blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
edf3f30c07f10dba8aff46dbff9ccfe43faef8d1 | [
"self.users = [UserFactory.create() for i in range(10)]\nself.images = [ImageFactory.build() for i in range(10)]\nself.albums = [AlbumFactory.build() for i in range(10)]\nfor i in range(10):\n curr_image = self.images[i]\n curr_album = self.albums[i]\n curr_image.author = self.users[i]\n curr_album.owne... | <|body_start_0|>
self.users = [UserFactory.create() for i in range(10)]
self.images = [ImageFactory.build() for i in range(10)]
self.albums = [AlbumFactory.build() for i in range(10)]
for i in range(10):
curr_image = self.images[i]
curr_album = self.albums[i]
... | The test runner for the Photo model. | ImageTestCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageTestCase:
"""The test runner for the Photo model."""
def setUp(self):
"""The appropriate setup for the appropriate test."""
<|body_0|>
def test_photo_can_be_assigned_to_user(self):
"""Test that a photo and user can be connected."""
<|body_1|>
de... | stack_v2_sparse_classes_75kplus_train_000000 | 7,924 | permissive | [
{
"docstring": "The appropriate setup for the appropriate test.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test that a photo and user can be connected.",
"name": "test_photo_can_be_assigned_to_user",
"signature": "def test_photo_can_be_assigned_to_user(self)"
... | 5 | stack_v2_sparse_classes_30k_train_016432 | Implement the Python class `ImageTestCase` described below.
Class description:
The test runner for the Photo model.
Method signatures and docstrings:
- def setUp(self): The appropriate setup for the appropriate test.
- def test_photo_can_be_assigned_to_user(self): Test that a photo and user can be connected.
- def te... | Implement the Python class `ImageTestCase` described below.
Class description:
The test runner for the Photo model.
Method signatures and docstrings:
- def setUp(self): The appropriate setup for the appropriate test.
- def test_photo_can_be_assigned_to_user(self): Test that a photo and user can be connected.
- def te... | 9b33bdde34b325af3d54dcfbb9ff952ca90a26c1 | <|skeleton|>
class ImageTestCase:
"""The test runner for the Photo model."""
def setUp(self):
"""The appropriate setup for the appropriate test."""
<|body_0|>
def test_photo_can_be_assigned_to_user(self):
"""Test that a photo and user can be connected."""
<|body_1|>
de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImageTestCase:
"""The test runner for the Photo model."""
def setUp(self):
"""The appropriate setup for the appropriate test."""
self.users = [UserFactory.create() for i in range(10)]
self.images = [ImageFactory.build() for i in range(10)]
self.albums = [AlbumFactory.build... | the_stack_v2_python_sparse | imagersite/imager_images/tests.py | CCallahanIV/django-imager | train | 0 |
ab87269cb25a751db5b14e4c1fe2914a25778318 | [
"self._clip_obs = clip_obs\nself._obs_shape = mdp_info.observation_space.shape\nself._obs_runstand = RunningStandardization(shape=self._obs_shape, alpha=alpha)\nself._add_save_attr(_clip_obs='primitive', _obs_shape='primitive', _obs_runstand='mushroom')",
"assert obs.shape == self._obs_shape, 'Values given to run... | <|body_start_0|>
self._clip_obs = clip_obs
self._obs_shape = mdp_info.observation_space.shape
self._obs_runstand = RunningStandardization(shape=self._obs_shape, alpha=alpha)
self._add_save_attr(_clip_obs='primitive', _obs_shape='primitive', _obs_runstand='mushroom')
<|end_body_0|>
<|bod... | Preprocess observations from the environment using a running standardization. | StandardizationPreprocessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardizationPreprocessor:
"""Preprocess observations from the environment using a running standardization."""
def __init__(self, mdp_info, clip_obs=10.0, alpha=1e-32):
"""Constructor. Args: mdp_info (MDPInfo): information of the MDP; clip_obs (float, 10.): values to clip the norma... | stack_v2_sparse_classes_75kplus_train_000001 | 4,016 | permissive | [
{
"docstring": "Constructor. Args: mdp_info (MDPInfo): information of the MDP; clip_obs (float, 10.): values to clip the normalized observations; alpha (float, 1e-32): moving average catchup parameter for the normalization.",
"name": "__init__",
"signature": "def __init__(self, mdp_info, clip_obs=10.0, ... | 2 | stack_v2_sparse_classes_30k_train_018967 | Implement the Python class `StandardizationPreprocessor` described below.
Class description:
Preprocess observations from the environment using a running standardization.
Method signatures and docstrings:
- def __init__(self, mdp_info, clip_obs=10.0, alpha=1e-32): Constructor. Args: mdp_info (MDPInfo): information of... | Implement the Python class `StandardizationPreprocessor` described below.
Class description:
Preprocess observations from the environment using a running standardization.
Method signatures and docstrings:
- def __init__(self, mdp_info, clip_obs=10.0, alpha=1e-32): Constructor. Args: mdp_info (MDPInfo): information of... | 2decae31459a3481130afe1263bc0a5ba7954a99 | <|skeleton|>
class StandardizationPreprocessor:
"""Preprocess observations from the environment using a running standardization."""
def __init__(self, mdp_info, clip_obs=10.0, alpha=1e-32):
"""Constructor. Args: mdp_info (MDPInfo): information of the MDP; clip_obs (float, 10.): values to clip the norma... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StandardizationPreprocessor:
"""Preprocess observations from the environment using a running standardization."""
def __init__(self, mdp_info, clip_obs=10.0, alpha=1e-32):
"""Constructor. Args: mdp_info (MDPInfo): information of the MDP; clip_obs (float, 10.): values to clip the normalized observa... | the_stack_v2_python_sparse | mushroom_rl/utils/preprocessors.py | MushroomRL/mushroom-rl | train | 477 |
be145d69da147d8c0a117bd4ee974866ea1e8ea3 | [
"N = len(nums)\nW = (sum(nums) + S) // 2\nif (sum(nums) + S) % 2 == 1:\n return 0\nif sum(nums) < S or sum(nums) < -S:\n return 0\ndp = [0] * (W + 1)\ndp[0] = 1\nfor i in range(1, N + 1):\n for j in range(W, nums[i - 1] - 1, -1):\n dp[j] = dp[j] + dp[j - nums[i - 1]]\nprint(dp)\nreturn dp[W]",
"de... | <|body_start_0|>
N = len(nums)
W = (sum(nums) + S) // 2
if (sum(nums) + S) % 2 == 1:
return 0
if sum(nums) < S or sum(nums) < -S:
return 0
dp = [0] * (W + 1)
dp[0] = 1
for i in range(1, N + 1):
for j in range(W, nums[i - 1] - 1,... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findTargetSumWays(self, nums: List[int], S: int) -> int:
"""状态转移方程：0-1背包 假设所有元素和为sum，所有添加正号的元素的和为A，所有添加负号的元素和为B， 则有sum = A + B 且 S = A - B，解方程得A = (sum + S)/2。 即题目转换成：从数组中选取一些元素使和恰好为(sum + S) / 2"""
<|body_0|>
def findTargetSumWays1(self, nums: List[int], S: in... | stack_v2_sparse_classes_75kplus_train_000002 | 3,913 | permissive | [
{
"docstring": "状态转移方程：0-1背包 假设所有元素和为sum，所有添加正号的元素的和为A，所有添加负号的元素和为B， 则有sum = A + B 且 S = A - B，解方程得A = (sum + S)/2。 即题目转换成：从数组中选取一些元素使和恰好为(sum + S) / 2",
"name": "findTargetSumWays",
"signature": "def findTargetSumWays(self, nums: List[int], S: int) -> int"
},
{
"docstring": "回溯算法：二进制递归枚举",
... | 3 | stack_v2_sparse_classes_30k_train_014214 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTargetSumWays(self, nums: List[int], S: int) -> int: 状态转移方程：0-1背包 假设所有元素和为sum，所有添加正号的元素的和为A，所有添加负号的元素和为B， 则有sum = A + B 且 S = A - B，解方程得A = (sum + S)/2。 即题目转换成：从数组中选取一些元素... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTargetSumWays(self, nums: List[int], S: int) -> int: 状态转移方程：0-1背包 假设所有元素和为sum，所有添加正号的元素的和为A，所有添加负号的元素和为B， 则有sum = A + B 且 S = A - B，解方程得A = (sum + S)/2。 即题目转换成：从数组中选取一些元素... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def findTargetSumWays(self, nums: List[int], S: int) -> int:
"""状态转移方程：0-1背包 假设所有元素和为sum，所有添加正号的元素的和为A，所有添加负号的元素和为B， 则有sum = A + B 且 S = A - B，解方程得A = (sum + S)/2。 即题目转换成：从数组中选取一些元素使和恰好为(sum + S) / 2"""
<|body_0|>
def findTargetSumWays1(self, nums: List[int], S: in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findTargetSumWays(self, nums: List[int], S: int) -> int:
"""状态转移方程：0-1背包 假设所有元素和为sum，所有添加正号的元素的和为A，所有添加负号的元素和为B， 则有sum = A + B 且 S = A - B，解方程得A = (sum + S)/2。 即题目转换成：从数组中选取一些元素使和恰好为(sum + S) / 2"""
N = len(nums)
W = (sum(nums) + S) // 2
if (sum(nums) + S) % 2 == ... | the_stack_v2_python_sparse | 494-target-sum.py | yuenliou/leetcode | train | 0 | |
2ce78c7158dc1cc9446cc4ca6345778382c57f50 | [
"super().__init__(name=name)\nself.fragments_storage = CloudFiles(fragments_path)\nself.output_storage = CloudFiles(output_path)",
"print(f'aggregate skeletons with prefix of {prefix}')\nid2filenames = defaultdict(list)\nfor filename in self.fragments_storage.list_files(prefix=prefix):\n filename = os.path.bas... | <|body_start_0|>
super().__init__(name=name)
self.fragments_storage = CloudFiles(fragments_path)
self.output_storage = CloudFiles(output_path)
<|end_body_0|>
<|body_start_1|>
print(f'aggregate skeletons with prefix of {prefix}')
id2filenames = defaultdict(list)
for filen... | Merge skeleton fragments for Neuroglancer visualization. | AggregateSkeletonFragmentsOperator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AggregateSkeletonFragmentsOperator:
"""Merge skeleton fragments for Neuroglancer visualization."""
def __init__(self, fragments_path: str, output_path: str, name: str='aggregate-skeleton-fragments'):
"""Parameters ------------ fragments_path: path to store fragment files output_path:... | stack_v2_sparse_classes_75kplus_train_000003 | 2,270 | permissive | [
{
"docstring": "Parameters ------------ fragments_path: path to store fragment files output_path: save the merged skeleton file here.",
"name": "__init__",
"signature": "def __init__(self, fragments_path: str, output_path: str, name: str='aggregate-skeleton-fragments')"
},
{
"docstring": "To-do:... | 2 | stack_v2_sparse_classes_30k_train_033821 | Implement the Python class `AggregateSkeletonFragmentsOperator` described below.
Class description:
Merge skeleton fragments for Neuroglancer visualization.
Method signatures and docstrings:
- def __init__(self, fragments_path: str, output_path: str, name: str='aggregate-skeleton-fragments'): Parameters ------------ ... | Implement the Python class `AggregateSkeletonFragmentsOperator` described below.
Class description:
Merge skeleton fragments for Neuroglancer visualization.
Method signatures and docstrings:
- def __init__(self, fragments_path: str, output_path: str, name: str='aggregate-skeleton-fragments'): Parameters ------------ ... | 4b1b6cc7844f8bf453ae0ba3b618106163fa9bcf | <|skeleton|>
class AggregateSkeletonFragmentsOperator:
"""Merge skeleton fragments for Neuroglancer visualization."""
def __init__(self, fragments_path: str, output_path: str, name: str='aggregate-skeleton-fragments'):
"""Parameters ------------ fragments_path: path to store fragment files output_path:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AggregateSkeletonFragmentsOperator:
"""Merge skeleton fragments for Neuroglancer visualization."""
def __init__(self, fragments_path: str, output_path: str, name: str='aggregate-skeleton-fragments'):
"""Parameters ------------ fragments_path: path to store fragment files output_path: save the mer... | the_stack_v2_python_sparse | chunkflow/plugins/aggregate_skeleton_fragments.py | seung-lab/chunkflow | train | 47 |
811a74e29519b7b7a5811d119bd4def2468c16d9 | [
"parameters = models.CheckSkuAvailabilityParameter(skus=skus, kind=kind, type=type)\nurl = self.check_sku_availability.metadata['url']\npath_format_arguments = {'subscriptionId': self._serialize.url('self.config.subscription_id', self.config.subscription_id, 'str', min_length=1), 'location': self._serialize.url('lo... | <|body_start_0|>
parameters = models.CheckSkuAvailabilityParameter(skus=skus, kind=kind, type=type)
url = self.check_sku_availability.metadata['url']
path_format_arguments = {'subscriptionId': self._serialize.url('self.config.subscription_id', self.config.subscription_id, 'str', min_length=1), '... | CognitiveServicesManagementClientOperationsMixin | [
"LicenseRef-scancode-generic-cla",
"LGPL-2.1-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CognitiveServicesManagementClientOperationsMixin:
def check_sku_availability(self, location, skus, kind, type, custom_headers=None, raw=False, **operation_config):
"""Check available SKUs. :param location: Resource location. :type location: str :param skus: The SKU of the resource. :type... | stack_v2_sparse_classes_75kplus_train_000004 | 7,119 | permissive | [
{
"docstring": "Check available SKUs. :param location: Resource location. :type location: str :param skus: The SKU of the resource. :type skus: list[str] :param kind: The Kind of the resource. :type kind: str :param type: The Type of the resource. :type type: str :param dict custom_headers: headers that will be... | 2 | stack_v2_sparse_classes_30k_val_001355 | Implement the Python class `CognitiveServicesManagementClientOperationsMixin` described below.
Class description:
Implement the CognitiveServicesManagementClientOperationsMixin class.
Method signatures and docstrings:
- def check_sku_availability(self, location, skus, kind, type, custom_headers=None, raw=False, **ope... | Implement the Python class `CognitiveServicesManagementClientOperationsMixin` described below.
Class description:
Implement the CognitiveServicesManagementClientOperationsMixin class.
Method signatures and docstrings:
- def check_sku_availability(self, location, skus, kind, type, custom_headers=None, raw=False, **ope... | f779de8e53dbec033f98f976284e6d9491fd60b3 | <|skeleton|>
class CognitiveServicesManagementClientOperationsMixin:
def check_sku_availability(self, location, skus, kind, type, custom_headers=None, raw=False, **operation_config):
"""Check available SKUs. :param location: Resource location. :type location: str :param skus: The SKU of the resource. :type... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CognitiveServicesManagementClientOperationsMixin:
def check_sku_availability(self, location, skus, kind, type, custom_headers=None, raw=False, **operation_config):
"""Check available SKUs. :param location: Resource location. :type location: str :param skus: The SKU of the resource. :type skus: list[st... | the_stack_v2_python_sparse | sdk/cognitiveservices/azure-mgmt-cognitiveservices/azure/mgmt/cognitiveservices/operations/_cognitive_services_management_client_operations.py | YijunXieMS/azure-sdk-for-python | train | 1 | |
66fd1e94308a90fcc9030a979f26c054d3fe6061 | [
"super().__init__(**kwargs)\nself.label = label\nself.did = did\nself.recipient_keys = list(recipient_keys) if recipient_keys else None\nself.endpoint = endpoint\nself.routing_keys = list(routing_keys) if routing_keys else None\nself.image_url = image_url",
"c_json = self.to_json()\nc_i = bytes_to_b64(c_json.enco... | <|body_start_0|>
super().__init__(**kwargs)
self.label = label
self.did = did
self.recipient_keys = list(recipient_keys) if recipient_keys else None
self.endpoint = endpoint
self.routing_keys = list(routing_keys) if routing_keys else None
self.image_url = image_ur... | Class representing a connection invitation. | ConnectionInvitation | [
"LicenseRef-scancode-dco-1.1",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConnectionInvitation:
"""Class representing a connection invitation."""
def __init__(self, *, label: str=None, did: str=None, recipient_keys: Sequence[str]=None, endpoint: str=None, routing_keys: Sequence[str]=None, image_url: str=None, **kwargs):
"""Initialize connection invitation ... | stack_v2_sparse_classes_75kplus_train_000005 | 5,648 | permissive | [
{
"docstring": "Initialize connection invitation object. Args: label: Optional label for connection invitation did: DID for this connection invitation recipient_keys: List of recipient keys endpoint: Endpoint which this agent can be reached at routing_keys: List of routing keys image_url: Optional image URL for... | 3 | stack_v2_sparse_classes_30k_train_031714 | Implement the Python class `ConnectionInvitation` described below.
Class description:
Class representing a connection invitation.
Method signatures and docstrings:
- def __init__(self, *, label: str=None, did: str=None, recipient_keys: Sequence[str]=None, endpoint: str=None, routing_keys: Sequence[str]=None, image_ur... | Implement the Python class `ConnectionInvitation` described below.
Class description:
Class representing a connection invitation.
Method signatures and docstrings:
- def __init__(self, *, label: str=None, did: str=None, recipient_keys: Sequence[str]=None, endpoint: str=None, routing_keys: Sequence[str]=None, image_ur... | 39cac36d8937ce84a9307ce100aaefb8bc05ec04 | <|skeleton|>
class ConnectionInvitation:
"""Class representing a connection invitation."""
def __init__(self, *, label: str=None, did: str=None, recipient_keys: Sequence[str]=None, endpoint: str=None, routing_keys: Sequence[str]=None, image_url: str=None, **kwargs):
"""Initialize connection invitation ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConnectionInvitation:
"""Class representing a connection invitation."""
def __init__(self, *, label: str=None, did: str=None, recipient_keys: Sequence[str]=None, endpoint: str=None, routing_keys: Sequence[str]=None, image_url: str=None, **kwargs):
"""Initialize connection invitation object. Args:... | the_stack_v2_python_sparse | aries_cloudagent/protocols/connections/v1_0/messages/connection_invitation.py | hyperledger/aries-cloudagent-python | train | 370 |
e4ff882ac432ed2ee43f9e7487b700100fccbea4 | [
"super(Morphological_Chan_Vese, self).__init__(paramlist)\nif not paramlist:\n self.params['algorithm'] = 'Morphological_Chan_Vese'\n self.params['alpha1'] = 1\n self.params['beta1'] = 1\n self.params['beta2'] = 1\n self.params['max_iter'] = 10\n self.params['n_segments'] = 0\nself.paramindexes = ... | <|body_start_0|>
super(Morphological_Chan_Vese, self).__init__(paramlist)
if not paramlist:
self.params['algorithm'] = 'Morphological_Chan_Vese'
self.params['alpha1'] = 1
self.params['beta1'] = 1
self.params['beta2'] = 1
self.params['max_iter']... | Peform Morphological Chan Vese segmentation algorithm. ONLY WORKS ON GRAYSCALE. Active contours without edges. Can be used to segment images/volumes without good borders. Required that the inside of the object looks different than outside (color, shade, darker). Parameters: image -- ndarray of grayscale image iteration... | Morphological_Chan_Vese | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Morphological_Chan_Vese:
"""Peform Morphological Chan Vese segmentation algorithm. ONLY WORKS ON GRAYSCALE. Active contours without edges. Can be used to segment images/volumes without good borders. Required that the inside of the object looks different than outside (color, shade, darker). Parame... | stack_v2_sparse_classes_75kplus_train_000006 | 29,598 | permissive | [
{
"docstring": "Get parameters from parameter list that are used in segmentation algorithm. Assign default values to these parameters.",
"name": "__init__",
"signature": "def __init__(self, paramlist=None)"
},
{
"docstring": "Evaluate segmentation algorithm on training image. Keyword arguments: ... | 2 | stack_v2_sparse_classes_30k_train_000742 | Implement the Python class `Morphological_Chan_Vese` described below.
Class description:
Peform Morphological Chan Vese segmentation algorithm. ONLY WORKS ON GRAYSCALE. Active contours without edges. Can be used to segment images/volumes without good borders. Required that the inside of the object looks different than... | Implement the Python class `Morphological_Chan_Vese` described below.
Class description:
Peform Morphological Chan Vese segmentation algorithm. ONLY WORKS ON GRAYSCALE. Active contours without edges. Can be used to segment images/volumes without good borders. Required that the inside of the object looks different than... | 9246b8b20510d4c89357a6764ed96b919eb92d5a | <|skeleton|>
class Morphological_Chan_Vese:
"""Peform Morphological Chan Vese segmentation algorithm. ONLY WORKS ON GRAYSCALE. Active contours without edges. Can be used to segment images/volumes without good borders. Required that the inside of the object looks different than outside (color, shade, darker). Parame... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Morphological_Chan_Vese:
"""Peform Morphological Chan Vese segmentation algorithm. ONLY WORKS ON GRAYSCALE. Active contours without edges. Can be used to segment images/volumes without good borders. Required that the inside of the object looks different than outside (color, shade, darker). Parameters: image -... | the_stack_v2_python_sparse | see/Segmentors.py | Deepak768/see-segment | train | 0 |
c8b2ca6de19c3c372573a4acf4791283971199ca | [
"self._host = host\nself._port = port\nif os.environ.get('TEST_MODE') != 'UNIT_TEST':\n self.connection = pika.BlockingConnection(pika.ConnectionParameters(host=self._host, port=self._port))\nself.sender_lock = threading.Lock()",
"while True:\n try:\n with self.sender_lock:\n with self.con... | <|body_start_0|>
self._host = host
self._port = port
if os.environ.get('TEST_MODE') != 'UNIT_TEST':
self.connection = pika.BlockingConnection(pika.ConnectionParameters(host=self._host, port=self._port))
self.sender_lock = threading.Lock()
<|end_body_0|>
<|body_start_1|>
... | The singleton - is a core API object for API class. | RabbitApi | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RabbitApi:
"""The singleton - is a core API object for API class."""
def __init__(self, host: str, port: int):
"""Constructor for RabbitApi class :param host (str): ip or hostname of Rabbitmq service :param port (int):port of Rabbitmq service"""
<|body_0|>
def emit(self,... | stack_v2_sparse_classes_75kplus_train_000007 | 2,095 | permissive | [
{
"docstring": "Constructor for RabbitApi class :param host (str): ip or hostname of Rabbitmq service :param port (int):port of Rabbitmq service",
"name": "__init__",
"signature": "def __init__(self, host: str, port: int)"
},
{
"docstring": "Function for sending events used by API.send() :param ... | 2 | stack_v2_sparse_classes_30k_train_004037 | Implement the Python class `RabbitApi` described below.
Class description:
The singleton - is a core API object for API class.
Method signatures and docstrings:
- def __init__(self, host: str, port: int): Constructor for RabbitApi class :param host (str): ip or hostname of Rabbitmq service :param port (int):port of R... | Implement the Python class `RabbitApi` described below.
Class description:
The singleton - is a core API object for API class.
Method signatures and docstrings:
- def __init__(self, host: str, port: int): Constructor for RabbitApi class :param host (str): ip or hostname of Rabbitmq service :param port (int):port of R... | 647ad6d7cc5f91c188aa45e403d9c1a33a7fe947 | <|skeleton|>
class RabbitApi:
"""The singleton - is a core API object for API class."""
def __init__(self, host: str, port: int):
"""Constructor for RabbitApi class :param host (str): ip or hostname of Rabbitmq service :param port (int):port of Rabbitmq service"""
<|body_0|>
def emit(self,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RabbitApi:
"""The singleton - is a core API object for API class."""
def __init__(self, host: str, port: int):
"""Constructor for RabbitApi class :param host (str): ip or hostname of Rabbitmq service :param port (int):port of Rabbitmq service"""
self._host = host
self._port = port... | the_stack_v2_python_sparse | main_node/tools/rabbit_API_class.py | dpukhkaiev/BRISE2 | train | 6 |
c4fe4105eaa1555c6bb452e20b8d972c34fec537 | [
"from anima.dcc.blackmagic import get_fusion\nfusion = get_fusion()\ncomp = fusion.GetCurrentComp()\nreturn comp.ActiveTool",
"node_input_list = node.GetInputList()\nfor input_entry_key in node_input_list.keys():\n input_entry = node_input_list[input_entry_key]\n input_id = input_entry.GetAttrs()['INPS_ID']... | <|body_start_0|>
from anima.dcc.blackmagic import get_fusion
fusion = get_fusion()
comp = fusion.GetCurrentComp()
return comp.ActiveTool
<|end_body_0|>
<|body_start_1|>
node_input_list = node.GetInputList()
for input_entry_key in node_input_list.keys():
input... | Node related utils for Fusion | NodeUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeUtils:
"""Node related utils for Fusion"""
def get_active_node(self):
"""returns the active node"""
<|body_0|>
def list_input_ids(cls, node):
"""List input ids of the given node :param node: :return:"""
<|body_1|>
def get_node_attr(cls, node, att... | stack_v2_sparse_classes_75kplus_train_000008 | 10,465 | permissive | [
{
"docstring": "returns the active node",
"name": "get_active_node",
"signature": "def get_active_node(self)"
},
{
"docstring": "List input ids of the given node :param node: :return:",
"name": "list_input_ids",
"signature": "def list_input_ids(cls, node)"
},
{
"docstring": "gets... | 6 | stack_v2_sparse_classes_30k_train_003586 | Implement the Python class `NodeUtils` described below.
Class description:
Node related utils for Fusion
Method signatures and docstrings:
- def get_active_node(self): returns the active node
- def list_input_ids(cls, node): List input ids of the given node :param node: :return:
- def get_node_attr(cls, node, attr): ... | Implement the Python class `NodeUtils` described below.
Class description:
Node related utils for Fusion
Method signatures and docstrings:
- def get_active_node(self): returns the active node
- def list_input_ids(cls, node): List input ids of the given node :param node: :return:
- def get_node_attr(cls, node, attr): ... | 7b4cf60cb17f00435ecc3e03d573a9e2d0b44fe0 | <|skeleton|>
class NodeUtils:
"""Node related utils for Fusion"""
def get_active_node(self):
"""returns the active node"""
<|body_0|>
def list_input_ids(cls, node):
"""List input ids of the given node :param node: :return:"""
<|body_1|>
def get_node_attr(cls, node, att... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NodeUtils:
"""Node related utils for Fusion"""
def get_active_node(self):
"""returns the active node"""
from anima.dcc.blackmagic import get_fusion
fusion = get_fusion()
comp = fusion.GetCurrentComp()
return comp.ActiveTool
def list_input_ids(cls, node):
... | the_stack_v2_python_sparse | anima/dcc/fusion/utils.py | eoyilmaz/anima | train | 113 |
f5d152942a426e5154f715a2c4f16e0228ac1ef9 | [
"key_file = tempfile.NamedTemporaryFile()\nkey_file.write(test_crypto.TEST_PRIVATE_KEY_PEM)\nkey_file.flush()\ncrypto = util.read_private_key(key_file.name)\nself.assertEqual(test_crypto.TEST_PRIVATE_KEY_X, crypto.x)\nkey_file.close()",
"key_file = tempfile.NamedTemporaryFile()\nkey_file.write(TEST_SECT163K1_PRIV... | <|body_start_0|>
key_file = tempfile.NamedTemporaryFile()
key_file.write(test_crypto.TEST_PRIVATE_KEY_PEM)
key_file.flush()
crypto = util.read_private_key(key_file.name)
self.assertEqual(test_crypto.TEST_PRIVATE_KEY_X, crypto.x)
key_file.close()
<|end_body_0|>
<|body_sta... | TestReadPrivateKey | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestReadPrivateKey:
def test_read_private_key(self):
"""Test reading the signing key from a file."""
<|body_0|>
def test_read_private_key_invalid_curve(self):
"""Test that we require NIST384p for the signing key."""
<|body_1|>
def test_read_private_key_i... | stack_v2_sparse_classes_75kplus_train_000009 | 6,083 | permissive | [
{
"docstring": "Test reading the signing key from a file.",
"name": "test_read_private_key",
"signature": "def test_read_private_key(self)"
},
{
"docstring": "Test that we require NIST384p for the signing key.",
"name": "test_read_private_key_invalid_curve",
"signature": "def test_read_p... | 3 | stack_v2_sparse_classes_30k_train_023706 | Implement the Python class `TestReadPrivateKey` described below.
Class description:
Implement the TestReadPrivateKey class.
Method signatures and docstrings:
- def test_read_private_key(self): Test reading the signing key from a file.
- def test_read_private_key_invalid_curve(self): Test that we require NIST384p for ... | Implement the Python class `TestReadPrivateKey` described below.
Class description:
Implement the TestReadPrivateKey class.
Method signatures and docstrings:
- def test_read_private_key(self): Test reading the signing key from a file.
- def test_read_private_key_invalid_curve(self): Test that we require NIST384p for ... | 936355508212b55ba9d34aeec41a0aadb96ac645 | <|skeleton|>
class TestReadPrivateKey:
def test_read_private_key(self):
"""Test reading the signing key from a file."""
<|body_0|>
def test_read_private_key_invalid_curve(self):
"""Test that we require NIST384p for the signing key."""
<|body_1|>
def test_read_private_key_i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestReadPrivateKey:
def test_read_private_key(self):
"""Test reading the signing key from a file."""
key_file = tempfile.NamedTemporaryFile()
key_file.write(test_crypto.TEST_PRIVATE_KEY_PEM)
key_file.flush()
crypto = util.read_private_key(key_file.name)
self.ass... | the_stack_v2_python_sparse | brkt_cli/test_util.py | ramyabrkt/brkt-cli | train | 0 | |
3921ffc20c6e6fcb32261a5b42c703f6855121ff | [
"self.angle1 = angle1\nself.angle2 = angle2\nself.angle3 = angle3\nnumber_of_sides = 3",
"if self.angle1 + self.angle2 + self.angle3 == 180:\n print('This is a triangle')\n return True\nelse:\n print('This is not a traingle')\n return False"
] | <|body_start_0|>
self.angle1 = angle1
self.angle2 = angle2
self.angle3 = angle3
number_of_sides = 3
<|end_body_0|>
<|body_start_1|>
if self.angle1 + self.angle2 + self.angle3 == 180:
print('This is a triangle')
return True
else:
print(... | validateTriangle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class validateTriangle:
def __init__(self, angle1, angle2, angle3):
"""initializing"""
<|body_0|>
def checkValidity(self):
"""function to check if three sides form a triangle or not"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.angle1 = angle1
... | stack_v2_sparse_classes_75kplus_train_000010 | 738 | no_license | [
{
"docstring": "initializing",
"name": "__init__",
"signature": "def __init__(self, angle1, angle2, angle3)"
},
{
"docstring": "function to check if three sides form a triangle or not",
"name": "checkValidity",
"signature": "def checkValidity(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_041672 | Implement the Python class `validateTriangle` described below.
Class description:
Implement the validateTriangle class.
Method signatures and docstrings:
- def __init__(self, angle1, angle2, angle3): initializing
- def checkValidity(self): function to check if three sides form a triangle or not | Implement the Python class `validateTriangle` described below.
Class description:
Implement the validateTriangle class.
Method signatures and docstrings:
- def __init__(self, angle1, angle2, angle3): initializing
- def checkValidity(self): function to check if three sides form a triangle or not
<|skeleton|>
class va... | 646355ed2334cc28ab5ceedbd6d7036a5aa331ee | <|skeleton|>
class validateTriangle:
def __init__(self, angle1, angle2, angle3):
"""initializing"""
<|body_0|>
def checkValidity(self):
"""function to check if three sides form a triangle or not"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class validateTriangle:
def __init__(self, angle1, angle2, angle3):
"""initializing"""
self.angle1 = angle1
self.angle2 = angle2
self.angle3 = angle3
number_of_sides = 3
def checkValidity(self):
"""function to check if three sides form a triangle or not"""
... | the_stack_v2_python_sparse | validate_triangle.py | vidzierlein/Internship-Sep2020-Code | train | 0 | |
72f8ba893736985521e157cf42d768137923168e | [
"super(DFTXC, self).__init__()\nself.xcstr = xcstr\nself.nnmodel = nnmodel",
"hybridxc = HybridXC(self.xcstr, self.nnmodel, aweight0=0.0)\noutput = []\nfor entry in inputs:\n evl = XCNNSCF(hybridxc, entry)\n qcs = []\n for system in entry.get_systems():\n qcs.append(evl.run(system))\n if entry.... | <|body_start_0|>
super(DFTXC, self).__init__()
self.xcstr = xcstr
self.nnmodel = nnmodel
<|end_body_0|>
<|body_start_1|>
hybridxc = HybridXC(self.xcstr, self.nnmodel, aweight0=0.0)
output = []
for entry in inputs:
evl = XCNNSCF(hybridxc, entry)
qc... | This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepchem.models.dft.dftxc import DFTXC >>> e_type = 'ie' >>> true_val= '0.5341... | DFTXC | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DFTXC:
"""This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepchem.models.dft.dftxc import DFTXC >>> e_... | stack_v2_sparse_classes_75kplus_train_000011 | 9,553 | permissive | [
{
"docstring": "Parameters ---------- xcstr: str The choice of xc to use. Some of the commonly used ones are: lda_x, lda_c_pw, lda_c_ow, lda_c_pz, lda_xc_lp_a, lda_xc_lp_b. nnmodel: torch.nn.Module the PyTorch model implementing the calculation Notes ----- It is not necessary to use the default method(_construc... | 2 | stack_v2_sparse_classes_30k_train_004720 | Implement the Python class `DFTXC` described below.
Class description:
This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepch... | Implement the Python class `DFTXC` described below.
Class description:
This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepch... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class DFTXC:
"""This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepchem.models.dft.dftxc import DFTXC >>> e_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DFTXC:
"""This layer initializes the neural network exchange correlation functional and the hybrid functional. It is then used to run the Kohn Sham iterations. Examples -------- >>> import torch >>> from deepchem.feat.dft_data import DFTEntry >>> from deepchem.models.dft.dftxc import DFTXC >>> e_type = 'ie' >... | the_stack_v2_python_sparse | deepchem/models/dft/dftxc.py | deepchem/deepchem | train | 4,876 |
3ca2f8b2dd0b84b9f9491d80ba02bcd19da80d24 | [
"if not root:\n return ''\nreturn '{} '.format(root.val) + self.serialize(root.left) + self.serialize(root.right)",
"if not data:\n return\nstack = []\ndata = [int(d) for d in data[:-1].split(' ')]\nroot = node = TreeNode(data[0])\nfor val in data[1:]:\n if val < node.val:\n node.left = TreeNode(v... | <|body_start_0|>
if not root:
return ''
return '{} '.format(root.val) + self.serialize(root.left) + self.serialize(root.right)
<|end_body_0|>
<|body_start_1|>
if not data:
return
stack = []
data = [int(d) for d in data[:-1].split(' ')]
root = node... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_75kplus_train_000012 | 1,716 | 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_025100 | 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:... | 9126c2089e41d4d7fd3a204115eba2b5074076ad | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
return '{} '.format(root.val) + self.serialize(root.left) + self.serialize(root.right)
def deserialize(self, data):
"""Decodes you... | the_stack_v2_python_sparse | 449_Serialize and Deserialize BST.py | Shwan-Yu/Data_Structures_and_Algorithms | train | 0 | |
7cbf2015f363bdc69003436862a65a41531440ab | [
"super().__init__()\nself.tade1 = TADELayer(in_channels=in_channels, aux_channels=aux_channels, kernel_size=kernel_size, bias=bias, upsample_factor=1, upsample_mode=upsample_mode)\nself.gated_conv1 = torch.nn.Conv1d(in_channels, in_channels * 2, kernel_size, 1, bias=bias, padding=(kernel_size - 1) // 2)\nself.tade2... | <|body_start_0|>
super().__init__()
self.tade1 = TADELayer(in_channels=in_channels, aux_channels=aux_channels, kernel_size=kernel_size, bias=bias, upsample_factor=1, upsample_mode=upsample_mode)
self.gated_conv1 = torch.nn.Conv1d(in_channels, in_channels * 2, kernel_size, 1, bias=bias, padding=(... | TADEResBlock module. | TADEResBlock | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TADEResBlock:
"""TADEResBlock module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, dilation: int=2, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest', gated_function: str='softmax'):
"""Initialize TADEResBlock module. Args: ... | stack_v2_sparse_classes_75kplus_train_000013 | 5,864 | permissive | [
{
"docstring": "Initialize TADEResBlock module. Args: in_channels (int): Number of input channles. aux_channels (int): Number of auxirialy channles. kernel_size (int): Kernel size. bias (bool): Whether to use bias parameter in conv. upsample_factor (int): Upsample factor. upsample_mode (str): Upsample mode. gat... | 2 | stack_v2_sparse_classes_30k_test_002999 | Implement the Python class `TADEResBlock` described below.
Class description:
TADEResBlock module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, dilation: int=2, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest', gated_functio... | Implement the Python class `TADEResBlock` described below.
Class description:
TADEResBlock module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, dilation: int=2, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest', gated_functio... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class TADEResBlock:
"""TADEResBlock module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, dilation: int=2, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest', gated_function: str='softmax'):
"""Initialize TADEResBlock module. Args: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TADEResBlock:
"""TADEResBlock module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, dilation: int=2, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest', gated_function: str='softmax'):
"""Initialize TADEResBlock module. Args: in_channels (... | the_stack_v2_python_sparse | espnet2/gan_tts/style_melgan/tade_res_block.py | espnet/espnet | train | 7,242 |
500bd1291abc2514a42f87040782b27f7e778456 | [
"user_id = request.user.id\nadmin = request.user.is_superuser\nuser = api.keystone.user_get(request, user_id, admin)\ndata = user.to_dict()\nitems = []\nemail = data.get('email')\nmobile = data.get('mobile')\ninclude_myself = False\nif data.get('notify_list'):\n for item in data.get('notify_list'):\n name... | <|body_start_0|>
user_id = request.user.id
admin = request.user.is_superuser
user = api.keystone.user_get(request, user_id, admin)
data = user.to_dict()
items = []
email = data.get('email')
mobile = data.get('mobile')
include_myself = False
if data... | API for create and update notify list which belongs to current user. The notify list is used for alarms. | NotifyList | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotifyList:
"""API for create and update notify list which belongs to current user. The notify list is used for alarms."""
def get(self, request):
"""Get notify list of current user"""
<|body_0|>
def post(self, request):
"""Create notify list, update current user... | stack_v2_sparse_classes_75kplus_train_000014 | 34,106 | permissive | [
{
"docstring": "Get notify list of current user",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create notify list, update current user",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "Update notify list of current user",
"... | 3 | stack_v2_sparse_classes_30k_train_044603 | Implement the Python class `NotifyList` described below.
Class description:
API for create and update notify list which belongs to current user. The notify list is used for alarms.
Method signatures and docstrings:
- def get(self, request): Get notify list of current user
- def post(self, request): Create notify list... | Implement the Python class `NotifyList` described below.
Class description:
API for create and update notify list which belongs to current user. The notify list is used for alarms.
Method signatures and docstrings:
- def get(self, request): Get notify list of current user
- def post(self, request): Create notify list... | 9524f1952461c83db485d5d1702c350b158d7ce0 | <|skeleton|>
class NotifyList:
"""API for create and update notify list which belongs to current user. The notify list is used for alarms."""
def get(self, request):
"""Get notify list of current user"""
<|body_0|>
def post(self, request):
"""Create notify list, update current user... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NotifyList:
"""API for create and update notify list which belongs to current user. The notify list is used for alarms."""
def get(self, request):
"""Get notify list of current user"""
user_id = request.user.id
admin = request.user.is_superuser
user = api.keystone.user_get... | the_stack_v2_python_sparse | easystack_dashboard/api/rest/keystone.py | oksbsb/horizon-acc | train | 0 |
56f51b3403ad229105b492b082a63caafd4b4099 | [
"left = 1\nright = len(nums)\nresult = 0\nwhile left <= right:\n mid = left + (right - left) // 2\n tmp = self.windowex(nums, mid, s)\n if tmp:\n right = mid - 1\n result = mid\n else:\n left = mid + 1\nreturn result",
"sumnum = 0\nfor i in range(len(nums)):\n if i >= size:\n ... | <|body_start_0|>
left = 1
right = len(nums)
result = 0
while left <= right:
mid = left + (right - left) // 2
tmp = self.windowex(nums, mid, s)
if tmp:
right = mid - 1
result = mid
else:
left =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minSubArrayLen(self, s: int, nums: [int]) -> int:
"""二分查找法 o(nlogn) 将原数组分为两部分，0~mid作为一个窗口大小，遍历整个数组， 如果一旦满足，窗口内的和>=s，则将mid-1作为右边界，形成新的mid窗口，进行遍历 如果窗口内 :param s: :param nums: :return:"""
<|body_0|>
def windowex(self, nums, size, s):
"""判断在窗口中，是否和>s :param... | stack_v2_sparse_classes_75kplus_train_000015 | 2,091 | no_license | [
{
"docstring": "二分查找法 o(nlogn) 将原数组分为两部分，0~mid作为一个窗口大小，遍历整个数组， 如果一旦满足，窗口内的和>=s，则将mid-1作为右边界，形成新的mid窗口，进行遍历 如果窗口内 :param s: :param nums: :return:",
"name": "minSubArrayLen",
"signature": "def minSubArrayLen(self, s: int, nums: [int]) -> int"
},
{
"docstring": "判断在窗口中，是否和>s :param nums: :param siz... | 2 | stack_v2_sparse_classes_30k_train_004051 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minSubArrayLen(self, s: int, nums: [int]) -> int: 二分查找法 o(nlogn) 将原数组分为两部分，0~mid作为一个窗口大小，遍历整个数组， 如果一旦满足，窗口内的和>=s，则将mid-1作为右边界，形成新的mid窗口，进行遍历 如果窗口内 :param s: :param nums: :ret... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minSubArrayLen(self, s: int, nums: [int]) -> int: 二分查找法 o(nlogn) 将原数组分为两部分，0~mid作为一个窗口大小，遍历整个数组， 如果一旦满足，窗口内的和>=s，则将mid-1作为右边界，形成新的mid窗口，进行遍历 如果窗口内 :param s: :param nums: :ret... | f68e60dd1d8bb010cdae88e6273b3fac4ea48776 | <|skeleton|>
class Solution:
def minSubArrayLen(self, s: int, nums: [int]) -> int:
"""二分查找法 o(nlogn) 将原数组分为两部分，0~mid作为一个窗口大小，遍历整个数组， 如果一旦满足，窗口内的和>=s，则将mid-1作为右边界，形成新的mid窗口，进行遍历 如果窗口内 :param s: :param nums: :return:"""
<|body_0|>
def windowex(self, nums, size, s):
"""判断在窗口中，是否和>s :param... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def minSubArrayLen(self, s: int, nums: [int]) -> int:
"""二分查找法 o(nlogn) 将原数组分为两部分，0~mid作为一个窗口大小，遍历整个数组， 如果一旦满足，窗口内的和>=s，则将mid-1作为右边界，形成新的mid窗口，进行遍历 如果窗口内 :param s: :param nums: :return:"""
left = 1
right = len(nums)
result = 0
while left <= right:
... | the_stack_v2_python_sparse | string/209_minSubArrayLen.py | liying123456/python_leetcode | train | 0 | |
6b3b7eed1a30982e3a59498fdb51a54af20a669d | [
"if n == 0:\n return []\ntotal_l = []\ntotal_l.append([None])\ntotal_l.append(['()'])\nfor i in range(2, n + 1):\n l = []\n for j in range(i):\n now_list1 = total_l[j]\n now_list2 = total_l[i - 1 - j]\n print(now_list1, now_list2)\n for k1 in now_list1:\n for k2 in no... | <|body_start_0|>
if n == 0:
return []
total_l = []
total_l.append([None])
total_l.append(['()'])
for i in range(2, n + 1):
l = []
for j in range(i):
now_list1 = total_l[j]
now_list2 = total_l[i - 1 - j]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generateParenthesis(self, n):
""":type n: int :rtype: List[str]"""
<|body_0|>
def _gen(self, left, right, n, result):
"""left: 左括号用了多少个 right：右括号用了多少个 n： 括号对数 result：当前产生的括号序列"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 0:
... | stack_v2_sparse_classes_75kplus_train_000016 | 3,718 | no_license | [
{
"docstring": ":type n: int :rtype: List[str]",
"name": "generateParenthesis",
"signature": "def generateParenthesis(self, n)"
},
{
"docstring": "left: 左括号用了多少个 right：右括号用了多少个 n： 括号对数 result：当前产生的括号序列",
"name": "_gen",
"signature": "def _gen(self, left, right, n, result)"
}
] | 2 | stack_v2_sparse_classes_30k_train_030156 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateParenthesis(self, n): :type n: int :rtype: List[str]
- def _gen(self, left, right, n, result): left: 左括号用了多少个 right：右括号用了多少个 n： 括号对数 result：当前产生的括号序列 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateParenthesis(self, n): :type n: int :rtype: List[str]
- def _gen(self, left, right, n, result): left: 左括号用了多少个 right：右括号用了多少个 n： 括号对数 result：当前产生的括号序列
<|skeleton|>
cl... | a32c096e192a89a88457ccc1899be10352bf1edd | <|skeleton|>
class Solution:
def generateParenthesis(self, n):
""":type n: int :rtype: List[str]"""
<|body_0|>
def _gen(self, left, right, n, result):
"""left: 左括号用了多少个 right：右括号用了多少个 n： 括号对数 result：当前产生的括号序列"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def generateParenthesis(self, n):
""":type n: int :rtype: List[str]"""
if n == 0:
return []
total_l = []
total_l.append([None])
total_l.append(['()'])
for i in range(2, n + 1):
l = []
for j in range(i):
... | the_stack_v2_python_sparse | leetcode/022.括号生成.py | luhao2013/Algorithms | train | 0 | |
3685099924cb1869e32120a01b7c8a8819448837 | [
"inshape = self.observation_space.shape[0]\nself.net = FeedForwardNet(inshape, [32, 32], activate_last=True)\nif hasattr(self.action_space, 'n'):\n self.dist = Categorical(32, self.action_space.n)\nelse:\n self.dist = DiagGaussian(32, self.action_space.shape[0])\nself.vf = torch.nn.Linear(32, 1)",
"if isins... | <|body_start_0|>
inshape = self.observation_space.shape[0]
self.net = FeedForwardNet(inshape, [32, 32], activate_last=True)
if hasattr(self.action_space, 'n'):
self.dist = Categorical(32, self.action_space.n)
else:
self.dist = DiagGaussian(32, self.action_space.sh... | Test feed forward network. | FeedForwardBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeedForwardBase:
"""Test feed forward network."""
def build(self):
"""Build network."""
<|body_0|>
def forward(self, ob):
"""Forward."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
inshape = self.observation_space.shape[0]
self.net = Fe... | stack_v2_sparse_classes_75kplus_train_000017 | 13,010 | no_license | [
{
"docstring": "Build network.",
"name": "build",
"signature": "def build(self)"
},
{
"docstring": "Forward.",
"name": "forward",
"signature": "def forward(self, ob)"
}
] | 2 | stack_v2_sparse_classes_30k_train_048334 | Implement the Python class `FeedForwardBase` described below.
Class description:
Test feed forward network.
Method signatures and docstrings:
- def build(self): Build network.
- def forward(self, ob): Forward. | Implement the Python class `FeedForwardBase` described below.
Class description:
Test feed forward network.
Method signatures and docstrings:
- def build(self): Build network.
- def forward(self, ob): Forward.
<|skeleton|>
class FeedForwardBase:
"""Test feed forward network."""
def build(self):
"""B... | e71c4b12955b01bfb907aa31c91ded6bcd8aaec8 | <|skeleton|>
class FeedForwardBase:
"""Test feed forward network."""
def build(self):
"""Build network."""
<|body_0|>
def forward(self, ob):
"""Forward."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeedForwardBase:
"""Test feed forward network."""
def build(self):
"""Build network."""
inshape = self.observation_space.shape[0]
self.net = FeedForwardNet(inshape, [32, 32], activate_last=True)
if hasattr(self.action_space, 'n'):
self.dist = Categorical(32, se... | the_stack_v2_python_sparse | dl/rl/data_collection/rollout_data_collection.py | cbschaff/dl | train | 1 |
d2761373fd20a8173ba1af2c29ee3f8d121fe007 | [
"super(TimeDistributedDenseLayerSCP, self).__init__()\nassert isinstance(input_shape, tuple) and len(input_shape) == 1, '\"input_shape\" should be a tuple with single value.'\nassert isinstance(output_shape, tuple) and len(output_shape) == 1, '\"output_shape\" should be a tuple with single value.'\nassert isinstanc... | <|body_start_0|>
super(TimeDistributedDenseLayerSCP, self).__init__()
assert isinstance(input_shape, tuple) and len(input_shape) == 1, '"input_shape" should be a tuple with single value.'
assert isinstance(output_shape, tuple) and len(output_shape) == 1, '"output_shape" should be a tuple with si... | This class implements time distributed dense layer connection. | TimeDistributedDenseLayerSCP | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeDistributedDenseLayerSCP:
"""This class implements time distributed dense layer connection."""
def __init__(self, input_shape, output_shape, use_bias=True, target_cpu=False):
"""This function initializes the class. Input is 3D tensor, output is 3D tensor. For efficient following ... | stack_v2_sparse_classes_75kplus_train_000018 | 8,571 | permissive | [
{
"docstring": "This function initializes the class. Input is 3D tensor, output is 3D tensor. For efficient following batch normalization, use_bias = False. Parameters ---------- input_shape: tuple a tuple of single value, i.e., (input dim,) output_shape: tupe a tuple of single value, i.e., (output dim,) use_bi... | 4 | null | Implement the Python class `TimeDistributedDenseLayerSCP` described below.
Class description:
This class implements time distributed dense layer connection.
Method signatures and docstrings:
- def __init__(self, input_shape, output_shape, use_bias=True, target_cpu=False): This function initializes the class. Input is... | Implement the Python class `TimeDistributedDenseLayerSCP` described below.
Class description:
This class implements time distributed dense layer connection.
Method signatures and docstrings:
- def __init__(self, input_shape, output_shape, use_bias=True, target_cpu=False): This function initializes the class. Input is... | 7585261dd1b1c6c99dada5d2d1aabf482e89e880 | <|skeleton|>
class TimeDistributedDenseLayerSCP:
"""This class implements time distributed dense layer connection."""
def __init__(self, input_shape, output_shape, use_bias=True, target_cpu=False):
"""This function initializes the class. Input is 3D tensor, output is 3D tensor. For efficient following ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TimeDistributedDenseLayerSCP:
"""This class implements time distributed dense layer connection."""
def __init__(self, input_shape, output_shape, use_bias=True, target_cpu=False):
"""This function initializes the class. Input is 3D tensor, output is 3D tensor. For efficient following batch normali... | the_stack_v2_python_sparse | lemontree/experimentals/dense_scp.py | khshim/lemontree | train | 3 |
8fb9673920f307f9923af87c72706bfd9d24a3a7 | [
"obs = real_env.reset()\nR = 0\nstates = []\nfor i in range(H):\n if render:\n real_env.render()\n ac = policy @ obs\n new_obs, rew, done, info = real_env.step(ac)\n R += rew\n if done:\n break\n obs = new_obs\n states.append(obs)\nreturn (R, states)",
"max_rewards = [max(reward... | <|body_start_0|>
obs = real_env.reset()
R = 0
states = []
for i in range(H):
if render:
real_env.render()
ac = policy @ obs
new_obs, rew, done, info = real_env.step(ac)
R += rew
if done:
break
... | Basic ARS Agent for solving continuous control tasks. Without Safe Exploration. | Basic_ARS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Basic_ARS:
"""Basic ARS Agent for solving continuous control tasks. Without Safe Exploration."""
def rollout(self, real_env, policy, H, render=False):
""":param real_env: :param policy: :param H: :param render: :return:"""
<|body_0|>
def sort_directions(self, deltas, rew... | stack_v2_sparse_classes_75kplus_train_000019 | 4,774 | no_license | [
{
"docstring": ":param real_env: :param policy: :param H: :param render: :return:",
"name": "rollout",
"signature": "def rollout(self, real_env, policy, H, render=False)"
},
{
"docstring": "Sort the directions deltas by max{r_k_+, r_k_-} :param deltas: array of matrices :param rewards: array of ... | 4 | stack_v2_sparse_classes_30k_train_024256 | Implement the Python class `Basic_ARS` described below.
Class description:
Basic ARS Agent for solving continuous control tasks. Without Safe Exploration.
Method signatures and docstrings:
- def rollout(self, real_env, policy, H, render=False): :param real_env: :param policy: :param H: :param render: :return:
- def s... | Implement the Python class `Basic_ARS` described below.
Class description:
Basic ARS Agent for solving continuous control tasks. Without Safe Exploration.
Method signatures and docstrings:
- def rollout(self, real_env, policy, H, render=False): :param real_env: :param policy: :param H: :param render: :return:
- def s... | e10c1b6038f357ee5e9b67593a15a1d5f61c1e99 | <|skeleton|>
class Basic_ARS:
"""Basic ARS Agent for solving continuous control tasks. Without Safe Exploration."""
def rollout(self, real_env, policy, H, render=False):
""":param real_env: :param policy: :param H: :param render: :return:"""
<|body_0|>
def sort_directions(self, deltas, rew... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Basic_ARS:
"""Basic ARS Agent for solving continuous control tasks. Without Safe Exploration."""
def rollout(self, real_env, policy, H, render=False):
""":param real_env: :param policy: :param H: :param render: :return:"""
obs = real_env.reset()
R = 0
states = []
f... | the_stack_v2_python_sparse | safe_ars/ars.py | leonzheng2/Safe-Exploration-with-Simulator-in-RL-algorithms | train | 0 |
f1595690445b58d8c24c8c40dc353829e05c7775 | [
"res = set()\nif len(nums) < 4:\n return []\nnums.sort()\nfor i in range(len(nums) - 3):\n for j in range(i + 1, len(nums) - 2):\n l, r = (j + 1, len(nums) - 1)\n while l < r:\n s = nums[i] + nums[j] + nums[l] + nums[r]\n if s < target:\n l += 1\n ... | <|body_start_0|>
res = set()
if len(nums) < 4:
return []
nums.sort()
for i in range(len(nums) - 3):
for j in range(i + 1, len(nums) - 2):
l, r = (j + 1, len(nums) - 1)
while l < r:
s = nums[i] + nums[j] + nums[l]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]] 向中间压缩的方式 O(n^3)"""
<|body_0|>
def fourSum1(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]] 方法二 O(n^3) 有点问题"""
... | stack_v2_sparse_classes_75kplus_train_000020 | 2,372 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]] 向中间压缩的方式 O(n^3)",
"name": "fourSum",
"signature": "def fourSum(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]] 方法二 O(n^3) 有点问题",
"name": "fourSum1",
"si... | 2 | stack_v2_sparse_classes_30k_train_032612 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]] 向中间压缩的方式 O(n^3)
- def fourSum1(self, nums, target): :type nums: List[int] :type t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]] 向中间压缩的方式 O(n^3)
- def fourSum1(self, nums, target): :type nums: List[int] :type t... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]] 向中间压缩的方式 O(n^3)"""
<|body_0|>
def fourSum1(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]] 方法二 O(n^3) 有点问题"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]] 向中间压缩的方式 O(n^3)"""
res = set()
if len(nums) < 4:
return []
nums.sort()
for i in range(len(nums) - 3):
for j in range(i + 1, len(nums) - ... | the_stack_v2_python_sparse | 算法/学习笔记/四数之和.py | RichieSong/algorithm | train | 0 | |
b8996bf48c29938c7c14e599decb94ae6c9945e0 | [
"words_to_counts = {'cat': 1}\nexpected_result = {'cat': 1}\ntweets.common_words(words_to_counts, 1)\nself.assertEqual(words_to_counts, expected_result, 'none removed')",
"dic = {'I': 10, 'you': 5, 'miss': 8, 'here': 6, 'how': 6}\ntweets.common_words(dic, 3)\nexpect_result = {'I': 10, 'miss': 8}\nself.assertEqual... | <|body_start_0|>
words_to_counts = {'cat': 1}
expected_result = {'cat': 1}
tweets.common_words(words_to_counts, 1)
self.assertEqual(words_to_counts, expected_result, 'none removed')
<|end_body_0|>
<|body_start_1|>
dic = {'I': 10, 'you': 5, 'miss': 8, 'here': 6, 'how': 6}
... | TestCommonWords | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCommonWords:
def test_none_removed(self):
"""Test common_words with N so that no words are removed."""
<|body_0|>
def test_tie_removed(self):
"""Test common_words with N so that tied words are removed."""
<|body_1|>
def test_tie_remained(self):
... | stack_v2_sparse_classes_75kplus_train_000021 | 1,649 | permissive | [
{
"docstring": "Test common_words with N so that no words are removed.",
"name": "test_none_removed",
"signature": "def test_none_removed(self)"
},
{
"docstring": "Test common_words with N so that tied words are removed.",
"name": "test_tie_removed",
"signature": "def test_tie_removed(se... | 5 | stack_v2_sparse_classes_30k_train_013761 | Implement the Python class `TestCommonWords` described below.
Class description:
Implement the TestCommonWords class.
Method signatures and docstrings:
- def test_none_removed(self): Test common_words with N so that no words are removed.
- def test_tie_removed(self): Test common_words with N so that tied words are re... | Implement the Python class `TestCommonWords` described below.
Class description:
Implement the TestCommonWords class.
Method signatures and docstrings:
- def test_none_removed(self): Test common_words with N so that no words are removed.
- def test_tie_removed(self): Test common_words with N so that tied words are re... | 214525afeeb2da2409f451bf269e792c6940a1ba | <|skeleton|>
class TestCommonWords:
def test_none_removed(self):
"""Test common_words with N so that no words are removed."""
<|body_0|>
def test_tie_removed(self):
"""Test common_words with N so that tied words are removed."""
<|body_1|>
def test_tie_remained(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestCommonWords:
def test_none_removed(self):
"""Test common_words with N so that no words are removed."""
words_to_counts = {'cat': 1}
expected_result = {'cat': 1}
tweets.common_words(words_to_counts, 1)
self.assertEqual(words_to_counts, expected_result, 'none removed'... | the_stack_v2_python_sparse | Python/Tweet/test_common_words.py | LilyYC/legendary-train | train | 0 | |
11773ae801e8daa41783c17bfc9bdf99e33ab012 | [
"self.__window = window\nself.__back_color = BLUE\nself.__rect_color = RED\nself.__text_color = GREEN\nw, h = window.get_dimension()\nrect_w = 500\nrect_h = 300\nself.__rectangle = pygame.rect.Rect(int((w - rect_w) / 2), int((h - rect_h) / 2), rect_w, rect_h)\nself.__font = pygame.font.SysFont('comicsansms', 20)\ns... | <|body_start_0|>
self.__window = window
self.__back_color = BLUE
self.__rect_color = RED
self.__text_color = GREEN
w, h = window.get_dimension()
rect_w = 500
rect_h = 300
self.__rectangle = pygame.rect.Rect(int((w - rect_w) / 2), int((h - rect_h) / 2), rec... | This class represent the waiting screen where the players must wait the other is ready | DeconnectionScreen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeconnectionScreen:
"""This class represent the waiting screen where the players must wait the other is ready"""
def __init__(self, window):
"""Creates the connection screen"""
<|body_0|>
def launch(self):
"""Launches the connexion screen"""
<|body_1|>
<... | stack_v2_sparse_classes_75kplus_train_000022 | 2,404 | no_license | [
{
"docstring": "Creates the connection screen",
"name": "__init__",
"signature": "def __init__(self, window)"
},
{
"docstring": "Launches the connexion screen",
"name": "launch",
"signature": "def launch(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000956 | Implement the Python class `DeconnectionScreen` described below.
Class description:
This class represent the waiting screen where the players must wait the other is ready
Method signatures and docstrings:
- def __init__(self, window): Creates the connection screen
- def launch(self): Launches the connexion screen | Implement the Python class `DeconnectionScreen` described below.
Class description:
This class represent the waiting screen where the players must wait the other is ready
Method signatures and docstrings:
- def __init__(self, window): Creates the connection screen
- def launch(self): Launches the connexion screen
<|... | 6e3734d38e111f455912474268cb7d0e8474fa40 | <|skeleton|>
class DeconnectionScreen:
"""This class represent the waiting screen where the players must wait the other is ready"""
def __init__(self, window):
"""Creates the connection screen"""
<|body_0|>
def launch(self):
"""Launches the connexion screen"""
<|body_1|>
<... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeconnectionScreen:
"""This class represent the waiting screen where the players must wait the other is ready"""
def __init__(self, window):
"""Creates the connection screen"""
self.__window = window
self.__back_color = BLUE
self.__rect_color = RED
self.__text_colo... | the_stack_v2_python_sparse | client_side/graphical/deconnectionScreen.py | adam-hotait/3Dtictactoe | train | 1 |
7105125f392f78dccaf5513b8de75c58a8f9a654 | [
"self.sc_id = sc_id\nself.tleDir = tleDir\nself._loadTLEblacklist(blacklistFname)\nreturn",
"if fname is None:\n sc_name_underscore = self.sc_id.upper().replace(' ', '_')\n fname = f'{sc_name_underscore}_tle_table.txt'\nwith open(fname, 'w') as f:\n print('Created TLE table file', fname)\n f.write('# ... | <|body_start_0|>
self.sc_id = sc_id
self.tleDir = tleDir
self._loadTLEblacklist(blacklistFname)
return
<|end_body_0|>
<|body_start_1|>
if fname is None:
sc_name_underscore = self.sc_id.upper().replace(' ', '_')
fname = f'{sc_name_underscore}_tle_table.txt... | Make_TLE_table | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Make_TLE_table:
def __init__(self, sc_id, tleDir='/home/mike/research/firebird/tle', blacklistFname=None):
"""NAME: Make_TLE_table(self, sc_id) USE: Makes a csv table of the TLEs for sc_id spacecraft. ARGS: REQUIRED: sc_id: Spacecraft id OPTIONAL: tleDir='/home/mike/research/firebird/tle... | stack_v2_sparse_classes_75kplus_train_000023 | 16,081 | no_license | [
{
"docstring": "NAME: Make_TLE_table(self, sc_id) USE: Makes a csv table of the TLEs for sc_id spacecraft. ARGS: REQUIRED: sc_id: Spacecraft id OPTIONAL: tleDir='/home/mike/research/firebird/tle': The directory containing the spacecraft TLEs. If propagating for FIREBIRD, download them off of Europa. blacklistFn... | 3 | null | Implement the Python class `Make_TLE_table` described below.
Class description:
Implement the Make_TLE_table class.
Method signatures and docstrings:
- def __init__(self, sc_id, tleDir='/home/mike/research/firebird/tle', blacklistFname=None): NAME: Make_TLE_table(self, sc_id) USE: Makes a csv table of the TLEs for sc... | Implement the Python class `Make_TLE_table` described below.
Class description:
Implement the Make_TLE_table class.
Method signatures and docstrings:
- def __init__(self, sc_id, tleDir='/home/mike/research/firebird/tle', blacklistFname=None): NAME: Make_TLE_table(self, sc_id) USE: Makes a csv table of the TLEs for sc... | 196342fe358ff5e195541269646bb228941bed64 | <|skeleton|>
class Make_TLE_table:
def __init__(self, sc_id, tleDir='/home/mike/research/firebird/tle', blacklistFname=None):
"""NAME: Make_TLE_table(self, sc_id) USE: Makes a csv table of the TLEs for sc_id spacecraft. ARGS: REQUIRED: sc_id: Spacecraft id OPTIONAL: tleDir='/home/mike/research/firebird/tle... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Make_TLE_table:
def __init__(self, sc_id, tleDir='/home/mike/research/firebird/tle', blacklistFname=None):
"""NAME: Make_TLE_table(self, sc_id) USE: Makes a csv table of the TLEs for sc_id spacecraft. ARGS: REQUIRED: sc_id: Spacecraft id OPTIONAL: tleDir='/home/mike/research/firebird/tle': The directo... | the_stack_v2_python_sparse | mission_tools/orbit/make_ephem.py | mshumko/mission_tools | train | 0 | |
bc02a93b3db4a65d39291e73b15632f6bc1e7268 | [
"result = input.sqrt()\nresult[input < 0] = 0\nctx.save_for_backward(result)\nreturn result",
"result, = ctx.saved_tensors\ngrad_input = grad_output / (2 * result)\ngrad_input[result == 0] = 0\nreturn grad_input"
] | <|body_start_0|>
result = input.sqrt()
result[input < 0] = 0
ctx.save_for_backward(result)
return result
<|end_body_0|>
<|body_start_1|>
result, = ctx.saved_tensors
grad_input = grad_output / (2 * result)
grad_input[result == 0] = 0
return grad_input
<|en... | Compute the square root and gradients class of a given tensor. Taken from the geomloss package. | Sqrt0 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sqrt0:
"""Compute the square root and gradients class of a given tensor. Taken from the geomloss package."""
def forward(ctx, input):
"""Compute the square root for a given Tensor."""
<|body_0|>
def backward(ctx, grad_output):
"""Compute the square root gradients... | stack_v2_sparse_classes_75kplus_train_000024 | 8,555 | permissive | [
{
"docstring": "Compute the square root for a given Tensor.",
"name": "forward",
"signature": "def forward(ctx, input)"
},
{
"docstring": "Compute the square root gradients of a given Tensor.",
"name": "backward",
"signature": "def backward(ctx, grad_output)"
}
] | 2 | stack_v2_sparse_classes_30k_train_046915 | Implement the Python class `Sqrt0` described below.
Class description:
Compute the square root and gradients class of a given tensor. Taken from the geomloss package.
Method signatures and docstrings:
- def forward(ctx, input): Compute the square root for a given Tensor.
- def backward(ctx, grad_output): Compute the ... | Implement the Python class `Sqrt0` described below.
Class description:
Compute the square root and gradients class of a given tensor. Taken from the geomloss package.
Method signatures and docstrings:
- def forward(ctx, input): Compute the square root for a given Tensor.
- def backward(ctx, grad_output): Compute the ... | cd21033e5bbf974283fcb1b88e586270e5a6ba7e | <|skeleton|>
class Sqrt0:
"""Compute the square root and gradients class of a given tensor. Taken from the geomloss package."""
def forward(ctx, input):
"""Compute the square root for a given Tensor."""
<|body_0|>
def backward(ctx, grad_output):
"""Compute the square root gradients... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Sqrt0:
"""Compute the square root and gradients class of a given tensor. Taken from the geomloss package."""
def forward(ctx, input):
"""Compute the square root for a given Tensor."""
result = input.sqrt()
result[input < 0] = 0
ctx.save_for_backward(result)
return ... | the_stack_v2_python_sparse | GAN/utils.py | kilianFatras/unbiased_minibatch_sinkhorn_GAN | train | 9 |
6ce02c0a5f04d9d2b7081a2725edd4b711c2f9e8 | [
"super(SegnetConvLSTM, self).__init__()\nassert lstm_nlayers == len(lstm_hidden_dim)\nself.n_classes = decoder_out_channels\nself.v = verbose\nself.encoder = encoder.VGGencoder()\nself.decoder = decoder.VGGDecoder(decoder_out_channels, config=vgg_decoder_config)\nself.lstm = convlstm.ConvLSTM(input_size=(4, 8), inp... | <|body_start_0|>
super(SegnetConvLSTM, self).__init__()
assert lstm_nlayers == len(lstm_hidden_dim)
self.n_classes = decoder_out_channels
self.v = verbose
self.encoder = encoder.VGGencoder()
self.decoder = decoder.VGGDecoder(decoder_out_channels, config=vgg_decoder_config... | This class implements the whole end-to-end trainable model as described in the paper 'Robust Lane detection From Continuous Driving Scenes Using Deep Neural Networks'. The model comprises of a fully convolutional encoder-decoder (namely Segnet) and of a ConvLSTM, which 'fuses' information coming from multiple contiguou... | SegnetConvLSTM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegnetConvLSTM:
"""This class implements the whole end-to-end trainable model as described in the paper 'Robust Lane detection From Continuous Driving Scenes Using Deep Neural Networks'. The model comprises of a fully convolutional encoder-decoder (namely Segnet) and of a ConvLSTM, which 'fuses' ... | stack_v2_sparse_classes_75kplus_train_000025 | 4,953 | no_license | [
{
"docstring": ":param lstm_hidden_dim: list of hidden layers dimensions used to define the convlstm architecture (e.g [512, 512]). :param lstm_nlayers: number of hidden layers in lstm (== len(lstm_hidden_dim)) :param decoder_out_channels: number of channels the decoder output will have; it is generally the sam... | 2 | stack_v2_sparse_classes_30k_train_007050 | Implement the Python class `SegnetConvLSTM` described below.
Class description:
This class implements the whole end-to-end trainable model as described in the paper 'Robust Lane detection From Continuous Driving Scenes Using Deep Neural Networks'. The model comprises of a fully convolutional encoder-decoder (namely Se... | Implement the Python class `SegnetConvLSTM` described below.
Class description:
This class implements the whole end-to-end trainable model as described in the paper 'Robust Lane detection From Continuous Driving Scenes Using Deep Neural Networks'. The model comprises of a fully convolutional encoder-decoder (namely Se... | b7fb520080c48a418d4d009ee35f4f92e01f50bd | <|skeleton|>
class SegnetConvLSTM:
"""This class implements the whole end-to-end trainable model as described in the paper 'Robust Lane detection From Continuous Driving Scenes Using Deep Neural Networks'. The model comprises of a fully convolutional encoder-decoder (namely Segnet) and of a ConvLSTM, which 'fuses' ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SegnetConvLSTM:
"""This class implements the whole end-to-end trainable model as described in the paper 'Robust Lane detection From Continuous Driving Scenes Using Deep Neural Networks'. The model comprises of a fully convolutional encoder-decoder (namely Segnet) and of a ConvLSTM, which 'fuses' information c... | the_stack_v2_python_sparse | segnet_conv_lstm_model.py | arindam-modak/Robust-Lane-Detection-in-hazy-environment-using-Encoder-Decoder-CNN-LSTM-DCP | train | 4 |
3d9ec6bbd1a3daf68331456a1faa0930e7a4d176 | [
"n = len(s)\n\n@lru_cache(None)\ndef dfs(i):\n if i == n:\n return 1\n result = 0\n for j in range(i + 1, min(i + 3, n + 1)):\n if s[i] != '0' and 1 <= int(s[i:j]) <= 26:\n result += dfs(j)\n return result\nreturn dfs(0)",
"n = len(s)\ndp = [0] * (n + 1)\ndp[0] = 1\nfor i in r... | <|body_start_0|>
n = len(s)
@lru_cache(None)
def dfs(i):
if i == n:
return 1
result = 0
for j in range(i + 1, min(i + 3, n + 1)):
if s[i] != '0' and 1 <= int(s[i:j]) <= 26:
result += dfs(j)
retur... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numDecodings(self, s: str) -> int:
"""DFS+Memoization"""
<|body_0|>
def numDecodings(self, s: str) -> int:
"""DP, Time: O(n), Space: O(n)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(s)
@lru_cache(None)
def ... | stack_v2_sparse_classes_75kplus_train_000026 | 1,213 | no_license | [
{
"docstring": "DFS+Memoization",
"name": "numDecodings",
"signature": "def numDecodings(self, s: str) -> int"
},
{
"docstring": "DP, Time: O(n), Space: O(n)",
"name": "numDecodings",
"signature": "def numDecodings(self, s: str) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_val_001425 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numDecodings(self, s: str) -> int: DFS+Memoization
- def numDecodings(self, s: str) -> int: DP, Time: O(n), Space: O(n) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numDecodings(self, s: str) -> int: DFS+Memoization
- def numDecodings(self, s: str) -> int: DP, Time: O(n), Space: O(n)
<|skeleton|>
class Solution:
def numDecodings(se... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def numDecodings(self, s: str) -> int:
"""DFS+Memoization"""
<|body_0|>
def numDecodings(self, s: str) -> int:
"""DP, Time: O(n), Space: O(n)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def numDecodings(self, s: str) -> int:
"""DFS+Memoization"""
n = len(s)
@lru_cache(None)
def dfs(i):
if i == n:
return 1
result = 0
for j in range(i + 1, min(i + 3, n + 1)):
if s[i] != '0' and 1 <= i... | the_stack_v2_python_sparse | python/91-Decode Ways.py | cwza/leetcode | train | 0 | |
be3246926d6a756cc4c67f7a826d87740007c1aa | [
"plt.figure(figsize=figsize)\nkey_list = []\nfor i in self.keys():\n key_list.append(i)\ntotal_time = len(self[key_list[0]])\nif legendlist == None:\n legendlist = ['variable {}'.format(i) for i in key_list]\nk = 0\nfor i in key_list:\n plt.plot(range(0, total_time), self[i], label=legendlist[k], linewidth... | <|body_start_0|>
plt.figure(figsize=figsize)
key_list = []
for i in self.keys():
key_list.append(i)
total_time = len(self[key_list[0]])
if legendlist == None:
legendlist = ['variable {}'.format(i) for i in key_list]
k = 0
for i in key_list:... | Solution dictionary is an ordered dictionary that stores the optimization results Solution dictionary struture: D[name key]=time series data | SolutionDict | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SolutionDict:
"""Solution dictionary is an ordered dictionary that stores the optimization results Solution dictionary struture: D[name key]=time series data"""
def plot_2d(self, x_str='Time', y_str='Value', title_str='Results', figsize=(15, 7), legendlist=None):
"""step plot"""
... | stack_v2_sparse_classes_75kplus_train_000027 | 6,642 | no_license | [
{
"docstring": "step plot",
"name": "plot_2d",
"signature": "def plot_2d(self, x_str='Time', y_str='Value', title_str='Results', figsize=(15, 7), legendlist=None)"
},
{
"docstring": "step plot",
"name": "plot_step_2d",
"signature": "def plot_step_2d(self, x_str='Time', y_str='Value', tit... | 3 | null | Implement the Python class `SolutionDict` described below.
Class description:
Solution dictionary is an ordered dictionary that stores the optimization results Solution dictionary struture: D[name key]=time series data
Method signatures and docstrings:
- def plot_2d(self, x_str='Time', y_str='Value', title_str='Resul... | Implement the Python class `SolutionDict` described below.
Class description:
Solution dictionary is an ordered dictionary that stores the optimization results Solution dictionary struture: D[name key]=time series data
Method signatures and docstrings:
- def plot_2d(self, x_str='Time', y_str='Value', title_str='Resul... | bdc3f39883aed5b2e85624525c662c00f60d35e3 | <|skeleton|>
class SolutionDict:
"""Solution dictionary is an ordered dictionary that stores the optimization results Solution dictionary struture: D[name key]=time series data"""
def plot_2d(self, x_str='Time', y_str='Value', title_str='Results', figsize=(15, 7), legendlist=None):
"""step plot"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SolutionDict:
"""Solution dictionary is an ordered dictionary that stores the optimization results Solution dictionary struture: D[name key]=time series data"""
def plot_2d(self, x_str='Time', y_str='Value', title_str='Results', figsize=(15, 7), legendlist=None):
"""step plot"""
plt.figur... | the_stack_v2_python_sparse | Application/Application_DSOPT/formulation_general.py | whoiszyc/Repo_python | train | 5 |
971bbe032c4be62aaa482df3a569b3e9d2ed665d | [
"self.maximum_requests = maximum_requests\nself.maximum_age = maximum_age\nself.birth = None\nself.kill_signal = None\nself.handled_tasks = 0\nself.task = task_handler(*handler_args, **handler_kwargs)",
"self.birth = time.time()\nwhile self.handled_tasks < self.maximum_requests:\n if self.kill_signal:\n ... | <|body_start_0|>
self.maximum_requests = maximum_requests
self.maximum_age = maximum_age
self.birth = None
self.kill_signal = None
self.handled_tasks = 0
self.task = task_handler(*handler_args, **handler_kwargs)
<|end_body_0|>
<|body_start_1|>
self.birth = time.t... | Worker executing tasks | Worker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Worker:
"""Worker executing tasks"""
def __init__(self, task_handler, maximum_requests, maximum_age, handler_args, handler_kwargs):
"""Create a new Worker to execute tasks. :param task_handler: Task handler to fetch and execute tasks. :param maximum_requests: Maximum number of tasks ... | stack_v2_sparse_classes_75kplus_train_000028 | 1,467 | permissive | [
{
"docstring": "Create a new Worker to execute tasks. :param task_handler: Task handler to fetch and execute tasks. :param maximum_requests: Maximum number of tasks this worker can execute. :param maximum_age: Maximum age of the worker.",
"name": "__init__",
"signature": "def __init__(self, task_handler... | 2 | stack_v2_sparse_classes_30k_train_053341 | Implement the Python class `Worker` described below.
Class description:
Worker executing tasks
Method signatures and docstrings:
- def __init__(self, task_handler, maximum_requests, maximum_age, handler_args, handler_kwargs): Create a new Worker to execute tasks. :param task_handler: Task handler to fetch and execute... | Implement the Python class `Worker` described below.
Class description:
Worker executing tasks
Method signatures and docstrings:
- def __init__(self, task_handler, maximum_requests, maximum_age, handler_args, handler_kwargs): Create a new Worker to execute tasks. :param task_handler: Task handler to fetch and execute... | d8d3c9a86ab3235d4e36583fcee6f656e5209b7e | <|skeleton|>
class Worker:
"""Worker executing tasks"""
def __init__(self, task_handler, maximum_requests, maximum_age, handler_args, handler_kwargs):
"""Create a new Worker to execute tasks. :param task_handler: Task handler to fetch and execute tasks. :param maximum_requests: Maximum number of tasks ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Worker:
"""Worker executing tasks"""
def __init__(self, task_handler, maximum_requests, maximum_age, handler_args, handler_kwargs):
"""Create a new Worker to execute tasks. :param task_handler: Task handler to fetch and execute tasks. :param maximum_requests: Maximum number of tasks this worker c... | the_stack_v2_python_sparse | src/mercury/common/task_managers/base/worker.py | jr0d/mercury | train | 4 |
68edfb9888274b111beb4f45ebc052cbe9332fc0 | [
"factor_dict = get_factor_dict()\n_factor_provider = HDFDataProvider(factor_dict[factor_name]['abs_path'], start_time, end_time)\n_rebcalculator = load_rebcalculator(reb_type, start_time, end_time)\n_quote_provider = HDFDataProvider(factor_dict['ADJ_CLOSE']['abs_path'], start_time, end_time)\nif universe is None:\n... | <|body_start_0|>
factor_dict = get_factor_dict()
_factor_provider = HDFDataProvider(factor_dict[factor_name]['abs_path'], start_time, end_time)
_rebcalculator = load_rebcalculator(reb_type, start_time, end_time)
_quote_provider = HDFDataProvider(factor_dict['ADJ_CLOSE']['abs_path'], star... | 计算因子（rank）IC的衰减情况 具体如下： 假设计算10期IC衰减情况，则分别计算每一个滞后期对应的IC的序列，然后求平均值，返回这10期的 所有的IC平均值 | ICDecay | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ICDecay:
"""计算因子（rank）IC的衰减情况 具体如下： 假设计算10期IC衰减情况，则分别计算每一个滞后期对应的IC的序列，然后求平均值，返回这10期的 所有的IC平均值"""
def __init__(self, factor_name, start_time, end_time, universe=None, period_num=10, reb_type=MONTHLY):
"""Parameter --------- factor_name: str 因子名称，要求能在fmanager.get_factor_dict中找到 start_t... | stack_v2_sparse_classes_75kplus_train_000029 | 16,864 | no_license | [
{
"docstring": "Parameter --------- factor_name: str 因子名称，要求能在fmanager.get_factor_dict中找到 start_time: datetime like 测试的开始时间 end_time: datetime like 测试的结束时间 universe: str 使用的universe名称，要求能在fmanager.list_allfactor()中找到 period_num: int, default 10 IC衰减的最大期数 reb_type: str, default MONTHLY 换仓日计算的规则，目前只支持月度(MONTHLY)和... | 2 | stack_v2_sparse_classes_30k_test_000881 | Implement the Python class `ICDecay` described below.
Class description:
计算因子（rank）IC的衰减情况 具体如下： 假设计算10期IC衰减情况，则分别计算每一个滞后期对应的IC的序列，然后求平均值，返回这10期的 所有的IC平均值
Method signatures and docstrings:
- def __init__(self, factor_name, start_time, end_time, universe=None, period_num=10, reb_type=MONTHLY): Parameter --------- fact... | Implement the Python class `ICDecay` described below.
Class description:
计算因子（rank）IC的衰减情况 具体如下： 假设计算10期IC衰减情况，则分别计算每一个滞后期对应的IC的序列，然后求平均值，返回这10期的 所有的IC平均值
Method signatures and docstrings:
- def __init__(self, factor_name, start_time, end_time, universe=None, period_num=10, reb_type=MONTHLY): Parameter --------- fact... | 4080154dbf05781f3b48f551ee830d9f66687f87 | <|skeleton|>
class ICDecay:
"""计算因子（rank）IC的衰减情况 具体如下： 假设计算10期IC衰减情况，则分别计算每一个滞后期对应的IC的序列，然后求平均值，返回这10期的 所有的IC平均值"""
def __init__(self, factor_name, start_time, end_time, universe=None, period_num=10, reb_type=MONTHLY):
"""Parameter --------- factor_name: str 因子名称，要求能在fmanager.get_factor_dict中找到 start_t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ICDecay:
"""计算因子（rank）IC的衰减情况 具体如下： 假设计算10期IC衰减情况，则分别计算每一个滞后期对应的IC的序列，然后求平均值，返回这10期的 所有的IC平均值"""
def __init__(self, factor_name, start_time, end_time, universe=None, period_num=10, reb_type=MONTHLY):
"""Parameter --------- factor_name: str 因子名称，要求能在fmanager.get_factor_dict中找到 start_time: datetime... | the_stack_v2_python_sparse | factortest/correlation.py | rlcjj/GeneralLib | train | 0 |
9150f2afa3a0045999b1dc3d991be81023990781 | [
"midindex_0 = (len(A) + len(B) - 1) / 2\nmidindex_1 = (len(A) + len(B)) / 2\nif midindex_0 == midindex_1:\n return self._nthmin(midindex_0, A, B)\nelse:\n return (self._nthmin(midindex_0, A, B) + self._nthmin(midindex_1, A, B)) / 2.0",
"if not A:\n return B[n]\nif not B:\n return A[n]\nif n == 0:\n ... | <|body_start_0|>
midindex_0 = (len(A) + len(B) - 1) / 2
midindex_1 = (len(A) + len(B)) / 2
if midindex_0 == midindex_1:
return self._nthmin(midindex_0, A, B)
else:
return (self._nthmin(midindex_0, A, B) + self._nthmin(midindex_1, A, B)) / 2.0
<|end_body_0|>
<|bod... | Solver for https://oj.leetcode.com/problems/median-of-two-sorted-arrays/ | Solution | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Solver for https://oj.leetcode.com/problems/median-of-two-sorted-arrays/"""
def findMedianSortedArrays(self, A, B):
"""The main solver function."""
<|body_0|>
def _nthmin(n, A, B):
"""Returns nth(0-indexed) minimum element of sorted arrays A and B.""... | stack_v2_sparse_classes_75kplus_train_000030 | 1,082 | permissive | [
{
"docstring": "The main solver function.",
"name": "findMedianSortedArrays",
"signature": "def findMedianSortedArrays(self, A, B)"
},
{
"docstring": "Returns nth(0-indexed) minimum element of sorted arrays A and B.",
"name": "_nthmin",
"signature": "def _nthmin(n, A, B)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044460 | Implement the Python class `Solution` described below.
Class description:
Solver for https://oj.leetcode.com/problems/median-of-two-sorted-arrays/
Method signatures and docstrings:
- def findMedianSortedArrays(self, A, B): The main solver function.
- def _nthmin(n, A, B): Returns nth(0-indexed) minimum element of sor... | Implement the Python class `Solution` described below.
Class description:
Solver for https://oj.leetcode.com/problems/median-of-two-sorted-arrays/
Method signatures and docstrings:
- def findMedianSortedArrays(self, A, B): The main solver function.
- def _nthmin(n, A, B): Returns nth(0-indexed) minimum element of sor... | bdce2100d226f61e89cd7c6c21669756a2b6a30d | <|skeleton|>
class Solution:
"""Solver for https://oj.leetcode.com/problems/median-of-two-sorted-arrays/"""
def findMedianSortedArrays(self, A, B):
"""The main solver function."""
<|body_0|>
def _nthmin(n, A, B):
"""Returns nth(0-indexed) minimum element of sorted arrays A and B.""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""Solver for https://oj.leetcode.com/problems/median-of-two-sorted-arrays/"""
def findMedianSortedArrays(self, A, B):
"""The main solver function."""
midindex_0 = (len(A) + len(B) - 1) / 2
midindex_1 = (len(A) + len(B)) / 2
if midindex_0 == midindex_1:
... | the_stack_v2_python_sparse | src/median-of-two-sorted-arrays.py | starrify/leetcode | train | 0 |
1fb5c36c989205f77733c6677947d6c47ab6dc6d | [
"storage = get_messages(request)\nflash_message = {'error': [], 'success': [], 'warning': [], 'info': []}\nfor message in storage:\n flash_message[message.tags].append(message.__str__())\nreturn render(request, 'authentication/signup.html', {'error_message': flash_message['error'], 'success_message': flash_messa... | <|body_start_0|>
storage = get_messages(request)
flash_message = {'error': [], 'success': [], 'warning': [], 'info': []}
for message in storage:
flash_message[message.tags].append(message.__str__())
return render(request, 'authentication/signup.html', {'error_message': flash_... | RegistrationView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistrationView:
def get(self, request):
"""GET"""
<|body_0|>
def post(self, request):
"""Handle post request"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
storage = get_messages(request)
flash_message = {'error': [], 'success': [], 'warn... | stack_v2_sparse_classes_75kplus_train_000031 | 10,104 | no_license | [
{
"docstring": "GET",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Handle post request",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | null | Implement the Python class `RegistrationView` described below.
Class description:
Implement the RegistrationView class.
Method signatures and docstrings:
- def get(self, request): GET
- def post(self, request): Handle post request | Implement the Python class `RegistrationView` described below.
Class description:
Implement the RegistrationView class.
Method signatures and docstrings:
- def get(self, request): GET
- def post(self, request): Handle post request
<|skeleton|>
class RegistrationView:
def get(self, request):
"""GET"""
... | 992b0a23e4c22672d58af3a2ce3b48c5dbb8f748 | <|skeleton|>
class RegistrationView:
def get(self, request):
"""GET"""
<|body_0|>
def post(self, request):
"""Handle post request"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegistrationView:
def get(self, request):
"""GET"""
storage = get_messages(request)
flash_message = {'error': [], 'success': [], 'warning': [], 'info': []}
for message in storage:
flash_message[message.tags].append(message.__str__())
return render(request, '... | the_stack_v2_python_sparse | authentication/views.py | sadiachow15/platform | train | 0 | |
dc156979d8ed1c65d899a410e59272acabb493b5 | [
"if 'id_token' in params:\n user = _get_user_from_google_token(params['id_token'])\nelse:\n user = User.find_by_email_or_username(params['email_or_username'])\n if not validate_user(user, params['password']):\n return ({'error': 'Bad username or password'}, 401)\nreturn _build_login_response(user, p... | <|body_start_0|>
if 'id_token' in params:
user = _get_user_from_google_token(params['id_token'])
else:
user = User.find_by_email_or_username(params['email_or_username'])
if not validate_user(user, params['password']):
return ({'error': 'Bad username or... | Controller for authentication | AuthenticationsView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticationsView:
"""Controller for authentication"""
def post(self, **params):
"""Returns a cookie and a csrf token for double submit CSRF protection."""
<|body_0|>
def delete(self):
"""Unsets the cookie in response"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_75kplus_train_000032 | 2,913 | permissive | [
{
"docstring": "Returns a cookie and a csrf token for double submit CSRF protection.",
"name": "post",
"signature": "def post(self, **params)"
},
{
"docstring": "Unsets the cookie in response",
"name": "delete",
"signature": "def delete(self)"
}
] | 2 | null | Implement the Python class `AuthenticationsView` described below.
Class description:
Controller for authentication
Method signatures and docstrings:
- def post(self, **params): Returns a cookie and a csrf token for double submit CSRF protection.
- def delete(self): Unsets the cookie in response | Implement the Python class `AuthenticationsView` described below.
Class description:
Controller for authentication
Method signatures and docstrings:
- def post(self, **params): Returns a cookie and a csrf token for double submit CSRF protection.
- def delete(self): Unsets the cookie in response
<|skeleton|>
class Au... | 98173eb380bd6add52b21dc9045893949a8a2d30 | <|skeleton|>
class AuthenticationsView:
"""Controller for authentication"""
def post(self, **params):
"""Returns a cookie and a csrf token for double submit CSRF protection."""
<|body_0|>
def delete(self):
"""Unsets the cookie in response"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuthenticationsView:
"""Controller for authentication"""
def post(self, **params):
"""Returns a cookie and a csrf token for double submit CSRF protection."""
if 'id_token' in params:
user = _get_user_from_google_token(params['id_token'])
else:
user = User.f... | the_stack_v2_python_sparse | application/authentications/authentications_view.py | hpi-sam/ask-your-repository-api | train | 4 |
dfe1f0e000450e3c3b62e1b59b231293c1b91e77 | [
"super(TwoLayerNet, self).__init__()\nself.linear1 = torch.nn.Linear(D_in, H)\nself.linear2 = torch.nn.Linear(H, D_out)",
"h_relu = self.linear1(x).clamp(min=0)\ny_pred = self.linear2(h_relu)\nreturn y_pred"
] | <|body_start_0|>
super(TwoLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
<|end_body_0|>
<|body_start_1|>
h_relu = self.linear1(x).clamp(min=0)
y_pred = self.linear2(h_relu)
return y_pred
<|end_body_1|>
| TwoLayerNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
<|body_0|>
def forward(self, x):
"""In the forward function we accept a Variable of input data and we must return a Var... | stack_v2_sparse_classes_75kplus_train_000033 | 3,631 | no_license | [
{
"docstring": "In the constructor we instantiate two nn.Linear modules and assign them as member variables.",
"name": "__init__",
"signature": "def __init__(self, D_in, H, D_out)"
},
{
"docstring": "In the forward function we accept a Variable of input data and we must return a Variable of outp... | 2 | stack_v2_sparse_classes_30k_train_032865 | Implement the Python class `TwoLayerNet` described below.
Class description:
Implement the TwoLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): In the constructor we instantiate two nn.Linear modules and assign them as member variables.
- def forward(self, x): In the forward func... | Implement the Python class `TwoLayerNet` described below.
Class description:
Implement the TwoLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): In the constructor we instantiate two nn.Linear modules and assign them as member variables.
- def forward(self, x): In the forward func... | 868d54b6094cb92240600418f2849d4b196374be | <|skeleton|>
class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
<|body_0|>
def forward(self, x):
"""In the forward function we accept a Variable of input data and we must return a Var... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
super(TwoLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
def forw... | the_stack_v2_python_sparse | pytorchtest/simpleMnist.py | metatron/pythontest | train | 1 | |
abc4e4ef09fd4da1cc6df66a3f00982d0f022ea4 | [
"if graph.is_directed():\n raise ValueError('the graph is directed')\nself.graph = graph\nfor edge in self.graph.iteredges():\n if edge.source == edge.target:\n raise ValueError('a loop detected')\nself.independent_set = set()\nself.cardinality = 0\nself.source = None",
"used = set()\nif source is no... | <|body_start_0|>
if graph.is_directed():
raise ValueError('the graph is directed')
self.graph = graph
for edge in self.graph.iteredges():
if edge.source == edge.target:
raise ValueError('a loop detected')
self.independent_set = set()
self.c... | Find a maximal independent set. | UnorderedSequentialIndependentSet1 | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnorderedSequentialIndependentSet1:
"""Find a maximal independent set."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
def run(self, source=None):
"""Executable pseudocode."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_000034 | 3,887 | permissive | [
{
"docstring": "The algorithm initialization.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self, source=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026723 | Implement the Python class `UnorderedSequentialIndependentSet1` described below.
Class description:
Find a maximal independent set.
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization.
- def run(self, source=None): Executable pseudocode. | Implement the Python class `UnorderedSequentialIndependentSet1` described below.
Class description:
Find a maximal independent set.
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization.
- def run(self, source=None): Executable pseudocode.
<|skeleton|>
class UnorderedSequentialI... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class UnorderedSequentialIndependentSet1:
"""Find a maximal independent set."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
def run(self, source=None):
"""Executable pseudocode."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnorderedSequentialIndependentSet1:
"""Find a maximal independent set."""
def __init__(self, graph):
"""The algorithm initialization."""
if graph.is_directed():
raise ValueError('the graph is directed')
self.graph = graph
for edge in self.graph.iteredges():
... | the_stack_v2_python_sparse | graphtheory/independentsets/isetus.py | kgashok/graphs-dict | train | 0 |
d01e4f7e3b3ee39208237293aaf6869aefbce9e5 | [
"node1 = None\nwords = ['']\nself.assertEqual(make_dafsa.to_words(node1), words)",
"node1 = ('ab', [None])\nwords = ['ab']\nself.assertEqual(make_dafsa.to_words(node1), words)",
"node2 = ('cd', [None])\nnode1 = ('ab', [node2])\nwords = ['abcd']\nself.assertEqual(make_dafsa.to_words(node1), words)",
"node2 = (... | <|body_start_0|>
node1 = None
words = ['']
self.assertEqual(make_dafsa.to_words(node1), words)
<|end_body_0|>
<|body_start_1|>
node1 = ('ab', [None])
words = ['ab']
self.assertEqual(make_dafsa.to_words(node1), words)
<|end_body_1|>
<|body_start_2|>
node2 = ('cd'... | ToWordsTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ToWordsTest:
def testSink(self):
"""Tests the sink is exapnded to a list with an empty string."""
<|body_0|>
def testSingleNode(self):
"""Tests a single node is expanded to a list with the label string."""
<|body_1|>
def testChain(self):
"""Tests... | stack_v2_sparse_classes_75kplus_train_000035 | 20,781 | permissive | [
{
"docstring": "Tests the sink is exapnded to a list with an empty string.",
"name": "testSink",
"signature": "def testSink(self)"
},
{
"docstring": "Tests a single node is expanded to a list with the label string.",
"name": "testSingleNode",
"signature": "def testSingleNode(self)"
},
... | 5 | stack_v2_sparse_classes_30k_train_028702 | Implement the Python class `ToWordsTest` described below.
Class description:
Implement the ToWordsTest class.
Method signatures and docstrings:
- def testSink(self): Tests the sink is exapnded to a list with an empty string.
- def testSingleNode(self): Tests a single node is expanded to a list with the label string.
... | Implement the Python class `ToWordsTest` described below.
Class description:
Implement the ToWordsTest class.
Method signatures and docstrings:
- def testSink(self): Tests the sink is exapnded to a list with an empty string.
- def testSingleNode(self): Tests a single node is expanded to a list with the label string.
... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class ToWordsTest:
def testSink(self):
"""Tests the sink is exapnded to a list with an empty string."""
<|body_0|>
def testSingleNode(self):
"""Tests a single node is expanded to a list with the label string."""
<|body_1|>
def testChain(self):
"""Tests... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ToWordsTest:
def testSink(self):
"""Tests the sink is exapnded to a list with an empty string."""
node1 = None
words = ['']
self.assertEqual(make_dafsa.to_words(node1), words)
def testSingleNode(self):
"""Tests a single node is expanded to a list with the label str... | the_stack_v2_python_sparse | tools/media_engagement_preload/make_dafsa_unittest.py | chromium/chromium | train | 17,408 | |
76eea2440fe671983efef8d9ab4704e2a0b195a0 | [
"username = self.cleaned_data.get('username')\nif User.objects.filter(username__iexact=username):\n raise ValidationError(self.error_messages['duplicate_username'])\nreturn username",
"email = self.cleaned_data.get('email')\nif email and User.objects.filter(email__iexact=email):\n raise ValidationError(self... | <|body_start_0|>
username = self.cleaned_data.get('username')
if User.objects.filter(username__iexact=username):
raise ValidationError(self.error_messages['duplicate_username'])
return username
<|end_body_0|>
<|body_start_1|>
email = self.cleaned_data.get('email')
if... | Form for registering a new user account. Validates that the requested username and email is not already in use, and requires the password to be entered twice to catch typos. | RegistrationForm | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistrationForm:
"""Form for registering a new user account. Validates that the requested username and email is not already in use, and requires the password to be entered twice to catch typos."""
def clean_username(self):
"""Validate that the username is not already in use."""
... | stack_v2_sparse_classes_75kplus_train_000036 | 3,293 | permissive | [
{
"docstring": "Validate that the username is not already in use.",
"name": "clean_username",
"signature": "def clean_username(self)"
},
{
"docstring": "Validate that the supplied email address is unique for the site.",
"name": "clean_email",
"signature": "def clean_email(self)"
},
{... | 4 | stack_v2_sparse_classes_30k_train_026499 | Implement the Python class `RegistrationForm` described below.
Class description:
Form for registering a new user account. Validates that the requested username and email is not already in use, and requires the password to be entered twice to catch typos.
Method signatures and docstrings:
- def clean_username(self): ... | Implement the Python class `RegistrationForm` described below.
Class description:
Form for registering a new user account. Validates that the requested username and email is not already in use, and requires the password to be entered twice to catch typos.
Method signatures and docstrings:
- def clean_username(self): ... | a05a5161c415b546084bbe98b00e0671860c9bc6 | <|skeleton|>
class RegistrationForm:
"""Form for registering a new user account. Validates that the requested username and email is not already in use, and requires the password to be entered twice to catch typos."""
def clean_username(self):
"""Validate that the username is not already in use."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegistrationForm:
"""Form for registering a new user account. Validates that the requested username and email is not already in use, and requires the password to be entered twice to catch typos."""
def clean_username(self):
"""Validate that the username is not already in use."""
username ... | the_stack_v2_python_sparse | DistributedSocialNetworking/Hindlebook/forms/auth_forms.py | Roshack/cmput410-project | train | 0 |
041025a714706ad0a5beaa4f852d2f2f4cd0a4b6 | [
"num1_len = len(nums1)\nnum2_len = len(nums2)\nif k > num1_len + num2_len:\n return -1\nret = [0] * k\nfor i in xrange(0, k + 1):\n j = k - i\n if i > num1_len or j > num2_len:\n continue\n left = self.maxsubstringNum(nums1, i)\n right = self.maxsubstringNum(nums2, k - i)\n num = self.merge... | <|body_start_0|>
num1_len = len(nums1)
num2_len = len(nums2)
if k > num1_len + num2_len:
return -1
ret = [0] * k
for i in xrange(0, k + 1):
j = k - i
if i > num1_len or j > num2_len:
continue
left = self.maxsubstring... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxNumber(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def merge(self, left, right):
""":type left: List[int], the left part of maxinum :type right: List[int], the right part of th... | stack_v2_sparse_classes_75kplus_train_000037 | 2,089 | permissive | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]",
"name": "maxNumber",
"signature": "def maxNumber(self, nums1, nums2, k)"
},
{
"docstring": ":type left: List[int], the left part of maxinum :type right: List[int], the right part of the maxinum :rtype:... | 3 | stack_v2_sparse_classes_30k_train_005755 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxNumber(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]
- def merge(self, left, right): :type left: List[int], the left... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxNumber(self, nums1, nums2, k): :type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]
- def merge(self, left, right): :type left: List[int], the left... | 86f1cb98de801f58c39d9a48ce9de12df7303d20 | <|skeleton|>
class Solution:
def maxNumber(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def merge(self, left, right):
""":type left: List[int], the left part of maxinum :type right: List[int], the right part of th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxNumber(self, nums1, nums2, k):
""":type nums1: List[int] :type nums2: List[int] :type k: int :rtype: List[int]"""
num1_len = len(nums1)
num2_len = len(nums2)
if k > num1_len + num2_len:
return -1
ret = [0] * k
for i in xrange(0, k + ... | the_stack_v2_python_sparse | 321-Create-Maximum-Number/solution.py | Tanych/CodeTracking | train | 0 | |
888f1fd253e04c41ad1badbf3034942cdaf23cb0 | [
"if not asyncEstimate:\n error, estimation = self._coreEstimator.estimate(imageWithFaceDetection.image.coreImage, imageWithFaceDetection.boundingBox.coreEstimation)\n return POST_PROCESSING.postProcessing(error, estimation)\ntask = self._coreEstimator.asyncEstimate(imageWithFaceDetection.image.coreImage, imag... | <|body_start_0|>
if not asyncEstimate:
error, estimation = self._coreEstimator.estimate(imageWithFaceDetection.image.coreImage, imageWithFaceDetection.boundingBox.coreEstimation)
return POST_PROCESSING.postProcessing(error, estimation)
task = self._coreEstimator.asyncEstimate(ima... | Fisheye effect estimator. Work on face detections | FisheyeEstimator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FisheyeEstimator:
"""Fisheye effect estimator. Work on face detections"""
def estimate(self, imageWithFaceDetection: ImageWithFaceDetection, asyncEstimate: bool=False) -> Union[Fisheye, AsyncTask[Fisheye]]:
"""Estimate fisheye. Args: imageWithFaceDetection: image with face detection ... | stack_v2_sparse_classes_75kplus_train_000038 | 3,851 | permissive | [
{
"docstring": "Estimate fisheye. Args: imageWithFaceDetection: image with face detection asyncEstimate: estimate or run estimation in background Returns: fisheye estimation if asyncEstimate is false otherwise async task Raises: LunaSDKException: if estimation is failed",
"name": "estimate",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_004715 | Implement the Python class `FisheyeEstimator` described below.
Class description:
Fisheye effect estimator. Work on face detections
Method signatures and docstrings:
- def estimate(self, imageWithFaceDetection: ImageWithFaceDetection, asyncEstimate: bool=False) -> Union[Fisheye, AsyncTask[Fisheye]]: Estimate fisheye.... | Implement the Python class `FisheyeEstimator` described below.
Class description:
Fisheye effect estimator. Work on face detections
Method signatures and docstrings:
- def estimate(self, imageWithFaceDetection: ImageWithFaceDetection, asyncEstimate: bool=False) -> Union[Fisheye, AsyncTask[Fisheye]]: Estimate fisheye.... | 7a4bebc92ae7a96d8d9c18a024208308942f90cd | <|skeleton|>
class FisheyeEstimator:
"""Fisheye effect estimator. Work on face detections"""
def estimate(self, imageWithFaceDetection: ImageWithFaceDetection, asyncEstimate: bool=False) -> Union[Fisheye, AsyncTask[Fisheye]]:
"""Estimate fisheye. Args: imageWithFaceDetection: image with face detection ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FisheyeEstimator:
"""Fisheye effect estimator. Work on face detections"""
def estimate(self, imageWithFaceDetection: ImageWithFaceDetection, asyncEstimate: bool=False) -> Union[Fisheye, AsyncTask[Fisheye]]:
"""Estimate fisheye. Args: imageWithFaceDetection: image with face detection asyncEstimate... | the_stack_v2_python_sparse | lunavl/sdk/estimators/face_estimators/fisheye.py | matemax/lunasdk | train | 16 |
baaaf14016aefe59dbbb7b16964c11dd56f8af92 | [
"self.ylim_down = ylim_down\nself.ylim_up = ylim_up\nself.xlim_down = xlim_down\nself.xlim_up = xlim_up\nself.background = background\nself.min_value = min_value\nself.max_value = max_value\nself.extend = extend\nself.legend_label = self._keyword_to_legend_label(background)",
"if keyword == 'sig_vm':\n return ... | <|body_start_0|>
self.ylim_down = ylim_down
self.ylim_up = ylim_up
self.xlim_down = xlim_down
self.xlim_up = xlim_up
self.background = background
self.min_value = min_value
self.max_value = max_value
self.extend = extend
self.legend_label = self._k... | PlotSettings | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlotSettings:
def __init__(self, xlim_down: float=None, xlim_up: float=None, ylim_down: float=None, ylim_up: float=None, background: str='eps_vm', min_value: float=None, max_value: float=None, extend: str=None):
"""Define plot settings for Plotter class object. Args: xlim_down: lower lim... | stack_v2_sparse_classes_75kplus_train_000039 | 15,762 | permissive | [
{
"docstring": "Define plot settings for Plotter class object. Args: xlim_down: lower limit of x-axis xlim_up: upper limit of x-axis ylim_down: bottom of plot in [mm] (negative) ylim_up: top of plot in [mm] background: background plotted (e.g. 'sig_vm', 'eps_vm', 'disp_y', 'disp_x') min_value: minimum value of ... | 2 | null | Implement the Python class `PlotSettings` described below.
Class description:
Implement the PlotSettings class.
Method signatures and docstrings:
- def __init__(self, xlim_down: float=None, xlim_up: float=None, ylim_down: float=None, ylim_up: float=None, background: str='eps_vm', min_value: float=None, max_value: flo... | Implement the Python class `PlotSettings` described below.
Class description:
Implement the PlotSettings class.
Method signatures and docstrings:
- def __init__(self, xlim_down: float=None, xlim_up: float=None, ylim_down: float=None, ylim_up: float=None, background: str='eps_vm', min_value: float=None, max_value: flo... | 7556651812bc1c0d38159d718a47847524fd1dd0 | <|skeleton|>
class PlotSettings:
def __init__(self, xlim_down: float=None, xlim_up: float=None, ylim_down: float=None, ylim_up: float=None, background: str='eps_vm', min_value: float=None, max_value: float=None, extend: str=None):
"""Define plot settings for Plotter class object. Args: xlim_down: lower lim... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PlotSettings:
def __init__(self, xlim_down: float=None, xlim_up: float=None, ylim_down: float=None, ylim_up: float=None, background: str='eps_vm', min_value: float=None, max_value: float=None, extend: str=None):
"""Define plot settings for Plotter class object. Args: xlim_down: lower limit of x-axis x... | the_stack_v2_python_sparse | crackpy/fracture_analysis/plot.py | dlr-wf/crackpy | train | 40 | |
0e3569fc19211dd8b1c16ac6b855860ddf8929e7 | [
"if not root:\n return ''\nfrom collections import deque\ndeq = deque([root])\nres = [str(root.val), 'None']\nwhile deq:\n size = len(deq)\n for _ in range(size):\n node = deq.popleft()\n if node.children:\n res += [str(child.val) for child in node.children]\n deq += nod... | <|body_start_0|>
if not root:
return ''
from collections import deque
deq = deque([root])
res = [str(root.val), 'None']
while deq:
size = len(deq)
for _ in range(size):
node = deq.popleft()
if node.children:
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|e... | stack_v2_sparse_classes_75kplus_train_000040 | 2,282 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root: 'Node') -> str"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: Node",
"name": "deserialize",
"signature": "def des... | 2 | stack_v2_sparse_classes_30k_train_027380 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to tre... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: 'Node') -> str: Encodes a tree to a single string. :type root: Node :rtype: str
- def deserialize(self, data: str) -> 'Node': Decodes your encoded data to tre... | 4cf03307c5caeccaa87ccce249322bd02397f489 | <|skeleton|>
class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> 'Node':
"""Decodes your encoded data to tree. :type data: str :rtype: Node"""
<|body_1|>
<|e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root: 'Node') -> str:
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
if not root:
return ''
from collections import deque
deq = deque([root])
res = [str(root.val), 'None']
while deq:
size ... | the_stack_v2_python_sparse | 0428. Serialize and Deserialize N-ary Tree.py | aidardarmesh/leetcode2 | train | 0 | |
488451854a3c0df8eaf4c34fbf79defc064719fc | [
"self.scorer = UniEvaluator(model_name_or_path='MingZhong/unieval-fact' if model_name_or_path == '' else model_name_or_path, max_length=max_length, device=device, cache_dir=cache_dir)\nself.task = 'fact'\nself.dim = 'consistency'",
"n_data = len(data)\neval_scores = [{} for _ in range(n_data)]\nsrc_list, output_l... | <|body_start_0|>
self.scorer = UniEvaluator(model_name_or_path='MingZhong/unieval-fact' if model_name_or_path == '' else model_name_or_path, max_length=max_length, device=device, cache_dir=cache_dir)
self.task = 'fact'
self.dim = 'consistency'
<|end_body_0|>
<|body_start_1|>
n_data = le... | FactEvaluator | [
"BSD-3-Clause",
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0",
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FactEvaluator:
def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None):
"""Set up evaluator for factual consistency detection"""
<|body_0|>
def evaluate(self, data, category):
"""Get the factual consistency score (only 1 dimension for... | stack_v2_sparse_classes_75kplus_train_000041 | 14,573 | permissive | [
{
"docstring": "Set up evaluator for factual consistency detection",
"name": "__init__",
"signature": "def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None)"
},
{
"docstring": "Get the factual consistency score (only 1 dimension for this task) category: The cat... | 2 | stack_v2_sparse_classes_30k_train_007023 | Implement the Python class `FactEvaluator` described below.
Class description:
Implement the FactEvaluator class.
Method signatures and docstrings:
- def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None): Set up evaluator for factual consistency detection
- def evaluate(self, data, ... | Implement the Python class `FactEvaluator` described below.
Class description:
Implement the FactEvaluator class.
Method signatures and docstrings:
- def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None): Set up evaluator for factual consistency detection
- def evaluate(self, data, ... | c7b60f75470f067d1342705708810a660eabd684 | <|skeleton|>
class FactEvaluator:
def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None):
"""Set up evaluator for factual consistency detection"""
<|body_0|>
def evaluate(self, data, category):
"""Get the factual consistency score (only 1 dimension for... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FactEvaluator:
def __init__(self, model_name_or_path, max_length=1024, device='cuda:0', cache_dir=None):
"""Set up evaluator for factual consistency detection"""
self.scorer = UniEvaluator(model_name_or_path='MingZhong/unieval-fact' if model_name_or_path == '' else model_name_or_path, max_leng... | the_stack_v2_python_sparse | applications/Chat/evaluate/unieval/evaluator.py | hpcaitech/ColossalAI | train | 32,044 | |
98ff02c37875270d80470b39fb8aa52d86c0424f | [
"l = [5, 2, 8, 2, 6, 1, 454, 8, 23]\nfinal = [1, 2, 2, 5, 6, 8, 8, 23, 454]\nself.assertEqual(radix_sort(l), final)",
"l = [5, 8, 2, 6, 3, 7, 3, 7, 1, 5, 789, 2344, 6, 1, 6, 7, 234, 8, 56, 4, 8, 234, 0, 12, 0]\nfinal = [0, 0, 1, 1, 2, 3, 3, 4, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 12, 56, 234, 234, 789, 2344]\nself.as... | <|body_start_0|>
l = [5, 2, 8, 2, 6, 1, 454, 8, 23]
final = [1, 2, 2, 5, 6, 8, 8, 23, 454]
self.assertEqual(radix_sort(l), final)
<|end_body_0|>
<|body_start_1|>
l = [5, 8, 2, 6, 3, 7, 3, 7, 1, 5, 789, 2344, 6, 1, 6, 7, 234, 8, 56, 4, 8, 234, 0, 12, 0]
final = [0, 0, 1, 1, 2, 3,... | TestRadixSort | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestRadixSort:
def test_short_list(self):
"""Tests if a short list of integers has been sorted"""
<|body_0|>
def test_long_list(self):
"""Tests if a long list of integers has been sorted"""
<|body_1|>
def test_float_list(self):
"""Tests if a list... | stack_v2_sparse_classes_75kplus_train_000042 | 1,656 | permissive | [
{
"docstring": "Tests if a short list of integers has been sorted",
"name": "test_short_list",
"signature": "def test_short_list(self)"
},
{
"docstring": "Tests if a long list of integers has been sorted",
"name": "test_long_list",
"signature": "def test_long_list(self)"
},
{
"do... | 3 | stack_v2_sparse_classes_30k_train_008499 | Implement the Python class `TestRadixSort` described below.
Class description:
Implement the TestRadixSort class.
Method signatures and docstrings:
- def test_short_list(self): Tests if a short list of integers has been sorted
- def test_long_list(self): Tests if a long list of integers has been sorted
- def test_flo... | Implement the Python class `TestRadixSort` described below.
Class description:
Implement the TestRadixSort class.
Method signatures and docstrings:
- def test_short_list(self): Tests if a short list of integers has been sorted
- def test_long_list(self): Tests if a long list of integers has been sorted
- def test_flo... | 189fe8bccb54a622d524ac813a8805a86f0a4a98 | <|skeleton|>
class TestRadixSort:
def test_short_list(self):
"""Tests if a short list of integers has been sorted"""
<|body_0|>
def test_long_list(self):
"""Tests if a long list of integers has been sorted"""
<|body_1|>
def test_float_list(self):
"""Tests if a list... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestRadixSort:
def test_short_list(self):
"""Tests if a short list of integers has been sorted"""
l = [5, 2, 8, 2, 6, 1, 454, 8, 23]
final = [1, 2, 2, 5, 6, 8, 8, 23, 454]
self.assertEqual(radix_sort(l), final)
def test_long_list(self):
"""Tests if a long list of i... | the_stack_v2_python_sparse | algorithms/sort_algorithms/radix_sort/test_radix_sort.py | nwthomas/data-structures-and-algorithms | train | 13 | |
27a55142a0835d99f741eafdf3e263040f7fae36 | [
"actual = a1.stock_price_summary([0.01, 0.03, -0.02, -0.14, 0, 0, 0.1, -0.01])\nexpected = (0.14, -0.17)\nself.assertEqual(actual, expected)",
"actual = actual = a1.stock_price_summary([-0.01, -0.03, 0.02, 0.14, 0, 0, -0.1, 0.01])\nexpected = (0.17, -0.14)\nself.assertEqual(actual, expected)",
"actual = a1.stoc... | <|body_start_0|>
actual = a1.stock_price_summary([0.01, 0.03, -0.02, -0.14, 0, 0, 0.1, -0.01])
expected = (0.14, -0.17)
self.assertEqual(actual, expected)
<|end_body_0|>
<|body_start_1|>
actual = actual = a1.stock_price_summary([-0.01, -0.03, 0.02, 0.14, 0, 0, -0.1, 0.01])
expec... | Test class for function a1.stock_price_summary. | TestStockPriceSummary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestStockPriceSummary:
"""Test class for function a1.stock_price_summary."""
def test_random1(self):
"""Test the function with random numbers"""
<|body_0|>
def test_random2(self):
"""Test the function with inverted random numbers"""
<|body_1|>
def te... | stack_v2_sparse_classes_75kplus_train_000043 | 1,114 | no_license | [
{
"docstring": "Test the function with random numbers",
"name": "test_random1",
"signature": "def test_random1(self)"
},
{
"docstring": "Test the function with inverted random numbers",
"name": "test_random2",
"signature": "def test_random2(self)"
},
{
"docstring": "The the funct... | 4 | stack_v2_sparse_classes_30k_train_030987 | Implement the Python class `TestStockPriceSummary` described below.
Class description:
Test class for function a1.stock_price_summary.
Method signatures and docstrings:
- def test_random1(self): Test the function with random numbers
- def test_random2(self): Test the function with inverted random numbers
- def test_z... | Implement the Python class `TestStockPriceSummary` described below.
Class description:
Test class for function a1.stock_price_summary.
Method signatures and docstrings:
- def test_random1(self): Test the function with random numbers
- def test_random2(self): Test the function with inverted random numbers
- def test_z... | ba0e48825e3f90f9da0e7506c89354622198c4a5 | <|skeleton|>
class TestStockPriceSummary:
"""Test class for function a1.stock_price_summary."""
def test_random1(self):
"""Test the function with random numbers"""
<|body_0|>
def test_random2(self):
"""Test the function with inverted random numbers"""
<|body_1|>
def te... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestStockPriceSummary:
"""Test class for function a1.stock_price_summary."""
def test_random1(self):
"""Test the function with random numbers"""
actual = a1.stock_price_summary([0.01, 0.03, -0.02, -0.14, 0, 0, 0.1, -0.01])
expected = (0.14, -0.17)
self.assertEqual(actual, ... | the_stack_v2_python_sparse | Coursera/Python3/Second Course Asignments/Assighment 1/test_stock_price_summary.py | Vutov/SideProjects | train | 0 |
e7aa4170c27ff36a2796c8ca58ed9dd6da40739c | [
"if isinstance(cmd, Command):\n ret = cmd.run(arg_str, cwd=cwd, environ=environ, **kwargs)\nelif hasattr(cmd, 'run'):\n ret = cmd.run(arg_str, cwd=cwd, environ=environ, **kwargs)\nelse:\n cmd = Command(cmd, cwd=cwd, environ=environ)\n ret = cmd.run(arg_str, **kwargs)\nreturn ret",
"if isinstance(cmd, ... | <|body_start_0|>
if isinstance(cmd, Command):
ret = cmd.run(arg_str, cwd=cwd, environ=environ, **kwargs)
elif hasattr(cmd, 'run'):
ret = cmd.run(arg_str, cwd=cwd, environ=environ, **kwargs)
else:
cmd = Command(cmd, cwd=cwd, environ=environ)
ret = c... | ClientData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClientData:
def run_command(self, cmd, arg_str='', cwd='', environ=None, **kwargs):
"""Run a command on the command line :param cmd: mixed, the command you want to run :param arg_str: string, extra flags that will be appended to the cmd :param **kwargs: allows you to pass into underlying... | stack_v2_sparse_classes_75kplus_train_000044 | 3,565 | permissive | [
{
"docstring": "Run a command on the command line :param cmd: mixed, the command you want to run :param arg_str: string, extra flags that will be appended to the cmd :param **kwargs: allows you to pass into underlying Command.run() method :returns: string, the output from the command",
"name": "run_command"... | 3 | null | Implement the Python class `ClientData` described below.
Class description:
Implement the ClientData class.
Method signatures and docstrings:
- def run_command(self, cmd, arg_str='', cwd='', environ=None, **kwargs): Run a command on the command line :param cmd: mixed, the command you want to run :param arg_str: strin... | Implement the Python class `ClientData` described below.
Class description:
Implement the ClientData class.
Method signatures and docstrings:
- def run_command(self, cmd, arg_str='', cwd='', environ=None, **kwargs): Run a command on the command line :param cmd: mixed, the command you want to run :param arg_str: strin... | 41ca4bbbff595c2bb50403c5353f19670ec9e2ef | <|skeleton|>
class ClientData:
def run_command(self, cmd, arg_str='', cwd='', environ=None, **kwargs):
"""Run a command on the command line :param cmd: mixed, the command you want to run :param arg_str: string, extra flags that will be appended to the cmd :param **kwargs: allows you to pass into underlying... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClientData:
def run_command(self, cmd, arg_str='', cwd='', environ=None, **kwargs):
"""Run a command on the command line :param cmd: mixed, the command you want to run :param arg_str: string, extra flags that will be appended to the cmd :param **kwargs: allows you to pass into underlying Command.run()... | the_stack_v2_python_sparse | testdata/client.py | Jaymon/testdata | train | 10 | |
8a35cc0467f05bc6c013748ef70aa4c80b707008 | [
"if head.next is None or head.next is None:\n return head\nnew_head = self.reverseList(head.next)\nhead.next.next = head\nhead.next = None\nreturn new_head",
"if head is None:\n return head\npre = None\ncur = head\nwhile cur is not None:\n next_node = cur.next\n cur.next = pre\n pre = cur\n cur ... | <|body_start_0|>
if head.next is None or head.next is None:
return head
new_head = self.reverseList(head.next)
head.next.next = head
head.next = None
return new_head
<|end_body_0|>
<|body_start_1|>
if head is None:
return head
pre = None
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head: ListNode) -> ListNode:
"""递归"""
<|body_0|>
def reverseList1(self, head: ListNode) -> ListNode:
"""迭代"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if head.next is None or head.next is None:
return ... | stack_v2_sparse_classes_75kplus_train_000045 | 941 | no_license | [
{
"docstring": "递归",
"name": "reverseList",
"signature": "def reverseList(self, head: ListNode) -> ListNode"
},
{
"docstring": "迭代",
"name": "reverseList1",
"signature": "def reverseList1(self, head: ListNode) -> ListNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_021754 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head: ListNode) -> ListNode: 递归
- def reverseList1(self, head: ListNode) -> ListNode: 迭代 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head: ListNode) -> ListNode: 递归
- def reverseList1(self, head: ListNode) -> ListNode: 迭代
<|skeleton|>
class Solution:
def reverseList(self, head: List... | 3fa96c81f92595cf076ad675ba332e2b0eb0e071 | <|skeleton|>
class Solution:
def reverseList(self, head: ListNode) -> ListNode:
"""递归"""
<|body_0|>
def reverseList1(self, head: ListNode) -> ListNode:
"""迭代"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reverseList(self, head: ListNode) -> ListNode:
"""递归"""
if head.next is None or head.next is None:
return head
new_head = self.reverseList(head.next)
head.next.next = head
head.next = None
return new_head
def reverseList1(self, hea... | the_stack_v2_python_sparse | 2020-03/3月每日一题复习/206反转链表.py | Annihilation7/Leetcode-Love | train | 0 | |
6ce4caed4560e626fd14e4b138382d5f3e8204b2 | [
"super(FunctionComponent, self).__init__(opts)\nself.opts = opts\nself.options = opts.get(CONFIG_DATA_SECTION, {})",
"self.opts = opts\nself.options = opts.get(CONFIG_DATA_SECTION, {})\nmaas360_utils = MaaS360Utils.get_the_maas360_utils()\nmaas360_utils.reload_options(opts)\nmaas360_utils.reconnect()",
"try:\n ... | <|body_start_0|>
super(FunctionComponent, self).__init__(opts)
self.opts = opts
self.options = opts.get(CONFIG_DATA_SECTION, {})
<|end_body_0|>
<|body_start_1|>
self.opts = opts
self.options = opts.get(CONFIG_DATA_SECTION, {})
maas360_utils = MaaS360Utils.get_the_maas360... | Component that implements Resilient function 'maas360_delete_app | FunctionComponent | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FunctionComponent:
"""Component that implements Resilient function 'maas360_delete_app"""
def __init__(self, opts):
"""constructor provides access to the configuration options"""
<|body_0|>
def _reload(self, event, opts):
"""Configuration options have changed, sa... | stack_v2_sparse_classes_75kplus_train_000046 | 3,056 | permissive | [
{
"docstring": "constructor provides access to the configuration options",
"name": "__init__",
"signature": "def __init__(self, opts)"
},
{
"docstring": "Configuration options have changed, save new values",
"name": "_reload",
"signature": "def _reload(self, event, opts)"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_038912 | Implement the Python class `FunctionComponent` described below.
Class description:
Component that implements Resilient function 'maas360_delete_app
Method signatures and docstrings:
- def __init__(self, opts): constructor provides access to the configuration options
- def _reload(self, event, opts): Configuration opt... | Implement the Python class `FunctionComponent` described below.
Class description:
Component that implements Resilient function 'maas360_delete_app
Method signatures and docstrings:
- def __init__(self, opts): constructor provides access to the configuration options
- def _reload(self, event, opts): Configuration opt... | 6878c78b94eeca407998a41ce8db2cc00f2b6758 | <|skeleton|>
class FunctionComponent:
"""Component that implements Resilient function 'maas360_delete_app"""
def __init__(self, opts):
"""constructor provides access to the configuration options"""
<|body_0|>
def _reload(self, event, opts):
"""Configuration options have changed, sa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FunctionComponent:
"""Component that implements Resilient function 'maas360_delete_app"""
def __init__(self, opts):
"""constructor provides access to the configuration options"""
super(FunctionComponent, self).__init__(opts)
self.opts = opts
self.options = opts.get(CONFIG_... | the_stack_v2_python_sparse | fn_maas360/fn_maas360/components/maas360_delete_app.py | ibmresilient/resilient-community-apps | train | 81 |
455f4aaa167b657db10c13ddbc928827ea84f387 | [
"self.config = config\nself.log = log\nself.reg_file = reg_file\nself.alignment = reg_file.alignment\nself.entry = []\nself.reset()\nself.num_read = 0\nself.num_write = 0\nreturn",
"perf_metrics = {}\nperf_metrics['num_read'] = self.num_read\nperf_metrics['num_write'] = self.num_write\nreturn {'reg_track_table': ... | <|body_start_0|>
self.config = config
self.log = log
self.reg_file = reg_file
self.alignment = reg_file.alignment
self.entry = []
self.reset()
self.num_read = 0
self.num_write = 0
return
<|end_body_0|>
<|body_start_1|>
perf_metrics = {}
... | RegTrackTable | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegTrackTable:
def __init__(self, config, log, reg_file):
"""This table contains each entry per warp to track its regiser location validity information."""
<|body_0|>
def get_perf_metrics(self):
"""Get a dictionary of performance metrics."""
<|body_1|>
d... | stack_v2_sparse_classes_75kplus_train_000047 | 11,641 | no_license | [
{
"docstring": "This table contains each entry per warp to track its regiser location validity information.",
"name": "__init__",
"signature": "def __init__(self, config, log, reg_file)"
},
{
"docstring": "Get a dictionary of performance metrics.",
"name": "get_perf_metrics",
"signature"... | 3 | null | Implement the Python class `RegTrackTable` described below.
Class description:
Implement the RegTrackTable class.
Method signatures and docstrings:
- def __init__(self, config, log, reg_file): This table contains each entry per warp to track its regiser location validity information.
- def get_perf_metrics(self): Get... | Implement the Python class `RegTrackTable` described below.
Class description:
Implement the RegTrackTable class.
Method signatures and docstrings:
- def __init__(self, config, log, reg_file): This table contains each entry per warp to track its regiser location validity information.
- def get_perf_metrics(self): Get... | a357e73239a03384bae73d7006667cfeb07df635 | <|skeleton|>
class RegTrackTable:
def __init__(self, config, log, reg_file):
"""This table contains each entry per warp to track its regiser location validity information."""
<|body_0|>
def get_perf_metrics(self):
"""Get a dictionary of performance metrics."""
<|body_1|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegTrackTable:
def __init__(self, config, log, reg_file):
"""This table contains each entry per warp to track its regiser location validity information."""
self.config = config
self.log = log
self.reg_file = reg_file
self.alignment = reg_file.alignment
self.entr... | the_stack_v2_python_sparse | simulator/subcore_table.py | GD06/MPU-ASPLOS-2021 | train | 3 | |
206e94ef8f92fc4b0e778fd4a47822f5bb777b4e | [
"if not circuit.instructions:\n return ''\ncircuit_qubits = circuit.qubits\ncircuit_qubits.sort()\ny_axis_width = len(str(int(max(circuit_qubits))))\ny_axis_str = '{0:{width}} : |\\n'.format('T', width=y_axis_width + 1)\nfor qubit in circuit_qubits:\n y_axis_str += '{0:{width}}\\n'.format(' ', width=y_axis_wi... | <|body_start_0|>
if not circuit.instructions:
return ''
circuit_qubits = circuit.qubits
circuit_qubits.sort()
y_axis_width = len(str(int(max(circuit_qubits))))
y_axis_str = '{0:{width}} : |\n'.format('T', width=y_axis_width + 1)
for qubit in circuit_qubits:
... | Builds ASCII string circuit diagrams. | AsciiCircuitDiagram | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsciiCircuitDiagram:
"""Builds ASCII string circuit diagrams."""
def build_diagram(circuit) -> str:
"""Build an ASCII string circuit diagram. Args: circuit (Circuit): Circuit to build a diagram of. Returns: str: ASCII string circuit diagram."""
<|body_0|>
def _ascii_diag... | stack_v2_sparse_classes_75kplus_train_000048 | 4,140 | permissive | [
{
"docstring": "Build an ASCII string circuit diagram. Args: circuit (Circuit): Circuit to build a diagram of. Returns: str: ASCII string circuit diagram.",
"name": "build_diagram",
"signature": "def build_diagram(circuit) -> str"
},
{
"docstring": "Return an ASCII string diagram of the circuit ... | 2 | null | Implement the Python class `AsciiCircuitDiagram` described below.
Class description:
Builds ASCII string circuit diagrams.
Method signatures and docstrings:
- def build_diagram(circuit) -> str: Build an ASCII string circuit diagram. Args: circuit (Circuit): Circuit to build a diagram of. Returns: str: ASCII string ci... | Implement the Python class `AsciiCircuitDiagram` described below.
Class description:
Builds ASCII string circuit diagrams.
Method signatures and docstrings:
- def build_diagram(circuit) -> str: Build an ASCII string circuit diagram. Args: circuit (Circuit): Circuit to build a diagram of. Returns: str: ASCII string ci... | 0c1c805fd5dfce465a8955ee3faf81037023a23e | <|skeleton|>
class AsciiCircuitDiagram:
"""Builds ASCII string circuit diagrams."""
def build_diagram(circuit) -> str:
"""Build an ASCII string circuit diagram. Args: circuit (Circuit): Circuit to build a diagram of. Returns: str: ASCII string circuit diagram."""
<|body_0|>
def _ascii_diag... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AsciiCircuitDiagram:
"""Builds ASCII string circuit diagrams."""
def build_diagram(circuit) -> str:
"""Build an ASCII string circuit diagram. Args: circuit (Circuit): Circuit to build a diagram of. Returns: str: ASCII string circuit diagram."""
if not circuit.instructions:
ret... | the_stack_v2_python_sparse | artifacts/minimal_bugfixes/amazon-braket-sdk-python/amazon-braket-sdk-python#44/before/ascii_circuit_diagram.py | MattePalte/Bugs-Quantum-Computing-Platforms | train | 4 |
7ba2bd6877db278af819581d2a973aa771ccc809 | [
"import sys\nn = len(nums)\nif n == 0:\n return 0\nnums.insert(0, -sys.maxsize)\nT = []\nfor i in range(n + 1):\n T.append([0] * (n + 2))\nfor j in range(n, 0, -1):\n for i in range(0, j):\n if nums[i] >= nums[j]:\n T[i][j] = T[i][j + 1]\n else:\n T[i][j] = max(T[i][j + ... | <|body_start_0|>
import sys
n = len(nums)
if n == 0:
return 0
nums.insert(0, -sys.maxsize)
T = []
for i in range(n + 1):
T.append([0] * (n + 2))
for j in range(n, 0, -1):
for i in range(0, j):
if nums[i] >= nums[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
"""DP approach Time: O(n^2) Space: O(n^2) TLE :type nums: List[int] :rtype: int"""
<|body_0|>
def lengthOfLIS2(self, nums):
"""DP approach 2: define dp[i] as LIS of nums[i...n] that starts with nums[i]. DP formula: dp[i] = 1 + m... | stack_v2_sparse_classes_75kplus_train_000049 | 1,733 | no_license | [
{
"docstring": "DP approach Time: O(n^2) Space: O(n^2) TLE :type nums: List[int] :rtype: int",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums)"
},
{
"docstring": "DP approach 2: define dp[i] as LIS of nums[i...n] that starts with nums[i]. DP formula: dp[i] = 1 + max{dp[j] | j > ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): DP approach Time: O(n^2) Space: O(n^2) TLE :type nums: List[int] :rtype: int
- def lengthOfLIS2(self, nums): DP approach 2: define dp[i] as LIS of nu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): DP approach Time: O(n^2) Space: O(n^2) TLE :type nums: List[int] :rtype: int
- def lengthOfLIS2(self, nums): DP approach 2: define dp[i] as LIS of nu... | 143aa25f92f3827aa379f29c67a9b7ec3757fef9 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
"""DP approach Time: O(n^2) Space: O(n^2) TLE :type nums: List[int] :rtype: int"""
<|body_0|>
def lengthOfLIS2(self, nums):
"""DP approach 2: define dp[i] as LIS of nums[i...n] that starts with nums[i]. DP formula: dp[i] = 1 + m... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def lengthOfLIS(self, nums):
"""DP approach Time: O(n^2) Space: O(n^2) TLE :type nums: List[int] :rtype: int"""
import sys
n = len(nums)
if n == 0:
return 0
nums.insert(0, -sys.maxsize)
T = []
for i in range(n + 1):
T.ap... | the_stack_v2_python_sparse | py/leetcode_py/300.py | imsure/tech-interview-prep | train | 0 | |
553a266e4f3e0b4b7d513389b2cec2c0c792d75c | [
"message = Mock()\nmessage.has_label.return_value = False\nwith patch('eventstore.whatsapp_actions.update_rapidpro_preferred_channel') as update:\n message.fallback_channel = True\n handle_inbound(message)\n update.assert_not_called()\n message.fallback_channel = False\n handle_inbound(message)\n ... | <|body_start_0|>
message = Mock()
message.has_label.return_value = False
with patch('eventstore.whatsapp_actions.update_rapidpro_preferred_channel') as update:
message.fallback_channel = True
handle_inbound(message)
update.assert_not_called()
messa... | HandleInboundTests | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HandleInboundTests:
def test_contact_update(self):
"""If the message is not over the fallback channel then it should update the preferred channel"""
<|body_0|>
def test_alert_optout(self):
"""If the button text matches the optout phrase then it should update the cont... | stack_v2_sparse_classes_75kplus_train_000050 | 17,041 | permissive | [
{
"docstring": "If the message is not over the fallback channel then it should update the preferred channel",
"name": "test_contact_update",
"signature": "def test_contact_update(self)"
},
{
"docstring": "If the button text matches the optout phrase then it should update the contact in Rapidpro"... | 4 | stack_v2_sparse_classes_30k_train_025346 | Implement the Python class `HandleInboundTests` described below.
Class description:
Implement the HandleInboundTests class.
Method signatures and docstrings:
- def test_contact_update(self): If the message is not over the fallback channel then it should update the preferred channel
- def test_alert_optout(self): If t... | Implement the Python class `HandleInboundTests` described below.
Class description:
Implement the HandleInboundTests class.
Method signatures and docstrings:
- def test_contact_update(self): If the message is not over the fallback channel then it should update the preferred channel
- def test_alert_optout(self): If t... | e1ea0beaf079f4f4d5f9562fb9d9a4f0670f459f | <|skeleton|>
class HandleInboundTests:
def test_contact_update(self):
"""If the message is not over the fallback channel then it should update the preferred channel"""
<|body_0|>
def test_alert_optout(self):
"""If the button text matches the optout phrase then it should update the cont... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HandleInboundTests:
def test_contact_update(self):
"""If the message is not over the fallback channel then it should update the preferred channel"""
message = Mock()
message.has_label.return_value = False
with patch('eventstore.whatsapp_actions.update_rapidpro_preferred_channel... | the_stack_v2_python_sparse | eventstore/test_whatsapp_actions.py | praekeltfoundation/ndoh-hub | train | 0 | |
6396d4fb00467611541cf92bb9b118ade7d42b08 | [
"if not self.__timestamp:\n self.__timestamp = int(os.stat(str(self.value)).st_mtime)\nreturn self.__timestamp",
"if not self.__size:\n self.__size = os.stat(str(self.value)).st_size\nreturn self.__size",
"if not self.__hash:\n self.__hash = compute_file_hash(str(self.value))\nreturn self.__hash",
"s... | <|body_start_0|>
if not self.__timestamp:
self.__timestamp = int(os.stat(str(self.value)).st_mtime)
return self.__timestamp
<|end_body_0|>
<|body_start_1|>
if not self.__size:
self.__size = os.stat(str(self.value)).st_size
return self.__size
<|end_body_1|>
<|bod... | Represent a cached Artifactory's artifact. | CachedArtifact | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CachedArtifact:
"""Represent a cached Artifactory's artifact."""
def timestamp(self):
"""Gets the Artifact's timestamp based on its value :return: Artifact's timestamp :rtype: int"""
<|body_0|>
def size(self):
"""Gets the Artifact's size (in bytes) based on its v... | stack_v2_sparse_classes_75kplus_train_000051 | 25,285 | permissive | [
{
"docstring": "Gets the Artifact's timestamp based on its value :return: Artifact's timestamp :rtype: int",
"name": "timestamp",
"signature": "def timestamp(self)"
},
{
"docstring": "Gets the Artifact's size (in bytes) based on its value :return: Artifact's size :rtype: int",
"name": "size"... | 5 | stack_v2_sparse_classes_30k_train_027960 | Implement the Python class `CachedArtifact` described below.
Class description:
Represent a cached Artifactory's artifact.
Method signatures and docstrings:
- def timestamp(self): Gets the Artifact's timestamp based on its value :return: Artifact's timestamp :rtype: int
- def size(self): Gets the Artifact's size (in ... | Implement the Python class `CachedArtifact` described below.
Class description:
Represent a cached Artifactory's artifact.
Method signatures and docstrings:
- def timestamp(self): Gets the Artifact's timestamp based on its value :return: Artifact's timestamp :rtype: int
- def size(self): Gets the Artifact's size (in ... | 7bf09f20f117fc74d02b7635305ce664b65cdcba | <|skeleton|>
class CachedArtifact:
"""Represent a cached Artifactory's artifact."""
def timestamp(self):
"""Gets the Artifact's timestamp based on its value :return: Artifact's timestamp :rtype: int"""
<|body_0|>
def size(self):
"""Gets the Artifact's size (in bytes) based on its v... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CachedArtifact:
"""Represent a cached Artifactory's artifact."""
def timestamp(self):
"""Gets the Artifact's timestamp based on its value :return: Artifact's timestamp :rtype: int"""
if not self.__timestamp:
self.__timestamp = int(os.stat(str(self.value)).st_mtime)
ret... | the_stack_v2_python_sparse | acs/acs/UtilitiesFWK/Caching.py | intel/test-framework-and-suites-for-android | train | 9 |
11db9682368c393662b60d25065f21eb15659e9f | [
"dists = []\nn = len(nums)\nfor i in range(n):\n for j in range(i + 1, n):\n dists.append(abs(nums[j] - nums[i]))\ndists.sort()\nreturn dists[k - 1]",
"def countPairs2(nums: list, mid: int) -> int:\n n = len(nums)\n res = 0\n for i in range(n):\n res += upperBound(nums, i, n - 1, nums[i]... | <|body_start_0|>
dists = []
n = len(nums)
for i in range(n):
for j in range(i + 1, n):
dists.append(abs(nums[j] - nums[i]))
dists.sort()
return dists[k - 1]
<|end_body_0|>
<|body_start_1|>
def countPairs2(nums: list, mid: int) -> int:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def smallestDistancePair0(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int Simple solution, but not effective in terms of time cost O(n^2)"""
<|body_0|>
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: ... | stack_v2_sparse_classes_75kplus_train_000052 | 21,677 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int Simple solution, but not effective in terms of time cost O(n^2)",
"name": "smallestDistancePair0",
"signature": "def smallestDistancePair0(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name"... | 2 | stack_v2_sparse_classes_30k_train_038398 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestDistancePair0(self, nums, k): :type nums: List[int] :type k: int :rtype: int Simple solution, but not effective in terms of time cost O(n^2)
- def smallestDistancePai... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestDistancePair0(self, nums, k): :type nums: List[int] :type k: int :rtype: int Simple solution, but not effective in terms of time cost O(n^2)
- def smallestDistancePai... | 54d3d9530b25272d4a2e5dc33e7035c44f506dc5 | <|skeleton|>
class Solution:
def smallestDistancePair0(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int Simple solution, but not effective in terms of time cost O(n^2)"""
<|body_0|>
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def smallestDistancePair0(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int Simple solution, but not effective in terms of time cost O(n^2)"""
dists = []
n = len(nums)
for i in range(n):
for j in range(i + 1, n):
dists.appen... | the_stack_v2_python_sparse | old/Session002/Arrays/FindKthSmallestPairDistance.py | MaxIakovliev/algorithms | train | 0 | |
5c8bf7b8334da03f4bbc466cfe9538442c47deb2 | [
"SparkReaderWriter.__init__(self, spark_session, None)\nDataFrameReader._jreader = HiveContext(sparkContext=spark_session.sparkContext)._ssql_ctx.read()\nDataFrameReader._spark = spark_session",
"db_func = CommonDBFunc()\ndriver = db_func.get_db_driver(db_name)\ngp_config = ConfigInit().read_python_properties(f'{... | <|body_start_0|>
SparkReaderWriter.__init__(self, spark_session, None)
DataFrameReader._jreader = HiveContext(sparkContext=spark_session.sparkContext)._ssql_ctx.read()
DataFrameReader._spark = spark_session
<|end_body_0|>
<|body_start_1|>
db_func = CommonDBFunc()
driver = db_fun... | 兼容原始read函数 | SparkReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparkReader:
"""兼容原始read函数"""
def __init__(self, spark_session):
"""初始化 :param spark_session: SparkSession"""
<|body_0|>
def relational_db(self, db_name, database_env, databases, query_sql_or_table, **options):
""":param db_name: :param database_env: :param datab... | stack_v2_sparse_classes_75kplus_train_000053 | 1,366 | no_license | [
{
"docstring": "初始化 :param spark_session: SparkSession",
"name": "__init__",
"signature": "def __init__(self, spark_session)"
},
{
"docstring": ":param db_name: :param database_env: :param databases: :param query_sql_or_table: :param options: :return:",
"name": "relational_db",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_025155 | Implement the Python class `SparkReader` described below.
Class description:
兼容原始read函数
Method signatures and docstrings:
- def __init__(self, spark_session): 初始化 :param spark_session: SparkSession
- def relational_db(self, db_name, database_env, databases, query_sql_or_table, **options): :param db_name: :param datab... | Implement the Python class `SparkReader` described below.
Class description:
兼容原始read函数
Method signatures and docstrings:
- def __init__(self, spark_session): 初始化 :param spark_session: SparkSession
- def relational_db(self, db_name, database_env, databases, query_sql_or_table, **options): :param db_name: :param datab... | e883217e27a44699064c30e386379dea049af30d | <|skeleton|>
class SparkReader:
"""兼容原始read函数"""
def __init__(self, spark_session):
"""初始化 :param spark_session: SparkSession"""
<|body_0|>
def relational_db(self, db_name, database_env, databases, query_sql_or_table, **options):
""":param db_name: :param database_env: :param datab... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SparkReader:
"""兼容原始read函数"""
def __init__(self, spark_session):
"""初始化 :param spark_session: SparkSession"""
SparkReaderWriter.__init__(self, spark_session, None)
DataFrameReader._jreader = HiveContext(sparkContext=spark_session.sparkContext)._ssql_ctx.read()
DataFrameRea... | the_stack_v2_python_sparse | mavenimportant/python/jobs/common/spark_reader.py | liProject/importantProject | train | 0 |
4ef2f7dc0402b25a53e840687a7fc0b06db3961e | [
"super().__init__(prefix, language_id, shortcuts)\nself.command_data = command_data\nif self.command_data is None:\n self.command_data = custom_json.load(definitions.USER_COMMAND_DATA)",
"if row is None:\n return None\nreturn UserData(prefix=row[0], language_id=row[1], command_data=custom_json.load(row[2]))... | <|body_start_0|>
super().__init__(prefix, language_id, shortcuts)
self.command_data = command_data
if self.command_data is None:
self.command_data = custom_json.load(definitions.USER_COMMAND_DATA)
<|end_body_0|>
<|body_start_1|>
if row is None:
return None
... | User data and configuration. | UserData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserData:
"""User data and configuration."""
def __init__(self, prefix=None, language_id=None, shortcuts=None, command_data=None):
"""Object initialisation."""
<|body_0|>
def create_object_from_database(row):
"""Create UserData object from a database row."""
... | stack_v2_sparse_classes_75kplus_train_000054 | 5,426 | no_license | [
{
"docstring": "Object initialisation.",
"name": "__init__",
"signature": "def __init__(self, prefix=None, language_id=None, shortcuts=None, command_data=None)"
},
{
"docstring": "Create UserData object from a database row.",
"name": "create_object_from_database",
"signature": "def creat... | 2 | stack_v2_sparse_classes_30k_train_037126 | Implement the Python class `UserData` described below.
Class description:
User data and configuration.
Method signatures and docstrings:
- def __init__(self, prefix=None, language_id=None, shortcuts=None, command_data=None): Object initialisation.
- def create_object_from_database(row): Create UserData object from a ... | Implement the Python class `UserData` described below.
Class description:
User data and configuration.
Method signatures and docstrings:
- def __init__(self, prefix=None, language_id=None, shortcuts=None, command_data=None): Object initialisation.
- def create_object_from_database(row): Create UserData object from a ... | 521bb272388d111c69109afe336de656b52bc9b1 | <|skeleton|>
class UserData:
"""User data and configuration."""
def __init__(self, prefix=None, language_id=None, shortcuts=None, command_data=None):
"""Object initialisation."""
<|body_0|>
def create_object_from_database(row):
"""Create UserData object from a database row."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserData:
"""User data and configuration."""
def __init__(self, prefix=None, language_id=None, shortcuts=None, command_data=None):
"""Object initialisation."""
super().__init__(prefix, language_id, shortcuts)
self.command_data = command_data
if self.command_data is None:
... | the_stack_v2_python_sparse | datatypes/config_data.py | saileille/mami | train | 0 |
668caf3beee50d8e05323253dd442794bc8ac9e5 | [
"url = '/api/itsystems/'\nresponse = self.client.get(url)\nself.assertEqual(response.status_code, 200)\nself.assertNotContains(response, self.it2.name)\nself.assertNotContains(response, self.it_dec.name)",
"url = '/api/itsystems/?all'\nresponse = self.client.get(url)\nself.assertEqual(response.status_code, 200)\n... | <|body_start_0|>
url = '/api/itsystems/'
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
self.assertNotContains(response, self.it2.name)
self.assertNotContains(response, self.it_dec.name)
<|end_body_0|>
<|body_start_1|>
url = '/api/itsystems/?... | ITSystemResourceTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ITSystemResourceTestCase:
def test_list(self):
"""Test the ITSystemResource list response"""
<|body_0|>
def test_list_all(self):
"""Test the ITSystemResource list response with all param"""
<|body_1|>
def test_list_filter(self):
"""Test the ITSys... | stack_v2_sparse_classes_75kplus_train_000055 | 2,926 | permissive | [
{
"docstring": "Test the ITSystemResource list response",
"name": "test_list",
"signature": "def test_list(self)"
},
{
"docstring": "Test the ITSystemResource list response with all param",
"name": "test_list_all",
"signature": "def test_list_all(self)"
},
{
"docstring": "Test th... | 3 | stack_v2_sparse_classes_30k_train_038042 | Implement the Python class `ITSystemResourceTestCase` described below.
Class description:
Implement the ITSystemResourceTestCase class.
Method signatures and docstrings:
- def test_list(self): Test the ITSystemResource list response
- def test_list_all(self): Test the ITSystemResource list response with all param
- d... | Implement the Python class `ITSystemResourceTestCase` described below.
Class description:
Implement the ITSystemResourceTestCase class.
Method signatures and docstrings:
- def test_list(self): Test the ITSystemResource list response
- def test_list_all(self): Test the ITSystemResource list response with all param
- d... | 4d5caceba69cac7f59b63745a0f52322004df2eb | <|skeleton|>
class ITSystemResourceTestCase:
def test_list(self):
"""Test the ITSystemResource list response"""
<|body_0|>
def test_list_all(self):
"""Test the ITSystemResource list response with all param"""
<|body_1|>
def test_list_filter(self):
"""Test the ITSys... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ITSystemResourceTestCase:
def test_list(self):
"""Test the ITSystemResource list response"""
url = '/api/itsystems/'
response = self.client.get(url)
self.assertEqual(response.status_code, 200)
self.assertNotContains(response, self.it2.name)
self.assertNotContain... | the_stack_v2_python_sparse | registers/test_api.py | bryceprince0/it-assets | train | 0 | |
669ba5d3ddcb833f1e01465ccec198b7daee4b80 | [
"super(Reader_Downstream, self).__init__()\nself.add = P.Add()\nself.para_bias = Parameter(Tensor(np.random.uniform(0, 1, (1,)).astype(np.float32)), name=None)\nself.para_output_layer = SupportingOutputLayer(linear_1_weight_shape=(4096, 8192), linear_1_bias_shape=(8192,), bert_layer_norm_weight_shape=(8192,), bert_... | <|body_start_0|>
super(Reader_Downstream, self).__init__()
self.add = P.Add()
self.para_bias = Parameter(Tensor(np.random.uniform(0, 1, (1,)).astype(np.float32)), name=None)
self.para_output_layer = SupportingOutputLayer(linear_1_weight_shape=(4096, 8192), linear_1_bias_shape=(8192,), be... | Downstream model for reader | Reader_Downstream | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reader_Downstream:
"""Downstream model for reader"""
def __init__(self):
"""init function"""
<|body_0|>
def construct(self, para_state, sent_state, state, context_mask):
"""construct function"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super... | stack_v2_sparse_classes_75kplus_train_000056 | 9,011 | permissive | [
{
"docstring": "init function",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "construct function",
"name": "construct",
"signature": "def construct(self, para_state, sent_state, state, context_mask)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002953 | Implement the Python class `Reader_Downstream` described below.
Class description:
Downstream model for reader
Method signatures and docstrings:
- def __init__(self): init function
- def construct(self, para_state, sent_state, state, context_mask): construct function | Implement the Python class `Reader_Downstream` described below.
Class description:
Downstream model for reader
Method signatures and docstrings:
- def __init__(self): init function
- def construct(self, para_state, sent_state, state, context_mask): construct function
<|skeleton|>
class Reader_Downstream:
"""Down... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class Reader_Downstream:
"""Downstream model for reader"""
def __init__(self):
"""init function"""
<|body_0|>
def construct(self, para_state, sent_state, state, context_mask):
"""construct function"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Reader_Downstream:
"""Downstream model for reader"""
def __init__(self):
"""init function"""
super(Reader_Downstream, self).__init__()
self.add = P.Add()
self.para_bias = Parameter(Tensor(np.random.uniform(0, 1, (1,)).astype(np.float32)), name=None)
self.para_outpu... | the_stack_v2_python_sparse | research/nlp/tprr/src/reader_downstream.py | mindspore-ai/models | train | 301 |
d8d82bff0f95ee16ca3f4001769161a5a3ddd319 | [
"nums.sort()\nn = len(nums)\nreturn nums[n - k]",
"import random\npivot = random.choice(nums)\nnums1, nums2 = ([], [])\nfor num in nums:\n if num > pivot:\n nums1.append(num)\n elif num < pivot:\n nums2.append(num)\nif k <= len(nums1):\n return self.findKthLargest(nums1, k)\nif k > len(nums... | <|body_start_0|>
nums.sort()
n = len(nums)
return nums[n - k]
<|end_body_0|>
<|body_start_1|>
import random
pivot = random.choice(nums)
nums1, nums2 = ([], [])
for num in nums:
if num > pivot:
nums1.append(num)
elif num < p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findKthLargest(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def findKthLargest_1(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
def findKthLargest_2(self, nums, k):
... | stack_v2_sparse_classes_75kplus_train_000057 | 1,788 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findKthLargest",
"signature": "def findKthLargest(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findKthLargest_1",
"signature": "def findKthLargest_1(self, nums, k)"
... | 3 | stack_v2_sparse_classes_30k_train_026080 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findKthLargest(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findKthLargest_1(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def find... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findKthLargest(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findKthLargest_1(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def find... | ba58ac60b32e261e43482d7e71b32587700e3719 | <|skeleton|>
class Solution:
def findKthLargest(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def findKthLargest_1(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
def findKthLargest_2(self, nums, k):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findKthLargest(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
nums.sort()
n = len(nums)
return nums[n - k]
def findKthLargest_1(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
import random
pi... | the_stack_v2_python_sparse | python/215_kth_largest_element_in_an_array.py | lingng/Leetcode | train | 0 | |
46b2934a2fde9c27678928d5b7492f1896be1501 | [
"super().__init__(name='critic')\nself.model_size = model_size\nself.ema_decay = ema_decay\nself.mlp = MLP(model_size=self.model_size, output_layer_size=None)\nself.return_layer = RewardPredictorLayer(num_buckets=num_buckets, lower_bound=lower_bound, upper_bound=upper_bound)\nself.mlp_ema = MLP(model_size=self.mode... | <|body_start_0|>
super().__init__(name='critic')
self.model_size = model_size
self.ema_decay = ema_decay
self.mlp = MLP(model_size=self.model_size, output_layer_size=None)
self.return_layer = RewardPredictorLayer(num_buckets=num_buckets, lower_bound=lower_bound, upper_bound=upper... | The critic network described in [1], predicting values for policy learning. Contains a copy of itself (EMA net) for weight regularization. The EMA net is updated after each train step via EMA (using the `ema_decay` parameter and the actual critic's weights). The EMA net is NOT used for target computations (we use the a... | CriticNetwork | [
"MIT",
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CriticNetwork:
"""The critic network described in [1], predicting values for policy learning. Contains a copy of itself (EMA net) for weight regularization. The EMA net is updated after each train step via EMA (using the `ema_decay` parameter and the actual critic's weights). The EMA net is NOT u... | stack_v2_sparse_classes_75kplus_train_000058 | 7,414 | permissive | [
{
"docstring": "Initializes a CriticNetwork instance. Args: model_size: The \"Model Size\" used according to [1] Appendinx B. Use None for manually setting the different network sizes. num_buckets: The number of buckets to create. Note that the number of possible symlog'd outcomes from the used distribution is ... | 4 | stack_v2_sparse_classes_30k_val_000187 | Implement the Python class `CriticNetwork` described below.
Class description:
The critic network described in [1], predicting values for policy learning. Contains a copy of itself (EMA net) for weight regularization. The EMA net is updated after each train step via EMA (using the `ema_decay` parameter and the actual ... | Implement the Python class `CriticNetwork` described below.
Class description:
The critic network described in [1], predicting values for policy learning. Contains a copy of itself (EMA net) for weight regularization. The EMA net is updated after each train step via EMA (using the `ema_decay` parameter and the actual ... | edba68c3e7cf255d1d6479329f305adb7fa4c3ed | <|skeleton|>
class CriticNetwork:
"""The critic network described in [1], predicting values for policy learning. Contains a copy of itself (EMA net) for weight regularization. The EMA net is updated after each train step via EMA (using the `ema_decay` parameter and the actual critic's weights). The EMA net is NOT u... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CriticNetwork:
"""The critic network described in [1], predicting values for policy learning. Contains a copy of itself (EMA net) for weight regularization. The EMA net is updated after each train step via EMA (using the `ema_decay` parameter and the actual critic's weights). The EMA net is NOT used for targe... | the_stack_v2_python_sparse | rllib/algorithms/dreamerv3/tf/models/critic_network.py | ray-project/ray | train | 29,482 |
a61867184b0743840a6010b67ef973857bdbf944 | [
"del params\nself.num_players = num_players\nself.hand_length = hand_length\npieces = [('player', num_players, (num_players,))]\nif iig_obs_type.private_info == pyspiel.PrivateInfoType.SINGLE_PLAYER:\n pieces.append(('private_hand', hand_length, (hand_length,)))\nif iig_obs_type.public_info:\n pieces.append((... | <|body_start_0|>
del params
self.num_players = num_players
self.hand_length = hand_length
pieces = [('player', num_players, (num_players,))]
if iig_obs_type.private_info == pyspiel.PrivateInfoType.SINGLE_PLAYER:
pieces.append(('private_hand', hand_length, (hand_length... | Observer, conforming to the PyObserver interface (see observation.py). An observation will consist of the following: - One hot encoding of the current player number: [0 0 0 1 0 0 0] - A vector of length hand_length containing the digits in a player's hand. - Two matrices each of size (hand_length * num_digits * num_pla... | LiarsPokerObserver | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LiarsPokerObserver:
"""Observer, conforming to the PyObserver interface (see observation.py). An observation will consist of the following: - One hot encoding of the current player number: [0 0 0 1 0 0 0] - A vector of length hand_length containing the digits in a player's hand. - Two matrices ea... | stack_v2_sparse_classes_75kplus_train_000059 | 16,165 | permissive | [
{
"docstring": "Initiliazes an empty observation tensor.",
"name": "__init__",
"signature": "def __init__(self, iig_obs_type, num_players, hand_length, num_digits, params=None)"
},
{
"docstring": "Updates `tensor` and `dict` to reflect `state` from PoV of `player`.",
"name": "set_from",
... | 3 | null | Implement the Python class `LiarsPokerObserver` described below.
Class description:
Observer, conforming to the PyObserver interface (see observation.py). An observation will consist of the following: - One hot encoding of the current player number: [0 0 0 1 0 0 0] - A vector of length hand_length containing the digit... | Implement the Python class `LiarsPokerObserver` described below.
Class description:
Observer, conforming to the PyObserver interface (see observation.py). An observation will consist of the following: - One hot encoding of the current player number: [0 0 0 1 0 0 0] - A vector of length hand_length containing the digit... | ee149736f7d85e16c119a463eee338c6d4c2ceb0 | <|skeleton|>
class LiarsPokerObserver:
"""Observer, conforming to the PyObserver interface (see observation.py). An observation will consist of the following: - One hot encoding of the current player number: [0 0 0 1 0 0 0] - A vector of length hand_length containing the digits in a player's hand. - Two matrices ea... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LiarsPokerObserver:
"""Observer, conforming to the PyObserver interface (see observation.py). An observation will consist of the following: - One hot encoding of the current player number: [0 0 0 1 0 0 0] - A vector of length hand_length containing the digits in a player's hand. - Two matrices each of size (h... | the_stack_v2_python_sparse | open_spiel/python/games/liars_poker.py | lanctot/open_spiel | train | 1 |
fa2af28e286bf670d1e12dd7e26469bcd7ebe88d | [
"self.dim = dim\nself.y_pos = y_pos\nself.bars = bars\nself.speed = speed\nself.palette = palette\nself.sin = sin\nself.surface = pygame.Surface((dim[0], dim[1]), flags=pygame.SRCALPHA)\nbar_height = 10\nself.bar_surface = pygame.Surface((dim[0], bar_height), flags=pygame.SRCALPHA)\nfor index, degree in enumerate(r... | <|body_start_0|>
self.dim = dim
self.y_pos = y_pos
self.bars = bars
self.speed = speed
self.palette = palette
self.sin = sin
self.surface = pygame.Surface((dim[0], dim[1]), flags=pygame.SRCALPHA)
bar_height = 10
self.bar_surface = pygame.Surface((d... | some simple horizontal raster bar | HorizontalRasterBar | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HorizontalRasterBar:
"""some simple horizontal raster bar"""
def __init__(self, dim: tuple, y_pos: int, bars: int=5, speed: int=2, palette: list=PALETTE, sin: list=SIN):
""":param dim: dimensio of surface to draw on :param y_pos: central y position :param bars: how many bars to draw ... | stack_v2_sparse_classes_75kplus_train_000060 | 5,116 | no_license | [
{
"docstring": ":param dim: dimensio of surface to draw on :param y_pos: central y position :param bars: how many bars to draw :param speed: speed per frame, 1 euqal one pixel per frame :param palette: palette to use 256 colors :param sin: pre calculated sins for 360 degrees",
"name": "__init__",
"signa... | 2 | stack_v2_sparse_classes_30k_train_031700 | Implement the Python class `HorizontalRasterBar` described below.
Class description:
some simple horizontal raster bar
Method signatures and docstrings:
- def __init__(self, dim: tuple, y_pos: int, bars: int=5, speed: int=2, palette: list=PALETTE, sin: list=SIN): :param dim: dimensio of surface to draw on :param y_po... | Implement the Python class `HorizontalRasterBar` described below.
Class description:
some simple horizontal raster bar
Method signatures and docstrings:
- def __init__(self, dim: tuple, y_pos: int, bars: int=5, speed: int=2, palette: list=PALETTE, sin: list=SIN): :param dim: dimensio of surface to draw on :param y_po... | 1fd421195a2888c0588a49f5a043a1110eedcdbf | <|skeleton|>
class HorizontalRasterBar:
"""some simple horizontal raster bar"""
def __init__(self, dim: tuple, y_pos: int, bars: int=5, speed: int=2, palette: list=PALETTE, sin: list=SIN):
""":param dim: dimensio of surface to draw on :param y_pos: central y position :param bars: how many bars to draw ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HorizontalRasterBar:
"""some simple horizontal raster bar"""
def __init__(self, dim: tuple, y_pos: int, bars: int=5, speed: int=2, palette: list=PALETTE, sin: list=SIN):
""":param dim: dimensio of surface to draw on :param y_pos: central y position :param bars: how many bars to draw :param speed:... | the_stack_v2_python_sparse | effects/RasterBar.py | gunny26/pygame | train | 5 |
900edb290b37d25e3c1623848e985c8624705a02 | [
"consumer_key = settings.TWITTER_CONSUMER_KEY\nconsumer_secret = settings.TWITTER_CONSUMER_SECRET\naccess_token = settings.TWITTER_ACCESS_TOKEN\naccess_token_secret = settings.TWITTER_ACCESS_TOKEN_SECRET\nauth = tweepy.OAuthHandler(consumer_key, consumer_secret)\nauth.set_access_token(access_token, access_token_sec... | <|body_start_0|>
consumer_key = settings.TWITTER_CONSUMER_KEY
consumer_secret = settings.TWITTER_CONSUMER_SECRET
access_token = settings.TWITTER_ACCESS_TOKEN
access_token_secret = settings.TWITTER_ACCESS_TOKEN_SECRET
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
... | Command | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
def setup_tweepy(self):
"""Returns a Tweepy API object, using credentials defined in settings.py"""
<|body_0|>
def tweet(self, message_body, api_handle):
"""Tweets the given message using a Tweepy API handle."""
<|body_1|>
def construct_message(... | stack_v2_sparse_classes_75kplus_train_000061 | 2,110 | permissive | [
{
"docstring": "Returns a Tweepy API object, using credentials defined in settings.py",
"name": "setup_tweepy",
"signature": "def setup_tweepy(self)"
},
{
"docstring": "Tweets the given message using a Tweepy API handle.",
"name": "tweet",
"signature": "def tweet(self, message_body, api_... | 4 | stack_v2_sparse_classes_30k_train_036980 | Implement the Python class `Command` described below.
Class description:
Implement the Command class.
Method signatures and docstrings:
- def setup_tweepy(self): Returns a Tweepy API object, using credentials defined in settings.py
- def tweet(self, message_body, api_handle): Tweets the given message using a Tweepy A... | Implement the Python class `Command` described below.
Class description:
Implement the Command class.
Method signatures and docstrings:
- def setup_tweepy(self): Returns a Tweepy API object, using credentials defined in settings.py
- def tweet(self, message_body, api_handle): Tweets the given message using a Tweepy A... | b1850ecfa5e2694961a34d450430a001a1a39a5e | <|skeleton|>
class Command:
def setup_tweepy(self):
"""Returns a Tweepy API object, using credentials defined in settings.py"""
<|body_0|>
def tweet(self, message_body, api_handle):
"""Tweets the given message using a Tweepy API handle."""
<|body_1|>
def construct_message(... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Command:
def setup_tweepy(self):
"""Returns a Tweepy API object, using credentials defined in settings.py"""
consumer_key = settings.TWITTER_CONSUMER_KEY
consumer_secret = settings.TWITTER_CONSUMER_SECRET
access_token = settings.TWITTER_ACCESS_TOKEN
access_token_secret ... | the_stack_v2_python_sparse | beer_search_v2/management/commands/announce.py | Ernir/bjorleitin | train | 1 | |
9f82ea2edfaa1f97df869b28a1868171460304ae | [
"if not Permission(UserNeed(profile_id)).can():\n if not VerifyEducationPermission.can():\n return abort(HTTPStatus.FORBIDDEN, 'User is not authorized to view this profile education')\neducation = Education.query.get(profile_id)\nif education is None:\n return abort(HTTPStatus.NOT_FOUND, 'Education is ... | <|body_start_0|>
if not Permission(UserNeed(profile_id)).can():
if not VerifyEducationPermission.can():
return abort(HTTPStatus.FORBIDDEN, 'User is not authorized to view this profile education')
education = Education.query.get(profile_id)
if education is None:
... | ProfileEducationResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileEducationResource:
def get(self, profile_id):
"""Get profile education info * User can view **their education** info * User with permission to **"verify education"** can view education info"""
<|body_0|>
def put(self, profile_id):
"""Update profile education i... | stack_v2_sparse_classes_75kplus_train_000062 | 2,764 | permissive | [
{
"docstring": "Get profile education info * User can view **their education** info * User with permission to **\"verify education\"** can view education info",
"name": "get",
"signature": "def get(self, profile_id)"
},
{
"docstring": "Update profile education info * User can edit **their educat... | 2 | stack_v2_sparse_classes_30k_test_001649 | Implement the Python class `ProfileEducationResource` described below.
Class description:
Implement the ProfileEducationResource class.
Method signatures and docstrings:
- def get(self, profile_id): Get profile education info * User can view **their education** info * User with permission to **"verify education"** ca... | Implement the Python class `ProfileEducationResource` described below.
Class description:
Implement the ProfileEducationResource class.
Method signatures and docstrings:
- def get(self, profile_id): Get profile education info * User can view **their education** info * User with permission to **"verify education"** ca... | dce87ffe395ae4bd08b47f28e07594e1889da819 | <|skeleton|>
class ProfileEducationResource:
def get(self, profile_id):
"""Get profile education info * User can view **their education** info * User with permission to **"verify education"** can view education info"""
<|body_0|>
def put(self, profile_id):
"""Update profile education i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProfileEducationResource:
def get(self, profile_id):
"""Get profile education info * User can view **their education** info * User with permission to **"verify education"** can view education info"""
if not Permission(UserNeed(profile_id)).can():
if not VerifyEducationPermission.ca... | the_stack_v2_python_sparse | src/backend/app/api/public/profiles/profile/education/education.py | aimanow/sft | train | 0 | |
de652ebf388e3ced877abf6411340b5fab44e4fe | [
"shift_x = constants.all_shifts[direction_index]['x']\nshift_y = constants.all_shifts[direction_index]['y']\nreturn (shift_x, shift_y)",
"shift_x, shift_y = Utilities.get_shift_by_direction(direction_index)\nnew_x, new_y = (shift_x + x, shift_y + y)\nreturn (new_x, new_y)"
] | <|body_start_0|>
shift_x = constants.all_shifts[direction_index]['x']
shift_y = constants.all_shifts[direction_index]['y']
return (shift_x, shift_y)
<|end_body_0|>
<|body_start_1|>
shift_x, shift_y = Utilities.get_shift_by_direction(direction_index)
new_x, new_y = (shift_x + x, ... | Utilities | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Utilities:
def get_shift_by_direction(direction_index):
"""Function return shift depending on direction. Args: direction_index(int): index specified direction Returns: (int, int): shift by columns and rows"""
<|body_0|>
def get_new_coordinates(direction_index, x, y):
... | stack_v2_sparse_classes_75kplus_train_000063 | 1,224 | permissive | [
{
"docstring": "Function return shift depending on direction. Args: direction_index(int): index specified direction Returns: (int, int): shift by columns and rows",
"name": "get_shift_by_direction",
"signature": "def get_shift_by_direction(direction_index)"
},
{
"docstring": "Function returns ne... | 2 | stack_v2_sparse_classes_30k_train_047821 | Implement the Python class `Utilities` described below.
Class description:
Implement the Utilities class.
Method signatures and docstrings:
- def get_shift_by_direction(direction_index): Function return shift depending on direction. Args: direction_index(int): index specified direction Returns: (int, int): shift by c... | Implement the Python class `Utilities` described below.
Class description:
Implement the Utilities class.
Method signatures and docstrings:
- def get_shift_by_direction(direction_index): Function return shift depending on direction. Args: direction_index(int): index specified direction Returns: (int, int): shift by c... | 291592e97b6d8fe9f9e6627dc0023875918d3463 | <|skeleton|>
class Utilities:
def get_shift_by_direction(direction_index):
"""Function return shift depending on direction. Args: direction_index(int): index specified direction Returns: (int, int): shift by columns and rows"""
<|body_0|>
def get_new_coordinates(direction_index, x, y):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Utilities:
def get_shift_by_direction(direction_index):
"""Function return shift depending on direction. Args: direction_index(int): index specified direction Returns: (int, int): shift by columns and rows"""
shift_x = constants.all_shifts[direction_index]['x']
shift_y = constants.all_... | the_stack_v2_python_sparse | Dmytro_Skorobohatskyi/batch_10/dungeon_game_stereotype_pkg/build/lib/dungeon_game_stereotype_pkg/utilities.py | SmischenkoB/campus_2018_python | train | 0 | |
246312b70c575409e7e1cc458bda5ce450bb26a2 | [
"self.first_idx = {}\nself.last_idx = {}\nself.key_map = {}\nself.arr = []",
"if key not in self.key_map:\n self.arr.append([1, key])\n if 1 not in self.last_idx:\n self.first_idx[1] = len(self.arr) - 1\n self.last_idx[1] = len(self.arr) - 1\n self.key_map[key] = len(self.arr) - 1\nelse:\n j... | <|body_start_0|>
self.first_idx = {}
self.last_idx = {}
self.key_map = {}
self.arr = []
<|end_body_0|>
<|body_start_1|>
if key not in self.key_map:
self.arr.append([1, key])
if 1 not in self.last_idx:
self.first_idx[1] = len(self.arr) - 1
... | AllOne | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllOne:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def inc(self, key):
"""Inserts a new key <Key> with value 1. Or increments an existing key by 1. :type key: str :rtype: void"""
<|body_1|>
def dec(self, key):
"""De... | stack_v2_sparse_classes_75kplus_train_000064 | 3,586 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Inserts a new key <Key> with value 1. Or increments an existing key by 1. :type key: str :rtype: void",
"name": "inc",
"signature": "def inc(self, key)"
},
... | 5 | stack_v2_sparse_classes_30k_train_032720 | Implement the Python class `AllOne` described below.
Class description:
Implement the AllOne class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def inc(self, key): Inserts a new key <Key> with value 1. Or increments an existing key by 1. :type key: str :rtype: void
-... | Implement the Python class `AllOne` described below.
Class description:
Implement the AllOne class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def inc(self, key): Inserts a new key <Key> with value 1. Or increments an existing key by 1. :type key: str :rtype: void
-... | 2722c0deafcd094ce64140a9a837b4027d29ed6f | <|skeleton|>
class AllOne:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def inc(self, key):
"""Inserts a new key <Key> with value 1. Or increments an existing key by 1. :type key: str :rtype: void"""
<|body_1|>
def dec(self, key):
"""De... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AllOne:
def __init__(self):
"""Initialize your data structure here."""
self.first_idx = {}
self.last_idx = {}
self.key_map = {}
self.arr = []
def inc(self, key):
"""Inserts a new key <Key> with value 1. Or increments an existing key by 1. :type key: str :rt... | the_stack_v2_python_sparse | 432_all_one_ds_h/main.py | chao-shi/lclc | train | 0 | |
d7eaa930fa37968931d1c5a2eb838918ff9f7236 | [
"epsilon = 0.25\nalpha = 2\nlamb = 2\n\ndef T(x):\n return func(xk) + epsilon * x * grad(xk).T @ dk\nwhile func(xk + lamb * dk) > T(lamb) or func(xk + alpha * lamb * dk) < T(alpha * lamb):\n if func(xk + lamb * dk) > T(lamb):\n lamb /= alpha\n else:\n lamb *= alpha\nreturn lamb",
"a = 0\nb0... | <|body_start_0|>
epsilon = 0.25
alpha = 2
lamb = 2
def T(x):
return func(xk) + epsilon * x * grad(xk).T @ dk
while func(xk + lamb * dk) > T(lamb) or func(xk + alpha * lamb * dk) < T(alpha * lamb):
if func(xk + lamb * dk) > T(lamb):
lamb /=... | Linesearch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Linesearch:
def inexactLinesearch(xk, dk, func, grad):
"""Armijo's rule"""
<|body_0|>
def exactLinesearch(xk, dk, func, grad):
"""The bisection method"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
epsilon = 0.25
alpha = 2
lamb = 2
... | stack_v2_sparse_classes_75kplus_train_000065 | 1,444 | no_license | [
{
"docstring": "Armijo's rule",
"name": "inexactLinesearch",
"signature": "def inexactLinesearch(xk, dk, func, grad)"
},
{
"docstring": "The bisection method",
"name": "exactLinesearch",
"signature": "def exactLinesearch(xk, dk, func, grad)"
}
] | 2 | null | Implement the Python class `Linesearch` described below.
Class description:
Implement the Linesearch class.
Method signatures and docstrings:
- def inexactLinesearch(xk, dk, func, grad): Armijo's rule
- def exactLinesearch(xk, dk, func, grad): The bisection method | Implement the Python class `Linesearch` described below.
Class description:
Implement the Linesearch class.
Method signatures and docstrings:
- def inexactLinesearch(xk, dk, func, grad): Armijo's rule
- def exactLinesearch(xk, dk, func, grad): The bisection method
<|skeleton|>
class Linesearch:
def inexactLines... | dc5dc96348248ce480ad3bdb6299dc4b28fb867c | <|skeleton|>
class Linesearch:
def inexactLinesearch(xk, dk, func, grad):
"""Armijo's rule"""
<|body_0|>
def exactLinesearch(xk, dk, func, grad):
"""The bisection method"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Linesearch:
def inexactLinesearch(xk, dk, func, grad):
"""Armijo's rule"""
epsilon = 0.25
alpha = 2
lamb = 2
def T(x):
return func(xk) + epsilon * x * grad(xk).T @ dk
while func(xk + lamb * dk) > T(lamb) or func(xk + alpha * lamb * dk) < T(alpha * l... | the_stack_v2_python_sparse | Newton/Linesearch.py | AugustBergoo/NumAlgPython | train | 0 | |
fe3d5f98df4a311f16bf7df30be598b0b17bbdfd | [
"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... | * Allow to communicate with the vehicle's system shell. | ShellServiceServicer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShellServiceServicer:
"""* Allow to communicate with the vehicle's system shell."""
def Send(self, request, context):
"""Send a command line."""
<|body_0|>
def SubscribeReceive(self, request, context):
"""Receive feedback from a sent command line. This subscripti... | stack_v2_sparse_classes_75kplus_train_000066 | 2,389 | permissive | [
{
"docstring": "Send a command line.",
"name": "Send",
"signature": "def Send(self, request, context)"
},
{
"docstring": "Receive feedback from a sent command line. This subscription needs to be made before a command line is sent, otherwise, no response will be sent.",
"name": "SubscribeRece... | 2 | stack_v2_sparse_classes_30k_train_041623 | Implement the Python class `ShellServiceServicer` described below.
Class description:
* Allow to communicate with the vehicle's system shell.
Method signatures and docstrings:
- def Send(self, request, context): Send a command line.
- def SubscribeReceive(self, request, context): Receive feedback from a sent command ... | Implement the Python class `ShellServiceServicer` described below.
Class description:
* Allow to communicate with the vehicle's system shell.
Method signatures and docstrings:
- def Send(self, request, context): Send a command line.
- def SubscribeReceive(self, request, context): Receive feedback from a sent command ... | a328834518621842f530804572ecb3baeec31805 | <|skeleton|>
class ShellServiceServicer:
"""* Allow to communicate with the vehicle's system shell."""
def Send(self, request, context):
"""Send a command line."""
<|body_0|>
def SubscribeReceive(self, request, context):
"""Receive feedback from a sent command line. This subscripti... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ShellServiceServicer:
"""* Allow to communicate with the vehicle's system shell."""
def Send(self, request, context):
"""Send a command line."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method... | the_stack_v2_python_sparse | mavsdk/shell_pb2_grpc.py | PML-UCF/MAVSDK-Python | train | 0 |
701f142fc3f245ea291ebd663f9e903bee70eaa5 | [
"if user.id:\n try:\n provider_auth = pyramid_basemodel.Session.query(AuthenticationProvider).filter(AuthenticationProvider.user_id == user.id, AuthenticationProvider.provider == provider_name).one()\n if provider_auth.provider_id != user_provider_id:\n return False\n return True\... | <|body_start_0|>
if user.id:
try:
provider_auth = pyramid_basemodel.Session.query(AuthenticationProvider).filter(AuthenticationProvider.user_id == user.id, AuthenticationProvider.provider == provider_name).one()
if provider_auth.provider_id != user_provider_id:
... | Social login views definition. | SocialLoginViews | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SocialLoginViews:
"""Social login views definition."""
def set_provider(self, user, provider_name, user_provider_id):
"""Set authentication provider on user. This method will connect given provider with given user, unless provider_id has already been used on another user. :param pyra... | stack_v2_sparse_classes_75kplus_train_000067 | 8,669 | permissive | [
{
"docstring": "Set authentication provider on user. This method will connect given provider with given user, unless provider_id has already been used on another user. :param pyramid_fullauth.user.User user: user object :param str provider_name: provider name :param str user_provider_id: user id delivered by gi... | 5 | null | Implement the Python class `SocialLoginViews` described below.
Class description:
Social login views definition.
Method signatures and docstrings:
- def set_provider(self, user, provider_name, user_provider_id): Set authentication provider on user. This method will connect given provider with given user, unless provi... | Implement the Python class `SocialLoginViews` described below.
Class description:
Social login views definition.
Method signatures and docstrings:
- def set_provider(self, user, provider_name, user_provider_id): Set authentication provider on user. This method will connect given provider with given user, unless provi... | 0088fceeeb100497afc88a291ccc9b1ee9bfaa49 | <|skeleton|>
class SocialLoginViews:
"""Social login views definition."""
def set_provider(self, user, provider_name, user_provider_id):
"""Set authentication provider on user. This method will connect given provider with given user, unless provider_id has already been used on another user. :param pyra... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SocialLoginViews:
"""Social login views definition."""
def set_provider(self, user, provider_name, user_provider_id):
"""Set authentication provider on user. This method will connect given provider with given user, unless provider_id has already been used on another user. :param pyramid_fullauth.... | the_stack_v2_python_sparse | pyramid_fullauth/views/social.py | fizyk/pyramid_fullauth | train | 22 |
e0a26975717a4560f4f184dfd94261cb0577016c | [
"if len(names) == 0:\n self.leader = None\nelse:\n self.leader = Person(names[0])\n current_person = self.leader\n for name in names[1:]:\n current_person.next = Person(name)\n current_person = current_person.next",
"if not self.leader:\n raise ShortChainError\nelse:\n return self.... | <|body_start_0|>
if len(names) == 0:
self.leader = None
else:
self.leader = Person(names[0])
current_person = self.leader
for name in names[1:]:
current_person.next = Person(name)
current_person = current_person.next
<|end_b... | A chain of people. === Attributes === leader: Person | None The first person in the chain, or None if the chain is empty. | PeopleChain | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PeopleChain:
"""A chain of people. === Attributes === leader: Person | None The first person in the chain, or None if the chain is empty."""
def __init__(self, names: List[str]) -> None:
"""Create people linked together in the order provided in <names>. The leader of the chain is the... | stack_v2_sparse_classes_75kplus_train_000068 | 4,481 | no_license | [
{
"docstring": "Create people linked together in the order provided in <names>. The leader of the chain is the first person in <names>.",
"name": "__init__",
"signature": "def __init__(self, names: List[str]) -> None"
},
{
"docstring": "Return the name of the leader of the chain. Raise ShortChai... | 5 | stack_v2_sparse_classes_30k_train_044807 | Implement the Python class `PeopleChain` described below.
Class description:
A chain of people. === Attributes === leader: Person | None The first person in the chain, or None if the chain is empty.
Method signatures and docstrings:
- def __init__(self, names: List[str]) -> None: Create people linked together in the ... | Implement the Python class `PeopleChain` described below.
Class description:
A chain of people. === Attributes === leader: Person | None The first person in the chain, or None if the chain is empty.
Method signatures and docstrings:
- def __init__(self, names: List[str]) -> None: Create people linked together in the ... | b876b816ae2610ef18812371cd3ba7e92392b4f0 | <|skeleton|>
class PeopleChain:
"""A chain of people. === Attributes === leader: Person | None The first person in the chain, or None if the chain is empty."""
def __init__(self, names: List[str]) -> None:
"""Create people linked together in the order provided in <names>. The leader of the chain is the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PeopleChain:
"""A chain of people. === Attributes === leader: Person | None The first person in the chain, or None if the chain is empty."""
def __init__(self, names: List[str]) -> None:
"""Create people linked together in the order provided in <names>. The leader of the chain is the first person... | the_stack_v2_python_sparse | mini-exercises/mini exercise 2/chain.py | ColeRichardson/CSC148 | train | 0 |
9f6612c20775ec9469ae89dd92f50276327e5a22 | [
"super(PCC_Layer, self).__init__()\nself.alpha = alpha\nself.centroid = centroid",
"z = emb.unsqueeze(1)\nu = self.centroid\nqij = (1.0 + torch.sum((z - u) ** 2, dim=2) / self.alpha) ** (-1)\nqij_normalize = qij.T / torch.sum(qij, dim=1)\nqij_normalize = qij_normalize.T\nreturn qij_normalize"
] | <|body_start_0|>
super(PCC_Layer, self).__init__()
self.alpha = alpha
self.centroid = centroid
<|end_body_0|>
<|body_start_1|>
z = emb.unsqueeze(1)
u = self.centroid
qij = (1.0 + torch.sum((z - u) ** 2, dim=2) / self.alpha) ** (-1)
qij_normalize = qij.T / torch.s... | PCC_Layer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PCC_Layer:
def __init__(self, centroid, alpha=1.0):
""":param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)"""
<|body_0|>
def forward(self, emb):
"""see paper `Unsupervised Deep Embedding for Clustering Analysis` qij = 1/(1+dist(zi, uj)^2), then no... | stack_v2_sparse_classes_75kplus_train_000069 | 2,727 | no_license | [
{
"docstring": ":param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)",
"name": "__init__",
"signature": "def __init__(self, centroid, alpha=1.0)"
},
{
"docstring": "see paper `Unsupervised Deep Embedding for Clustering Analysis` qij = 1/(1+dist(zi, uj)^2), then normalize it. q... | 2 | stack_v2_sparse_classes_30k_train_053223 | Implement the Python class `PCC_Layer` described below.
Class description:
Implement the PCC_Layer class.
Method signatures and docstrings:
- def __init__(self, centroid, alpha=1.0): :param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)
- def forward(self, emb): see paper `Unsupervised Deep Embeddin... | Implement the Python class `PCC_Layer` described below.
Class description:
Implement the PCC_Layer class.
Method signatures and docstrings:
- def __init__(self, centroid, alpha=1.0): :param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)
- def forward(self, emb): see paper `Unsupervised Deep Embeddin... | 4e5908eb4c230e80e7d49bdbd77e7ec73de327c6 | <|skeleton|>
class PCC_Layer:
def __init__(self, centroid, alpha=1.0):
""":param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)"""
<|body_0|>
def forward(self, emb):
"""see paper `Unsupervised Deep Embedding for Clustering Analysis` qij = 1/(1+dist(zi, uj)^2), then no... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PCC_Layer:
def __init__(self, centroid, alpha=1.0):
""":param centroid: tensor, predefined centroid, shape: (n_class, emb_dim)"""
super(PCC_Layer, self).__init__()
self.alpha = alpha
self.centroid = centroid
def forward(self, emb):
"""see paper `Unsupervised Deep E... | the_stack_v2_python_sparse | network_torch/Dual_CSA.py | lusccc/Trajectory-Classification-using-Dual-CSA | train | 10 | |
d747529797c266d0199220879c7cdd9392d532d6 | [
"super().__init__(embed_dim, num_heads, dropout=dropout, bias=True, add_bias_kv=False, add_zero_attn=add_zero_attn, kdim=None, vdim=None)\nself.id_out_weight = torch.eye(self.head_dim)\nself.id_out_bias = torch.zeros(self.head_dim)",
"query = query.transpose(1, 0)\nkey = key.transpose(1, 0)\nvalue = value.transpo... | <|body_start_0|>
super().__init__(embed_dim, num_heads, dropout=dropout, bias=True, add_bias_kv=False, add_zero_attn=add_zero_attn, kdim=None, vdim=None)
self.id_out_weight = torch.eye(self.head_dim)
self.id_out_bias = torch.zeros(self.head_dim)
<|end_body_0|>
<|body_start_1|>
query = q... | MultiheadAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiheadAttention:
def __init__(self, embed_dim, num_heads, dropout=0.0, add_zero_attn=False):
"""Same as `torch.nn.MultiheadAttention`, but with option to return attention weights for each head separately instead of as average. Disallow specifying bias, add_bias_kv, kdim, vdim."""
... | stack_v2_sparse_classes_75kplus_train_000070 | 20,414 | no_license | [
{
"docstring": "Same as `torch.nn.MultiheadAttention`, but with option to return attention weights for each head separately instead of as average. Disallow specifying bias, add_bias_kv, kdim, vdim.",
"name": "__init__",
"signature": "def __init__(self, embed_dim, num_heads, dropout=0.0, add_zero_attn=Fa... | 2 | stack_v2_sparse_classes_30k_train_028088 | Implement the Python class `MultiheadAttention` described below.
Class description:
Implement the MultiheadAttention class.
Method signatures and docstrings:
- def __init__(self, embed_dim, num_heads, dropout=0.0, add_zero_attn=False): Same as `torch.nn.MultiheadAttention`, but with option to return attention weights... | Implement the Python class `MultiheadAttention` described below.
Class description:
Implement the MultiheadAttention class.
Method signatures and docstrings:
- def __init__(self, embed_dim, num_heads, dropout=0.0, add_zero_attn=False): Same as `torch.nn.MultiheadAttention`, but with option to return attention weights... | 793543ebd3e526bdd8931a269fdf17808762d9bc | <|skeleton|>
class MultiheadAttention:
def __init__(self, embed_dim, num_heads, dropout=0.0, add_zero_attn=False):
"""Same as `torch.nn.MultiheadAttention`, but with option to return attention weights for each head separately instead of as average. Disallow specifying bias, add_bias_kv, kdim, vdim."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MultiheadAttention:
def __init__(self, embed_dim, num_heads, dropout=0.0, add_zero_attn=False):
"""Same as `torch.nn.MultiheadAttention`, but with option to return attention weights for each head separately instead of as average. Disallow specifying bias, add_bias_kv, kdim, vdim."""
super().__... | the_stack_v2_python_sparse | seqmodel/model/transformer.py | devinkwok/seqmodelv2 | train | 0 | |
bb199b1e282a9949748c56fcefd6739e6d05e6de | [
"self.feature_of_interest_id = BNode()\nself.label = Literal(label)\nself.comment = Literal(comment)",
"return self.feature_of_interest_id\nobsgraph.add((self.feature_of_interest_id, RDF.type, sosa.FeatureOfInterest))\nobsgraph.add((self.feature_of_interest_id, RDFS.comment, self.comment))\nobsgraph.add((self.fea... | <|body_start_0|>
self.feature_of_interest_id = BNode()
self.label = Literal(label)
self.comment = Literal(comment)
<|end_body_0|>
<|body_start_1|>
return self.feature_of_interest_id
obsgraph.add((self.feature_of_interest_id, RDF.type, sosa.FeatureOfInterest))
obsgraph.ad... | Creates a feature of interest object representing SOSA FOI The thing whose property is being estimated or calculated in the course of an Observation to arrive at a Result, or whose property is being manipulated by an Actuator, or which is being sampled or transformed in an act of Sampling. | FeatureOfInterest | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureOfInterest:
"""Creates a feature of interest object representing SOSA FOI The thing whose property is being estimated or calculated in the course of an Observation to arrive at a Result, or whose property is being manipulated by an Actuator, or which is being sampled or transformed in an a... | stack_v2_sparse_classes_75kplus_train_000071 | 1,302 | permissive | [
{
"docstring": "constructor for Feature of Interest Args: label, comment (literal): label and comment for the feature of interest Returns: FOI object: instantiated with feature_of_interest_id, label and comment",
"name": "__init__",
"signature": "def __init__(self, label, comment)"
},
{
"docstri... | 2 | stack_v2_sparse_classes_30k_train_004893 | Implement the Python class `FeatureOfInterest` described below.
Class description:
Creates a feature of interest object representing SOSA FOI The thing whose property is being estimated or calculated in the course of an Observation to arrive at a Result, or whose property is being manipulated by an Actuator, or which ... | Implement the Python class `FeatureOfInterest` described below.
Class description:
Creates a feature of interest object representing SOSA FOI The thing whose property is being estimated or calculated in the course of an Observation to arrive at a Result, or whose property is being manipulated by an Actuator, or which ... | 1993668bd75bc882286da818955a40dd01d2f7c6 | <|skeleton|>
class FeatureOfInterest:
"""Creates a feature of interest object representing SOSA FOI The thing whose property is being estimated or calculated in the course of an Observation to arrive at a Result, or whose property is being manipulated by an Actuator, or which is being sampled or transformed in an a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeatureOfInterest:
"""Creates a feature of interest object representing SOSA FOI The thing whose property is being estimated or calculated in the course of an Observation to arrive at a Result, or whose property is being manipulated by an Actuator, or which is being sampled or transformed in an act of Samplin... | the_stack_v2_python_sparse | PySOSA/FeatureOfInterest.py | landrs-toolkit/PySOSA | train | 1 |
7bb0d73167a60aa90d9d8ddaae89802b3571ad85 | [
"TestCommand.finalize_options(self)\nself.test_args = []\nself.test_suite = True",
"import tox\nerrcode = tox.cmdline(self.test_args)\nsys.exit(errcode)"
] | <|body_start_0|>
TestCommand.finalize_options(self)
self.test_args = []
self.test_suite = True
<|end_body_0|>
<|body_start_1|>
import tox
errcode = tox.cmdline(self.test_args)
sys.exit(errcode)
<|end_body_1|>
| Runs Tox comands | Tox | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tox:
"""Runs Tox comands"""
def finalize_options(self):
"""preps test suite"""
<|body_0|>
def run_tests(self):
"""runs test suite"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
TestCommand.finalize_options(self)
self.test_args = []
... | stack_v2_sparse_classes_75kplus_train_000072 | 752 | permissive | [
{
"docstring": "preps test suite",
"name": "finalize_options",
"signature": "def finalize_options(self)"
},
{
"docstring": "runs test suite",
"name": "run_tests",
"signature": "def run_tests(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_024056 | Implement the Python class `Tox` described below.
Class description:
Runs Tox comands
Method signatures and docstrings:
- def finalize_options(self): preps test suite
- def run_tests(self): runs test suite | Implement the Python class `Tox` described below.
Class description:
Runs Tox comands
Method signatures and docstrings:
- def finalize_options(self): preps test suite
- def run_tests(self): runs test suite
<|skeleton|>
class Tox:
"""Runs Tox comands"""
def finalize_options(self):
"""preps test suite... | 3abf8b93c6d1c162cba3e7cb2a1777dadbaffebe | <|skeleton|>
class Tox:
"""Runs Tox comands"""
def finalize_options(self):
"""preps test suite"""
<|body_0|>
def run_tests(self):
"""runs test suite"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Tox:
"""Runs Tox comands"""
def finalize_options(self):
"""preps test suite"""
TestCommand.finalize_options(self)
self.test_args = []
self.test_suite = True
def run_tests(self):
"""runs test suite"""
import tox
errcode = tox.cmdline(self.test_a... | the_stack_v2_python_sparse | setup.py | pcaruana/armada | train | 0 |
13a2825e1dba546a69beb6a2cda328345ef71920 | [
"n = len(nums)\nif n * k == 0:\n return []\nreturn [max(nums[i:i + k]) for i in range(n - k + 1)]",
"size = len(nums)\nif size * k == 0:\n return []\nif size == 1:\n return nums\nqueue, output, max_idx = (deque(), [], 0)\n\ndef clean_up(index: int):\n if queue and queue[0] == index - k:\n queue... | <|body_start_0|>
n = len(nums)
if n * k == 0:
return []
return [max(nums[i:i + k]) for i in range(n - k + 1)]
<|end_body_0|>
<|body_start_1|>
size = len(nums)
if size * k == 0:
return []
if size == 1:
return nums
queue, output,... | SlidingWindow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SlidingWindow:
def get_max_in_window__(self, nums: List[int], k: int) -> List[int]:
"""Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:"""
<|body_0|>
def get_max_in_window_(self, nums: List[int], k: int) -> List[int]:
... | stack_v2_sparse_classes_75kplus_train_000073 | 2,981 | no_license | [
{
"docstring": "Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:",
"name": "get_max_in_window__",
"signature": "def get_max_in_window__(self, nums: List[int], k: int) -> List[int]"
},
{
"docstring": "Approach: Using Deque Time Complexity: O(N) Spa... | 3 | stack_v2_sparse_classes_30k_train_037481 | Implement the Python class `SlidingWindow` described below.
Class description:
Implement the SlidingWindow class.
Method signatures and docstrings:
- def get_max_in_window__(self, nums: List[int], k: int) -> List[int]: Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:
-... | Implement the Python class `SlidingWindow` described below.
Class description:
Implement the SlidingWindow class.
Method signatures and docstrings:
- def get_max_in_window__(self, nums: List[int], k: int) -> List[int]: Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:
-... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class SlidingWindow:
def get_max_in_window__(self, nums: List[int], k: int) -> List[int]:
"""Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:"""
<|body_0|>
def get_max_in_window_(self, nums: List[int], k: int) -> List[int]:
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SlidingWindow:
def get_max_in_window__(self, nums: List[int], k: int) -> List[int]:
"""Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:"""
n = len(nums)
if n * k == 0:
return []
return [max(nums[i:i + k]) for i in ran... | the_stack_v2_python_sparse | revisited/arrays/sliding_window.py | Shiv2157k/leet_code | train | 1 | |
3077b4a38ab4845fb78851c919da24877c0f68af | [
"super().__init__(*args, **kwargs)\nself.token = config.get('api-token', None)\nself.chatid = config.get('chat-id', None)\nif self.token is not None and self.chatid is not None:\n self.useable = True\nelse:\n self.useable = False",
"if self.useable:\n message = self.format(record)\n thread = threading... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.token = config.get('api-token', None)
self.chatid = config.get('chat-id', None)
if self.token is not None and self.chatid is not None:
self.useable = True
else:
self.useable = False
<|end_body_0|>
<|... | A logging.StreamHandler which handles log dispatching to a Telegram-Bot. | TelegramHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TelegramHandler:
"""A logging.StreamHandler which handles log dispatching to a Telegram-Bot."""
def __init__(self, *args, **kwargs):
"""Construct a logging.StreamHandler which sends messages to a bot. This StreamHandler relies on the contents of api-token and chat-id in src/utils/tel... | stack_v2_sparse_classes_75kplus_train_000074 | 3,270 | permissive | [
{
"docstring": "Construct a logging.StreamHandler which sends messages to a bot. This StreamHandler relies on the contents of api-token and chat-id in src/utils/telegram.py. They get generated by either environment variables or a telegram.json file in src/utils. For more details look at the source code! The com... | 2 | null | Implement the Python class `TelegramHandler` described below.
Class description:
A logging.StreamHandler which handles log dispatching to a Telegram-Bot.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Construct a logging.StreamHandler which sends messages to a bot. This StreamHandler relies ... | Implement the Python class `TelegramHandler` described below.
Class description:
A logging.StreamHandler which handles log dispatching to a Telegram-Bot.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Construct a logging.StreamHandler which sends messages to a bot. This StreamHandler relies ... | 7f0086d2cdec23b49958c5afc0e6d12a08598465 | <|skeleton|>
class TelegramHandler:
"""A logging.StreamHandler which handles log dispatching to a Telegram-Bot."""
def __init__(self, *args, **kwargs):
"""Construct a logging.StreamHandler which sends messages to a bot. This StreamHandler relies on the contents of api-token and chat-id in src/utils/tel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TelegramHandler:
"""A logging.StreamHandler which handles log dispatching to a Telegram-Bot."""
def __init__(self, *args, **kwargs):
"""Construct a logging.StreamHandler which sends messages to a bot. This StreamHandler relies on the contents of api-token and chat-id in src/utils/telegram.py. The... | the_stack_v2_python_sparse | src/utils/telegram.py | image357/conex-generator | train | 0 |
122b0681a25c45b66b89c7f99c1b562d6e44ffbd | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(email=MyUserManager.normalize_email(email), date_of_birth=date_of_birth or timezone.now(), first_name=first_name or '', last_name=last_name or '')\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"if ... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=MyUserManager.normalize_email(email), date_of_birth=date_of_birth or timezone.now(), first_name=first_name or '', last_name=last_name or '')
user.set_password(password)
... | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, date_of_birth, first_name, last_name... | stack_v2_sparse_classes_75kplus_train_000075 | 1,411 | 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, email, first_name=None, last_name=None, date_of_birth=None, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given emai... | 2 | stack_v2_sparse_classes_30k_train_051026 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None): Creates and saves a User with the given email, date of birth and passw... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None): Creates and saves a User with the given email, date of birth and passw... | 42654f6c058de095ac6ff540bdd89854b7f864f9 | <|skeleton|>
class MyUserManager:
def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, date_of_birth, first_name, last_name... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyUserManager:
def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
if not email:
raise ValueError('Users must have an email address')
user = self.m... | the_stack_v2_python_sparse | thesis/DavideCrestini/tesi-crestini/Piattaforma/services/managers.py | lbedogni/iot | train | 0 | |
c25f12f104c9433903baa15292696b05b0171894 | [
"super(CustomEdit, self).__init__(None, parent)\nself.w = size[2]\nself.h = size[3]\nself.setGeometry(*size)\nself.setObjectName(name)\nself.drag_flag = False\nif drag:\n self.setAcceptDrops(True)\n self.setDragEnabled(True)\nelse:\n self.setAcceptDrops(False)\n self.setDragEnabled(False)\nself.click_fl... | <|body_start_0|>
super(CustomEdit, self).__init__(None, parent)
self.w = size[2]
self.h = size[3]
self.setGeometry(*size)
self.setObjectName(name)
self.drag_flag = False
if drag:
self.setAcceptDrops(True)
self.setDragEnabled(True)
e... | 带下拉框的文本输入框类（文本下拉输入框），输入文字可以搜索内容 | CustomEdit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomEdit:
"""带下拉框的文本输入框类（文本下拉输入框），输入文字可以搜索内容"""
def __init__(self, parent, size=(50, 50, 100, 20), name='edit', drag=False, text_list=True, search=True, qss_file=''):
"""初始化控件 :param parent: 控件显示的父对象 :param size: 输入框控件尺寸 :param name: 输入框控件名称 :param drag: 拖放标识位 :param text_list: 是否开... | stack_v2_sparse_classes_75kplus_train_000076 | 5,622 | no_license | [
{
"docstring": "初始化控件 :param parent: 控件显示的父对象 :param size: 输入框控件尺寸 :param name: 输入框控件名称 :param drag: 拖放标识位 :param text_list: 是否开启下拉框功能标识位",
"name": "__init__",
"signature": "def __init__(self, parent, size=(50, 50, 100, 20), name='edit', drag=False, text_list=True, search=True, qss_file='')"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_033255 | Implement the Python class `CustomEdit` described below.
Class description:
带下拉框的文本输入框类（文本下拉输入框），输入文字可以搜索内容
Method signatures and docstrings:
- def __init__(self, parent, size=(50, 50, 100, 20), name='edit', drag=False, text_list=True, search=True, qss_file=''): 初始化控件 :param parent: 控件显示的父对象 :param size: 输入框控件尺寸 :par... | Implement the Python class `CustomEdit` described below.
Class description:
带下拉框的文本输入框类（文本下拉输入框），输入文字可以搜索内容
Method signatures and docstrings:
- def __init__(self, parent, size=(50, 50, 100, 20), name='edit', drag=False, text_list=True, search=True, qss_file=''): 初始化控件 :param parent: 控件显示的父对象 :param size: 输入框控件尺寸 :par... | 925612139b6ac62dfb0c1a5d143485f1fd36645a | <|skeleton|>
class CustomEdit:
"""带下拉框的文本输入框类（文本下拉输入框），输入文字可以搜索内容"""
def __init__(self, parent, size=(50, 50, 100, 20), name='edit', drag=False, text_list=True, search=True, qss_file=''):
"""初始化控件 :param parent: 控件显示的父对象 :param size: 输入框控件尺寸 :param name: 输入框控件名称 :param drag: 拖放标识位 :param text_list: 是否开... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomEdit:
"""带下拉框的文本输入框类（文本下拉输入框），输入文字可以搜索内容"""
def __init__(self, parent, size=(50, 50, 100, 20), name='edit', drag=False, text_list=True, search=True, qss_file=''):
"""初始化控件 :param parent: 控件显示的父对象 :param size: 输入框控件尺寸 :param name: 输入框控件名称 :param drag: 拖放标识位 :param text_list: 是否开启下拉框功能标识位"""
... | the_stack_v2_python_sparse | Custom_Edit.py | harry2002731/Stock-programe | train | 2 |
4db32db61e02696d8c3ccb2bd54c42a3e6579a0d | [
"self.__dict__.update(dict_data)\nself.comparable_service = comparable_name(self.service)\nself.formatted_date = formatted_github_day_and_time(self.date)",
"config_dict = service.config.copy()\nconfig_dict['service'] = service.name\nconfig_dict['site'] = service.site_name\nif service.config.get('sha', False):\n ... | <|body_start_0|>
self.__dict__.update(dict_data)
self.comparable_service = comparable_name(self.service)
self.formatted_date = formatted_github_day_and_time(self.date)
<|end_body_0|>
<|body_start_1|>
config_dict = service.config.copy()
config_dict['service'] = service.name
... | ServiceConfig | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceConfig:
def __init__(self, **dict_data):
"""The dict_data contains all the service config's attributes: Ex. { "service": "billweb", "author": "chrisg@surveymonkey.com", "site": "mt1", "sha": "3a2df77fbcf804165c8e79e3d22d05fa3798e405", "date": "2012-03-06T15:17:44-08:00", "message"... | stack_v2_sparse_classes_75kplus_train_000077 | 1,283 | permissive | [
{
"docstring": "The dict_data contains all the service config's attributes: Ex. { \"service\": \"billweb\", \"author\": \"chrisg@surveymonkey.com\", \"site\": \"mt1\", \"sha\": \"3a2df77fbcf804165c8e79e3d22d05fa3798e405\", \"date\": \"2012-03-06T15:17:44-08:00\", \"message\": \"Add ho-DOR\" }",
"name": "__i... | 2 | null | Implement the Python class `ServiceConfig` described below.
Class description:
Implement the ServiceConfig class.
Method signatures and docstrings:
- def __init__(self, **dict_data): The dict_data contains all the service config's attributes: Ex. { "service": "billweb", "author": "chrisg@surveymonkey.com", "site": "m... | Implement the Python class `ServiceConfig` described below.
Class description:
Implement the ServiceConfig class.
Method signatures and docstrings:
- def __init__(self, **dict_data): The dict_data contains all the service config's attributes: Ex. { "service": "billweb", "author": "chrisg@surveymonkey.com", "site": "m... | 239a8c522c9d3488920581f802f7a1ef1f5f6355 | <|skeleton|>
class ServiceConfig:
def __init__(self, **dict_data):
"""The dict_data contains all the service config's attributes: Ex. { "service": "billweb", "author": "chrisg@surveymonkey.com", "site": "mt1", "sha": "3a2df77fbcf804165c8e79e3d22d05fa3798e405", "date": "2012-03-06T15:17:44-08:00", "message"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ServiceConfig:
def __init__(self, **dict_data):
"""The dict_data contains all the service config's attributes: Ex. { "service": "billweb", "author": "chrisg@surveymonkey.com", "site": "mt1", "sha": "3a2df77fbcf804165c8e79e3d22d05fa3798e405", "date": "2012-03-06T15:17:44-08:00", "message": "Add ho-DOR"... | the_stack_v2_python_sparse | doula/models/service_config.py | msabramo/Doula | train | 0 | |
3b953875149dd9710aca7dac868373a618172a95 | [
"xx = np.vstack([x for i in range(N)]).T\nyy = np.vstack([y + np.random.normal(loc=0, scale=yerr) for i in range(N)]).T\nself._splines = [spline(x, yy[:, i], *args, **kwargs) for i in range(N)]",
"x = np.atleast_1d(x)\ns = np.vstack([curve(x, *args, **kwargs) for curve in self._splines])\nreturn (np.mean(s, axis=... | <|body_start_0|>
xx = np.vstack([x for i in range(N)]).T
yy = np.vstack([y + np.random.normal(loc=0, scale=yerr) for i in range(N)]).T
self._splines = [spline(x, yy[:, i], *args, **kwargs) for i in range(N)]
<|end_body_0|>
<|body_start_1|>
x = np.atleast_1d(x)
s = np.vstack([cur... | Does a spline fit, but returns both the spline value and associated uncertainty. This accomplishes the task by generating lots of splines, and return the mean and standard deviation of the spline values at the requested coordinates. It is therefore roughly N times slower than a normal spline! | ErrorPropagationSpline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ErrorPropagationSpline:
"""Does a spline fit, but returns both the spline value and associated uncertainty. This accomplishes the task by generating lots of splines, and return the mean and standard deviation of the spline values at the requested coordinates. It is therefore roughly N times slowe... | stack_v2_sparse_classes_75kplus_train_000078 | 47,749 | permissive | [
{
"docstring": "See docstring for InterpolatedUnivariateSpline The parameter `N` gives the number of splines to generate for error propagation.",
"name": "__init__",
"signature": "def __init__(self, x, y, yerr, N=1000, *args, **kwargs)"
},
{
"docstring": "Get the spline value and uncertainty at ... | 2 | stack_v2_sparse_classes_30k_train_031960 | Implement the Python class `ErrorPropagationSpline` described below.
Class description:
Does a spline fit, but returns both the spline value and associated uncertainty. This accomplishes the task by generating lots of splines, and return the mean and standard deviation of the spline values at the requested coordinates... | Implement the Python class `ErrorPropagationSpline` described below.
Class description:
Does a spline fit, but returns both the spline value and associated uncertainty. This accomplishes the task by generating lots of splines, and return the mean and standard deviation of the spline values at the requested coordinates... | 8a9f00a6977dad8d4477eef1d664fd62e9ecab75 | <|skeleton|>
class ErrorPropagationSpline:
"""Does a spline fit, but returns both the spline value and associated uncertainty. This accomplishes the task by generating lots of splines, and return the mean and standard deviation of the spline values at the requested coordinates. It is therefore roughly N times slowe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ErrorPropagationSpline:
"""Does a spline fit, but returns both the spline value and associated uncertainty. This accomplishes the task by generating lots of splines, and return the mean and standard deviation of the spline values at the requested coordinates. It is therefore roughly N times slower than a norm... | the_stack_v2_python_sparse | kglib/utils/HelperFunctions.py | kgullikson88/gullikson-scripts | train | 4 |
ebde779893a9261774b027f7e556b200470fcffe | [
"n = len(piles)\n'\\n Greedy approach does not work. One can try a few cases to see this.\\n DP is the way. What are the states? Playing this game requires one to choose\\n from either left end or right end. This should give a hint for (l,r) or (i,j)\\n Then the game is played by two pla... | <|body_start_0|>
n = len(piles)
'\n Greedy approach does not work. One can try a few cases to see this.\n DP is the way. What are the states? Playing this game requires one to choose\n from either left end or right end. This should give a hint for (l,r) or (i,j)\n Then the ga... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def stoneGame(self, piles):
""":type piles: List[int] :rtype: bool"""
<|body_0|>
def stoneGameDPfast(self, piles):
""":type piles: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(piles)
'\n Gre... | stack_v2_sparse_classes_75kplus_train_000079 | 5,113 | no_license | [
{
"docstring": ":type piles: List[int] :rtype: bool",
"name": "stoneGame",
"signature": "def stoneGame(self, piles)"
},
{
"docstring": ":type piles: List[int] :rtype: bool",
"name": "stoneGameDPfast",
"signature": "def stoneGameDPfast(self, piles)"
}
] | 2 | stack_v2_sparse_classes_30k_train_024087 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def stoneGame(self, piles): :type piles: List[int] :rtype: bool
- def stoneGameDPfast(self, piles): :type piles: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def stoneGame(self, piles): :type piles: List[int] :rtype: bool
- def stoneGameDPfast(self, piles): :type piles: List[int] :rtype: bool
<|skeleton|>
class Solution:
def sto... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def stoneGame(self, piles):
""":type piles: List[int] :rtype: bool"""
<|body_0|>
def stoneGameDPfast(self, piles):
""":type piles: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def stoneGame(self, piles):
""":type piles: List[int] :rtype: bool"""
n = len(piles)
'\n Greedy approach does not work. One can try a few cases to see this.\n DP is the way. What are the states? Playing this game requires one to choose\n from either left ... | the_stack_v2_python_sparse | S/StoneGame.py | bssrdf/pyleet | train | 2 | |
5533738cfe772ea3bb4f6f84500b97841a7e4725 | [
"if self.field:\n return 'Summary aggregations for \"{0:s}\"'.format(self.field)\nreturn 'Summary aggregations for an unknown field.'",
"self.field = field\nself.field_query_string = field_query_string\nformatted_field_name = self.format_field_by_type(field)\nif field_query_string == '*':\n formatted_field_... | <|body_start_0|>
if self.field:
return 'Summary aggregations for "{0:s}"'.format(self.field)
return 'Summary aggregations for an unknown field.'
<|end_body_0|>
<|body_start_1|>
self.field = field
self.field_query_string = field_query_string
formatted_field_name = sel... | Summary Aggregations. | SummaryAggregation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SummaryAggregation:
"""Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
<|body_0|>
def run(self, field, field_query_string='*', start_time='', end_time='', most_common_limit=10, rare_value_document_limit=5):
"""Runs the Summary... | stack_v2_sparse_classes_75kplus_train_000080 | 13,136 | permissive | [
{
"docstring": "Returns a title for the chart.",
"name": "chart_title",
"signature": "def chart_title(self)"
},
{
"docstring": "Runs the SummaryAggregation aggregator. Args: field: What field to aggregate on. field_query_string: The field value(s) to aggregate on. supported_charts: The chart typ... | 2 | stack_v2_sparse_classes_30k_train_026043 | Implement the Python class `SummaryAggregation` described below.
Class description:
Summary Aggregations.
Method signatures and docstrings:
- def chart_title(self): Returns a title for the chart.
- def run(self, field, field_query_string='*', start_time='', end_time='', most_common_limit=10, rare_value_document_limit... | Implement the Python class `SummaryAggregation` described below.
Class description:
Summary Aggregations.
Method signatures and docstrings:
- def chart_title(self): Returns a title for the chart.
- def run(self, field, field_query_string='*', start_time='', end_time='', most_common_limit=10, rare_value_document_limit... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class SummaryAggregation:
"""Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
<|body_0|>
def run(self, field, field_query_string='*', start_time='', end_time='', most_common_limit=10, rare_value_document_limit=5):
"""Runs the Summary... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SummaryAggregation:
"""Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
if self.field:
return 'Summary aggregations for "{0:s}"'.format(self.field)
return 'Summary aggregations for an unknown field.'
def run(self, field, field_q... | the_stack_v2_python_sparse | timesketch/lib/aggregators/summary.py | google/timesketch | train | 2,263 |
b6b789d8ac801d10a3d0eedcf367452c3210483e | [
"len_a = 0\nlen_b = 0\na = headA\nwhile a:\n len_a += 1\n a = a.next\nb = headB\nwhile b:\n len_b += 1\n b = b.next\nif len_a < len_b:\n headA, headB = (headB, headA)\n len_a, len_b = (len_b, len_a)\nfor _ in range(len_a - len_b):\n headA = headA.next\nwhile headA:\n if headA == headB:\n ... | <|body_start_0|>
len_a = 0
len_b = 0
a = headA
while a:
len_a += 1
a = a.next
b = headB
while b:
len_b += 1
b = b.next
if len_a < len_b:
headA, headB = (headB, headA)
len_a, len_b = (len_b, le... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getIntersectionNode1(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def getIntersectionNode2(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_1|>
def getIntersectionNode3(s... | stack_v2_sparse_classes_75kplus_train_000081 | 2,598 | no_license | [
{
"docstring": ":type head1, head1: ListNode :rtype: ListNode",
"name": "getIntersectionNode1",
"signature": "def getIntersectionNode1(self, headA, headB)"
},
{
"docstring": ":type head1, head1: ListNode :rtype: ListNode",
"name": "getIntersectionNode2",
"signature": "def getIntersection... | 4 | stack_v2_sparse_classes_30k_train_007013 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode1(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def getIntersectionNode2(self, headA, headB): :type head1, head1: ListNode :rtype: L... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getIntersectionNode1(self, headA, headB): :type head1, head1: ListNode :rtype: ListNode
- def getIntersectionNode2(self, headA, headB): :type head1, head1: ListNode :rtype: L... | 8fb6c1d947046dabd58ff8482b2c0b41f39aa988 | <|skeleton|>
class Solution:
def getIntersectionNode1(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_0|>
def getIntersectionNode2(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
<|body_1|>
def getIntersectionNode3(s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def getIntersectionNode1(self, headA, headB):
""":type head1, head1: ListNode :rtype: ListNode"""
len_a = 0
len_b = 0
a = headA
while a:
len_a += 1
a = a.next
b = headB
while b:
len_b += 1
b = b.n... | the_stack_v2_python_sparse | Python/LeetCode/160.py | czx94/Algorithms-Collection | train | 2 | |
973a1b2eceea1137486521b730f9110f3ff40762 | [
"\"\"\" Threading Data \"\"\"\nself.GRID_LOCK = GRID_LOCK\n' Surface Display Data '\nself.subsurface = subsurface\nself.clean_subsurface = subsurface.copy()\nself.x = coordinates[0]\nself.y = coordinates[1]\n' Surface Design Data'\nself.clock_font = pygame.font.SysFont('arial', 28, True, False) if font is None els... | <|body_start_0|>
""" Threading Data """
self.GRID_LOCK = GRID_LOCK
' Surface Display Data '
self.subsurface = subsurface
self.clean_subsurface = subsurface.copy()
self.x = coordinates[0]
self.y = coordinates[1]
' Surface Design Data'
self.clock_fo... | GameClock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameClock:
def __init__(self, GRID_LOCK, subsurface, coordinates, font=None):
""":param GRID_LOCK: :param subsurface: :param coordinates:"""
<|body_0|>
def run(self):
"""Runs the game clock"""
<|body_1|>
def display(self):
"""Displays the time st... | stack_v2_sparse_classes_75kplus_train_000082 | 2,449 | no_license | [
{
"docstring": ":param GRID_LOCK: :param subsurface: :param coordinates:",
"name": "__init__",
"signature": "def __init__(self, GRID_LOCK, subsurface, coordinates, font=None)"
},
{
"docstring": "Runs the game clock",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "... | 3 | null | Implement the Python class `GameClock` described below.
Class description:
Implement the GameClock class.
Method signatures and docstrings:
- def __init__(self, GRID_LOCK, subsurface, coordinates, font=None): :param GRID_LOCK: :param subsurface: :param coordinates:
- def run(self): Runs the game clock
- def display(s... | Implement the Python class `GameClock` described below.
Class description:
Implement the GameClock class.
Method signatures and docstrings:
- def __init__(self, GRID_LOCK, subsurface, coordinates, font=None): :param GRID_LOCK: :param subsurface: :param coordinates:
- def run(self): Runs the game clock
- def display(s... | 8995bd57ae0faaf7420c74e1a7b2c091c64d6942 | <|skeleton|>
class GameClock:
def __init__(self, GRID_LOCK, subsurface, coordinates, font=None):
""":param GRID_LOCK: :param subsurface: :param coordinates:"""
<|body_0|>
def run(self):
"""Runs the game clock"""
<|body_1|>
def display(self):
"""Displays the time st... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GameClock:
def __init__(self, GRID_LOCK, subsurface, coordinates, font=None):
""":param GRID_LOCK: :param subsurface: :param coordinates:"""
""" Threading Data """
self.GRID_LOCK = GRID_LOCK
' Surface Display Data '
self.subsurface = subsurface
self.clean_subsu... | the_stack_v2_python_sparse | widgets/widget___game_clock.py | EcoSimulator/EcoSim2.0 | train | 0 | |
9e334ff611cc040556c187b536407a49560c945d | [
"serializer = self.get_serializer(data=request.data)\nserializer.is_valid(raise_exception=True)\nserializer.preview()\nreturn Response(serializer.data, status=status.HTTP_200_OK)",
"self.get_object()\nserializer = self.get_serializer(data=request.data)\nserializer.is_valid(raise_exception=True)\nserializer.cancel... | <|body_start_0|>
serializer = self.get_serializer(data=request.data)
serializer.is_valid(raise_exception=True)
serializer.preview()
return Response(serializer.data, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
self.get_object()
serializer = self.get_seriali... | Quote ViewSet. | QuoteViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuoteViewSet:
"""Quote ViewSet."""
def preview(self, request, *args, **kwargs):
"""Same as `create` but without actually saving the changes."""
<|body_0|>
def cancel(self, request, *args, **kwargs):
"""Cancel a quote."""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_75kplus_train_000083 | 2,551 | permissive | [
{
"docstring": "Same as `create` but without actually saving the changes.",
"name": "preview",
"signature": "def preview(self, request, *args, **kwargs)"
},
{
"docstring": "Cancel a quote.",
"name": "cancel",
"signature": "def cancel(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_027828 | Implement the Python class `QuoteViewSet` described below.
Class description:
Quote ViewSet.
Method signatures and docstrings:
- def preview(self, request, *args, **kwargs): Same as `create` but without actually saving the changes.
- def cancel(self, request, *args, **kwargs): Cancel a quote. | Implement the Python class `QuoteViewSet` described below.
Class description:
Quote ViewSet.
Method signatures and docstrings:
- def preview(self, request, *args, **kwargs): Same as `create` but without actually saving the changes.
- def cancel(self, request, *args, **kwargs): Cancel a quote.
<|skeleton|>
class Quot... | a92faabf73fb93b5bfd94fd465eafc3e29aa6d8e | <|skeleton|>
class QuoteViewSet:
"""Quote ViewSet."""
def preview(self, request, *args, **kwargs):
"""Same as `create` but without actually saving the changes."""
<|body_0|>
def cancel(self, request, *args, **kwargs):
"""Cancel a quote."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QuoteViewSet:
"""Quote ViewSet."""
def preview(self, request, *args, **kwargs):
"""Same as `create` but without actually saving the changes."""
serializer = self.get_serializer(data=request.data)
serializer.is_valid(raise_exception=True)
serializer.preview()
return... | the_stack_v2_python_sparse | datahub/omis/quote/views.py | cgsunkel/data-hub-api | train | 0 |
3f0852cff7c49d86edf3535a79447785075f4ccb | [
"if not root:\n return -1\nret = 1 + max((self.find_leaves_helper(child, results) for child in (root.left, root.right)))\nif ret >= len(results):\n results.append([])\nresults[ret].append(root.val)\nreturn ret",
"ret = []\nself.find_leaves_helper(root, ret)\nreturn ret"
] | <|body_start_0|>
if not root:
return -1
ret = 1 + max((self.find_leaves_helper(child, results) for child in (root.left, root.right)))
if ret >= len(results):
results.append([])
results[ret].append(root.val)
return ret
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def find_leaves_helper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
<|body_0|>
def find_leaves(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_000084 | 1,688 | no_license | [
{
"docstring": "push root and all descendants to results return the distance from root to farthest leaf",
"name": "find_leaves_helper",
"signature": "def find_leaves_helper(self, root, results)"
},
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "find_leaves",
"sig... | 2 | stack_v2_sparse_classes_30k_train_044384 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_leaves_helper(self, root, results): push root and all descendants to results return the distance from root to farthest leaf
- def find_leaves(self, root): :type root: Tr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_leaves_helper(self, root, results): push root and all descendants to results return the distance from root to farthest leaf
- def find_leaves(self, root): :type root: Tr... | e3637e293c5e4e8b4e5cc2e24dcd638ef796c560 | <|skeleton|>
class Solution:
def find_leaves_helper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
<|body_0|>
def find_leaves(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def find_leaves_helper(self, root, results):
"""push root and all descendants to results return the distance from root to farthest leaf"""
if not root:
return -1
ret = 1 + max((self.find_leaves_helper(child, results) for child in (root.left, root.right)))
... | the_stack_v2_python_sparse | tree/findLeavesOfBinaryTree.py | ay701/Coding_Challenges | train | 1 | |
35d7968871449a894c7cb9f762d230d7daff2f86 | [
"max_profit = 0\n_len = len(prices)\nfor i in range(_len):\n for j in range(i + 1, _len):\n max_profit = max(prices[j] - prices[i], max_profit)\nreturn max_profit",
"profit = 0\nmin_price = float('inf')\nfor price in prices:\n min_price = min(price, min_price)\n profit = max(profit, price - min_pr... | <|body_start_0|>
max_profit = 0
_len = len(prices)
for i in range(_len):
for j in range(i + 1, _len):
max_profit = max(prices[j] - prices[i], max_profit)
return max_profit
<|end_body_0|>
<|body_start_1|>
profit = 0
min_price = float('inf')
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit2(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
max_profit = 0
_len = len(price... | stack_v2_sparse_classes_75kplus_train_000085 | 696 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit1",
"signature": "def maxProfit1(self, prices)"
},
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit2",
"signature": "def maxProfit2(self, prices)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit1(self, prices): :type prices: List[int] :rtype: int
- def maxProfit2(self, prices): :type prices: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit1(self, prices): :type prices: List[int] :rtype: int
- def maxProfit2(self, prices): :type prices: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxPr... | c338b66db9f8f09db9115e7ffe75925c455b17b8 | <|skeleton|>
class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit2(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
max_profit = 0
_len = len(prices)
for i in range(_len):
for j in range(i + 1, _len):
max_profit = max(prices[j] - prices[i], max_profit)
return max_profit
... | the_stack_v2_python_sparse | Array/Best Time to Buy and Sell Stock.py | mikolaje/leetcode_practice | train | 0 | |
22137a9f593b615b474b0755edcb3e7c4786999d | [
"self.device = device\nself.ip = ip\nself.netapp_user = user\nself.netapp_password = password\nself.path_prefix = prefix\nself.publish_metric = pm\nself._netapp_login()\nfilers_xml = self.get_netapp_data()\nfor volume in filers_xml:\n max_inodes = volume.find('files-total').text\n used_inodes = volume.find('f... | <|body_start_0|>
self.device = device
self.ip = ip
self.netapp_user = user
self.netapp_password = password
self.path_prefix = prefix
self.publish_metric = pm
self._netapp_login()
filers_xml = self.get_netapp_data()
for volume in filers_xml:
... | Our netapp_inode Collector | netapp_inodeCol | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class netapp_inodeCol:
"""Our netapp_inode Collector"""
def __init__(self, device, ip, user, password, prefix, pm):
"""Instantiate _our_ stuff"""
<|body_0|>
def push(self, metric_name=None, metric_value=None, volume=None):
"""Ship that shit off to graphite broski"""
... | stack_v2_sparse_classes_75kplus_train_000086 | 3,492 | permissive | [
{
"docstring": "Instantiate _our_ stuff",
"name": "__init__",
"signature": "def __init__(self, device, ip, user, password, prefix, pm)"
},
{
"docstring": "Ship that shit off to graphite broski",
"name": "push",
"signature": "def push(self, metric_name=None, metric_value=None, volume=None... | 4 | stack_v2_sparse_classes_30k_train_000283 | Implement the Python class `netapp_inodeCol` described below.
Class description:
Our netapp_inode Collector
Method signatures and docstrings:
- def __init__(self, device, ip, user, password, prefix, pm): Instantiate _our_ stuff
- def push(self, metric_name=None, metric_value=None, volume=None): Ship that shit off to ... | Implement the Python class `netapp_inodeCol` described below.
Class description:
Our netapp_inode Collector
Method signatures and docstrings:
- def __init__(self, device, ip, user, password, prefix, pm): Instantiate _our_ stuff
- def push(self, metric_name=None, metric_value=None, volume=None): Ship that shit off to ... | 461caf29e84db8cbf46f9fc4c895f56353e10c61 | <|skeleton|>
class netapp_inodeCol:
"""Our netapp_inode Collector"""
def __init__(self, device, ip, user, password, prefix, pm):
"""Instantiate _our_ stuff"""
<|body_0|>
def push(self, metric_name=None, metric_value=None, volume=None):
"""Ship that shit off to graphite broski"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class netapp_inodeCol:
"""Our netapp_inode Collector"""
def __init__(self, device, ip, user, password, prefix, pm):
"""Instantiate _our_ stuff"""
self.device = device
self.ip = ip
self.netapp_user = user
self.netapp_password = password
self.path_prefix = prefix
... | the_stack_v2_python_sparse | src/collectors/netapp/netapp_inode.py | python-diamond/Diamond | train | 1,874 |
81d22e75721c89511ef8dc2afedcabb678d6a98b | [
"EasyFrame.__init__(self, title='Square Rooting Numbers')\nself.addLabel(text='An integer', row=0, column=0)\nself.inputField = self.addIntegerField(value=0, row=0, column=1, width=10)\nself.addLabel(text='Square root', row=1, column=0)\nself.outputField = self.addFloatField(value=0.0, row=1, column=1, width=8, pre... | <|body_start_0|>
EasyFrame.__init__(self, title='Square Rooting Numbers')
self.addLabel(text='An integer', row=0, column=0)
self.inputField = self.addIntegerField(value=0, row=0, column=1, width=10)
self.addLabel(text='Square root', row=1, column=0)
self.outputField = self.addFlo... | Computes and displays the square root of an input number. | NumberFieldApplication | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumberFieldApplication:
"""Computes and displays the square root of an input number."""
def __init__(self):
"""Sets up the window and widgets."""
<|body_0|>
def compute_square_root(self):
"""Inputs the integer, computes the square root, and outputs the result. Ne... | stack_v2_sparse_classes_75kplus_train_000087 | 2,402 | no_license | [
{
"docstring": "Sets up the window and widgets.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Inputs the integer, computes the square root, and outputs the result. Negative and non integer numbers will have an error message displayed.",
"name": "compute_square_ro... | 2 | stack_v2_sparse_classes_30k_train_051019 | Implement the Python class `NumberFieldApplication` described below.
Class description:
Computes and displays the square root of an input number.
Method signatures and docstrings:
- def __init__(self): Sets up the window and widgets.
- def compute_square_root(self): Inputs the integer, computes the square root, and o... | Implement the Python class `NumberFieldApplication` described below.
Class description:
Computes and displays the square root of an input number.
Method signatures and docstrings:
- def __init__(self): Sets up the window and widgets.
- def compute_square_root(self): Inputs the integer, computes the square root, and o... | 86f50c0094dbbf43ad033b1153e57ad5c258700e | <|skeleton|>
class NumberFieldApplication:
"""Computes and displays the square root of an input number."""
def __init__(self):
"""Sets up the window and widgets."""
<|body_0|>
def compute_square_root(self):
"""Inputs the integer, computes the square root, and outputs the result. Ne... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumberFieldApplication:
"""Computes and displays the square root of an input number."""
def __init__(self):
"""Sets up the window and widgets."""
EasyFrame.__init__(self, title='Square Rooting Numbers')
self.addLabel(text='An integer', row=0, column=0)
self.inputField = se... | the_stack_v2_python_sparse | Week-13-1/gui-8.py | AdyGCode/Python-Basics-2021S1 | train | 0 |
5290ff69768a9011af417546c3e2ee3cc0917e8e | [
"self.error_status = 0\nself.username = None\nself.password = None\nself.client = None",
"test_status = False\nif self.error_status == 0 and self.username is not None:\n try:\n mail_server = smtplib.SMTP(self.client)\n mail_server.starttls()\n mail_server.login(self.username, self.password... | <|body_start_0|>
self.error_status = 0
self.username = None
self.password = None
self.client = None
<|end_body_0|>
<|body_start_1|>
test_status = False
if self.error_status == 0 and self.username is not None:
try:
mail_server = smtplib.SMTP(se... | Objects to send messages through a gmail account | MailSender | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailSender:
"""Objects to send messages through a gmail account"""
def __init__(self):
"""Creates an empty MailSender instance"""
<|body_0|>
def test_credentials(self):
"""Tests validity of credentials loaded in system by trying to log-in to gmail. OUTPUT (bool) ... | stack_v2_sparse_classes_75kplus_train_000088 | 9,487 | no_license | [
{
"docstring": "Creates an empty MailSender instance",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Tests validity of credentials loaded in system by trying to log-in to gmail. OUTPUT (bool) Whether or not credentials managed to be used to log into account",
"name... | 4 | stack_v2_sparse_classes_30k_train_015267 | Implement the Python class `MailSender` described below.
Class description:
Objects to send messages through a gmail account
Method signatures and docstrings:
- def __init__(self): Creates an empty MailSender instance
- def test_credentials(self): Tests validity of credentials loaded in system by trying to log-in to ... | Implement the Python class `MailSender` described below.
Class description:
Objects to send messages through a gmail account
Method signatures and docstrings:
- def __init__(self): Creates an empty MailSender instance
- def test_credentials(self): Tests validity of credentials loaded in system by trying to log-in to ... | 550a82b74a4422b5952c8618262755f9822f7c22 | <|skeleton|>
class MailSender:
"""Objects to send messages through a gmail account"""
def __init__(self):
"""Creates an empty MailSender instance"""
<|body_0|>
def test_credentials(self):
"""Tests validity of credentials loaded in system by trying to log-in to gmail. OUTPUT (bool) ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MailSender:
"""Objects to send messages through a gmail account"""
def __init__(self):
"""Creates an empty MailSender instance"""
self.error_status = 0
self.username = None
self.password = None
self.client = None
def test_credentials(self):
"""Tests va... | the_stack_v2_python_sparse | python/global_libraries/mail_sender.py | bopopescu/Home_Code | train | 0 |
a5f18d9776b4d2f5ad4db84ef0f98200d8305024 | [
"ulist = struct.unpack(pktt.header_rec, data)\nself.frame = pktt.frame\nself.index = pktt.index\nself.seconds = ulist[0]\nself.usecs = ulist[1]\nself.length_inc = ulist[2]\nself.length_orig = ulist[3]\npktt.pkt.record = self\nself.secs = float(self.seconds) + float(self.usecs) / 1000000.0\nif pktt.tstart is None:\n... | <|body_start_0|>
ulist = struct.unpack(pktt.header_rec, data)
self.frame = pktt.frame
self.index = pktt.index
self.seconds = ulist[0]
self.usecs = ulist[1]
self.length_inc = ulist[2]
self.length_orig = ulist[3]
pktt.pkt.record = self
self.secs = fl... | Record object Usage: from packet.record import Record x = Record(pktt, data) Object definition: Record( frame = int, # Frame number index = int, # Packet number seconds = int, # Seconds usecs = int, # Microseconds length_inc = int, # Number of bytes included in trace length_orig = int, # Number of bytes in packet secs ... | Record | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Record:
"""Record object Usage: from packet.record import Record x = Record(pktt, data) Object definition: Record( frame = int, # Frame number index = int, # Packet number seconds = int, # Seconds usecs = int, # Microseconds length_inc = int, # Number of bytes included in trace length_orig = int,... | stack_v2_sparse_classes_75kplus_train_000089 | 4,513 | no_license | [
{
"docstring": "Constructor Initialize object's private data. pktt: Packet trace object (packet.pktt.Pktt) so this layer has access to the parent layers. data: Raw packet data for this layer.",
"name": "__init__",
"signature": "def __init__(self, pktt, data)"
},
{
"docstring": "String representa... | 2 | stack_v2_sparse_classes_30k_train_049233 | Implement the Python class `Record` described below.
Class description:
Record object Usage: from packet.record import Record x = Record(pktt, data) Object definition: Record( frame = int, # Frame number index = int, # Packet number seconds = int, # Seconds usecs = int, # Microseconds length_inc = int, # Number of byt... | Implement the Python class `Record` described below.
Class description:
Record object Usage: from packet.record import Record x = Record(pktt, data) Object definition: Record( frame = int, # Frame number index = int, # Packet number seconds = int, # Seconds usecs = int, # Microseconds length_inc = int, # Number of byt... | 1f06ae8c73d253141a3434fb9d2c36be3fe768ea | <|skeleton|>
class Record:
"""Record object Usage: from packet.record import Record x = Record(pktt, data) Object definition: Record( frame = int, # Frame number index = int, # Packet number seconds = int, # Seconds usecs = int, # Microseconds length_inc = int, # Number of bytes included in trace length_orig = int,... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Record:
"""Record object Usage: from packet.record import Record x = Record(pktt, data) Object definition: Record( frame = int, # Frame number index = int, # Packet number seconds = int, # Seconds usecs = int, # Microseconds length_inc = int, # Number of bytes included in trace length_orig = int, # Number of ... | the_stack_v2_python_sparse | packet/record.py | MihailRusetskiy/nfs | train | 0 |
66239f52d2d85e8c8ea54fc1a2230bb85642f22c | [
"try:\n return cls.byName(campaignName)\nexcept SQLObjectNotFound:\n return cls(name=campaignName, searchQuery=query)",
"try:\n return cls.byName(campaignName)\nexcept SQLObjectNotFound as e:\n raise type(e)('Use the campaign manager to create the Campaign as name and search query. Name not found: {!r... | <|body_start_0|>
try:
return cls.byName(campaignName)
except SQLObjectNotFound:
return cls(name=campaignName, searchQuery=query)
<|end_body_0|>
<|body_start_1|>
try:
return cls.byName(campaignName)
except SQLObjectNotFound as e:
raise type... | Model a Campaign, which can be assigned to a Tweet as a label. Used to group Tweets which are added to the DB because they matched the same campaign, such as a search topic. See docs/models.md document. | Campaign | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Campaign:
"""Model a Campaign, which can be assigned to a Tweet as a label. Used to group Tweets which are added to the DB because they matched the same campaign, such as a search topic. See docs/models.md document."""
def getOrCreate(cls, campaignName, query=None):
"""Get a campaign... | stack_v2_sparse_classes_75kplus_train_000090 | 15,734 | permissive | [
{
"docstring": "Get a campaign otherwise create and return one. Query may be empty as in some cases like a utility's campaign label the campaign is a label for grouping rather than searching.",
"name": "getOrCreate",
"signature": "def getOrCreate(cls, campaignName, query=None)"
},
{
"docstring":... | 2 | null | Implement the Python class `Campaign` described below.
Class description:
Model a Campaign, which can be assigned to a Tweet as a label. Used to group Tweets which are added to the DB because they matched the same campaign, such as a search topic. See docs/models.md document.
Method signatures and docstrings:
- def g... | Implement the Python class `Campaign` described below.
Class description:
Model a Campaign, which can be assigned to a Tweet as a label. Used to group Tweets which are added to the DB because they matched the same campaign, such as a search topic. See docs/models.md document.
Method signatures and docstrings:
- def g... | e7c36efcd16dcd8141a5e198af53ab1a41010610 | <|skeleton|>
class Campaign:
"""Model a Campaign, which can be assigned to a Tweet as a label. Used to group Tweets which are added to the DB because they matched the same campaign, such as a search topic. See docs/models.md document."""
def getOrCreate(cls, campaignName, query=None):
"""Get a campaign... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Campaign:
"""Model a Campaign, which can be assigned to a Tweet as a label. Used to group Tweets which are added to the DB because they matched the same campaign, such as a search topic. See docs/models.md document."""
def getOrCreate(cls, campaignName, query=None):
"""Get a campaign otherwise cr... | the_stack_v2_python_sparse | app/models/tweets.py | MichaelCurrin/twitterverse | train | 12 |
daf79bd8d7e9f93793bd267bb36d7d790eeca8a6 | [
"def helper(remain, combi, idx):\n if remain < 0:\n return\n if remain == 0:\n res.append(combi)\n return\n if idx >= len(candidates):\n return\n helper(remain, combi, idx + 1)\n helper(remain - candidates[idx], combi + [candidates[idx]], idx)\nres = []\nhelper(target, [],... | <|body_start_0|>
def helper(remain, combi, idx):
if remain < 0:
return
if remain == 0:
res.append(combi)
return
if idx >= len(candidates):
return
helper(remain, combi, idx + 1)
helper(rema... | Solution_ | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_:
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def combinationSum_hash(self, candidates, target):
""":type candidates: List[int] :type target: int :rtype: List[List[int]]... | stack_v2_sparse_classes_75kplus_train_000091 | 3,701 | no_license | [
{
"docstring": ":type candidates: List[int] :type target: int :rtype: List[List[int]]",
"name": "combinationSum",
"signature": "def combinationSum(self, candidates, target)"
},
{
"docstring": ":type candidates: List[int] :type target: int :rtype: List[List[int]]",
"name": "combinationSum_has... | 2 | stack_v2_sparse_classes_30k_train_041784 | Implement the Python class `Solution_` described below.
Class description:
Implement the Solution_ class.
Method signatures and docstrings:
- def combinationSum(self, candidates, target): :type candidates: List[int] :type target: int :rtype: List[List[int]]
- def combinationSum_hash(self, candidates, target): :type c... | Implement the Python class `Solution_` described below.
Class description:
Implement the Solution_ class.
Method signatures and docstrings:
- def combinationSum(self, candidates, target): :type candidates: List[int] :type target: int :rtype: List[List[int]]
- def combinationSum_hash(self, candidates, target): :type c... | fab4c341486e872fb2926d1b6d50499d55e76a4a | <|skeleton|>
class Solution_:
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def combinationSum_hash(self, candidates, target):
""":type candidates: List[int] :type target: int :rtype: List[List[int]]... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution_:
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: int :rtype: List[List[int]]"""
def helper(remain, combi, idx):
if remain < 0:
return
if remain == 0:
res.append(combi)
r... | the_stack_v2_python_sparse | leetcode/39. Combination Sum.py | lunar-r/sword-to-offer-python | train | 0 | |
23345a776cf8013a11a56718ea6e5a526e25653e | [
"dp = [[False] * (len(pattern) + 1) for _ in range(len(text) + 1)]\ndp[-1][-1] = True\nfor i in range(len(text), -1, -1):\n for j in range(len(pattern) - 1, -1, -1):\n first_match = i < len(text) and pattern[j] in {text[i], '.'}\n if j + 1 < len(pattern) and pattern[j + 1] == '*':\n dp[i... | <|body_start_0|>
dp = [[False] * (len(pattern) + 1) for _ in range(len(text) + 1)]
dp[-1][-1] = True
for i in range(len(text), -1, -1):
for j in range(len(pattern) - 1, -1, -1):
first_match = i < len(text) and pattern[j] in {text[i], '.'}
if j + 1 < le... | PatternMatching | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PatternMatching:
def is_match(self, text: str, pattern: str) -> bool:
"""Approach: Dynamic Programming Bottom-Up Time Complexity: O(TP) Space Complexity: O(TP) :param text: :param pattern: :return:"""
<|body_0|>
def is_match_(self, text: str, pattern: str) -> bool:
"... | stack_v2_sparse_classes_75kplus_train_000092 | 1,884 | no_license | [
{
"docstring": "Approach: Dynamic Programming Bottom-Up Time Complexity: O(TP) Space Complexity: O(TP) :param text: :param pattern: :return:",
"name": "is_match",
"signature": "def is_match(self, text: str, pattern: str) -> bool"
},
{
"docstring": "Approach: Recursion :param text: :param pattern... | 2 | stack_v2_sparse_classes_30k_train_021163 | Implement the Python class `PatternMatching` described below.
Class description:
Implement the PatternMatching class.
Method signatures and docstrings:
- def is_match(self, text: str, pattern: str) -> bool: Approach: Dynamic Programming Bottom-Up Time Complexity: O(TP) Space Complexity: O(TP) :param text: :param patt... | Implement the Python class `PatternMatching` described below.
Class description:
Implement the PatternMatching class.
Method signatures and docstrings:
- def is_match(self, text: str, pattern: str) -> bool: Approach: Dynamic Programming Bottom-Up Time Complexity: O(TP) Space Complexity: O(TP) :param text: :param patt... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class PatternMatching:
def is_match(self, text: str, pattern: str) -> bool:
"""Approach: Dynamic Programming Bottom-Up Time Complexity: O(TP) Space Complexity: O(TP) :param text: :param pattern: :return:"""
<|body_0|>
def is_match_(self, text: str, pattern: str) -> bool:
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PatternMatching:
def is_match(self, text: str, pattern: str) -> bool:
"""Approach: Dynamic Programming Bottom-Up Time Complexity: O(TP) Space Complexity: O(TP) :param text: :param pattern: :return:"""
dp = [[False] * (len(pattern) + 1) for _ in range(len(text) + 1)]
dp[-1][-1] = True
... | the_stack_v2_python_sparse | math_and_srings/regular_expression_matching.py | Shiv2157k/leet_code | train | 1 | |
5b35020d867bf112d6fca90d753216f8bbb72769 | [
"super().__init__(trainloader, valloader, model, num_classes, linear_layer, loss, device, logger)\nself.eta = eta\nself.device = device\nself.init_out = list()\nself.init_l1 = list()\nself.selection_type = selection_type\nself.valid = valid\nself.ss_indices = ss_indices",
"omp_start_time = time.time()\nself.updat... | <|body_start_0|>
super().__init__(trainloader, valloader, model, num_classes, linear_layer, loss, device, logger)
self.eta = eta
self.device = device
self.init_out = list()
self.init_l1 = list()
self.selection_type = selection_type
self.valid = valid
self.... | Implementation of GradMatch Strategy from the paper :footcite:`sivasubramanian2020gradmatch` for supervised learning frameworks. GradMatch strategy tries to solve the optimization problem given below: .. math:: \\min_{\\mathbf{w}, S: |S| \\leq k} \\Vert \\sum_{i \\in S} w_i \\nabla_{\\theta}L_T^i(\\theta) - \\nabla_{\\... | AdapWeightsStrategy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdapWeightsStrategy:
"""Implementation of GradMatch Strategy from the paper :footcite:`sivasubramanian2020gradmatch` for supervised learning frameworks. GradMatch strategy tries to solve the optimization problem given below: .. math:: \\min_{\\mathbf{w}, S: |S| \\leq k} \\Vert \\sum_{i \\in S} w_... | stack_v2_sparse_classes_75kplus_train_000093 | 5,115 | permissive | [
{
"docstring": "Constructor method",
"name": "__init__",
"signature": "def __init__(self, trainloader, valloader, model, loss, eta, device, num_classes, linear_layer, selection_type, logger, ss_indices, valid=False)"
},
{
"docstring": "Apply OMP Algorithm for data selection Parameters ----------... | 2 | stack_v2_sparse_classes_30k_train_044649 | Implement the Python class `AdapWeightsStrategy` described below.
Class description:
Implementation of GradMatch Strategy from the paper :footcite:`sivasubramanian2020gradmatch` for supervised learning frameworks. GradMatch strategy tries to solve the optimization problem given below: .. math:: \\min_{\\mathbf{w}, S: ... | Implement the Python class `AdapWeightsStrategy` described below.
Class description:
Implementation of GradMatch Strategy from the paper :footcite:`sivasubramanian2020gradmatch` for supervised learning frameworks. GradMatch strategy tries to solve the optimization problem given below: .. math:: \\min_{\\mathbf{w}, S: ... | 8d10c7f5d96e071f98c20e4e9ff4c41c2c4ea2af | <|skeleton|>
class AdapWeightsStrategy:
"""Implementation of GradMatch Strategy from the paper :footcite:`sivasubramanian2020gradmatch` for supervised learning frameworks. GradMatch strategy tries to solve the optimization problem given below: .. math:: \\min_{\\mathbf{w}, S: |S| \\leq k} \\Vert \\sum_{i \\in S} w_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdapWeightsStrategy:
"""Implementation of GradMatch Strategy from the paper :footcite:`sivasubramanian2020gradmatch` for supervised learning frameworks. GradMatch strategy tries to solve the optimization problem given below: .. math:: \\min_{\\mathbf{w}, S: |S| \\leq k} \\Vert \\sum_{i \\in S} w_i \\nabla_{\\... | the_stack_v2_python_sparse | cords/selectionstrategies/SL/adapweightsstrategy.py | decile-team/cords | train | 289 |
e3224eec60d4161ee553dc6a6a8d5e4399bd5740 | [
"testfile = ('lib/l10n_utils/tests/test_files/templates/even_more_lang_files.html',)\nwith capture_stdio() as out:\n extracted = next(extract_from_files(testfile, method_map=METHODS))\nself.assertTupleEqual(extracted, (testfile[0], 9, 'Mark it 8 Dude.', []))\nself.assertEqual(out[0], ' %s' % testfile)",
"base... | <|body_start_0|>
testfile = ('lib/l10n_utils/tests/test_files/templates/even_more_lang_files.html',)
with capture_stdio() as out:
extracted = next(extract_from_files(testfile, method_map=METHODS))
self.assertTupleEqual(extracted, (testfile[0], 9, 'Mark it 8 Dude.', []))
self.... | TestL10nExtract | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestL10nExtract:
def test_extract_from_files(self):
"""Should be able to extract strings from a specific file."""
<|body_0|>
def test_extract_from_multiple_files(self):
"""Should be able to extract strings from specific files."""
<|body_1|>
def test_extr... | stack_v2_sparse_classes_75kplus_train_000094 | 14,956 | no_license | [
{
"docstring": "Should be able to extract strings from a specific file.",
"name": "test_extract_from_files",
"signature": "def test_extract_from_files(self)"
},
{
"docstring": "Should be able to extract strings from specific files.",
"name": "test_extract_from_multiple_files",
"signature... | 6 | stack_v2_sparse_classes_30k_train_020817 | Implement the Python class `TestL10nExtract` described below.
Class description:
Implement the TestL10nExtract class.
Method signatures and docstrings:
- def test_extract_from_files(self): Should be able to extract strings from a specific file.
- def test_extract_from_multiple_files(self): Should be able to extract s... | Implement the Python class `TestL10nExtract` described below.
Class description:
Implement the TestL10nExtract class.
Method signatures and docstrings:
- def test_extract_from_files(self): Should be able to extract strings from a specific file.
- def test_extract_from_multiple_files(self): Should be able to extract s... | 5fa3a818c3d41bd9c3eb25122e1d376c8910269c | <|skeleton|>
class TestL10nExtract:
def test_extract_from_files(self):
"""Should be able to extract strings from a specific file."""
<|body_0|>
def test_extract_from_multiple_files(self):
"""Should be able to extract strings from specific files."""
<|body_1|>
def test_extr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestL10nExtract:
def test_extract_from_files(self):
"""Should be able to extract strings from a specific file."""
testfile = ('lib/l10n_utils/tests/test_files/templates/even_more_lang_files.html',)
with capture_stdio() as out:
extracted = next(extract_from_files(testfile, m... | the_stack_v2_python_sparse | ExtractFeatures/Data/thesantosh/test_commands.py | vivekaxl/LexisNexis | train | 9 | |
d443527bada8adc6a4169dab68e87850448217a0 | [
"super(RMSModel, self).__init__()\nself.el = np.array(model_spec.keys())\nself.rms = np.array(model_spec.values())\nself.alpha, self.beta = fit_power_law(self.el, self.rms)",
"if el < 0:\n raise RuntimeError('el = {} < 0'.format(el))\nelif el > 90:\n raise RuntimeError('el = {} > 90'.format(el))\nif 0 <= el... | <|body_start_0|>
super(RMSModel, self).__init__()
self.el = np.array(model_spec.keys())
self.rms = np.array(model_spec.values())
self.alpha, self.beta = fit_power_law(self.el, self.rms)
<|end_body_0|>
<|body_start_1|>
if el < 0:
raise RuntimeError('el = {} < 0'.forma... | RMSModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RMSModel:
def __init__(self, model_spec=SNR_8):
"""???"""
<|body_0|>
def __call__(self, el):
"""??? note that el is in [deg]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(RMSModel, self).__init__()
self.el = np.array(model_spec.keys(... | stack_v2_sparse_classes_75kplus_train_000095 | 2,471 | permissive | [
{
"docstring": "???",
"name": "__init__",
"signature": "def __init__(self, model_spec=SNR_8)"
},
{
"docstring": "??? note that el is in [deg]",
"name": "__call__",
"signature": "def __call__(self, el)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020227 | Implement the Python class `RMSModel` described below.
Class description:
Implement the RMSModel class.
Method signatures and docstrings:
- def __init__(self, model_spec=SNR_8): ???
- def __call__(self, el): ??? note that el is in [deg] | Implement the Python class `RMSModel` described below.
Class description:
Implement the RMSModel class.
Method signatures and docstrings:
- def __init__(self, model_spec=SNR_8): ???
- def __call__(self, el): ??? note that el is in [deg]
<|skeleton|>
class RMSModel:
def __init__(self, model_spec=SNR_8):
... | e364be68cb0cadbeea10ca569963b8f99aa7b05b | <|skeleton|>
class RMSModel:
def __init__(self, model_spec=SNR_8):
"""???"""
<|body_0|>
def __call__(self, el):
"""??? note that el is in [deg]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RMSModel:
def __init__(self, model_spec=SNR_8):
"""???"""
super(RMSModel, self).__init__()
self.el = np.array(model_spec.keys())
self.rms = np.array(model_spec.values())
self.alpha, self.beta = fit_power_law(self.el, self.rms)
def __call__(self, el):
"""???... | the_stack_v2_python_sparse | pyrsss/gnss/rms_model.py | butala/pyrsss | train | 7 | |
77825902e31b4bfc1f4ac1898d638db067123821 | [
"c = ircdb.channels.getChannel(channel)\nc.addIgnore(banmask, expires)\nircdb.channels.setChannel(channel, c)\nirc.replySuccess()",
"c = ircdb.channels.getChannel(channel)\ntry:\n c.removeIgnore(banmask)\n ircdb.channels.setChannel(channel, c)\n irc.replySuccess()\nexcept KeyError:\n irc.error('There ... | <|body_start_0|>
c = ircdb.channels.getChannel(channel)
c.addIgnore(banmask, expires)
ircdb.channels.setChannel(channel, c)
irc.replySuccess()
<|end_body_0|>
<|body_start_1|>
c = ircdb.channels.getChannel(channel)
try:
c.removeIgnore(banmask)
ircd... | ignore | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ignore:
def add(self, irc, msg, args, channel, banmask, expires):
"""[<channel>] <nick|hostmask> [<expires>] If you have the #channel,op capability, this will set a persistent ignore on <hostmask> or the hostmask currently associated with <nick>. <expires> is an optional argument specify... | stack_v2_sparse_classes_75kplus_train_000096 | 35,475 | permissive | [
{
"docstring": "[<channel>] <nick|hostmask> [<expires>] If you have the #channel,op capability, this will set a persistent ignore on <hostmask> or the hostmask currently associated with <nick>. <expires> is an optional argument specifying when (in \"seconds from now\") the ignore will expire; if it isn't given,... | 3 | stack_v2_sparse_classes_30k_train_029846 | Implement the Python class `ignore` described below.
Class description:
Implement the ignore class.
Method signatures and docstrings:
- def add(self, irc, msg, args, channel, banmask, expires): [<channel>] <nick|hostmask> [<expires>] If you have the #channel,op capability, this will set a persistent ignore on <hostma... | Implement the Python class `ignore` described below.
Class description:
Implement the ignore class.
Method signatures and docstrings:
- def add(self, irc, msg, args, channel, banmask, expires): [<channel>] <nick|hostmask> [<expires>] If you have the #channel,op capability, this will set a persistent ignore on <hostma... | 656f42f8d6b3fe4544a5270e0dab816fd3603118 | <|skeleton|>
class ignore:
def add(self, irc, msg, args, channel, banmask, expires):
"""[<channel>] <nick|hostmask> [<expires>] If you have the #channel,op capability, this will set a persistent ignore on <hostmask> or the hostmask currently associated with <nick>. <expires> is an optional argument specify... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ignore:
def add(self, irc, msg, args, channel, banmask, expires):
"""[<channel>] <nick|hostmask> [<expires>] If you have the #channel,op capability, this will set a persistent ignore on <hostmask> or the hostmask currently associated with <nick>. <expires> is an optional argument specifying when (in "... | the_stack_v2_python_sparse | plugins/Channel/plugin.py | kblin/supybot-gsoc | train | 2 | |
fd870f007d03036bafb3d1d54f73e97f37d00fa2 | [
"if obj is None:\n return super(UseCaseAdminInLine, self).has_delete_permission(request, obj=None)\nelif (request.user == obj.created_by or request.user.has_perm('muo.can_edit_all')) and obj.status in ('draft', 'rejected'):\n return super(UseCaseAdminInLine, self).has_delete_permission(request, obj=None)\nels... | <|body_start_0|>
if obj is None:
return super(UseCaseAdminInLine, self).has_delete_permission(request, obj=None)
elif (request.user == obj.created_by or request.user.has_perm('muo.can_edit_all')) and obj.status in ('draft', 'rejected'):
return super(UseCaseAdminInLine, self).has_... | UseCaseAdminInLine | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UseCaseAdminInLine:
def has_delete_permission(self, request, obj=None):
"""Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The delete option ... | stack_v2_sparse_classes_75kplus_train_000097 | 18,243 | no_license | [
{
"docstring": "Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The delete option is only available to the original author or users with 'can_edit_all' permission if... | 3 | stack_v2_sparse_classes_30k_train_048086 | Implement the Python class `UseCaseAdminInLine` described below.
Class description:
Implement the UseCaseAdminInLine class.
Method signatures and docstrings:
- def has_delete_permission(self, request, obj=None): Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not ava... | Implement the Python class `UseCaseAdminInLine` described below.
Class description:
Implement the UseCaseAdminInLine class.
Method signatures and docstrings:
- def has_delete_permission(self, request, obj=None): Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not ava... | d9b330ef70b0d0985bfc8248612ba57ee46ff0f4 | <|skeleton|>
class UseCaseAdminInLine:
def has_delete_permission(self, request, obj=None):
"""Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The delete option ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UseCaseAdminInLine:
def has_delete_permission(self, request, obj=None):
"""Overriding the method such that the delete option on the UseCaseAdminInline form on change form is not available for the users except the original author or users with 'can_edit_all' permission. The delete option is only availa... | the_stack_v2_python_sparse | Code/EnhanceCWE-master/muo/admin.py | happinesstaker/more-website | train | 0 | |
da7e6db8d5b7bf251bd415e236ec1f155f4215c9 | [
"if not email:\n raise ValueError('The given email must be set')\nemail = normalize_email(email)\nuser = self.model(email=email, **extra_fields)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"extra_fields.setdefault('is_staff', False)\nextra_fields.setdefault('is_superuser', False)\nre... | <|body_start_0|>
if not email:
raise ValueError('The given email must be set')
email = normalize_email(email)
user = self.model(email=email, **extra_fields)
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
... | Define a model manager for User model with no username field. | CustomUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomUserManager:
"""Define a model manager for User model with no username field."""
def _create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
<|body_0|>
def create_user(self, email, password=None, **extra_... | stack_v2_sparse_classes_75kplus_train_000098 | 3,359 | no_license | [
{
"docstring": "Create and save a User with the given email and password.",
"name": "_create_user",
"signature": "def _create_user(self, email, password, **extra_fields)"
},
{
"docstring": "Create and save a regular User with the given email and password.",
"name": "create_user",
"signat... | 3 | stack_v2_sparse_classes_30k_train_038287 | Implement the Python class `CustomUserManager` described below.
Class description:
Define a model manager for User model with no username field.
Method signatures and docstrings:
- def _create_user(self, email, password, **extra_fields): Create and save a User with the given email and password.
- def create_user(self... | Implement the Python class `CustomUserManager` described below.
Class description:
Define a model manager for User model with no username field.
Method signatures and docstrings:
- def _create_user(self, email, password, **extra_fields): Create and save a User with the given email and password.
- def create_user(self... | 97c29690929693b172ab88a52c3b426b17461011 | <|skeleton|>
class CustomUserManager:
"""Define a model manager for User model with no username field."""
def _create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
<|body_0|>
def create_user(self, email, password=None, **extra_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomUserManager:
"""Define a model manager for User model with no username field."""
def _create_user(self, email, password, **extra_fields):
"""Create and save a User with the given email and password."""
if not email:
raise ValueError('The given email must be set')
... | the_stack_v2_python_sparse | stationery/apps/accounts/models.py | minidron/stationery | train | 0 |
0ac6044b2c4c86291768f2c820e5037f47242f2f | [
"if inputFile.sample != None:\n outDir = inputFile.sample.outputDir\nelse:\n outDir = inputFile.pool.outputDir\nif inputFile.fileName.endswith('.tar.gz'):\n return self._extractTarGz(inputFile, outDir)\nelif inputFile.fileName.endswith('.gz'):\n return self._extractGz(inputFile, outDir)\nelse:\n rais... | <|body_start_0|>
if inputFile.sample != None:
outDir = inputFile.sample.outputDir
else:
outDir = inputFile.pool.outputDir
if inputFile.fileName.endswith('.tar.gz'):
return self._extractTarGz(inputFile, outDir)
elif inputFile.fileName.endswith('.gz'):
... | The Decompressor class regulates all Decompress functions .. module:: programs .. moduleauthor:: Jetse Jacobi | Decompressor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decompressor:
"""The Decompressor class regulates all Decompress functions .. module:: programs .. moduleauthor:: Jetse Jacobi"""
def extract(self, inputFile):
"""This function calls extractGz if the file .gz compressed, if this file is .tar.gz compressed, the method extractTarGz is ... | stack_v2_sparse_classes_75kplus_train_000099 | 2,548 | no_license | [
{
"docstring": "This function calls extractGz if the file .gz compressed, if this file is .tar.gz compressed, the method extractTarGz is called :param inputFile: The compressed .gz or . tar.gz file which has to be extracted :type inputFile: instance of a child object of the :py:class:`File.File` object :returns... | 3 | stack_v2_sparse_classes_30k_train_047506 | Implement the Python class `Decompressor` described below.
Class description:
The Decompressor class regulates all Decompress functions .. module:: programs .. moduleauthor:: Jetse Jacobi
Method signatures and docstrings:
- def extract(self, inputFile): This function calls extractGz if the file .gz compressed, if thi... | Implement the Python class `Decompressor` described below.
Class description:
The Decompressor class regulates all Decompress functions .. module:: programs .. moduleauthor:: Jetse Jacobi
Method signatures and docstrings:
- def extract(self, inputFile): This function calls extractGz if the file .gz compressed, if thi... | 53315eca821785aa02218e903b60921ecf18246b | <|skeleton|>
class Decompressor:
"""The Decompressor class regulates all Decompress functions .. module:: programs .. moduleauthor:: Jetse Jacobi"""
def extract(self, inputFile):
"""This function calls extractGz if the file .gz compressed, if this file is .tar.gz compressed, the method extractTarGz is ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Decompressor:
"""The Decompressor class regulates all Decompress functions .. module:: programs .. moduleauthor:: Jetse Jacobi"""
def extract(self, inputFile):
"""This function calls extractGz if the file .gz compressed, if this file is .tar.gz compressed, the method extractTarGz is called :param... | the_stack_v2_python_sparse | pythonCodebase/src/programs/Decompressor.py | JJacobi13/VLPB | train | 0 |
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