` described below.
Class description:
Class grouping binary classifiers required for tuning. Parameters: pinchoff (optional nt.Classifier): pre-trained pinch-off classifier. singledot (optional nt.Classifier): pre-trained single dot classifier. doubledot (optional nt.Classifier):... | caf50f78c335cd1af4ed11e02c100ddf8d6755a5 | <|skeleton|>
class Classifiers:
"""Class grouping binary classifiers required for tuning. Parameters: pinchoff (optional nt.Classifier): pre-trained pinch-off classifier. singledot (optional nt.Classifier): pre-trained single dot classifier. doubledot (optional nt.Classifier): pre-trained double dot classifier. dot... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Classifiers:
"""Class grouping binary classifiers required for tuning. Parameters: pinchoff (optional nt.Classifier): pre-trained pinch-off classifier. singledot (optional nt.Classifier): pre-trained single dot classifier. doubledot (optional nt.Classifier): pre-trained double dot classifier. dotregime (optio... | the_stack_v2_python_sparse | nanotune/tuningstages/settings.py | picarro-yren/nanotune | train | 0 |
13322461e8e0238b7b5b14f835abcbe5fad75e0b | [
"self.courseID = courseID\nself.jobID = jobID\nself.submissionLanguage = submissionLanguage\nself.directoryFormat = directoryFormat\nself.baseFile = baseFile\nself.userEmail = userEmail\nself.toggleEmail = toggleEmail\nself.fRoot = fRoot\nself.fOut = fOut",
"path = os.path.join(dirname, 'folderizer.py')\nprint('s... | <|body_start_0|>
self.courseID = courseID
self.jobID = jobID
self.submissionLanguage = submissionLanguage
self.directoryFormat = directoryFormat
self.baseFile = baseFile
self.userEmail = userEmail
self.toggleEmail = toggleEmail
self.fRoot = fRoot
s... | The function of the jobRequest class is to unzip submission files, form the appropriate MOSS shell command, exceute it and receive output. The class handles the various states of the MOSS server. | jobRequest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class jobRequest:
"""The function of the jobRequest class is to unzip submission files, form the appropriate MOSS shell command, exceute it and receive output. The class handles the various states of the MOSS server."""
def __init__(self, courseID, jobID, submissionLanguage, directoryFormat, baseF... | stack_v2_sparse_classes_36k_train_028418 | 6,136 | no_license | [
{
"docstring": "Constructor of the Job Request that we submit to the MOSS server The job object takes 8 parameters namely: CourseID(course associated with user account) jobID(unique identifier of submitted job) submissionLanguage - Coding language utilised for code file submissions to MOSS directoryFormat - For... | 6 | stack_v2_sparse_classes_30k_train_005339 | Implement the Python class `jobRequest` described below.
Class description:
The function of the jobRequest class is to unzip submission files, form the appropriate MOSS shell command, exceute it and receive output. The class handles the various states of the MOSS server.
Method signatures and docstrings:
- def __init... | Implement the Python class `jobRequest` described below.
Class description:
The function of the jobRequest class is to unzip submission files, form the appropriate MOSS shell command, exceute it and receive output. The class handles the various states of the MOSS server.
Method signatures and docstrings:
- def __init... | 2c0d408a5ff930c34be669737ff4b6d0ae13da2f | <|skeleton|>
class jobRequest:
"""The function of the jobRequest class is to unzip submission files, form the appropriate MOSS shell command, exceute it and receive output. The class handles the various states of the MOSS server."""
def __init__(self, courseID, jobID, submissionLanguage, directoryFormat, baseF... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class jobRequest:
"""The function of the jobRequest class is to unzip submission files, form the appropriate MOSS shell command, exceute it and receive output. The class handles the various states of the MOSS server."""
def __init__(self, courseID, jobID, submissionLanguage, directoryFormat, baseFile, userEmai... | the_stack_v2_python_sparse | backend/SSRG/Jobs/MossBackendJobs/jobRequest.py | Suvanth/SSRG-Django-Website | train | 0 |
2fade3223644e7be5d016bfe25bf763879696566 | [
"if root == None:\n return False\nelif root.left == None and root.right == None:\n if sum == root.val:\n return True\n else:\n return False\nelse:\n return self.hasPathSum(root.left, sum - root.val) or self.hasPathSum(root.right, sum - root.val)",
"if root is None:\n return False\nsta... | <|body_start_0|>
if root == None:
return False
elif root.left == None and root.right == None:
if sum == root.val:
return True
else:
return False
else:
return self.hasPathSum(root.left, sum - root.val) or self.hasPath... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasPathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: bool"""
<|body_0|>
def hasPathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root... | stack_v2_sparse_classes_36k_train_028419 | 1,258 | no_license | [
{
"docstring": ":type root: TreeNode :type sum: int :rtype: bool",
"name": "hasPathSum",
"signature": "def hasPathSum(self, root, sum)"
},
{
"docstring": ":type root: TreeNode :type sum: int :rtype: bool",
"name": "hasPathSum",
"signature": "def hasPathSum(self, root, sum)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: bool
- def hasPathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: bool
- def hasPathSum(self, root, sum): :type root: TreeNode :type sum: int :rtype: bool
<|skeleton|... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def hasPathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: bool"""
<|body_0|>
def hasPathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hasPathSum(self, root, sum):
""":type root: TreeNode :type sum: int :rtype: bool"""
if root == None:
return False
elif root.left == None and root.right == None:
if sum == root.val:
return True
else:
retur... | the_stack_v2_python_sparse | code/112#Path Sum.py | EachenKuang/LeetCode | train | 28 | |
1c6315bf1ee497701ab03a0319aa9cf1024b13f0 | [
"url = '/admissions-cost/'\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 302)",
"url = '/admissions-cost/'\nself.client.login(username=self.adminUN, password='pass')\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.statu... | <|body_start_0|>
url = '/admissions-cost/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
<|end_body_0|>
<|body_start_1|>
url = '/admissions-cost/'
self.client.login(username=self.adminUN, password='pass')
response... | AdmissionsCostTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdmissionsCostTestCase:
def test_not_logged_in(self):
"""Test that the admissions costs view will not load whilst not logged in."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the admissions costs view will load whilst logged in as admin."""
<|bod... | stack_v2_sparse_classes_36k_train_028420 | 26,818 | permissive | [
{
"docstring": "Test that the admissions costs view will not load whilst not logged in.",
"name": "test_not_logged_in",
"signature": "def test_not_logged_in(self)"
},
{
"docstring": "Test that the admissions costs view will load whilst logged in as admin.",
"name": "test_logged_in_admin",
... | 3 | null | Implement the Python class `AdmissionsCostTestCase` described below.
Class description:
Implement the AdmissionsCostTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the admissions costs view will not load whilst not logged in.
- def test_logged_in_admin(self): Test that the ... | Implement the Python class `AdmissionsCostTestCase` described below.
Class description:
Implement the AdmissionsCostTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the admissions costs view will not load whilst not logged in.
- def test_logged_in_admin(self): Test that the ... | 37d2942efcbdaad072f7a06ac876a40e0f69f702 | <|skeleton|>
class AdmissionsCostTestCase:
def test_not_logged_in(self):
"""Test that the admissions costs view will not load whilst not logged in."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the admissions costs view will load whilst logged in as admin."""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdmissionsCostTestCase:
def test_not_logged_in(self):
"""Test that the admissions costs view will not load whilst not logged in."""
url = '/admissions-cost/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
def test_lo... | the_stack_v2_python_sparse | mooring/test_views.py | dbca-wa/moorings | train | 0 | |
1941dca737d2baaef65cf0b403cb3cb0fb67b085 | [
"self.cumhelper = CUMHelper(commu_ip, commu_port)\nself.cumhelper.chvolume(commu_volume)\nself.debug_handler = debug_handler\nrospy.loginfo('CommUWrapper instance created.')",
"rospy.loginfo(\"Saying '%s' in %s..\", utterance, 'English' if english else 'Japanese')\nif self.debug_handler is not None:\n self.deb... | <|body_start_0|>
self.cumhelper = CUMHelper(commu_ip, commu_port)
self.cumhelper.chvolume(commu_volume)
self.debug_handler = debug_handler
rospy.loginfo('CommUWrapper instance created.')
<|end_body_0|>
<|body_start_1|>
rospy.loginfo("Saying '%s' in %s..", utterance, 'English' if... | CommUWrapper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommUWrapper:
def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None):
"""Instantiates a new CommUWrapper instance. This wraps all the functions of the CommU Helper python library, found under ./helper/. :param commu_ip: The ip address of the CommU ... | stack_v2_sparse_classes_36k_train_028421 | 3,119 | no_license | [
{
"docstring": "Instantiates a new CommUWrapper instance. This wraps all the functions of the CommU Helper python library, found under ./helper/. :param commu_ip: The ip address of the CommU to control. :param commu_port: The port of the CommUManager on the CommU. :param commu_volume: The volume of the CommU. P... | 3 | stack_v2_sparse_classes_30k_train_000672 | Implement the Python class `CommUWrapper` described below.
Class description:
Implement the CommUWrapper class.
Method signatures and docstrings:
- def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None): Instantiates a new CommUWrapper instance. This wraps all the functions of ... | Implement the Python class `CommUWrapper` described below.
Class description:
Implement the CommUWrapper class.
Method signatures and docstrings:
- def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None): Instantiates a new CommUWrapper instance. This wraps all the functions of ... | 53aedca77d1f61437a22d0c52093555fb815d79b | <|skeleton|>
class CommUWrapper:
def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None):
"""Instantiates a new CommUWrapper instance. This wraps all the functions of the CommU Helper python library, found under ./helper/. :param commu_ip: The ip address of the CommU ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommUWrapper:
def __init__(self, commu_ip='127.0.0.1', commu_port=6019, commu_volume=10, debug_handler=None):
"""Instantiates a new CommUWrapper instance. This wraps all the functions of the CommU Helper python library, found under ./helper/. :param commu_ip: The ip address of the CommU to control. :p... | the_stack_v2_python_sparse | src/commu_wrapper/src/wrapper.py | mgmeedendorp/ros-commu | train | 2 | |
c8b1c1b2d2ab18f52a9460373d356f84e597c542 | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(username=username, email=self.normalize_email(email))\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(username, email, password=password)\nuser.is_admin = True\nuser.is_staff... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(username=username, email=self.normalize_email(email))
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user ... | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, username, email, password):
"""Creates and saves a superuser with the given em... | stack_v2_sparse_classes_36k_train_028422 | 3,320 | no_license | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, username, email, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
"name"... | 2 | stack_v2_sparse_classes_30k_train_002922 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, username, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, username,... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, username, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, username,... | 8b33a29e60d84853f8c1e92d7a4ca88c6ee349b4 | <|skeleton|>
class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, username, email, password):
"""Creates and saves a superuser with the given em... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyUserManager:
def create_user(self, username, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
if not email:
raise ValueError('Users must have an email address')
user = self.model(username=username, email=self.normaliz... | the_stack_v2_python_sparse | accounts/models.py | falbellaihi1/BST | train | 0 | |
0ab3d46aa9155999d1bccc5fb25b5041d5be5896 | [
"super().setUpClass()\ncls.application = 'mysql-innodb-cluster'\ncls.test_config = lifecycle_utils.get_charm_config(fatal=False)\ncls.states = cls.test_config.get('target_deploy_status', {})",
"logging.info('Scale in test: remove leader')\nleader, nons = generic_utils.get_leaders_and_non_leaders(self.application_... | <|body_start_0|>
super().setUpClass()
cls.application = 'mysql-innodb-cluster'
cls.test_config = lifecycle_utils.get_charm_config(fatal=False)
cls.states = cls.test_config.get('target_deploy_status', {})
<|end_body_0|>
<|body_start_1|>
logging.info('Scale in test: remove leader'... | Percona Cluster cold start tests. | MySQLInnoDBClusterScaleTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MySQLInnoDBClusterScaleTest:
"""Percona Cluster cold start tests."""
def setUpClass(cls):
"""Run class setup for running mysql-innodb-cluster scale tests."""
<|body_0|>
def test_800_remove_leader(self):
"""Remove leader node. We start with a three node cluster, r... | stack_v2_sparse_classes_36k_train_028423 | 45,009 | permissive | [
{
"docstring": "Run class setup for running mysql-innodb-cluster scale tests.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Remove leader node. We start with a three node cluster, remove one, down to two. The cluster will be in waiting state.",
"name": "test_8... | 5 | null | Implement the Python class `MySQLInnoDBClusterScaleTest` described below.
Class description:
Percona Cluster cold start tests.
Method signatures and docstrings:
- def setUpClass(cls): Run class setup for running mysql-innodb-cluster scale tests.
- def test_800_remove_leader(self): Remove leader node. We start with a ... | Implement the Python class `MySQLInnoDBClusterScaleTest` described below.
Class description:
Percona Cluster cold start tests.
Method signatures and docstrings:
- def setUpClass(cls): Run class setup for running mysql-innodb-cluster scale tests.
- def test_800_remove_leader(self): Remove leader node. We start with a ... | 3b17ad9d97c57b6e62797d4e3333e4b83e43a447 | <|skeleton|>
class MySQLInnoDBClusterScaleTest:
"""Percona Cluster cold start tests."""
def setUpClass(cls):
"""Run class setup for running mysql-innodb-cluster scale tests."""
<|body_0|>
def test_800_remove_leader(self):
"""Remove leader node. We start with a three node cluster, r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MySQLInnoDBClusterScaleTest:
"""Percona Cluster cold start tests."""
def setUpClass(cls):
"""Run class setup for running mysql-innodb-cluster scale tests."""
super().setUpClass()
cls.application = 'mysql-innodb-cluster'
cls.test_config = lifecycle_utils.get_charm_config(fa... | the_stack_v2_python_sparse | zaza/openstack/charm_tests/mysql/tests.py | openstack-charmers/zaza-openstack-tests | train | 7 |
786f0d598dd75e66c4184f07bc00043bfd2af4fc | [
"super().__init__()\nself.linear1 = nn.Linear(in_channels, in_channels // r)\nself.linear2 = nn.Linear(in_channels // r, in_channels)",
"input_x = x\nx = x.view(*x.shape[:-2], -1).mean(-1)\nx = F.relu(self.linear1(x), inplace=True)\nx = self.linear2(x)\nx = x.unsqueeze(-1).unsqueeze(-1)\nx = torch.sigmoid(x)\nx =... | <|body_start_0|>
super().__init__()
self.linear1 = nn.Linear(in_channels, in_channels // r)
self.linear2 = nn.Linear(in_channels // r, in_channels)
<|end_body_0|>
<|body_start_1|>
input_x = x
x = x.view(*x.shape[:-2], -1).mean(-1)
x = F.relu(self.linear1(x), inplace=True... | The channel-wise SE (Squeeze and Excitation) block from the `Squeeze-and-Excitation Networks`__ paper. Adapted from https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/65939 and https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/66178 Shape: - Input: (batch, channels, height, width)... | cSE | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class cSE:
"""The channel-wise SE (Squeeze and Excitation) block from the `Squeeze-and-Excitation Networks`__ paper. Adapted from https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/65939 and https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/66178 Shape: - Input: (... | stack_v2_sparse_classes_36k_train_028424 | 3,491 | permissive | [
{
"docstring": "Args: in_channels: The number of channels in the feature map of the input. r: The reduction ratio of the intermediate channels. Default: 16.",
"name": "__init__",
"signature": "def __init__(self, in_channels: int, r: int=16)"
},
{
"docstring": "Forward call.",
"name": "forwar... | 2 | null | Implement the Python class `cSE` described below.
Class description:
The channel-wise SE (Squeeze and Excitation) block from the `Squeeze-and-Excitation Networks`__ paper. Adapted from https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/65939 and https://www.kaggle.com/c/tgs-salt-identification-chall... | Implement the Python class `cSE` described below.
Class description:
The channel-wise SE (Squeeze and Excitation) block from the `Squeeze-and-Excitation Networks`__ paper. Adapted from https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/65939 and https://www.kaggle.com/c/tgs-salt-identification-chall... | e99f90655d0efcf22559a46e928f0f98c9807ebf | <|skeleton|>
class cSE:
"""The channel-wise SE (Squeeze and Excitation) block from the `Squeeze-and-Excitation Networks`__ paper. Adapted from https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/65939 and https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/66178 Shape: - Input: (... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class cSE:
"""The channel-wise SE (Squeeze and Excitation) block from the `Squeeze-and-Excitation Networks`__ paper. Adapted from https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/65939 and https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/66178 Shape: - Input: (batch, channe... | the_stack_v2_python_sparse | catalyst/contrib/layers/se.py | catalyst-team/catalyst | train | 3,038 |
a52cd2eea3173b51848685de09680f67ad60bcdf | [
"cursor = connection.cursor()\nparent_ad_rep_id = None\nif ad_rep_dict.get('parent_ad_rep_id'):\n try:\n parent_ad_rep_id = AdRep.objects.get(id=ad_rep_dict.get('parent_ad_rep_id')).id\n except AdRep.DoesNotExist:\n pass\ncursor.execute('\\n INSERT INTO firestorm_adrep(consumer_ptr_id... | <|body_start_0|>
cursor = connection.cursor()
parent_ad_rep_id = None
if ad_rep_dict.get('parent_ad_rep_id'):
try:
parent_ad_rep_id = AdRep.objects.get(id=ad_rep_dict.get('parent_ad_rep_id')).id
except AdRep.DoesNotExist:
pass
curso... | Manager class of AdRep, | AdRepManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdRepManager:
"""Manager class of AdRep,"""
def create_ad_rep_from_consumer(self, consumer_id, ad_rep_dict):
"""Create an ad_rep for an existing consumer."""
<|body_0|>
def create_ad_rep_from_ad_rep_lead(self, consumer_id, ad_rep_dict):
"""Convert ad ad_rep_lead ... | stack_v2_sparse_classes_36k_train_028425 | 28,242 | no_license | [
{
"docstring": "Create an ad_rep for an existing consumer.",
"name": "create_ad_rep_from_consumer",
"signature": "def create_ad_rep_from_consumer(self, consumer_id, ad_rep_dict)"
},
{
"docstring": "Convert ad ad_rep_lead into an ad_rep.",
"name": "create_ad_rep_from_ad_rep_lead",
"signat... | 3 | null | Implement the Python class `AdRepManager` described below.
Class description:
Manager class of AdRep,
Method signatures and docstrings:
- def create_ad_rep_from_consumer(self, consumer_id, ad_rep_dict): Create an ad_rep for an existing consumer.
- def create_ad_rep_from_ad_rep_lead(self, consumer_id, ad_rep_dict): Co... | Implement the Python class `AdRepManager` described below.
Class description:
Manager class of AdRep,
Method signatures and docstrings:
- def create_ad_rep_from_consumer(self, consumer_id, ad_rep_dict): Create an ad_rep for an existing consumer.
- def create_ad_rep_from_ad_rep_lead(self, consumer_id, ad_rep_dict): Co... | a780ccdc3350d4b5c7990c65d1af8d71060c62cc | <|skeleton|>
class AdRepManager:
"""Manager class of AdRep,"""
def create_ad_rep_from_consumer(self, consumer_id, ad_rep_dict):
"""Create an ad_rep for an existing consumer."""
<|body_0|>
def create_ad_rep_from_ad_rep_lead(self, consumer_id, ad_rep_dict):
"""Convert ad ad_rep_lead ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdRepManager:
"""Manager class of AdRep,"""
def create_ad_rep_from_consumer(self, consumer_id, ad_rep_dict):
"""Create an ad_rep for an existing consumer."""
cursor = connection.cursor()
parent_ad_rep_id = None
if ad_rep_dict.get('parent_ad_rep_id'):
try:
... | the_stack_v2_python_sparse | firestorm/models.py | wcirillo/ten | train | 0 |
62ef813b1adc90b6faf9187825ff5c0c6204b629 | [
"process_dic = {}\nfor key, value in request.GET.items():\n process_dic[key] = value\nsign = process_dic.pop('sign', None)\nalipay = AliPay(appid='2016091800536621', app_notify_url='http://47.106.211.59:8008/alipay/return/', app_private_key_path=private_key_path, alipay_public_key_path=ali_pub_path, debug=True, ... | <|body_start_0|>
process_dic = {}
for key, value in request.GET.items():
process_dic[key] = value
sign = process_dic.pop('sign', None)
alipay = AliPay(appid='2016091800536621', app_notify_url='http://47.106.211.59:8008/alipay/return/', app_private_key_path=private_key_path, a... | 支付宝接口 | AlipayView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlipayView:
"""支付宝接口"""
def get(self, request):
"""处理return_url返回 :param request: :return:"""
<|body_0|>
def post(self, request):
"""处理notify_url :param request: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
process_dic = {}
f... | stack_v2_sparse_classes_36k_train_028426 | 6,734 | no_license | [
{
"docstring": "处理return_url返回 :param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "处理notify_url :param request: :return:",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007866 | Implement the Python class `AlipayView` described below.
Class description:
支付宝接口
Method signatures and docstrings:
- def get(self, request): 处理return_url返回 :param request: :return:
- def post(self, request): 处理notify_url :param request: :return: | Implement the Python class `AlipayView` described below.
Class description:
支付宝接口
Method signatures and docstrings:
- def get(self, request): 处理return_url返回 :param request: :return:
- def post(self, request): 处理notify_url :param request: :return:
<|skeleton|>
class AlipayView:
"""支付宝接口"""
def get(self, requ... | 3ccc9bd50653ee38d59a5b8c4f4fa19d19f0b874 | <|skeleton|>
class AlipayView:
"""支付宝接口"""
def get(self, request):
"""处理return_url返回 :param request: :return:"""
<|body_0|>
def post(self, request):
"""处理notify_url :param request: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlipayView:
"""支付宝接口"""
def get(self, request):
"""处理return_url返回 :param request: :return:"""
process_dic = {}
for key, value in request.GET.items():
process_dic[key] = value
sign = process_dic.pop('sign', None)
alipay = AliPay(appid='2016091800536621',... | the_stack_v2_python_sparse | apps/trade/views.py | LYQCOOL/Vueshops | train | 1 |
7e2642811b17392adf07f375f495fd57aeb24639 | [
"super().__init__()\nself.last_batch = data.get('last_batch', None)\nself.batch_size: Optional[int] = data.get('batch_size')\nself.dataset: Optional[Dataset] = None\nif data.get('dataset'):\n self.set_dataset(data.get('dataset', {}))\nself.transform: OrderedDict = OrderedDict()\nif data.get('transform'):\n fo... | <|body_start_0|>
super().__init__()
self.last_batch = data.get('last_batch', None)
self.batch_size: Optional[int] = data.get('batch_size')
self.dataset: Optional[Dataset] = None
if data.get('dataset'):
self.set_dataset(data.get('dataset', {}))
self.transform: ... | Configuration Dataloader class. | Dataloader | [
"MIT",
"Intel",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataloader:
"""Configuration Dataloader class."""
def __init__(self, data: Dict[str, Any]={}) -> None:
"""Initialize Configuration Dataloader class."""
<|body_0|>
def set_dataset(self, dataset_data: Dict[str, Any]) -> None:
"""Set dataset for dataloader."""
... | stack_v2_sparse_classes_36k_train_028427 | 4,560 | permissive | [
{
"docstring": "Initialize Configuration Dataloader class.",
"name": "__init__",
"signature": "def __init__(self, data: Dict[str, Any]={}) -> None"
},
{
"docstring": "Set dataset for dataloader.",
"name": "set_dataset",
"signature": "def set_dataset(self, dataset_data: Dict[str, Any]) ->... | 3 | stack_v2_sparse_classes_30k_train_005833 | Implement the Python class `Dataloader` described below.
Class description:
Configuration Dataloader class.
Method signatures and docstrings:
- def __init__(self, data: Dict[str, Any]={}) -> None: Initialize Configuration Dataloader class.
- def set_dataset(self, dataset_data: Dict[str, Any]) -> None: Set dataset for... | Implement the Python class `Dataloader` described below.
Class description:
Configuration Dataloader class.
Method signatures and docstrings:
- def __init__(self, data: Dict[str, Any]={}) -> None: Initialize Configuration Dataloader class.
- def set_dataset(self, dataset_data: Dict[str, Any]) -> None: Set dataset for... | 3976edc4215398e69ce0213f87ec295f5dc96e0e | <|skeleton|>
class Dataloader:
"""Configuration Dataloader class."""
def __init__(self, data: Dict[str, Any]={}) -> None:
"""Initialize Configuration Dataloader class."""
<|body_0|>
def set_dataset(self, dataset_data: Dict[str, Any]) -> None:
"""Set dataset for dataloader."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataloader:
"""Configuration Dataloader class."""
def __init__(self, data: Dict[str, Any]={}) -> None:
"""Initialize Configuration Dataloader class."""
super().__init__()
self.last_batch = data.get('last_batch', None)
self.batch_size: Optional[int] = data.get('batch_size')... | the_stack_v2_python_sparse | neural_compressor/ux/utils/workload/dataloader.py | Skp80/neural-compressor | train | 0 |
654656ad224f1759df6d1e43b28e57c958ef5c41 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | The AlertPolicyService API is used to manage (list, create, delete, edit) alert policies in Stackdriver Monitoring. An alerting policy is a description of the conditions under which some aspect of your system is considered to be "unhealthy" and the ways to notify people or services about this state. In addition to usin... | AlertPolicyServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlertPolicyServiceServicer:
"""The AlertPolicyService API is used to manage (list, create, delete, edit) alert policies in Stackdriver Monitoring. An alerting policy is a description of the conditions under which some aspect of your system is considered to be "unhealthy" and the ways to notify pe... | stack_v2_sparse_classes_36k_train_028428 | 7,568 | permissive | [
{
"docstring": "Lists the existing alerting policies for the project.",
"name": "ListAlertPolicies",
"signature": "def ListAlertPolicies(self, request, context)"
},
{
"docstring": "Gets a single alerting policy.",
"name": "GetAlertPolicy",
"signature": "def GetAlertPolicy(self, request, ... | 5 | stack_v2_sparse_classes_30k_train_008361 | Implement the Python class `AlertPolicyServiceServicer` described below.
Class description:
The AlertPolicyService API is used to manage (list, create, delete, edit) alert policies in Stackdriver Monitoring. An alerting policy is a description of the conditions under which some aspect of your system is considered to b... | Implement the Python class `AlertPolicyServiceServicer` described below.
Class description:
The AlertPolicyService API is used to manage (list, create, delete, edit) alert policies in Stackdriver Monitoring. An alerting policy is a description of the conditions under which some aspect of your system is considered to b... | d897d56bce03d1fda98b79afb08264e51d46c421 | <|skeleton|>
class AlertPolicyServiceServicer:
"""The AlertPolicyService API is used to manage (list, create, delete, edit) alert policies in Stackdriver Monitoring. An alerting policy is a description of the conditions under which some aspect of your system is considered to be "unhealthy" and the ways to notify pe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlertPolicyServiceServicer:
"""The AlertPolicyService API is used to manage (list, create, delete, edit) alert policies in Stackdriver Monitoring. An alerting policy is a description of the conditions under which some aspect of your system is considered to be "unhealthy" and the ways to notify people or servi... | the_stack_v2_python_sparse | monitoring/google/cloud/monitoring_v3/proto/alert_service_pb2_grpc.py | tswast/google-cloud-python | train | 1 |
c04d96fa29b707d39bf204ba32c9791d7af2db15 | [
"super(WaitForPersonState, self).__init__(outcomes=['done', 'failure'])\nself._target_sub_topic = target_sub_topic\nself._persons = None\nself._start_sec = 0\nself._start_nsec = 0\nself._sub = ProxySubscriberCached({self._target_sub_topic: MinimalHumans})",
"self._persons = self._sub.get_last_msg(self._target_sub... | <|body_start_0|>
super(WaitForPersonState, self).__init__(outcomes=['done', 'failure'])
self._target_sub_topic = target_sub_topic
self._persons = None
self._start_sec = 0
self._start_nsec = 0
self._sub = ProxySubscriberCached({self._target_sub_topic: MinimalHumans})
<|end... | Implements a state that returns true if there is a face published on the given topic. -- target_sub_topic String The topic for the coordinates where to gaze. <= done There is a person. <= failure Something bad happend. | WaitForPersonState | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WaitForPersonState:
"""Implements a state that returns true if there is a face published on the given topic. -- target_sub_topic String The topic for the coordinates where to gaze. <= done There is a person. <= failure Something bad happend."""
def __init__(self, target_sub_topic='/hace/peop... | stack_v2_sparse_classes_36k_train_028429 | 1,815 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, target_sub_topic='/hace/people')"
},
{
"docstring": "Execute this state",
"name": "execute",
"signature": "def execute(self, userdata)"
},
{
"docstring": "Upon entering the state, save the start ti... | 3 | stack_v2_sparse_classes_30k_train_013069 | Implement the Python class `WaitForPersonState` described below.
Class description:
Implements a state that returns true if there is a face published on the given topic. -- target_sub_topic String The topic for the coordinates where to gaze. <= done There is a person. <= failure Something bad happend.
Method signatur... | Implement the Python class `WaitForPersonState` described below.
Class description:
Implements a state that returns true if there is a face published on the given topic. -- target_sub_topic String The topic for the coordinates where to gaze. <= done There is a person. <= failure Something bad happend.
Method signatur... | 12af38bbb13b4da70c41cf397bde4d79e21a6d28 | <|skeleton|>
class WaitForPersonState:
"""Implements a state that returns true if there is a face published on the given topic. -- target_sub_topic String The topic for the coordinates where to gaze. <= done There is a person. <= failure Something bad happend."""
def __init__(self, target_sub_topic='/hace/peop... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WaitForPersonState:
"""Implements a state that returns true if there is a face published on the given topic. -- target_sub_topic String The topic for the coordinates where to gaze. <= done There is a person. <= failure Something bad happend."""
def __init__(self, target_sub_topic='/hace/people'):
... | the_stack_v2_python_sparse | meka_flexbe_states/src/meka_flexbe_states/WaitForPerson.py | CentralLabFacilities/meka_behaviors | train | 0 |
8b49d0aff9689bdd4a533f118287fd64aa426859 | [
"m = len(matrix)\nn = len(matrix[0])\nlow = 0\nhigh = m * n - 1\nwhile low <= high:\n mid = (low + high) // 2\n if matrix[mid // n][mid % n] > target:\n high = mid - 1\n elif matrix[mid // n][mid % n] < target:\n low = mid + 1\n else:\n return True\nreturn False",
"m = len(matrix)... | <|body_start_0|>
m = len(matrix)
n = len(matrix[0])
low = 0
high = m * n - 1
while low <= high:
mid = (low + high) // 2
if matrix[mid // n][mid % n] > target:
high = mid - 1
elif matrix[mid // n][mid % n] < target:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool:
"""74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找"""
<|body_0|>
def searchMatrix(self, matrix: List[List[int]], target: int) -> bool:
"""240. 搜索二维矩阵 II 行升序，列升序 从左下角开始遍历"""
... | stack_v2_sparse_classes_36k_train_028430 | 3,089 | no_license | [
{
"docstring": "74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找",
"name": "searchMatrix74",
"signature": "def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool"
},
{
"docstring": "240. 搜索二维矩阵 II 行升序，列升序 从左下角开始遍历",
"name": "searchMatrix",
"signature": "def searchMatr... | 3 | stack_v2_sparse_classes_30k_train_003032 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool: 74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找
- def searchMatrix(self, matrix: List[List[int]], tar... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool: 74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找
- def searchMatrix(self, matrix: List[List[int]], tar... | 3fd69b85f52af861ff7e2c74d8aacc515b192615 | <|skeleton|>
class Solution:
def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool:
"""74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找"""
<|body_0|>
def searchMatrix(self, matrix: List[List[int]], target: int) -> bool:
"""240. 搜索二维矩阵 II 行升序，列升序 从左下角开始遍历"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def searchMatrix74(self, matrix: List[List[int]], target: int) -> bool:
"""74. 搜索二维矩阵 行升序，每行的第一个整数大于前一行的最后一个整数 映射为一个升序数组，一次二分查找"""
m = len(matrix)
n = len(matrix[0])
low = 0
high = m * n - 1
while low <= high:
mid = (low + high) // 2
... | the_stack_v2_python_sparse | Array/Array_search_74_240_81.py | helloprogram6/leetcode_Cookbook_python | train | 0 | |
0bf6bdb6674094afc967ed5f99f7d3559e2129e2 | [
"if 'tag' in self.request.GET:\n return self.model.objects.filter(tags__title=self.request.GET['tag']).order_by('date_created')\nreturn self.model.objects.all().order_by('date_created')",
"context = super().get_context_data(**kwargs)\nquery_params = self.request.GET.copy()\nquery_params.pop('page', None)\ncont... | <|body_start_0|>
if 'tag' in self.request.GET:
return self.model.objects.filter(tags__title=self.request.GET['tag']).order_by('date_created')
return self.model.objects.all().order_by('date_created')
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(**kwargs)
... | Base class for displaying a list of listings :param model: Listing subclass :param paginate_by: pagination limit :param template_name: base template for listviews | ListingList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListingList:
"""Base class for displaying a list of listings :param model: Listing subclass :param paginate_by: pagination limit :param template_name: base template for listviews"""
def get_queryset(self) -> QuerySet[Listing]:
"""Filters by tag if "tag" is in query_params. Order by '... | stack_v2_sparse_classes_36k_train_028431 | 4,095 | no_license | [
{
"docstring": "Filters by tag if \"tag\" is in query_params. Order by 'date_created'",
"name": "get_queryset",
"signature": "def get_queryset(self) -> QuerySet[Listing]"
},
{
"docstring": "Cleans 'page' query param between requests for pagination",
"name": "get_context_data",
"signature... | 2 | stack_v2_sparse_classes_30k_train_012497 | Implement the Python class `ListingList` described below.
Class description:
Base class for displaying a list of listings :param model: Listing subclass :param paginate_by: pagination limit :param template_name: base template for listviews
Method signatures and docstrings:
- def get_queryset(self) -> QuerySet[Listing... | Implement the Python class `ListingList` described below.
Class description:
Base class for displaying a list of listings :param model: Listing subclass :param paginate_by: pagination limit :param template_name: base template for listviews
Method signatures and docstrings:
- def get_queryset(self) -> QuerySet[Listing... | c71b81757e4fe2ec58b70e6434ad252032ae55ee | <|skeleton|>
class ListingList:
"""Base class for displaying a list of listings :param model: Listing subclass :param paginate_by: pagination limit :param template_name: base template for listviews"""
def get_queryset(self) -> QuerySet[Listing]:
"""Filters by tag if "tag" is in query_params. Order by '... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListingList:
"""Base class for displaying a list of listings :param model: Listing subclass :param paginate_by: pagination limit :param template_name: base template for listviews"""
def get_queryset(self) -> QuerySet[Listing]:
"""Filters by tag if "tag" is in query_params. Order by 'date_created'... | the_stack_v2_python_sparse | ecom_website/listings/views/base.py | ivanmclennon/e-commerce | train | 0 |
d5d5a5ef94395dafa56ab9300a52d0266ad518f7 | [
"super().__init__()\nself._dfetcher1 = BaselineDirectoryFetcher(dpath1)\nself._dfetcher2 = BaselineDirectoryFetcher(dpath2)\nself._tests = tests\nself._kernels = kernels\nself._codenames = codenames",
"result = {'source': self._dfetcher1.dpath, 'target': self._dfetcher2.dpath}\nfor test in self._tests:\n for k... | <|body_start_0|>
super().__init__()
self._dfetcher1 = BaselineDirectoryFetcher(dpath1)
self._dfetcher2 = BaselineDirectoryFetcher(dpath2)
self._tests = tests
self._kernels = kernels
self._codenames = codenames
<|end_body_0|>
<|body_start_1|>
result = {'source': s... | Class for comparing baselines between directories | DirectoryComparator | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectoryComparator:
"""Class for comparing baselines between directories"""
def __init__(self, dpath1, dpath2, tests, kernels, codenames):
"""Initialize 2 BaselineDirectoryFetcher"""
<|body_0|>
def compare(self, auxiliary=False):
"""Compare data between director... | stack_v2_sparse_classes_36k_train_028432 | 10,002 | permissive | [
{
"docstring": "Initialize 2 BaselineDirectoryFetcher",
"name": "__init__",
"signature": "def __init__(self, dpath1, dpath2, tests, kernels, codenames)"
},
{
"docstring": "Compare data between directories",
"name": "compare",
"signature": "def compare(self, auxiliary=False)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019735 | Implement the Python class `DirectoryComparator` described below.
Class description:
Class for comparing baselines between directories
Method signatures and docstrings:
- def __init__(self, dpath1, dpath2, tests, kernels, codenames): Initialize 2 BaselineDirectoryFetcher
- def compare(self, auxiliary=False): Compare ... | Implement the Python class `DirectoryComparator` described below.
Class description:
Class for comparing baselines between directories
Method signatures and docstrings:
- def __init__(self, dpath1, dpath2, tests, kernels, codenames): Initialize 2 BaselineDirectoryFetcher
- def compare(self, auxiliary=False): Compare ... | 028ace17e73dabb40601ecca95fea28bb6da4b4a | <|skeleton|>
class DirectoryComparator:
"""Class for comparing baselines between directories"""
def __init__(self, dpath1, dpath2, tests, kernels, codenames):
"""Initialize 2 BaselineDirectoryFetcher"""
<|body_0|>
def compare(self, auxiliary=False):
"""Compare data between director... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DirectoryComparator:
"""Class for comparing baselines between directories"""
def __init__(self, dpath1, dpath2, tests, kernels, codenames):
"""Initialize 2 BaselineDirectoryFetcher"""
super().__init__()
self._dfetcher1 = BaselineDirectoryFetcher(dpath1)
self._dfetcher2 = B... | the_stack_v2_python_sparse | tools/compare_baselines/utils/comparator.py | firecracker-microvm/firecracker | train | 22,629 |
a1a395007d8647610334b0fa4c1d0a8bbcd872c0 | [
"if not builder:\n raise ValueError('Quorum Server Builder is not specified')\nif not endpointReporter:\n raise ValueError('End-point reporter is not specified')\nself.__builder = builder\nself.__endpointReporter = endpointReporter",
"if not server:\n raise ValueError('Quorum Server is not specified')\ni... | <|body_start_0|>
if not builder:
raise ValueError('Quorum Server Builder is not specified')
if not endpointReporter:
raise ValueError('End-point reporter is not specified')
self.__builder = builder
self.__endpointReporter = endpointReporter
<|end_body_0|>
<|body_... | QuorumServerReporter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuorumServerReporter:
def __init__(self, builder, endpointReporter):
"""@types: QuorumServerBuilder, netutils.EndpointReporter @raise ValueError: Quorum Server Builder is not specified @raise ValueError: End-point reporter is not specified"""
<|body_0|>
def reportServer(self... | stack_v2_sparse_classes_36k_train_028433 | 23,160 | no_license | [
{
"docstring": "@types: QuorumServerBuilder, netutils.EndpointReporter @raise ValueError: Quorum Server Builder is not specified @raise ValueError: End-point reporter is not specified",
"name": "__init__",
"signature": "def __init__(self, builder, endpointReporter)"
},
{
"docstring": "@types: Qu... | 3 | stack_v2_sparse_classes_30k_train_017929 | Implement the Python class `QuorumServerReporter` described below.
Class description:
Implement the QuorumServerReporter class.
Method signatures and docstrings:
- def __init__(self, builder, endpointReporter): @types: QuorumServerBuilder, netutils.EndpointReporter @raise ValueError: Quorum Server Builder is not spec... | Implement the Python class `QuorumServerReporter` described below.
Class description:
Implement the QuorumServerReporter class.
Method signatures and docstrings:
- def __init__(self, builder, endpointReporter): @types: QuorumServerBuilder, netutils.EndpointReporter @raise ValueError: Quorum Server Builder is not spec... | c431e809e8d0f82e1bca7e3429dd0245560b5680 | <|skeleton|>
class QuorumServerReporter:
def __init__(self, builder, endpointReporter):
"""@types: QuorumServerBuilder, netutils.EndpointReporter @raise ValueError: Quorum Server Builder is not specified @raise ValueError: End-point reporter is not specified"""
<|body_0|>
def reportServer(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuorumServerReporter:
def __init__(self, builder, endpointReporter):
"""@types: QuorumServerBuilder, netutils.EndpointReporter @raise ValueError: Quorum Server Builder is not specified @raise ValueError: End-point reporter is not specified"""
if not builder:
raise ValueError('Quoru... | the_stack_v2_python_sparse | reference/ucmdb/discovery/service_guard.py | madmonkyang/cda-record | train | 0 | |
a637cbf19281f4d3af850234113a151b93c77ff4 | [
"d = collections.defaultdict(int)\nfor n in nums:\n d[n] += 1\ncounts = [[] for i in range(len(nums) + 1)]\nfor key in d:\n if d[key]:\n counts[d[key]].append(key)\nans = []\nc = len(nums)\nwhile len(ans) < k:\n if counts[c]:\n ans += counts[c]\n c -= 1\nreturn ans[:k]",
"d = collections... | <|body_start_0|>
d = collections.defaultdict(int)
for n in nums:
d[n] += 1
counts = [[] for i in range(len(nums) + 1)]
for key in d:
if d[key]:
counts[d[key]].append(key)
ans = []
c = len(nums)
while len(ans) < k:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def topKFrequent1(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def topKFrequent2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_1|>
def topKFrequent(self, nums, k):
... | stack_v2_sparse_classes_36k_train_028434 | 1,796 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: List[int]",
"name": "topKFrequent1",
"signature": "def topKFrequent1(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: List[int]",
"name": "topKFrequent2",
"signature": "def topKFrequent2(self, nums, k... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def topKFrequent1(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
- def topKFrequent2(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
- ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def topKFrequent1(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
- def topKFrequent2(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
- ... | 763674fcbe271af3d21eed790c3968c4d33f7b09 | <|skeleton|>
class Solution:
def topKFrequent1(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def topKFrequent2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_1|>
def topKFrequent(self, nums, k):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def topKFrequent1(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
d = collections.defaultdict(int)
for n in nums:
d[n] += 1
counts = [[] for i in range(len(nums) + 1)]
for key in d:
if d[key]:
... | the_stack_v2_python_sparse | 347_topk_frequent_elements/347.py | guzhoudiaoke/leetcode_python3 | train | 0 | |
df5aae72c2b7cb7c3de4c2736d228c58523f3b9f | [
"self.eof_index = -1\nself.timeout_index = -1\nself._strings = []\nself.longest_string = 0\nfor n, s in enumerate(strings):\n if s is EOF:\n self.eof_index = n\n continue\n if s is TIMEOUT:\n self.timeout_index = n\n continue\n self._strings.append((n, s))\n if len(s) > self.... | <|body_start_0|>
self.eof_index = -1
self.timeout_index = -1
self._strings = []
self.longest_string = 0
for n, s in enumerate(strings):
if s is EOF:
self.eof_index = n
continue
if s is TIMEOUT:
self.timeout_i... | This is a plain string search helper for the spawn.expect_any() method. This helper class is for speed. For more powerful regex patterns see the helper class, searcher_re. Attributes: eof_index - index of EOF, or -1 timeout_index - index of TIMEOUT, or -1 After a successful match by the search() method the following at... | searcher_string | [
"ISC",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-other-copyleft",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class searcher_string:
"""This is a plain string search helper for the spawn.expect_any() method. This helper class is for speed. For more powerful regex patterns see the helper class, searcher_re. Attributes: eof_index - index of EOF, or -1 timeout_index - index of TIMEOUT, or -1 After a successful ma... | stack_v2_sparse_classes_36k_train_028435 | 13,827 | permissive | [
{
"docstring": "This creates an instance of searcher_string. This argument 'strings' may be a list; a sequence of strings; or the EOF or TIMEOUT types.",
"name": "__init__",
"signature": "def __init__(self, strings)"
},
{
"docstring": "This returns a human-readable string that represents the sta... | 3 | null | Implement the Python class `searcher_string` described below.
Class description:
This is a plain string search helper for the spawn.expect_any() method. This helper class is for speed. For more powerful regex patterns see the helper class, searcher_re. Attributes: eof_index - index of EOF, or -1 timeout_index - index ... | Implement the Python class `searcher_string` described below.
Class description:
This is a plain string search helper for the spawn.expect_any() method. This helper class is for speed. For more powerful regex patterns see the helper class, searcher_re. Attributes: eof_index - index of EOF, or -1 timeout_index - index ... | f5042e35b945aded77b23470ead62d7eacefde92 | <|skeleton|>
class searcher_string:
"""This is a plain string search helper for the spawn.expect_any() method. This helper class is for speed. For more powerful regex patterns see the helper class, searcher_re. Attributes: eof_index - index of EOF, or -1 timeout_index - index of TIMEOUT, or -1 After a successful ma... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class searcher_string:
"""This is a plain string search helper for the spawn.expect_any() method. This helper class is for speed. For more powerful regex patterns see the helper class, searcher_re. Attributes: eof_index - index of EOF, or -1 timeout_index - index of TIMEOUT, or -1 After a successful match by the se... | the_stack_v2_python_sparse | contrib/python/pexpect/pexpect/expect.py | catboost/catboost | train | 8,012 |
b5b5b22f8fe0931962d950b57199771fdde231f3 | [
"self.eps_init = eps_init\nself.eps_mid = eps_mid\nself.eps_final = eps_final\nself.eps_eval = eps_eval\nself.init2mid_annealing_episode = init2mid_annealing_episode\nself.start_episode = start_episode\nself.mid_episode = self.start_episode + self.init2mid_annealing_episode\nself.max_episode = max_episode\nself.slo... | <|body_start_0|>
self.eps_init = eps_init
self.eps_mid = eps_mid
self.eps_final = eps_final
self.eps_eval = eps_eval
self.init2mid_annealing_episode = init2mid_annealing_episode
self.start_episode = start_episode
self.mid_episode = self.start_episode + self.init2m... | Exploration and exploitation compromise calculates epsilon value depending on parameters and current episode number | ExplorationExploitationClass | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExplorationExploitationClass:
"""Exploration and exploitation compromise calculates epsilon value depending on parameters and current episode number"""
def __init__(self, eps_init=1, eps_mid=0.2, eps_final=0.01, eps_eval=0, init2mid_annealing_episode=500, start_episode=0, max_episode=5000):
... | stack_v2_sparse_classes_36k_train_028436 | 2,862 | permissive | [
{
"docstring": "From eps_init decay to eps_mid within period start_episode to start_episode+init2mid_annealing_episode, Then, from eps_mid decay to eps_final within period start_episode+init2mid_annealing_episode to max_episode. Args: eps_init: Float, Exploration probability for the first episode eps_mid: Float... | 2 | stack_v2_sparse_classes_30k_train_001819 | Implement the Python class `ExplorationExploitationClass` described below.
Class description:
Exploration and exploitation compromise calculates epsilon value depending on parameters and current episode number
Method signatures and docstrings:
- def __init__(self, eps_init=1, eps_mid=0.2, eps_final=0.01, eps_eval=0, ... | Implement the Python class `ExplorationExploitationClass` described below.
Class description:
Exploration and exploitation compromise calculates epsilon value depending on parameters and current episode number
Method signatures and docstrings:
- def __init__(self, eps_init=1, eps_mid=0.2, eps_final=0.01, eps_eval=0, ... | 334df1e8afbfff3544413ade46fb12f03556014b | <|skeleton|>
class ExplorationExploitationClass:
"""Exploration and exploitation compromise calculates epsilon value depending on parameters and current episode number"""
def __init__(self, eps_init=1, eps_mid=0.2, eps_final=0.01, eps_eval=0, init2mid_annealing_episode=500, start_episode=0, max_episode=5000):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExplorationExploitationClass:
"""Exploration and exploitation compromise calculates epsilon value depending on parameters and current episode number"""
def __init__(self, eps_init=1, eps_mid=0.2, eps_final=0.01, eps_eval=0, init2mid_annealing_episode=500, start_episode=0, max_episode=5000):
"""Fr... | the_stack_v2_python_sparse | utils/expl_expt.py | Abluceli/HRG-SAC | train | 7 |
4b5138967c1399153a6017b312fffa391e733bdc | [
"cycletime = '20171122T0000Z'\ndt = 419808.0\nresult = cycletime_to_number(cycletime)\nself.assertIsInstance(result, float)\nself.assertAlmostEqual(result, dt)",
"cycletime = '201711220000'\ndt = 419808.0\nresult = cycletime_to_number(cycletime, cycletime_format='%Y%m%d%H%M')\nself.assertAlmostEqual(result, dt)",... | <|body_start_0|>
cycletime = '20171122T0000Z'
dt = 419808.0
result = cycletime_to_number(cycletime)
self.assertIsInstance(result, float)
self.assertAlmostEqual(result, dt)
<|end_body_0|>
<|body_start_1|>
cycletime = '201711220000'
dt = 419808.0
result = c... | Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value. | Test_cycletime_to_number | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_cycletime_to_number:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value."""
def test_basic(self):
"""Test that a number is returned of the expected value."""
<|body_0|>
def test_cycletime_format_defined(self):
... | stack_v2_sparse_classes_36k_train_028437 | 19,622 | permissive | [
{
"docstring": "Test that a number is returned of the expected value.",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test when a cycletime is defined.",
"name": "test_cycletime_format_defined",
"signature": "def test_cycletime_format_defined(self)"
},
... | 4 | null | Implement the Python class `Test_cycletime_to_number` described below.
Class description:
Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value.
Method signatures and docstrings:
- def test_basic(self): Test that a number is returned of the expected value.
- def test_cycletim... | Implement the Python class `Test_cycletime_to_number` described below.
Class description:
Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value.
Method signatures and docstrings:
- def test_basic(self): Test that a number is returned of the expected value.
- def test_cycletim... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_cycletime_to_number:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value."""
def test_basic(self):
"""Test that a number is returned of the expected value."""
<|body_0|>
def test_cycletime_format_defined(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_cycletime_to_number:
"""Test that a cycletime of a format such as YYYYMMDDTHHMMZ is converted into a numeric time value."""
def test_basic(self):
"""Test that a number is returned of the expected value."""
cycletime = '20171122T0000Z'
dt = 419808.0
result = cycletime_... | the_stack_v2_python_sparse | improver_tests/utilities/temporal/test_temporal.py | metoppv/improver | train | 101 |
3a31009a3d6a71eeda31ed4d942766d16d687c47 | [
"if model.confirmed_at:\n return '已验证'\nmail_url = url_for('.send_mail_view')\n_html = '\\n <form action=\"{mail_url}\" method=\"POST\">\\n <input id=\"user_id\" name=\"user_id\" type=\"hidden\" value=\"{user_id}\">\\n <button class=\"btn btn-info\" type=\\'submit\\'>发送邮... | <|body_start_0|>
if model.confirmed_at:
return '已验证'
mail_url = url_for('.send_mail_view')
_html = '\n <form action="{mail_url}" method="POST">\n <input id="user_id" name="user_id" type="hidden" value="{user_id}">\n <button class="btn btn-inf... | 用户管理 由于权限和用户是viewonly属性，所以权限只能是查看 | UserModelView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserModelView:
"""用户管理 由于权限和用户是viewonly属性，所以权限只能是查看"""
def _send_mail(self, _, model, __):
"""验证邮件栏目"""
<|body_0|>
def send_mail_view(self):
"""发送验证邮件"""
<|body_1|>
def on_model_change(self, form, model, is_created):
"""创建新账户时设置密码"""
... | stack_v2_sparse_classes_36k_train_028438 | 5,835 | permissive | [
{
"docstring": "验证邮件栏目",
"name": "_send_mail",
"signature": "def _send_mail(self, _, model, __)"
},
{
"docstring": "发送验证邮件",
"name": "send_mail_view",
"signature": "def send_mail_view(self)"
},
{
"docstring": "创建新账户时设置密码",
"name": "on_model_change",
"signature": "def on_m... | 3 | null | Implement the Python class `UserModelView` described below.
Class description:
用户管理 由于权限和用户是viewonly属性，所以权限只能是查看
Method signatures and docstrings:
- def _send_mail(self, _, model, __): 验证邮件栏目
- def send_mail_view(self): 发送验证邮件
- def on_model_change(self, form, model, is_created): 创建新账户时设置密码 | Implement the Python class `UserModelView` described below.
Class description:
用户管理 由于权限和用户是viewonly属性，所以权限只能是查看
Method signatures and docstrings:
- def _send_mail(self, _, model, __): 验证邮件栏目
- def send_mail_view(self): 发送验证邮件
- def on_model_change(self, form, model, is_created): 创建新账户时设置密码
<|skeleton|>
class UserMo... | 4f866b2264e224389c99bbbdb4521f4b0799b2a3 | <|skeleton|>
class UserModelView:
"""用户管理 由于权限和用户是viewonly属性，所以权限只能是查看"""
def _send_mail(self, _, model, __):
"""验证邮件栏目"""
<|body_0|>
def send_mail_view(self):
"""发送验证邮件"""
<|body_1|>
def on_model_change(self, form, model, is_created):
"""创建新账户时设置密码"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserModelView:
"""用户管理 由于权限和用户是viewonly属性，所以权限只能是查看"""
def _send_mail(self, _, model, __):
"""验证邮件栏目"""
if model.confirmed_at:
return '已验证'
mail_url = url_for('.send_mail_view')
_html = '\n <form action="{mail_url}" method="POST">\n <i... | the_stack_v2_python_sparse | admin/views/users.py | ssfdust/full-stack-flask-smorest | train | 39 |
39b90b767a0c2e78d513c660f0f122879701b22c | [
"self.build_settings = build_settings\nself.images_requested = images_requested\nself.tag = tag\nself.images_to_build = {}\nself.images_provided = {}\nfor name, di in images_requested.items():\n identifier = di['identifier']\n build_config = di['build_config']\n if build_config is None:\n self.image... | <|body_start_0|>
self.build_settings = build_settings
self.images_requested = images_requested
self.tag = tag
self.images_to_build = {}
self.images_provided = {}
for name, di in images_requested.items():
identifier = di['identifier']
build_config =... | Manages the following: 1) Figure out what docker images need to be built 2) Build (and push) them | SurrealDockerBuilder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SurrealDockerBuilder:
"""Manages the following: 1) Figure out what docker images need to be built 2) Build (and push) them"""
def __init__(self, build_settings, images_requested, tag, push=False):
"""Figures out what docker images need to be built Populates self.images_provided which... | stack_v2_sparse_classes_36k_train_028439 | 2,893 | permissive | [
{
"docstring": "Figures out what docker images need to be built Populates self.images_provided which computes {name: identifier} for all images Args: build_settings (dict): {build_settings_name: {<docker build setting accepted by symphony.addons.DockerBuilder.from_dict>}} images_requested (dict): { image_name: ... | 2 | stack_v2_sparse_classes_30k_train_009271 | Implement the Python class `SurrealDockerBuilder` described below.
Class description:
Manages the following: 1) Figure out what docker images need to be built 2) Build (and push) them
Method signatures and docstrings:
- def __init__(self, build_settings, images_requested, tag, push=False): Figures out what docker ima... | Implement the Python class `SurrealDockerBuilder` described below.
Class description:
Manages the following: 1) Figure out what docker images need to be built 2) Build (and push) them
Method signatures and docstrings:
- def __init__(self, build_settings, images_requested, tag, push=False): Figures out what docker ima... | 2556bd9c362a53e0a94da914ba59b5d4621c4081 | <|skeleton|>
class SurrealDockerBuilder:
"""Manages the following: 1) Figure out what docker images need to be built 2) Build (and push) them"""
def __init__(self, build_settings, images_requested, tag, push=False):
"""Figures out what docker images need to be built Populates self.images_provided which... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SurrealDockerBuilder:
"""Manages the following: 1) Figure out what docker images need to be built 2) Build (and push) them"""
def __init__(self, build_settings, images_requested, tag, push=False):
"""Figures out what docker images need to be built Populates self.images_provided which computes {na... | the_stack_v2_python_sparse | surreal/launch/build_images.py | PeihongYu/surreal | train | 0 |
86606bc769437f84b37de8eb1be2a52e0111826a | [
"dct = self._base_map(no_owner)\nif '.' in self.parser:\n sch, pars = self.parser.split('.')\n if sch == self.schema:\n dct['parser'] = pars\nreturn dct",
"clauses = []\nclauses.append('PARSER = %s' % self.parser)\nreturn ['CREATE TEXT SEARCH CONFIGURATION %s (\\n %s)' % (self.qualname(), ',\\n ... | <|body_start_0|>
dct = self._base_map(no_owner)
if '.' in self.parser:
sch, pars = self.parser.split('.')
if sch == self.schema:
dct['parser'] = pars
return dct
<|end_body_0|>
<|body_start_1|>
clauses = []
clauses.append('PARSER = %s' % se... | A text search configuration definition | TSConfiguration | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TSConfiguration:
"""A text search configuration definition"""
def to_map(self, no_owner):
"""Convert a text search configuration to a YAML-suitable format :return: dictionary"""
<|body_0|>
def create(self):
"""Return SQL statements to CREATE the configuration :re... | stack_v2_sparse_classes_36k_train_028440 | 15,925 | permissive | [
{
"docstring": "Convert a text search configuration to a YAML-suitable format :return: dictionary",
"name": "to_map",
"signature": "def to_map(self, no_owner)"
},
{
"docstring": "Return SQL statements to CREATE the configuration :return: SQL statements",
"name": "create",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_021090 | Implement the Python class `TSConfiguration` described below.
Class description:
A text search configuration definition
Method signatures and docstrings:
- def to_map(self, no_owner): Convert a text search configuration to a YAML-suitable format :return: dictionary
- def create(self): Return SQL statements to CREATE ... | Implement the Python class `TSConfiguration` described below.
Class description:
A text search configuration definition
Method signatures and docstrings:
- def to_map(self, no_owner): Convert a text search configuration to a YAML-suitable format :return: dictionary
- def create(self): Return SQL statements to CREATE ... | 0133f3bc522890e0564d27de6791824acb4d2773 | <|skeleton|>
class TSConfiguration:
"""A text search configuration definition"""
def to_map(self, no_owner):
"""Convert a text search configuration to a YAML-suitable format :return: dictionary"""
<|body_0|>
def create(self):
"""Return SQL statements to CREATE the configuration :re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TSConfiguration:
"""A text search configuration definition"""
def to_map(self, no_owner):
"""Convert a text search configuration to a YAML-suitable format :return: dictionary"""
dct = self._base_map(no_owner)
if '.' in self.parser:
sch, pars = self.parser.split('.')
... | the_stack_v2_python_sparse | pyrseas/dbobject/textsearch.py | vayerx/Pyrseas | train | 1 |
5fa73a8ebf6fd62932240b5afa1b959a7d194915 | [
"self.key = key\nself.count = count\nself.is_cluster = False\nself.children = None",
"if self.children is None:\n self.children = dict()\nkey, count = values[pos]\nif key not in self.children:\n self.children[key] = Node(key=key, count=count)\nnode = self.children[key]\nif len(values) == pos + 1:\n resul... | <|body_start_0|>
self.key = key
self.count = count
self.is_cluster = False
self.children = None
<|end_body_0|>
<|body_start_1|>
if self.children is None:
self.children = dict()
key, count = values[pos]
if key not in self.children:
self.chi... | Node in the cluster index. | Node | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
"""Node in the cluster index."""
def __init__(self, key: str, count: int):
"""Initialize the node key and frequency count. Parameters ---------- key: string Value in a cluster. count: int Frequency of the value."""
<|body_0|>
def add(self, values: List[Tuple[str, i... | stack_v2_sparse_classes_36k_train_028441 | 2,787 | permissive | [
{
"docstring": "Initialize the node key and frequency count. Parameters ---------- key: string Value in a cluster. count: int Frequency of the value.",
"name": "__init__",
"signature": "def __init__(self, key: str, count: int)"
},
{
"docstring": "Add the values in the given list starting from ``... | 2 | null | Implement the Python class `Node` described below.
Class description:
Node in the cluster index.
Method signatures and docstrings:
- def __init__(self, key: str, count: int): Initialize the node key and frequency count. Parameters ---------- key: string Value in a cluster. count: int Frequency of the value.
- def add... | Implement the Python class `Node` described below.
Class description:
Node in the cluster index.
Method signatures and docstrings:
- def __init__(self, key: str, count: int): Initialize the node key and frequency count. Parameters ---------- key: string Value in a cluster. count: int Frequency of the value.
- def add... | e3d0e04f90468c49f29ca53edc2feb12465c24d5 | <|skeleton|>
class Node:
"""Node in the cluster index."""
def __init__(self, key: str, count: int):
"""Initialize the node key and frequency count. Parameters ---------- key: string Value in a cluster. count: int Frequency of the value."""
<|body_0|>
def add(self, values: List[Tuple[str, i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
"""Node in the cluster index."""
def __init__(self, key: str, count: int):
"""Initialize the node key and frequency count. Parameters ---------- key: string Value in a cluster. count: int Frequency of the value."""
self.key = key
self.count = count
self.is_cluster = ... | the_stack_v2_python_sparse | openclean/cluster/index.py | Denisfench/openclean-core | train | 0 |
d212b6c73ece8e4a11261fbf50c893dddbce2086 | [
"def canShip(m):\n t, days = (0, 0)\n for w in weights:\n if t + w > m:\n days += 1\n t = w\n else:\n t += w\n return days + 1 <= D\nl, r = (max(weights), sum(weights))\nwhile l < r:\n mid = l + (r - l) // 2\n if canShip(mid):\n r = mid\n else:... | <|body_start_0|>
def canShip(m):
t, days = (0, 0)
for w in weights:
if t + w > m:
days += 1
t = w
else:
t += w
return days + 1 <= D
l, r = (max(weights), sum(weights))
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shipWithinDaysAC(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
<|body_0|>
def shipWithinDays(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_028442 | 3,083 | no_license | [
{
"docstring": ":type weights: List[int] :type D: int :rtype: int",
"name": "shipWithinDaysAC",
"signature": "def shipWithinDaysAC(self, weights, D)"
},
{
"docstring": ":type weights: List[int] :type D: int :rtype: int",
"name": "shipWithinDays",
"signature": "def shipWithinDays(self, we... | 2 | stack_v2_sparse_classes_30k_train_001595 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shipWithinDaysAC(self, weights, D): :type weights: List[int] :type D: int :rtype: int
- def shipWithinDays(self, weights, D): :type weights: List[int] :type D: int :rtype: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shipWithinDaysAC(self, weights, D): :type weights: List[int] :type D: int :rtype: int
- def shipWithinDays(self, weights, D): :type weights: List[int] :type D: int :rtype: in... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def shipWithinDaysAC(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
<|body_0|>
def shipWithinDays(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def shipWithinDaysAC(self, weights, D):
""":type weights: List[int] :type D: int :rtype: int"""
def canShip(m):
t, days = (0, 0)
for w in weights:
if t + w > m:
days += 1
t = w
else:
... | the_stack_v2_python_sparse | C/CapacityToShipPackagesWithinDDays.py | bssrdf/pyleet | train | 2 | |
9f701c10f6583d335e057396be8593465301dff5 | [
"client_ip, is_routable = get_client_ip(self.request)\nobject = get_object_or_404(Production, slug=slug)\nself.check_object_permissions(request, object)\nread_serializer = ProductionRetrieveSerializer(object, many=False, context={'authenticated_by': request.user, 'authenticated_from': client_ip, 'authenticated_from... | <|body_start_0|>
client_ip, is_routable = get_client_ip(self.request)
object = get_object_or_404(Production, slug=slug)
self.check_object_permissions(request, object)
read_serializer = ProductionRetrieveSerializer(object, many=False, context={'authenticated_by': request.user, 'authentica... | ProductionRetrieveUpdateAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductionRetrieveUpdateAPIView:
def get(self, request, slug=None):
"""Retrieve"""
<|body_0|>
def put(self, request, slug=None):
"""Update"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
client_ip, is_routable = get_client_ip(self.request)
o... | stack_v2_sparse_classes_36k_train_028443 | 3,226 | permissive | [
{
"docstring": "Retrieve",
"name": "get",
"signature": "def get(self, request, slug=None)"
},
{
"docstring": "Update",
"name": "put",
"signature": "def put(self, request, slug=None)"
}
] | 2 | null | Implement the Python class `ProductionRetrieveUpdateAPIView` described below.
Class description:
Implement the ProductionRetrieveUpdateAPIView class.
Method signatures and docstrings:
- def get(self, request, slug=None): Retrieve
- def put(self, request, slug=None): Update | Implement the Python class `ProductionRetrieveUpdateAPIView` described below.
Class description:
Implement the ProductionRetrieveUpdateAPIView class.
Method signatures and docstrings:
- def get(self, request, slug=None): Retrieve
- def put(self, request, slug=None): Update
<|skeleton|>
class ProductionRetrieveUpdate... | 98e1ff8bab7dda3492e5ff637bf5aafd111c840c | <|skeleton|>
class ProductionRetrieveUpdateAPIView:
def get(self, request, slug=None):
"""Retrieve"""
<|body_0|>
def put(self, request, slug=None):
"""Update"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductionRetrieveUpdateAPIView:
def get(self, request, slug=None):
"""Retrieve"""
client_ip, is_routable = get_client_ip(self.request)
object = get_object_or_404(Production, slug=slug)
self.check_object_permissions(request, object)
read_serializer = ProductionRetrieveS... | the_stack_v2_python_sparse | mikaponics/production/views/resource_views/production_retrieve_update_view.py | mikaponics/mikaponics-back | train | 4 | |
8e32ba5baf6f91b4f865ee937cd5284d503a14fc | [
"N = len(nums)\nans = [1] * N\nfor i in range(1, N):\n ans[i] = nums[i - 1] * ans[i - 1]\nright = 1\nfor i in range(N - 1, -1, -1):\n ans[i] *= right\n right = right * nums[i]\nreturn ans",
"N = len(nums)\nL = [1] * N\nR = [1] * N\nans = [1] * N\nfor i in range(1, N):\n L[i] = nums[i - 1] * L[i - 1]\n... | <|body_start_0|>
N = len(nums)
ans = [1] * N
for i in range(1, N):
ans[i] = nums[i - 1] * ans[i - 1]
right = 1
for i in range(N - 1, -1, -1):
ans[i] *= right
right = right * nums[i]
return ans
<|end_body_0|>
<|body_start_1|>
N ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def productExceptSelfO1Space(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
N = len(nums)
... | stack_v2_sparse_classes_36k_train_028444 | 1,592 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelfO1Space",
"signature": "def productExceptSelfO1Space(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums)"... | 2 | stack_v2_sparse_classes_30k_train_006926 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelfO1Space(self, nums): :type nums: List[int] :rtype: List[int]
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelfO1Space(self, nums): :type nums: List[int] :rtype: List[int]
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
class... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def productExceptSelfO1Space(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def productExceptSelfO1Space(self, nums):
""":type nums: List[int] :rtype: List[int]"""
N = len(nums)
ans = [1] * N
for i in range(1, N):
ans[i] = nums[i - 1] * ans[i - 1]
right = 1
for i in range(N - 1, -1, -1):
ans[i] *= right... | the_stack_v2_python_sparse | P/ProductofArrayExceptSelf.py | bssrdf/pyleet | train | 2 | |
025193f000837a77cf88b95b37d345daddd2cfc4 | [
"S = S.upper()\nl = len(S)\ndicts = {char: [[], 0] for char in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'}\nfor i, char in enumerate(S):\n dicts[char][0].append(i)\nans = 0\nprint(dicts)\nfor i, char in enumerate(S):\n pos = dicts[char][1]\n if pos - 1 >= 0:\n left = dicts[char][0][pos - 1]\n else:\n le... | <|body_start_0|>
S = S.upper()
l = len(S)
dicts = {char: [[], 0] for char in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'}
for i, char in enumerate(S):
dicts[char][0].append(i)
ans = 0
print(dicts)
for i, char in enumerate(S):
pos = dicts[char][1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniqueLetterString(self, S):
""":type S: str :rtype: int 517 ms"""
<|body_0|>
def uniqueLetterString_1(self, S):
"""136ms :param S: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
S = S.upper()
l = len(S)
dicts... | stack_v2_sparse_classes_36k_train_028445 | 2,560 | no_license | [
{
"docstring": ":type S: str :rtype: int 517 ms",
"name": "uniqueLetterString",
"signature": "def uniqueLetterString(self, S)"
},
{
"docstring": "136ms :param S: :return:",
"name": "uniqueLetterString_1",
"signature": "def uniqueLetterString_1(self, S)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004237 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniqueLetterString(self, S): :type S: str :rtype: int 517 ms
- def uniqueLetterString_1(self, S): 136ms :param S: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniqueLetterString(self, S): :type S: str :rtype: int 517 ms
- def uniqueLetterString_1(self, S): 136ms :param S: :return:
<|skeleton|>
class Solution:
def uniqueLetter... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def uniqueLetterString(self, S):
""":type S: str :rtype: int 517 ms"""
<|body_0|>
def uniqueLetterString_1(self, S):
"""136ms :param S: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def uniqueLetterString(self, S):
""":type S: str :rtype: int 517 ms"""
S = S.upper()
l = len(S)
dicts = {char: [[], 0] for char in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'}
for i, char in enumerate(S):
dicts[char][0].append(i)
ans = 0
print(dic... | the_stack_v2_python_sparse | UniqueLetterString_HARD_828.py | 953250587/leetcode-python | train | 2 | |
5e6fd7af273e4b69cdadb9c3324341d542123d57 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Authentication()",
"from .authentication_method import AuthenticationMethod\nfrom .email_authentication_method import EmailAuthenticationMethod\nfrom .entity import Entity\nfrom .fido2_authentication_method import Fido2AuthenticationMe... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Authentication()
<|end_body_0|>
<|body_start_1|>
from .authentication_method import AuthenticationMethod
from .email_authentication_method import EmailAuthenticationMethod
from .... | Authentication | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Authentication:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication:
"""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 Retur... | stack_v2_sparse_classes_36k_train_028446 | 8,427 | 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: Authentication",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | stack_v2_sparse_classes_30k_train_018650 | Implement the Python class `Authentication` described below.
Class description:
Implement the Authentication class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `Authentication` described below.
Class description:
Implement the Authentication class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Authentication:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication:
"""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 Retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Authentication:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Authentication:
"""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: Authentica... | the_stack_v2_python_sparse | msgraph/generated/models/authentication.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e2102c8b12d07505bba1a538198dc2624663b616 | [
"super().__init__(sdc_values=sdc_values, version=version, properties=properties, inputs=inputs, category=category, subcategory=subcategory)\nself.name: str = name or 'ONAP-test-PNF'\nself.vendor: Vendor = vendor\nself.vsp: Vsp = vsp",
"if not self.vsp and (not self.vendor):\n raise ParameterError('Neither Vsp ... | <|body_start_0|>
super().__init__(sdc_values=sdc_values, version=version, properties=properties, inputs=inputs, category=category, subcategory=subcategory)
self.name: str = name or 'ONAP-test-PNF'
self.vendor: Vendor = vendor
self.vsp: Vsp = vsp
<|end_body_0|>
<|body_start_1|>
i... | ONAP PNF Object used for SDC operations. Attributes: name (str): the name of the pnf. Defaults to "ONAP-test-PNF". identifier (str): the unique ID of the pnf from SDC. status (str): the status of the pnf from SDC. version (str): the version ID of the vendor from SDC. uuid (str): the UUID of the PNF (which is different ... | Pnf | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pnf:
"""ONAP PNF Object used for SDC operations. Attributes: name (str): the name of the pnf. Defaults to "ONAP-test-PNF". identifier (str): the unique ID of the pnf from SDC. status (str): the status of the pnf from SDC. version (str): the version ID of the vendor from SDC. uuid (str): the UUID ... | stack_v2_sparse_classes_36k_train_028447 | 2,481 | permissive | [
{
"docstring": "Initialize pnf object. Args: name (optional): the name of the pnf version (str, optional): the version of a PNF object",
"name": "__init__",
"signature": "def __init__(self, name: str=None, version: str=None, vendor: Vendor=None, sdc_values: Dict[str, str]=None, vsp: Vsp=None, properties... | 3 | null | Implement the Python class `Pnf` described below.
Class description:
ONAP PNF Object used for SDC operations. Attributes: name (str): the name of the pnf. Defaults to "ONAP-test-PNF". identifier (str): the unique ID of the pnf from SDC. status (str): the status of the pnf from SDC. version (str): the version ID of the... | Implement the Python class `Pnf` described below.
Class description:
ONAP PNF Object used for SDC operations. Attributes: name (str): the name of the pnf. Defaults to "ONAP-test-PNF". identifier (str): the unique ID of the pnf from SDC. status (str): the status of the pnf from SDC. version (str): the version ID of the... | b204aa63043825290d4c0a940edd7e9241f6c0ee | <|skeleton|>
class Pnf:
"""ONAP PNF Object used for SDC operations. Attributes: name (str): the name of the pnf. Defaults to "ONAP-test-PNF". identifier (str): the unique ID of the pnf from SDC. status (str): the status of the pnf from SDC. version (str): the version ID of the vendor from SDC. uuid (str): the UUID ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Pnf:
"""ONAP PNF Object used for SDC operations. Attributes: name (str): the name of the pnf. Defaults to "ONAP-test-PNF". identifier (str): the unique ID of the pnf from SDC. status (str): the status of the pnf from SDC. version (str): the version ID of the vendor from SDC. uuid (str): the UUID of the PNF (w... | the_stack_v2_python_sparse | src/onapsdk/sdc/pnf.py | Orange-OpenSource/python-onapsdk | train | 4 |
d6833695726151d1b0c10394847b834dcd352173 | [
"super(Model, self).__init__()\nself._input_shape = [-1, 28, 28, 1]\nself.conv1 = layers.Conv2D(32, 5, padding='same', data_format=data_format, activation=nn.relu)\nself.conv2 = layers.Conv2D(64, 5, padding='same', data_format=data_format, activation=nn.relu)\nself.fc1 = layers.Dense(1024, activation=nn.relu)\nself... | <|body_start_0|>
super(Model, self).__init__()
self._input_shape = [-1, 28, 28, 1]
self.conv1 = layers.Conv2D(32, 5, padding='same', data_format=data_format, activation=nn.relu)
self.conv2 = layers.Conv2D(64, 5, padding='same', data_format=data_format, activation=nn.relu)
self.fc... | Model to recognize digits in the MNIST dataset. Train and export savedmodel, used for testOnflyTrainMnistSavedModel Network structure is equivalent to: https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/examples/tutorials/mnist/mnist_deep.py and https://github.com/tensorflow/models/blob/master/tutorials/imag... | Model | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
"""Model to recognize digits in the MNIST dataset. Train and export savedmodel, used for testOnflyTrainMnistSavedModel Network structure is equivalent to: https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/examples/tutorials/mnist/mnist_deep.py and https://github.com/tensorflow/... | stack_v2_sparse_classes_36k_train_028448 | 10,776 | permissive | [
{
"docstring": "Creates a model for classifying a hand-written digit. Args: data_format: Either \"channels_first\" or \"channels_last\". \"channels_first\" is typically faster on GPUs while \"channels_last\" is typically faster on CPUs. See https://www.tensorflow.org/performance/performance_guide#data_formats",... | 2 | stack_v2_sparse_classes_30k_test_001168 | Implement the Python class `Model` described below.
Class description:
Model to recognize digits in the MNIST dataset. Train and export savedmodel, used for testOnflyTrainMnistSavedModel Network structure is equivalent to: https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/examples/tutorials/mnist/mnist_dee... | Implement the Python class `Model` described below.
Class description:
Model to recognize digits in the MNIST dataset. Train and export savedmodel, used for testOnflyTrainMnistSavedModel Network structure is equivalent to: https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/examples/tutorials/mnist/mnist_dee... | 181bc2b37aa8a3eeb11a942d8f330b04abc804b3 | <|skeleton|>
class Model:
"""Model to recognize digits in the MNIST dataset. Train and export savedmodel, used for testOnflyTrainMnistSavedModel Network structure is equivalent to: https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/examples/tutorials/mnist/mnist_deep.py and https://github.com/tensorflow/... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Model:
"""Model to recognize digits in the MNIST dataset. Train and export savedmodel, used for testOnflyTrainMnistSavedModel Network structure is equivalent to: https://github.com/tensorflow/tensorflow/blob/r1.5/tensorflow/examples/tutorials/mnist/mnist_deep.py and https://github.com/tensorflow/models/blob/m... | the_stack_v2_python_sparse | tensorflow/contrib/lite/python/convert_saved_model_test.py | zylo117/tensorflow-gpu-macosx | train | 116 |
b24e3c863e48554ff311e98e5fbd9828f15ac5e4 | [
"super(DecoderBlock, self).__init__()\nself.mha1 = MultiHeadAttention(dm, h)\nself.mha2 = MultiHeadAttention(dm, h)\nself.dense_hidden = tf.keras.layers.Dense(units=hidden, activation='relu')\nself.dense_output = tf.keras.layers.Dense(units=dm)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\ns... | <|body_start_0|>
super(DecoderBlock, self).__init__()
self.mha1 = MultiHeadAttention(dm, h)
self.mha2 = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(units=hidden, activation='relu')
self.dense_output = tf.keras.layers.Dense(units=dm)
self.layernorm1... | Class to create an decoder block for a transformer | DecoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderBlock:
"""Class to create an decoder block for a transformer"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Class constructor :param dm: an integer representing the dimensionality of the model :param h: an integer representing the number of heads :param hidden: the nu... | stack_v2_sparse_classes_36k_train_028449 | 2,864 | no_license | [
{
"docstring": "Class constructor :param dm: an integer representing the dimensionality of the model :param h: an integer representing the number of heads :param hidden: the number of hidden units in the fully connected layer :param drop_rate: the dropout rate",
"name": "__init__",
"signature": "def __i... | 2 | null | Implement the Python class `DecoderBlock` described below.
Class description:
Class to create an decoder block for a transformer
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Class constructor :param dm: an integer representing the dimensionality of the model :param h: an integ... | Implement the Python class `DecoderBlock` described below.
Class description:
Class to create an decoder block for a transformer
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Class constructor :param dm: an integer representing the dimensionality of the model :param h: an integ... | 856ee36006c2ff656877d592c2ddb7c941d63780 | <|skeleton|>
class DecoderBlock:
"""Class to create an decoder block for a transformer"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Class constructor :param dm: an integer representing the dimensionality of the model :param h: an integer representing the number of heads :param hidden: the nu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderBlock:
"""Class to create an decoder block for a transformer"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Class constructor :param dm: an integer representing the dimensionality of the model :param h: an integer representing the number of heads :param hidden: the number of hidde... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/8-transformer_decoder_block.py | garimasinghgryffindor/holbertonschool-machine_learning | train | 0 |
dabeaf7d14cd918d5ae92e58ae0a128fa0efe0f6 | [
"self.width = width\nself.height = height\nself.food = deque(food)\nself.snake = deque([[0, 0]])\nself.direct = {'U': [-1, 0], 'L': [0, -1], 'R': [0, +1], 'D': [1, 0]}\nprint('start from: 0, 0')",
"r0, c0 = self.snake[0]\nr1, c1 = self.direct[direction]\nnew_head = [r0 + r1, c0 + c1]\nif new_head[0] < 0 or new_he... | <|body_start_0|>
self.width = width
self.height = height
self.food = deque(food)
self.snake = deque([[0, 0]])
self.direct = {'U': [-1, 0], 'L': [0, -1], 'R': [0, +1], 'D': [1, 0]}
print('start from: 0, 0')
<|end_body_0|>
<|body_start_1|>
r0, c0 = self.snake[0]
... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k_train_028450 | 2,136 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :type height: int :type food: List[List[int]]",
... | 2 | null | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | bf98c8fa31043a45b3d21cfe78d4e08f9cac9de6 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :... | the_stack_v2_python_sparse | interviews/Palantir/353_design_snake_game.py | mistrydarshan99/Leetcode-3 | train | 0 | |
2054fc0ee98ac268f71744f7c2d8933d67eabee9 | [
"self.resultList = [None] * len(deferredList)\nDeferred.__init__(self)\nif len(deferredList) == 0 and (not fireOnOneCallback):\n self.callback(self.resultList)\nself.fireOnOneCallback = fireOnOneCallback\nself.fireOnOneErrback = fireOnOneErrback\nself.consumeErrors = consumeErrors\nself.finishedCount = 0\nindex ... | <|body_start_0|>
self.resultList = [None] * len(deferredList)
Deferred.__init__(self)
if len(deferredList) == 0 and (not fireOnOneCallback):
self.callback(self.resultList)
self.fireOnOneCallback = fireOnOneCallback
self.fireOnOneErrback = fireOnOneErrback
self... | I combine a group of deferreds into one callback. I track a list of L{Deferred}s for their callbacks, and make a single callback when they have all completed, a list of (success, result) tuples, 'success' being a boolean. Note that you can still use a L{Deferred} after putting it in a DeferredList. For example, you can... | DeferredList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeferredList:
"""I combine a group of deferreds into one callback. I track a list of L{Deferred}s for their callbacks, and make a single callback when they have all completed, a list of (success, result) tuples, 'success' being a boolean. Note that you can still use a L{Deferred} after putting it... | stack_v2_sparse_classes_36k_train_028451 | 3,907 | permissive | [
{
"docstring": "Initialize a DeferredList. @type deferredList: C{list} of L{Deferred}s @param deferredList: The list of deferreds to track. @param fireOnOneCallback: (keyword param) a flag indicating that only one callback needs to be fired for me to call my callback @param fireOnOneErrback: (keyword param) a f... | 2 | stack_v2_sparse_classes_30k_train_014847 | Implement the Python class `DeferredList` described below.
Class description:
I combine a group of deferreds into one callback. I track a list of L{Deferred}s for their callbacks, and make a single callback when they have all completed, a list of (success, result) tuples, 'success' being a boolean. Note that you can s... | Implement the Python class `DeferredList` described below.
Class description:
I combine a group of deferreds into one callback. I track a list of L{Deferred}s for their callbacks, and make a single callback when they have all completed, a list of (success, result) tuples, 'success' being a boolean. Note that you can s... | bf9c26051e8dfd1325bdc63aab1c560dbad7f6b7 | <|skeleton|>
class DeferredList:
"""I combine a group of deferreds into one callback. I track a list of L{Deferred}s for their callbacks, and make a single callback when they have all completed, a list of (success, result) tuples, 'success' being a boolean. Note that you can still use a L{Deferred} after putting it... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeferredList:
"""I combine a group of deferreds into one callback. I track a list of L{Deferred}s for their callbacks, and make a single callback when they have all completed, a list of (success, result) tuples, 'success' being a boolean. Note that you can still use a L{Deferred} after putting it in a Deferre... | the_stack_v2_python_sparse | Vertex/vertex/_unfortunate_defer_hack.py | feitianyiren/divmod.org | train | 0 |
e4ee08938bd9106e6c0f1d1ca0d18a06a202bbbd | [
"if type(self.nburn) in [float, int]:\n logger.info(f'Discarding {self.nburn} steps for burn-in')\nelif self.result.max_autocorrelation_time is None:\n logger.info(f'Autocorrelation time not calculated, discarding {self.nburn} steps for burn-in')\nelse:\n logger.info(f'Discarding {self.nburn} steps for bur... | <|body_start_0|>
if type(self.nburn) in [float, int]:
logger.info(f'Discarding {self.nburn} steps for burn-in')
elif self.result.max_autocorrelation_time is None:
logger.info(f'Autocorrelation time not calculated, discarding {self.nburn} steps for burn-in')
else:
... | MCMCSampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MCMCSampler:
def print_nburn_logging_info(self):
"""Prints logging info as to how nburn was calculated"""
<|body_0|>
def calculate_autocorrelation(self, samples, c=3):
"""Uses the `emcee.autocorr` module to estimate the autocorrelation Parameters ========== samples: ... | stack_v2_sparse_classes_36k_train_028452 | 36,082 | permissive | [
{
"docstring": "Prints logging info as to how nburn was calculated",
"name": "print_nburn_logging_info",
"signature": "def print_nburn_logging_info(self)"
},
{
"docstring": "Uses the `emcee.autocorr` module to estimate the autocorrelation Parameters ========== samples: array_like A chain of samp... | 2 | stack_v2_sparse_classes_30k_train_020393 | Implement the Python class `MCMCSampler` described below.
Class description:
Implement the MCMCSampler class.
Method signatures and docstrings:
- def print_nburn_logging_info(self): Prints logging info as to how nburn was calculated
- def calculate_autocorrelation(self, samples, c=3): Uses the `emcee.autocorr` module... | Implement the Python class `MCMCSampler` described below.
Class description:
Implement the MCMCSampler class.
Method signatures and docstrings:
- def print_nburn_logging_info(self): Prints logging info as to how nburn was calculated
- def calculate_autocorrelation(self, samples, c=3): Uses the `emcee.autocorr` module... | 9c1dda6cc1510692ce4ac75c608de5fae53e971c | <|skeleton|>
class MCMCSampler:
def print_nburn_logging_info(self):
"""Prints logging info as to how nburn was calculated"""
<|body_0|>
def calculate_autocorrelation(self, samples, c=3):
"""Uses the `emcee.autocorr` module to estimate the autocorrelation Parameters ========== samples: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MCMCSampler:
def print_nburn_logging_info(self):
"""Prints logging info as to how nburn was calculated"""
if type(self.nburn) in [float, int]:
logger.info(f'Discarding {self.nburn} steps for burn-in')
elif self.result.max_autocorrelation_time is None:
logger.inf... | the_stack_v2_python_sparse | bilby/core/sampler/base_sampler.py | khunsang/bilby | train | 0 | |
688e4ff0f0c1c6dd0ea62cbcc21c85b52de289e2 | [
"super().__init__()\nself.repository = repository\nself.commit_only = commit_only\nself.brain = Brain(repository)",
"if '/.' in event.src_path:\n return\nupdated_file = os.path.relpath(event.src_path, self.repository.original_path)\nif not updated_file or updated_file in self.repository.ignored_files or (not u... | <|body_start_0|>
super().__init__()
self.repository = repository
self.commit_only = commit_only
self.brain = Brain(repository)
<|end_body_0|>
<|body_start_1|>
if '/.' in event.src_path:
return
updated_file = os.path.relpath(event.src_path, self.repository.ori... | Is notified every time an event occurs on the fileystem and will snapshot the change | ChangeWatchdog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChangeWatchdog:
"""Is notified every time an event occurs on the fileystem and will snapshot the change"""
def __init__(self, repository, commit_only: bool):
"""Create a ChangeWatchdog instance"""
<|body_0|>
def on_any_event(self, event):
"""Catches all events"""... | stack_v2_sparse_classes_36k_train_028453 | 4,518 | no_license | [
{
"docstring": "Create a ChangeWatchdog instance",
"name": "__init__",
"signature": "def __init__(self, repository, commit_only: bool)"
},
{
"docstring": "Catches all events",
"name": "on_any_event",
"signature": "def on_any_event(self, event)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021501 | Implement the Python class `ChangeWatchdog` described below.
Class description:
Is notified every time an event occurs on the fileystem and will snapshot the change
Method signatures and docstrings:
- def __init__(self, repository, commit_only: bool): Create a ChangeWatchdog instance
- def on_any_event(self, event): ... | Implement the Python class `ChangeWatchdog` described below.
Class description:
Is notified every time an event occurs on the fileystem and will snapshot the change
Method signatures and docstrings:
- def __init__(self, repository, commit_only: bool): Create a ChangeWatchdog instance
- def on_any_event(self, event): ... | b669eab9abecfaf8310f0668a7e5f95b2308d885 | <|skeleton|>
class ChangeWatchdog:
"""Is notified every time an event occurs on the fileystem and will snapshot the change"""
def __init__(self, repository, commit_only: bool):
"""Create a ChangeWatchdog instance"""
<|body_0|>
def on_any_event(self, event):
"""Catches all events"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChangeWatchdog:
"""Is notified every time an event occurs on the fileystem and will snapshot the change"""
def __init__(self, repository, commit_only: bool):
"""Create a ChangeWatchdog instance"""
super().__init__()
self.repository = repository
self.commit_only = commit_on... | the_stack_v2_python_sparse | bug_buddy/watcher.py | NathanBWaters/bug_buddy | train | 0 |
a4600be0a16ad03e0b8c064d10dda43288b92713 | [
"phone = validated_data.get('phone')\ntry:\n self.User.objects.get(phone=phone)\n return Response(response_code.user_existed, status=status.HTTP_400_BAD_REQUEST)\nexcept self.User.DoesNotExist:\n code_status = self.redis.check_code(phone, validated_data.get('code'))\n if not code_status:\n return... | <|body_start_0|>
phone = validated_data.get('phone')
try:
self.User.objects.get(phone=phone)
return Response(response_code.user_existed, status=status.HTTP_400_BAD_REQUEST)
except self.User.DoesNotExist:
code_status = self.redis.check_code(phone, validated_dat... | 用户注册 | RegisterAPIView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterAPIView:
"""用户注册"""
def register_phone(self, validated_data):
"""手机注册"""
<|body_0|>
def register_email(self, validated_data):
"""邮箱注册"""
<|body_1|>
def factory(self, validated_data):
"""简单工厂管理用户不同注册方式"""
<|body_2|>
def po... | stack_v2_sparse_classes_36k_train_028454 | 6,225 | permissive | [
{
"docstring": "手机注册",
"name": "register_phone",
"signature": "def register_phone(self, validated_data)"
},
{
"docstring": "邮箱注册",
"name": "register_email",
"signature": "def register_email(self, validated_data)"
},
{
"docstring": "简单工厂管理用户不同注册方式",
"name": "factory",
"sig... | 4 | null | Implement the Python class `RegisterAPIView` described below.
Class description:
用户注册
Method signatures and docstrings:
- def register_phone(self, validated_data): 手机注册
- def register_email(self, validated_data): 邮箱注册
- def factory(self, validated_data): 简单工厂管理用户不同注册方式
- def post(self, request): 用户注册 | Implement the Python class `RegisterAPIView` described below.
Class description:
用户注册
Method signatures and docstrings:
- def register_phone(self, validated_data): 手机注册
- def register_email(self, validated_data): 邮箱注册
- def factory(self, validated_data): 简单工厂管理用户不同注册方式
- def post(self, request): 用户注册
<|skeleton|>
cl... | 13cb59130d15e782f78bc5148409bef0f1c516e0 | <|skeleton|>
class RegisterAPIView:
"""用户注册"""
def register_phone(self, validated_data):
"""手机注册"""
<|body_0|>
def register_email(self, validated_data):
"""邮箱注册"""
<|body_1|>
def factory(self, validated_data):
"""简单工厂管理用户不同注册方式"""
<|body_2|>
def po... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegisterAPIView:
"""用户注册"""
def register_phone(self, validated_data):
"""手机注册"""
phone = validated_data.get('phone')
try:
self.User.objects.get(phone=phone)
return Response(response_code.user_existed, status=status.HTTP_400_BAD_REQUEST)
except self.... | the_stack_v2_python_sparse | user_app/views/login_register_api.py | lmyfzx/Django-Mall | train | 0 |
e44a3f6dea27e0939e6d592d5fb05a558662f25f | [
"loader = ProductItemLoader(ProductItem(), response)\nloader.add_xpath('id', '//input[@name=\"product_id\"]/@value')\nloader.add_css('name', '.title-product')\nloader.add_css('category', '.breadcrumb > li:not(:first-child) > a')\nloader.add_css('price', '#thisIsOriginal')\nloader.add_css('description', '#tab-descri... | <|body_start_0|>
loader = ProductItemLoader(ProductItem(), response)
loader.add_xpath('id', '//input[@name="product_id"]/@value')
loader.add_css('name', '.title-product')
loader.add_css('category', '.breadcrumb > li:not(:first-child) > a')
loader.add_css('price', '#thisIsOriginal... | EssentialNaturalOils Products Spider | EssentialNaturalOilsProductsSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EssentialNaturalOilsProductsSpider:
"""EssentialNaturalOils Products Spider"""
def parse_product(self, response):
"""Extract product details @url https://www.essentialnaturaloils.com/natural-essential-oils/silver-fir-needle-essential-oil-abies-alba-oil @returns requests 1 1"""
... | stack_v2_sparse_classes_36k_train_028455 | 4,735 | no_license | [
{
"docstring": "Extract product details @url https://www.essentialnaturaloils.com/natural-essential-oils/silver-fir-needle-essential-oil-abies-alba-oil @returns requests 1 1",
"name": "parse_product",
"signature": "def parse_product(self, response)"
},
{
"docstring": "Extract product reviews @ur... | 2 | stack_v2_sparse_classes_30k_train_010794 | Implement the Python class `EssentialNaturalOilsProductsSpider` described below.
Class description:
EssentialNaturalOils Products Spider
Method signatures and docstrings:
- def parse_product(self, response): Extract product details @url https://www.essentialnaturaloils.com/natural-essential-oils/silver-fir-needle-ess... | Implement the Python class `EssentialNaturalOilsProductsSpider` described below.
Class description:
EssentialNaturalOils Products Spider
Method signatures and docstrings:
- def parse_product(self, response): Extract product details @url https://www.essentialnaturaloils.com/natural-essential-oils/silver-fir-needle-ess... | 67eeb08962725fd3aff8c8cb7e16360ffd651f06 | <|skeleton|>
class EssentialNaturalOilsProductsSpider:
"""EssentialNaturalOils Products Spider"""
def parse_product(self, response):
"""Extract product details @url https://www.essentialnaturaloils.com/natural-essential-oils/silver-fir-needle-essential-oil-abies-alba-oil @returns requests 1 1"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EssentialNaturalOilsProductsSpider:
"""EssentialNaturalOils Products Spider"""
def parse_product(self, response):
"""Extract product details @url https://www.essentialnaturaloils.com/natural-essential-oils/silver-fir-needle-essential-oil-abies-alba-oil @returns requests 1 1"""
loader = Pr... | the_stack_v2_python_sparse | pipeline/pipeline/spiders/essentialnaturaloils.py | DataRetrieval/pipeline | train | 1 |
f2bd0590aefc85d347cb33fb308221e2b72ce902 | [
"self._business_one = business_one\nself._business_two = business_two\nself._business_three = business_three",
"report_list = [self._business_one, self._business_two, self._business_three]\nrandom.shuffle(report_list)\nreport_list = report_list[0:random.randint(0, len(report_list))]\nreturn report_list"
] | <|body_start_0|>
self._business_one = business_one
self._business_two = business_two
self._business_three = business_three
<|end_body_0|>
<|body_start_1|>
report_list = [self._business_one, self._business_two, self._business_three]
random.shuffle(report_list)
report_list... | Assemble | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Assemble:
def __init__(self, business_one, business_two, business_three):
"""接受修改好的数据 :param business_one: :param business_two: :param business_three:"""
<|body_0|>
def single_element(self):
"""生成最终的上报数据 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_028456 | 785 | no_license | [
{
"docstring": "接受修改好的数据 :param business_one: :param business_two: :param business_three:",
"name": "__init__",
"signature": "def __init__(self, business_one, business_two, business_three)"
},
{
"docstring": "生成最终的上报数据 :return:",
"name": "single_element",
"signature": "def single_element... | 2 | stack_v2_sparse_classes_30k_train_000190 | Implement the Python class `Assemble` described below.
Class description:
Implement the Assemble class.
Method signatures and docstrings:
- def __init__(self, business_one, business_two, business_three): 接受修改好的数据 :param business_one: :param business_two: :param business_three:
- def single_element(self): 生成最终的上报数据 :r... | Implement the Python class `Assemble` described below.
Class description:
Implement the Assemble class.
Method signatures and docstrings:
- def __init__(self, business_one, business_two, business_three): 接受修改好的数据 :param business_one: :param business_two: :param business_three:
- def single_element(self): 生成最终的上报数据 :r... | 9dc610c68a2c6e3026725c1bb98c017edb51e2b9 | <|skeleton|>
class Assemble:
def __init__(self, business_one, business_two, business_three):
"""接受修改好的数据 :param business_one: :param business_two: :param business_three:"""
<|body_0|>
def single_element(self):
"""生成最终的上报数据 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Assemble:
def __init__(self, business_one, business_two, business_three):
"""接受修改好的数据 :param business_one: :param business_two: :param business_three:"""
self._business_one = business_one
self._business_two = business_two
self._business_three = business_three
def single_el... | the_stack_v2_python_sparse | hugh/simulat_probe/report_data/data_assemble/assemble.py | windorchidwarm/py_test_project | train | 0 | |
7d2bf70a1736b50409a315ef6f4f601f3d63e250 | [
"super(Matern32, self).__init__(n_dims=n_dims, active_dims=active_dims, name=name)\nlogger.debug('Initializing %s kernel.' % self.name)\nself.variance = np.float64(variance)\nself.lengthscale = np.float64(lengthscale)\nself.parameter_list = ['variance', 'lengthscale']\nself.constraint_map = {'variance': '+ve', 'len... | <|body_start_0|>
super(Matern32, self).__init__(n_dims=n_dims, active_dims=active_dims, name=name)
logger.debug('Initializing %s kernel.' % self.name)
self.variance = np.float64(variance)
self.lengthscale = np.float64(lengthscale)
self.parameter_list = ['variance', 'lengthscale']... | Matern32 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Matern32:
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specif... | stack_v2_sparse_classes_36k_train_028457 | 9,047 | no_license | [
{
"docstring": "squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specified",
"name": "__init__",
"signature": "def __init__(self, n_dims, variance=1.0, lengthscale=1.0, act... | 2 | stack_v2_sparse_classes_30k_train_021561 | Implement the Python class `Matern32` described below.
Class description:
Implement the Matern32 class.
Method signatures and docstrings:
- def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None): squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel varianc... | Implement the Python class `Matern32` described below.
Class description:
Implement the Matern32 class.
Method signatures and docstrings:
- def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None): squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel varianc... | 1bed882b8a94ee58fd0bde6920ee85f81ffb77bb | <|skeleton|>
class Matern32:
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specif... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Matern32:
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specified"""
... | the_stack_v2_python_sparse | gp_grief/kern/stationary.py | scwolof/gp_grief | train | 2 | |
c641e64d4c9f91e85b7e8a0ceeaf350f8b219c50 | [
"config.setdefault('password', None)\nconfig.setdefault('private_key', None)\nconfig.setdefault('private_key_pass', None)\nconfig.setdefault('host_key', None)\nconfig.setdefault('dirs', ['.'])\nreturn config",
"config = cls.prepare_config(config)\nfiles_only: bool = config['files_only']\ndirs_only: bool = config[... | <|body_start_0|>
config.setdefault('password', None)
config.setdefault('private_key', None)
config.setdefault('private_key_pass', None)
config.setdefault('host_key', None)
config.setdefault('dirs', ['.'])
return config
<|end_body_0|>
<|body_start_1|>
config = cls... | Generate entries from SFTP. This plugin requires the pysftp Python module and its dependencies. Configuration: host: Host to connect to. port: Port the remote SSH server is listening on (default 22). username: Username to log in as. password: The password to use. Optional if a private key is provided. private_key: Path... | SftpList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SftpList:
"""Generate entries from SFTP. This plugin requires the pysftp Python module and its dependencies. Configuration: host: Host to connect to. port: Port the remote SSH server is listening on (default 22). username: Username to log in as. password: The password to use. Optional if a privat... | stack_v2_sparse_classes_36k_train_028458 | 15,674 | permissive | [
{
"docstring": "Sets defaults for the provided configuration",
"name": "prepare_config",
"signature": "def prepare_config(config: dict) -> dict"
},
{
"docstring": "Input task handler",
"name": "on_task_input",
"signature": "def on_task_input(cls, task: Task, config: dict) -> List[Entry]"... | 2 | stack_v2_sparse_classes_30k_train_019470 | Implement the Python class `SftpList` described below.
Class description:
Generate entries from SFTP. This plugin requires the pysftp Python module and its dependencies. Configuration: host: Host to connect to. port: Port the remote SSH server is listening on (default 22). username: Username to log in as. password: Th... | Implement the Python class `SftpList` described below.
Class description:
Generate entries from SFTP. This plugin requires the pysftp Python module and its dependencies. Configuration: host: Host to connect to. port: Port the remote SSH server is listening on (default 22). username: Username to log in as. password: Th... | 2b7e8314d103c94cf4552bd0152699eeca0ad159 | <|skeleton|>
class SftpList:
"""Generate entries from SFTP. This plugin requires the pysftp Python module and its dependencies. Configuration: host: Host to connect to. port: Port the remote SSH server is listening on (default 22). username: Username to log in as. password: The password to use. Optional if a privat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SftpList:
"""Generate entries from SFTP. This plugin requires the pysftp Python module and its dependencies. Configuration: host: Host to connect to. port: Port the remote SSH server is listening on (default 22). username: Username to log in as. password: The password to use. Optional if a private key is prov... | the_stack_v2_python_sparse | flexget/components/ftp/sftp.py | BrutuZ/Flexget | train | 1 |
201496e5694d4607e3ddba735373ef19957571fc | [
"ents: Tuple[str, int, Tuple[int, int]] = []\ndoc: FeatureDocument\nfor six, (cls, doc) in enumerate(zip(classes, docs)):\n tok: FeatureToken\n start_ix = None\n start_lab = None\n ent: str\n for stix, (ent, tok) in enumerate(zip(cls, doc.tokens)):\n pos: int = ent.find('-')\n bio, lab ... | <|body_start_0|>
ents: Tuple[str, int, Tuple[int, int]] = []
doc: FeatureDocument
for six, (cls, doc) in enumerate(zip(classes, docs)):
tok: FeatureToken
start_ix = None
start_lab = None
ent: str
for stix, (ent, tok) in enumerate(zip(cl... | Matches feature documents/tokens with spaCy document/tokens and entity labels. | BioSequenceAnnotationMapper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BioSequenceAnnotationMapper:
"""Matches feature documents/tokens with spaCy document/tokens and entity labels."""
def _map_entities(self, classes: Tuple[List[str]], docs: Tuple[FeatureDocument]) -> Tuple[str, int, Tuple[int, int]]:
"""Map BIO entities and documents to a pairing of bo... | stack_v2_sparse_classes_36k_train_028459 | 7,916 | permissive | [
{
"docstring": "Map BIO entities and documents to a pairing of both. :param classes: the clases (labels, or usually, predictions) :param docs: the feature documents to assign labels :return: a tuple of label, sentence index and lexical feature document index interval of tokens",
"name": "_map_entities",
... | 3 | stack_v2_sparse_classes_30k_train_008825 | Implement the Python class `BioSequenceAnnotationMapper` described below.
Class description:
Matches feature documents/tokens with spaCy document/tokens and entity labels.
Method signatures and docstrings:
- def _map_entities(self, classes: Tuple[List[str]], docs: Tuple[FeatureDocument]) -> Tuple[str, int, Tuple[int,... | Implement the Python class `BioSequenceAnnotationMapper` described below.
Class description:
Matches feature documents/tokens with spaCy document/tokens and entity labels.
Method signatures and docstrings:
- def _map_entities(self, classes: Tuple[List[str]], docs: Tuple[FeatureDocument]) -> Tuple[str, int, Tuple[int,... | d2735848199741e818a49efb5197eb4a716fd96f | <|skeleton|>
class BioSequenceAnnotationMapper:
"""Matches feature documents/tokens with spaCy document/tokens and entity labels."""
def _map_entities(self, classes: Tuple[List[str]], docs: Tuple[FeatureDocument]) -> Tuple[str, int, Tuple[int, int]]:
"""Map BIO entities and documents to a pairing of bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BioSequenceAnnotationMapper:
"""Matches feature documents/tokens with spaCy document/tokens and entity labels."""
def _map_entities(self, classes: Tuple[List[str]], docs: Tuple[FeatureDocument]) -> Tuple[str, int, Tuple[int, int]]:
"""Map BIO entities and documents to a pairing of both. :param cl... | the_stack_v2_python_sparse | src/python/zensols/deepnlp/model/sequence.py | plandes/deepnlp | train | 9 |
19d9f9b11a6aed5c2e6d70303378a9655551e521 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Interface exported by the server. | TrainingCoordinatorServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainingCoordinatorServicer:
"""Interface exported by the server."""
def Train(self, request, context):
"""Train a model"""
<|body_0|>
def GetStatus(self, request, context):
"""Get status of training job"""
<|body_1|>
def GetEvaluations(self, request... | stack_v2_sparse_classes_36k_train_028460 | 10,496 | no_license | [
{
"docstring": "Train a model",
"name": "Train",
"signature": "def Train(self, request, context)"
},
{
"docstring": "Get status of training job",
"name": "GetStatus",
"signature": "def GetStatus(self, request, context)"
},
{
"docstring": "Get evaluation metrics for the training j... | 6 | stack_v2_sparse_classes_30k_train_020589 | Implement the Python class `TrainingCoordinatorServicer` described below.
Class description:
Interface exported by the server.
Method signatures and docstrings:
- def Train(self, request, context): Train a model
- def GetStatus(self, request, context): Get status of training job
- def GetEvaluations(self, request, co... | Implement the Python class `TrainingCoordinatorServicer` described below.
Class description:
Interface exported by the server.
Method signatures and docstrings:
- def Train(self, request, context): Train a model
- def GetStatus(self, request, context): Get status of training job
- def GetEvaluations(self, request, co... | 49dc92036e71ca758cc35e8851a803b89d76ef52 | <|skeleton|>
class TrainingCoordinatorServicer:
"""Interface exported by the server."""
def Train(self, request, context):
"""Train a model"""
<|body_0|>
def GetStatus(self, request, context):
"""Get status of training job"""
<|body_1|>
def GetEvaluations(self, request... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrainingCoordinatorServicer:
"""Interface exported by the server."""
def Train(self, request, context):
"""Train a model"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
... | the_stack_v2_python_sparse | proto/trainer/trainer_pb2_grpc.py | selwynClarifai/video-manager | train | 2 |
2949e51fec5fd32e3ab9a9417dccb84f67bb43da | [
"super(mpich, self).__init__(**kwargs)\nself.__baseurl = kwargs.pop('baseurl', 'https://www.mpich.org/static/downloads')\nself.__check = kwargs.pop('check', False)\nself.__configure_opts = kwargs.pop('configure_opts', [])\nself.__ospackages = kwargs.pop('ospackages', [])\nself.__prefix = kwargs.pop('prefix', '/usr/... | <|body_start_0|>
super(mpich, self).__init__(**kwargs)
self.__baseurl = kwargs.pop('baseurl', 'https://www.mpich.org/static/downloads')
self.__check = kwargs.pop('check', False)
self.__configure_opts = kwargs.pop('configure_opts', [])
self.__ospackages = kwargs.pop('ospackages', ... | The `mpich` building block configures, builds, and installs the [MPICH](https://www.mpich.org) component. As a side effect, a toolchain is created containing the MPI compiler wrappers. The tool can be passed to other operations that want to build using the MPI compiler wrappers. # Parameters annotate: Boolean flag to s... | mpich | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class mpich:
"""The `mpich` building block configures, builds, and installs the [MPICH](https://www.mpich.org) component. As a side effect, a toolchain is created containing the MPI compiler wrappers. The tool can be passed to other operations that want to build using the MPI compiler wrappers. # Param... | stack_v2_sparse_classes_36k_train_028461 | 8,511 | permissive | [
{
"docstring": "Initialize building block",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Setup configure options based on user parameters",
"name": "__configure",
"signature": "def __configure(self)"
},
{
"docstring": "Based on the Linux dist... | 4 | stack_v2_sparse_classes_30k_train_014878 | Implement the Python class `mpich` described below.
Class description:
The `mpich` building block configures, builds, and installs the [MPICH](https://www.mpich.org) component. As a side effect, a toolchain is created containing the MPI compiler wrappers. The tool can be passed to other operations that want to build u... | Implement the Python class `mpich` described below.
Class description:
The `mpich` building block configures, builds, and installs the [MPICH](https://www.mpich.org) component. As a side effect, a toolchain is created containing the MPI compiler wrappers. The tool can be passed to other operations that want to build u... | 60fd2a51c171258a6b3f93c2523101cb7018ba1b | <|skeleton|>
class mpich:
"""The `mpich` building block configures, builds, and installs the [MPICH](https://www.mpich.org) component. As a side effect, a toolchain is created containing the MPI compiler wrappers. The tool can be passed to other operations that want to build using the MPI compiler wrappers. # Param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class mpich:
"""The `mpich` building block configures, builds, and installs the [MPICH](https://www.mpich.org) component. As a side effect, a toolchain is created containing the MPI compiler wrappers. The tool can be passed to other operations that want to build using the MPI compiler wrappers. # Parameters annotat... | the_stack_v2_python_sparse | hpccm/building_blocks/mpich.py | NVIDIA/hpc-container-maker | train | 419 |
aef530f2e9879c8e8228768f445778d78e6aa473 | [
"c = [core.Commit('f123', 'desc', nomination_type=core.NominationType.FIXES, because_sha='abcd'), core.Commit('abcd', 'desc', True)]\nawait core.resolve_fixes(c, [])\nassert c[1].nominated",
"c = [core.Commit('f123', 'desc', nomination_type=core.NominationType.FIXES, because_sha='abcd'), core.Commit('abcd', 'desc... | <|body_start_0|>
c = [core.Commit('f123', 'desc', nomination_type=core.NominationType.FIXES, because_sha='abcd'), core.Commit('abcd', 'desc', True)]
await core.resolve_fixes(c, [])
assert c[1].nominated
<|end_body_0|>
<|body_start_1|>
c = [core.Commit('f123', 'desc', nomination_type=cor... | TestResolveFixes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestResolveFixes:
async def test_in_new(self):
"""Because commit abcd is nominated, so f123 should be as well."""
<|body_0|>
async def test_not_in_new(self):
"""Because commit abcd is not nominated, commit f123 shouldn't be either."""
<|body_1|>
async de... | stack_v2_sparse_classes_36k_train_028462 | 18,255 | no_license | [
{
"docstring": "Because commit abcd is nominated, so f123 should be as well.",
"name": "test_in_new",
"signature": "async def test_in_new(self)"
},
{
"docstring": "Because commit abcd is not nominated, commit f123 shouldn't be either.",
"name": "test_not_in_new",
"signature": "async def ... | 4 | stack_v2_sparse_classes_30k_train_015723 | Implement the Python class `TestResolveFixes` described below.
Class description:
Implement the TestResolveFixes class.
Method signatures and docstrings:
- async def test_in_new(self): Because commit abcd is nominated, so f123 should be as well.
- async def test_not_in_new(self): Because commit abcd is not nominated,... | Implement the Python class `TestResolveFixes` described below.
Class description:
Implement the TestResolveFixes class.
Method signatures and docstrings:
- async def test_in_new(self): Because commit abcd is nominated, so f123 should be as well.
- async def test_not_in_new(self): Because commit abcd is not nominated,... | b10df64ea1ff051768f367e321b4a3368de89397 | <|skeleton|>
class TestResolveFixes:
async def test_in_new(self):
"""Because commit abcd is nominated, so f123 should be as well."""
<|body_0|>
async def test_not_in_new(self):
"""Because commit abcd is not nominated, commit f123 shouldn't be either."""
<|body_1|>
async de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestResolveFixes:
async def test_in_new(self):
"""Because commit abcd is nominated, so f123 should be as well."""
c = [core.Commit('f123', 'desc', nomination_type=core.NominationType.FIXES, because_sha='abcd'), core.Commit('abcd', 'desc', True)]
await core.resolve_fixes(c, [])
... | the_stack_v2_python_sparse | bin/pick/core_test.py | maurossi/mesa | train | 20 | |
e26f900b6dd9620dd2dd3d2cdd4d2e612dcf66fa | [
"m = len(grid)\nn = len(grid[0]) if m else 0\nif n == 0:\n return []\ni, j = (0, n)\nmaxCnt, res = (0, [])\nwhile i < m:\n if 0 <= j < n and grid[i][j] == 0:\n i += 1\n continue\n while j - 1 >= 0 and grid[i][j - 1] == 1:\n j -= 1\n if n - j != 0 and n - j == maxCnt:\n res.ap... | <|body_start_0|>
m = len(grid)
n = len(grid[0]) if m else 0
if n == 0:
return []
i, j = (0, n)
maxCnt, res = (0, [])
while i < m:
if 0 <= j < n and grid[i][j] == 0:
i += 1
continue
while j - 1 >= 0 and gr... | Solutions | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solutions:
def problem1(self, grid):
"""include most 1, start from top-right, when meet 1, go left, when meet 0, go down Time complexity: O(m + n) # m: rows, n: cols Space complexity: O(1) # not create space param: grid: list[list[int]] rtype: list[int]"""
<|body_0|>
def pro... | stack_v2_sparse_classes_36k_train_028463 | 4,073 | no_license | [
{
"docstring": "include most 1, start from top-right, when meet 1, go left, when meet 0, go down Time complexity: O(m + n) # m: rows, n: cols Space complexity: O(1) # not create space param: grid: list[list[int]] rtype: list[int]",
"name": "problem1",
"signature": "def problem1(self, grid)"
},
{
... | 4 | null | Implement the Python class `Solutions` described below.
Class description:
Implement the Solutions class.
Method signatures and docstrings:
- def problem1(self, grid): include most 1, start from top-right, when meet 1, go left, when meet 0, go down Time complexity: O(m + n) # m: rows, n: cols Space complexity: O(1) #... | Implement the Python class `Solutions` described below.
Class description:
Implement the Solutions class.
Method signatures and docstrings:
- def problem1(self, grid): include most 1, start from top-right, when meet 1, go left, when meet 0, go down Time complexity: O(m + n) # m: rows, n: cols Space complexity: O(1) #... | e16702d2b3ec4e5054baad56f4320bc3b31676ad | <|skeleton|>
class Solutions:
def problem1(self, grid):
"""include most 1, start from top-right, when meet 1, go left, when meet 0, go down Time complexity: O(m + n) # m: rows, n: cols Space complexity: O(1) # not create space param: grid: list[list[int]] rtype: list[int]"""
<|body_0|>
def pro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solutions:
def problem1(self, grid):
"""include most 1, start from top-right, when meet 1, go left, when meet 0, go down Time complexity: O(m + n) # m: rows, n: cols Space complexity: O(1) # not create space param: grid: list[list[int]] rtype: list[int]"""
m = len(grid)
n = len(grid[0]... | the_stack_v2_python_sparse | interview_exam/pinduoduo/problems.py | SuperMartinYang/learning_algorithm | train | 0 | |
da93e0746aaedfb7d36cd653f0e250c0b86fe8cd | [
"Instrument.__init__(self, cle)\nself.emplacement = 'mains'\nself.positions = (1, 2)\nself.precision = 10\nself.calcul = 60\nself.etendre_editeur('r', 'précision', Uniligne, self, 'precision')\nself.etendre_editeur('ca', 'temps de calcul', Uniligne, self, 'calcul')",
"precision = enveloppes['r']\nprecision.apercu... | <|body_start_0|>
Instrument.__init__(self, cle)
self.emplacement = 'mains'
self.positions = (1, 2)
self.precision = 10
self.calcul = 60
self.etendre_editeur('r', 'précision', Uniligne, self, 'precision')
self.etendre_editeur('ca', 'temps de calcul', Uniligne, self... | Type d'objet: sextant. | Sextant | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sextant:
"""Type d'objet: sextant."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
<|body_0|>
def travailler_enveloppes(self, enveloppes):
"""Travail sur les enveloppes"""
<|body_1|>
def regarder(self, personnage):
"""Quand on re... | stack_v2_sparse_classes_36k_train_028464 | 3,821 | permissive | [
{
"docstring": "Constructeur de l'objet",
"name": "__init__",
"signature": "def __init__(self, cle='')"
},
{
"docstring": "Travail sur les enveloppes",
"name": "travailler_enveloppes",
"signature": "def travailler_enveloppes(self, enveloppes)"
},
{
"docstring": "Quand on regarde ... | 3 | stack_v2_sparse_classes_30k_test_000296 | Implement the Python class `Sextant` described below.
Class description:
Type d'objet: sextant.
Method signatures and docstrings:
- def __init__(self, cle=''): Constructeur de l'objet
- def travailler_enveloppes(self, enveloppes): Travail sur les enveloppes
- def regarder(self, personnage): Quand on regarde la sextan... | Implement the Python class `Sextant` described below.
Class description:
Type d'objet: sextant.
Method signatures and docstrings:
- def __init__(self, cle=''): Constructeur de l'objet
- def travailler_enveloppes(self, enveloppes): Travail sur les enveloppes
- def regarder(self, personnage): Quand on regarde la sextan... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class Sextant:
"""Type d'objet: sextant."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
<|body_0|>
def travailler_enveloppes(self, enveloppes):
"""Travail sur les enveloppes"""
<|body_1|>
def regarder(self, personnage):
"""Quand on re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sextant:
"""Type d'objet: sextant."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
Instrument.__init__(self, cle)
self.emplacement = 'mains'
self.positions = (1, 2)
self.precision = 10
self.calcul = 60
self.etendre_editeur('r', 'précisi... | the_stack_v2_python_sparse | src/secondaires/navigation/types/sextant.py | vincent-lg/tsunami | train | 5 |
be3ad784cd8c97e97ec274d958d39f6e8bdaea91 | [
"self.num_bits = num_bits\nself.num_hash_fn = num_hash_fn\nself.bits = [0] * num_bits\nself.primes = [3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47]\nself.hash_fns = []\nfor i in xrange(num_hash_fn):\n prime = random.choice(self.primes)\n self.primes.remove(prime)\n self.hash_fns.append(self.generate... | <|body_start_0|>
self.num_bits = num_bits
self.num_hash_fn = num_hash_fn
self.bits = [0] * num_bits
self.primes = [3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47]
self.hash_fns = []
for i in xrange(num_hash_fn):
prime = random.choice(self.primes)
... | Models a bloom filter data structure. A bloom filter holds an array of bytes and a small set of hash functions. Attributes: num_bits: int, the size of the memory the datastructure uses. num_hash_fn: int, how many hash function to use to store data. bits: list, the container for the stored data. primes: list, a list of ... | BloomFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BloomFilter:
"""Models a bloom filter data structure. A bloom filter holds an array of bytes and a small set of hash functions. Attributes: num_bits: int, the size of the memory the datastructure uses. num_hash_fn: int, how many hash function to use to store data. bits: list, the container for th... | stack_v2_sparse_classes_36k_train_028465 | 2,204 | permissive | [
{
"docstring": "Initialize a bloom filter by giving the size of the storage array. Params: num_bits: size of the internal array num_hash_fn: number of hash functions to generate to store data.",
"name": "__init__",
"signature": "def __init__(self, num_bits, num_hash_fn)"
},
{
"docstring": "Gener... | 4 | null | Implement the Python class `BloomFilter` described below.
Class description:
Models a bloom filter data structure. A bloom filter holds an array of bytes and a small set of hash functions. Attributes: num_bits: int, the size of the memory the datastructure uses. num_hash_fn: int, how many hash function to use to store... | Implement the Python class `BloomFilter` described below.
Class description:
Models a bloom filter data structure. A bloom filter holds an array of bytes and a small set of hash functions. Attributes: num_bits: int, the size of the memory the datastructure uses. num_hash_fn: int, how many hash function to use to store... | 1c5b1433c3d6bfd834df35dee08607fcbdd9f4e3 | <|skeleton|>
class BloomFilter:
"""Models a bloom filter data structure. A bloom filter holds an array of bytes and a small set of hash functions. Attributes: num_bits: int, the size of the memory the datastructure uses. num_hash_fn: int, how many hash function to use to store data. bits: list, the container for th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BloomFilter:
"""Models a bloom filter data structure. A bloom filter holds an array of bytes and a small set of hash functions. Attributes: num_bits: int, the size of the memory the datastructure uses. num_hash_fn: int, how many hash function to use to store data. bits: list, the container for the stored data... | the_stack_v2_python_sparse | python/algo/src/bloom_filter.py | topliceanu/learn | train | 26 |
1bb69a91efb77ee151f70f2ba35860b4a4cbaaea | [
"incl = ['a', 'b']\nexcl = ['b', 'c']\nfcn = da.lwc.search._get_dual_regex_indicator_fcn(incl, excl)\nassert fcn('a')\nassert not fcn('b')\nassert not fcn('c')\nassert not fcn('d')",
"incl = ['a', 'b']\nfcn = da.lwc.search._get_dual_regex_indicator_fcn(incl, excl=None)\nassert fcn('a')\nassert fcn('b')\nassert no... | <|body_start_0|>
incl = ['a', 'b']
excl = ['b', 'c']
fcn = da.lwc.search._get_dual_regex_indicator_fcn(incl, excl)
assert fcn('a')
assert not fcn('b')
assert not fcn('c')
assert not fcn('d')
<|end_body_0|>
<|body_start_1|>
incl = ['a', 'b']
fcn = ... | Specify the _get_dual_regex_indicator_fcn. | Specify_GetDualRegexIndicatorFcn | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Specify_GetDualRegexIndicatorFcn:
"""Specify the _get_dual_regex_indicator_fcn."""
def it_detects_items_in_include_list_but_not_those_in_exclude_list(self):
"""Test that items in include list return true unless in the exclude list."""
<|body_0|>
def it_nothing_is_exclude... | stack_v2_sparse_classes_36k_train_028466 | 29,518 | permissive | [
{
"docstring": "Test that items in include list return true unless in the exclude list.",
"name": "it_detects_items_in_include_list_but_not_those_in_exclude_list",
"signature": "def it_detects_items_in_include_list_but_not_those_in_exclude_list(self)"
},
{
"docstring": "Test that no include item... | 4 | null | Implement the Python class `Specify_GetDualRegexIndicatorFcn` described below.
Class description:
Specify the _get_dual_regex_indicator_fcn.
Method signatures and docstrings:
- def it_detects_items_in_include_list_but_not_those_in_exclude_list(self): Test that items in include list return true unless in the exclude l... | Implement the Python class `Specify_GetDualRegexIndicatorFcn` described below.
Class description:
Specify the _get_dual_regex_indicator_fcn.
Method signatures and docstrings:
- def it_detects_items_in_include_list_but_not_those_in_exclude_list(self): Test that items in include list return true unless in the exclude l... | 04a13be2792323e3f9fdb83fd236a8e9cfe6aa2d | <|skeleton|>
class Specify_GetDualRegexIndicatorFcn:
"""Specify the _get_dual_regex_indicator_fcn."""
def it_detects_items_in_include_list_but_not_those_in_exclude_list(self):
"""Test that items in include list return true unless in the exclude list."""
<|body_0|>
def it_nothing_is_exclude... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Specify_GetDualRegexIndicatorFcn:
"""Specify the _get_dual_regex_indicator_fcn."""
def it_detects_items_in_include_list_but_not_those_in_exclude_list(self):
"""Test that items in include list return true unless in the exclude list."""
incl = ['a', 'b']
excl = ['b', 'c']
fc... | the_stack_v2_python_sparse | a3_src/h70_internal/da/lwc/spec/spec_search.py | wtpayne/hiai | train | 5 |
567c1b7258acf3cdba3fbf1bb6a97be31e4b58e1 | [
"i = 1\nret = [0] * num_people\nwhile candies > i:\n ret[(i - 1) % num_people] += i\n candies -= i\n i += 1\nret[(i - 1) % num_people] += candies\nreturn ret",
"n = int(math.sqrt(2 * candies + 0.25) - 0.5)\nrows, cols = divmod(n, num_people)\nret = [0] * num_people\nfor i in range(num_people):\n ret[i... | <|body_start_0|>
i = 1
ret = [0] * num_people
while candies > i:
ret[(i - 1) % num_people] += i
candies -= i
i += 1
ret[(i - 1) % num_people] += candies
return ret
<|end_body_0|>
<|body_start_1|>
n = int(math.sqrt(2 * candies + 0.25) -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def distributeCandies_MK1(self, candies: int, num_people: int) -> List[int]:
"""BF."""
<|body_0|>
def distributeCandies_MK2(self, candies: int, num_people: int) -> List[int]:
"""Math."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i = 1
... | stack_v2_sparse_classes_36k_train_028467 | 896 | no_license | [
{
"docstring": "BF.",
"name": "distributeCandies_MK1",
"signature": "def distributeCandies_MK1(self, candies: int, num_people: int) -> List[int]"
},
{
"docstring": "Math.",
"name": "distributeCandies_MK2",
"signature": "def distributeCandies_MK2(self, candies: int, num_people: int) -> Li... | 2 | stack_v2_sparse_classes_30k_train_002656 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def distributeCandies_MK1(self, candies: int, num_people: int) -> List[int]: BF.
- def distributeCandies_MK2(self, candies: int, num_people: int) -> List[int]: Math. | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def distributeCandies_MK1(self, candies: int, num_people: int) -> List[int]: BF.
- def distributeCandies_MK2(self, candies: int, num_people: int) -> List[int]: Math.
<|skeleton|... | d7ba416d22becfa8f2a2ae4eee04c86617cd9332 | <|skeleton|>
class Solution:
def distributeCandies_MK1(self, candies: int, num_people: int) -> List[int]:
"""BF."""
<|body_0|>
def distributeCandies_MK2(self, candies: int, num_people: int) -> List[int]:
"""Math."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def distributeCandies_MK1(self, candies: int, num_people: int) -> List[int]:
"""BF."""
i = 1
ret = [0] * num_people
while candies > i:
ret[(i - 1) % num_people] += i
candies -= i
i += 1
ret[(i - 1) % num_people] += candies
... | the_stack_v2_python_sparse | 1103. Distribute Candies to People/Solution.py | faterazer/LeetCode | train | 4 | |
500e8ca776184cac5ece24ee08aa1b26a15bee2a | [
"points.sort()\nif len(points) < 4:\n return 0\nMAX = 10000\ndict_X = set()\nres = float('inf')\nfor i in range(len(points)):\n for j in range(len(points)):\n if points[i][0] == points[j][0] or points[i][1] == points[j][1]:\n continue\n if points[i][0] * MAX + points[j][1] in dict_X a... | <|body_start_0|>
points.sort()
if len(points) < 4:
return 0
MAX = 10000
dict_X = set()
res = float('inf')
for i in range(len(points)):
for j in range(len(points)):
if points[i][0] == points[j][0] or points[i][1] == points[j][1]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minAreaRect(self, points):
""":type points: List[List[int]] :rtype: int"""
<|body_0|>
def minAreaRect2(self, points):
""":type points: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
points.sort()
if... | stack_v2_sparse_classes_36k_train_028468 | 1,437 | no_license | [
{
"docstring": ":type points: List[List[int]] :rtype: int",
"name": "minAreaRect",
"signature": "def minAreaRect(self, points)"
},
{
"docstring": ":type points: List[List[int]] :rtype: int",
"name": "minAreaRect2",
"signature": "def minAreaRect2(self, points)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000946 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minAreaRect(self, points): :type points: List[List[int]] :rtype: int
- def minAreaRect2(self, points): :type points: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minAreaRect(self, points): :type points: List[List[int]] :rtype: int
- def minAreaRect2(self, points): :type points: List[List[int]] :rtype: int
<|skeleton|>
class Solution:... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def minAreaRect(self, points):
""":type points: List[List[int]] :rtype: int"""
<|body_0|>
def minAreaRect2(self, points):
""":type points: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minAreaRect(self, points):
""":type points: List[List[int]] :rtype: int"""
points.sort()
if len(points) < 4:
return 0
MAX = 10000
dict_X = set()
res = float('inf')
for i in range(len(points)):
for j in range(len(poin... | the_stack_v2_python_sparse | minAreaRect.py | NeilWangziyu/Leetcode_py | train | 2 | |
45a7a36584c056c15650a48c18cc037e73ebb62f | [
"driver.find_element_by_css_selector('.start-webinar').click()\nwindows = driver.window_handles\ndriver.switch_to.window(windows[1])\nsleep(2)\ndriver.find_element_by_link_text('发起直播').click()\ndriver.switch_to.window(windows[1])\nelement = WebDriverWait(driver, 20, 1).until(EC.presence_of_element_located((By.CSS_S... | <|body_start_0|>
driver.find_element_by_css_selector('.start-webinar').click()
windows = driver.window_handles
driver.switch_to.window(windows[1])
sleep(2)
driver.find_element_by_link_text('发起直播').click()
driver.switch_to.window(windows[1])
element = WebDriverWait... | Test_case_03_toolsAB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_case_03_toolsAB:
def test_03_startVideo(self):
"""开始直播"""
<|body_0|>
def test_04_questionnaire(self):
"""发起问卷"""
<|body_1|>
def test_05_signIn(self):
"""发起签到"""
<|body_2|>
def test_06_QandA(self):
"""开启问答"""
<|bo... | stack_v2_sparse_classes_36k_train_028469 | 3,477 | no_license | [
{
"docstring": "开始直播",
"name": "test_03_startVideo",
"signature": "def test_03_startVideo(self)"
},
{
"docstring": "发起问卷",
"name": "test_04_questionnaire",
"signature": "def test_04_questionnaire(self)"
},
{
"docstring": "发起签到",
"name": "test_05_signIn",
"signature": "def... | 6 | null | Implement the Python class `Test_case_03_toolsAB` described below.
Class description:
Implement the Test_case_03_toolsAB class.
Method signatures and docstrings:
- def test_03_startVideo(self): 开始直播
- def test_04_questionnaire(self): 发起问卷
- def test_05_signIn(self): 发起签到
- def test_06_QandA(self): 开启问答
- def test_07_... | Implement the Python class `Test_case_03_toolsAB` described below.
Class description:
Implement the Test_case_03_toolsAB class.
Method signatures and docstrings:
- def test_03_startVideo(self): 开始直播
- def test_04_questionnaire(self): 发起问卷
- def test_05_signIn(self): 发起签到
- def test_06_QandA(self): 开启问答
- def test_07_... | a47c6afe7734037695e397052cf189510e816f9e | <|skeleton|>
class Test_case_03_toolsAB:
def test_03_startVideo(self):
"""开始直播"""
<|body_0|>
def test_04_questionnaire(self):
"""发起问卷"""
<|body_1|>
def test_05_signIn(self):
"""发起签到"""
<|body_2|>
def test_06_QandA(self):
"""开启问答"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_case_03_toolsAB:
def test_03_startVideo(self):
"""开始直播"""
driver.find_element_by_css_selector('.start-webinar').click()
windows = driver.window_handles
driver.switch_to.window(windows[1])
sleep(2)
driver.find_element_by_link_text('发起直播').click()
dri... | the_stack_v2_python_sparse | Test_vhall/vhall_unittest/test_case/test_case_03_toolsAB.py | 1065865483/python_script | train | 0 | |
45c2183425132b43255f633e938adef96e1c3146 | [
"self.stop = stop\nself.route = route\nself.info = None",
"bridge = BizkaibusData(self.stop, self.route)\nbridge.getNextBus()\nself.info = bridge.info"
] | <|body_start_0|>
self.stop = stop
self.route = route
self.info = None
<|end_body_0|>
<|body_start_1|>
bridge = BizkaibusData(self.stop, self.route)
bridge.getNextBus()
self.info = bridge.info
<|end_body_1|>
| The class for handling the data retrieval. | Bizkaibus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bizkaibus:
"""The class for handling the data retrieval."""
def __init__(self, stop, route):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Retrieve the information from API."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
sel... | stack_v2_sparse_classes_36k_train_028470 | 2,206 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, stop, route)"
},
{
"docstring": "Retrieve the information from API.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010601 | Implement the Python class `Bizkaibus` described below.
Class description:
The class for handling the data retrieval.
Method signatures and docstrings:
- def __init__(self, stop, route): Initialize the data object.
- def update(self): Retrieve the information from API. | Implement the Python class `Bizkaibus` described below.
Class description:
The class for handling the data retrieval.
Method signatures and docstrings:
- def __init__(self, stop, route): Initialize the data object.
- def update(self): Retrieve the information from API.
<|skeleton|>
class Bizkaibus:
"""The class ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class Bizkaibus:
"""The class for handling the data retrieval."""
def __init__(self, stop, route):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Retrieve the information from API."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bizkaibus:
"""The class for handling the data retrieval."""
def __init__(self, stop, route):
"""Initialize the data object."""
self.stop = stop
self.route = route
self.info = None
def update(self):
"""Retrieve the information from API."""
bridge = Bizk... | the_stack_v2_python_sparse | homeassistant/components/bizkaibus/sensor.py | home-assistant/core | train | 35,501 |
7b0847d9aad677cc871f5d2b890469a2f52ae1c8 | [
"logger.debug('cleaned_data %s' % self.cleaned_data)\nif self.files:\n self.key_str = self.files['key_file'].read()\n if not self.key_str or not self.key_str.startswith('ssh-rsa '):\n raise forms.ValidationError('Provided file does not seem to contain a valid public SSH key. Please check and try again.... | <|body_start_0|>
logger.debug('cleaned_data %s' % self.cleaned_data)
if self.files:
self.key_str = self.files['key_file'].read()
if not self.key_str or not self.key_str.startswith('ssh-rsa '):
raise forms.ValidationError('Provided file does not seem to contain a v... | Form to upload a public SSH key. | UploadKeyForm | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadKeyForm:
"""Form to upload a public SSH key."""
def clean(self):
"""Perform minimal sanity check"""
<|body_0|>
def save(self, user):
"""Update the SSH keys @param user: the user to update SSH keys for. @type user: C{django.contrib.auth.models.User}"""
... | stack_v2_sparse_classes_36k_train_028471 | 6,630 | permissive | [
{
"docstring": "Perform minimal sanity check",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Update the SSH keys @param user: the user to update SSH keys for. @type user: C{django.contrib.auth.models.User}",
"name": "save",
"signature": "def save(self, user)"
}
] | 2 | null | Implement the Python class `UploadKeyForm` described below.
Class description:
Form to upload a public SSH key.
Method signatures and docstrings:
- def clean(self): Perform minimal sanity check
- def save(self, user): Update the SSH keys @param user: the user to update SSH keys for. @type user: C{django.contrib.auth.... | Implement the Python class `UploadKeyForm` described below.
Class description:
Form to upload a public SSH key.
Method signatures and docstrings:
- def clean(self): Perform minimal sanity check
- def save(self, user): Update the SSH keys @param user: the user to update SSH keys for. @type user: C{django.contrib.auth.... | 059ed2b3308bda2af5e1942dc9967e6573dd6a53 | <|skeleton|>
class UploadKeyForm:
"""Form to upload a public SSH key."""
def clean(self):
"""Perform minimal sanity check"""
<|body_0|>
def save(self, user):
"""Update the SSH keys @param user: the user to update SSH keys for. @type user: C{django.contrib.auth.models.User}"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UploadKeyForm:
"""Form to upload a public SSH key."""
def clean(self):
"""Perform minimal sanity check"""
logger.debug('cleaned_data %s' % self.cleaned_data)
if self.files:
self.key_str = self.files['key_file'].read()
if not self.key_str or not self.key_str... | the_stack_v2_python_sparse | expedient/src/python/expedient/clearinghouse/geni/forms.py | dana-i2cat/felix | train | 4 |
e449e7d1c34871c58ccdbb9e7564c4d0e664f25d | [
"if x == 0:\n return 0\nleft = 1\nright = x // 2\nwhile left < right:\n mid = left + right + 1 >> 1\n square = mid * mid\n if square > x:\n right = mid - 1\n else:\n left = mid\nreturn left",
"if x == 0:\n return 0\ncur = 1\nwhile True:\n pre = cur\n cur = (cur + x / cur) / 2... | <|body_start_0|>
if x == 0:
return 0
left = 1
right = x // 2
while left < right:
mid = left + right + 1 >> 1
square = mid * mid
if square > x:
right = mid - 1
else:
left = mid
return left
... | # 二分法 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""# 二分法"""
def mySqrt1(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def mySqrt(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if x == 0:
return 0
left = 1
right... | stack_v2_sparse_classes_36k_train_028472 | 1,468 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "mySqrt1",
"signature": "def mySqrt1(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "mySqrt",
"signature": "def mySqrt(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003475 | Implement the Python class `Solution` described below.
Class description:
# 二分法
Method signatures and docstrings:
- def mySqrt1(self, x): :type x: int :rtype: int
- def mySqrt(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
# 二分法
Method signatures and docstrings:
- def mySqrt1(self, x): :type x: int :rtype: int
- def mySqrt(self, x): :type x: int :rtype: int
<|skeleton|>
class Solution:
"""# 二分法"""
def mySqrt1(self, x):
""":type x: int :rtype: in... | f831fd9603592ae5bee3679924f962a3ebce381c | <|skeleton|>
class Solution:
"""# 二分法"""
def mySqrt1(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def mySqrt(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""# 二分法"""
def mySqrt1(self, x):
""":type x: int :rtype: int"""
if x == 0:
return 0
left = 1
right = x // 2
while left < right:
mid = left + right + 1 >> 1
square = mid * mid
if square > x:
... | the_stack_v2_python_sparse | old/t20190918_mySqrt/mySqrt.py | GongFuXiong/leetcode | train | 0 |
e7b91c67ce5a1b9010dab5622d105c843d05faec | [
"self.num = num\nself.proc = subprocess.Popen(['python', '-u', './DASP/system/initial.py', str(self.num)], shell=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\nself.printdata = printdata\nprint('[node{}]pid:{}'.format(num, self.proc.pid))\nself.thread = threading.Thread(target=self.getprintdata, args=(mode... | <|body_start_0|>
self.num = num
self.proc = subprocess.Popen(['python', '-u', './DASP/system/initial.py', str(self.num)], shell=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
self.printdata = printdata
print('[node{}]pid:{}'.format(num, self.proc.pid))
self.thread = threa... | 节点类 用于多进程开启任务节点 属性: num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据 proc: 节点进程 thread: 节点获取输出数据线程 | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
"""节点类 用于多进程开启任务节点 属性: num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据 proc: 节点进程 thread: 节点获取输出数据线程"""
def __init__(self, num, mode, printdata):
"""num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据"""
<|body_0|>
def getprintdata(self, mode=False):
""... | stack_v2_sparse_classes_36k_train_028473 | 2,119 | no_license | [
{
"docstring": "num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据",
"name": "__init__",
"signature": "def __init__(self, num, mode, printdata)"
},
{
"docstring": "获取输出数据",
"name": "getprintdata",
"signature": "def getprintdata(self, mode=False)"
},
{
"docstring": "杀死节点进程",
... | 3 | stack_v2_sparse_classes_30k_train_019344 | Implement the Python class `Node` described below.
Class description:
节点类 用于多进程开启任务节点 属性: num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据 proc: 节点进程 thread: 节点获取输出数据线程
Method signatures and docstrings:
- def __init__(self, num, mode, printdata): num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据
- def getprintda... | Implement the Python class `Node` described below.
Class description:
节点类 用于多进程开启任务节点 属性: num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据 proc: 节点进程 thread: 节点获取输出数据线程
Method signatures and docstrings:
- def __init__(self, num, mode, printdata): num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据
- def getprintda... | b6d056551d1323fd418f870b6340d8e9b906dc0f | <|skeleton|>
class Node:
"""节点类 用于多进程开启任务节点 属性: num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据 proc: 节点进程 thread: 节点获取输出数据线程"""
def __init__(self, num, mode, printdata):
"""num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据"""
<|body_0|>
def getprintdata(self, mode=False):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
"""节点类 用于多进程开启任务节点 属性: num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据 proc: 节点进程 thread: 节点获取输出数据线程"""
def __init__(self, num, mode, printdata):
"""num: 节点ID编号 从1开始 mode: 是否直接打印输出数据 printdata: 节点输出数据"""
self.num = num
self.proc = subprocess.Popen(['python', '-u', './DAS... | the_stack_v2_python_sparse | 树莓派节点/分布式平台/DSP3.0/DASP/module/DaspNode.py | Wales-Wyf/Mingze_Project | train | 1 |
49e2858afaf4c77f2c5c2c655e6a5efa9cf9eca0 | [
"self.name = name\nself.type = type\nself.required = required\nself.default = default\nself.ignore = ignore\nself.choices = choices\nself.nullable = nullable\nself.location = location\nself.discard = discard\nself.help = help",
"if self.location and hasattr(request, self.location):\n req_data = getattr(request... | <|body_start_0|>
self.name = name
self.type = type
self.required = required
self.default = default
self.ignore = ignore
self.choices = choices
self.nullable = nullable
self.location = location
self.discard = discard
self.help = help
<|end_b... | Param | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Param:
def __init__(self, name, type=str, required=False, default=None, nullable=True, ignore=False, choices=None, location=None, discard=False, help=''):
"""请求参数对象 Args: name (str): 字段名 type (class): 类型 required (bool): 是否必填 default (any): 默认值 (必填时无效) nullable (bool): 是否非空 ignore (bool)... | stack_v2_sparse_classes_36k_train_028474 | 3,546 | no_license | [
{
"docstring": "请求参数对象 Args: name (str): 字段名 type (class): 类型 required (bool): 是否必填 default (any): 默认值 (必填时无效) nullable (bool): 是否非空 ignore (bool): 是否忽略类型 choices (tuple): 可选值 location (str): 访问数据源 args, json, form 默认 GET: args, POST: json discard (bool): 不存在 key, 是否不解析参数 help (str): 参数不匹配时, 返回提示",
"name": ... | 2 | stack_v2_sparse_classes_30k_train_012240 | Implement the Python class `Param` described below.
Class description:
Implement the Param class.
Method signatures and docstrings:
- def __init__(self, name, type=str, required=False, default=None, nullable=True, ignore=False, choices=None, location=None, discard=False, help=''): 请求参数对象 Args: name (str): 字段名 type (c... | Implement the Python class `Param` described below.
Class description:
Implement the Param class.
Method signatures and docstrings:
- def __init__(self, name, type=str, required=False, default=None, nullable=True, ignore=False, choices=None, location=None, discard=False, help=''): 请求参数对象 Args: name (str): 字段名 type (c... | 7877724c7875fad0297f7801910f162d80c5d695 | <|skeleton|>
class Param:
def __init__(self, name, type=str, required=False, default=None, nullable=True, ignore=False, choices=None, location=None, discard=False, help=''):
"""请求参数对象 Args: name (str): 字段名 type (class): 类型 required (bool): 是否必填 default (any): 默认值 (必填时无效) nullable (bool): 是否非空 ignore (bool)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Param:
def __init__(self, name, type=str, required=False, default=None, nullable=True, ignore=False, choices=None, location=None, discard=False, help=''):
"""请求参数对象 Args: name (str): 字段名 type (class): 类型 required (bool): 是否必填 default (any): 默认值 (必填时无效) nullable (bool): 是否非空 ignore (bool): 是否忽略类型 choic... | the_stack_v2_python_sparse | base/params.py | HeyManLean/RedisApp | train | 0 | |
67448b3f2fbd09bb0e9fa61935aead5048c3879d | [
"response = self.client.get(reverse('index_rango'))\nself.assertEqual(response.status_code, 200)\nself.assertContains(response, 'There are no categories present.')\nself.assertQuerysetEqual(response.context['categories'], [])",
"add_cat('test', 1, 1)\nadd_cat('temp', 1, 1)\nadd_cat('tmp', 1, 1)\nadd_cat('tmp test... | <|body_start_0|>
response = self.client.get(reverse('index_rango'))
self.assertEqual(response.status_code, 200)
self.assertContains(response, 'There are no categories present.')
self.assertQuerysetEqual(response.context['categories'], [])
<|end_body_0|>
<|body_start_1|>
add_cat(... | IndexViewTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexViewTests:
def test_index_view_with_no_categories(self):
"""Если не существует категорий, то должно выводиться соответствующее сообщение."""
<|body_0|>
def test_index_view_with_categories(self):
"""Если не существует категорий, то должно выводиться соответствующ... | stack_v2_sparse_classes_36k_train_028475 | 2,626 | no_license | [
{
"docstring": "Если не существует категорий, то должно выводиться соответствующее сообщение.",
"name": "test_index_view_with_no_categories",
"signature": "def test_index_view_with_no_categories(self)"
},
{
"docstring": "Если не существует категорий, то должно выводиться соответствующее сообщени... | 2 | stack_v2_sparse_classes_30k_train_012916 | Implement the Python class `IndexViewTests` described below.
Class description:
Implement the IndexViewTests class.
Method signatures and docstrings:
- def test_index_view_with_no_categories(self): Если не существует категорий, то должно выводиться соответствующее сообщение.
- def test_index_view_with_categories(self... | Implement the Python class `IndexViewTests` described below.
Class description:
Implement the IndexViewTests class.
Method signatures and docstrings:
- def test_index_view_with_no_categories(self): Если не существует категорий, то должно выводиться соответствующее сообщение.
- def test_index_view_with_categories(self... | 80f1a6bcbe2e0448b844e1352ebd1ae3c5f5e858 | <|skeleton|>
class IndexViewTests:
def test_index_view_with_no_categories(self):
"""Если не существует категорий, то должно выводиться соответствующее сообщение."""
<|body_0|>
def test_index_view_with_categories(self):
"""Если не существует категорий, то должно выводиться соответствующ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IndexViewTests:
def test_index_view_with_no_categories(self):
"""Если не существует категорий, то должно выводиться соответствующее сообщение."""
response = self.client.get(reverse('index_rango'))
self.assertEqual(response.status_code, 200)
self.assertContains(response, 'There ... | the_stack_v2_python_sparse | rango/tests.py | blazer-05/tangotest | train | 1 | |
987c5813c7ee342ddd161b86fecf1fbb2183a3e6 | [
"kwargs['pid_value'] = record['id']\nkwargs['status'] = cls.default_status\nkwargs['object_type'] = cls.object_type\nkwargs['object_uuid'] = record.model.id\nreturn super(CommunitiesIdProvider, cls).create(**kwargs)",
"try:\n existing_pid = cls.get(new_value).pid\nexcept PIDDoesNotExistError:\n pass\nelse:\... | <|body_start_0|>
kwargs['pid_value'] = record['id']
kwargs['status'] = cls.default_status
kwargs['object_type'] = cls.object_type
kwargs['object_uuid'] = record.model.id
return super(CommunitiesIdProvider, cls).create(**kwargs)
<|end_body_0|>
<|body_start_1|>
try:
... | Community identifier provider. This is the recommended community id provider. It uses the value of the 'id' present in our data to generate the identifier. | CommunitiesIdProvider | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommunitiesIdProvider:
"""Community identifier provider. This is the recommended community id provider. It uses the value of the 'id' present in our data to generate the identifier."""
def create(cls, record, **kwargs):
"""Create a new commuinity identifier. For more information abou... | stack_v2_sparse_classes_36k_train_028476 | 2,431 | permissive | [
{
"docstring": "Create a new commuinity identifier. For more information about parameters, see :meth:`invenio_pidstore.providers.base.BaseProvider.create`. :param record: The community record. :param kwargs: dict to hold generated pid_value and status. See :meth:`invenio_pidstore.providers.base.BaseProvider.cre... | 2 | stack_v2_sparse_classes_30k_train_003997 | Implement the Python class `CommunitiesIdProvider` described below.
Class description:
Community identifier provider. This is the recommended community id provider. It uses the value of the 'id' present in our data to generate the identifier.
Method signatures and docstrings:
- def create(cls, record, **kwargs): Crea... | Implement the Python class `CommunitiesIdProvider` described below.
Class description:
Community identifier provider. This is the recommended community id provider. It uses the value of the 'id' present in our data to generate the identifier.
Method signatures and docstrings:
- def create(cls, record, **kwargs): Crea... | e6e032960abd5d4062a63824d6d349a6158339af | <|skeleton|>
class CommunitiesIdProvider:
"""Community identifier provider. This is the recommended community id provider. It uses the value of the 'id' present in our data to generate the identifier."""
def create(cls, record, **kwargs):
"""Create a new commuinity identifier. For more information abou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommunitiesIdProvider:
"""Community identifier provider. This is the recommended community id provider. It uses the value of the 'id' present in our data to generate the identifier."""
def create(cls, record, **kwargs):
"""Create a new commuinity identifier. For more information about parameters,... | the_stack_v2_python_sparse | invenio_communities/communities/records/providers.py | lnielsen/invenio-communities | train | 0 |
3415448113694a52f93b776484738952f2803d20 | [
"if len(nums) == 1 or nums is None:\n return\nif k >= len(nums):\n k = k - len(nums)\nif k < len(nums) / 2:\n sub = nums[-k:]\n print(sub)\n for i in range(len(nums) - 1, k - 1, -1):\n nums[i] = nums[i - k]\n for i in range(k):\n nums[i] = sub[i]\nelse:\n k = len(nums) - k\n su... | <|body_start_0|>
if len(nums) == 1 or nums is None:
return
if k >= len(nums):
k = k - len(nums)
if k < len(nums) / 2:
sub = nums[-k:]
print(sub)
for i in range(len(nums) - 1, k - 1, -1):
nums[i] = nums[i - k]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, nums, k) -> None:
"""Do not return anything, modify nums in-place instead. 方案：向右移动k等于把末尾k个元素放到开头"""
<|body_0|>
def rotate_(self, nums, k) -> None:
"""三步翻转法：但是不是原地算法需要返回值"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if l... | stack_v2_sparse_classes_36k_train_028477 | 2,096 | no_license | [
{
"docstring": "Do not return anything, modify nums in-place instead. 方案：向右移动k等于把末尾k个元素放到开头",
"name": "rotate",
"signature": "def rotate(self, nums, k) -> None"
},
{
"docstring": "三步翻转法：但是不是原地算法需要返回值",
"name": "rotate_",
"signature": "def rotate_(self, nums, k) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_val_000614 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums, k) -> None: Do not return anything, modify nums in-place instead. 方案：向右移动k等于把末尾k个元素放到开头
- def rotate_(self, nums, k) -> None: 三步翻转法：但是不是原地算法需要返回值 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, nums, k) -> None: Do not return anything, modify nums in-place instead. 方案：向右移动k等于把末尾k个元素放到开头
- def rotate_(self, nums, k) -> None: 三步翻转法：但是不是原地算法需要返回值
<|skelet... | 2e81b871bf1db7ea7432d1ebf889c72066e64753 | <|skeleton|>
class Solution:
def rotate(self, nums, k) -> None:
"""Do not return anything, modify nums in-place instead. 方案：向右移动k等于把末尾k个元素放到开头"""
<|body_0|>
def rotate_(self, nums, k) -> None:
"""三步翻转法：但是不是原地算法需要返回值"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, nums, k) -> None:
"""Do not return anything, modify nums in-place instead. 方案：向右移动k等于把末尾k个元素放到开头"""
if len(nums) == 1 or nums is None:
return
if k >= len(nums):
k = k - len(nums)
if k < len(nums) / 2:
sub = nums[-k:... | the_stack_v2_python_sparse | array/rotateArray.py | NextNight/LeetCodeAndStructAndAlgorithm | train | 0 | |
5f3e797d27a35f3f3047f3069842179bf35eebc9 | [
"self.model_name = model_name\nself.ckpt_path = ckpt_path\nself.params = hparams_config.get_detection_config(model_name).as_dict()\nif model_params:\n self.params.update(model_params)\nself.params.update(dict(is_training_bn=False))\nself.label_map = self.params.get('label_map', None)",
"params = copy.deepcopy(... | <|body_start_0|>
self.model_name = model_name
self.ckpt_path = ckpt_path
self.params = hparams_config.get_detection_config(model_name).as_dict()
if model_params:
self.params.update(model_params)
self.params.update(dict(is_training_bn=False))
self.label_map = s... | A driver for doing batch inference. Example usage: driver = inference.InferenceDriver('efficientdet-d0', '/tmp/efficientdet-d0') driver.inference('/tmp/*.jpg', '/tmp/outputdir') | InferenceDriver | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InferenceDriver:
"""A driver for doing batch inference. Example usage: driver = inference.InferenceDriver('efficientdet-d0', '/tmp/efficientdet-d0') driver.inference('/tmp/*.jpg', '/tmp/outputdir')"""
def __init__(self, model_name: Text, ckpt_path: Text, model_params: Dict[Text, Any]=None):
... | stack_v2_sparse_classes_36k_train_028478 | 26,168 | permissive | [
{
"docstring": "Initialize the inference driver. Args: model_name: target model name, such as efficientdet-d0. ckpt_path: checkpoint path, such as /tmp/efficientdet-d0/. model_params: model parameters for overriding the config.",
"name": "__init__",
"signature": "def __init__(self, model_name: Text, ckp... | 2 | stack_v2_sparse_classes_30k_val_000636 | Implement the Python class `InferenceDriver` described below.
Class description:
A driver for doing batch inference. Example usage: driver = inference.InferenceDriver('efficientdet-d0', '/tmp/efficientdet-d0') driver.inference('/tmp/*.jpg', '/tmp/outputdir')
Method signatures and docstrings:
- def __init__(self, mode... | Implement the Python class `InferenceDriver` described below.
Class description:
A driver for doing batch inference. Example usage: driver = inference.InferenceDriver('efficientdet-d0', '/tmp/efficientdet-d0') driver.inference('/tmp/*.jpg', '/tmp/outputdir')
Method signatures and docstrings:
- def __init__(self, mode... | c7392f2bab3165244d1c565b66409fa11fa82367 | <|skeleton|>
class InferenceDriver:
"""A driver for doing batch inference. Example usage: driver = inference.InferenceDriver('efficientdet-d0', '/tmp/efficientdet-d0') driver.inference('/tmp/*.jpg', '/tmp/outputdir')"""
def __init__(self, model_name: Text, ckpt_path: Text, model_params: Dict[Text, Any]=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InferenceDriver:
"""A driver for doing batch inference. Example usage: driver = inference.InferenceDriver('efficientdet-d0', '/tmp/efficientdet-d0') driver.inference('/tmp/*.jpg', '/tmp/outputdir')"""
def __init__(self, model_name: Text, ckpt_path: Text, model_params: Dict[Text, Any]=None):
"""In... | the_stack_v2_python_sparse | efficientdet/inference.py | google/automl | train | 6,415 |
10f4e30ee07d0a9a9a3741e18f3ea963d89d1122 | [
"wall_placed_locs = []\nif right:\n locations = [[starting_location[0] + i, starting_location[1]] for i in range(length)]\n for loc in locations:\n if game_state.can_spawn(unit_enum_map['WALL'], loc):\n succ = game_state.attempt_spawn(unit_enum_map['WALL'], loc)\n if succ == 1:\n ... | <|body_start_0|>
wall_placed_locs = []
if right:
locations = [[starting_location[0] + i, starting_location[1]] for i in range(length)]
for loc in locations:
if game_state.can_spawn(unit_enum_map['WALL'], loc):
succ = game_state.attempt_spawn(un... | Contains builder/simulator for a line of horizontal walls | DefensiveWallStrat | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefensiveWallStrat:
"""Contains builder/simulator for a line of horizontal walls"""
def build_h_wall_line(self, game_state: GameState, unit_enum_map: dict, starting_location: (int, int) or [[int]], length: int, right: bool=True) -> [[int]]:
"""Used for placing a horizontal line of wa... | stack_v2_sparse_classes_36k_train_028479 | 6,790 | no_license | [
{
"docstring": "Used for placing a horizontal line of walls @param game_state: GameState object containing current gamestate info unit_enum_map (dict): Maps NAME to unit enum @param starting_location: (x, y) or [[x, y]] @param length: duh @param right: whether the wall goes right or left of the starting locatio... | 2 | stack_v2_sparse_classes_30k_train_009315 | Implement the Python class `DefensiveWallStrat` described below.
Class description:
Contains builder/simulator for a line of horizontal walls
Method signatures and docstrings:
- def build_h_wall_line(self, game_state: GameState, unit_enum_map: dict, starting_location: (int, int) or [[int]], length: int, right: bool=T... | Implement the Python class `DefensiveWallStrat` described below.
Class description:
Contains builder/simulator for a line of horizontal walls
Method signatures and docstrings:
- def build_h_wall_line(self, game_state: GameState, unit_enum_map: dict, starting_location: (int, int) or [[int]], length: int, right: bool=T... | e9439191d44f644c55752abadda6882eeb75671f | <|skeleton|>
class DefensiveWallStrat:
"""Contains builder/simulator for a line of horizontal walls"""
def build_h_wall_line(self, game_state: GameState, unit_enum_map: dict, starting_location: (int, int) or [[int]], length: int, right: bool=True) -> [[int]]:
"""Used for placing a horizontal line of wa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DefensiveWallStrat:
"""Contains builder/simulator for a line of horizontal walls"""
def build_h_wall_line(self, game_state: GameState, unit_enum_map: dict, starting_location: (int, int) or [[int]], length: int, right: bool=True) -> [[int]]:
"""Used for placing a horizontal line of walls @param ga... | the_stack_v2_python_sparse | algos/bruh_moment/defensive_building_functions.py | echudov/terminal | train | 0 |
3fb888b4254b0087c5b8a3ef0656a9349a554e9b | [
"if data is None:\n data = {}\ndata['reference_id'] = reference_id\nurl = f'{self.session.root_url}/study/api/study/'\nreturn self.session.post(url, data).json()",
"url = f'{self.session.root_url}/study/api/study/?assessment_id={assessment_id}'\nresponse_json = self.session.get(url).json()\nreturn pd.DataFrame... | <|body_start_0|>
if data is None:
data = {}
data['reference_id'] = reference_id
url = f'{self.session.root_url}/study/api/study/'
return self.session.post(url, data).json()
<|end_body_0|>
<|body_start_1|>
url = f'{self.session.root_url}/study/api/study/?assessment_id... | Client class for study requests. | StudyClient | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StudyClient:
"""Client class for study requests."""
def create(self, reference_id: int, data: dict | None=None) -> dict:
"""Creates a study using a given reference ID. Args: reference_id (int): Reference ID to create study from. data (dict, optional): Dict containing any additional f... | stack_v2_sparse_classes_36k_train_028480 | 3,384 | permissive | [
{
"docstring": "Creates a study using a given reference ID. Args: reference_id (int): Reference ID to create study from. data (dict, optional): Dict containing any additional field/value pairings for the study. Possible pairings are: short_citation (str): Short study citation, can be used as identifier. full_ci... | 3 | stack_v2_sparse_classes_30k_train_000850 | Implement the Python class `StudyClient` described below.
Class description:
Client class for study requests.
Method signatures and docstrings:
- def create(self, reference_id: int, data: dict | None=None) -> dict: Creates a study using a given reference ID. Args: reference_id (int): Reference ID to create study from... | Implement the Python class `StudyClient` described below.
Class description:
Client class for study requests.
Method signatures and docstrings:
- def create(self, reference_id: int, data: dict | None=None) -> dict: Creates a study using a given reference ID. Args: reference_id (int): Reference ID to create study from... | 51177c6fb9354cd028f7099fc10d83b1051fd50d | <|skeleton|>
class StudyClient:
"""Client class for study requests."""
def create(self, reference_id: int, data: dict | None=None) -> dict:
"""Creates a study using a given reference ID. Args: reference_id (int): Reference ID to create study from. data (dict, optional): Dict containing any additional f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StudyClient:
"""Client class for study requests."""
def create(self, reference_id: int, data: dict | None=None) -> dict:
"""Creates a study using a given reference ID. Args: reference_id (int): Reference ID to create study from. data (dict, optional): Dict containing any additional field/value pa... | the_stack_v2_python_sparse | client/hawc_client/study.py | shapiromatron/hawc | train | 25 |
fe16fb2b1ef95e286403584f8427bd9d371095b8 | [
"super(NFM, self).__init__()\nself.embedding_size = embedding_size\nself.feature_size = feature_size\nself.field_size = field_size\nself.emb_layer = nn.Embedding(num_embeddings=feature_size, embedding_dim=embedding_size)\nnn.init.xavier_uniform_(self.emb_layer.weight)\nself.bi_intaraction_layer = BiInteractionLayer... | <|body_start_0|>
super(NFM, self).__init__()
self.embedding_size = embedding_size
self.feature_size = feature_size
self.field_size = field_size
self.emb_layer = nn.Embedding(num_embeddings=feature_size, embedding_dim=embedding_size)
nn.init.xavier_uniform_(self.emb_layer.... | NFM Network | NFM | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NFM:
"""NFM Network"""
def __init__(self, feature_size, field_size, embedding_size=5, fc_dims=[32, 32], dropout=0.0, is_batch_norm=False, out_type='binary'):
"""Init model :param feature_size: int, size of the feature dictionary :param field_size: int, size of the feature fields :par... | stack_v2_sparse_classes_36k_train_028481 | 3,142 | permissive | [
{
"docstring": "Init model :param feature_size: int, size of the feature dictionary :param field_size: int, size of the feature fields :param embedding_size: int, size of the feature embedding :param fc_dims: range, sizes of fc dims :param dropout: float, dropout rate :param is_batch_norm: bool, use batch norma... | 2 | stack_v2_sparse_classes_30k_train_010769 | Implement the Python class `NFM` described below.
Class description:
NFM Network
Method signatures and docstrings:
- def __init__(self, feature_size, field_size, embedding_size=5, fc_dims=[32, 32], dropout=0.0, is_batch_norm=False, out_type='binary'): Init model :param feature_size: int, size of the feature dictionar... | Implement the Python class `NFM` described below.
Class description:
NFM Network
Method signatures and docstrings:
- def __init__(self, feature_size, field_size, embedding_size=5, fc_dims=[32, 32], dropout=0.0, is_batch_norm=False, out_type='binary'): Init model :param feature_size: int, size of the feature dictionar... | 8437dea8baf0137ab3c07dd19c5f2bb8c15b4435 | <|skeleton|>
class NFM:
"""NFM Network"""
def __init__(self, feature_size, field_size, embedding_size=5, fc_dims=[32, 32], dropout=0.0, is_batch_norm=False, out_type='binary'):
"""Init model :param feature_size: int, size of the feature dictionary :param field_size: int, size of the feature fields :par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NFM:
"""NFM Network"""
def __init__(self, feature_size, field_size, embedding_size=5, fc_dims=[32, 32], dropout=0.0, is_batch_norm=False, out_type='binary'):
"""Init model :param feature_size: int, size of the feature dictionary :param field_size: int, size of the feature fields :param embedding_... | the_stack_v2_python_sparse | rater/models/ctr/nfm.py | geziaka/rater | train | 0 |
28f89265d622d85c05a5957d6facab3c688aba38 | [
"self.inactive = inactive\nif method == 'random':\n self.sampler = RandomOverSampler()\nelif method == 'smote':\n self.sampler = SMOTE()\nelif method == 'adasyn':\n self.sampler = ADASYN()\nelse:\n raise TypeError(f\"The choice '{method}' for the argument 'method' is not available.\")",
"if self.inact... | <|body_start_0|>
self.inactive = inactive
if method == 'random':
self.sampler = RandomOverSampler()
elif method == 'smote':
self.sampler = SMOTE()
elif method == 'adasyn':
self.sampler = ADASYN()
else:
raise TypeError(f"The choice '... | Performs oversampling on imbalanced classes. Methods ------- __init__ fit_resample | OverSampler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OverSampler:
"""Performs oversampling on imbalanced classes. Methods ------- __init__ fit_resample"""
def __init__(self, method='random', inactive=False):
"""Initilization of OverSampler instances. Parameters ---------- method: str, default "random" Select on oversampling method inac... | stack_v2_sparse_classes_36k_train_028482 | 1,472 | no_license | [
{
"docstring": "Initilization of OverSampler instances. Parameters ---------- method: str, default \"random\" Select on oversampling method inactive bool, default False Bypass oversampling",
"name": "__init__",
"signature": "def __init__(self, method='random', inactive=False)"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_train_003090 | Implement the Python class `OverSampler` described below.
Class description:
Performs oversampling on imbalanced classes. Methods ------- __init__ fit_resample
Method signatures and docstrings:
- def __init__(self, method='random', inactive=False): Initilization of OverSampler instances. Parameters ---------- method:... | Implement the Python class `OverSampler` described below.
Class description:
Performs oversampling on imbalanced classes. Methods ------- __init__ fit_resample
Method signatures and docstrings:
- def __init__(self, method='random', inactive=False): Initilization of OverSampler instances. Parameters ---------- method:... | 227641cc02f5c3aef04f3c27cbfc316382041ae0 | <|skeleton|>
class OverSampler:
"""Performs oversampling on imbalanced classes. Methods ------- __init__ fit_resample"""
def __init__(self, method='random', inactive=False):
"""Initilization of OverSampler instances. Parameters ---------- method: str, default "random" Select on oversampling method inac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OverSampler:
"""Performs oversampling on imbalanced classes. Methods ------- __init__ fit_resample"""
def __init__(self, method='random', inactive=False):
"""Initilization of OverSampler instances. Parameters ---------- method: str, default "random" Select on oversampling method inactive bool, de... | the_stack_v2_python_sparse | yotta_p1/old-version/forecast/domain/over_sampling.py | j-bd/various_exs | train | 0 |
44ae87db978a052dd86ee549c48c28b84f95ed0c | [
"unique = {}\nfor item in items:\n arr = unique.get(item['name'], [])\n arr.append(item)\n unique[item['name']] = arr\nstrings = []\nfor name, arr in unique.items():\n if len(arr) == 1:\n strings.append(name)\n else:\n strings.append(f'{ItemFormatter.DEDUP_MARKER}{name}')\nreturn '\\n'.... | <|body_start_0|>
unique = {}
for item in items:
arr = unique.get(item['name'], [])
arr.append(item)
unique[item['name']] = arr
strings = []
for name, arr in unique.items():
if len(arr) == 1:
strings.append(name)
... | Formatter converting bw item lists to lists of strings for Rofi | ItemFormatter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemFormatter:
"""Formatter converting bw item lists to lists of strings for Rofi"""
def unique_format(items):
"""Return a list of items names, and group duplicates items by name"""
<|body_0|>
def group_format(items, converter):
"""Return a list of numbered items... | stack_v2_sparse_classes_36k_train_028483 | 2,460 | permissive | [
{
"docstring": "Return a list of items names, and group duplicates items by name",
"name": "unique_format",
"signature": "def unique_format(items)"
},
{
"docstring": "Return a list of numbered items transformed by a converter",
"name": "group_format",
"signature": "def group_format(items... | 2 | stack_v2_sparse_classes_30k_val_000491 | Implement the Python class `ItemFormatter` described below.
Class description:
Formatter converting bw item lists to lists of strings for Rofi
Method signatures and docstrings:
- def unique_format(items): Return a list of items names, and group duplicates items by name
- def group_format(items, converter): Return a l... | Implement the Python class `ItemFormatter` described below.
Class description:
Formatter converting bw item lists to lists of strings for Rofi
Method signatures and docstrings:
- def unique_format(items): Return a list of items names, and group duplicates items by name
- def group_format(items, converter): Return a l... | 2312452b7c56b1c534c4f3874f162b9dc0df92c3 | <|skeleton|>
class ItemFormatter:
"""Formatter converting bw item lists to lists of strings for Rofi"""
def unique_format(items):
"""Return a list of items names, and group duplicates items by name"""
<|body_0|>
def group_format(items, converter):
"""Return a list of numbered items... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ItemFormatter:
"""Formatter converting bw item lists to lists of strings for Rofi"""
def unique_format(items):
"""Return a list of items names, and group duplicates items by name"""
unique = {}
for item in items:
arr = unique.get(item['name'], [])
arr.appen... | the_stack_v2_python_sparse | bitwarden_pyro/util/formatter.py | mihalea/bitwarden-pyro | train | 8 |
271a9b156211331a53efbf7d15818f3d1f9835e2 | [
"Reference.__init__(self, reference_tokens)\nself.n = n\nself._reference_length = len(self._reference_tokens)\nself._reference_ngrams = self._get_ngrams(self._reference_tokens, self.n)",
"n_grams = []\nfor n in range(1, max_n + 1):\n n_grams.append(defaultdict(int))\n for n_gram in zip(*[tokens[i:] for i in... | <|body_start_0|>
Reference.__init__(self, reference_tokens)
self.n = n
self._reference_length = len(self._reference_tokens)
self._reference_ngrams = self._get_ngrams(self._reference_tokens, self.n)
<|end_body_0|>
<|body_start_1|>
n_grams = []
for n in range(1, max_n + 1)... | Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014). | SentenceBleuReference | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentenceBleuReference:
"""Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014)."""
def __init__(self, reference_tokens, n=4):
"""@param reference the reference translation that hypotheses shall be scored against. Must ... | stack_v2_sparse_classes_36k_train_028484 | 3,952 | permissive | [
{
"docstring": "@param reference the reference translation that hypotheses shall be scored against. Must be an iterable of tokens (any type). @param n maximum n-gram order to consider.",
"name": "__init__",
"signature": "def __init__(self, reference_tokens, n=4)"
},
{
"docstring": "Extracts all ... | 3 | null | Implement the Python class `SentenceBleuReference` described below.
Class description:
Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014).
Method signatures and docstrings:
- def __init__(self, reference_tokens, n=4): @param reference the reference t... | Implement the Python class `SentenceBleuReference` described below.
Class description:
Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014).
Method signatures and docstrings:
- def __init__(self, reference_tokens, n=4): @param reference the reference t... | 49d050863bc9644b8c0a9d9ab6e54ccd30f927dd | <|skeleton|>
class SentenceBleuReference:
"""Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014)."""
def __init__(self, reference_tokens, n=4):
"""@param reference the reference translation that hypotheses shall be scored against. Must ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SentenceBleuReference:
"""Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014)."""
def __init__(self, reference_tokens, n=4):
"""@param reference the reference translation that hypotheses shall be scored against. Must be an iterabl... | the_stack_v2_python_sparse | nematus/metrics/sentence_bleu.py | EdinburghNLP/nematus | train | 598 |
4c82c1c9d0216bb8450b7ef5ccc5505b0010b5a9 | [
"super(self.__class__, self).__init__(**kwargs)\nself.columns = columns\nself.css_class = css_class",
"if value is None:\n value = []\nhas_id = attrs and 'id' in attrs\nfinal_attrs = self.build_attrs(attrs, name=name)\nchoices_enum = list(enumerate(chain(self.choices, choices)))\ncolumn_sizes = columnize(len(c... | <|body_start_0|>
super(self.__class__, self).__init__(**kwargs)
self.columns = columns
self.css_class = css_class
<|end_body_0|>
<|body_start_1|>
if value is None:
value = []
has_id = attrs and 'id' in attrs
final_attrs = self.build_attrs(attrs, name=name)
... | Contrôle Multiselect affichant les choix en plusieurs colonnes Chaque colonne est contenue dans un <ul>. Le constructeur accepte columns et css_class | ColumnCheckboxSelectMultiple | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColumnCheckboxSelectMultiple:
"""Contrôle Multiselect affichant les choix en plusieurs colonnes Chaque colonne est contenue dans un <ul>. Le constructeur accepte columns et css_class"""
def __init__(self, columns=2, css_class=None, **kwargs):
"""Initialiser le widget"""
<|bod... | stack_v2_sparse_classes_36k_train_028485 | 8,234 | no_license | [
{
"docstring": "Initialiser le widget",
"name": "__init__",
"signature": "def __init__(self, columns=2, css_class=None, **kwargs)"
},
{
"docstring": "Rendre le widget",
"name": "render",
"signature": "def render(self, name, value, attrs=None, choices=())"
}
] | 2 | null | Implement the Python class `ColumnCheckboxSelectMultiple` described below.
Class description:
Contrôle Multiselect affichant les choix en plusieurs colonnes Chaque colonne est contenue dans un <ul>. Le constructeur accepte columns et css_class
Method signatures and docstrings:
- def __init__(self, columns=2, css_clas... | Implement the Python class `ColumnCheckboxSelectMultiple` described below.
Class description:
Contrôle Multiselect affichant les choix en plusieurs colonnes Chaque colonne est contenue dans un <ul>. Le constructeur accepte columns et css_class
Method signatures and docstrings:
- def __init__(self, columns=2, css_clas... | 8cef6f6e89c1990e2b25f83e54e0c3481d83b6d7 | <|skeleton|>
class ColumnCheckboxSelectMultiple:
"""Contrôle Multiselect affichant les choix en plusieurs colonnes Chaque colonne est contenue dans un <ul>. Le constructeur accepte columns et css_class"""
def __init__(self, columns=2, css_class=None, **kwargs):
"""Initialiser le widget"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ColumnCheckboxSelectMultiple:
"""Contrôle Multiselect affichant les choix en plusieurs colonnes Chaque colonne est contenue dans un <ul>. Le constructeur accepte columns et css_class"""
def __init__(self, columns=2, css_class=None, **kwargs):
"""Initialiser le widget"""
super(self.__class... | the_stack_v2_python_sparse | scoop/core/util/model/widgets.py | artscoop/scoop | train | 0 |
dd0390c1f124d104adb0c5a2e1252f04d8726f55 | [
"logging.info(self.fit.__name__)\nfor i in range(n_iter):\n logging.info('Epoch {}'.format(i + 1))\n grad = self.compute_gradient()\n self.gradient_step(grad, eta)\nreturn self.params",
"logging.info(self.compute_gradient.__name__)\nlogging.debug('self.x shape: {}'.format(self.x.shape))\npred = self.pred... | <|body_start_0|>
logging.info(self.fit.__name__)
for i in range(n_iter):
logging.info('Epoch {}'.format(i + 1))
grad = self.compute_gradient()
self.gradient_step(grad, eta)
return self.params
<|end_body_0|>
<|body_start_1|>
logging.info(self.compute_g... | Run linear regression either with local data or by gradient steps, where gradients can be sent from a remote host. | LinearRegression | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearRegression:
"""Run linear regression either with local data or by gradient steps, where gradients can be sent from a remote host."""
def fit(self, n_iter, eta=0.01):
"""Fit the model"""
<|body_0|>
def compute_gradient(self):
"""Return the gradient computed ... | stack_v2_sparse_classes_36k_train_028486 | 2,007 | no_license | [
{
"docstring": "Fit the model",
"name": "fit",
"signature": "def fit(self, n_iter, eta=0.01)"
},
{
"docstring": "Return the gradient computed for the current model on all training data",
"name": "compute_gradient",
"signature": "def compute_gradient(self)"
},
{
"docstring": "Upda... | 4 | stack_v2_sparse_classes_30k_train_008066 | Implement the Python class `LinearRegression` described below.
Class description:
Run linear regression either with local data or by gradient steps, where gradients can be sent from a remote host.
Method signatures and docstrings:
- def fit(self, n_iter, eta=0.01): Fit the model
- def compute_gradient(self): Return t... | Implement the Python class `LinearRegression` described below.
Class description:
Run linear regression either with local data or by gradient steps, where gradients can be sent from a remote host.
Method signatures and docstrings:
- def fit(self, n_iter, eta=0.01): Fit the model
- def compute_gradient(self): Return t... | b2a1733a914e3c43d4ab7393fea30515389bf8a4 | <|skeleton|>
class LinearRegression:
"""Run linear regression either with local data or by gradient steps, where gradients can be sent from a remote host."""
def fit(self, n_iter, eta=0.01):
"""Fit the model"""
<|body_0|>
def compute_gradient(self):
"""Return the gradient computed ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearRegression:
"""Run linear regression either with local data or by gradient steps, where gradients can be sent from a remote host."""
def fit(self, n_iter, eta=0.01):
"""Fit the model"""
logging.info(self.fit.__name__)
for i in range(n_iter):
logging.info('Epoch {... | the_stack_v2_python_sparse | linear_regression.py | markmo/federated_trainer | train | 0 |
66617fa2583b9f290ef6cc0b8dfbc3de79e900a8 | [
"print('setUp')\nself.item_code = 654\nself.market_price = 800",
"print('test_get_latest_price')\nactual_price = market_prices.get_latest_price(654)\nexpected_price = 24\nself.assertEqual(actual_price, expected_price)",
"print('test_mock_get_latest_price')\nmock = MagicMock(return_value=800)\nactual_price = moc... | <|body_start_0|>
print('setUp')
self.item_code = 654
self.market_price = 800
<|end_body_0|>
<|body_start_1|>
print('test_get_latest_price')
actual_price = market_prices.get_latest_price(654)
expected_price = 24
self.assertEqual(actual_price, expected_price)
<|end... | Perform tests on market_prices module. | MarketPricesTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MarketPricesTests:
"""Perform tests on market_prices module."""
def setUp(self):
"""Define set up characteristics of Market Price tests."""
<|body_0|>
def test_get_latest_price(self):
"""Test get_latest_price module using MagicMock."""
<|body_1|>
def... | stack_v2_sparse_classes_36k_train_028487 | 10,660 | no_license | [
{
"docstring": "Define set up characteristics of Market Price tests.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test get_latest_price module using MagicMock.",
"name": "test_get_latest_price",
"signature": "def test_get_latest_price(self)"
},
{
"docstrin... | 3 | null | Implement the Python class `MarketPricesTests` described below.
Class description:
Perform tests on market_prices module.
Method signatures and docstrings:
- def setUp(self): Define set up characteristics of Market Price tests.
- def test_get_latest_price(self): Test get_latest_price module using MagicMock.
- def tes... | Implement the Python class `MarketPricesTests` described below.
Class description:
Perform tests on market_prices module.
Method signatures and docstrings:
- def setUp(self): Define set up characteristics of Market Price tests.
- def test_get_latest_price(self): Test get_latest_price module using MagicMock.
- def tes... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class MarketPricesTests:
"""Perform tests on market_prices module."""
def setUp(self):
"""Define set up characteristics of Market Price tests."""
<|body_0|>
def test_get_latest_price(self):
"""Test get_latest_price module using MagicMock."""
<|body_1|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MarketPricesTests:
"""Perform tests on market_prices module."""
def setUp(self):
"""Define set up characteristics of Market Price tests."""
print('setUp')
self.item_code = 654
self.market_price = 800
def test_get_latest_price(self):
"""Test get_latest_price mo... | the_stack_v2_python_sparse | students/Reem_Alqaysi/Lesson_01/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 |
599af88d2b0bed14370bf53769fdee1cd092246a | [
"nums1, nums2 = (sorted(nums1), sorted(nums2))\ni, j = (0, 0)\nres = []\nwhile i < len(nums1) and j < len(nums2):\n if nums1[i] < nums2[j]:\n i += 1\n elif nums1[i] > nums2[j]:\n j += 1\n else:\n res.append(nums1[i])\n i += 1\n j += 1\nreturn res",
"if len(nums1) > len(... | <|body_start_0|>
nums1, nums2 = (sorted(nums1), sorted(nums2))
i, j = (0, 0)
res = []
while i < len(nums1) and j < len(nums2):
if nums1[i] < nums2[j]:
i += 1
elif nums1[i] > nums2[j]:
j += 1
else:
res.app... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_0|>
def intersect0(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_028488 | 1,227 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: List[int]",
"name": "intersect",
"signature": "def intersect(self, nums1, nums2)"
},
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: List[int]",
"name": "intersect0",
"signature": "def intersect0(... | 2 | stack_v2_sparse_classes_30k_train_013645 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: List[int]
- def intersect0(self, nums1, nums2): :type nums1: List[int] :type nums2: List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def intersect(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: List[int]
- def intersect0(self, nums1, nums2): :type nums1: List[int] :type nums2: List[... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_0|>
def intersect0(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def intersect(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: List[int]"""
nums1, nums2 = (sorted(nums1), sorted(nums2))
i, j = (0, 0)
res = []
while i < len(nums1) and j < len(nums2):
if nums1[i] < nums2[j]:
... | the_stack_v2_python_sparse | out/production/leetcode/350.两个数组的交集-ii.py | yangyuxiang1996/leetcode | train | 0 | |
09c15b34fc1ebb4dee9252980e9fb49bcfc335f4 | [
"PygameScreen.__init__(self)\nself.menuView = MenuWithBackgroundWidget(menu, self.width * 0.4, self.height)\nself.lastScreen = lastScreen",
"screenSurface = self.lastScreen.draw()\nself.drawOnSurface(screenSurface, left=0, top=0)\nmenuSurface = self.menuView.draw()\nself.drawOnSurface(menuSurface, right=1, top=0)... | <|body_start_0|>
PygameScreen.__init__(self)
self.menuView = MenuWithBackgroundWidget(menu, self.width * 0.4, self.height)
self.lastScreen = lastScreen
<|end_body_0|>
<|body_start_1|>
screenSurface = self.lastScreen.draw()
self.drawOnSurface(screenSurface, left=0, top=0)
... | Represents the screen for the Zone Menu | ZoneMenuScreen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZoneMenuScreen:
"""Represents the screen for the Zone Menu"""
def __init__(self, menu, lastScreen):
"""Initialize the screen"""
<|body_0|>
def drawSurface(self):
"""Draws the screen"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
PygameScreen.__... | stack_v2_sparse_classes_36k_train_028489 | 768 | no_license | [
{
"docstring": "Initialize the screen",
"name": "__init__",
"signature": "def __init__(self, menu, lastScreen)"
},
{
"docstring": "Draws the screen",
"name": "drawSurface",
"signature": "def drawSurface(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005916 | Implement the Python class `ZoneMenuScreen` described below.
Class description:
Represents the screen for the Zone Menu
Method signatures and docstrings:
- def __init__(self, menu, lastScreen): Initialize the screen
- def drawSurface(self): Draws the screen | Implement the Python class `ZoneMenuScreen` described below.
Class description:
Represents the screen for the Zone Menu
Method signatures and docstrings:
- def __init__(self, menu, lastScreen): Initialize the screen
- def drawSurface(self): Draws the screen
<|skeleton|>
class ZoneMenuScreen:
"""Represents the sc... | 3931eee5fd04e18bb1738a0b27a4c6979dc4db01 | <|skeleton|>
class ZoneMenuScreen:
"""Represents the screen for the Zone Menu"""
def __init__(self, menu, lastScreen):
"""Initialize the screen"""
<|body_0|>
def drawSurface(self):
"""Draws the screen"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZoneMenuScreen:
"""Represents the screen for the Zone Menu"""
def __init__(self, menu, lastScreen):
"""Initialize the screen"""
PygameScreen.__init__(self)
self.menuView = MenuWithBackgroundWidget(menu, self.width * 0.4, self.height)
self.lastScreen = lastScreen
def d... | the_stack_v2_python_sparse | src/Screen/Pygame/Menu/ZoneMenu/zone_menu_screen.py | sgtnourry/Pokemon-Project | train | 0 |
74feaa5bc2b7f188fe1ccb62c12a7e9381a925b6 | [
"self.max_read_throughput = max_read_throughput\nself.max_write_throughput = max_write_throughput\nself.read_throughput_samples = read_throughput_samples\nself.write_throughput_samples = write_throughput_samples",
"if dictionary is None:\n return None\nmax_read_throughput = dictionary.get('maxReadThroughput')\... | <|body_start_0|>
self.max_read_throughput = max_read_throughput
self.max_write_throughput = max_write_throughput
self.read_throughput_samples = read_throughput_samples
self.write_throughput_samples = write_throughput_samples
<|end_body_0|>
<|body_start_1|>
if dictionary is None:... | Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 hours. read_throughput_samples (list of Sample): Read throughput samples taken for... | ThroughputTile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThroughputTile:
"""Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 hours. read_throughput_samples (list of ... | stack_v2_sparse_classes_36k_train_028490 | 3,283 | permissive | [
{
"docstring": "Constructor for the ThroughputTile class",
"name": "__init__",
"signature": "def __init__(self, max_read_throughput=None, max_write_throughput=None, read_throughput_samples=None, write_throughput_samples=None)"
},
{
"docstring": "Creates an instance of this model from a dictionar... | 2 | stack_v2_sparse_classes_30k_train_018703 | Implement the Python class `ThroughputTile` described below.
Class description:
Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 h... | Implement the Python class `ThroughputTile` described below.
Class description:
Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 h... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ThroughputTile:
"""Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 hours. read_throughput_samples (list of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThroughputTile:
"""Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 hours. read_throughput_samples (list of Sample): Read... | the_stack_v2_python_sparse | cohesity_management_sdk/models/throughput_tile.py | cohesity/management-sdk-python | train | 24 |
f0406cb197e032a72ddf1641254ff9bf5c4c2e4a | [
"Arme.__init__(self, cle)\nself.peut_depecer = False\nself.emplacement = ''\nself.positions = ()",
"evt_atteint = self.script.creer_evenement('atteint')\nevt_atteint.aide_courte = 'le projectile atteint une cible'\nevt_atteint.aide_longue = \"Cet évènement est appelé quand le projectile vient d'atteindre une cibl... | <|body_start_0|>
Arme.__init__(self, cle)
self.peut_depecer = False
self.emplacement = ''
self.positions = ()
<|end_body_0|>
<|body_start_1|>
evt_atteint = self.script.creer_evenement('atteint')
evt_atteint.aide_courte = 'le projectile atteint une cible'
evt_atte... | Type d'objet: projectile. | Projectile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Projectile:
"""Type d'objet: projectile."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
<|body_0|>
def etendre_script(self):
"""Extension du scripting."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Arme.__init__(self, cle)
... | stack_v2_sparse_classes_36k_train_028491 | 3,007 | permissive | [
{
"docstring": "Constructeur de l'objet",
"name": "__init__",
"signature": "def __init__(self, cle='')"
},
{
"docstring": "Extension du scripting.",
"name": "etendre_script",
"signature": "def etendre_script(self)"
}
] | 2 | null | Implement the Python class `Projectile` described below.
Class description:
Type d'objet: projectile.
Method signatures and docstrings:
- def __init__(self, cle=''): Constructeur de l'objet
- def etendre_script(self): Extension du scripting. | Implement the Python class `Projectile` described below.
Class description:
Type d'objet: projectile.
Method signatures and docstrings:
- def __init__(self, cle=''): Constructeur de l'objet
- def etendre_script(self): Extension du scripting.
<|skeleton|>
class Projectile:
"""Type d'objet: projectile."""
def... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class Projectile:
"""Type d'objet: projectile."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
<|body_0|>
def etendre_script(self):
"""Extension du scripting."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Projectile:
"""Type d'objet: projectile."""
def __init__(self, cle=''):
"""Constructeur de l'objet"""
Arme.__init__(self, cle)
self.peut_depecer = False
self.emplacement = ''
self.positions = ()
def etendre_script(self):
"""Extension du scripting."""
... | the_stack_v2_python_sparse | src/primaires/combat/types/projectile.py | vincent-lg/tsunami | train | 5 |
0a5b89f0b86a8831e5291a270d789161ea7f8056 | [
"keep = (input,)\nctx.num_classes = num_classes\nctx.dim = dim\ndata = input[:, :-num_classes]\nsegmentation = input[:, -num_classes:]\nclass_index = torch.argmax(segmentation, dim=1)\nbatch_indices = torch.unique(data[:, dim])\nkeep += (class_index, batch_indices)\noutput = []\nfor b in batch_indices:\n batch_i... | <|body_start_0|>
keep = (input,)
ctx.num_classes = num_classes
ctx.dim = dim
data = input[:, :-num_classes]
segmentation = input[:, -num_classes:]
class_index = torch.argmax(segmentation, dim=1)
batch_indices = torch.unique(data[:, dim])
keep += (class_ind... | DBScanFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBScanFunction:
def forward(ctx, input, epsilon, minPoints, num_classes, dim):
"""input.shape = (N, dim + batch_index + feature + num_classes) epsilon, minPoints: parameters of DBScan num_classes: semantic segmentation classes dim: 2D or 3D"""
<|body_0|>
def backward(ctx, *g... | stack_v2_sparse_classes_36k_train_028492 | 12,354 | no_license | [
{
"docstring": "input.shape = (N, dim + batch_index + feature + num_classes) epsilon, minPoints: parameters of DBScan num_classes: semantic segmentation classes dim: 2D or 3D",
"name": "forward",
"signature": "def forward(ctx, input, epsilon, minPoints, num_classes, dim)"
},
{
"docstring": "len(... | 2 | stack_v2_sparse_classes_30k_train_017236 | Implement the Python class `DBScanFunction` described below.
Class description:
Implement the DBScanFunction class.
Method signatures and docstrings:
- def forward(ctx, input, epsilon, minPoints, num_classes, dim): input.shape = (N, dim + batch_index + feature + num_classes) epsilon, minPoints: parameters of DBScan n... | Implement the Python class `DBScanFunction` described below.
Class description:
Implement the DBScanFunction class.
Method signatures and docstrings:
- def forward(ctx, input, epsilon, minPoints, num_classes, dim): input.shape = (N, dim + batch_index + feature + num_classes) epsilon, minPoints: parameters of DBScan n... | 9f022c9204741273ae451e8b3ed40385e676c6e8 | <|skeleton|>
class DBScanFunction:
def forward(ctx, input, epsilon, minPoints, num_classes, dim):
"""input.shape = (N, dim + batch_index + feature + num_classes) epsilon, minPoints: parameters of DBScan num_classes: semantic segmentation classes dim: 2D or 3D"""
<|body_0|>
def backward(ctx, *g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DBScanFunction:
def forward(ctx, input, epsilon, minPoints, num_classes, dim):
"""input.shape = (N, dim + batch_index + feature + num_classes) epsilon, minPoints: parameters of DBScan num_classes: semantic segmentation classes dim: 2D or 3D"""
keep = (input,)
ctx.num_classes = num_clas... | the_stack_v2_python_sparse | mlreco/models/layers/dbscan.py | francois-drielsma/lartpc_mlreco3d | train | 0 | |
41b7649873ec0e4890a883ade215fe493c730512 | [
"if self.driver.owner != self.name:\n self.driver.owner = self.name\nsweep_modes = {'SA': 'Spectrum Analyzer', 'SPEC': 'Basic Spectrum Analyzer', 'WAV': 'Waveform'}\nd = self.driver\nheader = cleandoc('Start freq {}, Stop freq {}, Span freq {},\\n Center freq {}, Average number {}, Resol... | <|body_start_0|>
if self.driver.owner != self.name:
self.driver.owner = self.name
sweep_modes = {'SA': 'Spectrum Analyzer', 'SPEC': 'Basic Spectrum Analyzer', 'WAV': 'Waveform'}
d = self.driver
header = cleandoc('Start freq {}, Stop freq {}, Span freq {},\n ... | Get the trace displayed on the Power Spectrum Analyzer. | PSAGetTrace | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PSAGetTrace:
"""Get the trace displayed on the Power Spectrum Analyzer."""
def perform(self):
"""Get the specified trace from the instrument."""
<|body_0|>
def check(self, *args, **kwargs):
"""Validate the provided trace number."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k_train_028493 | 11,298 | permissive | [
{
"docstring": "Get the specified trace from the instrument.",
"name": "perform",
"signature": "def perform(self)"
},
{
"docstring": "Validate the provided trace number.",
"name": "check",
"signature": "def check(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000135 | Implement the Python class `PSAGetTrace` described below.
Class description:
Get the trace displayed on the Power Spectrum Analyzer.
Method signatures and docstrings:
- def perform(self): Get the specified trace from the instrument.
- def check(self, *args, **kwargs): Validate the provided trace number. | Implement the Python class `PSAGetTrace` described below.
Class description:
Get the trace displayed on the Power Spectrum Analyzer.
Method signatures and docstrings:
- def perform(self): Get the specified trace from the instrument.
- def check(self, *args, **kwargs): Validate the provided trace number.
<|skeleton|>... | b6f1f5b236c7a4e28d9a3bc8da9820c52d789309 | <|skeleton|>
class PSAGetTrace:
"""Get the trace displayed on the Power Spectrum Analyzer."""
def perform(self):
"""Get the specified trace from the instrument."""
<|body_0|>
def check(self, *args, **kwargs):
"""Validate the provided trace number."""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PSAGetTrace:
"""Get the trace displayed on the Power Spectrum Analyzer."""
def perform(self):
"""Get the specified trace from the instrument."""
if self.driver.owner != self.name:
self.driver.owner = self.name
sweep_modes = {'SA': 'Spectrum Analyzer', 'SPEC': 'Basic Sp... | the_stack_v2_python_sparse | exopy_hqc_legacy/tasks/tasks/instr/psa_tasks.py | Exopy/exopy_hqc_legacy | train | 0 |
830fdd57965002c33b9f60be7d82ded88b8b23f1 | [
"response: ResponseData = auth_service.list_users(session.get('token'))\nWebUtils.flash_response_messages(response)\nif response.get_content() is not None and isinstance(response.get_content(), list):\n return list(response.get_content())\nreturn []",
"response: ResponseData = auth_service.create_user(session.... | <|body_start_0|>
response: ResponseData = auth_service.list_users(session.get('token'))
WebUtils.flash_response_messages(response)
if response.get_content() is not None and isinstance(response.get_content(), list):
return list(response.get_content())
return []
<|end_body_0|>
... | Monostate class responsible of the user operation utilities. | WebUser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebUser:
"""Monostate class responsible of the user operation utilities."""
def list_users(auth_service: AuthService) -> List:
"""Gets the list of users from the authentication service. Args: - auth_service (AuthService): The authentication service. Returns: - List: A list of user da... | stack_v2_sparse_classes_36k_train_028494 | 3,230 | no_license | [
{
"docstring": "Gets the list of users from the authentication service. Args: - auth_service (AuthService): The authentication service. Returns: - List: A list of user data dictionaries (the list may be empty)",
"name": "list_users",
"signature": "def list_users(auth_service: AuthService) -> List"
},
... | 4 | stack_v2_sparse_classes_30k_train_019121 | Implement the Python class `WebUser` described below.
Class description:
Monostate class responsible of the user operation utilities.
Method signatures and docstrings:
- def list_users(auth_service: AuthService) -> List: Gets the list of users from the authentication service. Args: - auth_service (AuthService): The a... | Implement the Python class `WebUser` described below.
Class description:
Monostate class responsible of the user operation utilities.
Method signatures and docstrings:
- def list_users(auth_service: AuthService) -> List: Gets the list of users from the authentication service. Args: - auth_service (AuthService): The a... | d7d50f84e93914d388ccd084b3bee7e02c9e717b | <|skeleton|>
class WebUser:
"""Monostate class responsible of the user operation utilities."""
def list_users(auth_service: AuthService) -> List:
"""Gets the list of users from the authentication service. Args: - auth_service (AuthService): The authentication service. Returns: - List: A list of user da... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WebUser:
"""Monostate class responsible of the user operation utilities."""
def list_users(auth_service: AuthService) -> List:
"""Gets the list of users from the authentication service. Args: - auth_service (AuthService): The authentication service. Returns: - List: A list of user data dictionari... | the_stack_v2_python_sparse | components/dms2122frontend/dms2122frontend/presentation/web/webuser.py | Kencho/practica-dms-2021-2022 | train | 0 |
fe6133b057ca146dfd8c8446bb3a4c85bb58d49e | [
"self.upper_num = 320\nself.x = np.random.randint(-1, self.upper_num, size=(6000, 200)).astype('int64')\nself.out = count(self.x, self.upper_num)\nself.place = paddle.CUDAPlace(0)",
"paddle.enable_static()\nwith paddle.static.program_guard(paddle.static.Program()):\n x = paddle.static.data('x', self.x.shape, d... | <|body_start_0|>
self.upper_num = 320
self.x = np.random.randint(-1, self.upper_num, size=(6000, 200)).astype('int64')
self.out = count(self.x, self.upper_num)
self.place = paddle.CUDAPlace(0)
<|end_body_0|>
<|body_start_1|>
paddle.enable_static()
with paddle.static.prog... | TestNumberCountAPI | TestNumberCountAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestNumberCountAPI:
"""TestNumberCountAPI"""
def setUp(self):
"""setUp"""
<|body_0|>
def test_MoE_number_count_static(self):
"""test_MoE_number_count_static"""
<|body_1|>
def test_MoE_number_count_dygraph(self):
"""test_MoE_number_count_dygra... | stack_v2_sparse_classes_36k_train_028495 | 2,365 | no_license | [
{
"docstring": "setUp",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "test_MoE_number_count_static",
"name": "test_MoE_number_count_static",
"signature": "def test_MoE_number_count_static(self)"
},
{
"docstring": "test_MoE_number_count_dygraph",
"name": "... | 3 | stack_v2_sparse_classes_30k_train_006959 | Implement the Python class `TestNumberCountAPI` described below.
Class description:
TestNumberCountAPI
Method signatures and docstrings:
- def setUp(self): setUp
- def test_MoE_number_count_static(self): test_MoE_number_count_static
- def test_MoE_number_count_dygraph(self): test_MoE_number_count_dygraph | Implement the Python class `TestNumberCountAPI` described below.
Class description:
TestNumberCountAPI
Method signatures and docstrings:
- def setUp(self): setUp
- def test_MoE_number_count_static(self): test_MoE_number_count_static
- def test_MoE_number_count_dygraph(self): test_MoE_number_count_dygraph
<|skeleton|... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class TestNumberCountAPI:
"""TestNumberCountAPI"""
def setUp(self):
"""setUp"""
<|body_0|>
def test_MoE_number_count_static(self):
"""test_MoE_number_count_static"""
<|body_1|>
def test_MoE_number_count_dygraph(self):
"""test_MoE_number_count_dygra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestNumberCountAPI:
"""TestNumberCountAPI"""
def setUp(self):
"""setUp"""
self.upper_num = 320
self.x = np.random.randint(-1, self.upper_num, size=(6000, 200)).astype('int64')
self.out = count(self.x, self.upper_num)
self.place = paddle.CUDAPlace(0)
def test_M... | the_stack_v2_python_sparse | distributed/CE_API/case/dist_MoE_number_count.py | PaddlePaddle/PaddleTest | train | 42 |
cb45201393807138cd6afb8704970b72f6b2267a | [
"self.source: str = source\nself.content: str = content\nself.is_error: bool = is_error",
"pad = len(self.source) if len(self.source) > source_len else source_len\ncolor_code = '\\x1b[31;1m' if self.is_error and colorize else ''\nreset_code = '\\x1b[0m' if self.is_error and colorize else ''\nreturn f'[ {self.sour... | <|body_start_0|>
self.source: str = source
self.content: str = content
self.is_error: bool = is_error
<|end_body_0|>
<|body_start_1|>
pad = len(self.source) if len(self.source) > source_len else source_len
color_code = '\x1b[31;1m' if self.is_error and colorize else ''
r... | Helper class for managing messages. | Message | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message:
"""Helper class for managing messages."""
def __init__(self, source: str, content: str, is_error: bool=False) -> None:
"""Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runtime name. content: The content of the message. is_error: T... | stack_v2_sparse_classes_36k_train_028496 | 17,020 | permissive | [
{
"docstring": "Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runtime name. content: The content of the message. is_error: True if the message is an error message, False otherwise.",
"name": "__init__",
"signature": "def __init__(self, source: str, content: s... | 2 | stack_v2_sparse_classes_30k_train_019191 | Implement the Python class `Message` described below.
Class description:
Helper class for managing messages.
Method signatures and docstrings:
- def __init__(self, source: str, content: str, is_error: bool=False) -> None: Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runti... | Implement the Python class `Message` described below.
Class description:
Helper class for managing messages.
Method signatures and docstrings:
- def __init__(self, source: str, content: str, is_error: bool=False) -> None: Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runti... | bcea85b1ce7a0feb2aa28b5be4fc6ae124e8ca3c | <|skeleton|>
class Message:
"""Helper class for managing messages."""
def __init__(self, source: str, content: str, is_error: bool=False) -> None:
"""Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runtime name. content: The content of the message. is_error: T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Message:
"""Helper class for managing messages."""
def __init__(self, source: str, content: str, is_error: bool=False) -> None:
"""Initialize a Message object. Args: source: The source of the message, eg 'dftimewolf' or a runtime name. content: The content of the message. is_error: True if the me... | the_stack_v2_python_sparse | dftimewolf/cli/curses_display_manager.py | log2timeline/dftimewolf | train | 248 |
435b2f192cd22e0af748734c701b465bcc46ee9f | [
"agent = request.user.userinfo.agent\nobj = SetPay.objects.get_or_create(agent=agent)[0]\nmydata = model_to_dict(obj)\nuser = request.user\ncrm = Crm(user=user)\ndata = crm.get_agent_info()\nif data['status'] == 200:\n mydata['pay_online'] = int(mydata['pay_online'])\n mydata['pay_outline'] = int(mydata['pay_... | <|body_start_0|>
agent = request.user.userinfo.agent
obj = SetPay.objects.get_or_create(agent=agent)[0]
mydata = model_to_dict(obj)
user = request.user
crm = Crm(user=user)
data = crm.get_agent_info()
if data['status'] == 200:
mydata['pay_online'] = in... | 支付信息 | Finance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Finance:
"""支付信息"""
def get(self, request):
"""获取财务设置信息 包括在线支付离线支付"""
<|body_0|>
def put(self, request):
"""修改财务信息"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
agent = request.user.userinfo.agent
obj = SetPay.objects.get_or_create(age... | stack_v2_sparse_classes_36k_train_028497 | 32,690 | no_license | [
{
"docstring": "获取财务设置信息 包括在线支付离线支付",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "修改财务信息",
"name": "put",
"signature": "def put(self, request)"
}
] | 2 | null | Implement the Python class `Finance` described below.
Class description:
支付信息
Method signatures and docstrings:
- def get(self, request): 获取财务设置信息 包括在线支付离线支付
- def put(self, request): 修改财务信息 | Implement the Python class `Finance` described below.
Class description:
支付信息
Method signatures and docstrings:
- def get(self, request): 获取财务设置信息 包括在线支付离线支付
- def put(self, request): 修改财务信息
<|skeleton|>
class Finance:
"""支付信息"""
def get(self, request):
"""获取财务设置信息 包括在线支付离线支付"""
<|body_0|>
... | d6e025d7e9d9e3aecfd399c77f376130edd8a2df | <|skeleton|>
class Finance:
"""支付信息"""
def get(self, request):
"""获取财务设置信息 包括在线支付离线支付"""
<|body_0|>
def put(self, request):
"""修改财务信息"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Finance:
"""支付信息"""
def get(self, request):
"""获取财务设置信息 包括在线支付离线支付"""
agent = request.user.userinfo.agent
obj = SetPay.objects.get_or_create(agent=agent)[0]
mydata = model_to_dict(obj)
user = request.user
crm = Crm(user=user)
data = crm.get_agent_in... | the_stack_v2_python_sparse | soc_system/views/set_views.py | sundw2015/841 | train | 4 |
9948a0726f7a8ac952d193426f00b0befa4c3166 | [
"self.nx = config['nx']\ndx = config['dx']\nxbgn, xend = config['x_limits']\nxpos = position - xbgn\nixs = max(1, int(np.ceil(xpos / dx)))\nfrac = ixs - xpos / dx\nfrac = 0.0 if ixs == 1 else frac\nfrac = 1.0 if ixs == self.nx - 1 else frac\nself.ixs = ixs\nself.frac = frac",
"f = torch.zeros([self.nx]).to(device... | <|body_start_0|>
self.nx = config['nx']
dx = config['dx']
xbgn, xend = config['x_limits']
xpos = position - xbgn
ixs = max(1, int(np.ceil(xpos / dx)))
frac = ixs - xpos / dx
frac = 0.0 if ixs == 1 else frac
frac = 1.0 if ixs == self.nx - 1 else frac
... | Point_Source | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Point_Source:
def __init__(self, position, config):
"""Configures interpolation of source in sampling grid"""
<|body_0|>
def set(self, value):
"""Sets amplitude at source point for current time"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.nx... | stack_v2_sparse_classes_36k_train_028498 | 20,893 | no_license | [
{
"docstring": "Configures interpolation of source in sampling grid",
"name": "__init__",
"signature": "def __init__(self, position, config)"
},
{
"docstring": "Sets amplitude at source point for current time",
"name": "set",
"signature": "def set(self, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018456 | Implement the Python class `Point_Source` described below.
Class description:
Implement the Point_Source class.
Method signatures and docstrings:
- def __init__(self, position, config): Configures interpolation of source in sampling grid
- def set(self, value): Sets amplitude at source point for current time | Implement the Python class `Point_Source` described below.
Class description:
Implement the Point_Source class.
Method signatures and docstrings:
- def __init__(self, position, config): Configures interpolation of source in sampling grid
- def set(self, value): Sets amplitude at source point for current time
<|skele... | b7477f7659126da69b9a1bab0377f12c595ffbfb | <|skeleton|>
class Point_Source:
def __init__(self, position, config):
"""Configures interpolation of source in sampling grid"""
<|body_0|>
def set(self, value):
"""Sets amplitude at source point for current time"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Point_Source:
def __init__(self, position, config):
"""Configures interpolation of source in sampling grid"""
self.nx = config['nx']
dx = config['dx']
xbgn, xend = config['x_limits']
xpos = position - xbgn
ixs = max(1, int(np.ceil(xpos / dx)))
frac = ixs... | the_stack_v2_python_sparse | fwi-dl/Wave1D_AGfunc.py | lhuang-pvamu/pytorch-examples | train | 1 | |
74c3d40ebce98239fdf97bb088898407e971718f | [
"connect = Operate_datebase_table('adv_spider_article_link')\nurl = connect.selectTable('(url,source_id,id)', 'fetched=0')\nif url != ():\n for url_one in url:\n data_connect = Operate_datebase_table('adv_spider_source')\n datas = data_connect.selectTable('(extract_tittle_rule,extract_content_rule)... | <|body_start_0|>
connect = Operate_datebase_table('adv_spider_article_link')
url = connect.selectTable('(url,source_id,id)', 'fetched=0')
if url != ():
for url_one in url:
data_connect = Operate_datebase_table('adv_spider_source')
datas = data_connect.... | SpiderSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpiderSpider:
def start_requests(self):
"""flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :return:"""
<|body_0|>
def parse(self, response):
"""flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :... | stack_v2_sparse_classes_36k_train_028499 | 3,065 | no_license | [
{
"docstring": "flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :return:",
"name": "start_requests",
"signature": "def start_requests(self)"
},
{
"docstring": "flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :return:",
... | 2 | stack_v2_sparse_classes_30k_train_008938 | Implement the Python class `SpiderSpider` described below.
Class description:
Implement the SpiderSpider class.
Method signatures and docstrings:
- def start_requests(self): flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :return:
- def parse(self, response): flag 标志位：是否已经爬取 title... | Implement the Python class `SpiderSpider` described below.
Class description:
Implement the SpiderSpider class.
Method signatures and docstrings:
- def start_requests(self): flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :return:
- def parse(self, response): flag 标志位：是否已经爬取 title... | 206fa55b1a0b471478beaad06a09f6718cbeb00f | <|skeleton|>
class SpiderSpider:
def start_requests(self):
"""flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :return:"""
<|body_0|>
def parse(self, response):
"""flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpiderSpider:
def start_requests(self):
"""flag 标志位：是否已经爬取 title 标题：文章标题 content 内容：文章的内容 author 作者：文章的作者 creat_time 时间：文章发表的时间 :return:"""
connect = Operate_datebase_table('adv_spider_article_link')
url = connect.selectTable('(url,source_id,id)', 'fetched=0')
if url != ():
... | the_stack_v2_python_sparse | spider_system/spider_list/spider_list/spiders/spider_page.py | logonmy/colely | train | 0 |
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