blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
427e87b8c23f922fc6dd3a79c450d236349ffd05 | [
"self.address = address\nself.port = port\nself.SOCK = None\nself.connected = False",
"if self.connected:\n return True\ntry:\n self.SOCK = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n self.connected = True\n return True\nexcept:\n logger.error('Could not open UDP socket')\n return False",... | <|body_start_0|>
self.address = address
self.port = port
self.SOCK = None
self.connected = False
<|end_body_0|>
<|body_start_1|>
if self.connected:
return True
try:
self.SOCK = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.conn... | LogUDP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogUDP:
def __init__(self, address, port):
"""Intialize our UDP logger @param address: Address of remote server @param port: port of listening server"""
<|body_0|>
def _connect(self):
"""Create our socket"""
<|body_1|>
def append(self, data):
"""... | stack_v2_sparse_classes_36k_train_001000 | 1,294 | no_license | [
{
"docstring": "Intialize our UDP logger @param address: Address of remote server @param port: port of listening server",
"name": "__init__",
"signature": "def __init__(self, address, port)"
},
{
"docstring": "Create our socket",
"name": "_connect",
"signature": "def _connect(self)"
},... | 3 | null | Implement the Python class `LogUDP` described below.
Class description:
Implement the LogUDP class.
Method signatures and docstrings:
- def __init__(self, address, port): Intialize our UDP logger @param address: Address of remote server @param port: port of listening server
- def _connect(self): Create our socket
- d... | Implement the Python class `LogUDP` described below.
Class description:
Implement the LogUDP class.
Method signatures and docstrings:
- def __init__(self, address, port): Intialize our UDP logger @param address: Address of remote server @param port: port of listening server
- def _connect(self): Create our socket
- d... | 8f92c4efb94061cb08b7e9b0ff96346565c12653 | <|skeleton|>
class LogUDP:
def __init__(self, address, port):
"""Intialize our UDP logger @param address: Address of remote server @param port: port of listening server"""
<|body_0|>
def _connect(self):
"""Create our socket"""
<|body_1|>
def append(self, data):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogUDP:
def __init__(self, address, port):
"""Intialize our UDP logger @param address: Address of remote server @param port: port of listening server"""
self.address = address
self.port = port
self.SOCK = None
self.connected = False
def _connect(self):
"""C... | the_stack_v2_python_sparse | lophi-automation/lophi_automation/dataconsumers/logudp.py | puppycodes/LO-PHI | train | 0 | |
213d40a0ee761a9adba16e95b30d63937da0cc0d | [
"try:\n return blob_api.get_by_id(pk, request.user)\nexcept exceptions.DoesNotExist:\n raise Http404",
"try:\n blob_object = self.get_object(request, pk)\n serializer = BlobSerializer(blob_object, context={'request': request})\n return Response(serializer.data)\nexcept AccessControlError as e:\n ... | <|body_start_0|>
try:
return blob_api.get_by_id(pk, request.user)
except exceptions.DoesNotExist:
raise Http404
<|end_body_0|>
<|body_start_1|>
try:
blob_object = self.get_object(request, pk)
serializer = BlobSerializer(blob_object, context={'requ... | Retrieve, update or delete a Blob | BlobDetail | [
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlobDetail:
"""Retrieve, update or delete a Blob"""
def get_object(self, request, pk):
"""Get Blob from db Args: request: HTTP request pk: ObjectId Returns: Blob"""
<|body_0|>
def get(self, request, pk):
"""Retrieve Blob Args: request: HTTP request pk: ObjectId R... | stack_v2_sparse_classes_36k_train_001001 | 11,564 | permissive | [
{
"docstring": "Get Blob from db Args: request: HTTP request pk: ObjectId Returns: Blob",
"name": "get_object",
"signature": "def get_object(self, request, pk)"
},
{
"docstring": "Retrieve Blob Args: request: HTTP request pk: ObjectId Returns: - code: 200 content: Blob - code: 403 content: Authe... | 3 | stack_v2_sparse_classes_30k_train_008780 | Implement the Python class `BlobDetail` described below.
Class description:
Retrieve, update or delete a Blob
Method signatures and docstrings:
- def get_object(self, request, pk): Get Blob from db Args: request: HTTP request pk: ObjectId Returns: Blob
- def get(self, request, pk): Retrieve Blob Args: request: HTTP r... | Implement the Python class `BlobDetail` described below.
Class description:
Retrieve, update or delete a Blob
Method signatures and docstrings:
- def get_object(self, request, pk): Get Blob from db Args: request: HTTP request pk: ObjectId Returns: Blob
- def get(self, request, pk): Retrieve Blob Args: request: HTTP r... | 568cb75a40ccff1d74a1a757866112535efd769a | <|skeleton|>
class BlobDetail:
"""Retrieve, update or delete a Blob"""
def get_object(self, request, pk):
"""Get Blob from db Args: request: HTTP request pk: ObjectId Returns: Blob"""
<|body_0|>
def get(self, request, pk):
"""Retrieve Blob Args: request: HTTP request pk: ObjectId R... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BlobDetail:
"""Retrieve, update or delete a Blob"""
def get_object(self, request, pk):
"""Get Blob from db Args: request: HTTP request pk: ObjectId Returns: Blob"""
try:
return blob_api.get_by_id(pk, request.user)
except exceptions.DoesNotExist:
raise Http4... | the_stack_v2_python_sparse | core_main_app/rest/blob/views.py | adilmania/core_main_app | train | 0 |
8ef4e2c8a66b23fffd05394de4111ee6cfc2a2e3 | [
"if not self._device.supports_set_brightness():\n raise HomeAssistantError('This device does not support setting brightness')\nif brightness == 0:\n await self.async_set_power_belief(False)\n return\ntry:\n await self._hub.bond.action(self._device.device_id, Action.set_brightness_belief(round(brightness... | <|body_start_0|>
if not self._device.supports_set_brightness():
raise HomeAssistantError('This device does not support setting brightness')
if brightness == 0:
await self.async_set_power_belief(False)
return
try:
await self._hub.bond.action(self._d... | Representation of a Bond light. | BondBaseLight | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BondBaseLight:
"""Representation of a Bond light."""
async def async_set_brightness_belief(self, brightness: int) -> None:
"""Set the belief state of the light."""
<|body_0|>
async def async_set_power_belief(self, power_state: bool) -> None:
"""Set the belief sta... | stack_v2_sparse_classes_36k_train_001002 | 12,277 | permissive | [
{
"docstring": "Set the belief state of the light.",
"name": "async_set_brightness_belief",
"signature": "async def async_set_brightness_belief(self, brightness: int) -> None"
},
{
"docstring": "Set the belief state of the light.",
"name": "async_set_power_belief",
"signature": "async de... | 2 | null | Implement the Python class `BondBaseLight` described below.
Class description:
Representation of a Bond light.
Method signatures and docstrings:
- async def async_set_brightness_belief(self, brightness: int) -> None: Set the belief state of the light.
- async def async_set_power_belief(self, power_state: bool) -> Non... | Implement the Python class `BondBaseLight` described below.
Class description:
Representation of a Bond light.
Method signatures and docstrings:
- async def async_set_brightness_belief(self, brightness: int) -> None: Set the belief state of the light.
- async def async_set_power_belief(self, power_state: bool) -> Non... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class BondBaseLight:
"""Representation of a Bond light."""
async def async_set_brightness_belief(self, brightness: int) -> None:
"""Set the belief state of the light."""
<|body_0|>
async def async_set_power_belief(self, power_state: bool) -> None:
"""Set the belief sta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BondBaseLight:
"""Representation of a Bond light."""
async def async_set_brightness_belief(self, brightness: int) -> None:
"""Set the belief state of the light."""
if not self._device.supports_set_brightness():
raise HomeAssistantError('This device does not support setting bri... | the_stack_v2_python_sparse | homeassistant/components/bond/light.py | home-assistant/core | train | 35,501 |
1eb378f92879565898c3ac1f32e1f68b7c4acdf4 | [
"if obj:\n return settings.REVEAL_OPENSRP_ACTIVE\nreturn None",
"if obj and obj.parent:\n return obj.parent.id\nreturn None",
"if obj:\n if obj.level == settings.REVEAL_DISTRICT:\n return settings.REVEAL_OPENSRP_DISTRICT\n if obj.level == settings.REVEAL_RHC:\n return settings.REVEAL_O... | <|body_start_0|>
if obj:
return settings.REVEAL_OPENSRP_ACTIVE
return None
<|end_body_0|>
<|body_start_1|>
if obj and obj.parent:
return obj.parent.id
return None
<|end_body_1|>
<|body_start_2|>
if obj:
if obj.level == settings.REVEAL_DISTRIC... | A class to serialize locations as OpenSRP GeoJSON compatible data | LocationSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocationSerializer:
"""A class to serialize locations as OpenSRP GeoJSON compatible data"""
def get_status(self, obj):
"""get location_type"""
<|body_0|>
def get_parentId(self, obj):
"""get parentId"""
<|body_1|>
def get_geographicLevel(self, obj):
... | stack_v2_sparse_classes_36k_train_001003 | 2,106 | permissive | [
{
"docstring": "get location_type",
"name": "get_status",
"signature": "def get_status(self, obj)"
},
{
"docstring": "get parentId",
"name": "get_parentId",
"signature": "def get_parentId(self, obj)"
},
{
"docstring": "get geographicLevel",
"name": "get_geographicLevel",
... | 3 | stack_v2_sparse_classes_30k_train_006560 | Implement the Python class `LocationSerializer` described below.
Class description:
A class to serialize locations as OpenSRP GeoJSON compatible data
Method signatures and docstrings:
- def get_status(self, obj): get location_type
- def get_parentId(self, obj): get parentId
- def get_geographicLevel(self, obj): get g... | Implement the Python class `LocationSerializer` described below.
Class description:
A class to serialize locations as OpenSRP GeoJSON compatible data
Method signatures and docstrings:
- def get_status(self, obj): get location_type
- def get_parentId(self, obj): get parentId
- def get_geographicLevel(self, obj): get g... | b3e0f4b5855abbf0298de6b66f2e9f472f2bf838 | <|skeleton|>
class LocationSerializer:
"""A class to serialize locations as OpenSRP GeoJSON compatible data"""
def get_status(self, obj):
"""get location_type"""
<|body_0|>
def get_parentId(self, obj):
"""get parentId"""
<|body_1|>
def get_geographicLevel(self, obj):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocationSerializer:
"""A class to serialize locations as OpenSRP GeoJSON compatible data"""
def get_status(self, obj):
"""get location_type"""
if obj:
return settings.REVEAL_OPENSRP_ACTIVE
return None
def get_parentId(self, obj):
"""get parentId"""
... | the_stack_v2_python_sparse | mspray/apps/reveal/serializers.py | Frazerbesa/mspray | train | 0 |
fdd1a9132780130bacd70bb4c9446a4484b80b12 | [
"if id is not None:\n self.id = id\nelse:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects",
"if list_dictionaries is None or len(list_dictionaries) is 0:\n return '[]'\nelse:\n return json.dumps(list_dictionaries)",
"if json_string is None or len(json_string) is 0:\n return []\nelse:\n ... | <|body_start_0|>
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
<|end_body_0|>
<|body_start_1|>
if list_dictionaries is None or len(list_dictionaries) is 0:
return '[]'
else:
return jso... | This class forms the base of all shape classes | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""This class forms the base of all shape classes"""
def __init__(self, id=None):
"""initializes the class Args: id(int): shape id, defaults to nb if None"""
<|body_0|>
def to_json_string(list_dictionaries):
"""Sends the dictionary to a json string"""
... | stack_v2_sparse_classes_36k_train_001004 | 2,087 | no_license | [
{
"docstring": "initializes the class Args: id(int): shape id, defaults to nb if None",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "Sends the dictionary to a json string",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"... | 6 | stack_v2_sparse_classes_30k_train_009569 | Implement the Python class `Base` described below.
Class description:
This class forms the base of all shape classes
Method signatures and docstrings:
- def __init__(self, id=None): initializes the class Args: id(int): shape id, defaults to nb if None
- def to_json_string(list_dictionaries): Sends the dictionary to a... | Implement the Python class `Base` described below.
Class description:
This class forms the base of all shape classes
Method signatures and docstrings:
- def __init__(self, id=None): initializes the class Args: id(int): shape id, defaults to nb if None
- def to_json_string(list_dictionaries): Sends the dictionary to a... | 37477d021ddc909a622bd944003eabb3478c8a2a | <|skeleton|>
class Base:
"""This class forms the base of all shape classes"""
def __init__(self, id=None):
"""initializes the class Args: id(int): shape id, defaults to nb if None"""
<|body_0|>
def to_json_string(list_dictionaries):
"""Sends the dictionary to a json string"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Base:
"""This class forms the base of all shape classes"""
def __init__(self, id=None):
"""initializes the class Args: id(int): shape id, defaults to nb if None"""
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | Selidex/holbertonschool-higher_level_programming | train | 0 |
eb1dfe920f25681e1b757850b76d5a609398a60e | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn SynchronizationTaskExecution()",
"from .synchronization_error import SynchronizationError\nfrom .synchronization_task_execution_result import SynchronizationTaskExecutionResult\nfrom .synchronization_error import SynchronizationError\n... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return SynchronizationTaskExecution()
<|end_body_0|>
<|body_start_1|>
from .synchronization_error import SynchronizationError
from .synchronization_task_execution_result import SynchronizationT... | SynchronizationTaskExecution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SynchronizationTaskExecution:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationTaskExecution:
"""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... | stack_v2_sparse_classes_36k_train_001005 | 6,954 | 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: SynchronizationTaskExecution",
"name": "create_from_discriminator_value",
"signature": "def create_from_disc... | 3 | null | Implement the Python class `SynchronizationTaskExecution` described below.
Class description:
Implement the SynchronizationTaskExecution class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationTaskExecution: Creates a new instance of the a... | Implement the Python class `SynchronizationTaskExecution` described below.
Class description:
Implement the SynchronizationTaskExecution class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationTaskExecution: Creates a new instance of the a... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class SynchronizationTaskExecution:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationTaskExecution:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SynchronizationTaskExecution:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationTaskExecution:
"""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 th... | the_stack_v2_python_sparse | msgraph/generated/models/synchronization_task_execution.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
6a8cd2950f6b94c5d9344334fede04012c162db9 | [
"alpha = np.where(x < x_break, alpha_1, alpha_2)\nxx = x / x_break\nreturn amplitude * xx ** (-alpha)",
"alpha = np.where(x < x_break, alpha_1, alpha_2)\nxx = x / x_break\nd_amplitude = xx ** (-alpha)\nd_x_break = amplitude * alpha * d_amplitude / x_break\nd_alpha = -amplitude * d_amplitude * np.log(xx)\nd_alpha_... | <|body_start_0|>
alpha = np.where(x < x_break, alpha_1, alpha_2)
xx = x / x_break
return amplitude * xx ** (-alpha)
<|end_body_0|>
<|body_start_1|>
alpha = np.where(x < x_break, alpha_1, alpha_2)
xx = x / x_break
d_amplitude = xx ** (-alpha)
d_x_break = amplitude... | One dimensional power law model with a break. Parameters ---------- amplitude : float Model amplitude at the break point x_break : float Break point alpha_1 : float Power law index for x < x_break alpha_2 : float Power law index for x > x_break See Also -------- PowerLaw1D, ExponentialCutoffPowerLaw1D, LogParabola1D No... | BrokenPowerLaw1D | [
"Python-2.0",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrokenPowerLaw1D:
"""One dimensional power law model with a break. Parameters ---------- amplitude : float Model amplitude at the break point x_break : float Break point alpha_1 : float Power law index for x < x_break alpha_2 : float Power law index for x > x_break See Also -------- PowerLaw1D, E... | stack_v2_sparse_classes_36k_train_001006 | 6,539 | permissive | [
{
"docstring": "One dimensional broken power law model function",
"name": "evaluate",
"signature": "def evaluate(x, amplitude, x_break, alpha_1, alpha_2)"
},
{
"docstring": "One dimensional broken power law derivative with respect to parameters",
"name": "fit_deriv",
"signature": "def fi... | 2 | stack_v2_sparse_classes_30k_test_000210 | Implement the Python class `BrokenPowerLaw1D` described below.
Class description:
One dimensional power law model with a break. Parameters ---------- amplitude : float Model amplitude at the break point x_break : float Break point alpha_1 : float Power law index for x < x_break alpha_2 : float Power law index for x > ... | Implement the Python class `BrokenPowerLaw1D` described below.
Class description:
One dimensional power law model with a break. Parameters ---------- amplitude : float Model amplitude at the break point x_break : float Break point alpha_1 : float Power law index for x < x_break alpha_2 : float Power law index for x > ... | 2c9002f16bb5c265e0d14f4a2314c86eeaa35cb6 | <|skeleton|>
class BrokenPowerLaw1D:
"""One dimensional power law model with a break. Parameters ---------- amplitude : float Model amplitude at the break point x_break : float Break point alpha_1 : float Power law index for x < x_break alpha_2 : float Power law index for x > x_break See Also -------- PowerLaw1D, E... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BrokenPowerLaw1D:
"""One dimensional power law model with a break. Parameters ---------- amplitude : float Model amplitude at the break point x_break : float Break point alpha_1 : float Power law index for x < x_break alpha_2 : float Power law index for x > x_break See Also -------- PowerLaw1D, ExponentialCut... | the_stack_v2_python_sparse | lib/python2.7/site-packages/astropy/modeling/powerlaws.py | wangyum/Anaconda | train | 11 |
0852949b3fe023ac1a58c58cc878eeaec2885fb4 | [
"query_filter = LineageFilter(entities=[LineageEntityEnum.ARTIFACT], sources=[LineageSourceEnum.DATASET])\nquery_result = LineageQuery(self.sagemaker_session).query(start_arns=[self.action_arn], query_filter=query_filter, direction=direction, include_edges=False)\nreturn [vertex.to_lineage_object() for vertex in qu... | <|body_start_0|>
query_filter = LineageFilter(entities=[LineageEntityEnum.ARTIFACT], sources=[LineageSourceEnum.DATASET])
query_result = LineageQuery(self.sagemaker_session).query(start_arns=[self.action_arn], query_filter=query_filter, direction=direction, include_edges=False)
return [vertex.to... | An Amazon SageMaker model package approval action, which is part of a SageMaker lineage. | ModelPackageApprovalAction | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelPackageApprovalAction:
"""An Amazon SageMaker model package approval action, which is part of a SageMaker lineage."""
def datasets(self, direction: LineageQueryDirectionEnum=LineageQueryDirectionEnum.ASCENDANTS) -> List[Artifact]:
"""Use a lineage query to retrieve all upstream ... | stack_v2_sparse_classes_36k_train_001007 | 12,422 | permissive | [
{
"docstring": "Use a lineage query to retrieve all upstream datasets that use this action. Args: direction (LineageQueryDirectionEnum, optional): The query direction. Returns: list of Artifacts: Artifacts representing a dataset.",
"name": "datasets",
"signature": "def datasets(self, direction: LineageQ... | 3 | null | Implement the Python class `ModelPackageApprovalAction` described below.
Class description:
An Amazon SageMaker model package approval action, which is part of a SageMaker lineage.
Method signatures and docstrings:
- def datasets(self, direction: LineageQueryDirectionEnum=LineageQueryDirectionEnum.ASCENDANTS) -> List... | Implement the Python class `ModelPackageApprovalAction` described below.
Class description:
An Amazon SageMaker model package approval action, which is part of a SageMaker lineage.
Method signatures and docstrings:
- def datasets(self, direction: LineageQueryDirectionEnum=LineageQueryDirectionEnum.ASCENDANTS) -> List... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class ModelPackageApprovalAction:
"""An Amazon SageMaker model package approval action, which is part of a SageMaker lineage."""
def datasets(self, direction: LineageQueryDirectionEnum=LineageQueryDirectionEnum.ASCENDANTS) -> List[Artifact]:
"""Use a lineage query to retrieve all upstream ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelPackageApprovalAction:
"""An Amazon SageMaker model package approval action, which is part of a SageMaker lineage."""
def datasets(self, direction: LineageQueryDirectionEnum=LineageQueryDirectionEnum.ASCENDANTS) -> List[Artifact]:
"""Use a lineage query to retrieve all upstream datasets that... | the_stack_v2_python_sparse | src/sagemaker/lineage/action.py | aws/sagemaker-python-sdk | train | 2,050 |
79c6dcf36a28b214983ccc7cef64c1052c0c04ab | [
"temp = sorted(nums)\nstart = -1\nend = -2\nfor i in range(len(nums)):\n if temp[i] != nums[i]:\n start = i\n break\nfor j in range(len(nums))[::-1]:\n if temp[j] != nums[j]:\n end = j\n break\nreturn end - start + 1",
"start = -1\nend = -2\nn = len(nums)\nmaxcur = nums[0]\nmincu... | <|body_start_0|>
temp = sorted(nums)
start = -1
end = -2
for i in range(len(nums)):
if temp[i] != nums[i]:
start = i
break
for j in range(len(nums))[::-1]:
if temp[j] != nums[j]:
end = j
break... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findUnsortedSubarray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findUnsortedSubarray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
temp = sorted(nums)
... | stack_v2_sparse_classes_36k_train_001008 | 1,527 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findUnsortedSubarray",
"signature": "def findUnsortedSubarray(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findUnsortedSubarray",
"signature": "def findUnsortedSubarray(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002026 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findUnsortedSubarray(self, nums): :type nums: List[int] :rtype: int
- def findUnsortedSubarray(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findUnsortedSubarray(self, nums): :type nums: List[int] :rtype: int
- def findUnsortedSubarray(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
... | 6698f83614b01e43147f869a342e0e30943f4cf3 | <|skeleton|>
class Solution:
def findUnsortedSubarray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findUnsortedSubarray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findUnsortedSubarray(self, nums):
""":type nums: List[int] :rtype: int"""
temp = sorted(nums)
start = -1
end = -2
for i in range(len(nums)):
if temp[i] != nums[i]:
start = i
break
for j in range(len(nums)... | the_stack_v2_python_sparse | LeetCode/Easy/Shortest_Unsorted_Continuous_Subarray.py | kongyitian/coding_interviews | train | 0 | |
f2a7002db877d3ca46d3b3749af4876ae0da4027 | [
"self.conv1 = ConvModule(self.in_channels, 64, kernel_size=7, stride=2, padding=3, bias=False, conv_cfg=self.conv_cfg, norm_cfg=self.norm_cfg, act_cfg=self.act_cfg)\nself.maxpool3d_1 = nn.MaxPool3d(kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 0, 0))\nself.maxpool3d_2 = nn.MaxPool3d(kernel_size=(2, 1, 1), st... | <|body_start_0|>
self.conv1 = ConvModule(self.in_channels, 64, kernel_size=7, stride=2, padding=3, bias=False, conv_cfg=self.conv_cfg, norm_cfg=self.norm_cfg, act_cfg=self.act_cfg)
self.maxpool3d_1 = nn.MaxPool3d(kernel_size=(1, 3, 3), stride=(1, 2, 2), padding=(0, 0, 0))
self.maxpool3d_2 = nn.M... | C2D backbone. Compared to ResNet-50, a temporal-pool is added after the first bottleneck. Detailed structure is kept same as "video-nonlocal-net" repo. Please refer to https://github.com/facebookresearch/video-nonlocal-net/blob /main/scripts/run_c2d_baseline_400k.sh. Please note that there are some improvements compare... | C2D | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class C2D:
"""C2D backbone. Compared to ResNet-50, a temporal-pool is added after the first bottleneck. Detailed structure is kept same as "video-nonlocal-net" repo. Please refer to https://github.com/facebookresearch/video-nonlocal-net/blob /main/scripts/run_c2d_baseline_400k.sh. Please note that ther... | stack_v2_sparse_classes_36k_train_001009 | 3,040 | permissive | [
{
"docstring": "Construct the stem layers consists of a conv+norm+act module and a pooling layer.",
"name": "_make_stem_layer",
"signature": "def _make_stem_layer(self) -> None"
},
{
"docstring": "Defines the computation performed at every call. Args: x (torch.Tensor): The input data. Returns: U... | 2 | null | Implement the Python class `C2D` described below.
Class description:
C2D backbone. Compared to ResNet-50, a temporal-pool is added after the first bottleneck. Detailed structure is kept same as "video-nonlocal-net" repo. Please refer to https://github.com/facebookresearch/video-nonlocal-net/blob /main/scripts/run_c2d_... | Implement the Python class `C2D` described below.
Class description:
C2D backbone. Compared to ResNet-50, a temporal-pool is added after the first bottleneck. Detailed structure is kept same as "video-nonlocal-net" repo. Please refer to https://github.com/facebookresearch/video-nonlocal-net/blob /main/scripts/run_c2d_... | 582b78fd6c3240500d5cacd292339d7d1ddbb056 | <|skeleton|>
class C2D:
"""C2D backbone. Compared to ResNet-50, a temporal-pool is added after the first bottleneck. Detailed structure is kept same as "video-nonlocal-net" repo. Please refer to https://github.com/facebookresearch/video-nonlocal-net/blob /main/scripts/run_c2d_baseline_400k.sh. Please note that ther... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class C2D:
"""C2D backbone. Compared to ResNet-50, a temporal-pool is added after the first bottleneck. Detailed structure is kept same as "video-nonlocal-net" repo. Please refer to https://github.com/facebookresearch/video-nonlocal-net/blob /main/scripts/run_c2d_baseline_400k.sh. Please note that there are some im... | the_stack_v2_python_sparse | mmaction/models/backbones/c2d.py | open-mmlab/mmaction2 | train | 3,498 |
f71d46c318b9366ee0575837d8cf89fe149d40a0 | [
"dic = collections.Counter(nums)\nmaxValue = 0\nfor i in dic:\n if dic[i] > maxValue:\n maxValue = dic[i]\nres = len(nums)\nfor i in dic:\n if dic[i] == maxValue:\n index_left = nums.index(i)\n index_right = nums[::-1].index(i)\n length = len(nums) - (index_left + index_right)\n ... | <|body_start_0|>
dic = collections.Counter(nums)
maxValue = 0
for i in dic:
if dic[i] > maxValue:
maxValue = dic[i]
res = len(nums)
for i in dic:
if dic[i] == maxValue:
index_left = nums.index(i)
index_right ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findShortestSubArray(self, nums: List[int]) -> int:
"""执行用时 :1672 ms, 在所有 Python3 提交中击败了13.05%的用户 内存消耗 :14.7 MB, 在所有 Python3 提交中击败了12.50%的用户 第一遍的答案 :param nums: :return:"""
<|body_0|>
def findShortestSubArray2(self, nums: List[int]) -> int:
"""执行用时 :260... | stack_v2_sparse_classes_36k_train_001010 | 3,311 | no_license | [
{
"docstring": "执行用时 :1672 ms, 在所有 Python3 提交中击败了13.05%的用户 内存消耗 :14.7 MB, 在所有 Python3 提交中击败了12.50%的用户 第一遍的答案 :param nums: :return:",
"name": "findShortestSubArray",
"signature": "def findShortestSubArray(self, nums: List[int]) -> int"
},
{
"docstring": "执行用时 :260 ms, 在所有 Python3 提交中击败了93.81%的用户 ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findShortestSubArray(self, nums: List[int]) -> int: 执行用时 :1672 ms, 在所有 Python3 提交中击败了13.05%的用户 内存消耗 :14.7 MB, 在所有 Python3 提交中击败了12.50%的用户 第一遍的答案 :param nums: :return:
- def f... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findShortestSubArray(self, nums: List[int]) -> int: 执行用时 :1672 ms, 在所有 Python3 提交中击败了13.05%的用户 内存消耗 :14.7 MB, 在所有 Python3 提交中击败了12.50%的用户 第一遍的答案 :param nums: :return:
- def f... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def findShortestSubArray(self, nums: List[int]) -> int:
"""执行用时 :1672 ms, 在所有 Python3 提交中击败了13.05%的用户 内存消耗 :14.7 MB, 在所有 Python3 提交中击败了12.50%的用户 第一遍的答案 :param nums: :return:"""
<|body_0|>
def findShortestSubArray2(self, nums: List[int]) -> int:
"""执行用时 :260... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findShortestSubArray(self, nums: List[int]) -> int:
"""执行用时 :1672 ms, 在所有 Python3 提交中击败了13.05%的用户 内存消耗 :14.7 MB, 在所有 Python3 提交中击败了12.50%的用户 第一遍的答案 :param nums: :return:"""
dic = collections.Counter(nums)
maxValue = 0
for i in dic:
if dic[i] > maxValue... | the_stack_v2_python_sparse | LeetCode/697. Degree of an Array.py | yiming1012/MyLeetCode | train | 2 | |
f720b5011987aa38eaca3b0ccf778cb043c22c57 | [
"super(Encoder, self).__init__()\nself.N = N\nself.dm = dm\nself.embedding = tf.keras.layers.Embedding(input_vocab, dm)\nself.positional_encoding = positional_encoding(max_seq_len, self.dm)\nself.blocks = [EncoderBlock(dm, h, hidden, drop_rate) for n in range(self.N)]\nself.dropout = tf.keras.layers.Dropout(drop_ra... | <|body_start_0|>
super(Encoder, self).__init__()
self.N = N
self.dm = dm
self.embedding = tf.keras.layers.Embedding(input_vocab, dm)
self.positional_encoding = positional_encoding(max_seq_len, self.dm)
self.blocks = [EncoderBlock(dm, h, hidden, drop_rate) for n in range(s... | Encoder Class | Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
"""Encoder Class"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (int): the number of heads. hidden (int): the number of hi... | stack_v2_sparse_classes_36k_train_001011 | 2,055 | no_license | [
{
"docstring": "Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (int): the number of heads. hidden (int): the number of hidden units in the fully connected layer. input_vocab (int): the size of the input vocabulary. max_seq_len (int): the maximu... | 2 | null | Implement the Python class `Encoder` described below.
Class description:
Encoder Class
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (... | Implement the Python class `Encoder` described below.
Class description:
Encoder Class
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (... | 5aff923277cfe9f2b5324a773e4e5c3cac810a0c | <|skeleton|>
class Encoder:
"""Encoder Class"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (int): the number of heads. hidden (int): the number of hi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder:
"""Encoder Class"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (int): the number of heads. hidden (int): the number of hidden units in... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/9-transformer_encoder.py | cmmolanos1/holbertonschool-machine_learning | train | 1 |
bb91cbc762751f307b2ddc76f1a358afd5daa74d | [
"rset = ResultSet(names=('uuid', 'provider_id', 'av_zone', 'addresses'), types=(str, str, str, str))\nif not skip_store:\n if generic_filters or meta_filters:\n raise _errors.ConfigurationError(\"Filters are only supported when the 'skip_store' option is set.\")\n provider = _retrieve_provider(provider... | <|body_start_0|>
rset = ResultSet(names=('uuid', 'provider_id', 'av_zone', 'addresses'), types=(str, str, str, str))
if not skip_store:
if generic_filters or meta_filters:
raise _errors.ConfigurationError("Filters are only supported when the 'skip_store' option is set.")
... | Return information on existing machine(s) created by a provider. | MachineLookup | [
"Apache-2.0",
"LicenseRef-scancode-python-cwi",
"LGPL-2.0-or-later",
"BSD-3-Clause",
"bzip2-1.0.6",
"LicenseRef-scancode-free-unknown",
"GPL-2.0-only",
"LicenseRef-scancode-other-copyleft",
"Sleepycat",
"LicenseRef-scancode-proprietary-license",
"LicenseRef-scancode-unknown-license-reference",
... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MachineLookup:
"""Return information on existing machine(s) created by a provider."""
def execute(self, provider_id, generic_filters=None, meta_filters=None, skip_store=False):
"""Return information on existing machine(s). :param provider_id: Provider's Id. :param generic_filters: Fi... | stack_v2_sparse_classes_36k_train_001012 | 19,734 | permissive | [
{
"docstring": "Return information on existing machine(s). :param provider_id: Provider's Id. :param generic_filters: Filter returned machines by some properites but metadata properties. :param meta_filters: Filter returned machines by metadata properties. :param skip_store: Proceed anyway if there is no inform... | 2 | stack_v2_sparse_classes_30k_train_011720 | Implement the Python class `MachineLookup` described below.
Class description:
Return information on existing machine(s) created by a provider.
Method signatures and docstrings:
- def execute(self, provider_id, generic_filters=None, meta_filters=None, skip_store=False): Return information on existing machine(s). :par... | Implement the Python class `MachineLookup` described below.
Class description:
Return information on existing machine(s) created by a provider.
Method signatures and docstrings:
- def execute(self, provider_id, generic_filters=None, meta_filters=None, skip_store=False): Return information on existing machine(s). :par... | 1e912fd87282be3b3bed48487e6beb0ecb1de339 | <|skeleton|>
class MachineLookup:
"""Return information on existing machine(s) created by a provider."""
def execute(self, provider_id, generic_filters=None, meta_filters=None, skip_store=False):
"""Return information on existing machine(s). :param provider_id: Provider's Id. :param generic_filters: Fi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MachineLookup:
"""Return information on existing machine(s) created by a provider."""
def execute(self, provider_id, generic_filters=None, meta_filters=None, skip_store=False):
"""Return information on existing machine(s). :param provider_id: Provider's Id. :param generic_filters: Filter returned... | the_stack_v2_python_sparse | mysql-utilities-1.6.0/mysql/fabric/services/machine.py | scavarda/mysql-dbcompare | train | 2 |
f3796b5ce9e7e3df872886bef92f085c57425ddc | [
"if self.action == 'retrieve':\n permission_classes = [IsAuthenticated]\nelse:\n permission_classes = [IsAdminUser]\nreturn [permission() for permission in permission_classes]",
"if pk == 'i':\n return response.Response(UserSerializer(request.user, context={'request': request}).data)\nreturn super(UserVi... | <|body_start_0|>
if self.action == 'retrieve':
permission_classes = [IsAuthenticated]
else:
permission_classes = [IsAdminUser]
return [permission() for permission in permission_classes]
<|end_body_0|>
<|body_start_1|>
if pk == 'i':
return response.Res... | UserViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserViewSet:
def get_permissions(self):
"""Instantiates and returns the list of permissions that this view requires."""
<|body_0|>
def retrieve(self, request, pk=None):
"""este metodo serve para retornar informacoes do usuario logado e so retorna informacao se o id p... | stack_v2_sparse_classes_36k_train_001013 | 42,051 | permissive | [
{
"docstring": "Instantiates and returns the list of permissions that this view requires.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "este metodo serve para retornar informacoes do usuario logado e so retorna informacao se o id passado por 'i'",
"... | 2 | stack_v2_sparse_classes_30k_train_006762 | Implement the Python class `UserViewSet` described below.
Class description:
Implement the UserViewSet class.
Method signatures and docstrings:
- def get_permissions(self): Instantiates and returns the list of permissions that this view requires.
- def retrieve(self, request, pk=None): este metodo serve para retornar... | Implement the Python class `UserViewSet` described below.
Class description:
Implement the UserViewSet class.
Method signatures and docstrings:
- def get_permissions(self): Instantiates and returns the list of permissions that this view requires.
- def retrieve(self, request, pk=None): este metodo serve para retornar... | 54c63d84c81cc3d2ca12485f932f12b46d0603e1 | <|skeleton|>
class UserViewSet:
def get_permissions(self):
"""Instantiates and returns the list of permissions that this view requires."""
<|body_0|>
def retrieve(self, request, pk=None):
"""este metodo serve para retornar informacoes do usuario logado e so retorna informacao se o id p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserViewSet:
def get_permissions(self):
"""Instantiates and returns the list of permissions that this view requires."""
if self.action == 'retrieve':
permission_classes = [IsAuthenticated]
else:
permission_classes = [IsAdminUser]
return [permission() for... | the_stack_v2_python_sparse | core_admin/tno/views.py | linea-it/tno | train | 1 | |
b95402d7cc07ea2f776eec712fe032acd4793238 | [
"url = os.path.join(prefix, filename)\nresponse = self.client.get(url)\nhere = os.path.abspath(os.path.dirname(__file__))\noutput_dir = os.path.join(here, '..', '..', 'js_tmp')\noutput_dir = os.path.abspath(output_dir)\nif not os.path.exists(output_dir):\n os.mkdir(output_dir)\noutput_file = os.path.join(output_... | <|body_start_0|>
url = os.path.join(prefix, filename)
response = self.client.get(url)
here = os.path.abspath(os.path.dirname(__file__))
output_dir = os.path.join(here, '..', '..', 'js_tmp')
output_dir = os.path.abspath(output_dir)
if not os.path.exists(output_dir):
... | A unit test to "render" javascript files. The server renders templated javascript files, we need the fully-rendered files for linting and static tests. | RenderJavascriptFiles | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RenderJavascriptFiles:
"""A unit test to "render" javascript files. The server renders templated javascript files, we need the fully-rendered files for linting and static tests."""
def download_file(self, filename, prefix):
"""Function to `download`(copy) a file to a temporary firect... | stack_v2_sparse_classes_36k_train_001014 | 2,122 | permissive | [
{
"docstring": "Function to `download`(copy) a file to a temporary firectory.",
"name": "download_file",
"signature": "def download_file(self, filename, prefix)"
},
{
"docstring": "Download files in directory.",
"name": "download_files",
"signature": "def download_files(self, subdir, pre... | 3 | stack_v2_sparse_classes_30k_train_008027 | Implement the Python class `RenderJavascriptFiles` described below.
Class description:
A unit test to "render" javascript files. The server renders templated javascript files, we need the fully-rendered files for linting and static tests.
Method signatures and docstrings:
- def download_file(self, filename, prefix): ... | Implement the Python class `RenderJavascriptFiles` described below.
Class description:
A unit test to "render" javascript files. The server renders templated javascript files, we need the fully-rendered files for linting and static tests.
Method signatures and docstrings:
- def download_file(self, filename, prefix): ... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class RenderJavascriptFiles:
"""A unit test to "render" javascript files. The server renders templated javascript files, we need the fully-rendered files for linting and static tests."""
def download_file(self, filename, prefix):
"""Function to `download`(copy) a file to a temporary firect... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RenderJavascriptFiles:
"""A unit test to "render" javascript files. The server renders templated javascript files, we need the fully-rendered files for linting and static tests."""
def download_file(self, filename, prefix):
"""Function to `download`(copy) a file to a temporary firectory."""
... | the_stack_v2_python_sparse | InvenTree/InvenTree/ci_render_js.py | inventree/InvenTree | train | 3,077 |
be326aa2f6a61e1638659defe1e51d619a434f98 | [
"super().__init__(im_ids=im_ids, pos_slice_dict=pos_slice_dict, transforms=transforms, preprocessing=preprocessing, p_pos_per_sample=p_pos_per_sample, mode=mode, num_classes=num_classes)\nself.num_pseudo_slices = num_pseudo_slices\nassert num_pseudo_slices % 2 == 1, '`num_pseudo_slices` must be odd. i.e. 7 -> 3 abo... | <|body_start_0|>
super().__init__(im_ids=im_ids, pos_slice_dict=pos_slice_dict, transforms=transforms, preprocessing=preprocessing, p_pos_per_sample=p_pos_per_sample, mode=mode, num_classes=num_classes)
self.num_pseudo_slices = num_pseudo_slices
assert num_pseudo_slices % 2 == 1, '`num_pseudo_sl... | PseudoSliceDataset | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PseudoSliceDataset:
def __init__(self, im_ids: np.array, pos_slice_dict: dict, transforms=None, preprocessing=None, p_pos_per_sample: float=0.33, mode: str='segmentation', num_classes: int=3, num_pseudo_slices=1):
"""Reads from a directory of 2D slice numpy arrays and samples positive sl... | stack_v2_sparse_classes_36k_train_001015 | 10,666 | permissive | [
{
"docstring": "Reads from a directory of 2D slice numpy arrays and samples positive slices. Assumes the data directory contains 2D slices processed by `io.Preprocessor.save_dir_as_2d()`. Attributes im_ids (np.ndarray): of image names. pos_slice_dict (dict): dictionary generated by `io.Preprocessor.save_dir_as_... | 3 | stack_v2_sparse_classes_30k_train_016224 | Implement the Python class `PseudoSliceDataset` described below.
Class description:
Implement the PseudoSliceDataset class.
Method signatures and docstrings:
- def __init__(self, im_ids: np.array, pos_slice_dict: dict, transforms=None, preprocessing=None, p_pos_per_sample: float=0.33, mode: str='segmentation', num_cl... | Implement the Python class `PseudoSliceDataset` described below.
Class description:
Implement the PseudoSliceDataset class.
Method signatures and docstrings:
- def __init__(self, im_ids: np.array, pos_slice_dict: dict, transforms=None, preprocessing=None, p_pos_per_sample: float=0.33, mode: str='segmentation', num_cl... | 0c1c861ca1a211a840a77e52895548e8d8033470 | <|skeleton|>
class PseudoSliceDataset:
def __init__(self, im_ids: np.array, pos_slice_dict: dict, transforms=None, preprocessing=None, p_pos_per_sample: float=0.33, mode: str='segmentation', num_classes: int=3, num_pseudo_slices=1):
"""Reads from a directory of 2D slice numpy arrays and samples positive sl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PseudoSliceDataset:
def __init__(self, im_ids: np.array, pos_slice_dict: dict, transforms=None, preprocessing=None, p_pos_per_sample: float=0.33, mode: str='segmentation', num_classes: int=3, num_pseudo_slices=1):
"""Reads from a directory of 2D slice numpy arrays and samples positive slices. Assumes ... | the_stack_v2_python_sparse | kits19cnn/io/dataset_2d.py | Ramsha04/kits19_cnn | train | 0 | |
c783eac9327ad43e302fbfb66b43e5ec7bc3c1bf | [
"if not quota_max_calls:\n use_rate_limiter = False\nself._instances = None\nsuper(CloudSqlRepositoryClient, self).__init__(API_NAME, versions=['v1beta4'], quota_max_calls=quota_max_calls, quota_period=quota_period, use_rate_limiter=use_rate_limiter)",
"if not self._instances:\n self._instances = self._init... | <|body_start_0|>
if not quota_max_calls:
use_rate_limiter = False
self._instances = None
super(CloudSqlRepositoryClient, self).__init__(API_NAME, versions=['v1beta4'], quota_max_calls=quota_max_calls, quota_period=quota_period, use_rate_limiter=use_rate_limiter)
<|end_body_0|>
<|bod... | Cloud SQL Admin API Respository. | CloudSqlRepositoryClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CloudSqlRepositoryClient:
"""Cloud SQL Admin API Respository."""
def __init__(self, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True):
"""Constructor. Args: quota_max_calls (int): Allowed requests per <quota_period> for the API. quota_period (float): The time period to t... | stack_v2_sparse_classes_36k_train_001016 | 4,834 | permissive | [
{
"docstring": "Constructor. Args: quota_max_calls (int): Allowed requests per <quota_period> for the API. quota_period (float): The time period to track requests over. use_rate_limiter (bool): Set to false to disable the use of a rate limiter for this service.",
"name": "__init__",
"signature": "def __... | 2 | stack_v2_sparse_classes_30k_train_018218 | Implement the Python class `CloudSqlRepositoryClient` described below.
Class description:
Cloud SQL Admin API Respository.
Method signatures and docstrings:
- def __init__(self, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True): Constructor. Args: quota_max_calls (int): Allowed requests per <quota_period... | Implement the Python class `CloudSqlRepositoryClient` described below.
Class description:
Cloud SQL Admin API Respository.
Method signatures and docstrings:
- def __init__(self, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True): Constructor. Args: quota_max_calls (int): Allowed requests per <quota_period... | d4421afa50a17ed47cbebe942044ebab3720e0f5 | <|skeleton|>
class CloudSqlRepositoryClient:
"""Cloud SQL Admin API Respository."""
def __init__(self, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True):
"""Constructor. Args: quota_max_calls (int): Allowed requests per <quota_period> for the API. quota_period (float): The time period to t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CloudSqlRepositoryClient:
"""Cloud SQL Admin API Respository."""
def __init__(self, quota_max_calls=None, quota_period=1.0, use_rate_limiter=True):
"""Constructor. Args: quota_max_calls (int): Allowed requests per <quota_period> for the API. quota_period (float): The time period to track requests... | the_stack_v2_python_sparse | google/cloud/forseti/common/gcp_api/cloudsql.py | kevensen/forseti-security | train | 1 |
37cf30dadce3f1ff1c8fb8ef0e729a578a2cbdd8 | [
"self.auth = auth\nif isinstance(rid, FaceUDistinguishRecord):\n self.record = rid\nelse:\n self.record = self.get_record_model(rid)",
"if not rid:\n return None\nrecord = FaceUDistinguishRecord.objects.get_once(pk=rid)\nif not record:\n raise FaceURecordInfoExcept.record_is_not_exists()\nreturn recor... | <|body_start_0|>
self.auth = auth
if isinstance(rid, FaceUDistinguishRecord):
self.record = rid
else:
self.record = self.get_record_model(rid)
<|end_body_0|>
<|body_start_1|>
if not rid:
return None
record = FaceUDistinguishRecord.objects.get_... | FaceURecordLogic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaceURecordLogic:
def __init__(self, auth, rid=''):
"""INIT :param auth: :param rid:"""
<|body_0|>
def get_record_model(self, rid):
"""获取记录model :param rid: :return:"""
<|body_1|>
def get_record_info(self):
"""获取记录信息 :return:"""
<|body_2|... | stack_v2_sparse_classes_36k_train_001017 | 1,633 | no_license | [
{
"docstring": "INIT :param auth: :param rid:",
"name": "__init__",
"signature": "def __init__(self, auth, rid='')"
},
{
"docstring": "获取记录model :param rid: :return:",
"name": "get_record_model",
"signature": "def get_record_model(self, rid)"
},
{
"docstring": "获取记录信息 :return:",
... | 3 | stack_v2_sparse_classes_30k_train_005110 | Implement the Python class `FaceURecordLogic` described below.
Class description:
Implement the FaceURecordLogic class.
Method signatures and docstrings:
- def __init__(self, auth, rid=''): INIT :param auth: :param rid:
- def get_record_model(self, rid): 获取记录model :param rid: :return:
- def get_record_info(self): 获取记... | Implement the Python class `FaceURecordLogic` described below.
Class description:
Implement the FaceURecordLogic class.
Method signatures and docstrings:
- def __init__(self, auth, rid=''): INIT :param auth: :param rid:
- def get_record_model(self, rid): 获取记录model :param rid: :return:
- def get_record_info(self): 获取记... | 7467cd66e1fc91f0b3a264f8fc9b93f22f09fe7b | <|skeleton|>
class FaceURecordLogic:
def __init__(self, auth, rid=''):
"""INIT :param auth: :param rid:"""
<|body_0|>
def get_record_model(self, rid):
"""获取记录model :param rid: :return:"""
<|body_1|>
def get_record_info(self):
"""获取记录信息 :return:"""
<|body_2|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FaceURecordLogic:
def __init__(self, auth, rid=''):
"""INIT :param auth: :param rid:"""
self.auth = auth
if isinstance(rid, FaceUDistinguishRecord):
self.record = rid
else:
self.record = self.get_record_model(rid)
def get_record_model(self, rid):
... | the_stack_v2_python_sparse | FireHydrant/server/faceU/logic/record.py | shoogoome/FireHydrant | train | 4 | |
4fd8d489c42581bf70adb761c29d8bce9950ee4e | [
"super().__init__()\nself.use_regex = use_regex\nself._exceptions = exceptions\nself.exceptions = None\nself.case_insensitive = case_insensitive\nself.edit_summary = edit_summary\nself.name = name",
"if not self.exceptions and self._exceptions is not None:\n self.exceptions = dict(self._exceptions)\n precom... | <|body_start_0|>
super().__init__()
self.use_regex = use_regex
self._exceptions = exceptions
self.exceptions = None
self.case_insensitive = case_insensitive
self.edit_summary = edit_summary
self.name = name
<|end_body_0|>
<|body_start_1|>
if not self.exce... | A list of replacements which all share some properties. The shared properties are: * use_regex * exceptions * case_insensitive Each entry in this list should be a ReplacementListEntry. The exceptions are compiled only once. | ReplacementList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReplacementList:
"""A list of replacements which all share some properties. The shared properties are: * use_regex * exceptions * case_insensitive Each entry in this list should be a ReplacementListEntry. The exceptions are compiled only once."""
def __init__(self, use_regex, exceptions, cas... | stack_v2_sparse_classes_36k_train_001018 | 42,775 | permissive | [
{
"docstring": "Create a fix list which can contain multiple replacements.",
"name": "__init__",
"signature": "def __init__(self, use_regex, exceptions, case_insensitive, edit_summary, name) -> None"
},
{
"docstring": "Compile the exceptions if not already done.",
"name": "_compile_exception... | 2 | stack_v2_sparse_classes_30k_train_007307 | Implement the Python class `ReplacementList` described below.
Class description:
A list of replacements which all share some properties. The shared properties are: * use_regex * exceptions * case_insensitive Each entry in this list should be a ReplacementListEntry. The exceptions are compiled only once.
Method signat... | Implement the Python class `ReplacementList` described below.
Class description:
A list of replacements which all share some properties. The shared properties are: * use_regex * exceptions * case_insensitive Each entry in this list should be a ReplacementListEntry. The exceptions are compiled only once.
Method signat... | 5c01e6bfcd328bc6eae643e661f1a0ae57612808 | <|skeleton|>
class ReplacementList:
"""A list of replacements which all share some properties. The shared properties are: * use_regex * exceptions * case_insensitive Each entry in this list should be a ReplacementListEntry. The exceptions are compiled only once."""
def __init__(self, use_regex, exceptions, cas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReplacementList:
"""A list of replacements which all share some properties. The shared properties are: * use_regex * exceptions * case_insensitive Each entry in this list should be a ReplacementListEntry. The exceptions are compiled only once."""
def __init__(self, use_regex, exceptions, case_insensitive... | the_stack_v2_python_sparse | scripts/replace.py | wikimedia/pywikibot | train | 432 |
eb61fcc3acc3bd9619406313a1e48c7f64e90ef5 | [
"self.multiengine = multiengine\nself.dist = dist\nself.targets = targets\nself.block = block",
"max_len = max((len(s) for s in sequences))\nfor s in sequences:\n if len(s) != max_len:\n raise ValueError('all sequences must have equal length')\nassert isinstance(func, (str, FunctionType)), 'func must be... | <|body_start_0|>
self.multiengine = multiengine
self.dist = dist
self.targets = targets
self.block = block
<|end_body_0|>
<|body_start_1|>
max_len = max((len(s) for s in sequences))
for s in sequences:
if len(s) != max_len:
raise ValueError('a... | A Mapper for `IMultiEngine` implementers. | MultiEngineMapper | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiEngineMapper:
"""A Mapper for `IMultiEngine` implementers."""
def __init__(self, multiengine, dist='b', targets='all', block=True):
"""Create a Mapper for a multiengine. The value of all arguments are used for all calls to `map`. This class allows these arguemnts to be set for a... | stack_v2_sparse_classes_36k_train_001019 | 8,554 | permissive | [
{
"docstring": "Create a Mapper for a multiengine. The value of all arguments are used for all calls to `map`. This class allows these arguemnts to be set for a series of map calls. :Parameters: multiengine : `IMultiEngine` implementer The multiengine to use for running the map commands dist : str The type of d... | 2 | stack_v2_sparse_classes_30k_train_010460 | Implement the Python class `MultiEngineMapper` described below.
Class description:
A Mapper for `IMultiEngine` implementers.
Method signatures and docstrings:
- def __init__(self, multiengine, dist='b', targets='all', block=True): Create a Mapper for a multiengine. The value of all arguments are used for all calls to... | Implement the Python class `MultiEngineMapper` described below.
Class description:
A Mapper for `IMultiEngine` implementers.
Method signatures and docstrings:
- def __init__(self, multiengine, dist='b', targets='all', block=True): Create a Mapper for a multiengine. The value of all arguments are used for all calls to... | 1cf44de3833929a4cf9e0069e8c75ef9086eeaca | <|skeleton|>
class MultiEngineMapper:
"""A Mapper for `IMultiEngine` implementers."""
def __init__(self, multiengine, dist='b', targets='all', block=True):
"""Create a Mapper for a multiengine. The value of all arguments are used for all calls to `map`. This class allows these arguemnts to be set for a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiEngineMapper:
"""A Mapper for `IMultiEngine` implementers."""
def __init__(self, multiengine, dist='b', targets='all', block=True):
"""Create a Mapper for a multiengine. The value of all arguments are used for all calls to `map`. This class allows these arguemnts to be set for a series of ma... | the_stack_v2_python_sparse | IPython/kernel/mapper.py | omazapa/ipython | train | 3 |
35b569df012d50638e88f5b01e9ce6e990a15d51 | [
"slow = 0\nfor fast in range(len(nums)):\n if nums[fast] != val:\n nums[slow] = nums[fast]\n slow += 1\nreturn slow",
"start, end = (0, len(nums) - 1)\nwhile start <= end:\n if nums[start] == val:\n nums[start], nums[end] = (nums[end], nums[start])\n end -= 1\n else:\n ... | <|body_start_0|>
slow = 0
for fast in range(len(nums)):
if nums[fast] != val:
nums[slow] = nums[fast]
slow += 1
return slow
<|end_body_0|>
<|body_start_1|>
start, end = (0, len(nums) - 1)
while start <= end:
if nums[start] ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeElement(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int 快慢指针"""
<|body_0|>
def removeElement1(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int 双指针"""
<|body_1|>
def removeElement0(self, nums,... | stack_v2_sparse_classes_36k_train_001020 | 1,558 | no_license | [
{
"docstring": ":type nums: List[int] :type val: int :rtype: int 快慢指针",
"name": "removeElement",
"signature": "def removeElement(self, nums, val)"
},
{
"docstring": ":type nums: List[int] :type val: int :rtype: int 双指针",
"name": "removeElement1",
"signature": "def removeElement1(self, nu... | 3 | stack_v2_sparse_classes_30k_train_000734 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement(self, nums, val): :type nums: List[int] :type val: int :rtype: int 快慢指针
- def removeElement1(self, nums, val): :type nums: List[int] :type val: int :rtype: int ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement(self, nums, val): :type nums: List[int] :type val: int :rtype: int 快慢指针
- def removeElement1(self, nums, val): :type nums: List[int] :type val: int :rtype: int ... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def removeElement(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int 快慢指针"""
<|body_0|>
def removeElement1(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int 双指针"""
<|body_1|>
def removeElement0(self, nums,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeElement(self, nums, val):
""":type nums: List[int] :type val: int :rtype: int 快慢指针"""
slow = 0
for fast in range(len(nums)):
if nums[fast] != val:
nums[slow] = nums[fast]
slow += 1
return slow
def removeElemen... | the_stack_v2_python_sparse | 27.移除元素.py | yangyuxiang1996/leetcode | train | 0 | |
793cf1e354c383c49617a82de8a30d5c251cffae | [
"address = address.lower()\nverify_existing_address(address)\nactivehome.action.send('sendplc', address, 'on')",
"address = address.lower()\nverify_existing_address(address)\nactivehome.action.send('sendplc', address, 'off')"
] | <|body_start_0|>
address = address.lower()
verify_existing_address(address)
activehome.action.send('sendplc', address, 'on')
<|end_body_0|>
<|body_start_1|>
address = address.lower()
verify_existing_address(address)
activehome.action.send('sendplc', address, 'off')
<|end... | The home daemon is a higher-level interface to ActiveHome. It allows modules to be configured, turned on, and turned off. It supports various types of modules, such as cameras (turning on any camera will cause all other cameras to be turned off) and chimes (turning off a chime has no effect, but it can be turned on mul... | Interface | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Interface:
"""The home daemon is a higher-level interface to ActiveHome. It allows modules to be configured, turned on, and turned off. It supports various types of modules, such as cameras (turning on any camera will cause all other cameras to be turned off) and chimes (turning off a chime has n... | stack_v2_sparse_classes_36k_train_001021 | 2,335 | no_license | [
{
"docstring": "Turns the specified module on. This module must be in the configuration file. This function will take special module types into effect; for example, calling this function on a camera will automatically turn all other cameras off.",
"name": "on",
"signature": "def on(self, address)"
},
... | 2 | null | Implement the Python class `Interface` described below.
Class description:
The home daemon is a higher-level interface to ActiveHome. It allows modules to be configured, turned on, and turned off. It supports various types of modules, such as cameras (turning on any camera will cause all other cameras to be turned off... | Implement the Python class `Interface` described below.
Class description:
The home daemon is a higher-level interface to ActiveHome. It allows modules to be configured, turned on, and turned off. It supports various types of modules, such as cameras (turning on any camera will cause all other cameras to be turned off... | d9d95e24673794a20bb8138ce44d5bac236e07ed | <|skeleton|>
class Interface:
"""The home daemon is a higher-level interface to ActiveHome. It allows modules to be configured, turned on, and turned off. It supports various types of modules, such as cameras (turning on any camera will cause all other cameras to be turned off) and chimes (turning off a chime has n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Interface:
"""The home daemon is a higher-level interface to ActiveHome. It allows modules to be configured, turned on, and turned off. It supports various types of modules, such as cameras (turning on any camera will cause all other cameras to be turned off) and chimes (turning off a chime has no effect, but... | the_stack_v2_python_sparse | afn/python/src/homed.py | javawizard/afn | train | 0 |
f87425751fa98f2c33671d5fa3caa80064e6460f | [
"self.s1 = []\nself.s2 = []\nself.front = None",
"if not self.s1:\n self.front = x\nself.s1.append(x)",
"if not self.s2:\n while self.s1:\n self.s2.append(self.s1.pop())\nreturn self.s2.pop()",
"if self.s2:\n return self.s2[-1]\nreturn self.front",
"if not self.s1 and (not self.s2):\n ret... | <|body_start_0|>
self.s1 = []
self.s2 = []
self.front = None
<|end_body_0|>
<|body_start_1|>
if not self.s1:
self.front = x
self.s1.append(x)
<|end_body_1|>
<|body_start_2|>
if not self.s2:
while self.s1:
self.s2.append(self.s1.po... | MyQueue | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyQueue:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def push(self, x: int) -> None:
"""Push element x to the back of queue."""
<|body_1|>
def pop(self) -> int:
"""Removes the element from in front of queue and retur... | stack_v2_sparse_classes_36k_train_001022 | 3,995 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Push element x to the back of queue.",
"name": "push",
"signature": "def push(self, x: int) -> None"
},
{
"docstring": "Removes the element from in fron... | 5 | stack_v2_sparse_classes_30k_train_012994 | Implement the Python class `MyQueue` described below.
Class description:
Implement the MyQueue class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def push(self, x: int) -> None: Push element x to the back of queue.
- def pop(self) -> int: Removes the element from in ... | Implement the Python class `MyQueue` described below.
Class description:
Implement the MyQueue class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def push(self, x: int) -> None: Push element x to the back of queue.
- def pop(self) -> int: Removes the element from in ... | 2e68822e82df37e8347a7c16616a0a99a8075c3f | <|skeleton|>
class MyQueue:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def push(self, x: int) -> None:
"""Push element x to the back of queue."""
<|body_1|>
def pop(self) -> int:
"""Removes the element from in front of queue and retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyQueue:
def __init__(self):
"""Initialize your data structure here."""
self.s1 = []
self.s2 = []
self.front = None
def push(self, x: int) -> None:
"""Push element x to the back of queue."""
if not self.s1:
self.front = x
self.s1.append(... | the_stack_v2_python_sparse | leet_code/232. 用栈实现队列.py | muyisanshuiliang/python | train | 0 | |
399e33108e8183e8a5a282f9388dd0dc383ea088 | [
"super(DecodeLeaf, self).__init__()\nself.in_channel = in_channel\nself.conv1x1 = nn.Conv1d(in_channel, 1, 1, 1, 0)\nself.scale = Parameter(0.5 * torch.ones(1))",
"x = self.conv1x1(x).squeeze(1)\nx = self.scale * 0.5 * torch.tanh(x)\nreturn x"
] | <|body_start_0|>
super(DecodeLeaf, self).__init__()
self.in_channel = in_channel
self.conv1x1 = nn.Conv1d(in_channel, 1, 1, 1, 0)
self.scale = Parameter(0.5 * torch.ones(1))
<|end_body_0|>
<|body_start_1|>
x = self.conv1x1(x).squeeze(1)
x = self.scale * 0.5 * torch.tanh(... | DecodeLeaf | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecodeLeaf:
def __init__(self, in_channel):
""":param in_channel: input planes"""
<|body_0|>
def forward(self, x):
""":param x: tensor of shape (N, C, L) :return tensor of shape (N, L)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(DecodeLeaf... | stack_v2_sparse_classes_36k_train_001023 | 7,677 | no_license | [
{
"docstring": ":param in_channel: input planes",
"name": "__init__",
"signature": "def __init__(self, in_channel)"
},
{
"docstring": ":param x: tensor of shape (N, C, L) :return tensor of shape (N, L)",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018628 | Implement the Python class `DecodeLeaf` described below.
Class description:
Implement the DecodeLeaf class.
Method signatures and docstrings:
- def __init__(self, in_channel): :param in_channel: input planes
- def forward(self, x): :param x: tensor of shape (N, C, L) :return tensor of shape (N, L) | Implement the Python class `DecodeLeaf` described below.
Class description:
Implement the DecodeLeaf class.
Method signatures and docstrings:
- def __init__(self, in_channel): :param in_channel: input planes
- def forward(self, x): :param x: tensor of shape (N, C, L) :return tensor of shape (N, L)
<|skeleton|>
class... | 666bbecd9f9b2c9bebaf82deab3ccb8586d60dca | <|skeleton|>
class DecodeLeaf:
def __init__(self, in_channel):
""":param in_channel: input planes"""
<|body_0|>
def forward(self, x):
""":param x: tensor of shape (N, C, L) :return tensor of shape (N, L)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecodeLeaf:
def __init__(self, in_channel):
""":param in_channel: input planes"""
super(DecodeLeaf, self).__init__()
self.in_channel = in_channel
self.conv1x1 = nn.Conv1d(in_channel, 1, 1, 1, 0)
self.scale = Parameter(0.5 * torch.ones(1))
def forward(self, x):
... | the_stack_v2_python_sparse | experiments/exp3_segmentation/model.py | maxjiang93/DDSL | train | 55 | |
983143aa0915f882aeaee564716774482ff8c522 | [
"self.url = cmds.url\nresponse = requests.get(f'{self.url}').text\nself.htmlcontent = BeautifulSoup(response, 'html.parser')",
"dwnload = cmds.download\nanchors = self.htmlcontent.find_all('img')\nfiltered_list = list(set(anchors))\nfor images in filtered_list:\n print(self.url + images['src'])\n'If --download... | <|body_start_0|>
self.url = cmds.url
response = requests.get(f'{self.url}').text
self.htmlcontent = BeautifulSoup(response, 'html.parser')
<|end_body_0|>
<|body_start_1|>
dwnload = cmds.download
anchors = self.htmlcontent.find_all('img')
filtered_list = list(set(anchors)... | Fetch | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Fetch:
def __init__(self):
"""Requests passed urls and Store Response for Further use"""
<|body_0|>
def pull_images(self):
"""Scrapes all Images links found in img tage"""
<|body_1|>
def get_all_links(self):
"""Get Scrapes All links found in anch... | stack_v2_sparse_classes_36k_train_001024 | 2,996 | permissive | [
{
"docstring": "Requests passed urls and Store Response for Further use",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Scrapes all Images links found in img tage",
"name": "pull_images",
"signature": "def pull_images(self)"
},
{
"docstring": "Get Scrap... | 3 | stack_v2_sparse_classes_30k_train_010687 | Implement the Python class `Fetch` described below.
Class description:
Implement the Fetch class.
Method signatures and docstrings:
- def __init__(self): Requests passed urls and Store Response for Further use
- def pull_images(self): Scrapes all Images links found in img tage
- def get_all_links(self): Get Scrapes A... | Implement the Python class `Fetch` described below.
Class description:
Implement the Fetch class.
Method signatures and docstrings:
- def __init__(self): Requests passed urls and Store Response for Further use
- def pull_images(self): Scrapes all Images links found in img tage
- def get_all_links(self): Get Scrapes A... | 70a3d5d798e2987d37e7562d2e556f364627a59c | <|skeleton|>
class Fetch:
def __init__(self):
"""Requests passed urls and Store Response for Further use"""
<|body_0|>
def pull_images(self):
"""Scrapes all Images links found in img tage"""
<|body_1|>
def get_all_links(self):
"""Get Scrapes All links found in anch... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Fetch:
def __init__(self):
"""Requests passed urls and Store Response for Further use"""
self.url = cmds.url
response = requests.get(f'{self.url}').text
self.htmlcontent = BeautifulSoup(response, 'html.parser')
def pull_images(self):
"""Scrapes all Images links fou... | the_stack_v2_python_sparse | Python-Programs/webpage-link-image-scraper/webpage-link-image-scraper/fetch.py | MMVonnSeek/Hacktoberfest-2021 | train | 5 | |
b4fd9bffee583db8cc45237db4c0604fa3a2c574 | [
"super(AddNoiseToVehicle, self).__init__(name)\nself.logger.debug('%s.__init__()' % self.__class__.__name__)\nself._control = carla.VehicleControl()\nself._actor = actor\nself._steer_value = steer_value\nself._throttle_value = throttle_value",
"self._control = self._actor.get_control()\nself._control.steer = self... | <|body_start_0|>
super(AddNoiseToVehicle, self).__init__(name)
self.logger.debug('%s.__init__()' % self.__class__.__name__)
self._control = carla.VehicleControl()
self._actor = actor
self._steer_value = steer_value
self._throttle_value = throttle_value
<|end_body_0|>
<|b... | This class contains an atomic jitter behavior. To add noise to steer as well as throttle of the vehicle. Important parameters: - actor: CARLA actor to execute the behavior - steer_value: Applied steering noise in [0,1] - throttle_value: Applied throttle noise in [0,1] The behavior terminates after setting the new actor... | AddNoiseToVehicle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddNoiseToVehicle:
"""This class contains an atomic jitter behavior. To add noise to steer as well as throttle of the vehicle. Important parameters: - actor: CARLA actor to execute the behavior - steer_value: Applied steering noise in [0,1] - throttle_value: Applied throttle noise in [0,1] The be... | stack_v2_sparse_classes_36k_train_001025 | 39,839 | permissive | [
{
"docstring": "Setup actor , maximum steer value and throttle value",
"name": "__init__",
"signature": "def __init__(self, actor, steer_value, throttle_value, name='Jittering')"
},
{
"docstring": "Set steer to steer_value and throttle to throttle_value until reaching full stop",
"name": "up... | 2 | null | Implement the Python class `AddNoiseToVehicle` described below.
Class description:
This class contains an atomic jitter behavior. To add noise to steer as well as throttle of the vehicle. Important parameters: - actor: CARLA actor to execute the behavior - steer_value: Applied steering noise in [0,1] - throttle_value:... | Implement the Python class `AddNoiseToVehicle` described below.
Class description:
This class contains an atomic jitter behavior. To add noise to steer as well as throttle of the vehicle. Important parameters: - actor: CARLA actor to execute the behavior - steer_value: Applied steering noise in [0,1] - throttle_value:... | 8ab0894b92e1f994802a218002021ee075c405bf | <|skeleton|>
class AddNoiseToVehicle:
"""This class contains an atomic jitter behavior. To add noise to steer as well as throttle of the vehicle. Important parameters: - actor: CARLA actor to execute the behavior - steer_value: Applied steering noise in [0,1] - throttle_value: Applied throttle noise in [0,1] The be... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddNoiseToVehicle:
"""This class contains an atomic jitter behavior. To add noise to steer as well as throttle of the vehicle. Important parameters: - actor: CARLA actor to execute the behavior - steer_value: Applied steering noise in [0,1] - throttle_value: Applied throttle noise in [0,1] The behavior termin... | the_stack_v2_python_sparse | carla_rllib/carla_rllib-prak_evaluator-carla_rllib-prak_evaluator/carla_rllib/prak_evaluator/srunner/scenarioconfigs/scenariomanager/scenarioatomics/atomic_behaviors.py | TinaMenke/Deep-Reinforcement-Learning | train | 9 |
20d5095d9f428e5cf571296bdb759f3fbbe2c270 | [
"if root is None:\n return 0\nres_list = []\nqueue = [root]\nwhile queue:\n res = []\n node_list = []\n for node in queue:\n res.append(node.val)\n if node.children:\n node_list.extend(node.children)\n queue = node_list\n res_list.append(res)\nreturn len(res_list)",
"if ... | <|body_start_0|>
if root is None:
return 0
res_list = []
queue = [root]
while queue:
res = []
node_list = []
for node in queue:
res.append(node.val)
if node.children:
node_list.extend(node... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxDepth(self, root):
"""广度优先，层序遍历 :type root: Node :rtype: int"""
<|body_0|>
def maxDepth2(self, root):
"""深度优先 :type root: Node :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
return 0
... | stack_v2_sparse_classes_36k_train_001026 | 1,952 | no_license | [
{
"docstring": "广度优先，层序遍历 :type root: Node :rtype: int",
"name": "maxDepth",
"signature": "def maxDepth(self, root)"
},
{
"docstring": "深度优先 :type root: Node :rtype: int",
"name": "maxDepth2",
"signature": "def maxDepth2(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000153 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root): 广度优先，层序遍历 :type root: Node :rtype: int
- def maxDepth2(self, root): 深度优先 :type root: Node :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root): 广度优先，层序遍历 :type root: Node :rtype: int
- def maxDepth2(self, root): 深度优先 :type root: Node :rtype: int
<|skeleton|>
class Solution:
def maxDepth(se... | 3b13b36f37eb364410b3b5b4f10a1808d8b1111e | <|skeleton|>
class Solution:
def maxDepth(self, root):
"""广度优先，层序遍历 :type root: Node :rtype: int"""
<|body_0|>
def maxDepth2(self, root):
"""深度优先 :type root: Node :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxDepth(self, root):
"""广度优先，层序遍历 :type root: Node :rtype: int"""
if root is None:
return 0
res_list = []
queue = [root]
while queue:
res = []
node_list = []
for node in queue:
res.append(nod... | the_stack_v2_python_sparse | leetcode/559.py | yanggelinux/algorithm-data-structure | train | 0 | |
c7ebeb7082d5ebac1e4aca2f8b739b0b030e0694 | [
"try:\n payload = jwt.decode(data, settings.SECRET_KEY, algorithm=['HS256'])\nexcept jwt.ExpiredSignatureError:\n raise serializers.ValidationError('Verificacion link has expired')\nexcept jwt.PyJWTError:\n raise serializers.ValidationError('Invalid token')\nif payload['type'] != 'email_confirmation':\n ... | <|body_start_0|>
try:
payload = jwt.decode(data, settings.SECRET_KEY, algorithm=['HS256'])
except jwt.ExpiredSignatureError:
raise serializers.ValidationError('Verificacion link has expired')
except jwt.PyJWTError:
raise serializers.ValidationError('Invalid to... | Account verification serializer | AccountVerificationSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountVerificationSerializer:
"""Account verification serializer"""
def validate_token(self, data):
"""Verify token is valid"""
<|body_0|>
def save(self):
"""Update users verified status"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_36k_train_001027 | 5,109 | no_license | [
{
"docstring": "Verify token is valid",
"name": "validate_token",
"signature": "def validate_token(self, data)"
},
{
"docstring": "Update users verified status",
"name": "save",
"signature": "def save(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006253 | Implement the Python class `AccountVerificationSerializer` described below.
Class description:
Account verification serializer
Method signatures and docstrings:
- def validate_token(self, data): Verify token is valid
- def save(self): Update users verified status | Implement the Python class `AccountVerificationSerializer` described below.
Class description:
Account verification serializer
Method signatures and docstrings:
- def validate_token(self, data): Verify token is valid
- def save(self): Update users verified status
<|skeleton|>
class AccountVerificationSerializer:
... | 0cede53169041667bd40bbce3c4774af84ffc2fa | <|skeleton|>
class AccountVerificationSerializer:
"""Account verification serializer"""
def validate_token(self, data):
"""Verify token is valid"""
<|body_0|>
def save(self):
"""Update users verified status"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountVerificationSerializer:
"""Account verification serializer"""
def validate_token(self, data):
"""Verify token is valid"""
try:
payload = jwt.decode(data, settings.SECRET_KEY, algorithm=['HS256'])
except jwt.ExpiredSignatureError:
raise serializers.Va... | the_stack_v2_python_sparse | users/serializers/users.py | KrystellCR/DjangoRF | train | 0 |
84f0181cd48491109c751a518356c6176ca7c44e | [
"super(Inclusive, self).__init__()\ninclusivespec = cfnlint.helpers.load_resource(AdditionalSpecs, 'Inclusive.json')\nself.resource_types_specs = inclusivespec['ResourceTypes']\nself.property_types_specs = inclusivespec['PropertyTypes']\nfor resource_type_spec in self.resource_types_specs:\n self.resource_proper... | <|body_start_0|>
super(Inclusive, self).__init__()
inclusivespec = cfnlint.helpers.load_resource(AdditionalSpecs, 'Inclusive.json')
self.resource_types_specs = inclusivespec['ResourceTypes']
self.property_types_specs = inclusivespec['PropertyTypes']
for resource_type_spec in self... | Check Properties Resource Configuration | Inclusive | [
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Inclusive:
"""Check Properties Resource Configuration"""
def __init__(self):
"""Init"""
<|body_0|>
def check(self, properties, inclusions, path, cfn):
"""Check itself"""
<|body_1|>
def match_resource_sub_properties(self, properties, property_type, pa... | stack_v2_sparse_classes_36k_train_001028 | 3,327 | permissive | [
{
"docstring": "Init",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Check itself",
"name": "check",
"signature": "def check(self, properties, inclusions, path, cfn)"
},
{
"docstring": "Match for sub properties",
"name": "match_resource_sub_properti... | 4 | null | Implement the Python class `Inclusive` described below.
Class description:
Check Properties Resource Configuration
Method signatures and docstrings:
- def __init__(self): Init
- def check(self, properties, inclusions, path, cfn): Check itself
- def match_resource_sub_properties(self, properties, property_type, path, ... | Implement the Python class `Inclusive` described below.
Class description:
Check Properties Resource Configuration
Method signatures and docstrings:
- def __init__(self): Init
- def check(self, properties, inclusions, path, cfn): Check itself
- def match_resource_sub_properties(self, properties, property_type, path, ... | 5176573c2f4cb7313998b4bc0bcb0716b58ea380 | <|skeleton|>
class Inclusive:
"""Check Properties Resource Configuration"""
def __init__(self):
"""Init"""
<|body_0|>
def check(self, properties, inclusions, path, cfn):
"""Check itself"""
<|body_1|>
def match_resource_sub_properties(self, properties, property_type, pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Inclusive:
"""Check Properties Resource Configuration"""
def __init__(self):
"""Init"""
super(Inclusive, self).__init__()
inclusivespec = cfnlint.helpers.load_resource(AdditionalSpecs, 'Inclusive.json')
self.resource_types_specs = inclusivespec['ResourceTypes']
sel... | the_stack_v2_python_sparse | src/cfnlint/rules/resources/properties/Inclusive.py | rene84/cfn-python-lint | train | 1 |
5d88a606103eced4a00d2ac8bd19e6b727ff1827 | [
"sleep(2)\nslot1_number = SC.PUBLIC_SLOT1_PHONE_NUMBER\nhold_time = int(SC.PRIVATE_PHONE_CALL_TIME)\nno_answer_wait_time = int(SC.PRIVATE_PHONE_NO_ANSWER_WAIT_TIME)\ninterval_time = hold_time + no_answer_wait_time + 15\ncall_repeat_times = int(SC.PRIVATE_PHONE_CALL_REPEAT_TIMES)\ndefine_case_success_times = int(SC.... | <|body_start_0|>
sleep(2)
slot1_number = SC.PUBLIC_SLOT1_PHONE_NUMBER
hold_time = int(SC.PRIVATE_PHONE_CALL_TIME)
no_answer_wait_time = int(SC.PRIVATE_PHONE_NO_ANSWER_WAIT_TIME)
interval_time = hold_time + no_answer_wait_time + 15
call_repeat_times = int(SC.PRIVATE_PHONE_... | test_suit_phone_case3 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>} | test_suit_phone_case3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_suit_phone_case3:
"""test_suit_phone_case3 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}"""
def test_case_main(self, case_results):
"""main entry. @type case_results: tuple @param case_results: record some case result information"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_001029 | 3,571 | no_license | [
{
"docstring": "main entry. @type case_results: tuple @param case_results: record some case result information",
"name": "test_case_main",
"signature": "def test_case_main(self, case_results)"
},
{
"docstring": "record the case result",
"name": "test_case_end",
"signature": "def test_cas... | 2 | null | Implement the Python class `test_suit_phone_case3` described below.
Class description:
test_suit_phone_case3 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}
Method signatures and docstrings:
- def test_case_main(self, case_results): main entry. @type case_results: tuple @param case_results: record som... | Implement the Python class `test_suit_phone_case3` described below.
Class description:
test_suit_phone_case3 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}
Method signatures and docstrings:
- def test_case_main(self, case_results): main entry. @type case_results: tuple @param case_results: record som... | a04b717ae437511abae1e7e9e399373c161a7b65 | <|skeleton|>
class test_suit_phone_case3:
"""test_suit_phone_case3 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}"""
def test_case_main(self, case_results):
"""main entry. @type case_results: tuple @param case_results: record some case result information"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test_suit_phone_case3:
"""test_suit_phone_case3 is a class for phone case. @see: L{TestCaseBase <TestCaseBase>}"""
def test_case_main(self, case_results):
"""main entry. @type case_results: tuple @param case_results: record some case result information"""
sleep(2)
slot1_number = S... | the_stack_v2_python_sparse | test_env/test_suit_phone/test_suit_phone_case3.py | wwlwwlqaz/Qualcomm | train | 1 |
15a33f3fd93703409a0fe7597f24a7ee84e5a6f6 | [
"if self.is_active(global_step):\n tic = self._compute(global_step, params, batch_loss).item()\n if self._verbose:\n print(f'[Step {global_step}] TICDiag: {tic:.4f}')\n self.output[global_step]['tic_diag'] = tic\n if self._check:\n self.__run_check(global_step, params, batch_loss)",
"sum... | <|body_start_0|>
if self.is_active(global_step):
tic = self._compute(global_step, params, batch_loss).item()
if self._verbose:
print(f'[Step {global_step}] TICDiag: {tic:.4f}')
self.output[global_step]['tic_diag'] = tic
if self._check:
... | TIC with diagonal curvature approximation for cheap inversion. | TICDiag | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TICDiag:
"""TIC with diagonal curvature approximation for cheap inversion."""
def compute(self, global_step, params, batch_loss):
"""Compute the TICDiag. Args: global_step (int): The current iteration number. params ([torch.Tensor]): List of torch.Tensors holding the network's parame... | stack_v2_sparse_classes_36k_train_001030 | 9,326 | permissive | [
{
"docstring": "Compute the TICDiag. Args: global_step (int): The current iteration number. params ([torch.Tensor]): List of torch.Tensors holding the network's parameters. batch_loss (torch.Tensor): Mini-batch loss from current step.",
"name": "compute",
"signature": "def compute(self, global_step, par... | 3 | stack_v2_sparse_classes_30k_train_004761 | Implement the Python class `TICDiag` described below.
Class description:
TIC with diagonal curvature approximation for cheap inversion.
Method signatures and docstrings:
- def compute(self, global_step, params, batch_loss): Compute the TICDiag. Args: global_step (int): The current iteration number. params ([torch.Ten... | Implement the Python class `TICDiag` described below.
Class description:
TIC with diagonal curvature approximation for cheap inversion.
Method signatures and docstrings:
- def compute(self, global_step, params, batch_loss): Compute the TICDiag. Args: global_step (int): The current iteration number. params ([torch.Ten... | 5bd5ab3cda03eda0b0bf276f29d5c28b83d70b06 | <|skeleton|>
class TICDiag:
"""TIC with diagonal curvature approximation for cheap inversion."""
def compute(self, global_step, params, batch_loss):
"""Compute the TICDiag. Args: global_step (int): The current iteration number. params ([torch.Tensor]): List of torch.Tensors holding the network's parame... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TICDiag:
"""TIC with diagonal curvature approximation for cheap inversion."""
def compute(self, global_step, params, batch_loss):
"""Compute the TICDiag. Args: global_step (int): The current iteration number. params ([torch.Tensor]): List of torch.Tensors holding the network's parameters. batch_l... | the_stack_v2_python_sparse | cockpit/quantities/tic.py | MeNicefellow/cockpit | train | 0 |
96be437b242dfe48977008a9770755fb83548c87 | [
"self.win = grid.win\nself.grid = grid\nself.row = row\nself.col = col\nself.value = value\nul, lr = grid.tile_corners(row, col)\nbackground = graphics.Rectangle(ul, lr)\nbackground.setFill(RAMP[value])\nbackground.setOutline(TILE_OUTLINE_NEW)\nself.background = background\ncx = (ul.getX() + lr.getX()) / 2.0\ncy = ... | <|body_start_0|>
self.win = grid.win
self.grid = grid
self.row = row
self.col = col
self.value = value
ul, lr = grid.tile_corners(row, col)
background = graphics.Rectangle(ul, lr)
background.setFill(RAMP[value])
background.setOutline(TILE_OUTLINE_N... | A tile is the thing with a number that slides around the grid | Tile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tile:
"""A tile is the thing with a number that slides around the grid"""
def __init__(self, grid, row, col, value=2):
"""Display the tile on the grid. Internally there are actually two graphics objects: A background rectangle and text within it. The background rectangle has a visibl... | stack_v2_sparse_classes_36k_train_001031 | 7,288 | no_license | [
{
"docstring": "Display the tile on the grid. Internally there are actually two graphics objects: A background rectangle and text within it. The background rectangle has a visible outline until the first time it moves.",
"name": "__init__",
"signature": "def __init__(self, grid, row, col, value=2)"
},... | 3 | stack_v2_sparse_classes_30k_train_004705 | Implement the Python class `Tile` described below.
Class description:
A tile is the thing with a number that slides around the grid
Method signatures and docstrings:
- def __init__(self, grid, row, col, value=2): Display the tile on the grid. Internally there are actually two graphics objects: A background rectangle ... | Implement the Python class `Tile` described below.
Class description:
A tile is the thing with a number that slides around the grid
Method signatures and docstrings:
- def __init__(self, grid, row, col, value=2): Display the tile on the grid. Internally there are actually two graphics objects: A background rectangle ... | 559f81086bd3495348aa605da66117cb0fbc7277 | <|skeleton|>
class Tile:
"""A tile is the thing with a number that slides around the grid"""
def __init__(self, grid, row, col, value=2):
"""Display the tile on the grid. Internally there are actually two graphics objects: A background rectangle and text within it. The background rectangle has a visibl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tile:
"""A tile is the thing with a number that slides around the grid"""
def __init__(self, grid, row, col, value=2):
"""Display the tile on the grid. Internally there are actually two graphics objects: A background rectangle and text within it. The background rectangle has a visible outline unt... | the_stack_v2_python_sparse | CIS 211 - CS II/Proj 3 - FiveTwelve-master/view.py | noahtigner/UO-ComputerScience-DataScience | train | 3 |
687f63423d7be487d2047d7ce4d0d016350369ce | [
"self._logger = logging.getLogger(__name__)\nself.temp_file = str(uuid.uuid4()) + '.tar.gz'\nself.source_gzip = os.path.join(temp_folder, self.temp_file)",
"if not (os.path.exists(source_dir_path) and os.access(source_dir_path, os.R_OK)):\n raise MLOpsException('Path: {} does not exist or not readable'.format(... | <|body_start_0|>
self._logger = logging.getLogger(__name__)
self.temp_file = str(uuid.uuid4()) + '.tar.gz'
self.source_gzip = os.path.join(temp_folder, self.temp_file)
<|end_body_0|>
<|body_start_1|>
if not (os.path.exists(source_dir_path) and os.access(source_dir_path, os.R_OK)):
... | Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps. | DirectoryPack | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectoryPack:
"""Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps."""
def __init__(self, temp_folder='/tmp'):
"""Perform initialization of the DirectoryPack. :param temp_folder: folder to save a tar gz file :ret... | stack_v2_sparse_classes_36k_train_001032 | 2,096 | permissive | [
{
"docstring": "Perform initialization of the DirectoryPack. :param temp_folder: folder to save a tar gz file :return:",
"name": "__init__",
"signature": "def __init__(self, temp_folder='/tmp')"
},
{
"docstring": "Packs a folder :param source_dir_path: folder to pack :return: path to created tar... | 3 | stack_v2_sparse_classes_30k_train_000086 | Implement the Python class `DirectoryPack` described below.
Class description:
Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps.
Method signatures and docstrings:
- def __init__(self, temp_folder='/tmp'): Perform initialization of the DirectoryPa... | Implement the Python class `DirectoryPack` described below.
Class description:
Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps.
Method signatures and docstrings:
- def __init__(self, temp_folder='/tmp'): Perform initialization of the DirectoryPa... | 738356ce6d5e691a5d813acafa3f0ff730e76136 | <|skeleton|>
class DirectoryPack:
"""Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps."""
def __init__(self, temp_folder='/tmp'):
"""Perform initialization of the DirectoryPack. :param temp_folder: folder to save a tar gz file :ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DirectoryPack:
"""Provides API to pack a folder as tar gz archive. This is an internal class which should not be exposed to users of MLOps."""
def __init__(self, temp_folder='/tmp'):
"""Perform initialization of the DirectoryPack. :param temp_folder: folder to save a tar gz file :return:"""
... | the_stack_v2_python_sparse | mlops/parallelm/mlops/packer.py | theromis/mlpiper | train | 0 |
ca569650d5c812c2bf3e2bd042061bbacbb3965b | [
"if R <= 1:\n sys.exit('Error: you must initialize R>0.')\nif R > 300000000.0:\n sys.exit('Error: R^2 too large for double format.')\nelse:\n self.R = R\n self.Rvar = 4 * R ** 2 / 3\n self.minN = math.ceil(R / math.sqrt(3))\n self.maxN = math.floor(2 * R / 3)",
"if a < 0:\n sys.exit('Error: w... | <|body_start_0|>
if R <= 1:
sys.exit('Error: you must initialize R>0.')
if R > 300000000.0:
sys.exit('Error: R^2 too large for double format.')
else:
self.R = R
self.Rvar = 4 * R ** 2 / 3
self.minN = math.ceil(R / math.sqrt(3))
... | Rotated Ellipse satisfying a^2+b^2+ab=R^2/3. (a,b) cell address of unit-side honeycomb N=a+b cell column index | RotatedEllipse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RotatedEllipse:
"""Rotated Ellipse satisfying a^2+b^2+ab=R^2/3. (a,b) cell address of unit-side honeycomb N=a+b cell column index"""
def __init__(self, R):
"""Set initial radius, R"""
<|body_0|>
def b(self, a):
"""Compute b=sqrt(4R^2/3-3a^2)/2-a"""
<|body... | stack_v2_sparse_classes_36k_train_001033 | 1,436 | permissive | [
{
"docstring": "Set initial radius, R",
"name": "__init__",
"signature": "def __init__(self, R)"
},
{
"docstring": "Compute b=sqrt(4R^2/3-3a^2)/2-a",
"name": "b",
"signature": "def b(self, a)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011319 | Implement the Python class `RotatedEllipse` described below.
Class description:
Rotated Ellipse satisfying a^2+b^2+ab=R^2/3. (a,b) cell address of unit-side honeycomb N=a+b cell column index
Method signatures and docstrings:
- def __init__(self, R): Set initial radius, R
- def b(self, a): Compute b=sqrt(4R^2/3-3a^2)/... | Implement the Python class `RotatedEllipse` described below.
Class description:
Rotated Ellipse satisfying a^2+b^2+ab=R^2/3. (a,b) cell address of unit-side honeycomb N=a+b cell column index
Method signatures and docstrings:
- def __init__(self, R): Set initial radius, R
- def b(self, a): Compute b=sqrt(4R^2/3-3a^2)/... | af88bdeded262bce42d52f309075b036cc638880 | <|skeleton|>
class RotatedEllipse:
"""Rotated Ellipse satisfying a^2+b^2+ab=R^2/3. (a,b) cell address of unit-side honeycomb N=a+b cell column index"""
def __init__(self, R):
"""Set initial radius, R"""
<|body_0|>
def b(self, a):
"""Compute b=sqrt(4R^2/3-3a^2)/2-a"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RotatedEllipse:
"""Rotated Ellipse satisfying a^2+b^2+ab=R^2/3. (a,b) cell address of unit-side honeycomb N=a+b cell column index"""
def __init__(self, R):
"""Set initial radius, R"""
if R <= 1:
sys.exit('Error: you must initialize R>0.')
if R > 300000000.0:
... | the_stack_v2_python_sparse | ProjectEuler/honeycomb.py | mbdeaton/BrettCodeProjects | train | 2 |
ee2c16e77bae27854b7f286bbcd6490cc65b4467 | [
"dict_q = {}\nheaders = quanta_headers(int_fmt)\ncount = min(int_fmt % 10, len(str_quanta) // 3)\nfor i in range(0, count):\n str_q = str_quanta[i * 3:(i + 1) * 3]\n dict_q[headers[i]] = int(str_q)\nreturn dict_q",
"str_quanta = ''\nheaders = quanta_headers(int_fmt)[0:len(dict_q)]\nfor str_q in ['%3d' % dic... | <|body_start_0|>
dict_q = {}
headers = quanta_headers(int_fmt)
count = min(int_fmt % 10, len(str_quanta) // 3)
for i in range(0, count):
str_q = str_quanta[i * 3:(i + 1) * 3]
dict_q[headers[i]] = int(str_q)
return dict_q
<|end_body_0|>
<|body_start_1|>
... | Manages entries of .egy files. | EgyConverter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EgyConverter:
"""Manages entries of .egy files."""
def __read_quanta(str_quanta, int_fmt):
"""convert quanta from .egy to dict"""
<|body_0|>
def __write_quanta(dict_q, int_fmt):
"""convert quanta from dict to .egy str"""
<|body_1|>
def str2state(str_... | stack_v2_sparse_classes_36k_train_001034 | 11,597 | no_license | [
{
"docstring": "convert quanta from .egy to dict",
"name": "__read_quanta",
"signature": "def __read_quanta(str_quanta, int_fmt)"
},
{
"docstring": "convert quanta from dict to .egy str",
"name": "__write_quanta",
"signature": "def __write_quanta(dict_q, int_fmt)"
},
{
"docstring... | 4 | stack_v2_sparse_classes_30k_train_016318 | Implement the Python class `EgyConverter` described below.
Class description:
Manages entries of .egy files.
Method signatures and docstrings:
- def __read_quanta(str_quanta, int_fmt): convert quanta from .egy to dict
- def __write_quanta(dict_q, int_fmt): convert quanta from dict to .egy str
- def str2state(str_stat... | Implement the Python class `EgyConverter` described below.
Class description:
Manages entries of .egy files.
Method signatures and docstrings:
- def __read_quanta(str_quanta, int_fmt): convert quanta from .egy to dict
- def __write_quanta(dict_q, int_fmt): convert quanta from dict to .egy str
- def str2state(str_stat... | 57bda76b211c8efd3bd24bd2895bd57ea855003e | <|skeleton|>
class EgyConverter:
"""Manages entries of .egy files."""
def __read_quanta(str_quanta, int_fmt):
"""convert quanta from .egy to dict"""
<|body_0|>
def __write_quanta(dict_q, int_fmt):
"""convert quanta from dict to .egy str"""
<|body_1|>
def str2state(str_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EgyConverter:
"""Manages entries of .egy files."""
def __read_quanta(str_quanta, int_fmt):
"""convert quanta from .egy to dict"""
dict_q = {}
headers = quanta_headers(int_fmt)
count = min(int_fmt % 10, len(str_quanta) // 3)
for i in range(0, count):
str... | the_stack_v2_python_sparse | pickett/converters.py | kiraboris/scanner | train | 0 |
f841bbd7e7c9a9ec4c96e9e92ce8c41b201d5da3 | [
"logger.info('开始获取token的url地址：')\nself.url = KFPT_IP + ':' + PORT1 + '/pm-oauth/oauth/token'\nlogger.info('获取token的url地址为：{}'.format(self.url))",
"params = {'grant_type': grant_type, 'username': data['username'], 'password': data['password'], 'client_id': client_id, 'client_secret': client_secret}\nlogger.info('准... | <|body_start_0|>
logger.info('开始获取token的url地址：')
self.url = KFPT_IP + ':' + PORT1 + '/pm-oauth/oauth/token'
logger.info('获取token的url地址为：{}'.format(self.url))
<|end_body_0|>
<|body_start_1|>
params = {'grant_type': grant_type, 'username': data['username'], 'password': data['password'], '... | ApiGetToken | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApiGetToken:
def __init__(self):
"""todo 初始化"""
<|body_0|>
def get_token(self, session, data):
"""todo 对获取token接口进行自动化操作，并根据响应获取返回值中的”access_token“值 data: 动态传参，由于用户名和密码是动态的其他参数都是固定的，这里只需要动态传用户名和密码"""
<|body_1|>
def get_token_success(self, session):
... | stack_v2_sparse_classes_36k_train_001035 | 3,125 | no_license | [
{
"docstring": "todo 初始化",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "todo 对获取token接口进行自动化操作，并根据响应获取返回值中的”access_token“值 data: 动态传参，由于用户名和密码是动态的其他参数都是固定的，这里只需要动态传用户名和密码",
"name": "get_token",
"signature": "def get_token(self, session, data)"
},
{
"do... | 3 | stack_v2_sparse_classes_30k_train_010299 | Implement the Python class `ApiGetToken` described below.
Class description:
Implement the ApiGetToken class.
Method signatures and docstrings:
- def __init__(self): todo 初始化
- def get_token(self, session, data): todo 对获取token接口进行自动化操作，并根据响应获取返回值中的”access_token“值 data: 动态传参，由于用户名和密码是动态的其他参数都是固定的，这里只需要动态传用户名和密码
- def ... | Implement the Python class `ApiGetToken` described below.
Class description:
Implement the ApiGetToken class.
Method signatures and docstrings:
- def __init__(self): todo 初始化
- def get_token(self, session, data): todo 对获取token接口进行自动化操作，并根据响应获取返回值中的”access_token“值 data: 动态传参，由于用户名和密码是动态的其他参数都是固定的，这里只需要动态传用户名和密码
- def ... | 5a2e26de65097827482dc7cc02b579d866e3a3c5 | <|skeleton|>
class ApiGetToken:
def __init__(self):
"""todo 初始化"""
<|body_0|>
def get_token(self, session, data):
"""todo 对获取token接口进行自动化操作，并根据响应获取返回值中的”access_token“值 data: 动态传参，由于用户名和密码是动态的其他参数都是固定的，这里只需要动态传用户名和密码"""
<|body_1|>
def get_token_success(self, session):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApiGetToken:
def __init__(self):
"""todo 初始化"""
logger.info('开始获取token的url地址：')
self.url = KFPT_IP + ':' + PORT1 + '/pm-oauth/oauth/token'
logger.info('获取token的url地址为：{}'.format(self.url))
def get_token(self, session, data):
"""todo 对获取token接口进行自动化操作，并根据响应获取返回值中的”a... | the_stack_v2_python_sparse | api/api_get_token.py | zuochen0806/icdm_Interface | train | 0 | |
8b1e6b5431e8dfdc593dd53cca768c42e8f4e2b8 | [
"if not head:\n return True\ncur = head\nvalues = []\nwhile cur:\n values.append(cur.val)\n cur = cur.next\nif values == values[::-1]:\n return True\nelse:\n return False",
"fast = slow = head\nwhile fast and fast.next:\n fast = fast.next.next\n slow = slow.next\nnode = None\nwhile slow:\n ... | <|body_start_0|>
if not head:
return True
cur = head
values = []
while cur:
values.append(cur.val)
cur = cur.next
if values == values[::-1]:
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def isPalindrome2(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not head:
return True
... | stack_v2_sparse_classes_36k_train_001036 | 1,364 | no_license | [
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "isPalindrome2",
"signature": "def isPalindrome2(self, head)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head): :type head: ListNode :rtype: bool
- def isPalindrome2(self, head): :type head: ListNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head): :type head: ListNode :rtype: bool
- def isPalindrome2(self, head): :type head: ListNode :rtype: bool
<|skeleton|>
class Solution:
def isPalind... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def isPalindrome2(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, head):
""":type head: ListNode :rtype: bool"""
if not head:
return True
cur = head
values = []
while cur:
values.append(cur.val)
cur = cur.next
if values == values[::-1]:
return Tru... | the_stack_v2_python_sparse | 234. Palindrome Linked List/isPalindrome.py | Macielyoung/LeetCode | train | 1 | |
5c35c89a4f1e8eee365fe7636fab6132cc236834 | [
"super(Pollution, self).__init__(*args, **kwargs)\nself._host_name = socket.gethostname()\nself._client_random_id = ''.join((random.choice(string.ascii_lowercase) for i in range(4)))\nself._client_id = '[{}]-{}'.format(self._client_random_id, self._host_name)",
"print('Start injecting messages ...')\ndata = 0\nwh... | <|body_start_0|>
super(Pollution, self).__init__(*args, **kwargs)
self._host_name = socket.gethostname()
self._client_random_id = ''.join((random.choice(string.ascii_lowercase) for i in range(4)))
self._client_id = '[{}]-{}'.format(self._client_random_id, self._host_name)
<|end_body_0|>
... | Pollute the `junk` channel. | Pollution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pollution:
"""Pollute the `junk` channel."""
def __init__(self, *args, **kwargs):
"""Initialize the pollution client."""
<|body_0|>
async def work(self):
"""Inject a number in the `junk` channel."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_36k_train_001037 | 1,054 | no_license | [
{
"docstring": "Initialize the pollution client.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Inject a number in the `junk` channel.",
"name": "work",
"signature": "async def work(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001687 | Implement the Python class `Pollution` described below.
Class description:
Pollute the `junk` channel.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the pollution client.
- async def work(self): Inject a number in the `junk` channel. | Implement the Python class `Pollution` described below.
Class description:
Pollute the `junk` channel.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the pollution client.
- async def work(self): Inject a number in the `junk` channel.
<|skeleton|>
class Pollution:
"""Pollute ... | 40a0aaf9b10cf510eebb16d16e6021fb98ae51bd | <|skeleton|>
class Pollution:
"""Pollute the `junk` channel."""
def __init__(self, *args, **kwargs):
"""Initialize the pollution client."""
<|body_0|>
async def work(self):
"""Inject a number in the `junk` channel."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Pollution:
"""Pollute the `junk` channel."""
def __init__(self, *args, **kwargs):
"""Initialize the pollution client."""
super(Pollution, self).__init__(*args, **kwargs)
self._host_name = socket.gethostname()
self._client_random_id = ''.join((random.choice(string.ascii_low... | the_stack_v2_python_sparse | nats_overlay_broker/pollution.py | mateimicu/nats-overlay-broker | train | 0 |
0c2cd98161d69fdcdcebda67e9497789e7c637b2 | [
"res = []\n\ndef _dfs(root):\n if root:\n res.append(str(root.val))\n _dfs(root.left)\n _dfs(root.right)\n_dfs(root)\nreturn ''.join(res)",
"def _build(k, parent):\n if k >= len(data):\n return (None, k)\n root = TreeNode(int(data[k]))\n val = int(data[k + 1])\n parent =... | <|body_start_0|>
res = []
def _dfs(root):
if root:
res.append(str(root.val))
_dfs(root.left)
_dfs(root.right)
_dfs(root)
return ''.join(res)
<|end_body_0|>
<|body_start_1|>
def _build(k, parent):
if k >= 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_36k_train_001038 | 2,230 | 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_020232 | 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:... | 085b8dfa8e12f7c39107bab60110cd3b182f0c13 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = []
def _dfs(root):
if root:
res.append(str(root.val))
_dfs(root.left)
_dfs(root.right)
_dfs(root)
... | the_stack_v2_python_sparse | eet/Serialize_and_Deserialize_BST.py | wangyunge/algorithmpractice | train | 0 | |
934cf366ac9b71bcf7dabcc9f4804d57eb82f32c | [
"package = handlers.request().package\nuser_to_add = users.User(email)\nif package.has_uploader(user_to_add):\n handlers.http_error(400, \"User '%s' is already an uploader for package '%s'.\" % (email, package.name))\npackage.uploaders.append(user_to_add)\npackage.put()\nreturn handlers.json_success(\"'%s' added... | <|body_start_0|>
package = handlers.request().package
user_to_add = users.User(email)
if package.has_uploader(user_to_add):
handlers.http_error(400, "User '%s' is already an uploader for package '%s'." % (email, package.name))
package.uploaders.append(user_to_add)
pac... | The handler for /api/packages/*/uploaders/*. | PackageUploaders | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PackageUploaders:
"""The handler for /api/packages/*/uploaders/*."""
def create(self, package_id, email):
"""Add a new uploader for this package. Only other uploaders may add new uploaders."""
<|body_0|>
def delete(self, package_id, id, format=None):
"""Delete on... | stack_v2_sparse_classes_36k_train_001039 | 2,401 | permissive | [
{
"docstring": "Add a new uploader for this package. Only other uploaders may add new uploaders.",
"name": "create",
"signature": "def create(self, package_id, email)"
},
{
"docstring": "Delete one of this package's uploaders. Only uploaders may delete uploaders. If only one uploader remains, th... | 2 | stack_v2_sparse_classes_30k_train_000061 | Implement the Python class `PackageUploaders` described below.
Class description:
The handler for /api/packages/*/uploaders/*.
Method signatures and docstrings:
- def create(self, package_id, email): Add a new uploader for this package. Only other uploaders may add new uploaders.
- def delete(self, package_id, id, fo... | Implement the Python class `PackageUploaders` described below.
Class description:
The handler for /api/packages/*/uploaders/*.
Method signatures and docstrings:
- def create(self, package_id, email): Add a new uploader for this package. Only other uploaders may add new uploaders.
- def delete(self, package_id, id, fo... | 5701b2a6ef4c94a3026f03e1bbea09cd999e9d88 | <|skeleton|>
class PackageUploaders:
"""The handler for /api/packages/*/uploaders/*."""
def create(self, package_id, email):
"""Add a new uploader for this package. Only other uploaders may add new uploaders."""
<|body_0|>
def delete(self, package_id, id, format=None):
"""Delete on... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PackageUploaders:
"""The handler for /api/packages/*/uploaders/*."""
def create(self, package_id, email):
"""Add a new uploader for this package. Only other uploaders may add new uploaders."""
package = handlers.request().package
user_to_add = users.User(email)
if package.... | the_stack_v2_python_sparse | app/handlers/api/package_uploaders.py | tapted/pub-dartlang | train | 0 |
f0eee202a7d54235a3d24e3e083b2fa78f78bcce | [
"if num1 == '0' or num2 == '0':\n return '0'\nl1 = len(num1)\nl2 = len(num2)\nres = '0'\nnum2 = num2[::-1]\nnum1 = num1[::-1]\nfor i in range(l2):\n n2 = num2[i]\n carry = 0\n s = ''\n for j in range(l1):\n n1 = num1[j]\n tmp = int(n1) * int(n2) + carry\n carry = tmp // 10\n ... | <|body_start_0|>
if num1 == '0' or num2 == '0':
return '0'
l1 = len(num1)
l2 = len(num2)
res = '0'
num2 = num2[::-1]
num1 = num1[::-1]
for i in range(l2):
n2 = num2[i]
carry = 0
s = ''
for j in range(l1):... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def multiply(self, num1, num2):
""":type num1: str :type num2: str :rtype: str"""
<|body_0|>
def addStrings(self, num1, num2):
""":type num1: str :type num2: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if num1 == '0' or... | stack_v2_sparse_classes_36k_train_001040 | 1,654 | no_license | [
{
"docstring": ":type num1: str :type num2: str :rtype: str",
"name": "multiply",
"signature": "def multiply(self, num1, num2)"
},
{
"docstring": ":type num1: str :type num2: str :rtype: str",
"name": "addStrings",
"signature": "def addStrings(self, num1, num2)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def multiply(self, num1, num2): :type num1: str :type num2: str :rtype: str
- def addStrings(self, num1, num2): :type num1: str :type num2: str :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def multiply(self, num1, num2): :type num1: str :type num2: str :rtype: str
- def addStrings(self, num1, num2): :type num1: str :type num2: str :rtype: str
<|skeleton|>
class So... | b049816905f3ea19707577d07f4b414147da3cfb | <|skeleton|>
class Solution:
def multiply(self, num1, num2):
""":type num1: str :type num2: str :rtype: str"""
<|body_0|>
def addStrings(self, num1, num2):
""":type num1: str :type num2: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def multiply(self, num1, num2):
""":type num1: str :type num2: str :rtype: str"""
if num1 == '0' or num2 == '0':
return '0'
l1 = len(num1)
l2 = len(num2)
res = '0'
num2 = num2[::-1]
num1 = num1[::-1]
for i in range(l2):
... | the_stack_v2_python_sparse | 0043multiply.py | mondon11/leetcode | train | 0 | |
c6ca08765c9a4de633916902e384d1b66479a6bb | [
"if self.isEmpty():\n self._head = self._Item(k, v)\n self._tail = self._head\n return\nitem = self._Item(k, v)\nwalk = self._head\nwhile walk.getNext():\n if walk.getNext().getVal() >= item.getVal():\n break\n walk = walk.getNext()\nitem.setNext(walk.getNext())\nwalk.setNext(item)",
"item =... | <|body_start_0|>
if self.isEmpty():
self._head = self._Item(k, v)
self._tail = self._head
return
item = self._Item(k, v)
walk = self._head
while walk.getNext():
if walk.getNext().getVal() >= item.getVal():
break
... | A min-oriented priority queue implemented with an unsorted list | SortedPriorityQueue | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SortedPriorityQueue:
"""A min-oriented priority queue implemented with an unsorted list"""
def add(self, k, v):
"""Add a key-value pair (unsorted order)"""
<|body_0|>
def min_(self):
"""Return but do not remove (k,v) tuple with minimun key"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_001041 | 4,764 | no_license | [
{
"docstring": "Add a key-value pair (unsorted order)",
"name": "add",
"signature": "def add(self, k, v)"
},
{
"docstring": "Return but do not remove (k,v) tuple with minimun key",
"name": "min_",
"signature": "def min_(self)"
},
{
"docstring": "Remove and return (k,v) tuple with... | 3 | stack_v2_sparse_classes_30k_val_000218 | Implement the Python class `SortedPriorityQueue` described below.
Class description:
A min-oriented priority queue implemented with an unsorted list
Method signatures and docstrings:
- def add(self, k, v): Add a key-value pair (unsorted order)
- def min_(self): Return but do not remove (k,v) tuple with minimun key
- ... | Implement the Python class `SortedPriorityQueue` described below.
Class description:
A min-oriented priority queue implemented with an unsorted list
Method signatures and docstrings:
- def add(self, k, v): Add a key-value pair (unsorted order)
- def min_(self): Return but do not remove (k,v) tuple with minimun key
- ... | 783daaca7c9b716f080df43c7aa581add3b86a46 | <|skeleton|>
class SortedPriorityQueue:
"""A min-oriented priority queue implemented with an unsorted list"""
def add(self, k, v):
"""Add a key-value pair (unsorted order)"""
<|body_0|>
def min_(self):
"""Return but do not remove (k,v) tuple with minimun key"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SortedPriorityQueue:
"""A min-oriented priority queue implemented with an unsorted list"""
def add(self, k, v):
"""Add a key-value pair (unsorted order)"""
if self.isEmpty():
self._head = self._Item(k, v)
self._tail = self._head
return
item = se... | the_stack_v2_python_sparse | labs/P-QueueBase.py | pithecuse527/Algorithms-MUN | train | 4 |
ea2abb05e7b0dc9927ed6bf05e6f00404c80a095 | [
"self.model = K.models.load_model(model_path)\nwith open(classes_path, 'r') as f:\n data = f.read()\nself.class_names = data.split()\nself.class_t = class_t\nself.nms_t = nms_t\nself.anchors = anchors",
"boxes = [output[:, :, :, 0:4] for output in outputs]\nfor oidx, output in enumerate(boxes):\n for y in r... | <|body_start_0|>
self.model = K.models.load_model(model_path)
with open(classes_path, 'r') as f:
data = f.read()
self.class_names = data.split()
self.class_t = class_t
self.nms_t = nms_t
self.anchors = anchors
<|end_body_0|>
<|body_start_1|>
boxes = [... | Yolo v3 algorithm | Yolo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Yolo:
"""Yolo v3 algorithm"""
def __init__(self, model_path, classes_path, class_t, nms_t, anchors):
"""class constructor"""
<|body_0|>
def process_outputs(self, outputs, image_size):
"""Process Darknet outputs"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_001042 | 2,207 | no_license | [
{
"docstring": "class constructor",
"name": "__init__",
"signature": "def __init__(self, model_path, classes_path, class_t, nms_t, anchors)"
},
{
"docstring": "Process Darknet outputs",
"name": "process_outputs",
"signature": "def process_outputs(self, outputs, image_size)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005893 | Implement the Python class `Yolo` described below.
Class description:
Yolo v3 algorithm
Method signatures and docstrings:
- def __init__(self, model_path, classes_path, class_t, nms_t, anchors): class constructor
- def process_outputs(self, outputs, image_size): Process Darknet outputs | Implement the Python class `Yolo` described below.
Class description:
Yolo v3 algorithm
Method signatures and docstrings:
- def __init__(self, model_path, classes_path, class_t, nms_t, anchors): class constructor
- def process_outputs(self, outputs, image_size): Process Darknet outputs
<|skeleton|>
class Yolo:
"... | a51fbcb76dae9281ff34ace0fb762ef899b4c380 | <|skeleton|>
class Yolo:
"""Yolo v3 algorithm"""
def __init__(self, model_path, classes_path, class_t, nms_t, anchors):
"""class constructor"""
<|body_0|>
def process_outputs(self, outputs, image_size):
"""Process Darknet outputs"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Yolo:
"""Yolo v3 algorithm"""
def __init__(self, model_path, classes_path, class_t, nms_t, anchors):
"""class constructor"""
self.model = K.models.load_model(model_path)
with open(classes_path, 'r') as f:
data = f.read()
self.class_names = data.split()
... | the_stack_v2_python_sparse | supervised_learning/0x0A-object_detection/1-yolo.py | Diegokernel/holbertonschool-machine_learning | train | 0 |
651e6dbe6deae95f463dd2e2991942f62c671b31 | [
"if any(((lot.lending_lot_type_id.medical_audit or lot.lending_lot_type_id.dental_audit) and lot.state == 'in_progress' for lot in self)):\n raise ValidationError('Los lotes deben ser revisados por la auditoría antes de finalizarlos.')\nreturn super(LendingLot, self).finish_lot()",
"for lot in self:\n if lo... | <|body_start_0|>
if any(((lot.lending_lot_type_id.medical_audit or lot.lending_lot_type_id.dental_audit) and lot.state == 'in_progress' for lot in self)):
raise ValidationError('Los lotes deben ser revisados por la auditoría antes de finalizarlos.')
return super(LendingLot, self).finish_lot(... | LendingLot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LendingLot:
def finish_lot(self):
"""Cambio de estado de lote a finalizado"""
<|body_0|>
def revised_lot(self):
"""Cambio de estado de lote a Revisado"""
<|body_1|>
def unlink(self):
"""Se redefine la eliminacion de lote"""
<|body_2|>
<|... | stack_v2_sparse_classes_36k_train_001043 | 2,197 | no_license | [
{
"docstring": "Cambio de estado de lote a finalizado",
"name": "finish_lot",
"signature": "def finish_lot(self)"
},
{
"docstring": "Cambio de estado de lote a Revisado",
"name": "revised_lot",
"signature": "def revised_lot(self)"
},
{
"docstring": "Se redefine la eliminacion de ... | 3 | null | Implement the Python class `LendingLot` described below.
Class description:
Implement the LendingLot class.
Method signatures and docstrings:
- def finish_lot(self): Cambio de estado de lote a finalizado
- def revised_lot(self): Cambio de estado de lote a Revisado
- def unlink(self): Se redefine la eliminacion de lot... | Implement the Python class `LendingLot` described below.
Class description:
Implement the LendingLot class.
Method signatures and docstrings:
- def finish_lot(self): Cambio de estado de lote a finalizado
- def revised_lot(self): Cambio de estado de lote a Revisado
- def unlink(self): Se redefine la eliminacion de lot... | 77921b4d965f2e4c081d523b373eb306a450a873 | <|skeleton|>
class LendingLot:
def finish_lot(self):
"""Cambio de estado de lote a finalizado"""
<|body_0|>
def revised_lot(self):
"""Cambio de estado de lote a Revisado"""
<|body_1|>
def unlink(self):
"""Se redefine la eliminacion de lote"""
<|body_2|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LendingLot:
def finish_lot(self):
"""Cambio de estado de lote a finalizado"""
if any(((lot.lending_lot_type_id.medical_audit or lot.lending_lot_type_id.dental_audit) and lot.state == 'in_progress' for lot in self)):
raise ValidationError('Los lotes deben ser revisados por la audito... | the_stack_v2_python_sparse | odoo_addons_customization/lending_medical_audit/models/lending_lot.py | test-odoorosario/opt | train | 0 | |
c651747cbea5fc8e3c760d64e20a847004586ec9 | [
"ub = self.app.module_map.userbase\nevent = self.barcamp.get_event(eid)\nrooms = event.timetable.get('rooms', [])\ntimeslots = event.timetable.get('timeslots', [])\nsessions = event.timetable.get('sessions', {})\nif self.barcamp.ticketmode_enabled:\n tdb = self.config.dbs.tickets\n tickets = tdb.get_tickets(b... | <|body_start_0|>
ub = self.app.module_map.userbase
event = self.barcamp.get_event(eid)
rooms = event.timetable.get('rooms', [])
timeslots = event.timetable.get('timeslots', [])
sessions = event.timetable.get('sessions', {})
if self.barcamp.ticketmode_enabled:
... | handles all AJAX related session board data | SessionBoardData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionBoardData:
"""handles all AJAX related session board data"""
def get(self, slug=None, eid=None):
"""return rooms and timeslots"""
<|body_0|>
def post(self, slug=None, eid=None):
"""store room and timetable data"""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_36k_train_001044 | 5,339 | permissive | [
{
"docstring": "return rooms and timeslots",
"name": "get",
"signature": "def get(self, slug=None, eid=None)"
},
{
"docstring": "store room and timetable data",
"name": "post",
"signature": "def post(self, slug=None, eid=None)"
}
] | 2 | null | Implement the Python class `SessionBoardData` described below.
Class description:
handles all AJAX related session board data
Method signatures and docstrings:
- def get(self, slug=None, eid=None): return rooms and timeslots
- def post(self, slug=None, eid=None): store room and timetable data | Implement the Python class `SessionBoardData` described below.
Class description:
handles all AJAX related session board data
Method signatures and docstrings:
- def get(self, slug=None, eid=None): return rooms and timeslots
- def post(self, slug=None, eid=None): store room and timetable data
<|skeleton|>
class Sess... | 9b45664e46c451b2cbe00bb55583b043e769083d | <|skeleton|>
class SessionBoardData:
"""handles all AJAX related session board data"""
def get(self, slug=None, eid=None):
"""return rooms and timeslots"""
<|body_0|>
def post(self, slug=None, eid=None):
"""store room and timetable data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SessionBoardData:
"""handles all AJAX related session board data"""
def get(self, slug=None, eid=None):
"""return rooms and timeslots"""
ub = self.app.module_map.userbase
event = self.barcamp.get_event(eid)
rooms = event.timetable.get('rooms', [])
timeslots = event... | the_stack_v2_python_sparse | camper/barcamps/sessionboard.py | comlounge/camper | train | 14 |
eccde246da6de1858ae7c1d888a31f1151cb821c | [
"super(TfdsInput, self).__init__(*args, **kwargs)\nself.dataset_name = dataset_name\nself.split = split\nself.data_dir = data_dir",
"if 'image' in value:\n images = value['image']\nelif 'video' in value:\n images = value['video']\nelse:\n raise ValueError('No \"image\" or \"video\" key found in TFDS datu... | <|body_start_0|>
super(TfdsInput, self).__init__(*args, **kwargs)
self.dataset_name = dataset_name
self.split = split
self.data_dir = data_dir
<|end_body_0|>
<|body_start_1|>
if 'image' in value:
images = value['image']
elif 'video' in value:
imag... | Generates an input_fn that works with TFDS datasets. | TfdsInput | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TfdsInput:
"""Generates an input_fn that works with TFDS datasets."""
def __init__(self, dataset_name, split, *args, data_dir=None, **kwargs):
"""Creates an input_fn for a TFDS dataset. Args: dataset_name: The name of the TFDS dataset, passed as the `name` argument of tfds.load(). sp... | stack_v2_sparse_classes_36k_train_001045 | 16,226 | permissive | [
{
"docstring": "Creates an input_fn for a TFDS dataset. Args: dataset_name: The name of the TFDS dataset, passed as the `name` argument of tfds.load(). split: The split name passed as the `split` argument to tfds.load(). *args: Arguments passed on to CommonInput. data_dir: The directory passed as the `data_dir`... | 3 | stack_v2_sparse_classes_30k_train_018481 | Implement the Python class `TfdsInput` described below.
Class description:
Generates an input_fn that works with TFDS datasets.
Method signatures and docstrings:
- def __init__(self, dataset_name, split, *args, data_dir=None, **kwargs): Creates an input_fn for a TFDS dataset. Args: dataset_name: The name of the TFDS ... | Implement the Python class `TfdsInput` described below.
Class description:
Generates an input_fn that works with TFDS datasets.
Method signatures and docstrings:
- def __init__(self, dataset_name, split, *args, data_dir=None, **kwargs): Creates an input_fn for a TFDS dataset. Args: dataset_name: The name of the TFDS ... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class TfdsInput:
"""Generates an input_fn that works with TFDS datasets."""
def __init__(self, dataset_name, split, *args, data_dir=None, **kwargs):
"""Creates an input_fn for a TFDS dataset. Args: dataset_name: The name of the TFDS dataset, passed as the `name` argument of tfds.load(). sp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TfdsInput:
"""Generates an input_fn that works with TFDS datasets."""
def __init__(self, dataset_name, split, *args, data_dir=None, **kwargs):
"""Creates an input_fn for a TFDS dataset. Args: dataset_name: The name of the TFDS dataset, passed as the `name` argument of tfds.load(). split: The spli... | the_stack_v2_python_sparse | supcon/inputs.py | Jimmy-INL/google-research | train | 1 |
c76a056c9bbde16bc6d50fadcb44081f3c54c2fd | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Proto file describing the Shared Set service. Service to manage shared sets. | SharedSetServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SharedSetServiceServicer:
"""Proto file describing the Shared Set service. Service to manage shared sets."""
def GetSharedSet(self, request, context):
"""Returns the requested shared set in full detail."""
<|body_0|>
def MutateSharedSets(self, request, context):
... | stack_v2_sparse_classes_36k_train_001046 | 5,356 | permissive | [
{
"docstring": "Returns the requested shared set in full detail.",
"name": "GetSharedSet",
"signature": "def GetSharedSet(self, request, context)"
},
{
"docstring": "Creates, updates, or removes shared sets. Operation statuses are returned.",
"name": "MutateSharedSets",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_010525 | Implement the Python class `SharedSetServiceServicer` described below.
Class description:
Proto file describing the Shared Set service. Service to manage shared sets.
Method signatures and docstrings:
- def GetSharedSet(self, request, context): Returns the requested shared set in full detail.
- def MutateSharedSets(s... | Implement the Python class `SharedSetServiceServicer` described below.
Class description:
Proto file describing the Shared Set service. Service to manage shared sets.
Method signatures and docstrings:
- def GetSharedSet(self, request, context): Returns the requested shared set in full detail.
- def MutateSharedSets(s... | 969eff5b6c3cec59d21191fa178cffb6270074c3 | <|skeleton|>
class SharedSetServiceServicer:
"""Proto file describing the Shared Set service. Service to manage shared sets."""
def GetSharedSet(self, request, context):
"""Returns the requested shared set in full detail."""
<|body_0|>
def MutateSharedSets(self, request, context):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SharedSetServiceServicer:
"""Proto file describing the Shared Set service. Service to manage shared sets."""
def GetSharedSet(self, request, context):
"""Returns the requested shared set in full detail."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method... | the_stack_v2_python_sparse | google/ads/google_ads/v6/proto/services/shared_set_service_pb2_grpc.py | VincentFritzsche/google-ads-python | train | 0 |
3f974777ea280d77a299b0a0076475abc6c06ba2 | [
"self.image = pygame.Surface((100, 100))\nself.image.fill(pygame.Color('White'))\nself.rect = self.image.get_rect()",
"self.velocity[0] = 10 * (pygame.key.get_pressed()[pygame.K_RIGHT] - pygame.key.get_pressed()[pygame.K_LEFT])\nif not pygame.key.get_pressed()[pygame.K_UP]:\n self.hold = False\nif self.rect.bo... | <|body_start_0|>
self.image = pygame.Surface((100, 100))
self.image.fill(pygame.Color('White'))
self.rect = self.image.get_rect()
<|end_body_0|>
<|body_start_1|>
self.velocity[0] = 10 * (pygame.key.get_pressed()[pygame.K_RIGHT] - pygame.key.get_pressed()[pygame.K_LEFT])
if not p... | Class for the player's attributes. | Player | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Player:
"""Class for the player's attributes."""
def __init__(self):
"""Initialise the player object."""
<|body_0|>
def update(self, display):
"""Check the current situation and update the player to match."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_001047 | 1,912 | no_license | [
{
"docstring": "Initialise the player object.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Check the current situation and update the player to match.",
"name": "update",
"signature": "def update(self, display)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000663 | Implement the Python class `Player` described below.
Class description:
Class for the player's attributes.
Method signatures and docstrings:
- def __init__(self): Initialise the player object.
- def update(self, display): Check the current situation and update the player to match. | Implement the Python class `Player` described below.
Class description:
Class for the player's attributes.
Method signatures and docstrings:
- def __init__(self): Initialise the player object.
- def update(self, display): Check the current situation and update the player to match.
<|skeleton|>
class Player:
"""C... | e7bbc0f7cfab13a2e16baa4c931d3a412c86277c | <|skeleton|>
class Player:
"""Class for the player's attributes."""
def __init__(self):
"""Initialise the player object."""
<|body_0|>
def update(self, display):
"""Check the current situation and update the player to match."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Player:
"""Class for the player's attributes."""
def __init__(self):
"""Initialise the player object."""
self.image = pygame.Surface((100, 100))
self.image.fill(pygame.Color('White'))
self.rect = self.image.get_rect()
def update(self, display):
"""Check the cu... | the_stack_v2_python_sparse | SideScrollSim.py | Chig00/Python | train | 1 |
f302ff91b67f2495e28cceca992ad3117e2a3b54 | [
"super(HPMLoss, self).__init__(dataset, None, norm, weight)\nself.hpm_input = hpm_input\nself.hpm_model = hpm_model",
"x.requires_grad = True\nprediction_u = model(x)\nhpm_input = self.hpm_input(x, prediction_u)\ntime_derivative = hpm_input[:, -1]\ninput = hpm_input[:, :-1]\nhpm_output = self.hpm_model(input)\nre... | <|body_start_0|>
super(HPMLoss, self).__init__(dataset, None, norm, weight)
self.hpm_input = hpm_input
self.hpm_model = hpm_model
<|end_body_0|>
<|body_start_1|>
x.requires_grad = True
prediction_u = model(x)
hpm_input = self.hpm_input(x, prediction_u)
time_deriv... | HPMLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HPMLoss:
def __init__(self, dataset, hpm_input, hpm_model, norm='L2', weight=1.0):
"""Constructor of the HPM loss Args: dataset (torch.utils.Dataset): dataset that provides the residual points hpm_input(function): function that calculates the needed input for the HPM model. The hpm_input... | stack_v2_sparse_classes_36k_train_001048 | 1,361 | permissive | [
{
"docstring": "Constructor of the HPM loss Args: dataset (torch.utils.Dataset): dataset that provides the residual points hpm_input(function): function that calculates the needed input for the HPM model. The hpm_input function should return a list of tensors, where the last entry is the time_derivative hpm_mod... | 2 | stack_v2_sparse_classes_30k_train_011774 | Implement the Python class `HPMLoss` described below.
Class description:
Implement the HPMLoss class.
Method signatures and docstrings:
- def __init__(self, dataset, hpm_input, hpm_model, norm='L2', weight=1.0): Constructor of the HPM loss Args: dataset (torch.utils.Dataset): dataset that provides the residual points... | Implement the Python class `HPMLoss` described below.
Class description:
Implement the HPMLoss class.
Method signatures and docstrings:
- def __init__(self, dataset, hpm_input, hpm_model, norm='L2', weight=1.0): Constructor of the HPM loss Args: dataset (torch.utils.Dataset): dataset that provides the residual points... | 2a6a20bf01bf355476272a0e622085e298d78112 | <|skeleton|>
class HPMLoss:
def __init__(self, dataset, hpm_input, hpm_model, norm='L2', weight=1.0):
"""Constructor of the HPM loss Args: dataset (torch.utils.Dataset): dataset that provides the residual points hpm_input(function): function that calculates the needed input for the HPM model. The hpm_input... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HPMLoss:
def __init__(self, dataset, hpm_input, hpm_model, norm='L2', weight=1.0):
"""Constructor of the HPM loss Args: dataset (torch.utils.Dataset): dataset that provides the residual points hpm_input(function): function that calculates the needed input for the HPM model. The hpm_input function shou... | the_stack_v2_python_sparse | PINNS/NeuralSolvers/PINNFramework/HPMLoss.py | juesuarezca/PhD_PINNs | train | 1 | |
72940c3351ed8d5acead4df7899c98379352d6c8 | [
"self.numsIter = iter(nums)\nself._hasNext = None\nself._nextVal = None",
"if self._hasNext is None:\n try:\n self._nextVal = next(self.numsIter)\n except StopIteration:\n self._hasNext = False\n else:\n self._hasNext = True\nreturn self._hasNext",
"if self._hasNext:\n result = ... | <|body_start_0|>
self.numsIter = iter(nums)
self._hasNext = None
self._nextVal = None
<|end_body_0|>
<|body_start_1|>
if self._hasNext is None:
try:
self._nextVal = next(self.numsIter)
except StopIteration:
self._hasNext = False
... | Iterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Iterator:
def __init__(self, nums):
"""Initializes an iterator object to the beginning of a list. :type nums: List[int]"""
<|body_0|>
def hasNext(self):
"""Returns true if the iteration has more elements. :rtype: bool"""
<|body_1|>
def next(self):
... | stack_v2_sparse_classes_36k_train_001049 | 6,268 | no_license | [
{
"docstring": "Initializes an iterator object to the beginning of a list. :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": "Returns true if the iteration has more elements. :rtype: bool",
"name": "hasNext",
"signature": "def hasNext(s... | 3 | stack_v2_sparse_classes_30k_train_012299 | Implement the Python class `Iterator` described below.
Class description:
Implement the Iterator class.
Method signatures and docstrings:
- def __init__(self, nums): Initializes an iterator object to the beginning of a list. :type nums: List[int]
- def hasNext(self): Returns true if the iteration has more elements. :... | Implement the Python class `Iterator` described below.
Class description:
Implement the Iterator class.
Method signatures and docstrings:
- def __init__(self, nums): Initializes an iterator object to the beginning of a list. :type nums: List[int]
- def hasNext(self): Returns true if the iteration has more elements. :... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Iterator:
def __init__(self, nums):
"""Initializes an iterator object to the beginning of a list. :type nums: List[int]"""
<|body_0|>
def hasNext(self):
"""Returns true if the iteration has more elements. :rtype: bool"""
<|body_1|>
def next(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Iterator:
def __init__(self, nums):
"""Initializes an iterator object to the beginning of a list. :type nums: List[int]"""
self.numsIter = iter(nums)
self._hasNext = None
self._nextVal = None
def hasNext(self):
"""Returns true if the iteration has more elements. :r... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00284.Peeking Iterator.py | roger6blog/LeetCode | train | 0 | |
dd11cd6e20e69b2c1173c9ef1e25b4d6a30fd312 | [
"self.max_data_reads = cnt_to_reach\nself.curr_data_reads = 0\nself.status_update = status_update",
"if self.status_update is True:\n self.curr_data_reads += 1\n log_text = text_to_print + ' ' + str(self.curr_data_reads) + '/' + str(self.max_data_reads) + ' done.'\n Utils.Logger_Instance.logger.info('Sta... | <|body_start_0|>
self.max_data_reads = cnt_to_reach
self.curr_data_reads = 0
self.status_update = status_update
<|end_body_0|>
<|body_start_1|>
if self.status_update is True:
self.curr_data_reads += 1
log_text = text_to_print + ' ' + str(self.curr_data_reads) + '... | StatusUpdate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StatusUpdate:
def __init__(self, cnt_to_reach, status_update=True):
""":param cnt_to_reach: number to show the current status, ex: 1/100 stocks read"""
<|body_0|>
def update_status(self, text_to_print):
"""update the read status and print it :return:"""
<|bod... | stack_v2_sparse_classes_36k_train_001050 | 737 | no_license | [
{
"docstring": ":param cnt_to_reach: number to show the current status, ex: 1/100 stocks read",
"name": "__init__",
"signature": "def __init__(self, cnt_to_reach, status_update=True)"
},
{
"docstring": "update the read status and print it :return:",
"name": "update_status",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_003240 | Implement the Python class `StatusUpdate` described below.
Class description:
Implement the StatusUpdate class.
Method signatures and docstrings:
- def __init__(self, cnt_to_reach, status_update=True): :param cnt_to_reach: number to show the current status, ex: 1/100 stocks read
- def update_status(self, text_to_prin... | Implement the Python class `StatusUpdate` described below.
Class description:
Implement the StatusUpdate class.
Method signatures and docstrings:
- def __init__(self, cnt_to_reach, status_update=True): :param cnt_to_reach: number to show the current status, ex: 1/100 stocks read
- def update_status(self, text_to_prin... | b6925f948c5f4a3fa6aedd1cd581e1c62defb305 | <|skeleton|>
class StatusUpdate:
def __init__(self, cnt_to_reach, status_update=True):
""":param cnt_to_reach: number to show the current status, ex: 1/100 stocks read"""
<|body_0|>
def update_status(self, text_to_print):
"""update the read status and print it :return:"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StatusUpdate:
def __init__(self, cnt_to_reach, status_update=True):
""":param cnt_to_reach: number to show the current status, ex: 1/100 stocks read"""
self.max_data_reads = cnt_to_reach
self.curr_data_reads = 0
self.status_update = status_update
def update_status(self, te... | the_stack_v2_python_sparse | Utils/StatusUpdate.py | hicode/pythonFinance | train | 0 | |
7973725eb750939927e0d0ef6dd74e79938d277a | [
"res = 0\ncnt = 0\nfor i in range(len(nums)):\n if nums[i] == 1:\n cnt += 1\n res = max(res, cnt)\n else:\n cnt = 0\nreturn res",
"res = 0\ncnt = 0\nfor i in range(len(nums)):\n if nums[i] == 1:\n cnt += 1\n else:\n res = max(res, cnt)\n cnt = 0\nreturn max(re... | <|body_start_0|>
res = 0
cnt = 0
for i in range(len(nums)):
if nums[i] == 1:
cnt += 1
res = max(res, cnt)
else:
cnt = 0
return res
<|end_body_0|>
<|body_start_1|>
res = 0
cnt = 0
for i in ran... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def findMaxConsecutiveOnes(self, nums):
""":type nums:... | stack_v2_sparse_classes_36k_train_001051 | 1,411 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findMaxConsecutiveOnes",
"signature": "def findMaxConsecutiveOnes(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findMaxConsecutiveOnes",
"signature": "def findMaxConsecutiveOnes(self, nums)"
},
... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxConsecutiveOnes(self, nums): :type nums: List[int] :rtype: int
- def findMaxConsecutiveOnes(self, nums): :type nums: List[int] :rtype: int
- def findMaxConsecutiveOnes... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxConsecutiveOnes(self, nums): :type nums: List[int] :rtype: int
- def findMaxConsecutiveOnes(self, nums): :type nums: List[int] :rtype: int
- def findMaxConsecutiveOnes... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def findMaxConsecutiveOnes(self, nums):
""":type nums:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMaxConsecutiveOnes(self, nums):
""":type nums: List[int] :rtype: int"""
res = 0
cnt = 0
for i in range(len(nums)):
if nums[i] == 1:
cnt += 1
res = max(res, cnt)
else:
cnt = 0
retur... | the_stack_v2_python_sparse | 0485_Max_Consecutive_Ones.py | bingli8802/leetcode | train | 0 | |
ce5ff41227402d99412c197b2dcfd4a113492449 | [
"super(FLAMELayer, self).__init__(*args, **kwargs)\nself.keypoint_src = keypoint_src\nself.keypoint_dst = keypoint_dst\nself.keypoint_approximate = keypoint_approximate\nself.num_verts = self.get_num_verts()\nself.num_faces = self.get_num_faces()\nself.num_joints = get_keypoint_num(convention=self.keypoint_dst)",
... | <|body_start_0|>
super(FLAMELayer, self).__init__(*args, **kwargs)
self.keypoint_src = keypoint_src
self.keypoint_dst = keypoint_dst
self.keypoint_approximate = keypoint_approximate
self.num_verts = self.get_num_verts()
self.num_faces = self.get_num_faces()
self.n... | Extension of the official FLAME implementation. | FLAMELayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FLAMELayer:
"""Extension of the official FLAME implementation."""
def __init__(self, *args, keypoint_src: str='flame', keypoint_dst: str='human_data', keypoint_approximate: bool=False, **kwargs):
"""Args: *args: extra arguments for FLAME initialization. keypoint_src: source conventio... | stack_v2_sparse_classes_36k_train_001052 | 6,673 | permissive | [
{
"docstring": "Args: *args: extra arguments for FLAME initialization. keypoint_src: source convention of keypoints. This convention is used for keypoints obtained from joint regressors. Keypoints then undergo conversion into keypoint_dst convention. keypoint_dst: destination convention of keypoints. This conve... | 2 | stack_v2_sparse_classes_30k_train_006547 | Implement the Python class `FLAMELayer` described below.
Class description:
Extension of the official FLAME implementation.
Method signatures and docstrings:
- def __init__(self, *args, keypoint_src: str='flame', keypoint_dst: str='human_data', keypoint_approximate: bool=False, **kwargs): Args: *args: extra arguments... | Implement the Python class `FLAMELayer` described below.
Class description:
Extension of the official FLAME implementation.
Method signatures and docstrings:
- def __init__(self, *args, keypoint_src: str='flame', keypoint_dst: str='human_data', keypoint_approximate: bool=False, **kwargs): Args: *args: extra arguments... | 9431addec32f7fbeffa1786927a854c0ab79d9ea | <|skeleton|>
class FLAMELayer:
"""Extension of the official FLAME implementation."""
def __init__(self, *args, keypoint_src: str='flame', keypoint_dst: str='human_data', keypoint_approximate: bool=False, **kwargs):
"""Args: *args: extra arguments for FLAME initialization. keypoint_src: source conventio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FLAMELayer:
"""Extension of the official FLAME implementation."""
def __init__(self, *args, keypoint_src: str='flame', keypoint_dst: str='human_data', keypoint_approximate: bool=False, **kwargs):
"""Args: *args: extra arguments for FLAME initialization. keypoint_src: source convention of keypoint... | the_stack_v2_python_sparse | mmhuman3d/models/body_models/flame.py | open-mmlab/mmhuman3d | train | 966 |
efdfd77feb771c8d8cc5f65aa9b027ee486c143d | [
"testName = 'meter_to_millimeter'\ntry:\n log.print_test_begin(testName)\n meters = 1\n millimeters = sc_Length.meter_to_millimeter(meters)\n self.assertEquals(millimeters, 1000)\n log.print_test_success(testName)\nexcept:\n log.print_test_failure(testName)\n self.fail(msg=testName[testName.rfi... | <|body_start_0|>
testName = 'meter_to_millimeter'
try:
log.print_test_begin(testName)
meters = 1
millimeters = sc_Length.meter_to_millimeter(meters)
self.assertEquals(millimeters, 1000)
log.print_test_success(testName)
except:
... | TestCalculations_length | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCalculations_length:
def meterToMillimeter(self):
"""Are meters correctly converted to millimeters?"""
<|body_0|>
def millimeterToMeter(self):
"""Are millimeters correctly converted to meters?"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
test... | stack_v2_sparse_classes_36k_train_001053 | 2,102 | permissive | [
{
"docstring": "Are meters correctly converted to millimeters?",
"name": "meterToMillimeter",
"signature": "def meterToMillimeter(self)"
},
{
"docstring": "Are millimeters correctly converted to meters?",
"name": "millimeterToMeter",
"signature": "def millimeterToMeter(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001136 | Implement the Python class `TestCalculations_length` described below.
Class description:
Implement the TestCalculations_length class.
Method signatures and docstrings:
- def meterToMillimeter(self): Are meters correctly converted to millimeters?
- def millimeterToMeter(self): Are millimeters correctly converted to me... | Implement the Python class `TestCalculations_length` described below.
Class description:
Implement the TestCalculations_length class.
Method signatures and docstrings:
- def meterToMillimeter(self): Are meters correctly converted to millimeters?
- def millimeterToMeter(self): Are millimeters correctly converted to me... | 6a5bfbb459f5a1309fdace4e38b44e8274c497db | <|skeleton|>
class TestCalculations_length:
def meterToMillimeter(self):
"""Are meters correctly converted to millimeters?"""
<|body_0|>
def millimeterToMeter(self):
"""Are millimeters correctly converted to meters?"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCalculations_length:
def meterToMillimeter(self):
"""Are meters correctly converted to millimeters?"""
testName = 'meter_to_millimeter'
try:
log.print_test_begin(testName)
meters = 1
millimeters = sc_Length.meter_to_millimeter(meters)
... | the_stack_v2_python_sparse | testCalculations/length.py | sativa/SPEED | train | 0 | |
915325a01da957c180772a309228c6dad07752e8 | [
"if not root:\n return ''\nres = str(root.val)\nif root.left:\n res += ',(' + self.serialize(root.left) + ')'\nif root.right:\n if not root.left:\n res += ',()'\n res += ',(' + self.serialize(root.right) + ')'\nreturn res",
"if not data:\n return\nif ',' not in data:\n return TreeNode(int... | <|body_start_0|>
if not root:
return ''
res = str(root.val)
if root.left:
res += ',(' + self.serialize(root.left) + ')'
if root.right:
if not root.left:
res += ',()'
res += ',(' + self.serialize(root.right) + ')'
ret... | 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_36k_train_001054 | 1,935 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 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:... | 25e5caf324e25edfdf0a7a3be1e572f5d4c88837 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
res = str(root.val)
if root.left:
res += ',(' + self.serialize(root.left) + ')'
if root.right:
if not r... | the_stack_v2_python_sparse | Trees/serialize_and_deserialize_bst.py | msraju2009/CodingProblemsPractice | train | 0 | |
2ef5a697b1f5d3a1870f107696efcbf58e5e0c73 | [
"try:\n courses = (yield Course.get_courses_from_ids(self.handler.room.courses))\n ids = {c['user_id'] for c in courses}\n names = (yield {id_: User.get_name(id_) for id_ in ids})\n for course in courses:\n course['owner'] = names[course['user_id']]\n del course['user_id']\n self.pub_su... | <|body_start_0|>
try:
courses = (yield Course.get_courses_from_ids(self.handler.room.courses))
ids = {c['user_id'] for c in courses}
names = (yield {id_: User.get_name(id_) for id_ in ids})
for course in courses:
course['owner'] = names[course['use... | CoursesWSC | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoursesWSC:
def send_room_courses(self, message):
"""Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of each course is replaced by the ``owner`` field. The ``owner`` field contains the name of the user, ... | stack_v2_sparse_classes_36k_train_001055 | 2,550 | no_license | [
{
"docstring": "Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of each course is replaced by the ``owner`` field. The ``owner`` field contains the name of the user, instead of it's ID. :param dict message: The client's message... | 2 | stack_v2_sparse_classes_30k_train_013605 | Implement the Python class `CoursesWSC` described below.
Class description:
Implement the CoursesWSC class.
Method signatures and docstrings:
- def send_room_courses(self, message): Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of ... | Implement the Python class `CoursesWSC` described below.
Class description:
Implement the CoursesWSC class.
Method signatures and docstrings:
- def send_room_courses(self, message): Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of ... | bc3870f809ad43feb78fbc39e7a4cead62207b27 | <|skeleton|>
class CoursesWSC:
def send_room_courses(self, message):
"""Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of each course is replaced by the ``owner`` field. The ``owner`` field contains the name of the user, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoursesWSC:
def send_room_courses(self, message):
"""Send current room's courses to the client. This method is subscribed to the ``courses.room.get`` message type. The ``user_id`` field of each course is replaced by the ``owner`` field. The ``owner`` field contains the name of the user, instead of it'... | the_stack_v2_python_sparse | backend_modules/courses/wsclass.py | pipegreyback/artificialAlan | train | 1 | |
6260698a778091b1c0d836752927da6b53939092 | [
"snap = super(FlowArea, self).snapshot()\nsnap['direction'] = self.direction\nsnap['align'] = self.align\nsnap['horizontal_spacing'] = self.horizontal_spacing\nsnap['vertical_spacing'] = self.vertical_spacing\nsnap['margins'] = self.margins\nreturn snap",
"super(FlowArea, self).bind()\nattrs = ('direction', 'alig... | <|body_start_0|>
snap = super(FlowArea, self).snapshot()
snap['direction'] = self.direction
snap['align'] = self.align
snap['horizontal_spacing'] = self.horizontal_spacing
snap['vertical_spacing'] = self.vertical_spacing
snap['margins'] = self.margins
return snap
... | A widget which lays out its children in flowing manner, wrapping around at the end of the available space. | FlowArea | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlowArea:
"""A widget which lays out its children in flowing manner, wrapping around at the end of the available space."""
def snapshot(self):
"""Returns the snapshot dict for the FlowArea."""
<|body_0|>
def bind(self):
"""Bind the change handler for the FlowItem... | stack_v2_sparse_classes_36k_train_001056 | 2,869 | permissive | [
{
"docstring": "Returns the snapshot dict for the FlowArea.",
"name": "snapshot",
"signature": "def snapshot(self)"
},
{
"docstring": "Bind the change handler for the FlowItem.",
"name": "bind",
"signature": "def bind(self)"
},
{
"docstring": "The getter for the 'flow_items' prop... | 3 | stack_v2_sparse_classes_30k_train_011142 | Implement the Python class `FlowArea` described below.
Class description:
A widget which lays out its children in flowing manner, wrapping around at the end of the available space.
Method signatures and docstrings:
- def snapshot(self): Returns the snapshot dict for the FlowArea.
- def bind(self): Bind the change han... | Implement the Python class `FlowArea` described below.
Class description:
A widget which lays out its children in flowing manner, wrapping around at the end of the available space.
Method signatures and docstrings:
- def snapshot(self): Returns the snapshot dict for the FlowArea.
- def bind(self): Bind the change han... | 424bba29219de58fe9e47196de6763de8b2009f2 | <|skeleton|>
class FlowArea:
"""A widget which lays out its children in flowing manner, wrapping around at the end of the available space."""
def snapshot(self):
"""Returns the snapshot dict for the FlowArea."""
<|body_0|>
def bind(self):
"""Bind the change handler for the FlowItem... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlowArea:
"""A widget which lays out its children in flowing manner, wrapping around at the end of the available space."""
def snapshot(self):
"""Returns the snapshot dict for the FlowArea."""
snap = super(FlowArea, self).snapshot()
snap['direction'] = self.direction
snap[... | the_stack_v2_python_sparse | enaml/widgets/flow_area.py | enthought/enaml | train | 17 |
0f027012c4cc833d629e898c23a42b744f558beb | [
"while True:\n try:\n move = random.choice(moves)\n return move\n except ValueError:\n continue",
"result = [elements[0]]\nfor index in range(1, len(elements)):\n if elements[index][0] > result[0][0]:\n result = [elements[index]]\n elif elements[index] == result[0][0]:\n ... | <|body_start_0|>
while True:
try:
move = random.choice(moves)
return move
except ValueError:
continue
<|end_body_0|>
<|body_start_1|>
result = [elements[0]]
for index in range(1, len(elements)):
if elements[inde... | Bot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bot:
def generate_move(moves):
"""Generates random move. :param moves: list of possible moves :return: int"""
<|body_0|>
def biggest_elements(elements):
"""Returns the biggest elements from elements. :param elements: list of elements :return: list of elements"""
... | stack_v2_sparse_classes_36k_train_001057 | 1,585 | no_license | [
{
"docstring": "Generates random move. :param moves: list of possible moves :return: int",
"name": "generate_move",
"signature": "def generate_move(moves)"
},
{
"docstring": "Returns the biggest elements from elements. :param elements: list of elements :return: list of elements",
"name": "bi... | 3 | stack_v2_sparse_classes_30k_train_002949 | Implement the Python class `Bot` described below.
Class description:
Implement the Bot class.
Method signatures and docstrings:
- def generate_move(moves): Generates random move. :param moves: list of possible moves :return: int
- def biggest_elements(elements): Returns the biggest elements from elements. :param elem... | Implement the Python class `Bot` described below.
Class description:
Implement the Bot class.
Method signatures and docstrings:
- def generate_move(moves): Generates random move. :param moves: list of possible moves :return: int
- def biggest_elements(elements): Returns the biggest elements from elements. :param elem... | 8367786a919b9566ed7e3378f0675872d539895d | <|skeleton|>
class Bot:
def generate_move(moves):
"""Generates random move. :param moves: list of possible moves :return: int"""
<|body_0|>
def biggest_elements(elements):
"""Returns the biggest elements from elements. :param elements: list of elements :return: list of elements"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bot:
def generate_move(moves):
"""Generates random move. :param moves: list of possible moves :return: int"""
while True:
try:
move = random.choice(moves)
return move
except ValueError:
continue
def biggest_elements(e... | the_stack_v2_python_sparse | base_tree_bot.py | borsukvasyl/NoughtsAndCrosses | train | 1 | |
9f698b853477b6f876f0a946e8dad425a05bedb7 | [
"if not date_string and (not time_string):\n raise errors.ParseError('Missing date or time string.')\ntry:\n month_string, day_of_month_string, year_string = date_string.split('/')\n year = int(year_string, 10)\n month = int(month_string, 10)\n day_of_month = int(day_of_month_string, 10)\nexcept (Att... | <|body_start_0|>
if not date_string and (not time_string):
raise errors.ParseError('Missing date or time string.')
try:
month_string, day_of_month_string, year_string = date_string.split('/')
year = int(year_string, 10)
month = int(month_string, 10)
... | Parses the McAfee AV Access Protection Log. | McafeeAccessProtectionParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class McafeeAccessProtectionParser:
"""Parses the McAfee AV Access Protection Log."""
def _CreateDateTime(self, date_string, time_string):
"""Creates a date time value from the date time strings. The format stores the date and time as 2 separate strings separated by a tab. The time is in l... | stack_v2_sparse_classes_36k_train_001058 | 6,022 | permissive | [
{
"docstring": "Creates a date time value from the date time strings. The format stores the date and time as 2 separate strings separated by a tab. The time is in local time. The month and day can be either 1 or 2 characters long, for example: \"7/30/2013\\\\t10:22:48 AM\" Args: date_string (str): date string. ... | 3 | stack_v2_sparse_classes_30k_train_011027 | Implement the Python class `McafeeAccessProtectionParser` described below.
Class description:
Parses the McAfee AV Access Protection Log.
Method signatures and docstrings:
- def _CreateDateTime(self, date_string, time_string): Creates a date time value from the date time strings. The format stores the date and time a... | Implement the Python class `McafeeAccessProtectionParser` described below.
Class description:
Parses the McAfee AV Access Protection Log.
Method signatures and docstrings:
- def _CreateDateTime(self, date_string, time_string): Creates a date time value from the date time strings. The format stores the date and time a... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class McafeeAccessProtectionParser:
"""Parses the McAfee AV Access Protection Log."""
def _CreateDateTime(self, date_string, time_string):
"""Creates a date time value from the date time strings. The format stores the date and time as 2 separate strings separated by a tab. The time is in l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class McafeeAccessProtectionParser:
"""Parses the McAfee AV Access Protection Log."""
def _CreateDateTime(self, date_string, time_string):
"""Creates a date time value from the date time strings. The format stores the date and time as 2 separate strings separated by a tab. The time is in local time. Th... | the_stack_v2_python_sparse | plaso/parsers/mcafeeav.py | log2timeline/plaso | train | 1,506 |
7e7b95a1aeebee239801632cfe9bedf2a848ed8c | [
"self.address = address\nself.is_cluster_auditing_enabled = is_cluster_auditing_enabled\nself.is_data_protection_enabled = is_data_protection_enabled\nself.is_filer_auditing_enabled = is_filer_auditing_enabled\nself.is_ssh_log_enabled = is_ssh_log_enabled\nself.name = name\nself.port = port\nself.protocol = protoco... | <|body_start_0|>
self.address = address
self.is_cluster_auditing_enabled = is_cluster_auditing_enabled
self.is_data_protection_enabled = is_data_protection_enabled
self.is_filer_auditing_enabled = is_filer_auditing_enabled
self.is_ssh_log_enabled = is_ssh_log_enabled
self... | Implementation of the 'SyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string): Specifies the IP address or hostname of the syslog server. is_cluster_auditing_enabled (bool): Specifies if Cluster audit logs should be sent to this sy... | SyslogServer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyslogServer:
"""Implementation of the 'SyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string): Specifies the IP address or hostname of the syslog server. is_cluster_auditing_enabled (bool): Specifies if Clus... | stack_v2_sparse_classes_36k_train_001059 | 4,641 | permissive | [
{
"docstring": "Constructor for the SyslogServer class",
"name": "__init__",
"signature": "def __init__(self, address=None, port=None, protocol=None, is_cluster_auditing_enabled=None, is_data_protection_enabled=None, is_filer_auditing_enabled=None, is_ssh_log_enabled=None, name=None)"
},
{
"docs... | 2 | stack_v2_sparse_classes_30k_train_020709 | Implement the Python class `SyslogServer` described below.
Class description:
Implementation of the 'SyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string): Specifies the IP address or hostname of the syslog server. is_cluster_aud... | Implement the Python class `SyslogServer` described below.
Class description:
Implementation of the 'SyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string): Specifies the IP address or hostname of the syslog server. is_cluster_aud... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class SyslogServer:
"""Implementation of the 'SyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string): Specifies the IP address or hostname of the syslog server. is_cluster_auditing_enabled (bool): Specifies if Clus... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SyslogServer:
"""Implementation of the 'SyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string): Specifies the IP address or hostname of the syslog server. is_cluster_auditing_enabled (bool): Specifies if Cluster audit log... | the_stack_v2_python_sparse | cohesity_management_sdk/models/syslog_server.py | cohesity/management-sdk-python | train | 24 |
b6211839220b437251d0b8fd96cd5c83d37ba005 | [
"if not username:\n raise ValueError('Users must have an username')\nuser = self.model(username=username)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(username=username, password=password)\nuser.is_admin = True\nuser.is_staff = True\nuser.save(using=self._db)\... | <|body_start_0|>
if not username:
raise ValueError('Users must have an username')
user = self.model(username=username)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.create_user(username=username,... | UserProfileManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfileManager:
def create_user(self, username, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, username, password):
"""Creates and saves a superuser with the given emai... | stack_v2_sparse_classes_36k_train_001060 | 12,800 | no_license | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, username, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
"name": "crea... | 2 | stack_v2_sparse_classes_30k_train_009589 | Implement the Python class `UserProfileManager` described below.
Class description:
Implement the UserProfileManager class.
Method signatures and docstrings:
- def create_user(self, username, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, email,... | Implement the Python class `UserProfileManager` described below.
Class description:
Implement the UserProfileManager class.
Method signatures and docstrings:
- def create_user(self, username, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, email,... | 57eeaa273c006af941be41499d2294d93105cf50 | <|skeleton|>
class UserProfileManager:
def create_user(self, username, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, username, password):
"""Creates and saves a superuser with the given emai... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserProfileManager:
def create_user(self, username, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
if not username:
raise ValueError('Users must have an username')
user = self.model(username=username)
user.set_passwo... | the_stack_v2_python_sparse | cmdb/models.py | hardyxia/AutoOps | train | 3 | |
9a943f8483c16ec0854de9637d8f8c0982661c67 | [
"num_subjects = len(extracted)\nnum_features = len(pipeline)\nfeatures = [[subject['features'][feature] for subject in extracted] for feature in range(num_features)]\nconsolidated = []\nfor feature in features:\n max_length = max((len(subject) for subject in feature))\n if all((len(subject) == max_length for ... | <|body_start_0|>
num_subjects = len(extracted)
num_features = len(pipeline)
features = [[subject['features'][feature] for subject in extracted] for feature in range(num_features)]
consolidated = []
for feature in features:
max_length = max((len(subject) for subject in... | Class implementing multi-subject feature values/labels utils | MultiSubjectFeatureUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiSubjectFeatureUtils:
"""Class implementing multi-subject feature values/labels utils"""
def prepare_feature_values(cls, extracted, pipeline):
"""Prepares the feature values. :param extracted: extracted features :type extracted: list :param pipeline: pipeline of the features to b... | stack_v2_sparse_classes_36k_train_001061 | 8,503 | permissive | [
{
"docstring": "Prepares the feature values. :param extracted: extracted features :type extracted: list :param pipeline: pipeline of the features to be extracted :type pipeline: list :return: finalized feature values :rtype: numpy.ndarray",
"name": "prepare_feature_values",
"signature": "def prepare_fea... | 2 | stack_v2_sparse_classes_30k_train_006878 | Implement the Python class `MultiSubjectFeatureUtils` described below.
Class description:
Class implementing multi-subject feature values/labels utils
Method signatures and docstrings:
- def prepare_feature_values(cls, extracted, pipeline): Prepares the feature values. :param extracted: extracted features :type extra... | Implement the Python class `MultiSubjectFeatureUtils` described below.
Class description:
Class implementing multi-subject feature values/labels utils
Method signatures and docstrings:
- def prepare_feature_values(cls, extracted, pipeline): Prepares the feature values. :param extracted: extracted features :type extra... | 0545ade5be63db78c99da9eb156a7be96ce63445 | <|skeleton|>
class MultiSubjectFeatureUtils:
"""Class implementing multi-subject feature values/labels utils"""
def prepare_feature_values(cls, extracted, pipeline):
"""Prepares the feature values. :param extracted: extracted features :type extracted: list :param pipeline: pipeline of the features to b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiSubjectFeatureUtils:
"""Class implementing multi-subject feature values/labels utils"""
def prepare_feature_values(cls, extracted, pipeline):
"""Prepares the feature values. :param extracted: extracted features :type extracted: list :param pipeline: pipeline of the features to be extracted :... | the_stack_v2_python_sparse | src/handwriting_features/interface/featurizer/utils.py | BDALab/handwriting-features | train | 6 |
6100f1a09996674b67a958a7026ada368ae699fb | [
"nn.Module.__init__(self)\nself.c = c\nself.nu = nu\nself.eps = eps\nself.soft_boundary = soft_boundary",
"dist = torch.sum((self.c - input) ** 2, dim=1)\nif self.soft_boundary:\n scores = dist - R ** 2\n loss = R ** 2 + 1 / self.nu * torch.mean(torch.max(torch.zeros_like(scores), scores))\nelse:\n loss ... | <|body_start_0|>
nn.Module.__init__(self)
self.c = c
self.nu = nu
self.eps = eps
self.soft_boundary = soft_boundary
<|end_body_0|>
<|body_start_1|>
dist = torch.sum((self.c - input) ** 2, dim=1)
if self.soft_boundary:
scores = dist - R ** 2
... | Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019) | DeepSVDDLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepSVDDLoss:
"""Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)"""
def __init__(self, c, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor) the center of the hypersphere as a multidimensional vec... | stack_v2_sparse_classes_36k_train_001062 | 18,386 | permissive | [
{
"docstring": "Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor) the center of the hypersphere as a multidimensional vector. |---- nu (float) a priory fraction of outliers. |---- eps (float) epsilon to ensure numerical stability in the | inverse distance. |---- soft_boundary (bool) whet... | 2 | stack_v2_sparse_classes_30k_train_009211 | Implement the Python class `DeepSVDDLoss` described below.
Class description:
Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)
Method signatures and docstrings:
- def __init__(self, c, nu, eps=1e-06, soft_boundary=False): Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor... | Implement the Python class `DeepSVDDLoss` described below.
Class description:
Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)
Method signatures and docstrings:
- def __init__(self, c, nu, eps=1e-06, soft_boundary=False): Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor... | 850b6195d6290a50eee865b4d5a66f5db5260e8f | <|skeleton|>
class DeepSVDDLoss:
"""Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)"""
def __init__(self, c, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor) the center of the hypersphere as a multidimensional vec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeepSVDDLoss:
"""Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)"""
def __init__(self, c, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor) the center of the hypersphere as a multidimensional vector. |---- nu... | the_stack_v2_python_sparse | Code/src/models/optim/CustomLosses.py | antoine-spahr/X-ray-Anomaly-Detection | train | 3 |
94e23ec24848e91906a5b33dba2072a562252fa2 | [
"MyInterestPage(app_page).login_user(data['username'], data['password'])\nMyInterestPage(app_page).my_interest()\nsuccess = MyInterestPage(app_page).confirm_my_interest()\nlogging.info('开始断言')\ntry:\n assert success == data['check']\n logging.info('我的兴趣页面跳转成功')\nexcept:\n print('我的兴趣页面跳转失败')\n common.sa... | <|body_start_0|>
MyInterestPage(app_page).login_user(data['username'], data['password'])
MyInterestPage(app_page).my_interest()
success = MyInterestPage(app_page).confirm_my_interest()
logging.info('开始断言')
try:
assert success == data['check']
logging.info(... | TestLoginUser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLoginUser:
def test_login_my_interest(self, data, app_page):
"""确认我的兴趣页面跳转是否成功"""
<|body_0|>
def test_my_interest_add(self, data, app_page):
"""我的兴趣-添加兴趣"""
<|body_1|>
def test_my_interest_del(self, data, app_page):
"""我的兴趣-删除兴趣"""
<|... | stack_v2_sparse_classes_36k_train_001063 | 4,839 | no_license | [
{
"docstring": "确认我的兴趣页面跳转是否成功",
"name": "test_login_my_interest",
"signature": "def test_login_my_interest(self, data, app_page)"
},
{
"docstring": "我的兴趣-添加兴趣",
"name": "test_my_interest_add",
"signature": "def test_my_interest_add(self, data, app_page)"
},
{
"docstring": "我的兴趣-... | 5 | null | Implement the Python class `TestLoginUser` described below.
Class description:
Implement the TestLoginUser class.
Method signatures and docstrings:
- def test_login_my_interest(self, data, app_page): 确认我的兴趣页面跳转是否成功
- def test_my_interest_add(self, data, app_page): 我的兴趣-添加兴趣
- def test_my_interest_del(self, data, app_... | Implement the Python class `TestLoginUser` described below.
Class description:
Implement the TestLoginUser class.
Method signatures and docstrings:
- def test_login_my_interest(self, data, app_page): 确认我的兴趣页面跳转是否成功
- def test_my_interest_add(self, data, app_page): 我的兴趣-添加兴趣
- def test_my_interest_del(self, data, app_... | b262c13e55a6e9eae1d4fa11d50b71814028261c | <|skeleton|>
class TestLoginUser:
def test_login_my_interest(self, data, app_page):
"""确认我的兴趣页面跳转是否成功"""
<|body_0|>
def test_my_interest_add(self, data, app_page):
"""我的兴趣-添加兴趣"""
<|body_1|>
def test_my_interest_del(self, data, app_page):
"""我的兴趣-删除兴趣"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestLoginUser:
def test_login_my_interest(self, data, app_page):
"""确认我的兴趣页面跳转是否成功"""
MyInterestPage(app_page).login_user(data['username'], data['password'])
MyInterestPage(app_page).my_interest()
success = MyInterestPage(app_page).confirm_my_interest()
logging.info('开始... | the_stack_v2_python_sparse | TestCase/test_app/test_my_interest.py | xjx985426946/Test_UI | train | 0 | |
fd190641c192e92d030316541d6db73178fe703a | [
"self.bytes_transferred = bytes_transferred\nself.end_timestamp_usecs = end_timestamp_usecs\nself.entity = entity\nself.error = error\nself.logical_bytes_transferred = logical_bytes_transferred\nself.logical_size_bytes = logical_size_bytes\nself.progress_monitor_task_path = progress_monitor_task_path\nself.relative... | <|body_start_0|>
self.bytes_transferred = bytes_transferred
self.end_timestamp_usecs = end_timestamp_usecs
self.entity = entity
self.error = error
self.logical_bytes_transferred = logical_bytes_transferred
self.logical_size_bytes = logical_size_bytes
self.progress... | Implementation of the 'RetrieveArchiveInfo_RetrievedEntity' model. Proto to define the info about the entity that was retrieved from an archive. Attributes: bytes_transferred (long|int): Number of physical bytes transferred over wire for this entity. end_timestamp_usecs (long|int): Time in microseconds when retrieve of... | RetrieveArchiveInfo_RetrievedEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetrieveArchiveInfo_RetrievedEntity:
"""Implementation of the 'RetrieveArchiveInfo_RetrievedEntity' model. Proto to define the info about the entity that was retrieved from an archive. Attributes: bytes_transferred (long|int): Number of physical bytes transferred over wire for this entity. end_ti... | stack_v2_sparse_classes_36k_train_001064 | 5,441 | permissive | [
{
"docstring": "Constructor for the RetrieveArchiveInfo_RetrievedEntity class",
"name": "__init__",
"signature": "def __init__(self, bytes_transferred=None, end_timestamp_usecs=None, entity=None, error=None, logical_bytes_transferred=None, logical_size_bytes=None, progress_monitor_task_path=None, relati... | 2 | null | Implement the Python class `RetrieveArchiveInfo_RetrievedEntity` described below.
Class description:
Implementation of the 'RetrieveArchiveInfo_RetrievedEntity' model. Proto to define the info about the entity that was retrieved from an archive. Attributes: bytes_transferred (long|int): Number of physical bytes transf... | Implement the Python class `RetrieveArchiveInfo_RetrievedEntity` described below.
Class description:
Implementation of the 'RetrieveArchiveInfo_RetrievedEntity' model. Proto to define the info about the entity that was retrieved from an archive. Attributes: bytes_transferred (long|int): Number of physical bytes transf... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RetrieveArchiveInfo_RetrievedEntity:
"""Implementation of the 'RetrieveArchiveInfo_RetrievedEntity' model. Proto to define the info about the entity that was retrieved from an archive. Attributes: bytes_transferred (long|int): Number of physical bytes transferred over wire for this entity. end_ti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RetrieveArchiveInfo_RetrievedEntity:
"""Implementation of the 'RetrieveArchiveInfo_RetrievedEntity' model. Proto to define the info about the entity that was retrieved from an archive. Attributes: bytes_transferred (long|int): Number of physical bytes transferred over wire for this entity. end_timestamp_usecs... | the_stack_v2_python_sparse | cohesity_management_sdk/models/retrieve_archive_info_retrieved_entity.py | cohesity/management-sdk-python | train | 24 |
d16c3c98671ff4be5693211dcd690bfd8a091c34 | [
"self.nums = []\nfor i in range(0, len(A), 2):\n cnt, val = (A[i], A[i + 1])\n if cnt > 0:\n self.nums.append([cnt, val])\nself.nums = self.nums[::-1]",
"while len(self.nums) > 0 and n > 0:\n c, v = self.nums[-1]\n if c > n:\n c -= n\n self.nums[-1][0] -= n\n return v\n ... | <|body_start_0|>
self.nums = []
for i in range(0, len(A), 2):
cnt, val = (A[i], A[i + 1])
if cnt > 0:
self.nums.append([cnt, val])
self.nums = self.nums[::-1]
<|end_body_0|>
<|body_start_1|>
while len(self.nums) > 0 and n > 0:
c, v = s... | RLEIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.nums = []
for i in range(0, len(A), 2):
cnt, val = (A[i],... | stack_v2_sparse_classes_36k_train_001065 | 2,706 | no_license | [
{
"docstring": ":type A: List[int]",
"name": "__init__",
"signature": "def __init__(self, A)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "next",
"signature": "def next(self, n)"
}
] | 2 | null | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int
<|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: Lis... | a5cb862f0c5a3cfd21468141800568c2dedded0a | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
self.nums = []
for i in range(0, len(A), 2):
cnt, val = (A[i], A[i + 1])
if cnt > 0:
self.nums.append([cnt, val])
self.nums = self.nums[::-1]
def next(self, n):
"""... | the_stack_v2_python_sparse | python/leetcode/design/900_RLE_iterator.py | Levintsky/topcoder | train | 0 | |
a1985af3fd7ab6331761630e066f5825900bbe66 | [
"ns_url = 'http://www.example.com/foo/namespace.txt'\nrelative_url = 'bar.txt'\nfinal_url = 'http://www.example.com/foo/bar.txt'\nx = lncore.basic_relative_url_handling_behavior(relative_url, ns_url)\nassert x == final_url",
"ns_url = 'http://www.example.com/foo/namespace.txt'\nabsolute_url = 'http://www.example.... | <|body_start_0|>
ns_url = 'http://www.example.com/foo/namespace.txt'
relative_url = 'bar.txt'
final_url = 'http://www.example.com/foo/bar.txt'
x = lncore.basic_relative_url_handling_behavior(relative_url, ns_url)
assert x == final_url
<|end_body_0|>
<|body_start_1|>
ns_u... | DOC DOC DOC | TestBasicRelativeURLHandlingBehavior | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestBasicRelativeURLHandlingBehavior:
"""DOC DOC DOC"""
def testBasic(self):
"""Test that basic relative URL handling behavior works."""
<|body_0|>
def testPassingAnAbsolute(self):
"""Test that absolute URLs are not handled specially."""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k_train_001066 | 34,773 | no_license | [
{
"docstring": "Test that basic relative URL handling behavior works.",
"name": "testBasic",
"signature": "def testBasic(self)"
},
{
"docstring": "Test that absolute URLs are not handled specially.",
"name": "testPassingAnAbsolute",
"signature": "def testPassingAnAbsolute(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003537 | Implement the Python class `TestBasicRelativeURLHandlingBehavior` described below.
Class description:
DOC DOC DOC
Method signatures and docstrings:
- def testBasic(self): Test that basic relative URL handling behavior works.
- def testPassingAnAbsolute(self): Test that absolute URLs are not handled specially. | Implement the Python class `TestBasicRelativeURLHandlingBehavior` described below.
Class description:
DOC DOC DOC
Method signatures and docstrings:
- def testBasic(self): Test that basic relative URL handling behavior works.
- def testPassingAnAbsolute(self): Test that absolute URLs are not handled specially.
<|skel... | da65d948b346d3f455e79168a8753b2b16d8fc5f | <|skeleton|>
class TestBasicRelativeURLHandlingBehavior:
"""DOC DOC DOC"""
def testBasic(self):
"""Test that basic relative URL handling behavior works."""
<|body_0|>
def testPassingAnAbsolute(self):
"""Test that absolute URLs are not handled specially."""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestBasicRelativeURLHandlingBehavior:
"""DOC DOC DOC"""
def testBasic(self):
"""Test that basic relative URL handling behavior works."""
ns_url = 'http://www.example.com/foo/namespace.txt'
relative_url = 'bar.txt'
final_url = 'http://www.example.com/foo/bar.txt'
x ... | the_stack_v2_python_sparse | pre2007/lncore/test.py | BackupTheBerlios/onebigsoup-svn | train | 0 |
a977567ffb25d182a782c53a33554d4c720f1903 | [
"if head is None:\n return None\nhead_old = head\nnew_node = head.next\nwhile new_node:\n tmp = new_node.next\n new_node.next = head\n head = new_node\n new_node = tmp\nhead_old.next = None\nreturn head",
"if head is None or head.next is None:\n return head\np = head\nrev = None\nwhile p:\n t... | <|body_start_0|>
if head is None:
return None
head_old = head
new_node = head.next
while new_node:
tmp = new_node.next
new_node.next = head
head = new_node
new_node = tmp
head_old.next = None
return head
<|end_bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList1(self, head):
"""modify list in place, needs three pointers. 1). Old head, which will become the tail at the end. old head.next should be the future head node 2). Next node: The one gonna become the new head, then back pointing to the next one in original list. ... | stack_v2_sparse_classes_36k_train_001067 | 2,049 | no_license | [
{
"docstring": "modify list in place, needs three pointers. 1). Old head, which will become the tail at the end. old head.next should be the future head node 2). Next node: The one gonna become the new head, then back pointing to the next one in original list. 3). New Head: The new head of reversed list. :type ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList1(self, head): modify list in place, needs three pointers. 1). Old head, which will become the tail at the end. old head.next should be the future head node 2). Ne... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList1(self, head): modify list in place, needs three pointers. 1). Old head, which will become the tail at the end. old head.next should be the future head node 2). Ne... | 11d6bf2ba7b50c07e048df37c4e05c8f46b92241 | <|skeleton|>
class Solution:
def reverseList1(self, head):
"""modify list in place, needs three pointers. 1). Old head, which will become the tail at the end. old head.next should be the future head node 2). Next node: The one gonna become the new head, then back pointing to the next one in original list. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList1(self, head):
"""modify list in place, needs three pointers. 1). Old head, which will become the tail at the end. old head.next should be the future head node 2). Next node: The one gonna become the new head, then back pointing to the next one in original list. 3). New Head: ... | the_stack_v2_python_sparse | LeetCodes/LinkedList/ReverseLinkedList.py | chutianwen/LeetCodes | 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_36k_train_001068 | 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_017757 | 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_36k | data/stack_v2_sparse_classes_30k | 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 | |
01a7bb3feae367edaef34dd5332a413a141475b6 | [
"total_size = sum([c[0] for c in counts])\navg_bin_size = total_size / K\nself.partitionAssignment = {}\npartitionSize = [0] * K\ncounts.sort(key=lambda k: k[0], reverse=True)\ni = 0\nfor count, partitionColumnStr in counts:\n jumps = 0\n while count + partitionSize[i] > avg_bin_size and jumps < K:\n i... | <|body_start_0|>
total_size = sum([c[0] for c in counts])
avg_bin_size = total_size / K
self.partitionAssignment = {}
partitionSize = [0] * K
counts.sort(key=lambda k: k[0], reverse=True)
i = 0
for count, partitionColumnStr in counts:
jumps = 0
... | FirstFitPartitioner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FirstFitPartitioner:
def __init__(self, K: int, counts: List[Tuple[int, str]]):
"""Initializer for the FirstFitPartitioner, which constructs a map of partitioner strings, and assigns them a parition id Keyword argument: K: number of partitions available counts: A list of entries of count... | stack_v2_sparse_classes_36k_train_001069 | 2,680 | no_license | [
{
"docstring": "Initializer for the FirstFitPartitioner, which constructs a map of partitioner strings, and assigns them a parition id Keyword argument: K: number of partitions available counts: A list of entries of counts of partitioning column string. When the column is user_id for example, it will be (counts... | 3 | stack_v2_sparse_classes_30k_train_002263 | Implement the Python class `FirstFitPartitioner` described below.
Class description:
Implement the FirstFitPartitioner class.
Method signatures and docstrings:
- def __init__(self, K: int, counts: List[Tuple[int, str]]): Initializer for the FirstFitPartitioner, which constructs a map of partitioner strings, and assig... | Implement the Python class `FirstFitPartitioner` described below.
Class description:
Implement the FirstFitPartitioner class.
Method signatures and docstrings:
- def __init__(self, K: int, counts: List[Tuple[int, str]]): Initializer for the FirstFitPartitioner, which constructs a map of partitioner strings, and assig... | f219dae1cbfb0f94789ca73982c90d999be048ed | <|skeleton|>
class FirstFitPartitioner:
def __init__(self, K: int, counts: List[Tuple[int, str]]):
"""Initializer for the FirstFitPartitioner, which constructs a map of partitioner strings, and assigns them a parition id Keyword argument: K: number of partitions available counts: A list of entries of count... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FirstFitPartitioner:
def __init__(self, K: int, counts: List[Tuple[int, str]]):
"""Initializer for the FirstFitPartitioner, which constructs a map of partitioner strings, and assigns them a parition id Keyword argument: K: number of partitions available counts: A list of entries of counts of partition... | the_stack_v2_python_sparse | fruit-phone-maker/Question2/Partitioner/FirstFitPartitioner.py | bhaavanmerchant/challenge-problems | train | 0 | |
d169f06c49e9beae3dc4d69b030f5ba9b0cf214c | [
"self.file_select_policy = file_select_policy\nself.file_size = file_size\nself.file_size_policy = file_size_policy\nself.hot_file_window = hot_file_window\nself.nfs_mount_path = nfs_mount_path\nself.num_file_access = num_file_access\nself.source_view_name = source_view_name\nself.uptier_all_files = uptier_all_file... | <|body_start_0|>
self.file_select_policy = file_select_policy
self.file_size = file_size
self.file_size_policy = file_size_policy
self.hot_file_window = hot_file_window
self.nfs_mount_path = nfs_mount_path
self.num_file_access = num_file_access
self.source_view_na... | Implementation of the 'FileUptieringParams' model. File Uptiering Parameters for NAS migration. Attributes: file_select_policy (int): File uptier policy based on file access/modify time. file_size (int): Gives the size criteria to be used for selecting the files to be uptiered. The hot files, which are greater or small... | FileUptieringParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileUptieringParams:
"""Implementation of the 'FileUptieringParams' model. File Uptiering Parameters for NAS migration. Attributes: file_select_policy (int): File uptier policy based on file access/modify time. file_size (int): Gives the size criteria to be used for selecting the files to be upti... | stack_v2_sparse_classes_36k_train_001070 | 4,196 | permissive | [
{
"docstring": "Constructor for the FileUptieringParams class",
"name": "__init__",
"signature": "def __init__(self, file_select_policy=None, file_size=None, file_size_policy=None, hot_file_window=None, nfs_mount_path=None, num_file_access=None, source_view_name=None, uptier_all_files=None)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_020575 | Implement the Python class `FileUptieringParams` described below.
Class description:
Implementation of the 'FileUptieringParams' model. File Uptiering Parameters for NAS migration. Attributes: file_select_policy (int): File uptier policy based on file access/modify time. file_size (int): Gives the size criteria to be ... | Implement the Python class `FileUptieringParams` described below.
Class description:
Implementation of the 'FileUptieringParams' model. File Uptiering Parameters for NAS migration. Attributes: file_select_policy (int): File uptier policy based on file access/modify time. file_size (int): Gives the size criteria to be ... | 0093194d125fc6746f55b8499da1270c64f473fc | <|skeleton|>
class FileUptieringParams:
"""Implementation of the 'FileUptieringParams' model. File Uptiering Parameters for NAS migration. Attributes: file_select_policy (int): File uptier policy based on file access/modify time. file_size (int): Gives the size criteria to be used for selecting the files to be upti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileUptieringParams:
"""Implementation of the 'FileUptieringParams' model. File Uptiering Parameters for NAS migration. Attributes: file_select_policy (int): File uptier policy based on file access/modify time. file_size (int): Gives the size criteria to be used for selecting the files to be uptiered. The hot... | the_stack_v2_python_sparse | cohesity_management_sdk/models/file_uptiering_params.py | hsantoyo2/management-sdk-python | train | 0 |
732df77d54a71c973574ed090dcd6bbb10b283a1 | [
"super().__init__()\nself.in_chans = in_chans\nself.out_chans = out_chans\nself.chans = chans\nself.num_pool_layers = num_pool_layers\nself.drop_prob = drop_prob\nself.down_sample_layers = nn.ModuleList([ConvBlock(in_chans, chans, drop_prob, variant=variant, ks=kernel_size, pad=padding, dil=dilation, num_group=grou... | <|body_start_0|>
super().__init__()
self.in_chans = in_chans
self.out_chans = out_chans
self.chans = chans
self.num_pool_layers = num_pool_layers
self.drop_prob = drop_prob
self.down_sample_layers = nn.ModuleList([ConvBlock(in_chans, chans, drop_prob, variant=vari... | PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention, pages 234–241. Springer, 2015. | UnetModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnetModel:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention, pages 234–241. S... | stack_v2_sparse_classes_36k_train_001071 | 7,919 | permissive | [
{
"docstring": "Args: in_chans (int): Number of channels in the input to the U-Net model. out_chans (int): Number of channels in the output to the U-Net model. chans (int): Number of output channels of the first convolution layer. num_pool_layers (int): Number of down-sampling and up-sampling layers. drop_prob ... | 2 | stack_v2_sparse_classes_30k_train_011262 | Implement the Python class `UnetModel` described below.
Class description:
PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-... | Implement the Python class `UnetModel` described below.
Class description:
PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-... | 84ab6e57748c2631b0e780255dcbc1d6e372269d | <|skeleton|>
class UnetModel:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention, pages 234–241. S... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnetModel:
"""PyTorch implementation of a U-Net model. This is based on: Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention, pages 234–241. Springer, 2015... | the_stack_v2_python_sparse | banding_removal/fastmri/model/public_unet.py | facebookresearch/fastMRI | train | 1,174 |
5d5cb8e6f60ffb6771aa1745b38aad782f530a31 | [
"object.__init__(self)\nself.stateLock = threading.Condition() if lock is None else lock\nself.msg = msg",
"self.stateLock.acquire()\ntry:\n self.msg = msg\nfinally:\n self.stateLock.notify()\n self.stateLock.release()",
"self.stateLock.acquire()\nwhile self.msg is None:\n self.stateLock.wait(timeOu... | <|body_start_0|>
object.__init__(self)
self.stateLock = threading.Condition() if lock is None else lock
self.msg = msg
<|end_body_0|>
<|body_start_1|>
self.stateLock.acquire()
try:
self.msg = msg
finally:
self.stateLock.notify()
self.s... | Used when a worker thread is told to do lengthy things to a shared resource (say a gui window) and only the last (whenever that may arrive) one matters. Like a 1 deep queue which only contains the last added entry. | LatestMessage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LatestMessage:
"""Used when a worker thread is told to do lengthy things to a shared resource (say a gui window) and only the last (whenever that may arrive) one matters. Like a 1 deep queue which only contains the last added entry."""
def __init__(self, msg=None, lock=None):
"""'msg... | stack_v2_sparse_classes_36k_train_001072 | 4,351 | no_license | [
{
"docstring": "'msg' is an initial value. 'lock' is an optional lock to be used else a new one is allocated.",
"name": "__init__",
"signature": "def __init__(self, msg=None, lock=None)"
},
{
"docstring": "place the message and ensure the worker thread is notified is waiting",
"name": "setMs... | 3 | stack_v2_sparse_classes_30k_train_019685 | Implement the Python class `LatestMessage` described below.
Class description:
Used when a worker thread is told to do lengthy things to a shared resource (say a gui window) and only the last (whenever that may arrive) one matters. Like a 1 deep queue which only contains the last added entry.
Method signatures and do... | Implement the Python class `LatestMessage` described below.
Class description:
Used when a worker thread is told to do lengthy things to a shared resource (say a gui window) and only the last (whenever that may arrive) one matters. Like a 1 deep queue which only contains the last added entry.
Method signatures and do... | b54f23c6c5f1f19e426ee06c9e9faf9f561ee9a9 | <|skeleton|>
class LatestMessage:
"""Used when a worker thread is told to do lengthy things to a shared resource (say a gui window) and only the last (whenever that may arrive) one matters. Like a 1 deep queue which only contains the last added entry."""
def __init__(self, msg=None, lock=None):
"""'msg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LatestMessage:
"""Used when a worker thread is told to do lengthy things to a shared resource (say a gui window) and only the last (whenever that may arrive) one matters. Like a 1 deep queue which only contains the last added entry."""
def __init__(self, msg=None, lock=None):
"""'msg' is an initi... | the_stack_v2_python_sparse | pylib/thread.py | chyser/bin | train | 1 |
326194bb2c87f4e67c20d817b10398053d16a00a | [
"length = 0\nfor a in args:\n if a:\n length = len(a)\nreturn length",
"self.image_id = image_id\nlength = self._get_length(question_ids, questions, answers, captions)\nself.question_ids = question_ids or [-1] * length\nself.questions = questions or ['_'] * length\nself.answers = answers or ['_'] * leng... | <|body_start_0|>
length = 0
for a in args:
if a:
length = len(a)
return length
<|end_body_0|>
<|body_start_1|>
self.image_id = image_id
length = self._get_length(question_ids, questions, answers, captions)
self.question_ids = question_ids or [... | Wrapper with defaults around image metadata (for both captions and QA). | ImageMetadata | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageMetadata:
"""Wrapper with defaults around image metadata (for both captions and QA)."""
def _get_length(*args):
"""Helper to establish length of arguments."""
<|body_0|>
def __init__(self, image_id=-1, question_ids=None, questions=None, answers=None, captions=None, ... | stack_v2_sparse_classes_36k_train_001073 | 4,191 | permissive | [
{
"docstring": "Helper to establish length of arguments.",
"name": "_get_length",
"signature": "def _get_length(*args)"
},
{
"docstring": "Initialization. Args: image_id: (optional) Identifier for the image. question_ids: (optional) List of unique identifiers for the questions. questions: (optio... | 2 | null | Implement the Python class `ImageMetadata` described below.
Class description:
Wrapper with defaults around image metadata (for both captions and QA).
Method signatures and docstrings:
- def _get_length(*args): Helper to establish length of arguments.
- def __init__(self, image_id=-1, question_ids=None, questions=Non... | Implement the Python class `ImageMetadata` described below.
Class description:
Wrapper with defaults around image metadata (for both captions and QA).
Method signatures and docstrings:
- def _get_length(*args): Helper to establish length of arguments.
- def __init__(self, image_id=-1, question_ids=None, questions=Non... | ac9447064195e06de48cc91ff642f7fffa28ffe8 | <|skeleton|>
class ImageMetadata:
"""Wrapper with defaults around image metadata (for both captions and QA)."""
def _get_length(*args):
"""Helper to establish length of arguments."""
<|body_0|>
def __init__(self, image_id=-1, question_ids=None, questions=None, answers=None, captions=None, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageMetadata:
"""Wrapper with defaults around image metadata (for both captions and QA)."""
def _get_length(*args):
"""Helper to establish length of arguments."""
length = 0
for a in args:
if a:
length = len(a)
return length
def __init__(s... | the_stack_v2_python_sparse | language/capwap/utils/image_utils.py | google-research/language | train | 1,567 |
3a022f3842aafbe513a4591d1ea30a49f76bff70 | [
"BEGIN = 'pg1'\nfor city in self.cities:\n print(self.lianjia_url.format(city=city, page=BEGIN))\n yield Request(self.lianjia_url.format(city=city, page=BEGIN), meta={'city': city}, callback=self.parse_start, dont_filter=True)",
"RP = 'rp'\ncity = response.meta['city']\nzone_lis = response.css('#filter ul:n... | <|body_start_0|>
BEGIN = 'pg1'
for city in self.cities:
print(self.lianjia_url.format(city=city, page=BEGIN))
yield Request(self.lianjia_url.format(city=city, page=BEGIN), meta={'city': city}, callback=self.parse_start, dont_filter=True)
<|end_body_0|>
<|body_start_1|>
R... | 爬取链家的出租房源，去重中介重复发的信息，如朝阳区有5266房源，但是重复的这有1000多条信息 就是中介重复发同一条房源信息，提高流量。 | RenthouseSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RenthouseSpider:
"""爬取链家的出租房源，去重中介重复发的信息，如朝阳区有5266房源，但是重复的这有1000多条信息 就是中介重复发同一条房源信息，提高流量。"""
def start_requests(self):
"""对每一个city进行请求 分析主页面"""
<|body_0|>
def parse_start(self, response):
"""获取主页的地区和价格分区 然后分类进行爬虫. 特殊逻辑：因为linajia只是吐出3000条数据一次性，不分类拿不到全部数据. 很多城市的房源都... | stack_v2_sparse_classes_36k_train_001074 | 6,571 | no_license | [
{
"docstring": "对每一个city进行请求 分析主页面",
"name": "start_requests",
"signature": "def start_requests(self)"
},
{
"docstring": "获取主页的地区和价格分区 然后分类进行爬虫. 特殊逻辑：因为linajia只是吐出3000条数据一次性，不分类拿不到全部数据. 很多城市的房源都是大于3000套的",
"name": "parse_start",
"signature": "def parse_start(self, response)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_011078 | Implement the Python class `RenthouseSpider` described below.
Class description:
爬取链家的出租房源，去重中介重复发的信息，如朝阳区有5266房源，但是重复的这有1000多条信息 就是中介重复发同一条房源信息，提高流量。
Method signatures and docstrings:
- def start_requests(self): 对每一个city进行请求 分析主页面
- def parse_start(self, response): 获取主页的地区和价格分区 然后分类进行爬虫. 特殊逻辑：因为linajia只是吐出3000条数据一次性... | Implement the Python class `RenthouseSpider` described below.
Class description:
爬取链家的出租房源，去重中介重复发的信息，如朝阳区有5266房源，但是重复的这有1000多条信息 就是中介重复发同一条房源信息，提高流量。
Method signatures and docstrings:
- def start_requests(self): 对每一个city进行请求 分析主页面
- def parse_start(self, response): 获取主页的地区和价格分区 然后分类进行爬虫. 特殊逻辑：因为linajia只是吐出3000条数据一次性... | 63b540cd60abf67dfe84d87d8c219075ccddc28a | <|skeleton|>
class RenthouseSpider:
"""爬取链家的出租房源，去重中介重复发的信息，如朝阳区有5266房源，但是重复的这有1000多条信息 就是中介重复发同一条房源信息，提高流量。"""
def start_requests(self):
"""对每一个city进行请求 分析主页面"""
<|body_0|>
def parse_start(self, response):
"""获取主页的地区和价格分区 然后分类进行爬虫. 特殊逻辑：因为linajia只是吐出3000条数据一次性，不分类拿不到全部数据. 很多城市的房源都... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RenthouseSpider:
"""爬取链家的出租房源，去重中介重复发的信息，如朝阳区有5266房源，但是重复的这有1000多条信息 就是中介重复发同一条房源信息，提高流量。"""
def start_requests(self):
"""对每一个city进行请求 分析主页面"""
BEGIN = 'pg1'
for city in self.cities:
print(self.lianjia_url.format(city=city, page=BEGIN))
yield Request(self.l... | the_stack_v2_python_sparse | lianjia/build/lib/lianjia/spiders/renthouse.py | Schneizelw/supreme | train | 0 |
48c465e44c706d49317aa6a4b55332d23166d421 | [
"super(CNN, self).__init__()\nself.input_channel_count = input_channel_count\nself.output_channel_count = output_channel_count\nself.conv = nn.Conv1d(in_channels=input_channel_count, out_channels=output_channel_count, kernel_size=kernel_size)\nself.max_pool = nn.AdaptiveMaxPool1d(output_size=1)\nself.relu = nn.ReLU... | <|body_start_0|>
super(CNN, self).__init__()
self.input_channel_count = input_channel_count
self.output_channel_count = output_channel_count
self.conv = nn.Conv1d(in_channels=input_channel_count, out_channels=output_channel_count, kernel_size=kernel_size)
self.max_pool = nn.Adapt... | CNN Layer, i.e. a layer of cnn network that takes the output of convolutional network as input | CNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CNN:
"""CNN Layer, i.e. a layer of cnn network that takes the output of convolutional network as input"""
def __init__(self, input_channel_count, output_channel_count, kernel_size=5):
"""Init HighWay Instance. @param input_channel_count: int @param output_channel_count: int @param ke... | stack_v2_sparse_classes_36k_train_001075 | 2,032 | no_license | [
{
"docstring": "Init HighWay Instance. @param input_channel_count: int @param output_channel_count: int @param kernel_size: int",
"name": "__init__",
"signature": "def __init__(self, input_channel_count, output_channel_count, kernel_size=5)"
},
{
"docstring": "Run a forward step that map a batch... | 2 | stack_v2_sparse_classes_30k_train_006314 | Implement the Python class `CNN` described below.
Class description:
CNN Layer, i.e. a layer of cnn network that takes the output of convolutional network as input
Method signatures and docstrings:
- def __init__(self, input_channel_count, output_channel_count, kernel_size=5): Init HighWay Instance. @param input_chan... | Implement the Python class `CNN` described below.
Class description:
CNN Layer, i.e. a layer of cnn network that takes the output of convolutional network as input
Method signatures and docstrings:
- def __init__(self, input_channel_count, output_channel_count, kernel_size=5): Init HighWay Instance. @param input_chan... | a883935d779dca3a3cc443c3fa6d6a455f21e87a | <|skeleton|>
class CNN:
"""CNN Layer, i.e. a layer of cnn network that takes the output of convolutional network as input"""
def __init__(self, input_channel_count, output_channel_count, kernel_size=5):
"""Init HighWay Instance. @param input_channel_count: int @param output_channel_count: int @param ke... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CNN:
"""CNN Layer, i.e. a layer of cnn network that takes the output of convolutional network as input"""
def __init__(self, input_channel_count, output_channel_count, kernel_size=5):
"""Init HighWay Instance. @param input_channel_count: int @param output_channel_count: int @param kernel_size: in... | the_stack_v2_python_sparse | stanford_nlp/a5/cnn.py | guocongyun/ml-projects | train | 0 |
e341edb681b88c6efbd65316388ccf6a01b326f3 | [
"type = kwargs['type']\nfile = kwargs['file']\nwith open(file, 'r') as data_file:\n for line in data_file:\n line = line[:-1]\n items_dict = ast.literal_eval(line)\n item = type.from_dict(items_dict)\n self.add_item(item, lambda i: i.uid)",
"file = kwargs['file']\nwith open(file, 'w... | <|body_start_0|>
type = kwargs['type']
file = kwargs['file']
with open(file, 'r') as data_file:
for line in data_file:
line = line[:-1]
items_dict = ast.literal_eval(line)
item = type.from_dict(items_dict)
self.add_item(... | RepositoryText | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RepositoryText:
def load_data(self, **kwargs):
"""Load repository from txt file. :param kwargs: file - file to load the data from type - the type of the objects :return:"""
<|body_0|>
def save_data(self, **kwargs):
"""Save repository to txt file. :param kwargs: file ... | stack_v2_sparse_classes_36k_train_001076 | 1,259 | no_license | [
{
"docstring": "Load repository from txt file. :param kwargs: file - file to load the data from type - the type of the objects :return:",
"name": "load_data",
"signature": "def load_data(self, **kwargs)"
},
{
"docstring": "Save repository to txt file. :param kwargs: file - file to load the data ... | 2 | stack_v2_sparse_classes_30k_train_002319 | Implement the Python class `RepositoryText` described below.
Class description:
Implement the RepositoryText class.
Method signatures and docstrings:
- def load_data(self, **kwargs): Load repository from txt file. :param kwargs: file - file to load the data from type - the type of the objects :return:
- def save_data... | Implement the Python class `RepositoryText` described below.
Class description:
Implement the RepositoryText class.
Method signatures and docstrings:
- def load_data(self, **kwargs): Load repository from txt file. :param kwargs: file - file to load the data from type - the type of the objects :return:
- def save_data... | 206b049700d8a3e03b52e57960cd44f85c415fe8 | <|skeleton|>
class RepositoryText:
def load_data(self, **kwargs):
"""Load repository from txt file. :param kwargs: file - file to load the data from type - the type of the objects :return:"""
<|body_0|>
def save_data(self, **kwargs):
"""Save repository to txt file. :param kwargs: file ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RepositoryText:
def load_data(self, **kwargs):
"""Load repository from txt file. :param kwargs: file - file to load the data from type - the type of the objects :return:"""
type = kwargs['type']
file = kwargs['file']
with open(file, 'r') as data_file:
for line in da... | the_stack_v2_python_sparse | semester_1/fp/assignment_09/src/repositories/repository_text.py | caprapaul/assignments | train | 0 | |
c9baccb09e5ac57daef9000707807c94034c59e4 | [
"self.screen_width = 1200\nself.screen_height = 680\nself.bg_color = (0, 20, 50)\nself.hero_limit = 3\nself.bullets_allowed = 5\nself.covid_vertical_speed_factor = 1\nself.speedup_scale = 1.1\nself.initialize_dynamic_settings()",
"self.hero_speed_factor = 1.5\nself.bullet_speed_factor = 1\nself.covid_horizontal_s... | <|body_start_0|>
self.screen_width = 1200
self.screen_height = 680
self.bg_color = (0, 20, 50)
self.hero_limit = 3
self.bullets_allowed = 5
self.covid_vertical_speed_factor = 1
self.speedup_scale = 1.1
self.initialize_dynamic_settings()
<|end_body_0|>
<|b... | A class that have all configurations of the game | Settings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""A class that have all configurations of the game"""
def __init__(self):
"""Initialize the game configs"""
<|body_0|>
def initialize_dynamic_settings(self):
"""Initializes the configurations that increase during the game"""
<|body_1|>
def... | stack_v2_sparse_classes_36k_train_001077 | 2,241 | permissive | [
{
"docstring": "Initialize the game configs",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Initializes the configurations that increase during the game",
"name": "initialize_dynamic_settings",
"signature": "def initialize_dynamic_settings(self)"
},
{
"... | 3 | stack_v2_sparse_classes_30k_train_005448 | Implement the Python class `Settings` described below.
Class description:
A class that have all configurations of the game
Method signatures and docstrings:
- def __init__(self): Initialize the game configs
- def initialize_dynamic_settings(self): Initializes the configurations that increase during the game
- def inc... | Implement the Python class `Settings` described below.
Class description:
A class that have all configurations of the game
Method signatures and docstrings:
- def __init__(self): Initialize the game configs
- def initialize_dynamic_settings(self): Initializes the configurations that increase during the game
- def inc... | 4b336ebf0bc29aa4c644f0996431d13f853ac6e7 | <|skeleton|>
class Settings:
"""A class that have all configurations of the game"""
def __init__(self):
"""Initialize the game configs"""
<|body_0|>
def initialize_dynamic_settings(self):
"""Initializes the configurations that increase during the game"""
<|body_1|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Settings:
"""A class that have all configurations of the game"""
def __init__(self):
"""Initialize the game configs"""
self.screen_width = 1200
self.screen_height = 680
self.bg_color = (0, 20, 50)
self.hero_limit = 3
self.bullets_allowed = 5
self.co... | the_stack_v2_python_sparse | pygame/hero_combat/hero_settings.py | carlinhoshk/python | train | 0 |
d421d458d0d27392352a69a7b631b84bdc8f09bb | [
"ApiProvider.__init__(self)\nself.http_provider = http_provider\nself.counter = itertools.count()\nself.to_vapi = JsonRpcDictToVapi\nself.post_processors = [constructor() for constructor in dynamic_import_list(post_processors)]",
"params = {'serviceId': service_id, 'operationId': operation_id, 'input': input_valu... | <|body_start_0|>
ApiProvider.__init__(self)
self.http_provider = http_provider
self.counter = itertools.count()
self.to_vapi = JsonRpcDictToVapi
self.post_processors = [constructor() for constructor in dynamic_import_list(post_processors)]
<|end_body_0|>
<|body_start_1|>
... | Json rpc client provider | JsonClientProvider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JsonClientProvider:
"""Json rpc client provider"""
def __init__(self, http_provider, post_processors):
"""Json rpc client provider init :type http_provider: :class:`vmware.vapi.protocol.client.rpc.provider.HTTPProvider` :param http_provider: rpc provider object :type post_processors:... | stack_v2_sparse_classes_36k_train_001078 | 5,842 | no_license | [
{
"docstring": "Json rpc client provider init :type http_provider: :class:`vmware.vapi.protocol.client.rpc.provider.HTTPProvider` :param http_provider: rpc provider object :type post_processors: :class:`list` of :class:`str` :param post_processors: List of post processor class names",
"name": "__init__",
... | 3 | null | Implement the Python class `JsonClientProvider` described below.
Class description:
Json rpc client provider
Method signatures and docstrings:
- def __init__(self, http_provider, post_processors): Json rpc client provider init :type http_provider: :class:`vmware.vapi.protocol.client.rpc.provider.HTTPProvider` :param ... | Implement the Python class `JsonClientProvider` described below.
Class description:
Json rpc client provider
Method signatures and docstrings:
- def __init__(self, http_provider, post_processors): Json rpc client provider init :type http_provider: :class:`vmware.vapi.protocol.client.rpc.provider.HTTPProvider` :param ... | 5d395700ab3d0d1d45b497e48beab8c366fca9f5 | <|skeleton|>
class JsonClientProvider:
"""Json rpc client provider"""
def __init__(self, http_provider, post_processors):
"""Json rpc client provider init :type http_provider: :class:`vmware.vapi.protocol.client.rpc.provider.HTTPProvider` :param http_provider: rpc provider object :type post_processors:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JsonClientProvider:
"""Json rpc client provider"""
def __init__(self, http_provider, post_processors):
"""Json rpc client provider init :type http_provider: :class:`vmware.vapi.protocol.client.rpc.provider.HTTPProvider` :param http_provider: rpc provider object :type post_processors: :class:`list... | the_stack_v2_python_sparse | alexa-program.bak/vmware/vapi/protocol/client/msg/json_connector.py | taromurata/TDP2018_VMCAPI | train | 1 |
e3ecdad0d3c76e27e790a9edda1c5f417303d55d | [
"if std_w is None:\n std_w = 1 / np.sqrt(0.5 * n_input)\nself.lr = lr\nself.w = Tensor(n_output, n_input).normal_(0, std_w)\nself.dw = Tensor(self.w.shape).zero_()\nself.bias = bias\nif bias:\n if not std_b:\n self.b = Tensor(n_output, 1).fill_(0)\n else:\n self.b = Tensor(n_output, 1).normal... | <|body_start_0|>
if std_w is None:
std_w = 1 / np.sqrt(0.5 * n_input)
self.lr = lr
self.w = Tensor(n_output, n_input).normal_(0, std_w)
self.dw = Tensor(self.w.shape).zero_()
self.bias = bias
if bias:
if not std_b:
self.b = Tensor(n... | Implements the fully connected layer module It requires the number of inputs and outputs. Weights are initialized assuming that a ReLU module will be used afterwards. If a Tanh module will be used instead, it is recommended to set std_w = 1 / np.sqrt(n_input) It is possible to set a default learning rate that will be u... | Linear | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Linear:
"""Implements the fully connected layer module It requires the number of inputs and outputs. Weights are initialized assuming that a ReLU module will be used afterwards. If a Tanh module will be used instead, it is recommended to set std_w = 1 / np.sqrt(n_input) It is possible to set a de... | stack_v2_sparse_classes_36k_train_001079 | 9,572 | permissive | [
{
"docstring": "INPUT: n_input: Size of input n_output: Number of hidden units lr: If adaptive learning rate is not used, learning rate used for update std_w: Normal distribution initialization of weights with std = std_w/ If None, std_w is chosen according to Xavier initialization. bias: If true, use bias std_... | 5 | stack_v2_sparse_classes_30k_train_017635 | Implement the Python class `Linear` described below.
Class description:
Implements the fully connected layer module It requires the number of inputs and outputs. Weights are initialized assuming that a ReLU module will be used afterwards. If a Tanh module will be used instead, it is recommended to set std_w = 1 / np.s... | Implement the Python class `Linear` described below.
Class description:
Implements the fully connected layer module It requires the number of inputs and outputs. Weights are initialized assuming that a ReLU module will be used afterwards. If a Tanh module will be used instead, it is recommended to set std_w = 1 / np.s... | 303fb507fc6a756b4bfbb3c9fbd57230c866b39b | <|skeleton|>
class Linear:
"""Implements the fully connected layer module It requires the number of inputs and outputs. Weights are initialized assuming that a ReLU module will be used afterwards. If a Tanh module will be used instead, it is recommended to set std_w = 1 / np.sqrt(n_input) It is possible to set a de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Linear:
"""Implements the fully connected layer module It requires the number of inputs and outputs. Weights are initialized assuming that a ReLU module will be used afterwards. If a Tanh module will be used instead, it is recommended to set std_w = 1 / np.sqrt(n_input) It is possible to set a default learnin... | the_stack_v2_python_sparse | Projects/Project2/framework/modules.py | lumosan/deeplearning2018 | train | 0 |
d4a04969cb0c0bf3cffc64ef162b3110e30b8d7b | [
"if is_horizontal:\n super(Composition3x1, self).__init__(3 * width, height)\nelse:\n super(Composition3x1, self).__init__(width, 3 * height)\nself.single_w = width\nself.single_h = height\nself.is_horizontal = is_horizontal\nself.empty = np.zeros((height, width, 3), dtype=np.uint8)\nself.left = left\nself.mi... | <|body_start_0|>
if is_horizontal:
super(Composition3x1, self).__init__(3 * width, height)
else:
super(Composition3x1, self).__init__(width, 3 * height)
self.single_w = width
self.single_h = height
self.is_horizontal = is_horizontal
self.empty = np... | Display two keras_tf next to each other. | Composition3x1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Composition3x1:
"""Display two keras_tf next to each other."""
def __init__(self, width, height, left, middle, right, is_horizontal: bool=True):
"""Initialize the step with all relevant attributes. :param width: Width of the final composition. :param height: Height of the final compo... | stack_v2_sparse_classes_36k_train_001080 | 1,891 | no_license | [
{
"docstring": "Initialize the step with all relevant attributes. :param width: Width of the final composition. :param height: Height of the final composition. :param left: Reference to the function which gets the frame to be displayed on left. :param right: Reference to the function which gets the frame to be ... | 2 | stack_v2_sparse_classes_30k_train_000390 | Implement the Python class `Composition3x1` described below.
Class description:
Display two keras_tf next to each other.
Method signatures and docstrings:
- def __init__(self, width, height, left, middle, right, is_horizontal: bool=True): Initialize the step with all relevant attributes. :param width: Width of the fi... | Implement the Python class `Composition3x1` described below.
Class description:
Display two keras_tf next to each other.
Method signatures and docstrings:
- def __init__(self, width, height, left, middle, right, is_horizontal: bool=True): Initialize the step with all relevant attributes. :param width: Width of the fi... | 8316bcc43805ba3cdc196b68b14f921f81610337 | <|skeleton|>
class Composition3x1:
"""Display two keras_tf next to each other."""
def __init__(self, width, height, left, middle, right, is_horizontal: bool=True):
"""Initialize the step with all relevant attributes. :param width: Width of the final composition. :param height: Height of the final compo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Composition3x1:
"""Display two keras_tf next to each other."""
def __init__(self, width, height, left, middle, right, is_horizontal: bool=True):
"""Initialize the step with all relevant attributes. :param width: Width of the final composition. :param height: Height of the final composition. :para... | the_stack_v2_python_sparse | video/pipeline/compositions/composition_3x1.py | breitmuuufrosch/OpenCvPipeline | train | 0 |
da6e8e90b303be724b177840345b1640e5b79a0c | [
"while n % 4 == 0:\n n = n // 4\nif n % 8 == 7:\n return 4\nx = 0\nwhile x * x <= n:\n y = int(math.sqrt(n - x * x))\n if x * x + y * y == n:\n if x == 0 or y == 0:\n return 1\n else:\n return 2\n x += 1\nreturn 3",
"dp = [2147483647 for _ in range(n + 1)]\ndp[0]... | <|body_start_0|>
while n % 4 == 0:
n = n // 4
if n % 8 == 7:
return 4
x = 0
while x * x <= n:
y = int(math.sqrt(n - x * x))
if x * x + y * y == n:
if x == 0 or y == 0:
return 1
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numSquares(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def numSquares_dp1(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def numSquares_dp2(self, n):
""":type n: int :rtype: int"""
<|body_2|>
def numSquares... | stack_v2_sparse_classes_36k_train_001081 | 4,676 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "numSquares",
"signature": "def numSquares(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "numSquares_dp1",
"signature": "def numSquares_dp1(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "nu... | 6 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSquares(self, n): :type n: int :rtype: int
- def numSquares_dp1(self, n): :type n: int :rtype: int
- def numSquares_dp2(self, n): :type n: int :rtype: int
- def numSquares... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSquares(self, n): :type n: int :rtype: int
- def numSquares_dp1(self, n): :type n: int :rtype: int
- def numSquares_dp2(self, n): :type n: int :rtype: int
- def numSquares... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def numSquares(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def numSquares_dp1(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def numSquares_dp2(self, n):
""":type n: int :rtype: int"""
<|body_2|>
def numSquares... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numSquares(self, n):
""":type n: int :rtype: int"""
while n % 4 == 0:
n = n // 4
if n % 8 == 7:
return 4
x = 0
while x * x <= n:
y = int(math.sqrt(n - x * x))
if x * x + y * y == n:
if x == 0 ... | the_stack_v2_python_sparse | src/lt_279.py | oxhead/CodingYourWay | train | 0 | |
dc77d866df98cac34dc54f350b08e3835b31220e | [
"status = _SpawnChild(exit_code=0)\nret = process_util.GetExitStatus(status)\nself.assertEqual(ret, 0)",
"status = _SpawnChild(exit_code=10)\nret = process_util.GetExitStatus(status)\nself.assertEqual(ret, 10)",
"status = _SpawnChild(exit_code=150)\nret = process_util.GetExitStatus(status)\nself.assertEqual(ret... | <|body_start_0|>
status = _SpawnChild(exit_code=0)
ret = process_util.GetExitStatus(status)
self.assertEqual(ret, 0)
<|end_body_0|>
<|body_start_1|>
status = _SpawnChild(exit_code=10)
ret = process_util.GetExitStatus(status)
self.assertEqual(ret, 10)
<|end_body_1|>
<|bo... | Tests for GetExitStatus() | GetExitStatusTests | [
"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 GetExitStatusTests:
"""Tests for GetExitStatus()"""
def testExitNormal(self):
"""Verify normal exits get decoded."""
<|body_0|>
def testExitError(self):
"""Verify error exits (>0 && <128) get decoded."""
<|body_1|>
def testExitWeird(self):
""... | stack_v2_sparse_classes_36k_train_001082 | 3,622 | permissive | [
{
"docstring": "Verify normal exits get decoded.",
"name": "testExitNormal",
"signature": "def testExitNormal(self)"
},
{
"docstring": "Verify error exits (>0 && <128) get decoded.",
"name": "testExitError",
"signature": "def testExitError(self)"
},
{
"docstring": "Verify weird e... | 5 | stack_v2_sparse_classes_30k_train_008225 | Implement the Python class `GetExitStatusTests` described below.
Class description:
Tests for GetExitStatus()
Method signatures and docstrings:
- def testExitNormal(self): Verify normal exits get decoded.
- def testExitError(self): Verify error exits (>0 && <128) get decoded.
- def testExitWeird(self): Verify weird e... | Implement the Python class `GetExitStatusTests` described below.
Class description:
Tests for GetExitStatus()
Method signatures and docstrings:
- def testExitNormal(self): Verify normal exits get decoded.
- def testExitError(self): Verify error exits (>0 && <128) get decoded.
- def testExitWeird(self): Verify weird e... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class GetExitStatusTests:
"""Tests for GetExitStatus()"""
def testExitNormal(self):
"""Verify normal exits get decoded."""
<|body_0|>
def testExitError(self):
"""Verify error exits (>0 && <128) get decoded."""
<|body_1|>
def testExitWeird(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetExitStatusTests:
"""Tests for GetExitStatus()"""
def testExitNormal(self):
"""Verify normal exits get decoded."""
status = _SpawnChild(exit_code=0)
ret = process_util.GetExitStatus(status)
self.assertEqual(ret, 0)
def testExitError(self):
"""Verify error ex... | the_stack_v2_python_sparse | third_party/chromite/lib/process_util_unittest.py | metux/chromium-suckless | train | 5 |
241bd309a865f0a82daeec969f00b7fc366a5ee9 | [
"if df is None:\n self._df = pd.DataFrame(columns=self.required_columns())\nelse:\n columns = set(df.columns)\n missing_columns = self.required_columns() - columns\n if missing_columns:\n raise ValueError(f'Dataframe must contain required columns {list(missing_columns)}.')\n extra_columns = co... | <|body_start_0|>
if df is None:
self._df = pd.DataFrame(columns=self.required_columns())
else:
columns = set(df.columns)
missing_columns = self.required_columns() - columns
if missing_columns:
raise ValueError(f'Dataframe must contain requi... | Class storing data for an experiment. The dataframe is retrieved via the `df` property. The data can be stored to an external store for future use by attaching it to an experiment using `experiment.attach_data()` (this requires a description to be set.) Attributes: df: DataFrame with underlying data, and required colum... | Data | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Data:
"""Class storing data for an experiment. The dataframe is retrieved via the `df` property. The data can be stored to an external store for future use by attaching it to an experiment using `experiment.attach_data()` (this requires a description to be set.) Attributes: df: DataFrame with und... | stack_v2_sparse_classes_36k_train_001083 | 10,526 | permissive | [
{
"docstring": "Init Data. Args: df: DataFrame with underlying data, and required columns. description: Human-readable description of data.",
"name": "__init__",
"signature": "def __init__(self, df: Optional[pd.DataFrame]=None, description: Optional[str]=None) -> None"
},
{
"docstring": "Combine... | 4 | stack_v2_sparse_classes_30k_train_005948 | Implement the Python class `Data` described below.
Class description:
Class storing data for an experiment. The dataframe is retrieved via the `df` property. The data can be stored to an external store for future use by attaching it to an experiment using `experiment.attach_data()` (this requires a description to be s... | Implement the Python class `Data` described below.
Class description:
Class storing data for an experiment. The dataframe is retrieved via the `df` property. The data can be stored to an external store for future use by attaching it to an experiment using `experiment.attach_data()` (this requires a description to be s... | 850b6975b7c7f9960ad5461e71d0304b2670232a | <|skeleton|>
class Data:
"""Class storing data for an experiment. The dataframe is retrieved via the `df` property. The data can be stored to an external store for future use by attaching it to an experiment using `experiment.attach_data()` (this requires a description to be set.) Attributes: df: DataFrame with und... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Data:
"""Class storing data for an experiment. The dataframe is retrieved via the `df` property. The data can be stored to an external store for future use by attaching it to an experiment using `experiment.attach_data()` (this requires a description to be set.) Attributes: df: DataFrame with underlying data,... | the_stack_v2_python_sparse | ax/core/data.py | liusulin/Ax | train | 1 |
b79266990d0c502ca390e30b53bdc5461a69c0cf | [
"self.config_entry = config_entry\nself.options = config_entry.options\nself.host = config_entry.data[CONF_HOST]\nself.key = config_entry.data[CONF_CLIENT_SECRET]",
"errors = {}\nif user_input is not None:\n options_input = {CONF_SOURCES: user_input[CONF_SOURCES]}\n return self.async_create_entry(title='', ... | <|body_start_0|>
self.config_entry = config_entry
self.options = config_entry.options
self.host = config_entry.data[CONF_HOST]
self.key = config_entry.data[CONF_CLIENT_SECRET]
<|end_body_0|>
<|body_start_1|>
errors = {}
if user_input is not None:
options_inpu... | Handle options. | OptionsFlowHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptionsFlowHandler:
"""Handle options."""
def __init__(self, config_entry: ConfigEntry) -> None:
"""Initialize options flow."""
<|body_0|>
async def async_step_init(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Manage the options."""
<|b... | stack_v2_sparse_classes_36k_train_001084 | 7,262 | permissive | [
{
"docstring": "Initialize options flow.",
"name": "__init__",
"signature": "def __init__(self, config_entry: ConfigEntry) -> None"
},
{
"docstring": "Manage the options.",
"name": "async_step_init",
"signature": "async def async_step_init(self, user_input: dict[str, Any] | None=None) ->... | 2 | stack_v2_sparse_classes_30k_train_009928 | Implement the Python class `OptionsFlowHandler` described below.
Class description:
Handle options.
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry) -> None: Initialize options flow.
- async def async_step_init(self, user_input: dict[str, Any] | None=None) -> FlowResult: Manage the op... | Implement the Python class `OptionsFlowHandler` described below.
Class description:
Handle options.
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry) -> None: Initialize options flow.
- async def async_step_init(self, user_input: dict[str, Any] | None=None) -> FlowResult: Manage the op... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class OptionsFlowHandler:
"""Handle options."""
def __init__(self, config_entry: ConfigEntry) -> None:
"""Initialize options flow."""
<|body_0|>
async def async_step_init(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Manage the options."""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OptionsFlowHandler:
"""Handle options."""
def __init__(self, config_entry: ConfigEntry) -> None:
"""Initialize options flow."""
self.config_entry = config_entry
self.options = config_entry.options
self.host = config_entry.data[CONF_HOST]
self.key = config_entry.dat... | the_stack_v2_python_sparse | homeassistant/components/webostv/config_flow.py | home-assistant/core | train | 35,501 |
3983fdd2c2f6ae410b60eb3d2db28d6f9ba2859a | [
"super(Exclusive, self).__init__()\nexclusivespec = cfnlint.helpers.load_resource(AdditionalSpecs, 'Exclusive.json')\nself.resource_types_specs = exclusivespec['ResourceTypes']\nself.property_types_specs = exclusivespec['PropertyTypes']\nfor resource_type_spec in self.resource_types_specs:\n self.resource_proper... | <|body_start_0|>
super(Exclusive, self).__init__()
exclusivespec = cfnlint.helpers.load_resource(AdditionalSpecs, 'Exclusive.json')
self.resource_types_specs = exclusivespec['ResourceTypes']
self.property_types_specs = exclusivespec['PropertyTypes']
for resource_type_spec in self... | Check Properties Resource Configuration | Exclusive | [
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exclusive:
"""Check Properties Resource Configuration"""
def __init__(self):
"""Init"""
<|body_0|>
def check(self, properties, exclusions, path, cfn):
"""Check itself"""
<|body_1|>
def match_resource_sub_properties(self, properties, property_type, pa... | stack_v2_sparse_classes_36k_train_001085 | 3,288 | permissive | [
{
"docstring": "Init",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Check itself",
"name": "check",
"signature": "def check(self, properties, exclusions, path, cfn)"
},
{
"docstring": "Match for sub properties",
"name": "match_resource_sub_properti... | 4 | stack_v2_sparse_classes_30k_train_014508 | Implement the Python class `Exclusive` described below.
Class description:
Check Properties Resource Configuration
Method signatures and docstrings:
- def __init__(self): Init
- def check(self, properties, exclusions, path, cfn): Check itself
- def match_resource_sub_properties(self, properties, property_type, path, ... | Implement the Python class `Exclusive` described below.
Class description:
Check Properties Resource Configuration
Method signatures and docstrings:
- def __init__(self): Init
- def check(self, properties, exclusions, path, cfn): Check itself
- def match_resource_sub_properties(self, properties, property_type, path, ... | 5176573c2f4cb7313998b4bc0bcb0716b58ea380 | <|skeleton|>
class Exclusive:
"""Check Properties Resource Configuration"""
def __init__(self):
"""Init"""
<|body_0|>
def check(self, properties, exclusions, path, cfn):
"""Check itself"""
<|body_1|>
def match_resource_sub_properties(self, properties, property_type, pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Exclusive:
"""Check Properties Resource Configuration"""
def __init__(self):
"""Init"""
super(Exclusive, self).__init__()
exclusivespec = cfnlint.helpers.load_resource(AdditionalSpecs, 'Exclusive.json')
self.resource_types_specs = exclusivespec['ResourceTypes']
sel... | the_stack_v2_python_sparse | src/cfnlint/rules/resources/properties/Exclusive.py | rene84/cfn-python-lint | train | 1 |
5bc4154f720b08151cfc6b91599c80d2148c1af7 | [
"self.voltage_input = VoltageInput(analog_pin)\nself.voltage = 0.0\nself.ambient_light = self.light_extremely_dark\nself.measure_light()",
"self.voltage = self.voltage_input.voltage\nif self.voltage < self.extremely_dark_max_voltage:\n self.ambient_light = self.light_extremely_dark\nelif self.voltage < self.ve... | <|body_start_0|>
self.voltage_input = VoltageInput(analog_pin)
self.voltage = 0.0
self.ambient_light = self.light_extremely_dark
self.measure_light()
<|end_body_0|>
<|body_start_1|>
self.voltage = self.voltage_input.voltage
if self.voltage < self.extremely_dark_max_volta... | DarknessSensor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DarknessSensor:
def __init__(self, analog_pin):
"""Setting up the default values of the sensor reading"""
<|body_0|>
def measure_light(self):
"""Measuring the values of the light needed based on the voltage"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_001086 | 4,115 | no_license | [
{
"docstring": "Setting up the default values of the sensor reading",
"name": "__init__",
"signature": "def __init__(self, analog_pin)"
},
{
"docstring": "Measuring the values of the light needed based on the voltage",
"name": "measure_light",
"signature": "def measure_light(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008358 | Implement the Python class `DarknessSensor` described below.
Class description:
Implement the DarknessSensor class.
Method signatures and docstrings:
- def __init__(self, analog_pin): Setting up the default values of the sensor reading
- def measure_light(self): Measuring the values of the light needed based on the v... | Implement the Python class `DarknessSensor` described below.
Class description:
Implement the DarknessSensor class.
Method signatures and docstrings:
- def __init__(self, analog_pin): Setting up the default values of the sensor reading
- def measure_light(self): Measuring the values of the light needed based on the v... | 21bc5a9daaf33074c40f6c926effb78d6f67665f | <|skeleton|>
class DarknessSensor:
def __init__(self, analog_pin):
"""Setting up the default values of the sensor reading"""
<|body_0|>
def measure_light(self):
"""Measuring the values of the light needed based on the voltage"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DarknessSensor:
def __init__(self, analog_pin):
"""Setting up the default values of the sensor reading"""
self.voltage_input = VoltageInput(analog_pin)
self.voltage = 0.0
self.ambient_light = self.light_extremely_dark
self.measure_light()
def measure_light(self):
... | the_stack_v2_python_sparse | Group Project/Code/Clients/LightSensor/light_sensor.py | omar-mohamed/Iot-Smart-Home | train | 1 | |
06e49ad763cea5c869d7afa3cc69f4865e387308 | [
"s1 = sorted(s1)\nwindow_sz = len(s1)\nfor i in range(len(s2) - window_sz + 1):\n sub_s2 = sorted(s2[i:i + window_sz])\n if s1 == sub_s2:\n return True\nreturn False",
"counter1 = Counter(s1)\nwindow_sz = len(s1)\nfor i in range(len(s2) - window_sz + 1):\n counter2 = Counter(s2[i:i + window_sz])\n... | <|body_start_0|>
s1 = sorted(s1)
window_sz = len(s1)
for i in range(len(s2) - window_sz + 1):
sub_s2 = sorted(s2[i:i + window_sz])
if s1 == sub_s2:
return True
return False
<|end_body_0|>
<|body_start_1|>
counter1 = Counter(s1)
win... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkInclusion(self, s1: str, s2: str) -> bool:
"""Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE"""
<|body_0|>
def checkInclusion(self, s1: str, s2: str) -> bool:
"""Approach3: HashTable, Time: O(l1+(l2-l1)*l1), Space: O(1)"... | stack_v2_sparse_classes_36k_train_001087 | 2,508 | no_license | [
{
"docstring": "Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE",
"name": "checkInclusion",
"signature": "def checkInclusion(self, s1: str, s2: str) -> bool"
},
{
"docstring": "Approach3: HashTable, Time: O(l1+(l2-l1)*l1), Space: O(1)",
"name": "checkInclusion",
... | 4 | stack_v2_sparse_classes_30k_train_015091 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE
- def checkInclusion(self, s1: str, s2: str) -> boo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkInclusion(self, s1: str, s2: str) -> bool: Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE
- def checkInclusion(self, s1: str, s2: str) -> boo... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def checkInclusion(self, s1: str, s2: str) -> bool:
"""Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE"""
<|body_0|>
def checkInclusion(self, s1: str, s2: str) -> bool:
"""Approach3: HashTable, Time: O(l1+(l2-l1)*l1), Space: O(1)"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def checkInclusion(self, s1: str, s2: str) -> bool:
"""Approach2: Sort, Time: O(l1logl1 + (l2-l1)*(l1logl1+l1)), Space: O(1), TLE"""
s1 = sorted(s1)
window_sz = len(s1)
for i in range(len(s2) - window_sz + 1):
sub_s2 = sorted(s2[i:i + window_sz])
... | the_stack_v2_python_sparse | python/567-Permutation in String.py | cwza/leetcode | train | 0 | |
4c35d409c8c2b8fee7ae31262762868e030894be | [
"def construct_serialization(cur):\n if cur is None:\n return 'N'\n else:\n return str(cur.val) + ',' + construct_serialization(cur.left) + ',' + construct_serialization(cur.right)\nreturn construct_serialization(root)",
"data = data.split(',')\nif len(data) == 0 or data[0] == 'N':\n return... | <|body_start_0|>
def construct_serialization(cur):
if cur is None:
return 'N'
else:
return str(cur.val) + ',' + construct_serialization(cur.left) + ',' + construct_serialization(cur.right)
return construct_serialization(root)
<|end_body_0|>
<|body... | 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_36k_train_001088 | 1,557 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 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:... | 3bfee704adb1d94efc8e531b732cf06c4f8aef0f | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def construct_serialization(cur):
if cur is None:
return 'N'
else:
return str(cur.val) + ',' + construct_serialization(cur.left) +... | the_stack_v2_python_sparse | serializeanddeserialize.py | zopepy/leetcode | train | 0 | |
9c1d1f110049ce7c1b4336241e75e541e33dd5f3 | [
"assert isinstance(nameRef, str), 'Invalid reference name %s' % nameRef\nassert isinstance(invoker, Invoker), 'Invalid invoker %s' % invoker\nassert isinstance(invoker.node, Node), 'Invalid invoker node %s' % invoker.node\nassert isinstance(invoker.doEncodePath, IDo), 'Invalid path encode %s' % invoker.doEncodePath... | <|body_start_0|>
assert isinstance(nameRef, str), 'Invalid reference name %s' % nameRef
assert isinstance(invoker, Invoker), 'Invalid invoker %s' % invoker
assert isinstance(invoker.node, Node), 'Invalid invoker node %s' % invoker.node
assert isinstance(invoker.doEncodePath, IDo), 'Inval... | Implementation for a @see: ISpecifier for attributes paths. | AttributesPath | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttributesPath:
"""Implementation for a @see: ISpecifier for attributes paths."""
def __init__(self, nameRef, invoker):
"""Construct the paths attributes."""
<|body_0|>
def populate(self, obj, specifications, support):
"""@see: ISpecifier.populate"""
<|bo... | stack_v2_sparse_classes_36k_train_001089 | 5,781 | no_license | [
{
"docstring": "Construct the paths attributes.",
"name": "__init__",
"signature": "def __init__(self, nameRef, invoker)"
},
{
"docstring": "@see: ISpecifier.populate",
"name": "populate",
"signature": "def populate(self, obj, specifications, support)"
}
] | 2 | null | Implement the Python class `AttributesPath` described below.
Class description:
Implementation for a @see: ISpecifier for attributes paths.
Method signatures and docstrings:
- def __init__(self, nameRef, invoker): Construct the paths attributes.
- def populate(self, obj, specifications, support): @see: ISpecifier.pop... | Implement the Python class `AttributesPath` described below.
Class description:
Implementation for a @see: ISpecifier for attributes paths.
Method signatures and docstrings:
- def __init__(self, nameRef, invoker): Construct the paths attributes.
- def populate(self, obj, specifications, support): @see: ISpecifier.pop... | e0b3466b34d31548996d57be4a9dac134d904380 | <|skeleton|>
class AttributesPath:
"""Implementation for a @see: ISpecifier for attributes paths."""
def __init__(self, nameRef, invoker):
"""Construct the paths attributes."""
<|body_0|>
def populate(self, obj, specifications, support):
"""@see: ISpecifier.populate"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttributesPath:
"""Implementation for a @see: ISpecifier for attributes paths."""
def __init__(self, nameRef, invoker):
"""Construct the paths attributes."""
assert isinstance(nameRef, str), 'Invalid reference name %s' % nameRef
assert isinstance(invoker, Invoker), 'Invalid invoke... | the_stack_v2_python_sparse | components/ally-core-http/ally/core/http/impl/processor/encoder/property_of_model_path.py | cristidomsa/Ally-Py | train | 0 |
9e616c560c96d1e76ad95dac8fde75f25843780d | [
"BaseQuantityTemplate.__init__(self, token, 'gs')\nself.group = None\nself.groupProb = 0.0\nself.outcome = None\nself.sentence = token.sentence\nself.outcomeNumber = None",
"if self.group == None:\n return -1\nif self.shouldBeAssociated(self.group):\n return 1\nreturn 0",
"s = str(self.value) + ', GROUP =... | <|body_start_0|>
BaseQuantityTemplate.__init__(self, token, 'gs')
self.group = None
self.groupProb = 0.0
self.outcome = None
self.sentence = token.sentence
self.outcomeNumber = None
<|end_body_0|>
<|body_start_1|>
if self.group == None:
return -1
... | manage the information relevant to a Group size template | GroupSize | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupSize:
"""manage the information relevant to a Group size template"""
def __init__(self, token):
"""Initialize a group size template given an integer token object"""
<|body_0|>
def correctAssociation(self, mType):
"""return True if quantity is correctly assoc... | stack_v2_sparse_classes_36k_train_001090 | 1,559 | no_license | [
{
"docstring": "Initialize a group size template given an integer token object",
"name": "__init__",
"signature": "def __init__(self, token)"
},
{
"docstring": "return True if quantity is correctly associated with mention of given type.",
"name": "correctAssociation",
"signature": "def c... | 3 | null | Implement the Python class `GroupSize` described below.
Class description:
manage the information relevant to a Group size template
Method signatures and docstrings:
- def __init__(self, token): Initialize a group size template given an integer token object
- def correctAssociation(self, mType): return True if quanti... | Implement the Python class `GroupSize` described below.
Class description:
manage the information relevant to a Group size template
Method signatures and docstrings:
- def __init__(self, token): Initialize a group size template given an integer token object
- def correctAssociation(self, mType): return True if quanti... | aecc4c4ac18ebc1c6cb39d54f9ed8cba5217c6f8 | <|skeleton|>
class GroupSize:
"""manage the information relevant to a Group size template"""
def __init__(self, token):
"""Initialize a group size template given an integer token object"""
<|body_0|>
def correctAssociation(self, mType):
"""return True if quantity is correctly assoc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupSize:
"""manage the information relevant to a Group size template"""
def __init__(self, token):
"""Initialize a group size template given an integer token object"""
BaseQuantityTemplate.__init__(self, token, 'gs')
self.group = None
self.groupProb = 0.0
self.ou... | the_stack_v2_python_sparse | groupsizetemplate.py | rlsummerscales/acres | train | 0 |
2f6bd914559d02cd2193922fc6d756fe3d9ae3ad | [
"requests = []\nfor node in response.xpath('//div[@class=\"bus-listing\"]'):\n l = BusinessLoader(selector=node, response=response)\n l.add_xpath('category', './preceding-sibling::h2[1]/ text()')\n l.add_xpath('data_url', './/a[contains(@href, \"CoID=\")]/ @href')\n l.add_value('data_uid', re.match(patt... | <|body_start_0|>
requests = []
for node in response.xpath('//div[@class="bus-listing"]'):
l = BusinessLoader(selector=node, response=response)
l.add_xpath('category', './preceding-sibling::h2[1]/ text()')
l.add_xpath('data_url', './/a[contains(@href, "CoID=")]/ @href'... | Spider for Columbus, OH Chamber of Commerce business index | XeniaChamberSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XeniaChamberSpider:
"""Spider for Columbus, OH Chamber of Commerce business index"""
def parse(self, response):
"""This will extract links to all categorized lists of businesses"""
<|body_0|>
def extract(self, response):
"""This extracts part of the information a... | stack_v2_sparse_classes_36k_train_001091 | 2,720 | no_license | [
{
"docstring": "This will extract links to all categorized lists of businesses",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "This extracts part of the information and then calls a child page to extract the rest of the business info",
"name": "extract",
"s... | 2 | stack_v2_sparse_classes_30k_train_005449 | Implement the Python class `XeniaChamberSpider` described below.
Class description:
Spider for Columbus, OH Chamber of Commerce business index
Method signatures and docstrings:
- def parse(self, response): This will extract links to all categorized lists of businesses
- def extract(self, response): This extracts part... | Implement the Python class `XeniaChamberSpider` described below.
Class description:
Spider for Columbus, OH Chamber of Commerce business index
Method signatures and docstrings:
- def parse(self, response): This will extract links to all categorized lists of businesses
- def extract(self, response): This extracts part... | e36d842228a6ce4e3029b42d289eaa000e92efb5 | <|skeleton|>
class XeniaChamberSpider:
"""Spider for Columbus, OH Chamber of Commerce business index"""
def parse(self, response):
"""This will extract links to all categorized lists of businesses"""
<|body_0|>
def extract(self, response):
"""This extracts part of the information a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XeniaChamberSpider:
"""Spider for Columbus, OH Chamber of Commerce business index"""
def parse(self, response):
"""This will extract links to all categorized lists of businesses"""
requests = []
for node in response.xpath('//div[@class="bus-listing"]'):
l = BusinessLoa... | the_stack_v2_python_sparse | spiders/xenia_chamber_spider.py | dwcaraway/govly-scraper | train | 1 |
454a9a1581b2e61a24c3a05f0513286b2bb7cf94 | [
"app = App.get_running_app()\n\nasync def load():\n \"\"\"Load networks from settings and filter out not trusted.\"\"\"\n networks = set()\n for row in await app.ioc.facade.api.settings.networks():\n if row[1]:\n networks.add(uuid.UUID(row[0]))\n return networks\ntry:\n network_id =... | <|body_start_0|>
app = App.get_running_app()
async def load():
"""Load networks from settings and filter out not trusted."""
networks = set()
for row in await app.ioc.facade.api.settings.networks():
if row[1]:
networks.add(uuid.UUI... | Networks | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Networks:
def list_networks(self):
"""Load all blocked contacts."""
<|body_0|>
def __load_rv(coro, content, tab=None, selectable=False, preselected=set()):
"""Update the ScrollView with new and changed data."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_001092 | 4,926 | permissive | [
{
"docstring": "Load all blocked contacts.",
"name": "list_networks",
"signature": "def list_networks(self)"
},
{
"docstring": "Update the ScrollView with new and changed data.",
"name": "__load_rv",
"signature": "def __load_rv(coro, content, tab=None, selectable=False, preselected=set()... | 2 | stack_v2_sparse_classes_30k_train_004137 | Implement the Python class `Networks` described below.
Class description:
Implement the Networks class.
Method signatures and docstrings:
- def list_networks(self): Load all blocked contacts.
- def __load_rv(coro, content, tab=None, selectable=False, preselected=set()): Update the ScrollView with new and changed data... | Implement the Python class `Networks` described below.
Class description:
Implement the Networks class.
Method signatures and docstrings:
- def list_networks(self): Load all blocked contacts.
- def __load_rv(coro, content, tab=None, selectable=False, preselected=set()): Update the ScrollView with new and changed data... | 7d8052cdf87d44159a56b1dbc2cbaa92283ec2ac | <|skeleton|>
class Networks:
def list_networks(self):
"""Load all blocked contacts."""
<|body_0|>
def __load_rv(coro, content, tab=None, selectable=False, preselected=set()):
"""Update the ScrollView with new and changed data."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Networks:
def list_networks(self):
"""Load all blocked contacts."""
app = App.get_running_app()
async def load():
"""Load networks from settings and filter out not trusted."""
networks = set()
for row in await app.ioc.facade.api.settings.networks():... | the_stack_v2_python_sparse | lib/logo/baseclass/networks.py | kristoffer-paulsson/logo | train | 0 | |
b8af26faeb4444367f05b43d3ffe9fba193942e1 | [
"if PDT_OT_ModalDrawOperator._handle is None:\n PDT_OT_ModalDrawOperator._handle = SpaceView3D.draw_handler_add(draw_callback_3d, (self, context), 'WINDOW', 'POST_VIEW')\n context.window_manager.pdt_run_opengl = True",
"if PDT_OT_ModalDrawOperator._handle is not None:\n SpaceView3D.draw_handler_remove(PD... | <|body_start_0|>
if PDT_OT_ModalDrawOperator._handle is None:
PDT_OT_ModalDrawOperator._handle = SpaceView3D.draw_handler_add(draw_callback_3d, (self, context), 'WINDOW', 'POST_VIEW')
context.window_manager.pdt_run_opengl = True
<|end_body_0|>
<|body_start_1|>
if PDT_OT_ModalDra... | Show/Hide Pivot Point | PDT_OT_ModalDrawOperator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PDT_OT_ModalDrawOperator:
"""Show/Hide Pivot Point"""
def handle_add(self, context):
"""Draw Pivot Point Graphic if not displayed. Note: Draws 7 element Pivot Point Graphic Args: context: Blender bpy.context instance. Returns: Nothing."""
<|body_0|>
def handle_remove(sel... | stack_v2_sparse_classes_36k_train_001093 | 13,734 | permissive | [
{
"docstring": "Draw Pivot Point Graphic if not displayed. Note: Draws 7 element Pivot Point Graphic Args: context: Blender bpy.context instance. Returns: Nothing.",
"name": "handle_add",
"signature": "def handle_add(self, context)"
},
{
"docstring": "Remove Pivot Point Graphic if displayed. Not... | 3 | stack_v2_sparse_classes_30k_train_016710 | Implement the Python class `PDT_OT_ModalDrawOperator` described below.
Class description:
Show/Hide Pivot Point
Method signatures and docstrings:
- def handle_add(self, context): Draw Pivot Point Graphic if not displayed. Note: Draws 7 element Pivot Point Graphic Args: context: Blender bpy.context instance. Returns: ... | Implement the Python class `PDT_OT_ModalDrawOperator` described below.
Class description:
Show/Hide Pivot Point
Method signatures and docstrings:
- def handle_add(self, context): Draw Pivot Point Graphic if not displayed. Note: Draws 7 element Pivot Point Graphic Args: context: Blender bpy.context instance. Returns: ... | 4d5c304878c1e0018d97c1b07bcaa3981632265a | <|skeleton|>
class PDT_OT_ModalDrawOperator:
"""Show/Hide Pivot Point"""
def handle_add(self, context):
"""Draw Pivot Point Graphic if not displayed. Note: Draws 7 element Pivot Point Graphic Args: context: Blender bpy.context instance. Returns: Nothing."""
<|body_0|>
def handle_remove(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PDT_OT_ModalDrawOperator:
"""Show/Hide Pivot Point"""
def handle_add(self, context):
"""Draw Pivot Point Graphic if not displayed. Note: Draws 7 element Pivot Point Graphic Args: context: Blender bpy.context instance. Returns: Nothing."""
if PDT_OT_ModalDrawOperator._handle is None:
... | the_stack_v2_python_sparse | src/bpy/3.6/scripts/addons/precision_drawing_tools/pdt_pivot_point.py | RnoB/3DVisualSwarm | train | 0 |
098ba368bab29cad3443e646c4ad16ff24325457 | [
"limit = int(self.request.get('limit', 100))\naccepted_filters = ('executable', 'first_arg', 'platform', 'domain')\nreports = ProfileReport.all()\nmin_duration = self.request.get('min_duration')\nmax_duration = self.request.get('max_duration')\nincludes_not = False\nfor key in accepted_filters:\n value = self.re... | <|body_start_0|>
limit = int(self.request.get('limit', 100))
accepted_filters = ('executable', 'first_arg', 'platform', 'domain')
reports = ProfileReport.all()
min_duration = self.request.get('min_duration')
max_duration = self.request.get('max_duration')
includes_not = F... | Profiling | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Profiling:
def get(self):
"""Returns json formated data according to the provided filters."""
<|body_0|>
def post(self):
"""Adds a new profile report. Anyone can add a report."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
limit = int(self.request.... | stack_v2_sparse_classes_36k_train_001094 | 4,040 | permissive | [
{
"docstring": "Returns json formated data according to the provided filters.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Adds a new profile report. Anyone can add a report.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `Profiling` described below.
Class description:
Implement the Profiling class.
Method signatures and docstrings:
- def get(self): Returns json formated data according to the provided filters.
- def post(self): Adds a new profile report. Anyone can add a report. | Implement the Python class `Profiling` described below.
Class description:
Implement the Profiling class.
Method signatures and docstrings:
- def get(self): Returns json formated data according to the provided filters.
- def post(self): Adds a new profile report. Anyone can add a report.
<|skeleton|>
class Profiling... | b5d4783f99461438ca9e6a477535617fadab6ba3 | <|skeleton|>
class Profiling:
def get(self):
"""Returns json formated data according to the provided filters."""
<|body_0|>
def post(self):
"""Adds a new profile report. Anyone can add a report."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Profiling:
def get(self):
"""Returns json formated data according to the provided filters."""
limit = int(self.request.get('limit', 100))
accepted_filters = ('executable', 'first_arg', 'platform', 'domain')
reports = ProfileReport.all()
min_duration = self.request.get('... | the_stack_v2_python_sparse | appengine/chromium_status/appengine_module/chromium_status/profiling.py | xinghun61/infra | train | 2 | |
e87e76f7ef72eca5f9d5cce01c4ad563a654479d | [
"posts = Post.objects.all()\nposts = post_filter(request, posts)\nif type(posts) == Response:\n return posts\nreturn Response(PostSerializer(posts, many=True).data)",
"serializer = PostSerializerCreate(data=request.data, context={'request': request})\nif serializer.is_valid():\n serializer.save()\n retur... | <|body_start_0|>
posts = Post.objects.all()
posts = post_filter(request, posts)
if type(posts) == Response:
return posts
return Response(PostSerializer(posts, many=True).data)
<|end_body_0|>
<|body_start_1|>
serializer = PostSerializerCreate(data=request.data, contex... | PostView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostView:
def get(request):
"""List posts"""
<|body_0|>
def post(request):
"""Create post"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
posts = Post.objects.all()
posts = post_filter(request, posts)
if type(posts) == Response:
... | stack_v2_sparse_classes_36k_train_001095 | 2,180 | permissive | [
{
"docstring": "List posts",
"name": "get",
"signature": "def get(request)"
},
{
"docstring": "Create post",
"name": "post",
"signature": "def post(request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000441 | Implement the Python class `PostView` described below.
Class description:
Implement the PostView class.
Method signatures and docstrings:
- def get(request): List posts
- def post(request): Create post | Implement the Python class `PostView` described below.
Class description:
Implement the PostView class.
Method signatures and docstrings:
- def get(request): List posts
- def post(request): Create post
<|skeleton|>
class PostView:
def get(request):
"""List posts"""
<|body_0|>
def post(reque... | b93fa2fea8d45df9f19c3c58037e59dad4981921 | <|skeleton|>
class PostView:
def get(request):
"""List posts"""
<|body_0|>
def post(request):
"""Create post"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PostView:
def get(request):
"""List posts"""
posts = Post.objects.all()
posts = post_filter(request, posts)
if type(posts) == Response:
return posts
return Response(PostSerializer(posts, many=True).data)
def post(request):
"""Create post"""
... | the_stack_v2_python_sparse | v1/posts/views/post.py | lawiz22/PLOUC-Backend-master | train | 0 | |
4517e517e873ae242677697f5cda761a8c2be5fb | [
"self.sent_freq_dict = defaultdict(int)\nself.curr_sent = ''\nfor i in range(len(sentences)):\n self.sent_freq_dict[sentences[i]] = times[i]",
"if c == '#':\n self.sent_freq_dict[self.curr_sent] += 1\n self.curr_sent = ''\nelse:\n self.curr_sent += c\n L = len(self.curr_sent)\n temp_lst = []\n ... | <|body_start_0|>
self.sent_freq_dict = defaultdict(int)
self.curr_sent = ''
for i in range(len(sentences)):
self.sent_freq_dict[sentences[i]] = times[i]
<|end_body_0|>
<|body_start_1|>
if c == '#':
self.sent_freq_dict[self.curr_sent] += 1
self.curr_se... | AutocompleteSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.sent_freq_dict = ... | stack_v2_sparse_classes_36k_train_001096 | 1,296 | no_license | [
{
"docstring": ":type sentences: List[str] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, sentences, times)"
},
{
"docstring": ":type c: str :rtype: List[str]",
"name": "input",
"signature": "def input(self, c)"
}
] | 2 | null | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str] | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str]
<|skeleton|>
cla... | a9b2de06306f3929a82ef4e6613c972e9a2c2200 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
self.sent_freq_dict = defaultdict(int)
self.curr_sent = ''
for i in range(len(sentences)):
self.sent_freq_dict[sentences[i]] = times[i]
def input(s... | the_stack_v2_python_sparse | Practice_3/Design_Search_Autocomplete_System.py | anantvir/Leetcode-Problems | train | 1 | |
73db89ba05ccf582a567cb06a8a8fbee1183aad6 | [
"response_message = ResponseMessage()\nresponse_message.callback_url = request_message.callback_url\nresponse_message.job_id = request_message.job_id\nresponse_message.username = request_message.username\nreturn response_message",
"message = yaml.load(message_yaml)\nassert isinstance(message, ResponseMessage)\nre... | <|body_start_0|>
response_message = ResponseMessage()
response_message.callback_url = request_message.callback_url
response_message.job_id = request_message.job_id
response_message.username = request_message.username
return response_message
<|end_body_0|>
<|body_start_1|>
... | Class for response messages. | ResponseMessage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResponseMessage:
"""Class for response messages."""
def from_request_message(request_message):
"""Builds a response object from a request object."""
<|body_0|>
def load(message_yaml):
"""Loads the response message from yaml asserting it deserialized properly."""
... | stack_v2_sparse_classes_36k_train_001097 | 4,974 | no_license | [
{
"docstring": "Builds a response object from a request object.",
"name": "from_request_message",
"signature": "def from_request_message(request_message)"
},
{
"docstring": "Loads the response message from yaml asserting it deserialized properly.",
"name": "load",
"signature": "def load(... | 2 | stack_v2_sparse_classes_30k_train_018701 | Implement the Python class `ResponseMessage` described below.
Class description:
Class for response messages.
Method signatures and docstrings:
- def from_request_message(request_message): Builds a response object from a request object.
- def load(message_yaml): Loads the response message from yaml asserting it deser... | Implement the Python class `ResponseMessage` described below.
Class description:
Class for response messages.
Method signatures and docstrings:
- def from_request_message(request_message): Builds a response object from a request object.
- def load(message_yaml): Loads the response message from yaml asserting it deser... | 0051a4b09a0c5d5f0de8bd923b928d75516d3186 | <|skeleton|>
class ResponseMessage:
"""Class for response messages."""
def from_request_message(request_message):
"""Builds a response object from a request object."""
<|body_0|>
def load(message_yaml):
"""Loads the response message from yaml asserting it deserialized properly."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResponseMessage:
"""Class for response messages."""
def from_request_message(request_message):
"""Builds a response object from a request object."""
response_message = ResponseMessage()
response_message.callback_url = request_message.callback_url
response_message.job_id = ... | the_stack_v2_python_sparse | daedalus/queueing/messages.py | Millz0r/daedalus | train | 0 |
d68e3a533f938063ed96f3d578dd16a22cab9d04 | [
"result = 0\nif len(s) == 1:\n return 1\nfor i in range(len(s)):\n print(s[i])\n hashset = []\n length = 0\n for j in range(i, len(s)):\n if s[j] not in hashset:\n length += 1\n hashset.append(s[j])\n print(hashset)\n else:\n break\n if... | <|body_start_0|>
result = 0
if len(s) == 1:
return 1
for i in range(len(s)):
print(s[i])
hashset = []
length = 0
for j in range(i, len(s)):
if s[j] not in hashset:
length += 1
hash... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring_slow(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = 0
if len(s) == 1:
... | stack_v2_sparse_classes_36k_train_001098 | 2,188 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "lengthOfLongestSubstring_slow",
"signature": "def lengthOfLongestSubstring_slow(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "lengthOfLongestSubstring",
"signature": "def lengthOfLongestSubstring(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring_slow(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring_slow(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def leng... | 4d7e675c795c841f99ca95b8b60c4995bcb632fb | <|skeleton|>
class Solution:
def lengthOfLongestSubstring_slow(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLongestSubstring_slow(self, s):
""":type s: str :rtype: int"""
result = 0
if len(s) == 1:
return 1
for i in range(len(s)):
print(s[i])
hashset = []
length = 0
for j in range(i, len(s)):
... | the_stack_v2_python_sparse | lengthOfLongestSubstring.py | stephenchenxj/myLeetCode | train | 0 | |
9cb433bc086e2861ea778fdee2a14ea07c547f16 | [
"payoff_fn = payoff_utils.make_basket_put_payoff([1.1, 1.2], dtype=dtype)\nsample_paths = tf.convert_to_tensor(_SAMPLES, dtype=dtype)\nsample_paths = tf.expand_dims(sample_paths, -1)\npayoff = payoff_fn(sample_paths, 3)\nexpected_payoff = [[0, 0], [0, 0], [0.07, 0.17], [0.18, 0.28], [0, 0], [0.2, 0.3], [0.09, 0.19]... | <|body_start_0|>
payoff_fn = payoff_utils.make_basket_put_payoff([1.1, 1.2], dtype=dtype)
sample_paths = tf.convert_to_tensor(_SAMPLES, dtype=dtype)
sample_paths = tf.expand_dims(sample_paths, -1)
payoff = payoff_fn(sample_paths, 3)
expected_payoff = [[0, 0], [0, 0], [0.07, 0.17]... | PayoffTest | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PayoffTest:
def test_put_payoff_function(self, dtype):
"""Tests the put payoff function for a batch of strikes."""
<|body_0|>
def test_put_payoff_function_batch(self, dtype):
"""Tests the put payoff function for a batch of samples."""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_001099 | 3,627 | permissive | [
{
"docstring": "Tests the put payoff function for a batch of strikes.",
"name": "test_put_payoff_function",
"signature": "def test_put_payoff_function(self, dtype)"
},
{
"docstring": "Tests the put payoff function for a batch of samples.",
"name": "test_put_payoff_function_batch",
"signa... | 2 | null | Implement the Python class `PayoffTest` described below.
Class description:
Implement the PayoffTest class.
Method signatures and docstrings:
- def test_put_payoff_function(self, dtype): Tests the put payoff function for a batch of strikes.
- def test_put_payoff_function_batch(self, dtype): Tests the put payoff funct... | Implement the Python class `PayoffTest` described below.
Class description:
Implement the PayoffTest class.
Method signatures and docstrings:
- def test_put_payoff_function(self, dtype): Tests the put payoff function for a batch of strikes.
- def test_put_payoff_function_batch(self, dtype): Tests the put payoff funct... | 0d3a2193c0f2d320b65e602cf01d7a617da484df | <|skeleton|>
class PayoffTest:
def test_put_payoff_function(self, dtype):
"""Tests the put payoff function for a batch of strikes."""
<|body_0|>
def test_put_payoff_function_batch(self, dtype):
"""Tests the put payoff function for a batch of samples."""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PayoffTest:
def test_put_payoff_function(self, dtype):
"""Tests the put payoff function for a batch of strikes."""
payoff_fn = payoff_utils.make_basket_put_payoff([1.1, 1.2], dtype=dtype)
sample_paths = tf.convert_to_tensor(_SAMPLES, dtype=dtype)
sample_paths = tf.expand_dims(s... | the_stack_v2_python_sparse | tf_quant_finance/experimental/lsm_algorithm/payoff_test.py | google/tf-quant-finance | train | 4,165 |
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