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value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
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value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1ea4af1694f47282d97b6ecb88bd57e07d6fafdf | [
"if len(token) != 59:\n raise InvalidTokenError('Discord Token must have exactly 59 characters.')\nself.__token = token\nself.__keep_alive = True\nself.__socket: Optional[WebSocketClientProtocol] = None\n\nasync def identify_and_handle_hello(socket: WebSocketClientProtocol, payload: GatewayDispatch):\n \"\"\"... | <|body_start_0|>
if len(token) != 59:
raise InvalidTokenError('Discord Token must have exactly 59 characters.')
self.__token = token
self.__keep_alive = True
self.__socket: Optional[WebSocketClientProtocol] = None
async def identify_and_handle_hello(socket: WebSocket... | The Dispatcher handles all interactions with discord websocket API. This also contains the main event loop, and handles the heartbeat. Running the dispatcher will create a connection with the Discord WebSocket API on behalf of the provided token. This token must be a bot token. (Which can be found on `<https://discord.... | Dispatcher | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dispatcher:
"""The Dispatcher handles all interactions with discord websocket API. This also contains the main event loop, and handles the heartbeat. Running the dispatcher will create a connection with the Discord WebSocket API on behalf of the provided token. This token must be a bot token. (Wh... | stack_v2_sparse_classes_75kplus_train_005800 | 9,329 | permissive | [
{
"docstring": ":param token: Bot token for discord's API. :raises InvalidTokenError: Discord Token length is not 59 characters.",
"name": "__init__",
"signature": "def __init__(self, token: str, *, handlers: Dict[int, Handler]) -> None"
},
{
"docstring": "This manages all handles for given OP c... | 5 | stack_v2_sparse_classes_30k_train_008999 | Implement the Python class `Dispatcher` described below.
Class description:
The Dispatcher handles all interactions with discord websocket API. This also contains the main event loop, and handles the heartbeat. Running the dispatcher will create a connection with the Discord WebSocket API on behalf of the provided tok... | Implement the Python class `Dispatcher` described below.
Class description:
The Dispatcher handles all interactions with discord websocket API. This also contains the main event loop, and handles the heartbeat. Running the dispatcher will create a connection with the Discord WebSocket API on behalf of the provided tok... | d130d8e92eba259fa662a77e3b23549c5d0ef0ff | <|skeleton|>
class Dispatcher:
"""The Dispatcher handles all interactions with discord websocket API. This also contains the main event loop, and handles the heartbeat. Running the dispatcher will create a connection with the Discord WebSocket API on behalf of the provided token. This token must be a bot token. (Wh... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Dispatcher:
"""The Dispatcher handles all interactions with discord websocket API. This also contains the main event loop, and handles the heartbeat. Running the dispatcher will create a connection with the Discord WebSocket API on behalf of the provided token. This token must be a bot token. (Which can be fo... | the_stack_v2_python_sparse | pincer/core/gateway.py | WhyDoWeLiveWithoutMeaning/Pincer | train | 0 |
bb4ff44961b1f4f7f8c0acd86a4c99f12f4b84c9 | [
"if isinstance(exc, NotImplementedError):\n return self._make_error_response(400, str(exc))\nif isinstance(exc, ItemNotFoundError):\n return self._make_error_response(400, str(exc))\nreturn super().handle_exception(exc)",
"course_key = CourseKey.from_string(course_id)\nif not has_studio_write_access(request... | <|body_start_0|>
if isinstance(exc, NotImplementedError):
return self._make_error_response(400, str(exc))
if isinstance(exc, ItemNotFoundError):
return self._make_error_response(400, str(exc))
return super().handle_exception(exc)
<|end_body_0|>
<|body_start_1|>
c... | API view for course tabs settings. | CourseTabSettingsView | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CourseTabSettingsView:
"""API view for course tabs settings."""
def handle_exception(self, exc):
"""Handle NotImplementedError and return a proper response for it."""
<|body_0|>
def post(self, request: Request, course_id: str) -> Response:
"""Change visibility of... | stack_v2_sparse_classes_75kplus_train_005801 | 8,341 | permissive | [
{
"docstring": "Handle NotImplementedError and return a proper response for it.",
"name": "handle_exception",
"signature": "def handle_exception(self, exc)"
},
{
"docstring": "Change visibility of tabs in a course. **Example Requests** You can provide either a tab_id or a tab_location. Hide a co... | 2 | stack_v2_sparse_classes_30k_train_023197 | Implement the Python class `CourseTabSettingsView` described below.
Class description:
API view for course tabs settings.
Method signatures and docstrings:
- def handle_exception(self, exc): Handle NotImplementedError and return a proper response for it.
- def post(self, request: Request, course_id: str) -> Response:... | Implement the Python class `CourseTabSettingsView` described below.
Class description:
API view for course tabs settings.
Method signatures and docstrings:
- def handle_exception(self, exc): Handle NotImplementedError and return a proper response for it.
- def post(self, request: Request, course_id: str) -> Response:... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class CourseTabSettingsView:
"""API view for course tabs settings."""
def handle_exception(self, exc):
"""Handle NotImplementedError and return a proper response for it."""
<|body_0|>
def post(self, request: Request, course_id: str) -> Response:
"""Change visibility of... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CourseTabSettingsView:
"""API view for course tabs settings."""
def handle_exception(self, exc):
"""Handle NotImplementedError and return a proper response for it."""
if isinstance(exc, NotImplementedError):
return self._make_error_response(400, str(exc))
if isinstance... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/cms/djangoapps/contentstore/rest_api/v0/views/tabs.py | luque/better-ways-of-thinking-about-software | train | 3 |
06a9076f56e9c141773fd7deea07ea4144544863 | [
"super().__init__(number, name, activation=activation, reg=reg, verbose=verbose)\nmu = 0\nstd = 1\nself.wts = np.random.normal(mu, std, (n_units_prev_layer, units)) * wt_scale\nself.b = np.random.normal(mu, std, (units,)) * wt_scale",
"input = np.reshape(self.input, [self.input.shape[0], np.prod(self.input.shape[... | <|body_start_0|>
super().__init__(number, name, activation=activation, reg=reg, verbose=verbose)
mu = 0
std = 1
self.wts = np.random.normal(mu, std, (n_units_prev_layer, units)) * wt_scale
self.b = np.random.normal(mu, std, (units,)) * wt_scale
<|end_body_0|>
<|body_start_1|>
... | Dense (fully-connected) layer. Each units recieves (weighted) input from all units in the previous layer. These are the layers used in a multilayer perceptron. NOTE: Units are spatially arranged in 1D only - no 2D like Conv2D. | Dense | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dense:
"""Dense (fully-connected) layer. Each units recieves (weighted) input from all units in the previous layer. These are the layers used in a multilayer perceptron. NOTE: Units are spatially arranged in 1D only - no 2D like Conv2D."""
def __init__(self, number, name, units, n_units_prev... | stack_v2_sparse_classes_75kplus_train_005802 | 28,030 | no_license | [
{
"docstring": "Parameters: ----------- number: int. Current layer number in the net. 0, ..., L-1, where L is the total number of layers. name: string. Human-readable string for identification/debugging. e.g. 'Conv2' units: int. Number of hidden units in the layer. n_units_prev_layer: int. Total number of units... | 3 | stack_v2_sparse_classes_30k_train_044368 | Implement the Python class `Dense` described below.
Class description:
Dense (fully-connected) layer. Each units recieves (weighted) input from all units in the previous layer. These are the layers used in a multilayer perceptron. NOTE: Units are spatially arranged in 1D only - no 2D like Conv2D.
Method signatures an... | Implement the Python class `Dense` described below.
Class description:
Dense (fully-connected) layer. Each units recieves (weighted) input from all units in the previous layer. These are the layers used in a multilayer perceptron. NOTE: Units are spatially arranged in 1D only - no 2D like Conv2D.
Method signatures an... | 924c5db8b7b7a70fae87d0fc30b28b6ce9cfa529 | <|skeleton|>
class Dense:
"""Dense (fully-connected) layer. Each units recieves (weighted) input from all units in the previous layer. These are the layers used in a multilayer perceptron. NOTE: Units are spatially arranged in 1D only - no 2D like Conv2D."""
def __init__(self, number, name, units, n_units_prev... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Dense:
"""Dense (fully-connected) layer. Each units recieves (weighted) input from all units in the previous layer. These are the layers used in a multilayer perceptron. NOTE: Units are spatially arranged in 1D only - no 2D like Conv2D."""
def __init__(self, number, name, units, n_units_prev_layer, wt_sc... | the_stack_v2_python_sparse | CNN and Optimizer/layer.py | luhangsnn/neuralnetworks | train | 0 |
f2236117e4e9c1f865190bc568386c39a03b83b4 | [
"if not root:\n return ''\nstack = [root]\nans = []\nwhile stack:\n node = stack.pop()\n ans.append(str(node.val))\n if node.right:\n stack.append(node.right)\n if node.left:\n stack.append(node.left)\nreturn ','.join(ans)",
"if not data:\n return None\ndata = data.split(',')\nroot... | <|body_start_0|>
if not root:
return ''
stack = [root]
ans = []
while stack:
node = stack.pop()
ans.append(str(node.val))
if node.right:
stack.append(node.right)
if node.left:
stack.append(node.le... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_005803 | 1,684 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_039385 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 5e09a5d36ac55d782628a888ad57d48e234b61ac | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
stack = [root]
ans = []
while stack:
node = stack.pop()
ans.append(str(node.val))
if node.r... | the_stack_v2_python_sparse | 449/449.py | sjzyjc/leetcode | train | 0 | |
4ab08eb130502f424c6fe02c1518230a553f56e9 | [
"self.numberClasses = numberClasses\nbatchSize = BATCH_SIZE\nprint('args!!!')\nprint(args)\nif args != []:\n batchSize = args.batch_size\n'\\n Data augmentation\\n transforms.RandomRotation(30),\\n transforms.RandomResizedCrop(224),\\n transforms.RandomHorizontalFlip()\\n INPUT... | <|body_start_0|>
self.numberClasses = numberClasses
batchSize = BATCH_SIZE
print('args!!!')
print(args)
if args != []:
batchSize = args.batch_size
'\n Data augmentation\n transforms.RandomRotation(30),\n transforms.RandomResizedCrop(224),\... | ModelManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelManager:
def loadData(self, numberClasses, args=[], kwargs=[]):
"""Creates the dataset loaders :param args, console argument names :param kwargs, data arguments :return training and test dataset loaders"""
<|body_0|>
def createModel(self, args, device):
"""Creat... | stack_v2_sparse_classes_75kplus_train_005804 | 7,833 | no_license | [
{
"docstring": "Creates the dataset loaders :param args, console argument names :param kwargs, data arguments :return training and test dataset loaders",
"name": "loadData",
"signature": "def loadData(self, numberClasses, args=[], kwargs=[])"
},
{
"docstring": "Creates the model, its optimizer w... | 4 | stack_v2_sparse_classes_30k_train_014706 | Implement the Python class `ModelManager` described below.
Class description:
Implement the ModelManager class.
Method signatures and docstrings:
- def loadData(self, numberClasses, args=[], kwargs=[]): Creates the dataset loaders :param args, console argument names :param kwargs, data arguments :return training and ... | Implement the Python class `ModelManager` described below.
Class description:
Implement the ModelManager class.
Method signatures and docstrings:
- def loadData(self, numberClasses, args=[], kwargs=[]): Creates the dataset loaders :param args, console argument names :param kwargs, data arguments :return training and ... | 2b9baa62c370feac0808212efe6b22295ae31044 | <|skeleton|>
class ModelManager:
def loadData(self, numberClasses, args=[], kwargs=[]):
"""Creates the dataset loaders :param args, console argument names :param kwargs, data arguments :return training and test dataset loaders"""
<|body_0|>
def createModel(self, args, device):
"""Creat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModelManager:
def loadData(self, numberClasses, args=[], kwargs=[]):
"""Creates the dataset loaders :param args, console argument names :param kwargs, data arguments :return training and test dataset loaders"""
self.numberClasses = numberClasses
batchSize = BATCH_SIZE
print('ar... | the_stack_v2_python_sparse | Src_unsharp_preprocessing/ModelManagerTemp.py | saul1917/PhD | train | 1 | |
1755ba81b0f11d4d4130ceff0b6418d46da612a9 | [
"import da.lwc.file\nfilepath_design_document = '/package/module.py'\nfilepath_test = '/package/spec/spec_module.py'\nassert da.lwc.file.specification_filepath_for(filepath_design_document) == filepath_test",
"import da.lwc.file\nfilepath_design_document = '/package/__init__.py'\nfilepath_test = '/package/spec/sp... | <|body_start_0|>
import da.lwc.file
filepath_design_document = '/package/module.py'
filepath_test = '/package/spec/spec_module.py'
assert da.lwc.file.specification_filepath_for(filepath_design_document) == filepath_test
<|end_body_0|>
<|body_start_1|>
import da.lwc.file
... | Specify the specification_filepath_for() function. | SpecifySpecificationFilepathFor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecifySpecificationFilepathFor:
"""Specify the specification_filepath_for() function."""
def it_returns_a_test_path_when_given_python_module_path(self):
"""When given a module path, the corresponding spec path is returned. When given a valid module path, the get_specification_filepa... | stack_v2_sparse_classes_75kplus_train_005805 | 16,001 | permissive | [
{
"docstring": "When given a module path, the corresponding spec path is returned. When given a valid module path, the get_specification_filepath_for() function shall return the specification path that corresponds to the path provided.",
"name": "it_returns_a_test_path_when_given_python_module_path",
"s... | 3 | null | Implement the Python class `SpecifySpecificationFilepathFor` described below.
Class description:
Specify the specification_filepath_for() function.
Method signatures and docstrings:
- def it_returns_a_test_path_when_given_python_module_path(self): When given a module path, the corresponding spec path is returned. Whe... | Implement the Python class `SpecifySpecificationFilepathFor` described below.
Class description:
Specify the specification_filepath_for() function.
Method signatures and docstrings:
- def it_returns_a_test_path_when_given_python_module_path(self): When given a module path, the corresponding spec path is returned. Whe... | 04a13be2792323e3f9fdb83fd236a8e9cfe6aa2d | <|skeleton|>
class SpecifySpecificationFilepathFor:
"""Specify the specification_filepath_for() function."""
def it_returns_a_test_path_when_given_python_module_path(self):
"""When given a module path, the corresponding spec path is returned. When given a valid module path, the get_specification_filepa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpecifySpecificationFilepathFor:
"""Specify the specification_filepath_for() function."""
def it_returns_a_test_path_when_given_python_module_path(self):
"""When given a module path, the corresponding spec path is returned. When given a valid module path, the get_specification_filepath_for() func... | the_stack_v2_python_sparse | a3_src/h70_internal/da/lwc/spec/spec_file.py | wtpayne/hiai | train | 5 |
d467144b4b77c2d0c68fea639717ee5482a85bdb | [
"self.container = container\nself.search_manager = self.container.search.manager\nself.search_parser = self.container.search_parser\nself.link_manager = self.container.link_manager\nself.resource_id = self.container.resource_identity\nself.schema_validator = self.container.schema_validator",
"search_path = '{0}={... | <|body_start_0|>
self.container = container
self.search_manager = self.container.search.manager
self.search_parser = self.container.search_parser
self.link_manager = self.container.link_manager
self.resource_id = self.container.resource_identity
self.schema_validator = se... | This class is the link between the request/view and the search layer. | SearchPortal | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchPortal:
"""This class is the link between the request/view and the search layer."""
def __init__(self, container):
"""Args: container(shelf.container.Container)"""
<|body_0|>
def search(self, criteria):
"""Searches based on criteria defined in request and a... | stack_v2_sparse_classes_75kplus_train_005806 | 2,410 | permissive | [
{
"docstring": "Args: container(shelf.container.Container)",
"name": "__init__",
"signature": "def __init__(self, container)"
},
{
"docstring": "Searches based on criteria defined in request and assigns links to response for each search hit. Args: criteria(schemas/search-request-criteria.json): ... | 3 | null | Implement the Python class `SearchPortal` described below.
Class description:
This class is the link between the request/view and the search layer.
Method signatures and docstrings:
- def __init__(self, container): Args: container(shelf.container.Container)
- def search(self, criteria): Searches based on criteria def... | Implement the Python class `SearchPortal` described below.
Class description:
This class is the link between the request/view and the search layer.
Method signatures and docstrings:
- def __init__(self, container): Args: container(shelf.container.Container)
- def search(self, criteria): Searches based on criteria def... | ea59703082402ad3b6454482f0487418295fbd19 | <|skeleton|>
class SearchPortal:
"""This class is the link between the request/view and the search layer."""
def __init__(self, container):
"""Args: container(shelf.container.Container)"""
<|body_0|>
def search(self, criteria):
"""Searches based on criteria defined in request and a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SearchPortal:
"""This class is the link between the request/view and the search layer."""
def __init__(self, container):
"""Args: container(shelf.container.Container)"""
self.container = container
self.search_manager = self.container.search.manager
self.search_parser = sel... | the_stack_v2_python_sparse | shelf/search_portal.py | bfilipov/shelf | train | 0 |
ad6b7a7363ac09990de09c4bac0707880a081c8a | [
"if not kwargs.get('zero_based_index', True):\n start = max(start - 1, 0)\n if end:\n end -= 1\n if pages:\n pages = [i - 1 for i in pages]\ncv = Converter(pdf_file)\ncv.convert(docx_file, start, end, pages, kwargs)\ncv.close()",
"if not kwargs.get('zero_based_index', True):\n page_index... | <|body_start_0|>
if not kwargs.get('zero_based_index', True):
start = max(start - 1, 0)
if end:
end -= 1
if pages:
pages = [i - 1 for i in pages]
cv = Converter(pdf_file)
cv.convert(docx_file, start, end, pages, kwargs)
... | Command line interface for ``pdf2docx``. | PDF2DOCX | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PDF2DOCX:
"""Command line interface for ``pdf2docx``."""
def convert(pdf_file: str, docx_file: str=None, start: int=0, end: int=None, pages: list=None, **kwargs):
"""Convert pdf file to docx file. Args: pdf_file (str) : PDF filename to read from. docx_file (str, optional): docx filen... | stack_v2_sparse_classes_75kplus_train_005807 | 3,158 | permissive | [
{
"docstring": "Convert pdf file to docx file. Args: pdf_file (str) : PDF filename to read from. docx_file (str, optional): docx filename to write to. Defaults to None. start (int, optional): First page to process. Defaults to 0. end (int, optional): Last page to process. Defaults to None. pages (list, optional... | 3 | stack_v2_sparse_classes_30k_train_016788 | Implement the Python class `PDF2DOCX` described below.
Class description:
Command line interface for ``pdf2docx``.
Method signatures and docstrings:
- def convert(pdf_file: str, docx_file: str=None, start: int=0, end: int=None, pages: list=None, **kwargs): Convert pdf file to docx file. Args: pdf_file (str) : PDF fil... | Implement the Python class `PDF2DOCX` described below.
Class description:
Command line interface for ``pdf2docx``.
Method signatures and docstrings:
- def convert(pdf_file: str, docx_file: str=None, start: int=0, end: int=None, pages: list=None, **kwargs): Convert pdf file to docx file. Args: pdf_file (str) : PDF fil... | 13cdbaa8acef8e1140e419ac488eb6f18d4ca6d5 | <|skeleton|>
class PDF2DOCX:
"""Command line interface for ``pdf2docx``."""
def convert(pdf_file: str, docx_file: str=None, start: int=0, end: int=None, pages: list=None, **kwargs):
"""Convert pdf file to docx file. Args: pdf_file (str) : PDF filename to read from. docx_file (str, optional): docx filen... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PDF2DOCX:
"""Command line interface for ``pdf2docx``."""
def convert(pdf_file: str, docx_file: str=None, start: int=0, end: int=None, pages: list=None, **kwargs):
"""Convert pdf file to docx file. Args: pdf_file (str) : PDF filename to read from. docx_file (str, optional): docx filename to write ... | the_stack_v2_python_sparse | CustomPdf2Docx/CustomPdf2Docx.py | ikdk5596/pdf_translate | train | 0 |
e9c32f36a1365b4dfbe8c593f8d51cfe54fcedf0 | [
"if widget.currentIndex() == -1:\n return None\nelse:\n return widget.itemText(widget.currentIndex())",
"idx = widget.findText(value)\nif idx == -1:\n if value is not None:\n raise ValueError(\"Cannot find text '{0}' in combo box\".format(value))\nwidget.setCurrentIndex(idx)"
] | <|body_start_0|>
if widget.currentIndex() == -1:
return None
else:
return widget.itemText(widget.currentIndex())
<|end_body_0|>
<|body_start_1|>
idx = widget.findText(value)
if idx == -1:
if value is not None:
raise ValueError("Cannot ... | Wrapper around the text in QComboBox. | CurrentComboTextProperty | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CurrentComboTextProperty:
"""Wrapper around the text in QComboBox."""
def getter(self, widget):
"""Return the itemData stored in the currently-selected item"""
<|body_0|>
def setter(self, widget, value):
"""Update the currently selected item to the one which stor... | stack_v2_sparse_classes_75kplus_train_005808 | 8,602 | permissive | [
{
"docstring": "Return the itemData stored in the currently-selected item",
"name": "getter",
"signature": "def getter(self, widget)"
},
{
"docstring": "Update the currently selected item to the one which stores value in its itemData",
"name": "setter",
"signature": "def setter(self, wid... | 2 | stack_v2_sparse_classes_30k_train_001785 | Implement the Python class `CurrentComboTextProperty` described below.
Class description:
Wrapper around the text in QComboBox.
Method signatures and docstrings:
- def getter(self, widget): Return the itemData stored in the currently-selected item
- def setter(self, widget, value): Update the currently selected item ... | Implement the Python class `CurrentComboTextProperty` described below.
Class description:
Wrapper around the text in QComboBox.
Method signatures and docstrings:
- def getter(self, widget): Return the itemData stored in the currently-selected item
- def setter(self, widget, value): Update the currently selected item ... | 4aa8c64a6f65629207e40df9963232473a24c9f6 | <|skeleton|>
class CurrentComboTextProperty:
"""Wrapper around the text in QComboBox."""
def getter(self, widget):
"""Return the itemData stored in the currently-selected item"""
<|body_0|>
def setter(self, widget, value):
"""Update the currently selected item to the one which stor... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CurrentComboTextProperty:
"""Wrapper around the text in QComboBox."""
def getter(self, widget):
"""Return the itemData stored in the currently-selected item"""
if widget.currentIndex() == -1:
return None
else:
return widget.itemText(widget.currentIndex())
... | the_stack_v2_python_sparse | glue/utils/qt/widget_properties.py | astrofrog/glue | train | 3 |
14875b035d162cb3559054657267b1b5387fdd7a | [
"index = template.find(COURSE_EMAIL_MESSAGE_BODY_TAG)\nif index < 0:\n msg = f'Missing tag: \"{COURSE_EMAIL_MESSAGE_BODY_TAG}\"'\n log.warning(msg)\n raise ValidationError(msg)\nif template.find(COURSE_EMAIL_MESSAGE_BODY_TAG, index + 1) >= 0:\n msg = f'Multiple instances of tag: \"{COURSE_EMAIL_MESSAGE_... | <|body_start_0|>
index = template.find(COURSE_EMAIL_MESSAGE_BODY_TAG)
if index < 0:
msg = f'Missing tag: "{COURSE_EMAIL_MESSAGE_BODY_TAG}"'
log.warning(msg)
raise ValidationError(msg)
if template.find(COURSE_EMAIL_MESSAGE_BODY_TAG, index + 1) >= 0:
... | Form providing validation of CourseEmail templates. | CourseEmailTemplateForm | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CourseEmailTemplateForm:
"""Form providing validation of CourseEmail templates."""
def _validate_template(self, template):
"""Check the template for required tags."""
<|body_0|>
def clean_html_template(self):
"""Validate the HTML template."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_005809 | 3,011 | permissive | [
{
"docstring": "Check the template for required tags.",
"name": "_validate_template",
"signature": "def _validate_template(self, template)"
},
{
"docstring": "Validate the HTML template.",
"name": "clean_html_template",
"signature": "def clean_html_template(self)"
},
{
"docstring... | 4 | null | Implement the Python class `CourseEmailTemplateForm` described below.
Class description:
Form providing validation of CourseEmail templates.
Method signatures and docstrings:
- def _validate_template(self, template): Check the template for required tags.
- def clean_html_template(self): Validate the HTML template.
- ... | Implement the Python class `CourseEmailTemplateForm` described below.
Class description:
Form providing validation of CourseEmail templates.
Method signatures and docstrings:
- def _validate_template(self, template): Check the template for required tags.
- def clean_html_template(self): Validate the HTML template.
- ... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class CourseEmailTemplateForm:
"""Form providing validation of CourseEmail templates."""
def _validate_template(self, template):
"""Check the template for required tags."""
<|body_0|>
def clean_html_template(self):
"""Validate the HTML template."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CourseEmailTemplateForm:
"""Form providing validation of CourseEmail templates."""
def _validate_template(self, template):
"""Check the template for required tags."""
index = template.find(COURSE_EMAIL_MESSAGE_BODY_TAG)
if index < 0:
msg = f'Missing tag: "{COURSE_EMAIL... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/lms/djangoapps/bulk_email/forms.py | luque/better-ways-of-thinking-about-software | train | 3 |
c5c28dce8de151c3539f901e0cf23a30b8b4cc02 | [
"self.access_token = options.get('access_token')\nif self.access_token is None:\n self.authorization_code = options.get('authorization_code')\nself.client_secret = options.get('client_secret')\nself.base_url = options['base_url'] if 'base_url' in options else 'https://api.fortnox.se'\nself.timeout = options['tim... | <|body_start_0|>
self.access_token = options.get('access_token')
if self.access_token is None:
self.authorization_code = options.get('authorization_code')
self.client_secret = options.get('client_secret')
self.base_url = options['base_url'] if 'base_url' in options else 'http... | Base CRM client configuration :class:`Configuration <Configuration>` object. Used by :class:`HttpClient <HttpClient>` to send requests to Fortnox's servers. | Configuration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Configuration:
"""Base CRM client configuration :class:`Configuration <Configuration>` object. Used by :class:`HttpClient <HttpClient>` to send requests to Fortnox's servers."""
def __init__(self, **options):
""":param str access_token: Personal access token. :param str base_url: (op... | stack_v2_sparse_classes_75kplus_train_005810 | 3,332 | permissive | [
{
"docstring": ":param str access_token: Personal access token. :param str base_url: (optional) Base url for the api. Default: ``https://api.fortnox.se``. :param bool verbose: (optional) Verbose/debug mode. Default: ``False``. :param int timeout: (optional) Connection and response timeout. Default: **30** secon... | 2 | null | Implement the Python class `Configuration` described below.
Class description:
Base CRM client configuration :class:`Configuration <Configuration>` object. Used by :class:`HttpClient <HttpClient>` to send requests to Fortnox's servers.
Method signatures and docstrings:
- def __init__(self, **options): :param str acce... | Implement the Python class `Configuration` described below.
Class description:
Base CRM client configuration :class:`Configuration <Configuration>` object. Used by :class:`HttpClient <HttpClient>` to send requests to Fortnox's servers.
Method signatures and docstrings:
- def __init__(self, **options): :param str acce... | 4d4fcfea09c5665350240770a773e326f43ad23d | <|skeleton|>
class Configuration:
"""Base CRM client configuration :class:`Configuration <Configuration>` object. Used by :class:`HttpClient <HttpClient>` to send requests to Fortnox's servers."""
def __init__(self, **options):
""":param str access_token: Personal access token. :param str base_url: (op... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Configuration:
"""Base CRM client configuration :class:`Configuration <Configuration>` object. Used by :class:`HttpClient <HttpClient>` to send requests to Fortnox's servers."""
def __init__(self, **options):
""":param str access_token: Personal access token. :param str base_url: (optional) Base ... | the_stack_v2_python_sparse | fortnox/configuration.py | xalien10/pyfortnox | train | 21 |
fd854992638f09ffa09dc0e18bee2ecd95db20d1 | [
"print(f'{Fore.YELLOW}SERVICES CHECK FOR {Env.environment} ENVIRONMENT STARTS:{Fore.RESET}')\nservice_check = TestService.test_service_runner()\nprint('*************************************************************')\nprint()\nif service_check:\n cls.test_suite_runner()\nelse:\n Tenv.overall_result = 'FAIL!'",... | <|body_start_0|>
print(f'{Fore.YELLOW}SERVICES CHECK FOR {Env.environment} ENVIRONMENT STARTS:{Fore.RESET}')
service_check = TestService.test_service_runner()
print('*************************************************************')
print()
if service_check:
cls.test_sui... | This class handles running of Test Suite for particular sport and entity. | TestSuiteRunner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSuiteRunner:
"""This class handles running of Test Suite for particular sport and entity."""
def services_check(cls):
"""This method is starting all the Automation Test by checking of availability of all services necessary for executing particular tests. In case of all services a... | stack_v2_sparse_classes_75kplus_train_005811 | 3,229 | no_license | [
{
"docstring": "This method is starting all the Automation Test by checking of availability of all services necessary for executing particular tests. In case of all services are available, testing starts by calling test_suite_runner method. In case of some service is unavailable, test running are cancelled.",
... | 2 | stack_v2_sparse_classes_30k_train_006750 | Implement the Python class `TestSuiteRunner` described below.
Class description:
This class handles running of Test Suite for particular sport and entity.
Method signatures and docstrings:
- def services_check(cls): This method is starting all the Automation Test by checking of availability of all services necessary ... | Implement the Python class `TestSuiteRunner` described below.
Class description:
This class handles running of Test Suite for particular sport and entity.
Method signatures and docstrings:
- def services_check(cls): This method is starting all the Automation Test by checking of availability of all services necessary ... | f5d3483bd40610bbbe241c81067101efcc4932ad | <|skeleton|>
class TestSuiteRunner:
"""This class handles running of Test Suite for particular sport and entity."""
def services_check(cls):
"""This method is starting all the Automation Test by checking of availability of all services necessary for executing particular tests. In case of all services a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestSuiteRunner:
"""This class handles running of Test Suite for particular sport and entity."""
def services_check(cls):
"""This method is starting all the Automation Test by checking of availability of all services necessary for executing particular tests. In case of all services are available,... | the_stack_v2_python_sparse | src/TestSuiteRunner.py | PeterAugustinak/frontend-auto-test-sample-project | train | 0 |
653d0e56877183e3b3e47cb2230dc65a5d0e150e | [
"scrolled.ScrolledPanel.__init__(self, parent, -1, size=(100, 500))\nself.visualizer = visualizer\nself.mode = mode\nself.sizer = wx.GridBagSizer()\nself.projectionBox = wx.RadioBox(self, -1, 'View projection', choices=['Max. IP', 'Avg. IP'], majorDimension=1, style=wx.RA_SPECIFY_COLS)\nself.updateButton = wx.Butto... | <|body_start_0|>
scrolled.ScrolledPanel.__init__(self, parent, -1, size=(100, 500))
self.visualizer = visualizer
self.mode = mode
self.sizer = wx.GridBagSizer()
self.projectionBox = wx.RadioBox(self, -1, 'View projection', choices=['Max. IP', 'Avg. IP'], majorDimension=1, style=w... | A configuration panel for the projection view | SimpleConfigurationPanel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleConfigurationPanel:
"""A configuration panel for the projection view"""
def __init__(self, parent, visualizer, mode, **kws):
"""Initialization"""
<|body_0|>
def onSetProjectionMode(self, event):
"""Configure what projection to show"""
<|body_1|>
<|... | stack_v2_sparse_classes_75kplus_train_005812 | 6,623 | no_license | [
{
"docstring": "Initialization",
"name": "__init__",
"signature": "def __init__(self, parent, visualizer, mode, **kws)"
},
{
"docstring": "Configure what projection to show",
"name": "onSetProjectionMode",
"signature": "def onSetProjectionMode(self, event)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005298 | Implement the Python class `SimpleConfigurationPanel` described below.
Class description:
A configuration panel for the projection view
Method signatures and docstrings:
- def __init__(self, parent, visualizer, mode, **kws): Initialization
- def onSetProjectionMode(self, event): Configure what projection to show | Implement the Python class `SimpleConfigurationPanel` described below.
Class description:
A configuration panel for the projection view
Method signatures and docstrings:
- def __init__(self, parent, visualizer, mode, **kws): Initialization
- def onSetProjectionMode(self, event): Configure what projection to show
<|s... | ea8bafa073de5090bd8f83fb4f5ca16669d0211f | <|skeleton|>
class SimpleConfigurationPanel:
"""A configuration panel for the projection view"""
def __init__(self, parent, visualizer, mode, **kws):
"""Initialization"""
<|body_0|>
def onSetProjectionMode(self, event):
"""Configure what projection to show"""
<|body_1|>
<|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleConfigurationPanel:
"""A configuration panel for the projection view"""
def __init__(self, parent, visualizer, mode, **kws):
"""Initialization"""
scrolled.ScrolledPanel.__init__(self, parent, -1, size=(100, 500))
self.visualizer = visualizer
self.mode = mode
... | the_stack_v2_python_sparse | Graphs/LX-2/molecule_otsu = False/BioImageXD-1.0/Modules/Visualization/Simple.py | giacomo21/Image-analysis | train | 1 |
f9aa7f112d4cae5ee007ed15c67de5ef4b735bdc | [
"from cupy.cuda import nccl\nsuper(CustomParallelUpdater, self).__init__(train_iters, optimizer, converter=converter, devices=devices)\nself.accum_grad = accum_grad\nself.forward_count = 0\nself.nccl = nccl\nlogging.debug('using custom parallel updater for transformer')",
"self.setup_workers()\nself._send_message... | <|body_start_0|>
from cupy.cuda import nccl
super(CustomParallelUpdater, self).__init__(train_iters, optimizer, converter=converter, devices=devices)
self.accum_grad = accum_grad
self.forward_count = 0
self.nccl = nccl
logging.debug('using custom parallel updater for tran... | Custom Parallel Updater for chainer. Defines the main update routine. Args: train_iter (iterator | dict[str, iterator]): Dataset iterator for the training dataset. It can also be a dictionary that maps strings to iterators. If this is just an iterator, then the iterator is registered by the name ``'main'``. optimizer (... | CustomParallelUpdater | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomParallelUpdater:
"""Custom Parallel Updater for chainer. Defines the main update routine. Args: train_iter (iterator | dict[str, iterator]): Dataset iterator for the training dataset. It can also be a dictionary that maps strings to iterators. If this is just an iterator, then the iterator ... | stack_v2_sparse_classes_75kplus_train_005813 | 11,798 | permissive | [
{
"docstring": "Initialize custom parallel updater.",
"name": "__init__",
"signature": "def __init__(self, train_iters, optimizer, converter, devices, accum_grad=1)"
},
{
"docstring": "Process main update routine for Custom Parallel Updater.",
"name": "update_core",
"signature": "def upd... | 3 | stack_v2_sparse_classes_30k_train_036964 | Implement the Python class `CustomParallelUpdater` described below.
Class description:
Custom Parallel Updater for chainer. Defines the main update routine. Args: train_iter (iterator | dict[str, iterator]): Dataset iterator for the training dataset. It can also be a dictionary that maps strings to iterators. If this ... | Implement the Python class `CustomParallelUpdater` described below.
Class description:
Custom Parallel Updater for chainer. Defines the main update routine. Args: train_iter (iterator | dict[str, iterator]): Dataset iterator for the training dataset. It can also be a dictionary that maps strings to iterators. If this ... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class CustomParallelUpdater:
"""Custom Parallel Updater for chainer. Defines the main update routine. Args: train_iter (iterator | dict[str, iterator]): Dataset iterator for the training dataset. It can also be a dictionary that maps strings to iterators. If this is just an iterator, then the iterator ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomParallelUpdater:
"""Custom Parallel Updater for chainer. Defines the main update routine. Args: train_iter (iterator | dict[str, iterator]): Dataset iterator for the training dataset. It can also be a dictionary that maps strings to iterators. If this is just an iterator, then the iterator is registered... | the_stack_v2_python_sparse | espnet/nets/chainer_backend/transformer/training.py | espnet/espnet | train | 7,242 |
8fb476bf92308c545637b83d705c1e155ddd018b | [
"self.grid_size = n\nself.grid = []\nfor i in range(n):\n row = [0] * n\n self.grid.append(row)\nself.init_animals(prey_count, predator_count)",
"if 0 <= x < self.grid_size and 0 <= y < self.grid_size:\n return self.grid[x][y]\nelse:\n return -1",
"count = 0\nwhile count < prey_count:\n x = rando... | <|body_start_0|>
self.grid_size = n
self.grid = []
for i in range(n):
row = [0] * n
self.grid.append(row)
self.init_animals(prey_count, predator_count)
<|end_body_0|>
<|body_start_1|>
if 0 <= x < self.grid_size and 0 <= y < self.grid_size:
ret... | Island | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Island:
def __init__(self, n, prey_count=0, predator_count=0):
"""Initialize grid to all 0s, then fill with animals"""
<|body_0|>
def animal(self, x, y):
"""Return animal at location (x,y)"""
<|body_1|>
def init_animals(self, prey_count, predator_count):... | stack_v2_sparse_classes_75kplus_train_005814 | 1,591 | no_license | [
{
"docstring": "Initialize grid to all 0s, then fill with animals",
"name": "__init__",
"signature": "def __init__(self, n, prey_count=0, predator_count=0)"
},
{
"docstring": "Return animal at location (x,y)",
"name": "animal",
"signature": "def animal(self, x, y)"
},
{
"docstrin... | 3 | null | Implement the Python class `Island` described below.
Class description:
Implement the Island class.
Method signatures and docstrings:
- def __init__(self, n, prey_count=0, predator_count=0): Initialize grid to all 0s, then fill with animals
- def animal(self, x, y): Return animal at location (x,y)
- def init_animals(... | Implement the Python class `Island` described below.
Class description:
Implement the Island class.
Method signatures and docstrings:
- def __init__(self, n, prey_count=0, predator_count=0): Initialize grid to all 0s, then fill with animals
- def animal(self, x, y): Return animal at location (x,y)
- def init_animals(... | 28fd3c344c49d004e20322e8d33b1f0bfec38e0c | <|skeleton|>
class Island:
def __init__(self, n, prey_count=0, predator_count=0):
"""Initialize grid to all 0s, then fill with animals"""
<|body_0|>
def animal(self, x, y):
"""Return animal at location (x,y)"""
<|body_1|>
def init_animals(self, prey_count, predator_count):... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Island:
def __init__(self, n, prey_count=0, predator_count=0):
"""Initialize grid to all 0s, then fill with animals"""
self.grid_size = n
self.grid = []
for i in range(n):
row = [0] * n
self.grid.append(row)
self.init_animals(prey_count, predator... | the_stack_v2_python_sparse | ch13/codeListing13-5.py | oilmcut2019/Teaching_material_python | train | 0 | |
25c42d4b23294fbd3df79e038134f53debdec550 | [
"name = clean_name(name)\ndistrict = clean_string(district).replace('&', 'and')\nrole = clean_string(role)\nif role == 'City Councillor':\n role = 'Councillor'\nfor k, v in kwargs.items():\n if isinstance(v, str):\n kwargs[k] = clean_string(v)\nif not district:\n raise Exception('No district')\nsupe... | <|body_start_0|>
name = clean_name(name)
district = clean_string(district).replace('&', 'and')
role = clean_string(role)
if role == 'City Councillor':
role = 'Councillor'
for k, v in kwargs.items():
if isinstance(v, str):
kwargs[k] = clean_... | CanadianPerson | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CanadianPerson:
def __init__(self, *, name, district, role, **kwargs):
"""Cleans a person's name, district, role and any other attributes."""
<|body_0|>
def __setattr__(self, name, value):
"""Corrects gender values."""
<|body_1|>
def add_link(self, url, ... | stack_v2_sparse_classes_75kplus_train_005815 | 27,455 | permissive | [
{
"docstring": "Cleans a person's name, district, role and any other attributes.",
"name": "__init__",
"signature": "def __init__(self, *, name, district, role, **kwargs)"
},
{
"docstring": "Corrects gender values.",
"name": "__setattr__",
"signature": "def __setattr__(self, name, value)... | 6 | stack_v2_sparse_classes_30k_train_007131 | Implement the Python class `CanadianPerson` described below.
Class description:
Implement the CanadianPerson class.
Method signatures and docstrings:
- def __init__(self, *, name, district, role, **kwargs): Cleans a person's name, district, role and any other attributes.
- def __setattr__(self, name, value): Corrects... | Implement the Python class `CanadianPerson` described below.
Class description:
Implement the CanadianPerson class.
Method signatures and docstrings:
- def __init__(self, *, name, district, role, **kwargs): Cleans a person's name, district, role and any other attributes.
- def __setattr__(self, name, value): Corrects... | ef7bd9990e2a31c731d3bd1e7c2616fbfa7f2882 | <|skeleton|>
class CanadianPerson:
def __init__(self, *, name, district, role, **kwargs):
"""Cleans a person's name, district, role and any other attributes."""
<|body_0|>
def __setattr__(self, name, value):
"""Corrects gender values."""
<|body_1|>
def add_link(self, url, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CanadianPerson:
def __init__(self, *, name, district, role, **kwargs):
"""Cleans a person's name, district, role and any other attributes."""
name = clean_name(name)
district = clean_string(district).replace('&', 'and')
role = clean_string(role)
if role == 'City Council... | the_stack_v2_python_sparse | utils.py | opencivicdata/scrapers-ca | train | 21 | |
615790fe38c460aae7f01acb5e9e111d9a8b05aa | [
"self.titulo = titulo\nself.autores = autores\nself.editor = editor\nself.isbn = isbn\nself.precio = precio",
"num = 0\nfor i in range(len(self.autores)):\n num += 1\nreturn num"
] | <|body_start_0|>
self.titulo = titulo
self.autores = autores
self.editor = editor
self.isbn = isbn
self.precio = precio
<|end_body_0|>
<|body_start_1|>
num = 0
for i in range(len(self.autores)):
num += 1
return num
<|end_body_1|>
| Información acerca de un libro, incluye título, lista de autores, editorial, ISBN y precio. | Libro | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Libro:
"""Información acerca de un libro, incluye título, lista de autores, editorial, ISBN y precio."""
def __init__(self, titulo, autores, editor, isbn, precio):
"""Construtor principal con parámetros por defecto."""
<|body_0|>
def num_autores(self):
"""Método ... | stack_v2_sparse_classes_75kplus_train_005816 | 976 | no_license | [
{
"docstring": "Construtor principal con parámetros por defecto.",
"name": "__init__",
"signature": "def __init__(self, titulo, autores, editor, isbn, precio)"
},
{
"docstring": "Método que cuenta el número de autores del libro y devuelve dicho número.",
"name": "num_autores",
"signature... | 2 | stack_v2_sparse_classes_30k_train_025600 | Implement the Python class `Libro` described below.
Class description:
Información acerca de un libro, incluye título, lista de autores, editorial, ISBN y precio.
Method signatures and docstrings:
- def __init__(self, titulo, autores, editor, isbn, precio): Construtor principal con parámetros por defecto.
- def num_a... | Implement the Python class `Libro` described below.
Class description:
Información acerca de un libro, incluye título, lista de autores, editorial, ISBN y precio.
Method signatures and docstrings:
- def __init__(self, titulo, autores, editor, isbn, precio): Construtor principal con parámetros por defecto.
- def num_a... | 5b86a497a7f2337aeb9711f0500a7fc7cebc986a | <|skeleton|>
class Libro:
"""Información acerca de un libro, incluye título, lista de autores, editorial, ISBN y precio."""
def __init__(self, titulo, autores, editor, isbn, precio):
"""Construtor principal con parámetros por defecto."""
<|body_0|>
def num_autores(self):
"""Método ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Libro:
"""Información acerca de un libro, incluye título, lista de autores, editorial, ISBN y precio."""
def __init__(self, titulo, autores, editor, isbn, precio):
"""Construtor principal con parámetros por defecto."""
self.titulo = titulo
self.autores = autores
self.edito... | the_stack_v2_python_sparse | Sergey_Examen/ej3.py | 2dam-spopov/di | train | 0 |
27701991639a3d2aeeb7689fba6321c07836db99 | [
"pygame.font.init()\nbasicfont = pygame.font.Font(None, fontsize)\nself.linewidths = []\nfor x in text:\n self.texttemp = basicfont.render(x, 0, (1, 1, 1))\n self.linewidths.append(self.texttemp.get_width())\nself.imagewidth = basicfont.render(text[self.linewidths.index(max(self.linewidths))], 0, (1, 1, 1)).g... | <|body_start_0|>
pygame.font.init()
basicfont = pygame.font.Font(None, fontsize)
self.linewidths = []
for x in text:
self.texttemp = basicfont.render(x, 0, (1, 1, 1))
self.linewidths.append(self.texttemp.get_width())
self.imagewidth = basicfont.render(text... | Linesoftext | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Linesoftext:
def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None):
"""This object will create an image of text that is passed in as a list of strings. It will put a new line for each element in the list. Use its image attribute to put... | stack_v2_sparse_classes_75kplus_train_005817 | 5,935 | no_license | [
{
"docstring": "This object will create an image of text that is passed in as a list of strings. It will put a new line for each element in the list. Use its image attribute to put this text on your screen",
"name": "__init__",
"signature": "def __init__(self, text, position, xmid=False, fontsize=36, ba... | 2 | stack_v2_sparse_classes_30k_val_002057 | Implement the Python class `Linesoftext` described below.
Class description:
Implement the Linesoftext class.
Method signatures and docstrings:
- def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None): This object will create an image of text that is passed in as a ... | Implement the Python class `Linesoftext` described below.
Class description:
Implement the Linesoftext class.
Method signatures and docstrings:
- def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None): This object will create an image of text that is passed in as a ... | 3eae1428fdd30fddc66669d40b8bb0a715d5595a | <|skeleton|>
class Linesoftext:
def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None):
"""This object will create an image of text that is passed in as a list of strings. It will put a new line for each element in the list. Use its image attribute to put... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Linesoftext:
def __init__(self, text, position, xmid=False, fontsize=36, backgroundcolor=(200, 200, 200), surface=None):
"""This object will create an image of text that is passed in as a list of strings. It will put a new line for each element in the list. Use its image attribute to put this text on ... | the_stack_v2_python_sparse | General Python/Guessing_game_with_gui/pygametools.py | jbm950/personal_projects | train | 0 | |
6fdbb45f1266e953964fbe6e539a6c4880df45ff | [
"course_key, _ = _get_course_with_access(request, course_key_string)\ntry:\n cohort = cohorts.get_cohort_by_id(course_key, cohort_id)\nexcept CourseUserGroup.DoesNotExist:\n msg = 'Cohort (ID {cohort_id}) not found for {course_key_string}'.format(cohort_id=cohort_id, course_key_string=course_key_string)\n ... | <|body_start_0|>
course_key, _ = _get_course_with_access(request, course_key_string)
try:
cohort = cohorts.get_cohort_by_id(course_key, cohort_id)
except CourseUserGroup.DoesNotExist:
msg = 'Cohort (ID {cohort_id}) not found for {course_key_string}'.format(cohort_id=cohor... | **Use Cases** List users in a cohort Removes an user from a cohort. Add a user to a specific cohort. **Example Requests** GET /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users DELETE /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users/{username} POST /api/cohorts/v1/courses/{course_id}/cohorts/{co... | CohortUsers | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CohortUsers:
"""**Use Cases** List users in a cohort Removes an user from a cohort. Add a user to a specific cohort. **Example Requests** GET /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users DELETE /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users/{username} POST /api/coh... | stack_v2_sparse_classes_75kplus_train_005818 | 31,213 | permissive | [
{
"docstring": "Return the course and cohort for the given course_key_string and cohort_id.",
"name": "_get_course_and_cohort",
"signature": "def _get_course_and_cohort(self, request, course_key_string, cohort_id)"
},
{
"docstring": "Lists the users in a specific cohort.",
"name": "get",
... | 4 | stack_v2_sparse_classes_30k_train_014971 | Implement the Python class `CohortUsers` described below.
Class description:
**Use Cases** List users in a cohort Removes an user from a cohort. Add a user to a specific cohort. **Example Requests** GET /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users DELETE /api/cohorts/v1/courses/{course_id}/cohorts/{co... | Implement the Python class `CohortUsers` described below.
Class description:
**Use Cases** List users in a cohort Removes an user from a cohort. Add a user to a specific cohort. **Example Requests** GET /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users DELETE /api/cohorts/v1/courses/{course_id}/cohorts/{co... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class CohortUsers:
"""**Use Cases** List users in a cohort Removes an user from a cohort. Add a user to a specific cohort. **Example Requests** GET /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users DELETE /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users/{username} POST /api/coh... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CohortUsers:
"""**Use Cases** List users in a cohort Removes an user from a cohort. Add a user to a specific cohort. **Example Requests** GET /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users DELETE /api/cohorts/v1/courses/{course_id}/cohorts/{cohort_id}/users/{username} POST /api/cohorts/v1/cours... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/djangoapps/course_groups/views.py | luque/better-ways-of-thinking-about-software | train | 3 |
ceb4452c1d2962045cef531f5f74ea60a19c819d | [
"super(CustomBatchNormAutograd, self).__init__()\nself.n_neurons = n_neurons\nself.eps = eps\nself.params = nn.ParameterDict({'gamma': nn.Parameter(torch.ones(n_neurons)), 'beta': nn.Parameter(torch.zeros(n_neurons))})",
"_n_batch, n_neurons = input.shape\nassert n_neurons == self.n_neurons\nmean = input.mean(dim... | <|body_start_0|>
super(CustomBatchNormAutograd, self).__init__()
self.n_neurons = n_neurons
self.eps = eps
self.params = nn.ParameterDict({'gamma': nn.Parameter(torch.ones(n_neurons)), 'beta': nn.Parameter(torch.zeros(n_neurons))})
<|end_body_0|>
<|body_start_1|>
_n_batch, n_neu... | This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need to be implemented, it is dealt with by the automatic differentiation provided by PyTorch. | CustomBatchNormAutograd | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomBatchNormAutograd:
"""This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need to be implemented, it is dealt with by... | stack_v2_sparse_classes_75kplus_train_005819 | 7,737 | no_license | [
{
"docstring": "Initializes CustomBatchNormAutograd object. Args: n_neurons: int specifying the number of neurons eps: small float to be added to the variance for stability",
"name": "__init__",
"signature": "def __init__(self, n_neurons, eps=1e-05)"
},
{
"docstring": "Compute the batch normaliz... | 2 | stack_v2_sparse_classes_30k_train_013063 | Implement the Python class `CustomBatchNormAutograd` described below.
Class description:
This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need... | Implement the Python class `CustomBatchNormAutograd` described below.
Class description:
This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need... | b2cd0d67337b101f3e204e519625e1aaf3cea43b | <|skeleton|>
class CustomBatchNormAutograd:
"""This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need to be implemented, it is dealt with by... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomBatchNormAutograd:
"""This nn.module implements a custom version of the batch norm operation for MLPs. The operations called in self.forward track the history if the input tensors have the flag requires_grad set to True. The backward pass does not need to be implemented, it is dealt with by the automati... | the_stack_v2_python_sparse | assignment_1/code/custom_batchnorm.py | Ivan-Yovchev/uvadlc_practicals_2019 | train | 0 |
9397719eded0c48fd704ed1d50788d7b4fe3366e | [
"i = infos.copy()\ni['device_number'] = infos['serial_number']\ndel i['serial_number']\nreturn i",
"c = self.format_connection_infos(connection)\nc.update(settings)\ndriver = None\n'\\n try:\\n driver = driver_cls(c)\\n res = driver.connected\\n except Exception:\\n ... | <|body_start_0|>
i = infos.copy()
i['device_number'] = infos['serial_number']
del i['serial_number']
return i
<|end_body_0|>
<|body_start_1|>
c = self.format_connection_infos(connection)
c.update(settings)
driver = None
'\n try:\n driver... | Starter for ZI instruments. | ZIQCircuitStarter | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZIQCircuitStarter:
"""Starter for ZI instruments."""
def format_connection_infos(self, infos):
"""Rename serial_number to device_number."""
<|body_0|>
def check_infos(self, driver_cls, connection, settings):
"""Attempt to open the connection to the instrument."""... | stack_v2_sparse_classes_75kplus_train_005820 | 1,604 | permissive | [
{
"docstring": "Rename serial_number to device_number.",
"name": "format_connection_infos",
"signature": "def format_connection_infos(self, infos)"
},
{
"docstring": "Attempt to open the connection to the instrument.",
"name": "check_infos",
"signature": "def check_infos(self, driver_cls... | 2 | stack_v2_sparse_classes_30k_train_014287 | Implement the Python class `ZIQCircuitStarter` described below.
Class description:
Starter for ZI instruments.
Method signatures and docstrings:
- def format_connection_infos(self, infos): Rename serial_number to device_number.
- def check_infos(self, driver_cls, connection, settings): Attempt to open the connection ... | Implement the Python class `ZIQCircuitStarter` described below.
Class description:
Starter for ZI instruments.
Method signatures and docstrings:
- def format_connection_infos(self, infos): Rename serial_number to device_number.
- def check_infos(self, driver_cls, connection, settings): Attempt to open the connection ... | dedbf77062e0a8af0275f231e374867fa0342e78 | <|skeleton|>
class ZIQCircuitStarter:
"""Starter for ZI instruments."""
def format_connection_infos(self, infos):
"""Rename serial_number to device_number."""
<|body_0|>
def check_infos(self, driver_cls, connection, settings):
"""Attempt to open the connection to the instrument."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ZIQCircuitStarter:
"""Starter for ZI instruments."""
def format_connection_infos(self, infos):
"""Rename serial_number to device_number."""
i = infos.copy()
i['device_number'] = infos['serial_number']
del i['serial_number']
return i
def check_infos(self, drive... | the_stack_v2_python_sparse | exopy_qcircuits/instruments/starters/ZIQCircuitStarter.py | jerjohste/ecpy_qcircuits | train | 0 |
d4ab58c68de28b35e72a7c2a1c61603e502f909e | [
"genre = Genre.query.filter_by(id=id).first()\nif genre is None:\n return ({'message': 'Genre does not exist'}, 404)\nreturn genre_schema.dump(genre)",
"req = api.payload\ngenre = Genre.query.filter_by(id=id).first()\nif genre is None:\n return ({'message': 'Genre does not exist'}, 404)\ntry:\n edit_genr... | <|body_start_0|>
genre = Genre.query.filter_by(id=id).first()
if genre is None:
return ({'message': 'Genre does not exist'}, 404)
return genre_schema.dump(genre)
<|end_body_0|>
<|body_start_1|>
req = api.payload
genre = Genre.query.filter_by(id=id).first()
if... | SingleGenre | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleGenre:
def get(self, id):
"""Get Genre by id"""
<|body_0|>
def put(self, id):
"""Update a Genre"""
<|body_1|>
def delete(self, id):
"""Delete a Genre by id"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
genre = Genre.quer... | stack_v2_sparse_classes_75kplus_train_005821 | 3,163 | no_license | [
{
"docstring": "Get Genre by id",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Update a Genre",
"name": "put",
"signature": "def put(self, id)"
},
{
"docstring": "Delete a Genre by id",
"name": "delete",
"signature": "def delete(self, id)"
}
] | 3 | stack_v2_sparse_classes_30k_train_044598 | Implement the Python class `SingleGenre` described below.
Class description:
Implement the SingleGenre class.
Method signatures and docstrings:
- def get(self, id): Get Genre by id
- def put(self, id): Update a Genre
- def delete(self, id): Delete a Genre by id | Implement the Python class `SingleGenre` described below.
Class description:
Implement the SingleGenre class.
Method signatures and docstrings:
- def get(self, id): Get Genre by id
- def put(self, id): Update a Genre
- def delete(self, id): Delete a Genre by id
<|skeleton|>
class SingleGenre:
def get(self, id):... | ae78fff9888b0f68d9403d7f65cba086dabb3802 | <|skeleton|>
class SingleGenre:
def get(self, id):
"""Get Genre by id"""
<|body_0|>
def put(self, id):
"""Update a Genre"""
<|body_1|>
def delete(self, id):
"""Delete a Genre by id"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SingleGenre:
def get(self, id):
"""Get Genre by id"""
genre = Genre.query.filter_by(id=id).first()
if genre is None:
return ({'message': 'Genre does not exist'}, 404)
return genre_schema.dump(genre)
def put(self, id):
"""Update a Genre"""
req = ... | the_stack_v2_python_sparse | api/v1/genres.py | mythril-io/flask-api | train | 0 | |
3c5fbc0bef2154d6a23d67b22beda73d26d1aa73 | [
"super().__init__(parent)\nself.parent = parent\nself.setupUi(self)\nself.search_btn.clicked.connect(self.search_city)\nself.search_inp.setText('')",
"self.error_label.setText('')\nself.label_name.setText('')\nself.label_place.setText('')\nself.label_v1.setText('')\nself.label_v2.setText('')\nself.label_v3.setTex... | <|body_start_0|>
super().__init__(parent)
self.parent = parent
self.setupUi(self)
self.search_btn.clicked.connect(self.search_city)
self.search_inp.setText('')
<|end_body_0|>
<|body_start_1|>
self.error_label.setText('')
self.label_name.setText('')
self.l... | SearchWindow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchWindow:
def __init__(self, parent=None):
""":does: init Search Window"""
<|body_0|>
def search_city(self):
""":does: search city by name in dataframe"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init__(parent)
self.parent ... | stack_v2_sparse_classes_75kplus_train_005822 | 11,130 | no_license | [
{
"docstring": ":does: init Search Window",
"name": "__init__",
"signature": "def __init__(self, parent=None)"
},
{
"docstring": ":does: search city by name in dataframe",
"name": "search_city",
"signature": "def search_city(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_040274 | Implement the Python class `SearchWindow` described below.
Class description:
Implement the SearchWindow class.
Method signatures and docstrings:
- def __init__(self, parent=None): :does: init Search Window
- def search_city(self): :does: search city by name in dataframe | Implement the Python class `SearchWindow` described below.
Class description:
Implement the SearchWindow class.
Method signatures and docstrings:
- def __init__(self, parent=None): :does: init Search Window
- def search_city(self): :does: search city by name in dataframe
<|skeleton|>
class SearchWindow:
def __i... | 5b2e4d0b63318c4d8c32c3e546cfef84e1006eed | <|skeleton|>
class SearchWindow:
def __init__(self, parent=None):
""":does: init Search Window"""
<|body_0|>
def search_city(self):
""":does: search city by name in dataframe"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SearchWindow:
def __init__(self, parent=None):
""":does: init Search Window"""
super().__init__(parent)
self.parent = parent
self.setupUi(self)
self.search_btn.clicked.connect(self.search_city)
self.search_inp.setText('')
def search_city(self):
""":... | the_stack_v2_python_sparse | menu.py | vodovozovaliza/SmartCity | train | 0 | |
85a384044dc73fa4202517f680d806dd78db5f80 | [
"cmd = 'python3 poll_http_endpoint.py --endpoint={endpoint} --max_retries={retries} --retry_interval={retry_interval} --timeout={timeout}'.format(endpoint=endpoint, retries=retries, retry_interval=retry_interval, timeout=timeout)\nif expected_response:\n cmd += ' --expected_response=%s' % expected_response\nif e... | <|body_start_0|>
cmd = 'python3 poll_http_endpoint.py --endpoint={endpoint} --max_retries={retries} --retry_interval={retry_interval} --timeout={timeout}'.format(endpoint=endpoint, retries=retries, retry_interval=retry_interval, timeout=timeout)
if expected_response:
cmd += ' --expected_resp... | Polls http endpoint. | HttpPoller | [
"Classpath-exception-2.0",
"BSD-3-Clause",
"AGPL-3.0-only",
"MIT",
"GPL-2.0-only",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HttpPoller:
"""Polls http endpoint."""
def _BuildCommand(self, endpoint, headers, retries, retry_interval, timeout, expected_response_code, expected_response):
"""Builds command for polling script."""
<|body_0|>
def Run(self, vm, endpoint, headers=(), retries=0, retry_in... | stack_v2_sparse_classes_75kplus_train_005823 | 3,784 | permissive | [
{
"docstring": "Builds command for polling script.",
"name": "_BuildCommand",
"signature": "def _BuildCommand(self, endpoint, headers, retries, retry_interval, timeout, expected_response_code, expected_response)"
},
{
"docstring": "Polls HTTP endpoint. Args: vm: VirtualMachine object. endpoint: ... | 2 | stack_v2_sparse_classes_30k_train_035352 | Implement the Python class `HttpPoller` described below.
Class description:
Polls http endpoint.
Method signatures and docstrings:
- def _BuildCommand(self, endpoint, headers, retries, retry_interval, timeout, expected_response_code, expected_response): Builds command for polling script.
- def Run(self, vm, endpoint,... | Implement the Python class `HttpPoller` described below.
Class description:
Polls http endpoint.
Method signatures and docstrings:
- def _BuildCommand(self, endpoint, headers, retries, retry_interval, timeout, expected_response_code, expected_response): Builds command for polling script.
- def Run(self, vm, endpoint,... | d0699f32998898757b036704fba39e5471641f01 | <|skeleton|>
class HttpPoller:
"""Polls http endpoint."""
def _BuildCommand(self, endpoint, headers, retries, retry_interval, timeout, expected_response_code, expected_response):
"""Builds command for polling script."""
<|body_0|>
def Run(self, vm, endpoint, headers=(), retries=0, retry_in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HttpPoller:
"""Polls http endpoint."""
def _BuildCommand(self, endpoint, headers, retries, retry_interval, timeout, expected_response_code, expected_response):
"""Builds command for polling script."""
cmd = 'python3 poll_http_endpoint.py --endpoint={endpoint} --max_retries={retries} --ret... | the_stack_v2_python_sparse | perfkitbenchmarker/linux_packages/http_poller.py | GoogleCloudPlatform/PerfKitBenchmarker | train | 1,923 |
34c9390051b20e4ba71c6b229863dabac924e83a | [
"super(SourceLoss, self).__init__()\nself.cheaptrick = CheapTrick(sampling_rate=sampling_rate, hop_size=hop_size, fft_size=fft_size, f0_floor=f0_floor, f0_ceil=f0_ceil, uv_threshold=uv_threshold, q1=q1)\nself.loss = nn.MSELoss()",
"spectral_envelope = self.cheaptrick.forward(x, f0)\nzeros = torch.zeros_like(spect... | <|body_start_0|>
super(SourceLoss, self).__init__()
self.cheaptrick = CheapTrick(sampling_rate=sampling_rate, hop_size=hop_size, fft_size=fft_size, f0_floor=f0_floor, f0_ceil=f0_ceil, uv_threshold=uv_threshold, q1=q1)
self.loss = nn.MSELoss()
<|end_body_0|>
<|body_start_1|>
spectral_env... | SourceLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceLoss:
def __init__(self, sampling_rate, hop_size, fft_size, f0_floor, f0_ceil, uv_threshold=0, q1=-0.15):
"""Initialize source loss module. Args: fft_size (int): FFT size. hop_size (int): Hop size. win_length (int): Window length. window (str): Window function type."""
<|bo... | stack_v2_sparse_classes_75kplus_train_005824 | 1,728 | permissive | [
{
"docstring": "Initialize source loss module. Args: fft_size (int): FFT size. hop_size (int): Hop size. win_length (int): Window length. window (str): Window function type.",
"name": "__init__",
"signature": "def __init__(self, sampling_rate, hop_size, fft_size, f0_floor, f0_ceil, uv_threshold=0, q1=-0... | 2 | stack_v2_sparse_classes_30k_train_046808 | Implement the Python class `SourceLoss` described below.
Class description:
Implement the SourceLoss class.
Method signatures and docstrings:
- def __init__(self, sampling_rate, hop_size, fft_size, f0_floor, f0_ceil, uv_threshold=0, q1=-0.15): Initialize source loss module. Args: fft_size (int): FFT size. hop_size (i... | Implement the Python class `SourceLoss` described below.
Class description:
Implement the SourceLoss class.
Method signatures and docstrings:
- def __init__(self, sampling_rate, hop_size, fft_size, f0_floor, f0_ceil, uv_threshold=0, q1=-0.15): Initialize source loss module. Args: fft_size (int): FFT size. hop_size (i... | 67331ddb5d6a7227120818842c61b6e07de52ba7 | <|skeleton|>
class SourceLoss:
def __init__(self, sampling_rate, hop_size, fft_size, f0_floor, f0_ceil, uv_threshold=0, q1=-0.15):
"""Initialize source loss module. Args: fft_size (int): FFT size. hop_size (int): Hop size. win_length (int): Window length. window (str): Window function type."""
<|bo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SourceLoss:
def __init__(self, sampling_rate, hop_size, fft_size, f0_floor, f0_ceil, uv_threshold=0, q1=-0.15):
"""Initialize source loss module. Args: fft_size (int): FFT size. hop_size (int): Hop size. win_length (int): Window length. window (str): Window function type."""
super(SourceLoss, ... | the_stack_v2_python_sparse | usfgan/losses/source_loss.py | hendrikTpl/UnifiedSourceFilterGAN | train | 0 | |
a0136f176b762c86bd3915de10a5ac47cac1e8cb | [
"self.schema = generic_ast_graphs.build_ast_graph_schema(self.ast_spec)\nself.edge_types = sorted({graph_edge_util.SAME_IDENTIFIER_EDGE_TYPE, *graph_edge_util.PROGRAM_GRAPH_EDGE_TYPES, *graph_edge_util.schema_edge_types(self.schema), *graph_edge_util.nth_child_edge_types(EDGE_NTH_CHILD_MAX)})\nself.builder = automa... | <|body_start_0|>
self.schema = generic_ast_graphs.build_ast_graph_schema(self.ast_spec)
self.edge_types = sorted({graph_edge_util.SAME_IDENTIFIER_EDGE_TYPE, *graph_edge_util.PROGRAM_GRAPH_EDGE_TYPES, *graph_edge_util.schema_edge_types(self.schema), *graph_edge_util.nth_child_edge_types(EDGE_NTH_CHILD_MA... | Keeps track of objects needed to encode and decode examples. Attributes: ast_spec: AST spec defining how to encode an AST. token_encoder: Subword encoder for encoding syntax tokens. schema: Automaton schema for the produced graphs. Generated automatically. edge_types: List of all edge types produced by the encoding. Ge... | ExampleEncodingInfo | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExampleEncodingInfo:
"""Keeps track of objects needed to encode and decode examples. Attributes: ast_spec: AST spec defining how to encode an AST. token_encoder: Subword encoder for encoding syntax tokens. schema: Automaton schema for the produced graphs. Generated automatically. edge_types: List... | stack_v2_sparse_classes_75kplus_train_005825 | 8,664 | permissive | [
{
"docstring": "Populates non-init fields based on `ast_spec`.",
"name": "__post_init__",
"signature": "def __post_init__(self)"
},
{
"docstring": "Builds an ExampleEncodingInfo object from files. Args: ast_spec_path: Path to a text file containing an AST spec definition. Format is expected to b... | 2 | stack_v2_sparse_classes_30k_train_044231 | Implement the Python class `ExampleEncodingInfo` described below.
Class description:
Keeps track of objects needed to encode and decode examples. Attributes: ast_spec: AST spec defining how to encode an AST. token_encoder: Subword encoder for encoding syntax tokens. schema: Automaton schema for the produced graphs. Ge... | Implement the Python class `ExampleEncodingInfo` described below.
Class description:
Keeps track of objects needed to encode and decode examples. Attributes: ast_spec: AST spec defining how to encode an AST. token_encoder: Subword encoder for encoding syntax tokens. schema: Automaton schema for the produced graphs. Ge... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class ExampleEncodingInfo:
"""Keeps track of objects needed to encode and decode examples. Attributes: ast_spec: AST spec defining how to encode an AST. token_encoder: Subword encoder for encoding syntax tokens. schema: Automaton schema for the produced graphs. Generated automatically. edge_types: List... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExampleEncodingInfo:
"""Keeps track of objects needed to encode and decode examples. Attributes: ast_spec: AST spec defining how to encode an AST. token_encoder: Subword encoder for encoding syntax tokens. schema: Automaton schema for the produced graphs. Generated automatically. edge_types: List of all edge ... | the_stack_v2_python_sparse | gfsa/datasets/var_misuse/example_definition.py | Jimmy-INL/google-research | train | 1 |
6c7451715302ae65863d2ecf89f0e80d2682f32d | [
"super().__init__()\nself.image = pygame.Surface([15, 15])\nself.image.fill(BLUE)\nself.rect = self.image.get_rect()\nself.rect.x = x\nself.rect.y = y\nself.change_x = 0\nself.change_y = 0",
"if stop != True:\n self.change_x += w\n self.change_y += z",
"self.rect.x += self.change_x\nself.rect.y += self.ch... | <|body_start_0|>
super().__init__()
self.image = pygame.Surface([15, 15])
self.image.fill(BLUE)
self.rect = self.image.get_rect()
self.rect.x = x
self.rect.y = y
self.change_x = 0
self.change_y = 0
<|end_body_0|>
<|body_start_1|>
if stop != True:
... | The class is the player-controlled sprite. | Player | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Player:
"""The class is the player-controlled sprite."""
def __init__(self, x, y):
"""Constructor function"""
<|body_0|>
def changespeed(self, w, z, stop):
"""Change the speed of the player"""
<|body_1|>
def update(self):
"""Find a new positi... | stack_v2_sparse_classes_75kplus_train_005826 | 17,606 | no_license | [
{
"docstring": "Constructor function",
"name": "__init__",
"signature": "def __init__(self, x, y)"
},
{
"docstring": "Change the speed of the player",
"name": "changespeed",
"signature": "def changespeed(self, w, z, stop)"
},
{
"docstring": "Find a new position for the player",
... | 3 | null | Implement the Python class `Player` described below.
Class description:
The class is the player-controlled sprite.
Method signatures and docstrings:
- def __init__(self, x, y): Constructor function
- def changespeed(self, w, z, stop): Change the speed of the player
- def update(self): Find a new position for the play... | Implement the Python class `Player` described below.
Class description:
The class is the player-controlled sprite.
Method signatures and docstrings:
- def __init__(self, x, y): Constructor function
- def changespeed(self, w, z, stop): Change the speed of the player
- def update(self): Find a new position for the play... | 31aa808a5516e653a1e06dec53b4cb74bd820c00 | <|skeleton|>
class Player:
"""The class is the player-controlled sprite."""
def __init__(self, x, y):
"""Constructor function"""
<|body_0|>
def changespeed(self, w, z, stop):
"""Change the speed of the player"""
<|body_1|>
def update(self):
"""Find a new positi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Player:
"""The class is the player-controlled sprite."""
def __init__(self, x, y):
"""Constructor function"""
super().__init__()
self.image = pygame.Surface([15, 15])
self.image.fill(BLUE)
self.rect = self.image.get_rect()
self.rect.x = x
self.rect.... | the_stack_v2_python_sparse | Fa18_student_games/Alex Kick Return/TARIK.py | fwparkercode/IntroGames | train | 0 |
69f503963c93393f8ae7bea02c28b2f87b025c0d | [
"super(TowLayerNet, self).__init__()\nself.linear1 = torch.nn.Linear(D_in, H)\nself.linear2 = torch.nn.Linear(H, D_out)",
"h_relu = self.linear1(x).clamp(min=0)\ny_pred = self.linear2(h_relu)\nreturn y_pred"
] | <|body_start_0|>
super(TowLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
<|end_body_0|>
<|body_start_1|>
h_relu = self.linear1(x).clamp(min=0)
y_pred = self.linear2(h_relu)
return y_pred
<|end_body_1|>
| TowLayerNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TowLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化两个nn.Linear模块并将其分配为成员变量。"""
<|body_0|>
def forward(self, x):
"""在前向函数中，我们接受输入数据的张量，并且必须返回输出数据的张量。 我们可以使用构造函数中定义的模块以及张量中的任意运算符。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(TowL... | stack_v2_sparse_classes_75kplus_train_005827 | 2,467 | no_license | [
{
"docstring": "在构造函数中，我们实例化两个nn.Linear模块并将其分配为成员变量。",
"name": "__init__",
"signature": "def __init__(self, D_in, H, D_out)"
},
{
"docstring": "在前向函数中，我们接受输入数据的张量，并且必须返回输出数据的张量。 我们可以使用构造函数中定义的模块以及张量中的任意运算符。",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | null | Implement the Python class `TowLayerNet` described below.
Class description:
Implement the TowLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们实例化两个nn.Linear模块并将其分配为成员变量。
- def forward(self, x): 在前向函数中，我们接受输入数据的张量，并且必须返回输出数据的张量。 我们可以使用构造函数中定义的模块以及张量中的任意运算符。 | Implement the Python class `TowLayerNet` described below.
Class description:
Implement the TowLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们实例化两个nn.Linear模块并将其分配为成员变量。
- def forward(self, x): 在前向函数中，我们接受输入数据的张量，并且必须返回输出数据的张量。 我们可以使用构造函数中定义的模块以及张量中的任意运算符。
<|skeleton|... | e06596fad4c689a6d19ae6d82cd9ab3795ae307a | <|skeleton|>
class TowLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化两个nn.Linear模块并将其分配为成员变量。"""
<|body_0|>
def forward(self, x):
"""在前向函数中，我们接受输入数据的张量，并且必须返回输出数据的张量。 我们可以使用构造函数中定义的模块以及张量中的任意运算符。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TowLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化两个nn.Linear模块并将其分配为成员变量。"""
super(TowLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
def forward(self, x):
"""在前向函数中，我们接受输入数据的张量，并且必须返回输出数据的张... | the_stack_v2_python_sparse | DP_PyTorch/PyTorchTutorials/PyT1.5_5_TowLayerNet.py | SunWeiKeS/dataScience | train | 0 | |
535ad59d4610e926b0e20e227c7191559f5b5469 | [
"organization = Organization.objects.get(id=id)\nserializer = AttachmentSerializer(Organization.attachments, many=True)\nreturn Response(serializer.data)",
"jsonString = self.request.POST['item']\ndata = json.loads(jsonString)\nfile_name = request.FILES['file'].name\nfileData = request.FILES['file'].read()\norgan... | <|body_start_0|>
organization = Organization.objects.get(id=id)
serializer = AttachmentSerializer(Organization.attachments, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
jsonString = self.request.POST['item']
data = json.loads(jsonString)
fi... | Returns attachments for a particular Organization | organizationsIdAttachmentsGet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class organizationsIdAttachmentsGet:
"""Returns attachments for a particular Organization"""
def get(self, request, id):
"""Returns attachments for a particular Fuel Supplier"""
<|body_0|>
def post(self, request, id):
"""Accepts a new file upload."""
<|body_1|>... | stack_v2_sparse_classes_75kplus_train_005828 | 11,433 | permissive | [
{
"docstring": "Returns attachments for a particular Fuel Supplier",
"name": "get",
"signature": "def get(self, request, id)"
},
{
"docstring": "Accepts a new file upload.",
"name": "post",
"signature": "def post(self, request, id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014420 | Implement the Python class `organizationsIdAttachmentsGet` described below.
Class description:
Returns attachments for a particular Organization
Method signatures and docstrings:
- def get(self, request, id): Returns attachments for a particular Fuel Supplier
- def post(self, request, id): Accepts a new file upload. | Implement the Python class `organizationsIdAttachmentsGet` described below.
Class description:
Returns attachments for a particular Organization
Method signatures and docstrings:
- def get(self, request, id): Returns attachments for a particular Fuel Supplier
- def post(self, request, id): Accepts a new file upload.
... | 83e1805312d3f13c6a7235e99840b44f399c8fde | <|skeleton|>
class organizationsIdAttachmentsGet:
"""Returns attachments for a particular Organization"""
def get(self, request, id):
"""Returns attachments for a particular Fuel Supplier"""
<|body_0|>
def post(self, request, id):
"""Accepts a new file upload."""
<|body_1|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class organizationsIdAttachmentsGet:
"""Returns attachments for a particular Organization"""
def get(self, request, id):
"""Returns attachments for a particular Fuel Supplier"""
organization = Organization.objects.get(id=id)
serializer = AttachmentSerializer(Organization.attachments, ma... | the_stack_v2_python_sparse | backend/api/views_custom.py | ActionAnalytics/tfrs | train | 0 |
e639acd1c4c57d897078d5f1dd62f794007ca024 | [
"extra = extra_context or {}\nextra['SPECTATOR_MAPS'] = app_settings.MAPS\nreturn super().add_view(request, form_url, extra_context=extra)",
"extra = extra_context or {}\nextra['SPECTATOR_MAPS'] = app_settings.MAPS\nreturn super().change_view(request, object_id, form_url, extra_context=extra)"
] | <|body_start_0|>
extra = extra_context or {}
extra['SPECTATOR_MAPS'] = app_settings.MAPS
return super().add_view(request, form_url, extra_context=extra)
<|end_body_0|>
<|body_start_1|>
extra = extra_context or {}
extra['SPECTATOR_MAPS'] = app_settings.MAPS
return super()... | VenueAdmin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VenueAdmin:
def add_view(self, request, form_url='', extra_context=None):
"""Add the SPECTATOR_MAPS setting to context. Only currently needed if we're using Mapbox, because we need to set the API key in JS in the page."""
<|body_0|>
def change_view(self, request, object_id, ... | stack_v2_sparse_classes_75kplus_train_005829 | 7,693 | permissive | [
{
"docstring": "Add the SPECTATOR_MAPS setting to context. Only currently needed if we're using Mapbox, because we need to set the API key in JS in the page.",
"name": "add_view",
"signature": "def add_view(self, request, form_url='', extra_context=None)"
},
{
"docstring": "Add the SPECTATOR_MAP... | 2 | stack_v2_sparse_classes_30k_test_000010 | Implement the Python class `VenueAdmin` described below.
Class description:
Implement the VenueAdmin class.
Method signatures and docstrings:
- def add_view(self, request, form_url='', extra_context=None): Add the SPECTATOR_MAPS setting to context. Only currently needed if we're using Mapbox, because we need to set t... | Implement the Python class `VenueAdmin` described below.
Class description:
Implement the VenueAdmin class.
Method signatures and docstrings:
- def add_view(self, request, form_url='', extra_context=None): Add the SPECTATOR_MAPS setting to context. Only currently needed if we're using Mapbox, because we need to set t... | 2d89dcdb624b01452a5b6ca0ee092774fcc0aa52 | <|skeleton|>
class VenueAdmin:
def add_view(self, request, form_url='', extra_context=None):
"""Add the SPECTATOR_MAPS setting to context. Only currently needed if we're using Mapbox, because we need to set the API key in JS in the page."""
<|body_0|>
def change_view(self, request, object_id, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VenueAdmin:
def add_view(self, request, form_url='', extra_context=None):
"""Add the SPECTATOR_MAPS setting to context. Only currently needed if we're using Mapbox, because we need to set the API key in JS in the page."""
extra = extra_context or {}
extra['SPECTATOR_MAPS'] = app_settin... | the_stack_v2_python_sparse | spectator/events/admin.py | philgyford/django-spectator | train | 45 | |
509d14ccce49086d167a85c7e2e2c37960668e60 | [
"if v and isinstance(v, dict):\n return ElasticContainerRegistryRepository.parse_obj({'repo_name': v.get('repo_name'), 'registry': ElasticContainerRegistry.parse_obj({'account_id': v.get('account_id'), 'alias': v.get('registry_alias'), 'aws_region': v.get('aws_region'), 'context': values.get('context')})})\nretu... | <|body_start_0|>
if v and isinstance(v, dict):
return ElasticContainerRegistryRepository.parse_obj({'repo_name': v.get('repo_name'), 'registry': ElasticContainerRegistry.parse_obj({'account_id': v.get('account_id'), 'alias': v.get('registry_alias'), 'aws_region': v.get('aws_region'), 'context': valu... | Args passed to image.push. | ImagePushArgs | [
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImagePushArgs:
"""Args passed to image.push."""
def _set_ecr_repo(cls, v: Any, values: Dict[str, Any]) -> Any:
"""Set the value of ``ecr_repo``."""
<|body_0|>
def _set_repo(cls, v: Optional[str], values: Dict[str, Any]) -> Optional[str]:
"""Set the value of ``rep... | stack_v2_sparse_classes_75kplus_train_005830 | 3,744 | permissive | [
{
"docstring": "Set the value of ``ecr_repo``.",
"name": "_set_ecr_repo",
"signature": "def _set_ecr_repo(cls, v: Any, values: Dict[str, Any]) -> Any"
},
{
"docstring": "Set the value of ``repo``.",
"name": "_set_repo",
"signature": "def _set_repo(cls, v: Optional[str], values: Dict[str,... | 3 | stack_v2_sparse_classes_30k_train_048942 | Implement the Python class `ImagePushArgs` described below.
Class description:
Args passed to image.push.
Method signatures and docstrings:
- def _set_ecr_repo(cls, v: Any, values: Dict[str, Any]) -> Any: Set the value of ``ecr_repo``.
- def _set_repo(cls, v: Optional[str], values: Dict[str, Any]) -> Optional[str]: S... | Implement the Python class `ImagePushArgs` described below.
Class description:
Args passed to image.push.
Method signatures and docstrings:
- def _set_ecr_repo(cls, v: Any, values: Dict[str, Any]) -> Any: Set the value of ``ecr_repo``.
- def _set_repo(cls, v: Optional[str], values: Dict[str, Any]) -> Optional[str]: S... | 0763b06aee07d2cf3f037a49ca0cb81a048c5deb | <|skeleton|>
class ImagePushArgs:
"""Args passed to image.push."""
def _set_ecr_repo(cls, v: Any, values: Dict[str, Any]) -> Any:
"""Set the value of ``ecr_repo``."""
<|body_0|>
def _set_repo(cls, v: Optional[str], values: Dict[str, Any]) -> Optional[str]:
"""Set the value of ``rep... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImagePushArgs:
"""Args passed to image.push."""
def _set_ecr_repo(cls, v: Any, values: Dict[str, Any]) -> Any:
"""Set the value of ``ecr_repo``."""
if v and isinstance(v, dict):
return ElasticContainerRegistryRepository.parse_obj({'repo_name': v.get('repo_name'), 'registry': E... | the_stack_v2_python_sparse | runway/cfngin/hooks/docker/image/_push.py | onicagroup/runway | train | 156 |
907caa2a83650a1a70c7d3873e5cb5114f5cc913 | [
"self.tasks = tasks\nself.task_validation = task_validation\nself.settings = EmmetBuildSettings.autoload(settings)\nself.query = query\nself.kwargs = kwargs\nself.potcar_hashes = potcar_hashes\nif self.settings.VASP_VALIDATE_POTCAR_HASHES:\n if not self.potcar_hashes:\n from pymatgen.io.vasp.inputs import... | <|body_start_0|>
self.tasks = tasks
self.task_validation = task_validation
self.settings = EmmetBuildSettings.autoload(settings)
self.query = query
self.kwargs = kwargs
self.potcar_hashes = potcar_hashes
if self.settings.VASP_VALIDATE_POTCAR_HASHES:
if... | TaskValidator | [
"LicenseRef-scancode-hdf5",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskValidator:
def __init__(self, tasks: Store, task_validation: Store, potcar_hashes: Optional[Dict[CalcType, Dict[str, str]]]=None, settings: Optional[EmmetBuildSettings]=None, query: Optional[Dict]=None, **kwargs):
"""Creates task_types from tasks and type definitions Args: tasks: Sto... | stack_v2_sparse_classes_75kplus_train_005831 | 3,600 | permissive | [
{
"docstring": "Creates task_types from tasks and type definitions Args: tasks: Store of task documents task_validation: Store of task_types for tasks potcar_hashes: Optional dictionary of potcar hash data. Mapping is calculation type -> potcar symbol -> hash value.",
"name": "__init__",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_022774 | Implement the Python class `TaskValidator` described below.
Class description:
Implement the TaskValidator class.
Method signatures and docstrings:
- def __init__(self, tasks: Store, task_validation: Store, potcar_hashes: Optional[Dict[CalcType, Dict[str, str]]]=None, settings: Optional[EmmetBuildSettings]=None, quer... | Implement the Python class `TaskValidator` described below.
Class description:
Implement the TaskValidator class.
Method signatures and docstrings:
- def __init__(self, tasks: Store, task_validation: Store, potcar_hashes: Optional[Dict[CalcType, Dict[str, str]]]=None, settings: Optional[EmmetBuildSettings]=None, quer... | 90e121d5cf1b6b57a33233c927e1044c59354bc5 | <|skeleton|>
class TaskValidator:
def __init__(self, tasks: Store, task_validation: Store, potcar_hashes: Optional[Dict[CalcType, Dict[str, str]]]=None, settings: Optional[EmmetBuildSettings]=None, query: Optional[Dict]=None, **kwargs):
"""Creates task_types from tasks and type definitions Args: tasks: Sto... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TaskValidator:
def __init__(self, tasks: Store, task_validation: Store, potcar_hashes: Optional[Dict[CalcType, Dict[str, str]]]=None, settings: Optional[EmmetBuildSettings]=None, query: Optional[Dict]=None, **kwargs):
"""Creates task_types from tasks and type definitions Args: tasks: Store of task doc... | the_stack_v2_python_sparse | emmet-builders/emmet/builders/vasp/task_validator.py | materialsproject/emmet | train | 37 | |
af119c70a07694a998762cdd6329b3fe73841182 | [
"self.text = text\nself.th = th\nself.attrs = attrs",
"if not self.th:\n return ' <td%s>%s</td>\\n' % (attrs2str(self.attrs), self.text)\nelse:\n return ' <th%s>%s</th>\\n' % (attrs2str(self.attrs), self.text)"
] | <|body_start_0|>
self.text = text
self.th = th
self.attrs = attrs
<|end_body_0|>
<|body_start_1|>
if not self.th:
return ' <td%s>%s</td>\n' % (attrs2str(self.attrs), self.text)
else:
return ' <th%s>%s</th>\n' % (attrs2str(self.attrs), self.text)
<|end... | Предназначен для хранения информации об одной ячейке, даже несуществующей. | TableCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TableCell:
"""Предназначен для хранения информации об одной ячейке, даже несуществующей."""
def __init__(self, text=' ', th=False, attrs={}):
"""Инициализирует объект ячейки таблицы. Аргументы: text - содержимое ячейки, по умолчанию неразрывный пробел; th - Отрисовывать с помощь... | stack_v2_sparse_classes_75kplus_train_005832 | 9,419 | no_license | [
{
"docstring": "Инициализирует объект ячейки таблицы. Аргументы: text - содержимое ячейки, по умолчанию неразрывный пробел; th - Отрисовывать с помощью тега th; attrs - атрибуты, выводимые непосредственно в теге <td>/<th>,",
"name": "__init__",
"signature": "def __init__(self, text=' ', th=False, a... | 2 | stack_v2_sparse_classes_30k_train_054553 | Implement the Python class `TableCell` described below.
Class description:
Предназначен для хранения информации об одной ячейке, даже несуществующей.
Method signatures and docstrings:
- def __init__(self, text=' ', th=False, attrs={}): Инициализирует объект ячейки таблицы. Аргументы: text - содержимое ячейки, по... | Implement the Python class `TableCell` described below.
Class description:
Предназначен для хранения информации об одной ячейке, даже несуществующей.
Method signatures and docstrings:
- def __init__(self, text=' ', th=False, attrs={}): Инициализирует объект ячейки таблицы. Аргументы: text - содержимое ячейки, по... | 5f0af16ba2727faceb6b7e1b98073cd7d3c60d4c | <|skeleton|>
class TableCell:
"""Предназначен для хранения информации об одной ячейке, даже несуществующей."""
def __init__(self, text=' ', th=False, attrs={}):
"""Инициализирует объект ячейки таблицы. Аргументы: text - содержимое ячейки, по умолчанию неразрывный пробел; th - Отрисовывать с помощь... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TableCell:
"""Предназначен для хранения информации об одной ячейке, даже несуществующей."""
def __init__(self, text=' ', th=False, attrs={}):
"""Инициализирует объект ячейки таблицы. Аргументы: text - содержимое ячейки, по умолчанию неразрывный пробел; th - Отрисовывать с помощью тега th; at... | the_stack_v2_python_sparse | src/lib/Table.py | andbar-ru/traceyourself.appspot.com | train | 1 |
68f103121e26adb536b71f8abe698682ec4a691a | [
"self.event_type = event_type\nself.sources = sources\nif not isinstance(mc_info, list):\n mc_info = [mc_info]\nself.mc_info = mc_info",
"if isinstance(other, MCRecord):\n new_ev_type = self.event_type + other.event_type\n new_src = self.sources + other.sources\n new_mcinfo = self.mc_info + other.mc_i... | <|body_start_0|>
self.event_type = event_type
self.sources = sources
if not isinstance(mc_info, list):
mc_info = [mc_info]
self.mc_info = mc_info
<|end_body_0|>
<|body_start_1|>
if isinstance(other, MCRecord):
new_ev_type = self.event_type + other.event_t... | Stores MC Truth information. Properties: event_type: str sources: List[PhotonSource_] List of photon sources mc_info: List[Dict[str, Any]] List of dictionaries containing MCTruth information. | MCRecord | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MCRecord:
"""Stores MC Truth information. Properties: event_type: str sources: List[PhotonSource_] List of photon sources mc_info: List[Dict[str, Any]] List of dictionaries containing MCTruth information."""
def __init__(self, event_type, sources, mc_info):
"""Initialize MCRecord."""... | stack_v2_sparse_classes_75kplus_train_005833 | 972 | no_license | [
{
"docstring": "Initialize MCRecord.",
"name": "__init__",
"signature": "def __init__(self, event_type, sources, mc_info)"
},
{
"docstring": "Combine two MCRecords.",
"name": "__add__",
"signature": "def __add__(self, other)"
}
] | 2 | stack_v2_sparse_classes_30k_train_053312 | Implement the Python class `MCRecord` described below.
Class description:
Stores MC Truth information. Properties: event_type: str sources: List[PhotonSource_] List of photon sources mc_info: List[Dict[str, Any]] List of dictionaries containing MCTruth information.
Method signatures and docstrings:
- def __init__(sel... | Implement the Python class `MCRecord` described below.
Class description:
Stores MC Truth information. Properties: event_type: str sources: List[PhotonSource_] List of photon sources mc_info: List[Dict[str, Any]] List of dictionaries containing MCTruth information.
Method signatures and docstrings:
- def __init__(sel... | 24f847a1ab9bfe3b1bafe1a19569f13fede7f2f6 | <|skeleton|>
class MCRecord:
"""Stores MC Truth information. Properties: event_type: str sources: List[PhotonSource_] List of photon sources mc_info: List[Dict[str, Any]] List of dictionaries containing MCTruth information."""
def __init__(self, event_type, sources, mc_info):
"""Initialize MCRecord."""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MCRecord:
"""Stores MC Truth information. Properties: event_type: str sources: List[PhotonSource_] List of photon sources mc_info: List[Dict[str, Any]] List of dictionaries containing MCTruth information."""
def __init__(self, event_type, sources, mc_info):
"""Initialize MCRecord."""
self... | the_stack_v2_python_sparse | gnn_testbed/event_generation/mc_record.py | chrhck/gnn_testbed | train | 0 |
de644062d2e674f73e7c3865a69f4e5449092fc9 | [
"self.coresys: CoreSys = coresys\nself.repositories: Dict[str, Any] = {}\nself.addons: Dict[str, Any] = {}",
"self.repositories.clear()\nself.addons.clear()\nself._read_addons_folder(self.sys_config.path_addons_core, REPOSITORY_CORE)\nself._read_addons_folder(self.sys_config.path_addons_local, REPOSITORY_LOCAL)\n... | <|body_start_0|>
self.coresys: CoreSys = coresys
self.repositories: Dict[str, Any] = {}
self.addons: Dict[str, Any] = {}
<|end_body_0|>
<|body_start_1|>
self.repositories.clear()
self.addons.clear()
self._read_addons_folder(self.sys_config.path_addons_core, REPOSITORY_CO... | Hold data for Add-ons inside Supervisor. | StoreData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StoreData:
"""Hold data for Add-ons inside Supervisor."""
def __init__(self, coresys: CoreSys):
"""Initialize data holder."""
<|body_0|>
def update(self):
"""Read data from add-on repository."""
<|body_1|>
def _read_git_repository(self, path):
... | stack_v2_sparse_classes_75kplus_train_005834 | 3,860 | permissive | [
{
"docstring": "Initialize data holder.",
"name": "__init__",
"signature": "def __init__(self, coresys: CoreSys)"
},
{
"docstring": "Read data from add-on repository.",
"name": "update",
"signature": "def update(self)"
},
{
"docstring": "Process a custom repository folder.",
... | 5 | stack_v2_sparse_classes_30k_train_036080 | Implement the Python class `StoreData` described below.
Class description:
Hold data for Add-ons inside Supervisor.
Method signatures and docstrings:
- def __init__(self, coresys: CoreSys): Initialize data holder.
- def update(self): Read data from add-on repository.
- def _read_git_repository(self, path): Process a ... | Implement the Python class `StoreData` described below.
Class description:
Hold data for Add-ons inside Supervisor.
Method signatures and docstrings:
- def __init__(self, coresys: CoreSys): Initialize data holder.
- def update(self): Read data from add-on repository.
- def _read_git_repository(self, path): Process a ... | d62aabc01be312417969ce177e080d5147e32749 | <|skeleton|>
class StoreData:
"""Hold data for Add-ons inside Supervisor."""
def __init__(self, coresys: CoreSys):
"""Initialize data holder."""
<|body_0|>
def update(self):
"""Read data from add-on repository."""
<|body_1|>
def _read_git_repository(self, path):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StoreData:
"""Hold data for Add-ons inside Supervisor."""
def __init__(self, coresys: CoreSys):
"""Initialize data holder."""
self.coresys: CoreSys = coresys
self.repositories: Dict[str, Any] = {}
self.addons: Dict[str, Any] = {}
def update(self):
"""Read data... | the_stack_v2_python_sparse | supervisor/store/data.py | mories76/supervisor | train | 24 |
1eb3edc4948f2d7a8a2f7bf6908311519bb30962 | [
"super().__init__()\nself.image_uri_key = image_uri_key\nself.image_good_counter = Metrics.counter(self.__class__, 'image_good')\nself.image_bad_counter = Metrics.counter(self.__class__, 'image_bad')",
"d = {}\ntry:\n image_uri = element.pop(self.image_uri_key)\n image = load(image_uri)\n element['image_... | <|body_start_0|>
super().__init__()
self.image_uri_key = image_uri_key
self.image_good_counter = Metrics.counter(self.__class__, 'image_good')
self.image_bad_counter = Metrics.counter(self.__class__, 'image_bad')
<|end_body_0|>
<|body_start_1|>
d = {}
try:
im... | Adds image to PCollection. | ExtractImagesDoFn | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtractImagesDoFn:
"""Adds image to PCollection."""
def __init__(self, image_uri_key: str):
"""Constructor."""
<|body_0|>
def process(self, element: Dict[str, Any], *args: Tuple[Any, ...], **kwargs: Dict) -> Generator[Dict[str, Any], None, None]:
"""Loads image a... | stack_v2_sparse_classes_75kplus_train_005835 | 3,408 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, image_uri_key: str)"
},
{
"docstring": "Loads image and creates image features. This DoFn extracts an image being stored on local disk or GCS and yields a base64 encoded image, the image height, image width, and ... | 2 | stack_v2_sparse_classes_30k_train_002635 | Implement the Python class `ExtractImagesDoFn` described below.
Class description:
Adds image to PCollection.
Method signatures and docstrings:
- def __init__(self, image_uri_key: str): Constructor.
- def process(self, element: Dict[str, Any], *args: Tuple[Any, ...], **kwargs: Dict) -> Generator[Dict[str, Any], None,... | Implement the Python class `ExtractImagesDoFn` described below.
Class description:
Adds image to PCollection.
Method signatures and docstrings:
- def __init__(self, image_uri_key: str): Constructor.
- def process(self, element: Dict[str, Any], *args: Tuple[Any, ...], **kwargs: Dict) -> Generator[Dict[str, Any], None,... | 80f421ef53778ad2dc793d344d079ab4a814687a | <|skeleton|>
class ExtractImagesDoFn:
"""Adds image to PCollection."""
def __init__(self, image_uri_key: str):
"""Constructor."""
<|body_0|>
def process(self, element: Dict[str, Any], *args: Tuple[Any, ...], **kwargs: Dict) -> Generator[Dict[str, Any], None, None]:
"""Loads image a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ExtractImagesDoFn:
"""Adds image to PCollection."""
def __init__(self, image_uri_key: str):
"""Constructor."""
super().__init__()
self.image_uri_key = image_uri_key
self.image_good_counter = Metrics.counter(self.__class__, 'image_good')
self.image_bad_counter = Met... | the_stack_v2_python_sparse | tfrecorder/beam_image.py | jared-burns/tensorflow-recorder | train | 0 |
b2d09fd9c253f55b159d990cdc611ad436947beb | [
"super().__init__()\nself._op = op\nself._param_sampler = RandBool(probability=probability)",
"apply = self._param_sampler.sample()\nsample_dict[op_id] = apply\nif apply:\n sample_dict = op_call(self._op, sample_dict, f'{op_id}.apply', **kwargs)\nreturn sample_dict",
"apply = sample_dict[op_id]\nif apply:\n ... | <|body_start_0|>
super().__init__()
self._op = op
self._param_sampler = RandBool(probability=probability)
<|end_body_0|>
<|body_start_1|>
apply = self._param_sampler.sample()
sample_dict[op_id] = apply
if apply:
sample_dict = op_call(self._op, sample_dict, f'... | OpRandApply | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpRandApply:
def __init__(self, op: OpBase, probability: float):
"""Randomly apply the op (according to the given probability) :param op: op"""
<|body_0|>
def __call__(self, sample_dict: NDict, op_id: Optional[str], **kwargs: dict) -> Union[None, dict, List[dict]]:
"... | stack_v2_sparse_classes_75kplus_train_005836 | 6,356 | permissive | [
{
"docstring": "Randomly apply the op (according to the given probability) :param op: op",
"name": "__init__",
"signature": "def __init__(self, op: OpBase, probability: float)"
},
{
"docstring": "See super class",
"name": "__call__",
"signature": "def __call__(self, sample_dict: NDict, o... | 3 | stack_v2_sparse_classes_30k_train_033467 | Implement the Python class `OpRandApply` described below.
Class description:
Implement the OpRandApply class.
Method signatures and docstrings:
- def __init__(self, op: OpBase, probability: float): Randomly apply the op (according to the given probability) :param op: op
- def __call__(self, sample_dict: NDict, op_id:... | Implement the Python class `OpRandApply` described below.
Class description:
Implement the OpRandApply class.
Method signatures and docstrings:
- def __init__(self, op: OpBase, probability: float): Randomly apply the op (according to the given probability) :param op: op
- def __call__(self, sample_dict: NDict, op_id:... | 8f22cd46c836245b9394b73ce2957afc03706bfc | <|skeleton|>
class OpRandApply:
def __init__(self, op: OpBase, probability: float):
"""Randomly apply the op (according to the given probability) :param op: op"""
<|body_0|>
def __call__(self, sample_dict: NDict, op_id: Optional[str], **kwargs: dict) -> Union[None, dict, List[dict]]:
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OpRandApply:
def __init__(self, op: OpBase, probability: float):
"""Randomly apply the op (according to the given probability) :param op: op"""
super().__init__()
self._op = op
self._param_sampler = RandBool(probability=probability)
def __call__(self, sample_dict: NDict, o... | the_stack_v2_python_sparse | fuse/data/ops/ops_aug_common.py | BiomedSciAI/fuse-med-ml | train | 45 | |
512fa7d7c5fe95444ef6b8b6d2eae9f9aea660cf | [
"assert not kwargs, kwargs\nattributes = AttributesHelper(self, attributes)\nif not attributes.iswildcard:\n warnings.warn(UnsupportedSelectiveCommunitySetConfig, 'IOS-XR does not support selective community-set configuration.')\n attributes = AttributesHelper(self)\nconfigurations = CliConfigBuilder()\nif Fa... | <|body_start_0|>
assert not kwargs, kwargs
attributes = AttributesHelper(self, attributes)
if not attributes.iswildcard:
warnings.warn(UnsupportedSelectiveCommunitySetConfig, 'IOS-XR does not support selective community-set configuration.')
attributes = AttributesHelper(s... | DeviceAttributes | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
<|body_0|>
def build_unconfig(self... | stack_v2_sparse_classes_75kplus_train_005837 | 7,073 | permissive | [
{
"docstring": "IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured.",
"name": "build_config",
"signature": "def build_config(self, apply=True, attributes=None, **kwargs)"
},
{
"docstring": "IOS-... | 2 | stack_v2_sparse_classes_30k_train_041108 | Implement the Python class `DeviceAttributes` described below.
Class description:
Implement the DeviceAttributes class.
Method signatures and docstrings:
- def build_config(self, apply=True, attributes=None, **kwargs): IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The wh... | Implement the Python class `DeviceAttributes` described below.
Class description:
Implement the DeviceAttributes class.
Method signatures and docstrings:
- def build_config(self, apply=True, attributes=None, **kwargs): IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The wh... | e42e51475cddcb10f5c7814d0fe892ac865742ba | <|skeleton|>
class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
<|body_0|>
def build_unconfig(self... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeviceAttributes:
def build_config(self, apply=True, attributes=None, **kwargs):
"""IOS-XR CommunitySet configuration. Note: Selective configuration is not supported on IOS-XR; The whole community-set is always removed and re-configured."""
assert not kwargs, kwargs
attributes = Attrib... | the_stack_v2_python_sparse | pkgs/conf-pkg/src/genie/libs/conf/community_set/iosxr/community_set.py | CiscoTestAutomation/genielibs | train | 109 | |
15ed22f7fffd066270fb8d0534cc859287a9c769 | [
"super().__init__(x, y)\nself.fill_color = QtCore.Qt.black\nself.line_color = QtCore.Qt.black\nself.center_x = self.x\nself.center_y = self.y\nself.time = random.randint(0, 360)\nself.radius = random.randint(64, 128)",
"self.time += 1\nself.x = math.sin(math.radians(self.time)) * self.radius + self.center_x\nself... | <|body_start_0|>
super().__init__(x, y)
self.fill_color = QtCore.Qt.black
self.line_color = QtCore.Qt.black
self.center_x = self.x
self.center_y = self.y
self.time = random.randint(0, 360)
self.radius = random.randint(64, 128)
<|end_body_0|>
<|body_start_1|>
... | Class to represent a Vulture. | Vulture | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vulture:
"""Class to represent a Vulture."""
def __init__(self, x, y):
"""Create a new Vulture with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero."""
<|body_0|>
def move(self, w, h):
"""... | stack_v2_sparse_classes_75kplus_train_005838 | 13,878 | no_license | [
{
"docstring": "Create a new Vulture with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero.",
"name": "__init__",
"signature": "def __init__(self, x, y)"
},
{
"docstring": "A Vulture flies in a circle centered around it's ... | 2 | stack_v2_sparse_classes_30k_train_021031 | Implement the Python class `Vulture` described below.
Class description:
Class to represent a Vulture.
Method signatures and docstrings:
- def __init__(self, x, y): Create a new Vulture with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero.
- d... | Implement the Python class `Vulture` described below.
Class description:
Class to represent a Vulture.
Method signatures and docstrings:
- def __init__(self, x, y): Create a new Vulture with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero.
- d... | 0e3470085083012f893adb22aa46d46039016965 | <|skeleton|>
class Vulture:
"""Class to represent a Vulture."""
def __init__(self, x, y):
"""Create a new Vulture with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero."""
<|body_0|>
def move(self, w, h):
"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Vulture:
"""Class to represent a Vulture."""
def __init__(self, x, y):
"""Create a new Vulture with the given x and y values. :param int x: The x-coordinate; default is zero. :param int y: The y-coordinate; default is zero."""
super().__init__(x, y)
self.fill_color = QtCore.Qt.bla... | the_stack_v2_python_sparse | CS_210 (Introduction to Programming)/Labs/Lab34_AviaryApp.py | JacobOrner/USAFA | train | 0 |
a5b717474c93ac5edfe8beaa1ea73d7598f7737d | [
"if not id:\n return Response(json='ID not found', status=404)\ntry:\n portfolio = Portfolio.one(request=request, pk=id)\nexcept (DataError, AttributeError):\n return Response(json='Not Found', status=404)\nschema = PortfolioSchema()\ndata = schema.dump(portfolio).data\nreturn Response(json=data, status=20... | <|body_start_0|>
if not id:
return Response(json='ID not found', status=404)
try:
portfolio = Portfolio.one(request=request, pk=id)
except (DataError, AttributeError):
return Response(json='Not Found', status=404)
schema = PortfolioSchema()
dat... | CRUD class for portfolio | PortfolioAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortfolioAPIView:
"""CRUD class for portfolio"""
def retrieve(self, request, id=None):
"""Getting a single portfolio"""
<|body_0|>
def create(self, request):
"""Posting a new portfolio"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not id:
... | stack_v2_sparse_classes_75kplus_train_005839 | 4,737 | no_license | [
{
"docstring": "Getting a single portfolio",
"name": "retrieve",
"signature": "def retrieve(self, request, id=None)"
},
{
"docstring": "Posting a new portfolio",
"name": "create",
"signature": "def create(self, request)"
}
] | 2 | null | Implement the Python class `PortfolioAPIView` described below.
Class description:
CRUD class for portfolio
Method signatures and docstrings:
- def retrieve(self, request, id=None): Getting a single portfolio
- def create(self, request): Posting a new portfolio | Implement the Python class `PortfolioAPIView` described below.
Class description:
CRUD class for portfolio
Method signatures and docstrings:
- def retrieve(self, request, id=None): Getting a single portfolio
- def create(self, request): Posting a new portfolio
<|skeleton|>
class PortfolioAPIView:
"""CRUD class f... | 6d018c849baca593d78ca08e3bf4222e860cd4b3 | <|skeleton|>
class PortfolioAPIView:
"""CRUD class for portfolio"""
def retrieve(self, request, id=None):
"""Getting a single portfolio"""
<|body_0|>
def create(self, request):
"""Posting a new portfolio"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PortfolioAPIView:
"""CRUD class for portfolio"""
def retrieve(self, request, id=None):
"""Getting a single portfolio"""
if not id:
return Response(json='ID not found', status=404)
try:
portfolio = Portfolio.one(request=request, pk=id)
except (DataEr... | the_stack_v2_python_sparse | stocks_api/views/portfolio.py | AndrewBaik/stocks_api | train | 0 |
abe6bc443e3c794542712adef4130caad60a009b | [
"Box2D.b2.rayCastCallback.__init__(self)\nself.agent_mask_filter = agent_mask_filter\nself.fixture = None",
"if fixture.filterData.categoryBits & self.agent_mask_filter == 0:\n return -1\nself.p2 = point\nself.fraction = fraction\nreturn fraction"
] | <|body_start_0|>
Box2D.b2.rayCastCallback.__init__(self)
self.agent_mask_filter = agent_mask_filter
self.fixture = None
<|end_body_0|>
<|body_start_1|>
if fixture.filterData.categoryBits & self.agent_mask_filter == 0:
return -1
self.p2 = point
self.fraction =... | Callback function triggered when lidar detects an object. | LidarCallback | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LidarCallback:
"""Callback function triggered when lidar detects an object."""
def __init__(self, agent_mask_filter):
"""Args: agent_mask_filter: Mask filter used to avoid detecting collisions with the agent's body"""
<|body_0|>
def ReportFixture(self, fixture, point, no... | stack_v2_sparse_classes_75kplus_train_005840 | 23,651 | permissive | [
{
"docstring": "Args: agent_mask_filter: Mask filter used to avoid detecting collisions with the agent's body",
"name": "__init__",
"signature": "def __init__(self, agent_mask_filter)"
},
{
"docstring": "Triggered when a body is detected by the lidar. Returns: Distance to object detected.",
... | 2 | stack_v2_sparse_classes_30k_train_021240 | Implement the Python class `LidarCallback` described below.
Class description:
Callback function triggered when lidar detects an object.
Method signatures and docstrings:
- def __init__(self, agent_mask_filter): Args: agent_mask_filter: Mask filter used to avoid detecting collisions with the agent's body
- def Report... | Implement the Python class `LidarCallback` described below.
Class description:
Callback function triggered when lidar detects an object.
Method signatures and docstrings:
- def __init__(self, agent_mask_filter): Args: agent_mask_filter: Mask filter used to avoid detecting collisions with the agent's body
- def Report... | 6c157511a609e84596c4f8aad99e7576a015ee15 | <|skeleton|>
class LidarCallback:
"""Callback function triggered when lidar detects an object."""
def __init__(self, agent_mask_filter):
"""Args: agent_mask_filter: Mask filter used to avoid detecting collisions with the agent's body"""
<|body_0|>
def ReportFixture(self, fixture, point, no... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LidarCallback:
"""Callback function triggered when lidar detects an object."""
def __init__(self, agent_mask_filter):
"""Args: agent_mask_filter: Mask filter used to avoid detecting collisions with the agent's body"""
Box2D.b2.rayCastCallback.__init__(self)
self.agent_mask_filter ... | the_stack_v2_python_sparse | TeachMyAgent/environments/envs/parametric_continuous_stump_tracks.py | flowersteam/TeachMyAgent | train | 70 |
fb7e236b28634dc11f3d015dab398e6661adb1b0 | [
"if n < 3:\n return 0\nprimes = [True] * n\nprimes[0] = primes[1] = False\nfor i in range(2, int(n ** 0.5) + 1):\n if primes[i]:\n primes[i * i:n:i] = [False] * len(primes[i * i:n:i])\nreturn sum(primes)",
"if n < 3:\n return 0\nprimes = [True] * n\nprimes[0] = primes[1] = False\nfor i in range(2,... | <|body_start_0|>
if n < 3:
return 0
primes = [True] * n
primes[0] = primes[1] = False
for i in range(2, int(n ** 0.5) + 1):
if primes[i]:
primes[i * i:n:i] = [False] * len(primes[i * i:n:i])
return sum(primes)
<|end_body_0|>
<|body_start_1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int https://leetcode.com/problems/count-primes/discuss/57595/ primes[i * i: n: i] = [False] * len(primes[i * i: n: i]) let's assume n == 100, we need to count all the primes which are less than 100: when i == 2: It will mark out... | stack_v2_sparse_classes_75kplus_train_005841 | 1,863 | no_license | [
{
"docstring": ":type n: int :rtype: int https://leetcode.com/problems/count-primes/discuss/57595/ primes[i * i: n: i] = [False] * len(primes[i * i: n: i]) let's assume n == 100, we need to count all the primes which are less than 100: when i == 2: It will mark out the numbers as none-prime: 4: 100 : 2 -> 4,6,8... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n): :type n: int :rtype: int https://leetcode.com/problems/count-primes/discuss/57595/ primes[i * i: n: i] = [False] * len(primes[i * i: n: i]) let's assume... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n): :type n: int :rtype: int https://leetcode.com/problems/count-primes/discuss/57595/ primes[i * i: n: i] = [False] * len(primes[i * i: n: i]) let's assume... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int https://leetcode.com/problems/count-primes/discuss/57595/ primes[i * i: n: i] = [False] * len(primes[i * i: n: i]) let's assume n == 100, we need to count all the primes which are less than 100: when i == 2: It will mark out... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int https://leetcode.com/problems/count-primes/discuss/57595/ primes[i * i: n: i] = [False] * len(primes[i * i: n: i]) let's assume n == 100, we need to count all the primes which are less than 100: when i == 2: It will mark out the numbers a... | the_stack_v2_python_sparse | LeetCode/204_count_primes.py | yao23/Machine_Learning_Playground | train | 12 | |
5c13d84db54c5a8fc3f5179bdfb30c203a2f5c91 | [
"nums.sort()\nif len(nums) < 3:\n return None\nres = nums[0] + nums[1] + nums[2]\nfor i in xrange(len(nums) - 2):\n if i > 0 and nums[i] == nums[i - 1]:\n continue\n l, r = (i + 1, len(nums) - 1)\n while l < r:\n value = nums[i] + nums[l] + nums[r]\n offset = abs(value - target)\n ... | <|body_start_0|>
nums.sort()
if len(nums) < 3:
return None
res = nums[0] + nums[1] + nums[2]
for i in xrange(len(nums) - 2):
if i > 0 and nums[i] == nums[i - 1]:
continue
l, r = (i + 1, len(nums) - 1)
while l < r:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSumClosest(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def threeSumClosest_v1(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_005842 | 2,983 | permissive | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "threeSumClosest",
"signature": "def threeSumClosest(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "threeSumClosest_v1",
"signature": "def threeSumClosest... | 2 | stack_v2_sparse_classes_30k_train_032299 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumClosest(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def threeSumClosest_v1(self, nums, target): :type nums: List[int] :type target: int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumClosest(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def threeSumClosest_v1(self, nums, target): :type nums: List[int] :type target: int... | 05420b73d28220681cd7be8253bebcaa83966954 | <|skeleton|>
class Solution:
def threeSumClosest(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def threeSumClosest_v1(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def threeSumClosest(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
nums.sort()
if len(nums) < 3:
return None
res = nums[0] + nums[1] + nums[2]
for i in xrange(len(nums) - 2):
if i > 0 and nums[i] == nums[... | the_stack_v2_python_sparse | 3sum-closest/test.py | optionalg/challenges-leetcode-interesting | train | 0 | |
50b52f41d7ecbd3781a4daa10041b5cc8448e97f | [
"super(KNNClassifier, self).__init__(**kwargs)\nself.model = neighbors.KNeighborsClassifier(n_neighbors=n_neighbors, algorithm='brute', metric='precomputed')\nself.use_model = True\nself.model_out = None",
"if len(np.unique(y)) == 1:\n self.use_model = False\n self.model_out = list(np.unique(y))[0]\nelse:\n... | <|body_start_0|>
super(KNNClassifier, self).__init__(**kwargs)
self.model = neighbors.KNeighborsClassifier(n_neighbors=n_neighbors, algorithm='brute', metric='precomputed')
self.use_model = True
self.model_out = None
<|end_body_0|>
<|body_start_1|>
if len(np.unique(y)) == 1:
... | KNNClassifier | KNNClassifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KNNClassifier:
"""KNNClassifier"""
def __init__(self, n_neighbors: int, **kwargs):
"""__init__. Args: n_neighbors (int): Number of neighbors kwargs: kwargs"""
<|body_0|>
def fit(self, X, y, **kwargs):
"""fit. For this model, make sure that X is a pairwise distanc... | stack_v2_sparse_classes_75kplus_train_005843 | 12,286 | no_license | [
{
"docstring": "__init__. Args: n_neighbors (int): Number of neighbors kwargs: kwargs",
"name": "__init__",
"signature": "def __init__(self, n_neighbors: int, **kwargs)"
},
{
"docstring": "fit. For this model, make sure that X is a pairwise distance matrix in the fit loop Args: X: X y: y kwargs:... | 3 | stack_v2_sparse_classes_30k_train_052948 | Implement the Python class `KNNClassifier` described below.
Class description:
KNNClassifier
Method signatures and docstrings:
- def __init__(self, n_neighbors: int, **kwargs): __init__. Args: n_neighbors (int): Number of neighbors kwargs: kwargs
- def fit(self, X, y, **kwargs): fit. For this model, make sure that X ... | Implement the Python class `KNNClassifier` described below.
Class description:
KNNClassifier
Method signatures and docstrings:
- def __init__(self, n_neighbors: int, **kwargs): __init__. Args: n_neighbors (int): Number of neighbors kwargs: kwargs
- def fit(self, X, y, **kwargs): fit. For this model, make sure that X ... | 84c9026c78bec9a2267960a87080b71beba5c305 | <|skeleton|>
class KNNClassifier:
"""KNNClassifier"""
def __init__(self, n_neighbors: int, **kwargs):
"""__init__. Args: n_neighbors (int): Number of neighbors kwargs: kwargs"""
<|body_0|>
def fit(self, X, y, **kwargs):
"""fit. For this model, make sure that X is a pairwise distanc... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KNNClassifier:
"""KNNClassifier"""
def __init__(self, n_neighbors: int, **kwargs):
"""__init__. Args: n_neighbors (int): Number of neighbors kwargs: kwargs"""
super(KNNClassifier, self).__init__(**kwargs)
self.model = neighbors.KNeighborsClassifier(n_neighbors=n_neighbors, algorit... | the_stack_v2_python_sparse | enzpred/models/sklearn_models.py | liudongliangHI/enz-pred | train | 0 |
2710effbac552ef12ecfc8ad7d45104b25f771a6 | [
"self.drizzle_params = drizzle_params.copy()\nself.mult_drizzle_par = mult_drizzle_par.copy()\nself.cont_info = cont_info\nself.opt_extr = opt_extr\nself.back = back\nif drztmp_dir != None:\n self.drztmp_dir = drztmp_dir\nelse:\n self.drztmp_dir = axeutils.getDRZTMP()\nif drizzle_dir != None:\n self.drizzl... | <|body_start_0|>
self.drizzle_params = drizzle_params.copy()
self.mult_drizzle_par = mult_drizzle_par.copy()
self.cont_info = cont_info
self.opt_extr = opt_extr
self.back = back
if drztmp_dir != None:
self.drztmp_dir = drztmp_dir
else:
self... | List class for all objects to be drizzled | MulDrzObjList | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MulDrzObjList:
"""List class for all objects to be drizzled"""
def __init__(self, drizzle_params, mult_drizzle_par, cont_info=None, opt_extr=False, back=False, drztmp_dir=None, drizzle_dir=None):
"""Initializes the class"""
<|body_0|>
def _objlist_to_drzobjects(self, obj... | stack_v2_sparse_classes_75kplus_train_005844 | 10,632 | permissive | [
{
"docstring": "Initializes the class",
"name": "__init__",
"signature": "def __init__(self, drizzle_params, mult_drizzle_par, cont_info=None, opt_extr=False, back=False, drztmp_dir=None, drizzle_dir=None)"
},
{
"docstring": "Converts the object list into drizzle objects",
"name": "_objlist_... | 4 | stack_v2_sparse_classes_30k_train_051124 | Implement the Python class `MulDrzObjList` described below.
Class description:
List class for all objects to be drizzled
Method signatures and docstrings:
- def __init__(self, drizzle_params, mult_drizzle_par, cont_info=None, opt_extr=False, back=False, drztmp_dir=None, drizzle_dir=None): Initializes the class
- def ... | Implement the Python class `MulDrzObjList` described below.
Class description:
List class for all objects to be drizzled
Method signatures and docstrings:
- def __init__(self, drizzle_params, mult_drizzle_par, cont_info=None, opt_extr=False, back=False, drztmp_dir=None, drizzle_dir=None): Initializes the class
- def ... | 043c173fd5497c18c2b1bfe8bcff65180bca3996 | <|skeleton|>
class MulDrzObjList:
"""List class for all objects to be drizzled"""
def __init__(self, drizzle_params, mult_drizzle_par, cont_info=None, opt_extr=False, back=False, drztmp_dir=None, drizzle_dir=None):
"""Initializes the class"""
<|body_0|>
def _objlist_to_drzobjects(self, obj... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MulDrzObjList:
"""List class for all objects to be drizzled"""
def __init__(self, drizzle_params, mult_drizzle_par, cont_info=None, opt_extr=False, back=False, drztmp_dir=None, drizzle_dir=None):
"""Initializes the class"""
self.drizzle_params = drizzle_params.copy()
self.mult_dri... | the_stack_v2_python_sparse | stsdas/pkg/analysis/slitless/axe/axesrc/mdrzobjects.py | spacetelescope/stsdas_stripped | train | 1 |
e7fb8a32158117a6c4ec4170d28107c8dd2d2034 | [
"self.log.debug(\"Submitting Inference request for model '%s' with '%s' objects and top_n '%s' \", model_name, len(objects), top_n)\nendpoint = InferencePaths.format_inference_endpoint_by_name(model_name)\nresponse = self.session.post_to_endpoint(endpoint, payload={'topN': top_n, 'objects': objects}, retry=retry)\n... | <|body_start_0|>
self.log.debug("Submitting Inference request for model '%s' with '%s' objects and top_n '%s' ", model_name, len(objects), top_n)
endpoint = InferencePaths.format_inference_endpoint_by_name(model_name)
response = self.session.post_to_endpoint(endpoint, payload={'topN': top_n, 'ob... | A client for the DAR Inference microservice. This class implements all basic API calls as well as some convenience methods which wrap individual API calls. If the API call fails, all methods will raise an :exc:`DARHTTPException`. | InferenceClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InferenceClient:
"""A client for the DAR Inference microservice. This class implements all basic API calls as well as some convenience methods which wrap individual API calls. If the API call fails, all methods will raise an :exc:`DARHTTPException`."""
def create_inference_request(self, mode... | stack_v2_sparse_classes_75kplus_train_005845 | 9,582 | permissive | [
{
"docstring": "Performs inference for the given *objects* with *model_name*. For each object in *objects*, returns the *topN* best predictions. The *retry* parameter determines whether to retry on HTTP errors indicated by the remote API endpoint or for other connection problems. See :ref:`retry` for trade-offs... | 3 | stack_v2_sparse_classes_30k_test_000565 | Implement the Python class `InferenceClient` described below.
Class description:
A client for the DAR Inference microservice. This class implements all basic API calls as well as some convenience methods which wrap individual API calls. If the API call fails, all methods will raise an :exc:`DARHTTPException`.
Method ... | Implement the Python class `InferenceClient` described below.
Class description:
A client for the DAR Inference microservice. This class implements all basic API calls as well as some convenience methods which wrap individual API calls. If the API call fails, all methods will raise an :exc:`DARHTTPException`.
Method ... | 445131264e81b5d98ca4b74690e467eb276a22df | <|skeleton|>
class InferenceClient:
"""A client for the DAR Inference microservice. This class implements all basic API calls as well as some convenience methods which wrap individual API calls. If the API call fails, all methods will raise an :exc:`DARHTTPException`."""
def create_inference_request(self, mode... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InferenceClient:
"""A client for the DAR Inference microservice. This class implements all basic API calls as well as some convenience methods which wrap individual API calls. If the API call fails, all methods will raise an :exc:`DARHTTPException`."""
def create_inference_request(self, model_name: str, ... | the_stack_v2_python_sparse | sap/aibus/dar/client/inference_client.py | SAP/data-attribute-recommendation-python-sdk | train | 13 |
6145367d89190aac19d6fc0b35bf12eca8e6707c | [
"name = 'DavisBirner'\nsuper(STJDavisBirner, self).__init__(name=name, props=props, data=data)\nself.upper_p_level = self.props['upper_p_level']\nself.lower_p_level = self.props['lower_p_level']\nself.surf_p_level = self.props['surface_p_level']\nif self.data[self.data.cfg['lev']].units in ['mb', 'millibars', 'hPa'... | <|body_start_0|>
name = 'DavisBirner'
super(STJDavisBirner, self).__init__(name=name, props=props, data=data)
self.upper_p_level = self.props['upper_p_level']
self.lower_p_level = self.props['lower_p_level']
self.surf_p_level = self.props['surface_p_level']
if self.data[s... | Subtropical jet position metric using the method of Davis and Birner 2016. Parameters ---------- props : :py:meth:`~STJ_PV.run_stj.JetFindRun` Class containing properties about the current search for the STJ data : :py:meth:`~STJ_PV.input_data.InputData` Input data class containing a year (or more) of required data Not... | STJDavisBirner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class STJDavisBirner:
"""Subtropical jet position metric using the method of Davis and Birner 2016. Parameters ---------- props : :py:meth:`~STJ_PV.run_stj.JetFindRun` Class containing properties about the current search for the STJ data : :py:meth:`~STJ_PV.input_data.InputData` Input data class contai... | stack_v2_sparse_classes_75kplus_train_005846 | 34,635 | no_license | [
{
"docstring": "Initialise Metric using Davis and Birner 2016 method.",
"name": "__init__",
"signature": "def __init__(self, props, data)"
},
{
"docstring": "Find the subtropical jet using method from Davis and Birner (2016). doi:10.1175/JCLI-D-15-0336.1 Parameters ---------- shemis : logical, o... | 4 | stack_v2_sparse_classes_30k_train_002565 | Implement the Python class `STJDavisBirner` described below.
Class description:
Subtropical jet position metric using the method of Davis and Birner 2016. Parameters ---------- props : :py:meth:`~STJ_PV.run_stj.JetFindRun` Class containing properties about the current search for the STJ data : :py:meth:`~STJ_PV.input_... | Implement the Python class `STJDavisBirner` described below.
Class description:
Subtropical jet position metric using the method of Davis and Birner 2016. Parameters ---------- props : :py:meth:`~STJ_PV.run_stj.JetFindRun` Class containing properties about the current search for the STJ data : :py:meth:`~STJ_PV.input_... | 092dc88fab708084a3136a1c1c08153ea6157721 | <|skeleton|>
class STJDavisBirner:
"""Subtropical jet position metric using the method of Davis and Birner 2016. Parameters ---------- props : :py:meth:`~STJ_PV.run_stj.JetFindRun` Class containing properties about the current search for the STJ data : :py:meth:`~STJ_PV.input_data.InputData` Input data class contai... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class STJDavisBirner:
"""Subtropical jet position metric using the method of Davis and Birner 2016. Parameters ---------- props : :py:meth:`~STJ_PV.run_stj.JetFindRun` Class containing properties about the current search for the STJ data : :py:meth:`~STJ_PV.input_data.InputData` Input data class containing a year (... | the_stack_v2_python_sparse | STJ_PV/stj_metric.py | LMXB/stj_pv | train | 0 |
cb3dae7c167d323c9070b34391adb5b90d5fe68c | [
"loaded = models.TimeSlot.load(uid)\nif loaded is None:\n abort(404)\nreturn loaded",
"loaded = models.TimeSlot.load(uid)\nif loaded is None:\n return ('', 404)\nloaded.delete()\nreturn ('', 204)",
"data = request.json\nstart = parse(data['start'])\nend = parse(data['end'])\nduration = end - start\ncapaci... | <|body_start_0|>
loaded = models.TimeSlot.load(uid)
if loaded is None:
abort(404)
return loaded
<|end_body_0|>
<|body_start_1|>
loaded = models.TimeSlot.load(uid)
if loaded is None:
return ('', 404)
loaded.delete()
return ('', 204)
<|end_b... | Operations related to the management of a single timeslot. | Timeslot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Timeslot:
"""Operations related to the management of a single timeslot."""
def get(self, uid):
"""Get a particular timeslot"""
<|body_0|>
def delete(self, uid):
"""Delete a particular timeslot"""
<|body_1|>
def put(self, uid):
"""Updates all ... | stack_v2_sparse_classes_75kplus_train_005847 | 6,359 | no_license | [
{
"docstring": "Get a particular timeslot",
"name": "get",
"signature": "def get(self, uid)"
},
{
"docstring": "Delete a particular timeslot",
"name": "delete",
"signature": "def delete(self, uid)"
},
{
"docstring": "Updates all non-readonly fields of a timeslot",
"name": "pu... | 4 | stack_v2_sparse_classes_30k_train_034918 | Implement the Python class `Timeslot` described below.
Class description:
Operations related to the management of a single timeslot.
Method signatures and docstrings:
- def get(self, uid): Get a particular timeslot
- def delete(self, uid): Delete a particular timeslot
- def put(self, uid): Updates all non-readonly fi... | Implement the Python class `Timeslot` described below.
Class description:
Operations related to the management of a single timeslot.
Method signatures and docstrings:
- def get(self, uid): Get a particular timeslot
- def delete(self, uid): Delete a particular timeslot
- def put(self, uid): Updates all non-readonly fi... | ab874354e94e789fbea090f29e507fca2223284d | <|skeleton|>
class Timeslot:
"""Operations related to the management of a single timeslot."""
def get(self, uid):
"""Get a particular timeslot"""
<|body_0|>
def delete(self, uid):
"""Delete a particular timeslot"""
<|body_1|>
def put(self, uid):
"""Updates all ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Timeslot:
"""Operations related to the management of a single timeslot."""
def get(self, uid):
"""Get a particular timeslot"""
loaded = models.TimeSlot.load(uid)
if loaded is None:
abort(404)
return loaded
def delete(self, uid):
"""Delete a particu... | the_stack_v2_python_sparse | app/apis/timeslot_api.py | TheWinch/flask-tuto | train | 0 |
0048e1501de9b748b7effbd9f61339aa8d7aceec | [
"num_dic = {}\nfor num in nums:\n if num in num_dic:\n num_dic[num] += 1\n else:\n num_dic[num] = 1\nfor key in num_dic.keys():\n if num_dic[key] >= len(nums) / 2:\n return key\nreturn -1",
"majority, count = (0, 0)\nfor num in nums:\n if count == 0:\n majority = num\n ... | <|body_start_0|>
num_dic = {}
for num in nums:
if num in num_dic:
num_dic[num] += 1
else:
num_dic[num] = 1
for key in num_dic.keys():
if num_dic[key] >= len(nums) / 2:
return key
return -1
<|end_body_0|>
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def majority_element(self, nums: List[int]) -> int:
"""大多数元素 Args: nums: 数组 Returns: 元素"""
<|body_0|>
def majority_element2(self, nums: List[int]) -> int:
"""大多数元素 Args: nums: 数组 Returns: 元素"""
<|body_1|>
def majority_element3(self, nums: List[... | stack_v2_sparse_classes_75kplus_train_005848 | 3,141 | permissive | [
{
"docstring": "大多数元素 Args: nums: 数组 Returns: 元素",
"name": "majority_element",
"signature": "def majority_element(self, nums: List[int]) -> int"
},
{
"docstring": "大多数元素 Args: nums: 数组 Returns: 元素",
"name": "majority_element2",
"signature": "def majority_element2(self, nums: List[int]) -... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majority_element(self, nums: List[int]) -> int: 大多数元素 Args: nums: 数组 Returns: 元素
- def majority_element2(self, nums: List[int]) -> int: 大多数元素 Args: nums: 数组 Returns: 元素
- def... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majority_element(self, nums: List[int]) -> int: 大多数元素 Args: nums: 数组 Returns: 元素
- def majority_element2(self, nums: List[int]) -> int: 大多数元素 Args: nums: 数组 Returns: 元素
- def... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def majority_element(self, nums: List[int]) -> int:
"""大多数元素 Args: nums: 数组 Returns: 元素"""
<|body_0|>
def majority_element2(self, nums: List[int]) -> int:
"""大多数元素 Args: nums: 数组 Returns: 元素"""
<|body_1|>
def majority_element3(self, nums: List[... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def majority_element(self, nums: List[int]) -> int:
"""大多数元素 Args: nums: 数组 Returns: 元素"""
num_dic = {}
for num in nums:
if num in num_dic:
num_dic[num] += 1
else:
num_dic[num] = 1
for key in num_dic.keys():
... | the_stack_v2_python_sparse | src/leetcodepython/array/majority_element_169.py | zhangyu345293721/leetcode | train | 101 | |
653175143676eb16895c0e12bf6e9ef0ce704a82 | [
"self.name = name\nself.end = end\nself.start = start",
"if self.start <= other.start < self.end:\n return True\nelif self.start <= other.end < self.end:\n return True\nelse:\n return False"
] | <|body_start_0|>
self.name = name
self.end = end
self.start = start
<|end_body_0|>
<|body_start_1|>
if self.start <= other.start < self.end:
return True
elif self.start <= other.end < self.end:
return True
else:
return False
<|end_body... | Appointment | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Appointment:
def __init__(self, name, start, end):
"""Initializes the name, end,and start."""
<|body_0|>
def overlaps(self, other):
"""Checks for overlaps by using the start and end times using another appointment onject named other. Returns a boolean of true or fals... | stack_v2_sparse_classes_75kplus_train_005849 | 657 | no_license | [
{
"docstring": "Initializes the name, end,and start.",
"name": "__init__",
"signature": "def __init__(self, name, start, end)"
},
{
"docstring": "Checks for overlaps by using the start and end times using another appointment onject named other. Returns a boolean of true or false depending on the... | 2 | stack_v2_sparse_classes_30k_train_037785 | Implement the Python class `Appointment` described below.
Class description:
Implement the Appointment class.
Method signatures and docstrings:
- def __init__(self, name, start, end): Initializes the name, end,and start.
- def overlaps(self, other): Checks for overlaps by using the start and end times using another a... | Implement the Python class `Appointment` described below.
Class description:
Implement the Appointment class.
Method signatures and docstrings:
- def __init__(self, name, start, end): Initializes the name, end,and start.
- def overlaps(self, other): Checks for overlaps by using the start and end times using another a... | 45c8c29b99ed619a8a4318bf22e645399dba8e57 | <|skeleton|>
class Appointment:
def __init__(self, name, start, end):
"""Initializes the name, end,and start."""
<|body_0|>
def overlaps(self, other):
"""Checks for overlaps by using the start and end times using another appointment onject named other. Returns a boolean of true or fals... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Appointment:
def __init__(self, name, start, end):
"""Initializes the name, end,and start."""
self.name = name
self.end = end
self.start = start
def overlaps(self, other):
"""Checks for overlaps by using the start and end times using another appointment onject name... | the_stack_v2_python_sparse | Appointment/appointment.py | shima3434/Introductory_Python_Projects | train | 0 | |
b616952a6a8b0366211dcad6c25aefc5b2390fa1 | [
"p, node = (head, None)\nwhile p:\n tmp = ListNode(p.val)\n tmp.next = node\n node = tmp\n p = p.next\nreturn node",
"if not head or not head.next:\n return head\na = head\nb = head.next\na.next = None\nwhile a and b:\n n = a\n a = b\n b = b.next\n a.next = n\nreturn a"
] | <|body_start_0|>
p, node = (head, None)
while p:
tmp = ListNode(p.val)
tmp.next = node
node = tmp
p = p.next
return node
<|end_body_0|>
<|body_start_1|>
if not head or not head.next:
return head
a = head
b = hea... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList_1(self, head: ListNode) -> ListNode:
"""time: O(N), space: O(N) input 바꾸지 않고 새롭게 노드를 생성 iterative"""
<|body_0|>
def reverseList_2(self, head: ListNode) -> ListNode:
"""time: O(N), space: O(1) in place iterative"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_005850 | 886 | no_license | [
{
"docstring": "time: O(N), space: O(N) input 바꾸지 않고 새롭게 노드를 생성 iterative",
"name": "reverseList_1",
"signature": "def reverseList_1(self, head: ListNode) -> ListNode"
},
{
"docstring": "time: O(N), space: O(1) in place iterative",
"name": "reverseList_2",
"signature": "def reverseList_2... | 2 | stack_v2_sparse_classes_30k_train_000712 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList_1(self, head: ListNode) -> ListNode: time: O(N), space: O(N) input 바꾸지 않고 새롭게 노드를 생성 iterative
- def reverseList_2(self, head: ListNode) -> ListNode: time: O(N), ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList_1(self, head: ListNode) -> ListNode: time: O(N), space: O(N) input 바꾸지 않고 새롭게 노드를 생성 iterative
- def reverseList_2(self, head: ListNode) -> ListNode: time: O(N), ... | 8f90a33abf451f2490f1d8d9993b64d60ef0bed0 | <|skeleton|>
class Solution:
def reverseList_1(self, head: ListNode) -> ListNode:
"""time: O(N), space: O(N) input 바꾸지 않고 새롭게 노드를 생성 iterative"""
<|body_0|>
def reverseList_2(self, head: ListNode) -> ListNode:
"""time: O(N), space: O(1) in place iterative"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reverseList_1(self, head: ListNode) -> ListNode:
"""time: O(N), space: O(N) input 바꾸지 않고 새롭게 노드를 생성 iterative"""
p, node = (head, None)
while p:
tmp = ListNode(p.val)
tmp.next = node
node = tmp
p = p.next
return node... | the_stack_v2_python_sparse | leetcode/leetcode_0206_Reverse_Linked_List.py | YunjinPark/algorithms | train | 0 | |
7ca337d1a0185b1e7015242c1cce698e9f0330b1 | [
"try:\n numberString = float(numberString)\n numberString = int(numberString)\nexcept ValueError:\n pass\nreturn numberString",
"if os.path.isfile(inputFile) == False:\n print('Invalid file path')\n return 0\nelse:\n with open(inputFile) as f:\n if ignoreHeader:\n next(f)\n ... | <|body_start_0|>
try:
numberString = float(numberString)
numberString = int(numberString)
except ValueError:
pass
return numberString
<|end_body_0|>
<|body_start_1|>
if os.path.isfile(inputFile) == False:
print('Invalid file path')
... | This is InputHandler class responsible for reading inputs to the program | InputHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputHandler:
"""This is InputHandler class responsible for reading inputs to the program"""
def convertToInteger(self, numberString):
"""This function checks if input is number and if yes then convert it into integer. :param numberString: Number string to convert into integer :retur... | stack_v2_sparse_classes_75kplus_train_005851 | 2,549 | no_license | [
{
"docstring": "This function checks if input is number and if yes then convert it into integer. :param numberString: Number string to convert into integer :return: Converted integer if string is digit else the same string",
"name": "convertToInteger",
"signature": "def convertToInteger(self, numberStri... | 3 | stack_v2_sparse_classes_30k_train_024759 | Implement the Python class `InputHandler` described below.
Class description:
This is InputHandler class responsible for reading inputs to the program
Method signatures and docstrings:
- def convertToInteger(self, numberString): This function checks if input is number and if yes then convert it into integer. :param n... | Implement the Python class `InputHandler` described below.
Class description:
This is InputHandler class responsible for reading inputs to the program
Method signatures and docstrings:
- def convertToInteger(self, numberString): This function checks if input is number and if yes then convert it into integer. :param n... | e67a831f92335e725d1c495e7d67401d1b30ed1e | <|skeleton|>
class InputHandler:
"""This is InputHandler class responsible for reading inputs to the program"""
def convertToInteger(self, numberString):
"""This function checks if input is number and if yes then convert it into integer. :param numberString: Number string to convert into integer :retur... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InputHandler:
"""This is InputHandler class responsible for reading inputs to the program"""
def convertToInteger(self, numberString):
"""This function checks if input is number and if yes then convert it into integer. :param numberString: Number string to convert into integer :return: Converted ... | the_stack_v2_python_sparse | DecisionTree/InputHandler.py | anwarsk/DecisionTree | train | 0 |
3d2d66b9de56ef158bb2106e3d821648d502f901 | [
"if version is None:\n return False\nif self.min_version is not None:\n if version < self.min_version:\n return False\nif self.max_version is not None:\n if version > self.max_version:\n return False\nreturn True",
"if sql is None:\n return []\ndatabase = conninfo['dbname']\noutput = []\... | <|body_start_0|>
if version is None:
return False
if self.min_version is not None:
if version < self.min_version:
return False
if self.max_version is not None:
if version > self.max_version:
return False
return True
<|en... | postgres probe base class | SqlProbe | [
"PostgreSQL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SqlProbe:
"""postgres probe base class"""
def check(self, version=None):
"""Check if the plugin can run on the target version of PostgreSQL."""
<|body_0|>
def run_sql(self, conn, conninfo, sql):
"""Get the result of the SQL query"""
<|body_1|>
def ru... | stack_v2_sparse_classes_75kplus_train_005852 | 30,100 | permissive | [
{
"docstring": "Check if the plugin can run on the target version of PostgreSQL.",
"name": "check",
"signature": "def check(self, version=None)"
},
{
"docstring": "Get the result of the SQL query",
"name": "run_sql",
"signature": "def run_sql(self, conn, conninfo, sql)"
},
{
"doc... | 3 | stack_v2_sparse_classes_30k_train_021689 | Implement the Python class `SqlProbe` described below.
Class description:
postgres probe base class
Method signatures and docstrings:
- def check(self, version=None): Check if the plugin can run on the target version of PostgreSQL.
- def run_sql(self, conn, conninfo, sql): Get the result of the SQL query
- def run(se... | Implement the Python class `SqlProbe` described below.
Class description:
postgres probe base class
Method signatures and docstrings:
- def check(self, version=None): Check if the plugin can run on the target version of PostgreSQL.
- def run_sql(self, conn, conninfo, sql): Get the result of the SQL query
- def run(se... | d26cb848f4b064e05d5e422ecc001889f224bd74 | <|skeleton|>
class SqlProbe:
"""postgres probe base class"""
def check(self, version=None):
"""Check if the plugin can run on the target version of PostgreSQL."""
<|body_0|>
def run_sql(self, conn, conninfo, sql):
"""Get the result of the SQL query"""
<|body_1|>
def ru... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SqlProbe:
"""postgres probe base class"""
def check(self, version=None):
"""Check if the plugin can run on the target version of PostgreSQL."""
if version is None:
return False
if self.min_version is not None:
if version < self.min_version:
... | the_stack_v2_python_sparse | agent/temboardagent/plugins/monitoring/probes.py | dalibo/temboard | train | 400 |
9f617bdbb01cb79f5218632d75c858a4626b2b4a | [
"for op in self.operations:\n if op.name == op_name:\n return op\nraise KeyError('Operation with name %s was not found in dataClay class %s' % (op_name, self.name))",
"if not hasattr(self, '_implementation_id_to_operation_cache'):\n setattr(self, '_implementation_id_to_operation_cache', LRU(50))\ntry... | <|body_start_0|>
for op in self.operations:
if op.name == op_name:
return op
raise KeyError('Operation with name %s was not found in dataClay class %s' % (op_name, self.name))
<|end_body_0|>
<|body_start_1|>
if not hasattr(self, '_implementation_id_to_operation_cache... | MetaClass | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetaClass:
def get_operation_from_name(self, op_name):
"""Return the operation from its name."""
<|body_0|>
def get_operation(self, implementation_id):
"""Return an Operation (management object) from an ImplementationID :param uuid.UUID implementation_id: The request... | stack_v2_sparse_classes_75kplus_train_005853 | 5,420 | permissive | [
{
"docstring": "Return the operation from its name.",
"name": "get_operation_from_name",
"signature": "def get_operation_from_name(self, op_name)"
},
{
"docstring": "Return an Operation (management object) from an ImplementationID :param uuid.UUID implementation_id: The requested ImplementationI... | 3 | stack_v2_sparse_classes_30k_train_018875 | Implement the Python class `MetaClass` described below.
Class description:
Implement the MetaClass class.
Method signatures and docstrings:
- def get_operation_from_name(self, op_name): Return the operation from its name.
- def get_operation(self, implementation_id): Return an Operation (management object) from an Im... | Implement the Python class `MetaClass` described below.
Class description:
Implement the MetaClass class.
Method signatures and docstrings:
- def get_operation_from_name(self, op_name): Return the operation from its name.
- def get_operation(self, implementation_id): Return an Operation (management object) from an Im... | 33df8fa9fff5c42bad6c2c772c8ee60a3d07dcbb | <|skeleton|>
class MetaClass:
def get_operation_from_name(self, op_name):
"""Return the operation from its name."""
<|body_0|>
def get_operation(self, implementation_id):
"""Return an Operation (management object) from an ImplementationID :param uuid.UUID implementation_id: The request... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MetaClass:
def get_operation_from_name(self, op_name):
"""Return the operation from its name."""
for op in self.operations:
if op.name == op_name:
return op
raise KeyError('Operation with name %s was not found in dataClay class %s' % (op_name, self.name))
... | the_stack_v2_python_sparse | src/dataclay/util/management/classmgr/MetaClass.py | bsc-dom/pyclay | train | 3 | |
69266f372ee307b9cb8178aecd307b8555366b44 | [
"objreader = ObjReader.ObjReader()\ndatlist = [['1'], ['1', '2'], ['1', '2', '3'], ['1', '', '3'], ['1', '2', ''], ['1', '', '']]\nanslist = [[True, False, False], [True, True, False], [True, True, True], [True, False, True], [True, True, False], [True, False, False]]\nn = len(datlist)\ni = 0\nwhile i < n:\n ite... | <|body_start_0|>
objreader = ObjReader.ObjReader()
datlist = [['1'], ['1', '2'], ['1', '2', '3'], ['1', '', '3'], ['1', '2', ''], ['1', '', '']]
anslist = [[True, False, False], [True, True, False], [True, True, True], [True, False, True], [True, True, False], [True, False, False]]
n = l... | test for obj file reader | TestObjReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestObjReader:
"""test for obj file reader"""
def test_objreader_unit0(self):
"""objreader test 0"""
<|body_0|>
def test_objreader_sample0(self):
"""objreader sample0"""
<|body_1|>
def test_objreader_sample2(self):
"""objreader sample2"""
... | stack_v2_sparse_classes_75kplus_train_005854 | 2,131 | no_license | [
{
"docstring": "objreader test 0",
"name": "test_objreader_unit0",
"signature": "def test_objreader_unit0(self)"
},
{
"docstring": "objreader sample0",
"name": "test_objreader_sample0",
"signature": "def test_objreader_sample0(self)"
},
{
"docstring": "objreader sample2",
"na... | 3 | stack_v2_sparse_classes_30k_train_018495 | Implement the Python class `TestObjReader` described below.
Class description:
test for obj file reader
Method signatures and docstrings:
- def test_objreader_unit0(self): objreader test 0
- def test_objreader_sample0(self): objreader sample0
- def test_objreader_sample2(self): objreader sample2 | Implement the Python class `TestObjReader` described below.
Class description:
test for obj file reader
Method signatures and docstrings:
- def test_objreader_unit0(self): objreader test 0
- def test_objreader_sample0(self): objreader sample0
- def test_objreader_sample2(self): objreader sample2
<|skeleton|>
class T... | f163b6b9e15100d223ddf4e180727a2b63fbae2d | <|skeleton|>
class TestObjReader:
"""test for obj file reader"""
def test_objreader_unit0(self):
"""objreader test 0"""
<|body_0|>
def test_objreader_sample0(self):
"""objreader sample0"""
<|body_1|>
def test_objreader_sample2(self):
"""objreader sample2"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestObjReader:
"""test for obj file reader"""
def test_objreader_unit0(self):
"""objreader test 0"""
objreader = ObjReader.ObjReader()
datlist = [['1'], ['1', '2'], ['1', '2', '3'], ['1', '', '3'], ['1', '2', ''], ['1', '', '']]
anslist = [[True, False, False], [True, True... | the_stack_v2_python_sparse | ifgi/scene/test_ObjReader.py | yamauchih/ifgi-path-tracer | train | 0 |
d6d013ecf9167030c28e20f045494d47640981d2 | [
"n = len(nums)\nans = 0\nfor i in range(n):\n prod = 1\n for j in range(i, n):\n prod *= nums[j]\n if prod >= k:\n continue\n else:\n ans += 1\nreturn ans",
"if k <= 1:\n return 0\nn = len(nums)\nl = 0\nprod = 1\nans = 0\nfor r in range(n):\n prod *= nums[r]\... | <|body_start_0|>
n = len(nums)
ans = 0
for i in range(n):
prod = 1
for j in range(i, n):
prod *= nums[j]
if prod >= k:
continue
else:
ans += 1
return ans
<|end_body_0|>
<|body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> int:
"""Brute Force, Time: O(n^2), Space: O(1)"""
<|body_0|>
def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> int:
"""Sliding Window, Time: O(n), Space: O(1)"""
<|bod... | stack_v2_sparse_classes_75kplus_train_005855 | 1,521 | no_license | [
{
"docstring": "Brute Force, Time: O(n^2), Space: O(1)",
"name": "numSubarrayProductLessThanK",
"signature": "def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> int"
},
{
"docstring": "Sliding Window, Time: O(n), Space: O(1)",
"name": "numSubarrayProductLessThanK",
"signat... | 2 | stack_v2_sparse_classes_30k_train_004555 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> int: Brute Force, Time: O(n^2), Space: O(1)
- def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> int: Brute Force, Time: O(n^2), Space: O(1)
- def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> ... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> int:
"""Brute Force, Time: O(n^2), Space: O(1)"""
<|body_0|>
def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> int:
"""Sliding Window, Time: O(n), Space: O(1)"""
<|bod... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def numSubarrayProductLessThanK(self, nums: List[int], k: int) -> int:
"""Brute Force, Time: O(n^2), Space: O(1)"""
n = len(nums)
ans = 0
for i in range(n):
prod = 1
for j in range(i, n):
prod *= nums[j]
if prod ... | the_stack_v2_python_sparse | python/713-Subarray Product Less Than K.py | cwza/leetcode | train | 0 | |
35eb14f18f7d14b130427e4c9492aa8f7a77a4b4 | [
"pows = np.array(pows)\nnx = len(pows)\nmaxpow = np.max(pows)\nif np.any(pows < 0):\n raise ValueError('All elements of pows must be non-negative integers.')\nsuper().__init__(self._monomial, nf=1, nx=nx, maxderiv=None, zlevel=maxpow)\nself.pows = pows\nreturn",
"nd, nvar = dfun.ndnvar(deriv, var, self.nx)\nif... | <|body_start_0|>
pows = np.array(pows)
nx = len(pows)
maxpow = np.max(pows)
if np.any(pows < 0):
raise ValueError('All elements of pows must be non-negative integers.')
super().__init__(self._monomial, nf=1, nx=nx, maxderiv=None, zlevel=maxpow)
self.pows = pow... | The monominal in multiple variables | Monomial | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Monomial:
"""The monominal in multiple variables"""
def __init__(self, pows):
"""Parameters ---------- pows : array_like A list of non-negative integer exponents."""
<|body_0|>
def _monomial(self, X, deriv=0, out=None, var=None):
"""evaluation function"""
... | stack_v2_sparse_classes_75kplus_train_005856 | 39,055 | permissive | [
{
"docstring": "Parameters ---------- pows : array_like A list of non-negative integer exponents.",
"name": "__init__",
"signature": "def __init__(self, pows)"
},
{
"docstring": "evaluation function",
"name": "_monomial",
"signature": "def _monomial(self, X, deriv=0, out=None, var=None)"... | 2 | stack_v2_sparse_classes_30k_train_049466 | Implement the Python class `Monomial` described below.
Class description:
The monominal in multiple variables
Method signatures and docstrings:
- def __init__(self, pows): Parameters ---------- pows : array_like A list of non-negative integer exponents.
- def _monomial(self, X, deriv=0, out=None, var=None): evaluatio... | Implement the Python class `Monomial` described below.
Class description:
The monominal in multiple variables
Method signatures and docstrings:
- def __init__(self, pows): Parameters ---------- pows : array_like A list of non-negative integer exponents.
- def _monomial(self, X, deriv=0, out=None, var=None): evaluatio... | c6341a58331deef3728cc43c627c556139deb673 | <|skeleton|>
class Monomial:
"""The monominal in multiple variables"""
def __init__(self, pows):
"""Parameters ---------- pows : array_like A list of non-negative integer exponents."""
<|body_0|>
def _monomial(self, X, deriv=0, out=None, var=None):
"""evaluation function"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Monomial:
"""The monominal in multiple variables"""
def __init__(self, pows):
"""Parameters ---------- pows : array_like A list of non-negative integer exponents."""
pows = np.array(pows)
nx = len(pows)
maxpow = np.max(pows)
if np.any(pows < 0):
raise V... | the_stack_v2_python_sparse | nitrogen/special.py | bchangala/nitrogen | train | 11 |
03d7ef71403e445c77fc720711810bb338f93751 | [
"self.mask = np.copy(mask)\nself.masked_vol = np.copy(vol)\nself.masked_vol[self.mask == 0] = 0",
"min_intensity = np.float64(np.min(self.masked_vol[self.masked_vol != 0]))\nmax_intensity = np.max(self.masked_vol)\nw1 = np.copy(self.masked_vol)\nw1 = (w1 - min_intensity) / (max_intensity - min_intensity)\nw1[w1 <... | <|body_start_0|>
self.mask = np.copy(mask)
self.masked_vol = np.copy(vol)
self.masked_vol[self.mask == 0] = 0
<|end_body_0|>
<|body_start_1|>
min_intensity = np.float64(np.min(self.masked_vol[self.masked_vol != 0]))
max_intensity = np.max(self.masked_vol)
w1 = np.copy(se... | vertices | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class vertices:
def __init__(self, mask, vol):
"""Constructor"""
<|body_0|>
def compute_w1(self):
"""Compute W1 for vertex weight computation"""
<|body_1|>
def compute_w2(self):
"""Compute W2 for vertex weight computation; Distance from boundaries."""
... | stack_v2_sparse_classes_75kplus_train_005857 | 8,906 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, mask, vol)"
},
{
"docstring": "Compute W1 for vertex weight computation",
"name": "compute_w1",
"signature": "def compute_w1(self)"
},
{
"docstring": "Compute W2 for vertex weight computation; Dist... | 5 | stack_v2_sparse_classes_30k_train_015466 | Implement the Python class `vertices` described below.
Class description:
Implement the vertices class.
Method signatures and docstrings:
- def __init__(self, mask, vol): Constructor
- def compute_w1(self): Compute W1 for vertex weight computation
- def compute_w2(self): Compute W2 for vertex weight computation; Dist... | Implement the Python class `vertices` described below.
Class description:
Implement the vertices class.
Method signatures and docstrings:
- def __init__(self, mask, vol): Constructor
- def compute_w1(self): Compute W1 for vertex weight computation
- def compute_w2(self): Compute W2 for vertex weight computation; Dist... | f966200d09d03a75ff9f56ab5c08b03b7bc3aadb | <|skeleton|>
class vertices:
def __init__(self, mask, vol):
"""Constructor"""
<|body_0|>
def compute_w1(self):
"""Compute W1 for vertex weight computation"""
<|body_1|>
def compute_w2(self):
"""Compute W2 for vertex weight computation; Distance from boundaries."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class vertices:
def __init__(self, mask, vol):
"""Constructor"""
self.mask = np.copy(mask)
self.masked_vol = np.copy(vol)
self.masked_vol[self.mask == 0] = 0
def compute_w1(self):
"""Compute W1 for vertex weight computation"""
min_intensity = np.float64(np.min(se... | the_stack_v2_python_sparse | src/jupyter/kkarbasi/cobalt_tractography/cobalt_tractography/tractography.py | neurodata-cobalt/cobalt | train | 0 | |
54c6c231c648e443008bc18d68c301b635f4b6e6 | [
"self.training_path = kwargs.get('train_data_path')\nself.predict_path = kwargs.get('predict_data_path')\nself.output_path = kwargs.get('output_path')",
"training_dataset = load_fn(self.training_path)\nprediction_dataset = load_fn(self.predict_path)\nmodel = train_fn(training_dataset, **options)\npredictions = so... | <|body_start_0|>
self.training_path = kwargs.get('train_data_path')
self.predict_path = kwargs.get('predict_data_path')
self.output_path = kwargs.get('output_path')
<|end_body_0|>
<|body_start_1|>
training_dataset = load_fn(self.training_path)
prediction_dataset = load_fn(self.p... | Generic model class for fitting a recommendation model. | Model | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
"""Generic model class for fitting a recommendation model."""
def __init__(self, **kwargs):
"""Initialize a Model object."""
<|body_0|>
def train(self, load_fn, train_fn, predict_fn, store_fn, **options):
"""Given the functions indicated below, load the tr... | stack_v2_sparse_classes_75kplus_train_005858 | 8,553 | permissive | [
{
"docstring": "Initialize a Model object.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Given the functions indicated below, load the training and prediction datasets, train with the training dataset and predict the values for the prediction dataset. Write... | 2 | stack_v2_sparse_classes_30k_train_026634 | Implement the Python class `Model` described below.
Class description:
Generic model class for fitting a recommendation model.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialize a Model object.
- def train(self, load_fn, train_fn, predict_fn, store_fn, **options): Given the functions indicat... | Implement the Python class `Model` described below.
Class description:
Generic model class for fitting a recommendation model.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialize a Model object.
- def train(self, load_fn, train_fn, predict_fn, store_fn, **options): Given the functions indicat... | 5e0c9efe3405245119bf5aa9bd81a4ca5159eab1 | <|skeleton|>
class Model:
"""Generic model class for fitting a recommendation model."""
def __init__(self, **kwargs):
"""Initialize a Model object."""
<|body_0|>
def train(self, load_fn, train_fn, predict_fn, store_fn, **options):
"""Given the functions indicated below, load the tr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Model:
"""Generic model class for fitting a recommendation model."""
def __init__(self, **kwargs):
"""Initialize a Model object."""
self.training_path = kwargs.get('train_data_path')
self.predict_path = kwargs.get('predict_data_path')
self.output_path = kwargs.get('output_... | the_stack_v2_python_sparse | project2/src/train.py | errikos/ml-makarona | train | 0 |
a211f98408db22db80974db7affa69d671d0ca0e | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Invitation()",
"from .entity import Entity\nfrom .invited_user_message_info import InvitedUserMessageInfo\nfrom .user import User\nfrom .entity import Entity\nfrom .invited_user_message_info import InvitedUserMessageInfo\nfrom .user im... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Invitation()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .invited_user_message_info import InvitedUserMessageInfo
from .user import User
from .entity ... | Invitation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Invitation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Invitation:
"""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: Invi... | stack_v2_sparse_classes_75kplus_train_005859 | 6,140 | 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: Invitation",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(pa... | 3 | null | Implement the Python class `Invitation` described below.
Class description:
Implement the Invitation class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Invitation: Creates a new instance of the appropriate class based on discriminator value Args: pa... | Implement the Python class `Invitation` described below.
Class description:
Implement the Invitation class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Invitation: Creates a new instance of the appropriate class based on discriminator value Args: pa... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Invitation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Invitation:
"""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: Invi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Invitation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Invitation:
"""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: Invitation"""
... | the_stack_v2_python_sparse | msgraph/generated/models/invitation.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
080f763229dc6df2d2a54807ffab2b120f726c4e | [
"super(PointWiseFeedForward, self).__init__()\nself.conv1 = torch.nn.Conv1d(hidden_units, hidden_units, kernel_size=1)\nself.dropout1 = torch.nn.Dropout(p=dropout_rate)\nself.relu = torch.nn.ReLU()\nself.conv2 = torch.nn.Conv1d(hidden_units, hidden_units, kernel_size=1)\nself.dropout2 = torch.nn.Dropout(p=dropout_r... | <|body_start_0|>
super(PointWiseFeedForward, self).__init__()
self.conv1 = torch.nn.Conv1d(hidden_units, hidden_units, kernel_size=1)
self.dropout1 = torch.nn.Dropout(p=dropout_rate)
self.relu = torch.nn.ReLU()
self.conv2 = torch.nn.Conv1d(hidden_units, hidden_units, kernel_size=... | PointWise forward Module. Args: torch ([type]): [description] | PointWiseFeedForward | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointWiseFeedForward:
"""PointWise forward Module. Args: torch ([type]): [description]"""
def __init__(self, hidden_units, dropout_rate):
"""Class Initialization. Args: hidden_units ([int]): Embedding dimension. dropout_rate ([float]): dropout rate."""
<|body_0|>
def for... | stack_v2_sparse_classes_75kplus_train_005860 | 15,823 | permissive | [
{
"docstring": "Class Initialization. Args: hidden_units ([int]): Embedding dimension. dropout_rate ([float]): dropout rate.",
"name": "__init__",
"signature": "def __init__(self, hidden_units, dropout_rate)"
},
{
"docstring": "Forward function. Args: inputs ([type]): [description] Returns: [typ... | 2 | stack_v2_sparse_classes_30k_train_030429 | Implement the Python class `PointWiseFeedForward` described below.
Class description:
PointWise forward Module. Args: torch ([type]): [description]
Method signatures and docstrings:
- def __init__(self, hidden_units, dropout_rate): Class Initialization. Args: hidden_units ([int]): Embedding dimension. dropout_rate ([... | Implement the Python class `PointWiseFeedForward` described below.
Class description:
PointWise forward Module. Args: torch ([type]): [description]
Method signatures and docstrings:
- def __init__(self, hidden_units, dropout_rate): Class Initialization. Args: hidden_units ([int]): Embedding dimension. dropout_rate ([... | 625189d5e1002a3edc27c3e3ce075fddf7ae1c92 | <|skeleton|>
class PointWiseFeedForward:
"""PointWise forward Module. Args: torch ([type]): [description]"""
def __init__(self, hidden_units, dropout_rate):
"""Class Initialization. Args: hidden_units ([int]): Embedding dimension. dropout_rate ([float]): dropout rate."""
<|body_0|>
def for... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PointWiseFeedForward:
"""PointWise forward Module. Args: torch ([type]): [description]"""
def __init__(self, hidden_units, dropout_rate):
"""Class Initialization. Args: hidden_units ([int]): Embedding dimension. dropout_rate ([float]): dropout rate."""
super(PointWiseFeedForward, self).__... | the_stack_v2_python_sparse | beta_rec/models/tisasrec.py | beta-team/beta-recsys | train | 156 |
9fbc97084b552f68d7c4b3cff0648c0abcbeaa9b | [
"Formulation.__init__(self, space, **kwargs)\nself._vertices = vertices\nif weights:\n assert len(vertices) == len(weights), 'if weights are provided, must be same dim as vertices'\nelse:\n weights = np.ones(len(vertices))\nself._weights = weights",
"C = []\nfor p in self._actions:\n M_p = np.ones(len(p)... | <|body_start_0|>
Formulation.__init__(self, space, **kwargs)
self._vertices = vertices
if weights:
assert len(vertices) == len(weights), 'if weights are provided, must be same dim as vertices'
else:
weights = np.ones(len(vertices))
self._weights = weights
... | VerticesNotOnInterior | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VerticesNotOnInterior:
def __init__(self, space, vertices=[], weights=[], **kwargs):
"""statement: 'These vertices must be on the boundary of tile placements' -- or-- 'These vertices cannot be on the interior of tile placements' :param space: mesh space :param vertices: list of indices""... | stack_v2_sparse_classes_75kplus_train_005861 | 12,011 | no_license | [
{
"docstring": "statement: 'These vertices must be on the boundary of tile placements' -- or-- 'These vertices cannot be on the interior of tile placements' :param space: mesh space :param vertices: list of indices",
"name": "__init__",
"signature": "def __init__(self, space, vertices=[], weights=[], **... | 3 | stack_v2_sparse_classes_30k_train_015443 | Implement the Python class `VerticesNotOnInterior` described below.
Class description:
Implement the VerticesNotOnInterior class.
Method signatures and docstrings:
- def __init__(self, space, vertices=[], weights=[], **kwargs): statement: 'These vertices must be on the boundary of tile placements' -- or-- 'These vert... | Implement the Python class `VerticesNotOnInterior` described below.
Class description:
Implement the VerticesNotOnInterior class.
Method signatures and docstrings:
- def __init__(self, space, vertices=[], weights=[], **kwargs): statement: 'These vertices must be on the boundary of tile placements' -- or-- 'These vert... | 5928c1ef1eb0d60bfa0726227e690c0a66570f45 | <|skeleton|>
class VerticesNotOnInterior:
def __init__(self, space, vertices=[], weights=[], **kwargs):
"""statement: 'These vertices must be on the boundary of tile placements' -- or-- 'These vertices cannot be on the interior of tile placements' :param space: mesh space :param vertices: list of indices""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VerticesNotOnInterior:
def __init__(self, space, vertices=[], weights=[], **kwargs):
"""statement: 'These vertices must be on the boundary of tile placements' -- or-- 'These vertices cannot be on the interior of tile placements' :param space: mesh space :param vertices: list of indices"""
Form... | the_stack_v2_python_sparse | src/cvopt/formulate/formulations.py | psavine42/juststuff | train | 0 | |
c0e42e8e9c17861f7169739cd1683759866ee304 | [
"self.disable_vlan = disable_vlan\nself.interface_name = interface_name\nself.vlan = vlan",
"if dictionary is None:\n return None\ndisable_vlan = dictionary.get('disableVlan')\ninterface_name = dictionary.get('interfaceName')\nvlan = dictionary.get('vlan')\nreturn cls(disable_vlan, interface_name, vlan)"
] | <|body_start_0|>
self.disable_vlan = disable_vlan
self.interface_name = interface_name
self.vlan = vlan
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
disable_vlan = dictionary.get('disableVlan')
interface_name = dictionary.get('interfaceN... | Implementation of the 'VlanParameters' model. Specifies VLAN parameters for the restore operation. Attributes: disable_vlan (bool): Specifies whether to use the VIPs even when VLANs are configured on the Cluster. If configured, VLAN IP addresses are used by default. If VLANs are not configured, this flag is ignored. Se... | VlanParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VlanParameters:
"""Implementation of the 'VlanParameters' model. Specifies VLAN parameters for the restore operation. Attributes: disable_vlan (bool): Specifies whether to use the VIPs even when VLANs are configured on the Cluster. If configured, VLAN IP addresses are used by default. If VLANs ar... | stack_v2_sparse_classes_75kplus_train_005862 | 2,414 | permissive | [
{
"docstring": "Constructor for the VlanParameters class",
"name": "__init__",
"signature": "def __init__(self, disable_vlan=None, interface_name=None, vlan=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of... | 2 | null | Implement the Python class `VlanParameters` described below.
Class description:
Implementation of the 'VlanParameters' model. Specifies VLAN parameters for the restore operation. Attributes: disable_vlan (bool): Specifies whether to use the VIPs even when VLANs are configured on the Cluster. If configured, VLAN IP add... | Implement the Python class `VlanParameters` described below.
Class description:
Implementation of the 'VlanParameters' model. Specifies VLAN parameters for the restore operation. Attributes: disable_vlan (bool): Specifies whether to use the VIPs even when VLANs are configured on the Cluster. If configured, VLAN IP add... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VlanParameters:
"""Implementation of the 'VlanParameters' model. Specifies VLAN parameters for the restore operation. Attributes: disable_vlan (bool): Specifies whether to use the VIPs even when VLANs are configured on the Cluster. If configured, VLAN IP addresses are used by default. If VLANs ar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VlanParameters:
"""Implementation of the 'VlanParameters' model. Specifies VLAN parameters for the restore operation. Attributes: disable_vlan (bool): Specifies whether to use the VIPs even when VLANs are configured on the Cluster. If configured, VLAN IP addresses are used by default. If VLANs are not configu... | the_stack_v2_python_sparse | cohesity_management_sdk/models/vlan_parameters.py | cohesity/management-sdk-python | train | 24 |
7cafc0356301b96505e5f57c2cfab529384dbe38 | [
"ans = 0\ntotalLength = 0\nstack = [(-1, 0)]\nfor p in input.split('\\n'):\n currDepth = p.count('\\t')\n currLength = len(p.replace('\\t', ''))\n depth, length = stack[-1]\n while depth >= currDepth:\n totalLength -= length\n stack.pop()\n depth, length = stack[-1]\n if currDept... | <|body_start_0|>
ans = 0
totalLength = 0
stack = [(-1, 0)]
for p in input.split('\n'):
currDepth = p.count('\t')
currLength = len(p.replace('\t', ''))
depth, length = stack[-1]
while depth >= currDepth:
totalLength -= length... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthLongestPath(self, input):
""":type input: str :rtype: int"""
<|body_0|>
def lengthLongestPath2(self, input):
""":type input: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ans = 0
totalLength = 0
... | stack_v2_sparse_classes_75kplus_train_005863 | 6,317 | no_license | [
{
"docstring": ":type input: str :rtype: int",
"name": "lengthLongestPath",
"signature": "def lengthLongestPath(self, input)"
},
{
"docstring": ":type input: str :rtype: int",
"name": "lengthLongestPath2",
"signature": "def lengthLongestPath2(self, input)"
}
] | 2 | stack_v2_sparse_classes_30k_train_023120 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthLongestPath(self, input): :type input: str :rtype: int
- def lengthLongestPath2(self, input): :type input: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthLongestPath(self, input): :type input: str :rtype: int
- def lengthLongestPath2(self, input): :type input: str :rtype: int
<|skeleton|>
class Solution:
def length... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def lengthLongestPath(self, input):
""":type input: str :rtype: int"""
<|body_0|>
def lengthLongestPath2(self, input):
""":type input: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def lengthLongestPath(self, input):
""":type input: str :rtype: int"""
ans = 0
totalLength = 0
stack = [(-1, 0)]
for p in input.split('\n'):
currDepth = p.count('\t')
currLength = len(p.replace('\t', ''))
depth, length = sta... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00388.Longest_Absolute_File_Path.py | roger6blog/LeetCode | train | 0 | |
b9982c155149e77bf1e62c06ec173ba725160e20 | [
"self.mPos = position\nself.mLen1 = 100\nself.mLen2 = 100\nself.mAlpha = 0\nself.mPhi = 0\nself.mObsts = obstacles",
"self.mAlpha = alpha\nself.mPhi = phi\nbase = self.mPos\nend1 = (base[0] + self.mLen1 * math.cos(alpha), base[1] + self.mLen1 * math.sin(alpha))\nend2 = (end1[0] + self.mLen2 * math.cos(phi + alpha... | <|body_start_0|>
self.mPos = position
self.mLen1 = 100
self.mLen2 = 100
self.mAlpha = 0
self.mPhi = 0
self.mObsts = obstacles
<|end_body_0|>
<|body_start_1|>
self.mAlpha = alpha
self.mPhi = phi
base = self.mPos
end1 = (base[0] + self.mLen1... | description of class | RobotArm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RobotArm:
"""description of class"""
def __init__(self, position, obstacles):
"""Create a 1-joint robot arm @parm position: the base position. @parm obstacles: a list of spheres as obstacles."""
<|body_0|>
def setParams(self, alpha, phi):
"""Set angles of the rob... | stack_v2_sparse_classes_75kplus_train_005864 | 3,453 | no_license | [
{
"docstring": "Create a 1-joint robot arm @parm position: the base position. @parm obstacles: a list of spheres as obstacles.",
"name": "__init__",
"signature": "def __init__(self, position, obstacles)"
},
{
"docstring": "Set angles of the robot arm, return if collide with obstacles.",
"nam... | 5 | stack_v2_sparse_classes_30k_train_045355 | Implement the Python class `RobotArm` described below.
Class description:
description of class
Method signatures and docstrings:
- def __init__(self, position, obstacles): Create a 1-joint robot arm @parm position: the base position. @parm obstacles: a list of spheres as obstacles.
- def setParams(self, alpha, phi): ... | Implement the Python class `RobotArm` described below.
Class description:
description of class
Method signatures and docstrings:
- def __init__(self, position, obstacles): Create a 1-joint robot arm @parm position: the base position. @parm obstacles: a list of spheres as obstacles.
- def setParams(self, alpha, phi): ... | 98724e32b932da0e92fc6354f7750ff0558f3005 | <|skeleton|>
class RobotArm:
"""description of class"""
def __init__(self, position, obstacles):
"""Create a 1-joint robot arm @parm position: the base position. @parm obstacles: a list of spheres as obstacles."""
<|body_0|>
def setParams(self, alpha, phi):
"""Set angles of the rob... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RobotArm:
"""description of class"""
def __init__(self, position, obstacles):
"""Create a 1-joint robot arm @parm position: the base position. @parm obstacles: a list of spheres as obstacles."""
self.mPos = position
self.mLen1 = 100
self.mLen2 = 100
self.mAlpha = 0... | the_stack_v2_python_sparse | SphereSamplingMotionPlanning/RobotArm.py | IanZhang1990/Robotics-MotionPlanning | train | 0 |
cc95fc34723ddc51a7162f768f2b4cae9ab980bd | [
"assert isinstance(errors, int) or errors in ('raise', 'ignore', 'report')\nself.function = function\nself.errors = errors\nself.error_count = 0",
"try:\n return self.function(*args, **kwds)\nexcept Exception as e:\n self.error_count += 1\n if self.errors == 'raise':\n raise\n if self.errors ==... | <|body_start_0|>
assert isinstance(errors, int) or errors in ('raise', 'ignore', 'report')
self.function = function
self.errors = errors
self.error_count = 0
<|end_body_0|>
<|body_start_1|>
try:
return self.function(*args, **kwds)
except Exception as e:
... | Wraps a function call to catch and report exceptions. | LogErrors | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogErrors:
"""Wraps a function call to catch and report exceptions."""
def __init__(self, function, errors):
""":param function: the function to wrap :param errors: either a number, indicating how many errors to report before ignoring them, or one of these strings: 'raise', meaning t... | stack_v2_sparse_classes_75kplus_train_005865 | 1,450 | permissive | [
{
"docstring": ":param function: the function to wrap :param errors: either a number, indicating how many errors to report before ignoring them, or one of these strings: 'raise', meaning to raise an exception 'ignore', meaning to ignore all errors 'report', meaning to report all errors",
"name": "__init__",... | 2 | stack_v2_sparse_classes_30k_train_031237 | Implement the Python class `LogErrors` described below.
Class description:
Wraps a function call to catch and report exceptions.
Method signatures and docstrings:
- def __init__(self, function, errors): :param function: the function to wrap :param errors: either a number, indicating how many errors to report before i... | Implement the Python class `LogErrors` described below.
Class description:
Wraps a function call to catch and report exceptions.
Method signatures and docstrings:
- def __init__(self, function, errors): :param function: the function to wrap :param errors: either a number, indicating how many errors to report before i... | fd97e6c651a4bbcade64733847f4eec8f7704b7c | <|skeleton|>
class LogErrors:
"""Wraps a function call to catch and report exceptions."""
def __init__(self, function, errors):
""":param function: the function to wrap :param errors: either a number, indicating how many errors to report before ignoring them, or one of these strings: 'raise', meaning t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LogErrors:
"""Wraps a function call to catch and report exceptions."""
def __init__(self, function, errors):
""":param function: the function to wrap :param errors: either a number, indicating how many errors to report before ignoring them, or one of these strings: 'raise', meaning to raise an ex... | the_stack_v2_python_sparse | bibliopixel/util/log_errors.py | dr-aryone/BiblioPixel | train | 2 |
4188f54d95e85a21e0ba58a3c913bd827c174202 | [
"counts = 0\nis_primes = [1] * n\nfor i in range(2, n):\n if is_primes[i]:\n counts += 1\n for j in range(i * i, n, i):\n is_primes[j] = 0\nreturn counts",
"primes = []\nis_primes = [1] * n\nfor i in range(2, n):\n if is_primes[i] == 1:\n primes.append(i)\n j = 0\n whil... | <|body_start_0|>
counts = 0
is_primes = [1] * n
for i in range(2, n):
if is_primes[i]:
counts += 1
for j in range(i * i, n, i):
is_primes[j] = 0
return counts
<|end_body_0|>
<|body_start_1|>
primes = []
is_p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countPrimes(self, n: int) -> int:
"""埃氏筛 :param n: :return:"""
<|body_0|>
def countPrimes1(self, n: int) -> int:
"""线性筛 :param n: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
counts = 0
is_primes = [1] * n
f... | stack_v2_sparse_classes_75kplus_train_005866 | 1,697 | no_license | [
{
"docstring": "埃氏筛 :param n: :return:",
"name": "countPrimes",
"signature": "def countPrimes(self, n: int) -> int"
},
{
"docstring": "线性筛 :param n: :return:",
"name": "countPrimes1",
"signature": "def countPrimes1(self, n: int) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_046229 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n: int) -> int: 埃氏筛 :param n: :return:
- def countPrimes1(self, n: int) -> int: 线性筛 :param n: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n: int) -> int: 埃氏筛 :param n: :return:
- def countPrimes1(self, n: int) -> int: 线性筛 :param n: :return:
<|skeleton|>
class Solution:
def countPrimes(se... | 578cacff5851c5c2522981693c34e3c318002d30 | <|skeleton|>
class Solution:
def countPrimes(self, n: int) -> int:
"""埃氏筛 :param n: :return:"""
<|body_0|>
def countPrimes1(self, n: int) -> int:
"""线性筛 :param n: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countPrimes(self, n: int) -> int:
"""埃氏筛 :param n: :return:"""
counts = 0
is_primes = [1] * n
for i in range(2, n):
if is_primes[i]:
counts += 1
for j in range(i * i, n, i):
is_primes[j] = 0
r... | the_stack_v2_python_sparse | 计数质数.py | cjrzs/MyLeetCode | train | 8 | |
b2390f948ae8888d5f30f6c382ed2705667eca12 | [
"if token:\n user = self.validate_token(token)\n if user:\n password_form = PasswordForm().get_form()\n self.render_template('user/password.html', form=password_form, token=token)\n else:\n error_message = _('Sorry, your link is expired, please try again.')\n logging.info(\"(Pro... | <|body_start_0|>
if token:
user = self.validate_token(token)
if user:
password_form = PasswordForm().get_form()
self.render_template('user/password.html', form=password_form, token=token)
else:
error_message = _('Sorry, your lin... | ResetPasswordHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResetPasswordHandler:
def get(self, token=None):
"""Someone coming back with a password reset token"""
<|body_0|>
def post(self):
"""Someone forgot their password, generate a token and send email"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if to... | stack_v2_sparse_classes_75kplus_train_005867 | 5,630 | no_license | [
{
"docstring": "Someone coming back with a password reset token",
"name": "get",
"signature": "def get(self, token=None)"
},
{
"docstring": "Someone forgot their password, generate a token and send email",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `ResetPasswordHandler` described below.
Class description:
Implement the ResetPasswordHandler class.
Method signatures and docstrings:
- def get(self, token=None): Someone coming back with a password reset token
- def post(self): Someone forgot their password, generate a token and send emai... | Implement the Python class `ResetPasswordHandler` described below.
Class description:
Implement the ResetPasswordHandler class.
Method signatures and docstrings:
- def get(self, token=None): Someone coming back with a password reset token
- def post(self): Someone forgot their password, generate a token and send emai... | c81873cff6f51a2326833c47557f66204c048779 | <|skeleton|>
class ResetPasswordHandler:
def get(self, token=None):
"""Someone coming back with a password reset token"""
<|body_0|>
def post(self):
"""Someone forgot their password, generate a token and send email"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResetPasswordHandler:
def get(self, token=None):
"""Someone coming back with a password reset token"""
if token:
user = self.validate_token(token)
if user:
password_form = PasswordForm().get_form()
self.render_template('user/password.html... | the_stack_v2_python_sparse | GAE/veosan/handler/user_pkg/password_handler.py | deltron/veosan | train | 0 | |
adfe19b9cf9c1ef924d9da4b27a34313254058f7 | [
"fake_command_file = 'cros_command_test.py'\nfiltered_file = 'cros_command_unittest.py'\nmydir = 'mydir'\nself.PatchObject(glob, 'glob', return_value=[fake_command_file, filtered_file])\nself.assertEqual(command._FindModules(mydir), [fake_command_file])",
"fake_module = 'cros_command_test'\nfake_command_file = os... | <|body_start_0|>
fake_command_file = 'cros_command_test.py'
filtered_file = 'cros_command_unittest.py'
mydir = 'mydir'
self.PatchObject(glob, 'glob', return_value=[fake_command_file, filtered_file])
self.assertEqual(command._FindModules(mydir), [fake_command_file])
<|end_body_0|>... | This test class tests that we can load modules correctly. | CommandTest | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommandTest:
"""This test class tests that we can load modules correctly."""
def testFindModules(self):
"""Tests that we can return modules correctly when mocking out glob."""
<|body_0|>
def testLoadCommands(self):
"""Tests import commands correctly."""
<... | stack_v2_sparse_classes_75kplus_train_005868 | 4,291 | permissive | [
{
"docstring": "Tests that we can return modules correctly when mocking out glob.",
"name": "testFindModules",
"signature": "def testFindModules(self)"
},
{
"docstring": "Tests import commands correctly.",
"name": "testLoadCommands",
"signature": "def testLoadCommands(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_048600 | Implement the Python class `CommandTest` described below.
Class description:
This test class tests that we can load modules correctly.
Method signatures and docstrings:
- def testFindModules(self): Tests that we can return modules correctly when mocking out glob.
- def testLoadCommands(self): Tests import commands co... | Implement the Python class `CommandTest` described below.
Class description:
This test class tests that we can load modules correctly.
Method signatures and docstrings:
- def testFindModules(self): Tests that we can return modules correctly when mocking out glob.
- def testLoadCommands(self): Tests import commands co... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class CommandTest:
"""This test class tests that we can load modules correctly."""
def testFindModules(self):
"""Tests that we can return modules correctly when mocking out glob."""
<|body_0|>
def testLoadCommands(self):
"""Tests import commands correctly."""
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommandTest:
"""This test class tests that we can load modules correctly."""
def testFindModules(self):
"""Tests that we can return modules correctly when mocking out glob."""
fake_command_file = 'cros_command_test.py'
filtered_file = 'cros_command_unittest.py'
mydir = 'my... | the_stack_v2_python_sparse | third_party/chromite/cli/command_unittest.py | metux/chromium-suckless | train | 5 |
d73fcc40a7f87da5d45ec25788941593e69084b3 | [
"movies = response.xpath('//div[@class=\"box clearfix\"]/ul/li')\nfor movie in movies:\n item = Rrys2019Top24Item()\n movieType = movie.xpath('./em/text()').extract_first().strip()\n movieTop = movie.xpath('./span/text()').extract_first().strip()\n rid = movie.xpath('./a/@href').extract_first().strip().... | <|body_start_0|>
movies = response.xpath('//div[@class="box clearfix"]/ul/li')
for movie in movies:
item = Rrys2019Top24Item()
movieType = movie.xpath('./em/text()').extract_first().strip()
movieTop = movie.xpath('./span/text()').extract_first().strip()
ri... | Rrys2019Spider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rrys2019Spider:
def parse(self, response):
"""解析首页 获取最近 24 小时热门：排名、名称、类型、详情 url"""
<|body_0|>
def parse2(self, response):
"""解析详情页 获取：电影分级、本站排名、收藏次数、简介"""
<|body_1|>
def parse3(self, response):
"""从接口获取 浏览次数"""
<|body_2|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus_train_005869 | 3,320 | no_license | [
{
"docstring": "解析首页 获取最近 24 小时热门：排名、名称、类型、详情 url",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "解析详情页 获取：电影分级、本站排名、收藏次数、简介",
"name": "parse2",
"signature": "def parse2(self, response)"
},
{
"docstring": "从接口获取 浏览次数",
"name": "parse3",
"sig... | 3 | stack_v2_sparse_classes_30k_train_000180 | Implement the Python class `Rrys2019Spider` described below.
Class description:
Implement the Rrys2019Spider class.
Method signatures and docstrings:
- def parse(self, response): 解析首页 获取最近 24 小时热门：排名、名称、类型、详情 url
- def parse2(self, response): 解析详情页 获取：电影分级、本站排名、收藏次数、简介
- def parse3(self, response): 从接口获取 浏览次数 | Implement the Python class `Rrys2019Spider` described below.
Class description:
Implement the Rrys2019Spider class.
Method signatures and docstrings:
- def parse(self, response): 解析首页 获取最近 24 小时热门：排名、名称、类型、详情 url
- def parse2(self, response): 解析详情页 获取：电影分级、本站排名、收藏次数、简介
- def parse3(self, response): 从接口获取 浏览次数
<|skel... | 982ebae5e3256a274392a0e4c64dafd55226b8df | <|skeleton|>
class Rrys2019Spider:
def parse(self, response):
"""解析首页 获取最近 24 小时热门：排名、名称、类型、详情 url"""
<|body_0|>
def parse2(self, response):
"""解析详情页 获取：电影分级、本站排名、收藏次数、简介"""
<|body_1|>
def parse3(self, response):
"""从接口获取 浏览次数"""
<|body_2|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Rrys2019Spider:
def parse(self, response):
"""解析首页 获取最近 24 小时热门：排名、名称、类型、详情 url"""
movies = response.xpath('//div[@class="box clearfix"]/ul/li')
for movie in movies:
item = Rrys2019Top24Item()
movieType = movie.xpath('./em/text()').extract_first().strip()
... | the_stack_v2_python_sparse | Week_03/G20200389010137/rrys2019Top24_/rrys2019Top24/spiders/rrys2019.py | kavanchen/Python000-class01 | train | 0 | |
2874baaa24f1c2cdafe8577cd7b68d50be0329b1 | [
"items = range(15)\nall_items = set()\nfor _ in xrange(50):\n combination = random_combination(items, 5)\n all_items |= set(combination)\neq_(all_items, set(items))",
"items = range(15)\nfor _ in xrange(50):\n combination = random_combination(items, len(items))\n eq_(len(combination), len(set(combinat... | <|body_start_0|>
items = range(15)
all_items = set()
for _ in xrange(50):
combination = random_combination(items, 5)
all_items |= set(combination)
eq_(all_items, set(items))
<|end_body_0|>
<|body_start_1|>
items = range(15)
for _ in xrange(50):
... | Tests for ``random_combination()`` | RandomCombinationTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomCombinationTests:
"""Tests for ``random_combination()``"""
def test_psuedorandomness(self):
"""ensure different subsets of the iterable get returned over many samplings of random combinations"""
<|body_0|>
def test_no_replacement(self):
"""ensure that eleme... | stack_v2_sparse_classes_75kplus_train_005870 | 47,145 | no_license | [
{
"docstring": "ensure different subsets of the iterable get returned over many samplings of random combinations",
"name": "test_psuedorandomness",
"signature": "def test_psuedorandomness(self)"
},
{
"docstring": "ensure that elements are sampled without replacement",
"name": "test_no_replac... | 2 | stack_v2_sparse_classes_30k_train_048675 | Implement the Python class `RandomCombinationTests` described below.
Class description:
Tests for ``random_combination()``
Method signatures and docstrings:
- def test_psuedorandomness(self): ensure different subsets of the iterable get returned over many samplings of random combinations
- def test_no_replacement(sel... | Implement the Python class `RandomCombinationTests` described below.
Class description:
Tests for ``random_combination()``
Method signatures and docstrings:
- def test_psuedorandomness(self): ensure different subsets of the iterable get returned over many samplings of random combinations
- def test_no_replacement(sel... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class RandomCombinationTests:
"""Tests for ``random_combination()``"""
def test_psuedorandomness(self):
"""ensure different subsets of the iterable get returned over many samplings of random combinations"""
<|body_0|>
def test_no_replacement(self):
"""ensure that eleme... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RandomCombinationTests:
"""Tests for ``random_combination()``"""
def test_psuedorandomness(self):
"""ensure different subsets of the iterable get returned over many samplings of random combinations"""
items = range(15)
all_items = set()
for _ in xrange(50):
com... | the_stack_v2_python_sparse | repoData/erikrose-more-itertools/allPythonContent.py | aCoffeeYin/pyreco | train | 0 |
390ffa2a5858a7af46141971311853352efc9d7d | [
"last = None\nfor i in nums:\n if last == None:\n last = i\n elif last > i:\n return i\n else:\n last = i\nreturn nums[0]",
"start, end = (0, len(nums) - 1)\nwhile start <= end:\n mid = (start + end) / 2\n if mid > 0 and nums[mid - 1] > nums[mid]:\n return nums[mid]\n ... | <|body_start_0|>
last = None
for i in nums:
if last == None:
last = i
elif last > i:
return i
else:
last = i
return nums[0]
<|end_body_0|>
<|body_start_1|>
start, end = (0, len(nums) - 1)
while s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findMin_v2(self, nums):
"""Use binary search :param nums: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
last = None
for i in nums:
... | stack_v2_sparse_classes_75kplus_train_005871 | 1,017 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findMin",
"signature": "def findMin(self, nums)"
},
{
"docstring": "Use binary search :param nums: :return:",
"name": "findMin_v2",
"signature": "def findMin_v2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_054352 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMin(self, nums): :type nums: List[int] :rtype: int
- def findMin_v2(self, nums): Use binary search :param nums: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMin(self, nums): :type nums: List[int] :rtype: int
- def findMin_v2(self, nums): Use binary search :param nums: :return:
<|skeleton|>
class Solution:
def findMin(se... | 0b4f293260e5ffa52cb0434619bcbb73be7dd5a6 | <|skeleton|>
class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findMin_v2(self, nums):
"""Use binary search :param nums: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int"""
last = None
for i in nums:
if last == None:
last = i
elif last > i:
return i
else:
last = i
return nums[0]
def fin... | the_stack_v2_python_sparse | LeetCode/153_Find_Minimum_in_Rotated_Sorted_Array.py | wangruowen/leetcode_practice | train | 0 | |
d82e1222fa043dd9194812e0d5ef1447152d9c40 | [
"n = len(A)\nprefix_sum = [0 for _ in range(n + 1)]\nfor i in range(1, n + 1):\n prefix_sum[i] = prefix_sum[i - 1] + A[i - 1]\nF = {}\nself.dfs(A, n, prefix_sum, F, K)\nreturn F[n, K]",
"if l < k:\n return -float('inf')\nif (l, k) not in F:\n if k == 1:\n ret = prefix_sum[l] / l\n else:\n ... | <|body_start_0|>
n = len(A)
prefix_sum = [0 for _ in range(n + 1)]
for i in range(1, n + 1):
prefix_sum[i] = prefix_sum[i - 1] + A[i - 1]
F = {}
self.dfs(A, n, prefix_sum, F, K)
return F[n, K]
<|end_body_0|>
<|body_start_1|>
if l < k:
retu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestSumOfAverages(self, A: List[int], K: int) -> float:
"""Memoized Backtracking + Prefix sum My first hunch is correct Complexity O(N^2 * K), mark sum and different way of forming groups (inserting dividers) calculating each F[l, k] will need O(N) time, thus total O(n^2... | stack_v2_sparse_classes_75kplus_train_005872 | 2,622 | no_license | [
{
"docstring": "Memoized Backtracking + Prefix sum My first hunch is correct Complexity O(N^2 * K), mark sum and different way of forming groups (inserting dividers) calculating each F[l, k] will need O(N) time, thus total O(n^2 k)",
"name": "largestSumOfAverages",
"signature": "def largestSumOfAverages... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestSumOfAverages(self, A: List[int], K: int) -> float: Memoized Backtracking + Prefix sum My first hunch is correct Complexity O(N^2 * K), mark sum and different way of f... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestSumOfAverages(self, A: List[int], K: int) -> float: Memoized Backtracking + Prefix sum My first hunch is correct Complexity O(N^2 * K), mark sum and different way of f... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class Solution:
def largestSumOfAverages(self, A: List[int], K: int) -> float:
"""Memoized Backtracking + Prefix sum My first hunch is correct Complexity O(N^2 * K), mark sum and different way of forming groups (inserting dividers) calculating each F[l, k] will need O(N) time, thus total O(n^2... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def largestSumOfAverages(self, A: List[int], K: int) -> float:
"""Memoized Backtracking + Prefix sum My first hunch is correct Complexity O(N^2 * K), mark sum and different way of forming groups (inserting dividers) calculating each F[l, k] will need O(N) time, thus total O(n^2 k)"""
... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/LeetCode/813 Largest Sum of Averages.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
f9fbb6daf384254d9b6ea34657362af4cf8abfdb | [
"if hasattr(self, 'client'):\n context = {self.client_context_object_name: self.client}\nelse:\n client_slug = self.kwargs.get(self.client_slug_url_kwarg)\n if client_slug:\n client = get_object_or_404(Client, slug__iexact=client_slug)\n context = {self.client_context_object_name: client}\n ... | <|body_start_0|>
if hasattr(self, 'client'):
context = {self.client_context_object_name: self.client}
else:
client_slug = self.kwargs.get(self.client_slug_url_kwarg)
if client_slug:
client = get_object_or_404(Client, slug__iexact=client_slug)
... | OrderCreateClientMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderCreateClientMixin:
def get_context_data(self, **kwargs):
"""Добавляет клиента и объект в контекст заказа"""
<|body_0|>
def get_initial(self):
"""Добавляет клиента и объект в заказ"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if hasattr(self,... | stack_v2_sparse_classes_75kplus_train_005873 | 4,913 | permissive | [
{
"docstring": "Добавляет клиента и объект в контекст заказа",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstring": "Добавляет клиента и объект в заказ",
"name": "get_initial",
"signature": "def get_initial(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021396 | Implement the Python class `OrderCreateClientMixin` described below.
Class description:
Implement the OrderCreateClientMixin class.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Добавляет клиента и объект в контекст заказа
- def get_initial(self): Добавляет клиента и объект в заказ | Implement the Python class `OrderCreateClientMixin` described below.
Class description:
Implement the OrderCreateClientMixin class.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Добавляет клиента и объект в контекст заказа
- def get_initial(self): Добавляет клиента и объект в заказ
<|skel... | 7246b4f524d138d48aadf4866e0b218bb924f69c | <|skeleton|>
class OrderCreateClientMixin:
def get_context_data(self, **kwargs):
"""Добавляет клиента и объект в контекст заказа"""
<|body_0|>
def get_initial(self):
"""Добавляет клиента и объект в заказ"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OrderCreateClientMixin:
def get_context_data(self, **kwargs):
"""Добавляет клиента и объект в контекст заказа"""
if hasattr(self, 'client'):
context = {self.client_context_object_name: self.client}
else:
client_slug = self.kwargs.get(self.client_slug_url_kwarg)
... | the_stack_v2_python_sparse | locker/calc/utils.py | crowmurk/locker | train | 0 | |
bfa2d8ac032899dd7d685ac4f19e0b9d501c78ea | [
"Validate.required(unit_cost, 'unit_cost')\nValidate.non_negative(unit_cost, 'unit_cost')\nValidate.required(demand_quantity, 'demand_quantity')\nValidate.non_negative(demand_quantity, 'demand_quantity')\nreturn unit_cost * demand_quantity",
"Validate.required(ordering_cost, 'ordering_cost')\nValidate.non_negativ... | <|body_start_0|>
Validate.required(unit_cost, 'unit_cost')
Validate.non_negative(unit_cost, 'unit_cost')
Validate.required(demand_quantity, 'demand_quantity')
Validate.non_negative(demand_quantity, 'demand_quantity')
return unit_cost * demand_quantity
<|end_body_0|>
<|body_start... | Provides methods for calculating costs, both at the "detail" level (e.g. purchase cost, ordering cost, etc.) and at the "combined" level (i.e. total relevant cost (TRC) and total cost (TC). | Costs | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Costs:
"""Provides methods for calculating costs, both at the "detail" level (e.g. purchase cost, ordering cost, etc.) and at the "combined" level (i.e. total relevant cost (TRC) and total cost (TC)."""
def purchase_cost(unit_cost, demand_quantity):
"""Calculate the purchase cost - t... | stack_v2_sparse_classes_75kplus_train_005874 | 6,030 | no_license | [
{
"docstring": "Calculate the purchase cost - the total landed cost for acquiring product needed to satisfy a given amount of demand. Parameters ---------- unit_cost : int or float Cost per unit, in dollars demand_quantity : int The amount of demand, in units Returns ------- purchase_cost: float",
"name": "... | 6 | stack_v2_sparse_classes_30k_train_011711 | Implement the Python class `Costs` described below.
Class description:
Provides methods for calculating costs, both at the "detail" level (e.g. purchase cost, ordering cost, etc.) and at the "combined" level (i.e. total relevant cost (TRC) and total cost (TC).
Method signatures and docstrings:
- def purchase_cost(uni... | Implement the Python class `Costs` described below.
Class description:
Provides methods for calculating costs, both at the "detail" level (e.g. purchase cost, ordering cost, etc.) and at the "combined" level (i.e. total relevant cost (TRC) and total cost (TC).
Method signatures and docstrings:
- def purchase_cost(uni... | 230b7bead81265dfee2e0e5c5819ae7a9c46acbc | <|skeleton|>
class Costs:
"""Provides methods for calculating costs, both at the "detail" level (e.g. purchase cost, ordering cost, etc.) and at the "combined" level (i.e. total relevant cost (TRC) and total cost (TC)."""
def purchase_cost(unit_cost, demand_quantity):
"""Calculate the purchase cost - t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Costs:
"""Provides methods for calculating costs, both at the "detail" level (e.g. purchase cost, ordering cost, etc.) and at the "combined" level (i.e. total relevant cost (TRC) and total cost (TC)."""
def purchase_cost(unit_cost, demand_quantity):
"""Calculate the purchase cost - the total land... | the_stack_v2_python_sparse | costs.py | rickhaffey/supply-chain-python | train | 2 |
c755d8ac977aff1e7aed3d5ee69884c591fb2ed1 | [
"self.alpha = 0.1\nself.alphadecay = 1.0\nself.momentum = 0.0\nself.momentumvector = None\nself.rprop = False\nself.deltamax = 5.0\nself.deltamin = 0.01\nself.deltanull = 0.1\nself.etaplus = 1.2\nself.etaminus = 0.5\nself.lastgradient = None",
"assert isinstance(values, ndarray)\nself.values = values.copy()\nif s... | <|body_start_0|>
self.alpha = 0.1
self.alphadecay = 1.0
self.momentum = 0.0
self.momentumvector = None
self.rprop = False
self.deltamax = 5.0
self.deltamin = 0.01
self.deltanull = 0.1
self.etaplus = 1.2
self.etaminus = 0.5
self.last... | GradientDescent | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GradientDescent:
def __init__(self):
"""initialize algorithms with standard parameters (typical values given in parentheses)"""
<|body_0|>
def init(self, values):
"""call this to initialize data structures *after* algorithm to use has been selected :arg values: the l... | stack_v2_sparse_classes_75kplus_train_005875 | 5,966 | permissive | [
{
"docstring": "initialize algorithms with standard parameters (typical values given in parentheses)",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "call this to initialize data structures *after* algorithm to use has been selected :arg values: the list (or array) of p... | 3 | null | Implement the Python class `GradientDescent` described below.
Class description:
Implement the GradientDescent class.
Method signatures and docstrings:
- def __init__(self): initialize algorithms with standard parameters (typical values given in parentheses)
- def init(self, values): call this to initialize data stru... | Implement the Python class `GradientDescent` described below.
Class description:
Implement the GradientDescent class.
Method signatures and docstrings:
- def __init__(self): initialize algorithms with standard parameters (typical values given in parentheses)
- def init(self, values): call this to initialize data stru... | 33ead60704d126e58c10d458ddd1e5e5fd17b65d | <|skeleton|>
class GradientDescent:
def __init__(self):
"""initialize algorithms with standard parameters (typical values given in parentheses)"""
<|body_0|>
def init(self, values):
"""call this to initialize data structures *after* algorithm to use has been selected :arg values: the l... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GradientDescent:
def __init__(self):
"""initialize algorithms with standard parameters (typical values given in parentheses)"""
self.alpha = 0.1
self.alphadecay = 1.0
self.momentum = 0.0
self.momentumvector = None
self.rprop = False
self.deltamax = 5.0
... | the_stack_v2_python_sparse | pybrain/auxiliary/gradientdescent.py | pybrain2/pybrain2 | train | 14 | |
cb68199199f518639e8d7314347556e2be7fa244 | [
"triplet = [nums[0], None, None]\nfor elem in nums[1:]:\n if not triplet[1] and elem < triplet[0]:\n triplet[0] = elem\n elif not triplet[1] or (not triplet[2] and triplet[0] < elem < triplet[1]):\n triplet[1] = elem\n elif not triplet[2] and elem > triplet[1]:\n print(triplet)\n ... | <|body_start_0|>
triplet = [nums[0], None, None]
for elem in nums[1:]:
if not triplet[1] and elem < triplet[0]:
triplet[0] = elem
elif not triplet[1] or (not triplet[2] and triplet[0] < elem < triplet[1]):
triplet[1] = elem
elif not tri... | Solution | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def increasingTriplet(self, nums) -> bool:
"""the code is wrong, but it could be a reference of the right code. There is a hidden trick between two versions"""
<|body_0|>
def increasingTriplet(self, nums) -> bool:
"""trick: we can directly replace the small... | stack_v2_sparse_classes_75kplus_train_005876 | 2,078 | permissive | [
{
"docstring": "the code is wrong, but it could be a reference of the right code. There is a hidden trick between two versions",
"name": "increasingTriplet",
"signature": "def increasingTriplet(self, nums) -> bool"
},
{
"docstring": "trick: we can directly replace the small when meet a value sma... | 2 | stack_v2_sparse_classes_30k_train_051649 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def increasingTriplet(self, nums) -> bool: the code is wrong, but it could be a reference of the right code. There is a hidden trick between two versions
- def increasingTriplet(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def increasingTriplet(self, nums) -> bool: the code is wrong, but it could be a reference of the right code. There is a hidden trick between two versions
- def increasingTriplet(... | 226cecde136531341ce23cdf88529345be1912fc | <|skeleton|>
class Solution:
def increasingTriplet(self, nums) -> bool:
"""the code is wrong, but it could be a reference of the right code. There is a hidden trick between two versions"""
<|body_0|>
def increasingTriplet(self, nums) -> bool:
"""trick: we can directly replace the small... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def increasingTriplet(self, nums) -> bool:
"""the code is wrong, but it could be a reference of the right code. There is a hidden trick between two versions"""
triplet = [nums[0], None, None]
for elem in nums[1:]:
if not triplet[1] and elem < triplet[0]:
... | the_stack_v2_python_sparse | Leetcode/Intermediate/Array_and_string/334_Increasing_Triplet_Subsequence.py | ZR-Huang/AlgorithmsPractices | train | 1 | |
dbf36004be77fc1c80331e3a64a7ec8fde1ff267 | [
"partname = package.next_partname('/word/footer%d.xml')\ncontent_type = CT.WML_FOOTER\nelement = parse_xml(cls._default_footer_xml())\nreturn cls(partname, content_type, element, package)",
"path = os.path.join(os.path.split(__file__)[0], '..', 'templates', 'default-footer.xml')\nwith open(path, 'rb') as f:\n ... | <|body_start_0|>
partname = package.next_partname('/word/footer%d.xml')
content_type = CT.WML_FOOTER
element = parse_xml(cls._default_footer_xml())
return cls(partname, content_type, element, package)
<|end_body_0|>
<|body_start_1|>
path = os.path.join(os.path.split(__file__)[0]... | Definition of a section footer. | FooterPart | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FooterPart:
"""Definition of a section footer."""
def new(cls, package):
"""Return newly created footer part."""
<|body_0|>
def _default_footer_xml(cls):
"""Return bytes containing XML for a default footer part."""
<|body_1|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_75kplus_train_005877 | 1,717 | permissive | [
{
"docstring": "Return newly created footer part.",
"name": "new",
"signature": "def new(cls, package)"
},
{
"docstring": "Return bytes containing XML for a default footer part.",
"name": "_default_footer_xml",
"signature": "def _default_footer_xml(cls)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015577 | Implement the Python class `FooterPart` described below.
Class description:
Definition of a section footer.
Method signatures and docstrings:
- def new(cls, package): Return newly created footer part.
- def _default_footer_xml(cls): Return bytes containing XML for a default footer part. | Implement the Python class `FooterPart` described below.
Class description:
Definition of a section footer.
Method signatures and docstrings:
- def new(cls, package): Return newly created footer part.
- def _default_footer_xml(cls): Return bytes containing XML for a default footer part.
<|skeleton|>
class FooterPart... | 2bfcf6b9779bf1abd41e1bc42c27007127ddbefb | <|skeleton|>
class FooterPart:
"""Definition of a section footer."""
def new(cls, package):
"""Return newly created footer part."""
<|body_0|>
def _default_footer_xml(cls):
"""Return bytes containing XML for a default footer part."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FooterPart:
"""Definition of a section footer."""
def new(cls, package):
"""Return newly created footer part."""
partname = package.next_partname('/word/footer%d.xml')
content_type = CT.WML_FOOTER
element = parse_xml(cls._default_footer_xml())
return cls(partname, ... | the_stack_v2_python_sparse | anuvaad-etl/anuvaad-extractor/file_translator/etl-file-translator/docx/parts/hdrftr.py | project-anuvaad/anuvaad | train | 41 |
8c5e3965c769d433df6974223c9281e50d513eb7 | [
"assert bias.shape[0] == 1\nassert weight_hh.shape[0] == 1\nassert weight_hh.shape[1] == 1\nself.hidden_size: int = 1\nself.input_size: int = input_size\nself.bias: np.ndarray = bias\nself.weight_hh: np.ndarray = weight_hh\nself.weight_xh: np.ndarray = weight_xh\nself.hx: np.ndarray = np.asarray([])",
"if len(sel... | <|body_start_0|>
assert bias.shape[0] == 1
assert weight_hh.shape[0] == 1
assert weight_hh.shape[1] == 1
self.hidden_size: int = 1
self.input_size: int = input_size
self.bias: np.ndarray = bias
self.weight_hh: np.ndarray = weight_hh
self.weight_xh: np.ndar... | Small variation of the PyTorch implementation of the simple RNN-cell. | RNNCell | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNCell:
"""Small variation of the PyTorch implementation of the simple RNN-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the RNN-cell with the provided parameters. :param input_size: Number of inputs going int... | stack_v2_sparse_classes_75kplus_train_005878 | 1,677 | permissive | [
{
"docstring": "Create the RNN-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bias: Bias for the internal node :param weight_hh: Weight of the hidden-state connection :param weight_xh: Weight-vector from input to hidden state",
"name": "__init__",
"sign... | 2 | stack_v2_sparse_classes_30k_train_012225 | Implement the Python class `RNNCell` described below.
Class description:
Small variation of the PyTorch implementation of the simple RNN-cell.
Method signatures and docstrings:
- def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray): Create the RNN-cell with the provided ... | Implement the Python class `RNNCell` described below.
Class description:
Small variation of the PyTorch implementation of the simple RNN-cell.
Method signatures and docstrings:
- def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray): Create the RNN-cell with the provided ... | 818a4ce941536611c0f1780f7c4a6238f0e1884e | <|skeleton|>
class RNNCell:
"""Small variation of the PyTorch implementation of the simple RNN-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the RNN-cell with the provided parameters. :param input_size: Number of inputs going int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RNNCell:
"""Small variation of the PyTorch implementation of the simple RNN-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the RNN-cell with the provided parameters. :param input_size: Number of inputs going into the cell :p... | the_stack_v2_python_sparse | population/utils/rnn_cell_util/simple_rnn.py | RubenPants/EvolvableRNN | train | 1 |
a97217f2b360b28bebbbbb2f80da67c2b826e01e | [
"left = 0\nright = len(numbers) - 1\nres = []\nif len(numbers) < 2 or numbers == None:\n return res\nwhile left < right:\n t = numbers[left] + numbers[right]\n if t == target:\n res.append(left + 1)\n res.append(right + 1)\n break\n if t > target:\n right -= 1\n else:\n ... | <|body_start_0|>
left = 0
right = len(numbers) - 1
res = []
if len(numbers) < 2 or numbers == None:
return res
while left < right:
t = numbers[left] + numbers[right]
if t == target:
res.append(left + 1)
res.appen... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSumv2(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_75kplus_train_005879 | 969 | no_license | [
{
"docstring": ":type numbers: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def twoSum(self, numbers, target)"
},
{
"docstring": ":type numbers: List[int] :type target: int :rtype: List[int]",
"name": "twoSumv2",
"signature": "def twoSumv2(self, numbers... | 2 | stack_v2_sparse_classes_30k_val_001163 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, numbers, target): :type numbers: List[int] :type target: int :rtype: List[int]
- def twoSumv2(self, numbers, target): :type numbers: List[int] :type target: int ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, numbers, target): :type numbers: List[int] :type target: int :rtype: List[int]
- def twoSumv2(self, numbers, target): :type numbers: List[int] :type target: int ... | dbb9be177c5e572eb72a79508bb6e24f357d54b3 | <|skeleton|>
class Solution:
def twoSum(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSumv2(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoSum(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
left = 0
right = len(numbers) - 1
res = []
if len(numbers) < 2 or numbers == None:
return res
while left < right:
t = numbers[... | the_stack_v2_python_sparse | Leetcode/167. Two Sum II - Input array is sorted.py | GuanzhouSong/Leetcode_Python | train | 0 | |
c0ea3dc7c1c0a7e085b22955c446bf65334b5b16 | [
"self._edge_color = _get_hex_color(_get_value(kwargs, ['color', 'c', 'edge_color', 'ec'], 'black'))\nself._edge_alpha = _get_value(kwargs, ['alpha', 'edge_alpha', 'ea'], 1.0)\nself._edge_width = _get_value(kwargs, ['edge_width', 'ew'], 1)\nself._face_alpha = _get_value(kwargs, ['alpha', 'face_alpha', 'fa'], 0.3)\ns... | <|body_start_0|>
self._edge_color = _get_hex_color(_get_value(kwargs, ['color', 'c', 'edge_color', 'ec'], 'black'))
self._edge_alpha = _get_value(kwargs, ['alpha', 'edge_alpha', 'ea'], 1.0)
self._edge_width = _get_value(kwargs, ['edge_width', 'ew'], 1)
self._face_alpha = _get_value(kwarg... | _Polygon | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Polygon:
def __init__(self, lats, lngs, **kwargs):
"""Args: lats ([float]): Latitudes. lngs ([float]): Longitudes. Optional: Args: color/c/edge_color/ec (str): Color of the polygon's edge. Can be hex ('#00FFFF'), named ('cyan'), or matplotlib-like ('c'). Defaults to black. alpha/edge_al... | stack_v2_sparse_classes_75kplus_train_005880 | 2,491 | permissive | [
{
"docstring": "Args: lats ([float]): Latitudes. lngs ([float]): Longitudes. Optional: Args: color/c/edge_color/ec (str): Color of the polygon's edge. Can be hex ('#00FFFF'), named ('cyan'), or matplotlib-like ('c'). Defaults to black. alpha/edge_alpha/ea (float): Opacity of the polygon's edge, ranging from 0 t... | 2 | null | Implement the Python class `_Polygon` described below.
Class description:
Implement the _Polygon class.
Method signatures and docstrings:
- def __init__(self, lats, lngs, **kwargs): Args: lats ([float]): Latitudes. lngs ([float]): Longitudes. Optional: Args: color/c/edge_color/ec (str): Color of the polygon's edge. C... | Implement the Python class `_Polygon` described below.
Class description:
Implement the _Polygon class.
Method signatures and docstrings:
- def __init__(self, lats, lngs, **kwargs): Args: lats ([float]): Latitudes. lngs ([float]): Longitudes. Optional: Args: color/c/edge_color/ec (str): Color of the polygon's edge. C... | 0979c51467e25cfe870668d3990ce7885e317f85 | <|skeleton|>
class _Polygon:
def __init__(self, lats, lngs, **kwargs):
"""Args: lats ([float]): Latitudes. lngs ([float]): Longitudes. Optional: Args: color/c/edge_color/ec (str): Color of the polygon's edge. Can be hex ('#00FFFF'), named ('cyan'), or matplotlib-like ('c'). Defaults to black. alpha/edge_al... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _Polygon:
def __init__(self, lats, lngs, **kwargs):
"""Args: lats ([float]): Latitudes. lngs ([float]): Longitudes. Optional: Args: color/c/edge_color/ec (str): Color of the polygon's edge. Can be hex ('#00FFFF'), named ('cyan'), or matplotlib-like ('c'). Defaults to black. alpha/edge_alpha/ea (float)... | the_stack_v2_python_sparse | gmplot/drawables/polygon.py | tirkarthi/gmplot | train | 0 | |
53f6d7ae93a90485397b67e1978952deef31b6a2 | [
"self.username = username\nself.template_lookup = LOOKUP\nself.mako_template = 'recover_pwd.mako'\nself.mako_template2 = 'ask_question.mako'\nself.mako_template3 = 'new_pwd.mako'",
"resp = Response()\ntemplate_args = self.templ_arg_func(end_point_index, **kwargs)\nmako_template_engine = self.template_lookup.get_t... | <|body_start_0|>
self.username = username
self.template_lookup = LOOKUP
self.mako_template = 'recover_pwd.mako'
self.mako_template2 = 'ask_question.mako'
self.mako_template3 = 'new_pwd.mako'
<|end_body_0|>
<|body_start_1|>
resp = Response()
template_args = self.t... | recovery_module | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class recovery_module:
def __init__(self, username):
""":param username: Username :param template_lookup: template lookup :return:"""
<|body_0|>
def __call__(self, cookie=None, end_point_index=0, **kwargs):
"""Put up the username form"""
<|body_1|>
def show_qu... | stack_v2_sparse_classes_75kplus_train_005881 | 5,495 | no_license | [
{
"docstring": ":param username: Username :param template_lookup: template lookup :return:",
"name": "__init__",
"signature": "def __init__(self, username)"
},
{
"docstring": "Put up the username form",
"name": "__call__",
"signature": "def __call__(self, cookie=None, end_point_index=0, ... | 5 | stack_v2_sparse_classes_30k_train_044160 | Implement the Python class `recovery_module` described below.
Class description:
Implement the recovery_module class.
Method signatures and docstrings:
- def __init__(self, username): :param username: Username :param template_lookup: template lookup :return:
- def __call__(self, cookie=None, end_point_index=0, **kwar... | Implement the Python class `recovery_module` described below.
Class description:
Implement the recovery_module class.
Method signatures and docstrings:
- def __init__(self, username): :param username: Username :param template_lookup: template lookup :return:
- def __call__(self, cookie=None, end_point_index=0, **kwar... | 4455de4eb61fb4bddf6cfa8a4ce9e5f9f8e9d812 | <|skeleton|>
class recovery_module:
def __init__(self, username):
""":param username: Username :param template_lookup: template lookup :return:"""
<|body_0|>
def __call__(self, cookie=None, end_point_index=0, **kwargs):
"""Put up the username form"""
<|body_1|>
def show_qu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class recovery_module:
def __init__(self, username):
""":param username: Username :param template_lookup: template lookup :return:"""
self.username = username
self.template_lookup = LOOKUP
self.mako_template = 'recover_pwd.mako'
self.mako_template2 = 'ask_question.mako'
... | the_stack_v2_python_sparse | server/recovery.py | CarlosGonzalezLuzardo/SECAS | train | 0 | |
5ce8b5059b2ed15ef699e0467d7d0b354739b260 | [
"self.color = color\nself.width = width\nself.beg_x = beg_x\nself.beg_y = beg_y\nself.end_x = end_x\nself.end_y = end_y",
"w_str = f'Wall2d:{self.color}'\nw_str += f' w:{self.width}'\nw_str += f' beg_xy:{self.beg_x},{self.beg_y}'\nw_str += f' end_xy:{self.end_x},{self.end_y}'\nreturn w_str"
] | <|body_start_0|>
self.color = color
self.width = width
self.beg_x = beg_x
self.beg_y = beg_y
self.end_x = end_x
self.end_y = end_y
<|end_body_0|>
<|body_start_1|>
w_str = f'Wall2d:{self.color}'
w_str += f' w:{self.width}'
w_str += f' beg_xy:{self.... | Wall2d | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Wall2d:
def __init__(self, color='green', width=1, beg_x=0, beg_y=0, end_x=300, end_y=0):
"""Define/Setup Wall's attributes :color: wall's color default: black :width: width(thickness) in default units default: 1 :beg_x: x (horizontal right) in default units default: 0 :beg_y: y (vertica... | stack_v2_sparse_classes_75kplus_train_005882 | 1,446 | no_license | [
{
"docstring": "Define/Setup Wall's attributes :color: wall's color default: black :width: width(thickness) in default units default: 1 :beg_x: x (horizontal right) in default units default: 0 :beg_y: y (vertical down) in default units default: 0 :end_x: x (horizontal right) default units, default time inc defa... | 2 | stack_v2_sparse_classes_30k_train_010516 | Implement the Python class `Wall2d` described below.
Class description:
Implement the Wall2d class.
Method signatures and docstrings:
- def __init__(self, color='green', width=1, beg_x=0, beg_y=0, end_x=300, end_y=0): Define/Setup Wall's attributes :color: wall's color default: black :width: width(thickness) in defau... | Implement the Python class `Wall2d` described below.
Class description:
Implement the Wall2d class.
Method signatures and docstrings:
- def __init__(self, color='green', width=1, beg_x=0, beg_y=0, end_x=300, end_y=0): Define/Setup Wall's attributes :color: wall's color default: black :width: width(thickness) in defau... | bedc16eb5f6db0ad3b313355df6d51b5161c3835 | <|skeleton|>
class Wall2d:
def __init__(self, color='green', width=1, beg_x=0, beg_y=0, end_x=300, end_y=0):
"""Define/Setup Wall's attributes :color: wall's color default: black :width: width(thickness) in default units default: 1 :beg_x: x (horizontal right) in default units default: 0 :beg_y: y (vertica... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Wall2d:
def __init__(self, color='green', width=1, beg_x=0, beg_y=0, end_x=300, end_y=0):
"""Define/Setup Wall's attributes :color: wall's color default: black :width: width(thickness) in default units default: 1 :beg_x: x (horizontal right) in default units default: 0 :beg_y: y (vertical down) in def... | the_stack_v2_python_sparse | exercises/classes/ball_classes/walll_2d.py | raysmith619/Introduction-To-Programming | train | 3 | |
1c82d096d7c6bdea7d863c8d1db7ea065e8f127a | [
"raise ApiError(500, 1, 'vlan status is null')\nobj = {'vlan_arr': []}\nargs = Verify.dict(self.req_args, {'limit?': (lambda x: x.type('int') and x > 0, ApiError(400, 1, 'invalid limit')), 'index?': (lambda x: x.type('int') and x > 0, ApiError(400, 1, 'invalid index'))})\narr = vcmd.get_arr_simple('cdbctl read/cdb/... | <|body_start_0|>
raise ApiError(500, 1, 'vlan status is null')
obj = {'vlan_arr': []}
args = Verify.dict(self.req_args, {'limit?': (lambda x: x.type('int') and x > 0, ApiError(400, 1, 'invalid limit')), 'index?': (lambda x: x.type('int') and x > 0, ApiError(400, 1, 'invalid index'))})
ar... | VlanApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VlanApi:
def get(self):
"""get vlan array"""
<|body_0|>
def post(self):
"""add vlan"""
<|body_1|>
def put(self):
"""modify vlan name"""
<|body_2|>
def delete(self):
"""delete vlans"""
<|body_3|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_75kplus_train_005883 | 3,263 | no_license | [
{
"docstring": "get vlan array",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "add vlan",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "modify vlan name",
"name": "put",
"signature": "def put(self)"
},
{
"docstring": "delete vla... | 4 | stack_v2_sparse_classes_30k_train_012383 | Implement the Python class `VlanApi` described below.
Class description:
Implement the VlanApi class.
Method signatures and docstrings:
- def get(self): get vlan array
- def post(self): add vlan
- def put(self): modify vlan name
- def delete(self): delete vlans | Implement the Python class `VlanApi` described below.
Class description:
Implement the VlanApi class.
Method signatures and docstrings:
- def get(self): get vlan array
- def post(self): add vlan
- def put(self): modify vlan name
- def delete(self): delete vlans
<|skeleton|>
class VlanApi:
def get(self):
... | 2fee6115caec25fd040188dda0cb922bfca1a55f | <|skeleton|>
class VlanApi:
def get(self):
"""get vlan array"""
<|body_0|>
def post(self):
"""add vlan"""
<|body_1|>
def put(self):
"""modify vlan name"""
<|body_2|>
def delete(self):
"""delete vlans"""
<|body_3|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VlanApi:
def get(self):
"""get vlan array"""
raise ApiError(500, 1, 'vlan status is null')
obj = {'vlan_arr': []}
args = Verify.dict(self.req_args, {'limit?': (lambda x: x.type('int') and x > 0, ApiError(400, 1, 'invalid limit')), 'index?': (lambda x: x.type('int') and x > 0, A... | the_stack_v2_python_sparse | osp_sai_2.1.8/system/apps/web/api_class/vlan.py | bonald/vim_cfg | train | 0 | |
d67be9963d1ff3e8431591af26382a2c4182ecf2 | [
"res = {}\n\ndef dfs(node, order):\n if not node:\n return\n res[order] = node.val\n dfs(node.left, order * 2 + 1)\n dfs(node.right, order * 2 + 2)\ndfs(root, 0)\nreturn str(res)",
"l = eval(data)\nfor key in l:\n l[key] = TreeNode(l[key])\nfor k in l:\n if k * 2 + 1 in l:\n l[k].l... | <|body_start_0|>
res = {}
def dfs(node, order):
if not node:
return
res[order] = node.val
dfs(node.left, order * 2 + 1)
dfs(node.right, order * 2 + 2)
dfs(root, 0)
return str(res)
<|end_body_0|>
<|body_start_1|>
l ... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_005884 | 1,234 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_009288 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 9ae68ada9f63483323cdeaa0f7da3410a0669371 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = {}
def dfs(node, order):
if not node:
return
res[order] = node.val
dfs(node.left, order * 2 + 1)
dfs(node.r... | the_stack_v2_python_sparse | problems/0297.serialize-and-deserialize-binary-tree/serialize-and-deserialize-binary-tree.py | tirsott/lc-go | train | 0 | |
e0076ffc2e5a25011085118bd93a86122f31dbdd | [
"super(TverskyLoss2D, self).__init__()\nself.alpha = alpha\nself.beta = beta\nself.weight = weight\nself.ignore_index = ignore_index",
"smooth = 1.0\npredictions = F.softmax(predictions, dim=1)\nencoded_target = predictions.detach() * 0\nmask = None\nif self.ignore_index is not None:\n mask = targets == self.i... | <|body_start_0|>
super(TverskyLoss2D, self).__init__()
self.alpha = alpha
self.beta = beta
self.weight = weight
self.ignore_index = ignore_index
<|end_body_0|>
<|body_start_1|>
smooth = 1.0
predictions = F.softmax(predictions, dim=1)
encoded_target = pred... | TverskyLoss2D | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TverskyLoss2D:
def __init__(self, alpha=0.4, beta=0.6, weight=None, ignore_index=-100):
"""Tversky Loss for Semantic Segmentation :param alpha: <int> Parameter to control precision and recall :param beta: <int> Parameter to control precision and recall :param weight: <torch.Tensor, optio... | stack_v2_sparse_classes_75kplus_train_005885 | 35,592 | permissive | [
{
"docstring": "Tversky Loss for Semantic Segmentation :param alpha: <int> Parameter to control precision and recall :param beta: <int> Parameter to control precision and recall :param weight: <torch.Tensor, optional> A manual rescaling weight given to each class. If given, has to be a Tensor of size C, where C... | 2 | stack_v2_sparse_classes_30k_train_033527 | Implement the Python class `TverskyLoss2D` described below.
Class description:
Implement the TverskyLoss2D class.
Method signatures and docstrings:
- def __init__(self, alpha=0.4, beta=0.6, weight=None, ignore_index=-100): Tversky Loss for Semantic Segmentation :param alpha: <int> Parameter to control precision and r... | Implement the Python class `TverskyLoss2D` described below.
Class description:
Implement the TverskyLoss2D class.
Method signatures and docstrings:
- def __init__(self, alpha=0.4, beta=0.6, weight=None, ignore_index=-100): Tversky Loss for Semantic Segmentation :param alpha: <int> Parameter to control precision and r... | ed226e5454b2144063a6d8132b07c90e6a64e2d3 | <|skeleton|>
class TverskyLoss2D:
def __init__(self, alpha=0.4, beta=0.6, weight=None, ignore_index=-100):
"""Tversky Loss for Semantic Segmentation :param alpha: <int> Parameter to control precision and recall :param beta: <int> Parameter to control precision and recall :param weight: <torch.Tensor, optio... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TverskyLoss2D:
def __init__(self, alpha=0.4, beta=0.6, weight=None, ignore_index=-100):
"""Tversky Loss for Semantic Segmentation :param alpha: <int> Parameter to control precision and recall :param beta: <int> Parameter to control precision and recall :param weight: <torch.Tensor, optional> A manual ... | the_stack_v2_python_sparse | utils/losses.py | tansyab1/LightNetPlus | train | 0 | |
8443889d7c9b25c593b4fdd14bbcb8cae5e2e6f8 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn DeviceComplianceActionItem()",
"from .device_compliance_action_type import DeviceComplianceActionType\nfrom .entity import Entity\nfrom .device_compliance_action_type import DeviceComplianceActionType\nfrom .entity import Entity\nfield... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return DeviceComplianceActionItem()
<|end_body_0|>
<|body_start_1|>
from .device_compliance_action_type import DeviceComplianceActionType
from .entity import Entity
from .device_complia... | Scheduled Action Configuration | DeviceComplianceActionItem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceComplianceActionItem:
"""Scheduled Action Configuration"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceComplianceActionItem:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node t... | stack_v2_sparse_classes_75kplus_train_005886 | 3,346 | 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: DeviceComplianceActionItem",
"name": "create_from_discriminator_value",
"signature": "def create_from_discri... | 3 | stack_v2_sparse_classes_30k_train_047133 | Implement the Python class `DeviceComplianceActionItem` described below.
Class description:
Scheduled Action Configuration
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceComplianceActionItem: Creates a new instance of the appropriate class based ... | Implement the Python class `DeviceComplianceActionItem` described below.
Class description:
Scheduled Action Configuration
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceComplianceActionItem: Creates a new instance of the appropriate class based ... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class DeviceComplianceActionItem:
"""Scheduled Action Configuration"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceComplianceActionItem:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeviceComplianceActionItem:
"""Scheduled Action Configuration"""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DeviceComplianceActionItem:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read... | the_stack_v2_python_sparse | msgraph/generated/models/device_compliance_action_item.py | microsoftgraph/msgraph-sdk-python | train | 135 |
8614f6c3c28f4f35ae86fd6b151814cd353ae817 | [
"def get(root, items):\n if root is None:\n items.append('null')\n return\n items.append(str(root.val))\n get(root.left, items)\n get(root.right, items)\nitems = []\nget(root, items)\nreturn ','.join(items)",
"def get_root(data):\n if not data:\n return\n curr = data.popleft... | <|body_start_0|>
def get(root, items):
if root is None:
items.append('null')
return
items.append(str(root.val))
get(root.left, items)
get(root.right, items)
items = []
get(root, items)
return ','.join(items)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_005887 | 1,352 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_033229 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 8e87b10bd77289b891591b770a6f7adc2c00fdf0 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def get(root, items):
if root is None:
items.append('null')
return
items.append(str(root.val))
get(root.left, items)
... | the_stack_v2_python_sparse | Temp/serialize_and_deserialize_bst.py | karthik4636/practice_problems | train | 0 | |
240dfe17f8091c20f806de1d17dcb81569eaaff6 | [
"super(RandomBrightness, self).__init__()\nself.probability = p\nself.min_factor = min_factor\nself.max_factor = max_factor",
"if np.random.random() < self.probability:\n factor = np.random.uniform(self.min_factor, self.max_factor)\n image_enhancer_brightness = ImageEnhance.Brightness(img)\n img = image_... | <|body_start_0|>
super(RandomBrightness, self).__init__()
self.probability = p
self.min_factor = min_factor
self.max_factor = max_factor
<|end_body_0|>
<|body_start_1|>
if np.random.random() < self.probability:
factor = np.random.uniform(self.min_factor, self.max_fac... | This class is used to random change image brightness. | RandomBrightness | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomBrightness:
"""This class is used to random change image brightness."""
def __init__(self, p=0.8, min_factor=0.4, max_factor=1.33):
"""required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_brightness` function. :param probability: Controls the probab... | stack_v2_sparse_classes_75kplus_train_005888 | 40,740 | no_license | [
{
"docstring": "required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_brightness` function. :param probability: Controls the probability that the operation is performed when it is invoked in the pipeline. :param min_factor: The value between 0.0 and max_factor that define the minimum... | 2 | stack_v2_sparse_classes_30k_train_006796 | Implement the Python class `RandomBrightness` described below.
Class description:
This class is used to random change image brightness.
Method signatures and docstrings:
- def __init__(self, p=0.8, min_factor=0.4, max_factor=1.33): required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_brig... | Implement the Python class `RandomBrightness` described below.
Class description:
This class is used to random change image brightness.
Method signatures and docstrings:
- def __init__(self, p=0.8, min_factor=0.4, max_factor=1.33): required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_brig... | a9c19225733b1a61eb0b006e6afc1bd2826bba2b | <|skeleton|>
class RandomBrightness:
"""This class is used to random change image brightness."""
def __init__(self, p=0.8, min_factor=0.4, max_factor=1.33):
"""required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_brightness` function. :param probability: Controls the probab... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RandomBrightness:
"""This class is used to random change image brightness."""
def __init__(self, p=0.8, min_factor=0.4, max_factor=1.33):
"""required :attr:`probability` parameter :func:`~Augmentor.Pipeline.Pipeline.random_brightness` function. :param probability: Controls the probability that th... | the_stack_v2_python_sparse | imcls/data/transforms/operations.py | iYuqinL/imcls | train | 0 |
5aab340e2768227da0c6e154bd0c3fbadbb76e44 | [
"B, npoints, nsample = idx.size()\n_, N, C = points.size()\noutput = torch.cuda.FloatTensor(B, npoints, nsample, C)\npoints = points.contiguous()\nidx = idx.contiguous()\noutput = output.contiguous()\npointnet2.group_points_wrapper(B, N, C, npoints, nsample, points, idx, output)\nctx.idx_N_C_for_backward = (idx, N,... | <|body_start_0|>
B, npoints, nsample = idx.size()
_, N, C = points.size()
output = torch.cuda.FloatTensor(B, npoints, nsample, C)
points = points.contiguous()
idx = idx.contiguous()
output = output.contiguous()
pointnet2.group_points_wrapper(B, N, C, npoints, nsam... | GroupPoints | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupPoints:
def forward(ctx, points: torch.Tensor, idx: torch.Tensor) -> torch.Tensor:
"""Parameters ---------- points : torch.Tensor (B, N, C) tensor of points to group idx : torch.Tensor (B, npoint, nsample) tensor containing the indicies of points to group with Returns ------- torch.... | stack_v2_sparse_classes_75kplus_train_005889 | 10,672 | no_license | [
{
"docstring": "Parameters ---------- points : torch.Tensor (B, N, C) tensor of points to group idx : torch.Tensor (B, npoint, nsample) tensor containing the indicies of points to group with Returns ------- torch.Tensor (B, npoint, nsample, C) tensor",
"name": "forward",
"signature": "def forward(ctx, p... | 2 | stack_v2_sparse_classes_30k_test_000208 | Implement the Python class `GroupPoints` described below.
Class description:
Implement the GroupPoints class.
Method signatures and docstrings:
- def forward(ctx, points: torch.Tensor, idx: torch.Tensor) -> torch.Tensor: Parameters ---------- points : torch.Tensor (B, N, C) tensor of points to group idx : torch.Tenso... | Implement the Python class `GroupPoints` described below.
Class description:
Implement the GroupPoints class.
Method signatures and docstrings:
- def forward(ctx, points: torch.Tensor, idx: torch.Tensor) -> torch.Tensor: Parameters ---------- points : torch.Tensor (B, N, C) tensor of points to group idx : torch.Tenso... | a573daa07b815f909771b8f648e34f52338129ef | <|skeleton|>
class GroupPoints:
def forward(ctx, points: torch.Tensor, idx: torch.Tensor) -> torch.Tensor:
"""Parameters ---------- points : torch.Tensor (B, N, C) tensor of points to group idx : torch.Tensor (B, npoint, nsample) tensor containing the indicies of points to group with Returns ------- torch.... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GroupPoints:
def forward(ctx, points: torch.Tensor, idx: torch.Tensor) -> torch.Tensor:
"""Parameters ---------- points : torch.Tensor (B, N, C) tensor of points to group idx : torch.Tensor (B, npoint, nsample) tensor containing the indicies of points to group with Returns ------- torch.Tensor (B, npo... | the_stack_v2_python_sparse | utils/pointnet2_utils.py | andrei-pokrovsky/GatechResearchF17 | train | 0 | |
b632b6dc44fabf5c3300a2568631dcf9063c2aca | [
"self.config = config\ndefinitions_provider = DefinitionsProviderFactory.instantiate(config['definitions']['type'], config)\nself.definitions = definitions_provider.get_definitions()",
"if lookml.filetype != 'view':\n raise Exception('Only views are supported. This is type ' + lookml.filetype)\nn = len(lookml.... | <|body_start_0|>
self.config = config
definitions_provider = DefinitionsProviderFactory.instantiate(config['definitions']['type'], config)
self.definitions = definitions_provider.get_definitions()
<|end_body_0|>
<|body_start_1|>
if lookml.filetype != 'view':
raise Exception(... | class that understands additions or modifications to be made and then delegates to filemodifier to make requested changes | LookMlModifier | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LookMlModifier:
"""class that understands additions or modifications to be made and then delegates to filemodifier to make requested changes"""
def __init__(self, config):
"""initialize the LookMlModifier Args: config (JSON): the JSON configuration"""
<|body_0|>
def find... | stack_v2_sparse_classes_75kplus_train_005890 | 5,054 | permissive | [
{
"docstring": "initialize the LookMlModifier Args: config (JSON): the JSON configuration",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "get the description, if any, from this measure or dimension Args: lookml (LookML): instance of LookML header_type (str): 'm... | 3 | stack_v2_sparse_classes_30k_test_000225 | Implement the Python class `LookMlModifier` described below.
Class description:
class that understands additions or modifications to be made and then delegates to filemodifier to make requested changes
Method signatures and docstrings:
- def __init__(self, config): initialize the LookMlModifier Args: config (JSON): t... | Implement the Python class `LookMlModifier` described below.
Class description:
class that understands additions or modifications to be made and then delegates to filemodifier to make requested changes
Method signatures and docstrings:
- def __init__(self, config): initialize the LookMlModifier Args: config (JSON): t... | cded1fd6a916cedebfd4a5b21993ce117a4a1a11 | <|skeleton|>
class LookMlModifier:
"""class that understands additions or modifications to be made and then delegates to filemodifier to make requested changes"""
def __init__(self, config):
"""initialize the LookMlModifier Args: config (JSON): the JSON configuration"""
<|body_0|>
def find... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LookMlModifier:
"""class that understands additions or modifications to be made and then delegates to filemodifier to make requested changes"""
def __init__(self, config):
"""initialize the LookMlModifier Args: config (JSON): the JSON configuration"""
self.config = config
definiti... | the_stack_v2_python_sparse | lkmltools/updater/lookml_modifier.py | mborukhava/lookml-tools | train | 1 |
01bf75baf7cb98762e200a8204fb6955182faae5 | [
"res = -1\nc = collections.Counter(arr)\nfor i in c:\n if c[i] == i:\n res = max(res, i)\nreturn res",
"res = -1\ndic = collections.defaultdict(int)\nfor i in arr:\n dic[i] += 1\nfor k in dic.keys():\n if dic[k] == k and k > res:\n res = k\nreturn res",
"res = -1\ndic = {}\nfor i in arr:\... | <|body_start_0|>
res = -1
c = collections.Counter(arr)
for i in c:
if c[i] == i:
res = max(res, i)
return res
<|end_body_0|>
<|body_start_1|>
res = -1
dic = collections.defaultdict(int)
for i in arr:
dic[i] += 1
for... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findLucky(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_0|>
def findLucky(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_1|>
def findLucky(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_2|>
... | stack_v2_sparse_classes_75kplus_train_005891 | 965 | no_license | [
{
"docstring": ":type arr: List[int] :rtype: int",
"name": "findLucky",
"signature": "def findLucky(self, arr)"
},
{
"docstring": ":type arr: List[int] :rtype: int",
"name": "findLucky",
"signature": "def findLucky(self, arr)"
},
{
"docstring": ":type arr: List[int] :rtype: int",... | 3 | stack_v2_sparse_classes_30k_train_017939 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLucky(self, arr): :type arr: List[int] :rtype: int
- def findLucky(self, arr): :type arr: List[int] :rtype: int
- def findLucky(self, arr): :type arr: List[int] :rtype: i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findLucky(self, arr): :type arr: List[int] :rtype: int
- def findLucky(self, arr): :type arr: List[int] :rtype: int
- def findLucky(self, arr): :type arr: List[int] :rtype: i... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def findLucky(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_0|>
def findLucky(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_1|>
def findLucky(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_2|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findLucky(self, arr):
""":type arr: List[int] :rtype: int"""
res = -1
c = collections.Counter(arr)
for i in c:
if c[i] == i:
res = max(res, i)
return res
def findLucky(self, arr):
""":type arr: List[int] :rtype: int... | the_stack_v2_python_sparse | 1394_Find_Lucky_Integer_in_an_Array.py | bingli8802/leetcode | train | 0 | |
b675b1a64fc89fedc36ca5187474ba5c2ef399b7 | [
"super(RNNDecoder, self).__init__()\nself.embedding = tf.keras.layers.Embedding(input_dim=vocab, output_dim=embedding)\nself.gru = tf.keras.layers.GRU(units=units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)\nself.F = tf.keras.layers.Dense(units=vocab)",
"batch, units = s_pre... | <|body_start_0|>
super(RNNDecoder, self).__init__()
self.embedding = tf.keras.layers.Embedding(input_dim=vocab, output_dim=embedding)
self.gru = tf.keras.layers.GRU(units=units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)
self.F = tf.keras.layers.Den... | doc | RNNDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNDecoder:
"""doc"""
def __init__(self, vocab, embedding, units, batch):
"""doc"""
<|body_0|>
def call(self, x, s_prev, hidden_states):
"""doc"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(RNNDecoder, self).__init__()
self.embed... | stack_v2_sparse_classes_75kplus_train_005892 | 1,304 | no_license | [
{
"docstring": "doc",
"name": "__init__",
"signature": "def __init__(self, vocab, embedding, units, batch)"
},
{
"docstring": "doc",
"name": "call",
"signature": "def call(self, x, s_prev, hidden_states)"
}
] | 2 | stack_v2_sparse_classes_30k_train_029337 | Implement the Python class `RNNDecoder` described below.
Class description:
doc
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): doc
- def call(self, x, s_prev, hidden_states): doc | Implement the Python class `RNNDecoder` described below.
Class description:
doc
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): doc
- def call(self, x, s_prev, hidden_states): doc
<|skeleton|>
class RNNDecoder:
"""doc"""
def __init__(self, vocab, embedding, units, bat... | 3bffd1391b3fc790f0137d0afbe90eb8e2f7d713 | <|skeleton|>
class RNNDecoder:
"""doc"""
def __init__(self, vocab, embedding, units, batch):
"""doc"""
<|body_0|>
def call(self, x, s_prev, hidden_states):
"""doc"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RNNDecoder:
"""doc"""
def __init__(self, vocab, embedding, units, batch):
"""doc"""
super(RNNDecoder, self).__init__()
self.embedding = tf.keras.layers.Embedding(input_dim=vocab, output_dim=embedding)
self.gru = tf.keras.layers.GRU(units=units, recurrent_initializer='gloro... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/2-rnn_decoder.py | pafuentess/holbertonschool-machine_learning | train | 0 |
03cc79c6bda59745752361ce520e967365a7c426 | [
"super(DrainageAreaModel, self).__init__(input_file=input_file, params=params)\nself.flow_router = FlowRouter(self.grid, **self.params)\nself.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)",
"self.flow_router.run_one_step()\nfrom landlab.io import write_esri_ascii\nimport numpy\nwrite_esri_asci... | <|body_start_0|>
super(DrainageAreaModel, self).__init__(input_file=input_file, params=params)
self.flow_router = FlowRouter(self.grid, **self.params)
self.lake_filler = DepressionFinderAndRouter(self.grid, **self.params)
<|end_body_0|>
<|body_start_1|>
self.flow_router.run_one_step()
... | A DrainageAreaModel simply computes drainage area on a raster-grid DEM. | DrainageAreaModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DrainageAreaModel:
"""A DrainageAreaModel simply computes drainage area on a raster-grid DEM."""
def __init__(self, input_file=None, params=None):
"""Initialize the LinearDiffusionModel."""
<|body_0|>
def run_one_step(self, dt):
"""Advance model for one time-step... | stack_v2_sparse_classes_75kplus_train_005893 | 2,284 | no_license | [
{
"docstring": "Initialize the LinearDiffusionModel.",
"name": "__init__",
"signature": "def __init__(self, input_file=None, params=None)"
},
{
"docstring": "Advance model for one time-step of duration dt.",
"name": "run_one_step",
"signature": "def run_one_step(self, dt)"
}
] | 2 | null | Implement the Python class `DrainageAreaModel` described below.
Class description:
A DrainageAreaModel simply computes drainage area on a raster-grid DEM.
Method signatures and docstrings:
- def __init__(self, input_file=None, params=None): Initialize the LinearDiffusionModel.
- def run_one_step(self, dt): Advance mo... | Implement the Python class `DrainageAreaModel` described below.
Class description:
A DrainageAreaModel simply computes drainage area on a raster-grid DEM.
Method signatures and docstrings:
- def __init__(self, input_file=None, params=None): Initialize the LinearDiffusionModel.
- def run_one_step(self, dt): Advance mo... | 3506ec741a7c8a170ea654d40c6119fefe1b93ba | <|skeleton|>
class DrainageAreaModel:
"""A DrainageAreaModel simply computes drainage area on a raster-grid DEM."""
def __init__(self, input_file=None, params=None):
"""Initialize the LinearDiffusionModel."""
<|body_0|>
def run_one_step(self, dt):
"""Advance model for one time-step... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DrainageAreaModel:
"""A DrainageAreaModel simply computes drainage area on a raster-grid DEM."""
def __init__(self, input_file=None, params=None):
"""Initialize the LinearDiffusionModel."""
super(DrainageAreaModel, self).__init__(input_file=input_file, params=params)
self.flow_rou... | the_stack_v2_python_sparse | erosion_modeling_suite/erosion_model/single_component/drainage_area/drainage_area_model.py | kbarnhart/inverting_topography_postglacial | train | 4 |
d0e0af05416528de6b183456529a8d3bb9775ba4 | [
"try:\n user = User.objects.get(username__iexact=username)\n if user.check_password(password):\n return user\n return None\nexcept User.DoesNotExist:\n return None",
"try:\n return User.objects.get(id=user_id)\nexcept User.DoesNotExist:\n return None"
] | <|body_start_0|>
try:
user = User.objects.get(username__iexact=username)
if user.check_password(password):
return user
return None
except User.DoesNotExist:
return None
<|end_body_0|>
<|body_start_1|>
try:
return User.o... | PrklModelBackend | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrklModelBackend:
def authenticate(self, username=None, password=None):
"""Use our derived User object but call superclass (contrib.auth) for check_password"""
<|body_0|>
def get_user(self, user_id):
"""User getter"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_75kplus_train_005894 | 1,543 | no_license | [
{
"docstring": "Use our derived User object but call superclass (contrib.auth) for check_password",
"name": "authenticate",
"signature": "def authenticate(self, username=None, password=None)"
},
{
"docstring": "User getter",
"name": "get_user",
"signature": "def get_user(self, user_id)"
... | 2 | stack_v2_sparse_classes_30k_train_042594 | Implement the Python class `PrklModelBackend` described below.
Class description:
Implement the PrklModelBackend class.
Method signatures and docstrings:
- def authenticate(self, username=None, password=None): Use our derived User object but call superclass (contrib.auth) for check_password
- def get_user(self, user_... | Implement the Python class `PrklModelBackend` described below.
Class description:
Implement the PrklModelBackend class.
Method signatures and docstrings:
- def authenticate(self, username=None, password=None): Use our derived User object but call superclass (contrib.auth) for check_password
- def get_user(self, user_... | 1c95d454c9efc180058156694b5c9900ef526ed0 | <|skeleton|>
class PrklModelBackend:
def authenticate(self, username=None, password=None):
"""Use our derived User object but call superclass (contrib.auth) for check_password"""
<|body_0|>
def get_user(self, user_id):
"""User getter"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PrklModelBackend:
def authenticate(self, username=None, password=None):
"""Use our derived User object but call superclass (contrib.auth) for check_password"""
try:
user = User.objects.get(username__iexact=username)
if user.check_password(password):
retu... | the_stack_v2_python_sparse | web/auth.py | mjtorn/prkl | train | 0 | |
a9c3ba960690756f88d22e81291e4d283be26e16 | [
"self.lr = lr\nself.b1 = b1\nself.b2 = b2\nself.num_params = num_params\nself.counter = 0\nself.momentum = [0 for _ in range(num_params)]\nself.velocity = [0 for _ in range(num_params)]",
"self.counter += 1\nepsilon = 1e-08\nnew_params = []\nfor i in range(self.num_params):\n self.momentum[i] = self.b1 * self.... | <|body_start_0|>
self.lr = lr
self.b1 = b1
self.b2 = b2
self.num_params = num_params
self.counter = 0
self.momentum = [0 for _ in range(num_params)]
self.velocity = [0 for _ in range(num_params)]
<|end_body_0|>
<|body_start_1|>
self.counter += 1
e... | Adamax | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Adamax:
def __init__(self, num_params, lr=0.00146, b1=0.9, b2=0.99):
"""Initializer for Adamax optimizer Inputs: num params: number of parameters which are ought to be passed lr: The learning rate with which the gradient step should be taken(integer/float), default is 0.00146 b1 : The ex... | stack_v2_sparse_classes_75kplus_train_005895 | 10,861 | no_license | [
{
"docstring": "Initializer for Adamax optimizer Inputs: num params: number of parameters which are ought to be passed lr: The learning rate with which the gradient step should be taken(integer/float), default is 0.00146 b1 : The exponential decay rate for the first moment(integer/float), default is 0.9 b2 : Th... | 2 | stack_v2_sparse_classes_30k_train_053962 | Implement the Python class `Adamax` described below.
Class description:
Implement the Adamax class.
Method signatures and docstrings:
- def __init__(self, num_params, lr=0.00146, b1=0.9, b2=0.99): Initializer for Adamax optimizer Inputs: num params: number of parameters which are ought to be passed lr: The learning r... | Implement the Python class `Adamax` described below.
Class description:
Implement the Adamax class.
Method signatures and docstrings:
- def __init__(self, num_params, lr=0.00146, b1=0.9, b2=0.99): Initializer for Adamax optimizer Inputs: num params: number of parameters which are ought to be passed lr: The learning r... | 9406b21aef9b2d94091d570e809f88a752277e30 | <|skeleton|>
class Adamax:
def __init__(self, num_params, lr=0.00146, b1=0.9, b2=0.99):
"""Initializer for Adamax optimizer Inputs: num params: number of parameters which are ought to be passed lr: The learning rate with which the gradient step should be taken(integer/float), default is 0.00146 b1 : The ex... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Adamax:
def __init__(self, num_params, lr=0.00146, b1=0.9, b2=0.99):
"""Initializer for Adamax optimizer Inputs: num params: number of parameters which are ought to be passed lr: The learning rate with which the gradient step should be taken(integer/float), default is 0.00146 b1 : The exponential deca... | the_stack_v2_python_sparse | optimizers.py | viswambhar-yasa/AuToDiFf | train | 0 | |
629ca01c8f28979a280d98248aba28a7dc3b6ebc | [
"super().__init__(db_interface)\nself.table_name = '自合成指数'\nself.policy = index_composition_policy\nself.weight = None\nif index_composition_policy.unit_base:\n self.weight = (CompactFactor(index_composition_policy.unit_base, self.db_interface) * self.data_reader.stock_close).weight()\nself.stock_ticker_selector... | <|body_start_0|>
super().__init__(db_interface)
self.table_name = '自合成指数'
self.policy = index_composition_policy
self.weight = None
if index_composition_policy.unit_base:
self.weight = (CompactFactor(index_composition_policy.unit_base, self.db_interface) * self.data_r... | IndexCompositor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexCompositor:
def __init__(self, index_composition_policy: utils.StockIndexCompositionPolicy, db_interface: DBInterface=None):
"""自建指数收益计算器"""
<|body_0|>
def update(self):
"""更新市场收益率"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super().__init_... | stack_v2_sparse_classes_75kplus_train_005896 | 13,646 | permissive | [
{
"docstring": "自建指数收益计算器",
"name": "__init__",
"signature": "def __init__(self, index_composition_policy: utils.StockIndexCompositionPolicy, db_interface: DBInterface=None)"
},
{
"docstring": "更新市场收益率",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004628 | Implement the Python class `IndexCompositor` described below.
Class description:
Implement the IndexCompositor class.
Method signatures and docstrings:
- def __init__(self, index_composition_policy: utils.StockIndexCompositionPolicy, db_interface: DBInterface=None): 自建指数收益计算器
- def update(self): 更新市场收益率 | Implement the Python class `IndexCompositor` described below.
Class description:
Implement the IndexCompositor class.
Method signatures and docstrings:
- def __init__(self, index_composition_policy: utils.StockIndexCompositionPolicy, db_interface: DBInterface=None): 自建指数收益计算器
- def update(self): 更新市场收益率
<|skeleton|>... | 13c78602fe00a5326f421c8a8003f3889492e6dd | <|skeleton|>
class IndexCompositor:
def __init__(self, index_composition_policy: utils.StockIndexCompositionPolicy, db_interface: DBInterface=None):
"""自建指数收益计算器"""
<|body_0|>
def update(self):
"""更新市场收益率"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IndexCompositor:
def __init__(self, index_composition_policy: utils.StockIndexCompositionPolicy, db_interface: DBInterface=None):
"""自建指数收益计算器"""
super().__init__(db_interface)
self.table_name = '自合成指数'
self.policy = index_composition_policy
self.weight = None
i... | the_stack_v2_python_sparse | AShareData/factor_compositor/factor_compositor.py | ccbobt/AShareData | train | 0 | |
092cde234f7272a0e0e5a55bdb1cdc677a5ae153 | [
"try:\n self.SOCK = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n self.SOCK.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\nexcept:\n print('启动失败')\n exit(0)\nself.application = app",
"self.SOCK.listen()\nwhile True:\n client_socket, client_ip = self.SOCK.accept()\n p = Process(targ... | <|body_start_0|>
try:
self.SOCK = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.SOCK.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
except:
print('启动失败')
exit(0)
self.application = app
<|end_body_0|>
<|body_start_1|>
self.S... | HTTPServer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTTPServer:
def __init__(self, app: object) -> None:
"""初始化参数，端口 启动时监听网路数据 IP 监听的IP port 监听的端口"""
<|body_0|>
def start(self) -> None:
"""主循环等待客户端连接"""
<|body_1|>
def bind(self, PORT: any=8000, IP: str='127.0.0.1') -> None:
"""绑定端口，IP"""
<... | stack_v2_sparse_classes_75kplus_train_005897 | 2,785 | no_license | [
{
"docstring": "初始化参数，端口 启动时监听网路数据 IP 监听的IP port 监听的端口",
"name": "__init__",
"signature": "def __init__(self, app: object) -> None"
},
{
"docstring": "主循环等待客户端连接",
"name": "start",
"signature": "def start(self) -> None"
},
{
"docstring": "绑定端口，IP",
"name": "bind",
"signat... | 5 | stack_v2_sparse_classes_30k_train_044891 | Implement the Python class `HTTPServer` described below.
Class description:
Implement the HTTPServer class.
Method signatures and docstrings:
- def __init__(self, app: object) -> None: 初始化参数，端口 启动时监听网路数据 IP 监听的IP port 监听的端口
- def start(self) -> None: 主循环等待客户端连接
- def bind(self, PORT: any=8000, IP: str='127.0.0.1') ->... | Implement the Python class `HTTPServer` described below.
Class description:
Implement the HTTPServer class.
Method signatures and docstrings:
- def __init__(self, app: object) -> None: 初始化参数，端口 启动时监听网路数据 IP 监听的IP port 监听的端口
- def start(self) -> None: 主循环等待客户端连接
- def bind(self, PORT: any=8000, IP: str='127.0.0.1') ->... | 9db454d173ef35576d1f5f453e69ad9181d76ee7 | <|skeleton|>
class HTTPServer:
def __init__(self, app: object) -> None:
"""初始化参数，端口 启动时监听网路数据 IP 监听的IP port 监听的端口"""
<|body_0|>
def start(self) -> None:
"""主循环等待客户端连接"""
<|body_1|>
def bind(self, PORT: any=8000, IP: str='127.0.0.1') -> None:
"""绑定端口，IP"""
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HTTPServer:
def __init__(self, app: object) -> None:
"""初始化参数，端口 启动时监听网路数据 IP 监听的IP port 监听的端口"""
try:
self.SOCK = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.SOCK.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
except:
print('启动失败')... | the_stack_v2_python_sparse | HTTP_SERVER/sys_http/server.py | WillOfTree/TaoWu | train | 0 | |
941242456a627032f5e0d32e5e734e3e245ac655 | [
"vis = {(0, 0)}\nfor i in range(m):\n for j in range(n):\n if ((i - 1, j) in vis or (i, j - 1) in vis) and digit_sum(i) + digit_sum(j) <= k:\n vis.add((i, j))\nreturn len(vis)",
"from queue import Queue\nq = Queue()\nq.put((0, 0))\ns = set()\nwhile not q.empty():\n x, y = q.get()\n if (... | <|body_start_0|>
vis = {(0, 0)}
for i in range(m):
for j in range(n):
if ((i - 1, j) in vis or (i, j - 1) in vis) and digit_sum(i) + digit_sum(j) <= k:
vis.add((i, j))
return len(vis)
<|end_body_0|>
<|body_start_1|>
from queue import Queue... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def movingCount(self, m: int, n: int, k: int) -> int:
"""递推法 这里需要注意，所有的可能题解都是联通的，只需要考虑向右或者向下的情况。"""
<|body_0|>
def movingCount_2(self, m: int, n: int, k: int) -> int:
"""广度优先法"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
vis = {(0, 0)}
... | stack_v2_sparse_classes_75kplus_train_005898 | 1,810 | no_license | [
{
"docstring": "递推法 这里需要注意，所有的可能题解都是联通的，只需要考虑向右或者向下的情况。",
"name": "movingCount",
"signature": "def movingCount(self, m: int, n: int, k: int) -> int"
},
{
"docstring": "广度优先法",
"name": "movingCount_2",
"signature": "def movingCount_2(self, m: int, n: int, k: int) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_002834 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def movingCount(self, m: int, n: int, k: int) -> int: 递推法 这里需要注意，所有的可能题解都是联通的，只需要考虑向右或者向下的情况。
- def movingCount_2(self, m: int, n: int, k: int) -> int: 广度优先法 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def movingCount(self, m: int, n: int, k: int) -> int: 递推法 这里需要注意，所有的可能题解都是联通的，只需要考虑向右或者向下的情况。
- def movingCount_2(self, m: int, n: int, k: int) -> int: 广度优先法
<|skeleton|>
class ... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def movingCount(self, m: int, n: int, k: int) -> int:
"""递推法 这里需要注意，所有的可能题解都是联通的，只需要考虑向右或者向下的情况。"""
<|body_0|>
def movingCount_2(self, m: int, n: int, k: int) -> int:
"""广度优先法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def movingCount(self, m: int, n: int, k: int) -> int:
"""递推法 这里需要注意，所有的可能题解都是联通的，只需要考虑向右或者向下的情况。"""
vis = {(0, 0)}
for i in range(m):
for j in range(n):
if ((i - 1, j) in vis or (i, j - 1) in vis) and digit_sum(i) + digit_sum(j) <= k:
... | the_stack_v2_python_sparse | SwordOffer/SwordOffer_13.py | EachenKuang/LeetCode | train | 28 | |
7b1ee8a032873f555036c4b432c1d9e974f0498c | [
"expected_required_inputs = PIPELINE_TO_REQD_INFILES_BY_SAMPLE['testpipeline.sh'][sample_index]\nsample = proj.samples[sample_index]\nsample.set_pipeline_attributes(pipe_iface, 'testpipeline.sh')\nobserved_required_inputs = [os.path.basename(f) for f in sample.required_inputs]\nassert expected_required_inputs == ob... | <|body_start_0|>
expected_required_inputs = PIPELINE_TO_REQD_INFILES_BY_SAMPLE['testpipeline.sh'][sample_index]
sample = proj.samples[sample_index]
sample.set_pipeline_attributes(pipe_iface, 'testpipeline.sh')
observed_required_inputs = [os.path.basename(f) for f in sample.required_input... | Tests for `Sample` related to `Project` construction | SampleWrtProjectCtorTests | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleWrtProjectCtorTests:
"""Tests for `Sample` related to `Project` construction"""
def test_required_inputs(self, proj, pipe_iface, sample_index):
"""A looper Sample's required inputs are based on pipeline."""
<|body_0|>
def test_ngs_pipe_ngs_sample(self, proj, pipe_i... | stack_v2_sparse_classes_75kplus_train_005899 | 4,853 | permissive | [
{
"docstring": "A looper Sample's required inputs are based on pipeline.",
"name": "test_required_inputs",
"signature": "def test_required_inputs(self, proj, pipe_iface, sample_index)"
},
{
"docstring": "NGS pipeline with NGS input works just fine.",
"name": "test_ngs_pipe_ngs_sample",
"... | 3 | null | Implement the Python class `SampleWrtProjectCtorTests` described below.
Class description:
Tests for `Sample` related to `Project` construction
Method signatures and docstrings:
- def test_required_inputs(self, proj, pipe_iface, sample_index): A looper Sample's required inputs are based on pipeline.
- def test_ngs_pi... | Implement the Python class `SampleWrtProjectCtorTests` described below.
Class description:
Tests for `Sample` related to `Project` construction
Method signatures and docstrings:
- def test_required_inputs(self, proj, pipe_iface, sample_index): A looper Sample's required inputs are based on pipeline.
- def test_ngs_pi... | df535be2a0bd7257ee37148cb601d688ec557909 | <|skeleton|>
class SampleWrtProjectCtorTests:
"""Tests for `Sample` related to `Project` construction"""
def test_required_inputs(self, proj, pipe_iface, sample_index):
"""A looper Sample's required inputs are based on pipeline."""
<|body_0|>
def test_ngs_pipe_ngs_sample(self, proj, pipe_i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SampleWrtProjectCtorTests:
"""Tests for `Sample` related to `Project` construction"""
def test_required_inputs(self, proj, pipe_iface, sample_index):
"""A looper Sample's required inputs are based on pipeline."""
expected_required_inputs = PIPELINE_TO_REQD_INFILES_BY_SAMPLE['testpipeline.... | the_stack_v2_python_sparse | oldtests/integration/def test_project_iface_sample_interaction.py | vreuter/looper | train | 1 |
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