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4919799fe8d39ff040812edc53f90913a320e728 | [
"if isinstance(layer, (tf.keras.layers.Conv2DTranspose, tf.keras.layers.DepthwiseConv2D)):\n transposed_tensor = tensor.transpose((2, 3, 0, 1))\nelif isinstance(layer, tf.keras.layers.Conv2D):\n transposed_tensor = tensor.transpose((2, 3, 1, 0))\nelse:\n raise ValueError(\"Only Conv2D or it's subclass is c... | <|body_start_0|>
if isinstance(layer, (tf.keras.layers.Conv2DTranspose, tf.keras.layers.DepthwiseConv2D)):
transposed_tensor = tensor.transpose((2, 3, 0, 1))
elif isinstance(layer, tf.keras.layers.Conv2D):
transposed_tensor = tensor.transpose((2, 3, 1, 0))
else:
... | Utility class to handle weight tensor | WeightTensorUtils | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeightTensorUtils:
"""Utility class to handle weight tensor"""
def transpose_from_libpymo_to_tf_format(tensor: np.ndarray, layer: tf.keras.layers.Layer) -> np.ndarray:
"""Transpose the weight tensor shape from libpymo format to TensorFlow format"""
<|body_0|>
def transpo... | stack_v2_sparse_classes_10k_train_006800 | 6,180 | permissive | [
{
"docstring": "Transpose the weight tensor shape from libpymo format to TensorFlow format",
"name": "transpose_from_libpymo_to_tf_format",
"signature": "def transpose_from_libpymo_to_tf_format(tensor: np.ndarray, layer: tf.keras.layers.Layer) -> np.ndarray"
},
{
"docstring": "Transpose the weig... | 4 | stack_v2_sparse_classes_30k_val_000348 | Implement the Python class `WeightTensorUtils` described below.
Class description:
Utility class to handle weight tensor
Method signatures and docstrings:
- def transpose_from_libpymo_to_tf_format(tensor: np.ndarray, layer: tf.keras.layers.Layer) -> np.ndarray: Transpose the weight tensor shape from libpymo format to... | Implement the Python class `WeightTensorUtils` described below.
Class description:
Utility class to handle weight tensor
Method signatures and docstrings:
- def transpose_from_libpymo_to_tf_format(tensor: np.ndarray, layer: tf.keras.layers.Layer) -> np.ndarray: Transpose the weight tensor shape from libpymo format to... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class WeightTensorUtils:
"""Utility class to handle weight tensor"""
def transpose_from_libpymo_to_tf_format(tensor: np.ndarray, layer: tf.keras.layers.Layer) -> np.ndarray:
"""Transpose the weight tensor shape from libpymo format to TensorFlow format"""
<|body_0|>
def transpo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WeightTensorUtils:
"""Utility class to handle weight tensor"""
def transpose_from_libpymo_to_tf_format(tensor: np.ndarray, layer: tf.keras.layers.Layer) -> np.ndarray:
"""Transpose the weight tensor shape from libpymo format to TensorFlow format"""
if isinstance(layer, (tf.keras.layers.Co... | the_stack_v2_python_sparse | TrainingExtensions/tensorflow/src/python/aimet_tensorflow/keras/utils/weight_tensor_utils.py | quic/aimet | train | 1,676 |
2592d9fdce78a4314e2c8cef8c791e4ddee155bc | [
"logger.info('initializing RBF kernel')\nself.d = int(d)\nself.n_rffs = int(n_rffs)\nself.n_features = 2 * n_rffs\nself.dtype = dtype\nself.freq_weights = np.asarray(np.random.normal(size=(self.d, self.n_rffs), loc=0, scale=1.0), dtype=self.dtype)\nself.bf_scale = 1.0 / np.sqrt(self.n_rffs)\nif np.size(log_lengthsc... | <|body_start_0|>
logger.info('initializing RBF kernel')
self.d = int(d)
self.n_rffs = int(n_rffs)
self.n_features = 2 * n_rffs
self.dtype = dtype
self.freq_weights = np.asarray(np.random.normal(size=(self.d, self.n_rffs), loc=0, scale=1.0), dtype=self.dtype)
self.... | random fourier features for an RBF kernel | RBF_RFF | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RBF_RFF:
"""random fourier features for an RBF kernel"""
def __init__(self, d, log_lengthscale=0, n_rffs=1000, dtype=np.float64, tune_len=True):
"""squared exponential kernel Input: d : number of input dims n_rffs : number of random features (will actually used twice this value)"""
... | stack_v2_sparse_classes_10k_train_006801 | 1,789 | no_license | [
{
"docstring": "squared exponential kernel Input: d : number of input dims n_rffs : number of random features (will actually used twice this value)",
"name": "__init__",
"signature": "def __init__(self, d, log_lengthscale=0, n_rffs=1000, dtype=np.float64, tune_len=True)"
},
{
"docstring": "Get t... | 2 | stack_v2_sparse_classes_30k_train_004196 | Implement the Python class `RBF_RFF` described below.
Class description:
random fourier features for an RBF kernel
Method signatures and docstrings:
- def __init__(self, d, log_lengthscale=0, n_rffs=1000, dtype=np.float64, tune_len=True): squared exponential kernel Input: d : number of input dims n_rffs : number of r... | Implement the Python class `RBF_RFF` described below.
Class description:
random fourier features for an RBF kernel
Method signatures and docstrings:
- def __init__(self, d, log_lengthscale=0, n_rffs=1000, dtype=np.float64, tune_len=True): squared exponential kernel Input: d : number of input dims n_rffs : number of r... | 1bed882b8a94ee58fd0bde6920ee85f81ffb77bb | <|skeleton|>
class RBF_RFF:
"""random fourier features for an RBF kernel"""
def __init__(self, d, log_lengthscale=0, n_rffs=1000, dtype=np.float64, tune_len=True):
"""squared exponential kernel Input: d : number of input dims n_rffs : number of random features (will actually used twice this value)"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RBF_RFF:
"""random fourier features for an RBF kernel"""
def __init__(self, d, log_lengthscale=0, n_rffs=1000, dtype=np.float64, tune_len=True):
"""squared exponential kernel Input: d : number of input dims n_rffs : number of random features (will actually used twice this value)"""
logger... | the_stack_v2_python_sparse | gp_grief/kern/rbf_rff.py | scwolof/gp_grief | train | 2 |
592d0bfeb755e797480a1d13cbb17972eeb9b97d | [
"logger.info('Overriding class: JS -> NBJS.')\nsuper(NBJS, self).__init__(params)\nlogger.info('Class overrided.')",
"r1 = r.generate_uniform_random_number()\nmotion = self.gamma * r1\nreturn motion"
] | <|body_start_0|>
logger.info('Overriding class: JS -> NBJS.')
super(NBJS, self).__init__(params)
logger.info('Class overrided.')
<|end_body_0|>
<|body_start_1|>
r1 = r.generate_uniform_random_number()
motion = self.gamma * r1
return motion
<|end_body_1|>
| An NBJS class, inherited from JS. This is the designed class to define NBJS-related variables and methods. References: Publication pending. | NBJS | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NBJS:
"""An NBJS class, inherited from JS. This is the designed class to define NBJS-related variables and methods. References: Publication pending."""
def __init__(self, params: Optional[Dict[str, Any]]=None) -> None:
"""Initialization method. Args: params: Contains key-value parame... | stack_v2_sparse_classes_10k_train_006802 | 7,453 | permissive | [
{
"docstring": "Initialization method. Args: params: Contains key-value parameters to the meta-heuristics.",
"name": "__init__",
"signature": "def __init__(self, params: Optional[Dict[str, Any]]=None) -> None"
},
{
"docstring": "Calculates type A motion. Args: lb: Array of lower bounds. ub: Arra... | 2 | stack_v2_sparse_classes_30k_train_006131 | Implement the Python class `NBJS` described below.
Class description:
An NBJS class, inherited from JS. This is the designed class to define NBJS-related variables and methods. References: Publication pending.
Method signatures and docstrings:
- def __init__(self, params: Optional[Dict[str, Any]]=None) -> None: Initi... | Implement the Python class `NBJS` described below.
Class description:
An NBJS class, inherited from JS. This is the designed class to define NBJS-related variables and methods. References: Publication pending.
Method signatures and docstrings:
- def __init__(self, params: Optional[Dict[str, Any]]=None) -> None: Initi... | 7326a887ed8e3858bc99c8815048d56d02edf88c | <|skeleton|>
class NBJS:
"""An NBJS class, inherited from JS. This is the designed class to define NBJS-related variables and methods. References: Publication pending."""
def __init__(self, params: Optional[Dict[str, Any]]=None) -> None:
"""Initialization method. Args: params: Contains key-value parame... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NBJS:
"""An NBJS class, inherited from JS. This is the designed class to define NBJS-related variables and methods. References: Publication pending."""
def __init__(self, params: Optional[Dict[str, Any]]=None) -> None:
"""Initialization method. Args: params: Contains key-value parameters to the m... | the_stack_v2_python_sparse | opytimizer/optimizers/swarm/js.py | gugarosa/opytimizer | train | 602 |
d6b0951d56090710b977a15731c4a71573c82f0d | [
"if result is None:\n return {'code': code, 'error': error}\nelse:\n return {'code': code, 'error': error, 'result': result}",
"if api_code is None:\n return {'code': code, 'error': error, 'api_response': api_response}\nelse:\n return {'code': code, 'error': error, 'api_code': api_code, 'api_error': a... | <|body_start_0|>
if result is None:
return {'code': code, 'error': error}
else:
return {'code': code, 'error': error, 'result': result}
<|end_body_0|>
<|body_start_1|>
if api_code is None:
return {'code': code, 'error': error, 'api_response': api_response}
... | HttpResponse | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HttpResponse:
def normal(code, error='', result=None):
"""通用的相应格式"""
<|body_0|>
def third_party(code, error='', api_code=None, api_error=None, api_response=None):
"""第三方API响应格式 Args: code: 0代表正常返回，消息合法。-1代表异常，超时、断开、拒绝 error: code -1 error 不空 api_code: api返回的错误码 api_e... | stack_v2_sparse_classes_10k_train_006803 | 5,683 | no_license | [
{
"docstring": "通用的相应格式",
"name": "normal",
"signature": "def normal(code, error='', result=None)"
},
{
"docstring": "第三方API响应格式 Args: code: 0代表正常返回，消息合法。-1代表异常，超时、断开、拒绝 error: code -1 error 不空 api_code: api返回的错误码 api_error: api返回的错误消息 api_response: api返回的原始消息",
"name": "third_party",
"s... | 2 | stack_v2_sparse_classes_30k_train_005734 | Implement the Python class `HttpResponse` described below.
Class description:
Implement the HttpResponse class.
Method signatures and docstrings:
- def normal(code, error='', result=None): 通用的相应格式
- def third_party(code, error='', api_code=None, api_error=None, api_response=None): 第三方API响应格式 Args: code: 0代表正常返回，消息合法。... | Implement the Python class `HttpResponse` described below.
Class description:
Implement the HttpResponse class.
Method signatures and docstrings:
- def normal(code, error='', result=None): 通用的相应格式
- def third_party(code, error='', api_code=None, api_error=None, api_response=None): 第三方API响应格式 Args: code: 0代表正常返回，消息合法。... | 59df7e469009aca346b292f63cf466fb58caa7d2 | <|skeleton|>
class HttpResponse:
def normal(code, error='', result=None):
"""通用的相应格式"""
<|body_0|>
def third_party(code, error='', api_code=None, api_error=None, api_response=None):
"""第三方API响应格式 Args: code: 0代表正常返回，消息合法。-1代表异常，超时、断开、拒绝 error: code -1 error 不空 api_code: api返回的错误码 api_e... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HttpResponse:
def normal(code, error='', result=None):
"""通用的相应格式"""
if result is None:
return {'code': code, 'error': error}
else:
return {'code': code, 'error': error, 'result': result}
def third_party(code, error='', api_code=None, api_error=None, api_re... | the_stack_v2_python_sparse | src/app/common/utils/http_util.py | eckoq/gold-digger-server | train | 1 | |
db5981bcb87979b8820c2aa6db9e410cf59f8cd3 | [
"rating_value = 7\nrating_meaning = 'Indecisive'\nfestival = create_festival('IDFA', '2022-07-17', '2022-07-27')\nfilm = Film(festival_id=festival.id, film_id=-1, seq_nr=-1, title='A Test Movie', duration=timedelta(minutes=666))\nfilm.save()\nfan = me()\nrating = FilmFanFilmRating(film=film, film_fan=fan, rating=ra... | <|body_start_0|>
rating_value = 7
rating_meaning = 'Indecisive'
festival = create_festival('IDFA', '2022-07-17', '2022-07-27')
film = Film(festival_id=festival.id, film_id=-1, seq_nr=-1, title='A Test Movie', duration=timedelta(minutes=666))
film.save()
fan = me()
... | RatingModelTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RatingModelTests:
def test_rating_has_correct_meaning(self):
"""Rating 7 has meaning INDECISIVE."""
<|body_0|>
def test_ratings_can_have_same_film_id_but_not_same_festival_id(self):
"""Two ratings can only have films with identical film_id if festivals are different.... | stack_v2_sparse_classes_10k_train_006804 | 17,658 | no_license | [
{
"docstring": "Rating 7 has meaning INDECISIVE.",
"name": "test_rating_has_correct_meaning",
"signature": "def test_rating_has_correct_meaning(self)"
},
{
"docstring": "Two ratings can only have films with identical film_id if festivals are different.",
"name": "test_ratings_can_have_same_f... | 2 | stack_v2_sparse_classes_30k_train_004935 | Implement the Python class `RatingModelTests` described below.
Class description:
Implement the RatingModelTests class.
Method signatures and docstrings:
- def test_rating_has_correct_meaning(self): Rating 7 has meaning INDECISIVE.
- def test_ratings_can_have_same_film_id_but_not_same_festival_id(self): Two ratings c... | Implement the Python class `RatingModelTests` described below.
Class description:
Implement the RatingModelTests class.
Method signatures and docstrings:
- def test_rating_has_correct_meaning(self): Rating 7 has meaning INDECISIVE.
- def test_ratings_can_have_same_film_id_but_not_same_festival_id(self): Two ratings c... | 4ebc9b43a07bbc627b5e21cae368ae31828d3d2e | <|skeleton|>
class RatingModelTests:
def test_rating_has_correct_meaning(self):
"""Rating 7 has meaning INDECISIVE."""
<|body_0|>
def test_ratings_can_have_same_film_id_but_not_same_festival_id(self):
"""Two ratings can only have films with identical film_id if festivals are different.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RatingModelTests:
def test_rating_has_correct_meaning(self):
"""Rating 7 has meaning INDECISIVE."""
rating_value = 7
rating_meaning = 'Indecisive'
festival = create_festival('IDFA', '2022-07-17', '2022-07-27')
film = Film(festival_id=festival.id, film_id=-1, seq_nr=-1, ... | the_stack_v2_python_sparse | FilmRatings/film_list/tests.py | maar35/film-festival-planner | train | 0 | |
cf2c02595365efd00b1628a9c11ab5e178f75920 | [
"if getattr(spec, 'project_id', None) and getattr(spec, 'labels', None):\n raise exceptions.ApiValueError(\"Can't set labels to a task inside a project. Tasks inside a project use project's labels.\", ['labels'])\ntask = self.create(spec=spec)\nself._client.logger.info('Created task ID: %s NAME: %s', task.id, ta... | <|body_start_0|>
if getattr(spec, 'project_id', None) and getattr(spec, 'labels', None):
raise exceptions.ApiValueError("Can't set labels to a task inside a project. Tasks inside a project use project's labels.", ['labels'])
task = self.create(spec=spec)
self._client.logger.info('Cre... | TasksRepo | [
"LGPL-2.0-or-later",
"MIT",
"GPL-1.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TasksRepo:
def create_from_data(self, spec: models.ITaskWriteRequest, resources: Sequence[StrPath], *, resource_type: ResourceType=ResourceType.LOCAL, data_params: Optional[Dict[str, Any]]=None, annotation_path: str='', annotation_format: str='CVAT XML 1.1', status_check_period: int=None, datase... | stack_v2_sparse_classes_10k_train_006805 | 14,269 | permissive | [
{
"docstring": "Create a new task with the given name and labels JSON and add the files to it. Returns: id of the created task",
"name": "create_from_data",
"signature": "def create_from_data(self, spec: models.ITaskWriteRequest, resources: Sequence[StrPath], *, resource_type: ResourceType=ResourceType.... | 3 | stack_v2_sparse_classes_30k_train_003381 | Implement the Python class `TasksRepo` described below.
Class description:
Implement the TasksRepo class.
Method signatures and docstrings:
- def create_from_data(self, spec: models.ITaskWriteRequest, resources: Sequence[StrPath], *, resource_type: ResourceType=ResourceType.LOCAL, data_params: Optional[Dict[str, Any]... | Implement the Python class `TasksRepo` described below.
Class description:
Implement the TasksRepo class.
Method signatures and docstrings:
- def create_from_data(self, spec: models.ITaskWriteRequest, resources: Sequence[StrPath], *, resource_type: ResourceType=ResourceType.LOCAL, data_params: Optional[Dict[str, Any]... | 899c9fd75146744def061efd7ab1b1c6c9f6942f | <|skeleton|>
class TasksRepo:
def create_from_data(self, spec: models.ITaskWriteRequest, resources: Sequence[StrPath], *, resource_type: ResourceType=ResourceType.LOCAL, data_params: Optional[Dict[str, Any]]=None, annotation_path: str='', annotation_format: str='CVAT XML 1.1', status_check_period: int=None, datase... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TasksRepo:
def create_from_data(self, spec: models.ITaskWriteRequest, resources: Sequence[StrPath], *, resource_type: ResourceType=ResourceType.LOCAL, data_params: Optional[Dict[str, Any]]=None, annotation_path: str='', annotation_format: str='CVAT XML 1.1', status_check_period: int=None, dataset_repository_u... | the_stack_v2_python_sparse | cvat-sdk/cvat_sdk/core/proxies/tasks.py | opencv/cvat | train | 6,558 | |
e5cb7e9827d9baa3b5468665610161d64aec31a8 | [
"self.model_dir = os.path.join(self.directory, 'webpage')\nself.conf_file = 'slda.conf'\nself.__engine = InferenceEngine(self.model_dir, self.conf_file)\nself.vocab_path = os.path.join(self.model_dir, 'vocab_info.txt')\nlac = hub.Module(name='lac')\nself.__tokenizer = LACTokenizer(self.vocab_path, lac)\nself.vocabu... | <|body_start_0|>
self.model_dir = os.path.join(self.directory, 'webpage')
self.conf_file = 'slda.conf'
self.__engine = InferenceEngine(self.model_dir, self.conf_file)
self.vocab_path = os.path.join(self.model_dir, 'vocab_info.txt')
lac = hub.Module(name='lac')
self.__toke... | TopicModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopicModel:
def _initialize(self):
"""Initialize with the necessary elements."""
<|body_0|>
def infer_doc_topic_distribution(self, document):
"""This interface infers the topic distribution of document. Args: document(str): the input document text. Returns: results(l... | stack_v2_sparse_classes_10k_train_006806 | 3,571 | permissive | [
{
"docstring": "Initialize with the necessary elements.",
"name": "_initialize",
"signature": "def _initialize(self)"
},
{
"docstring": "This interface infers the topic distribution of document. Args: document(str): the input document text. Returns: results(list): returns the topic distribution ... | 3 | stack_v2_sparse_classes_30k_train_001131 | Implement the Python class `TopicModel` described below.
Class description:
Implement the TopicModel class.
Method signatures and docstrings:
- def _initialize(self): Initialize with the necessary elements.
- def infer_doc_topic_distribution(self, document): This interface infers the topic distribution of document. A... | Implement the Python class `TopicModel` described below.
Class description:
Implement the TopicModel class.
Method signatures and docstrings:
- def _initialize(self): Initialize with the necessary elements.
- def infer_doc_topic_distribution(self, document): This interface infers the topic distribution of document. A... | b402610a6f0b382a978e82473b541ea1fc6cf09a | <|skeleton|>
class TopicModel:
def _initialize(self):
"""Initialize with the necessary elements."""
<|body_0|>
def infer_doc_topic_distribution(self, document):
"""This interface infers the topic distribution of document. Args: document(str): the input document text. Returns: results(l... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TopicModel:
def _initialize(self):
"""Initialize with the necessary elements."""
self.model_dir = os.path.join(self.directory, 'webpage')
self.conf_file = 'slda.conf'
self.__engine = InferenceEngine(self.model_dir, self.conf_file)
self.vocab_path = os.path.join(self.mod... | the_stack_v2_python_sparse | modules/text/language_model/slda_webpage/module.py | PaddlePaddle/PaddleHub | train | 12,914 | |
e0de74640c8a2f55e739fb3e847216fc118d0330 | [
"r, c = left_filter.shape\nassert left_filter.shape == right_filter.shape\nself.left_filter = left_filter\nself.right_filter = right_filter\nself.left_filter_dft = cv2.dft(left_filter)\nself.right_filter_dft = cv2.dft(right_filter)\nself.image = np.zeros((r, c), dtype=np.float32)\nself.image = np.zeros((r, c), dtyp... | <|body_start_0|>
r, c = left_filter.shape
assert left_filter.shape == right_filter.shape
self.left_filter = left_filter
self.right_filter = right_filter
self.left_filter_dft = cv2.dft(left_filter)
self.right_filter_dft = cv2.dft(right_filter)
self.image = np.zeros... | This class is used for someone only interested in locating the eyes in an image using correlation filters. This class does not include any support for training correlation filters. For training see ASEF. This class is written only using OpenCV and is much faster than the ASEF class. For details see the paper: David S. ... | OpenCVFilterEyeLocator | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpenCVFilterEyeLocator:
"""This class is used for someone only interested in locating the eyes in an image using correlation filters. This class does not include any support for training correlation filters. For training see ASEF. This class is written only using OpenCV and is much faster than th... | stack_v2_sparse_classes_10k_train_006807 | 14,116 | permissive | [
{
"docstring": "@param left_filter: is in the Fourier domain where the left eye corresponds to the real output and the right eye corresponds to the imaginary output",
"name": "__init__",
"signature": "def __init__(self, left_filter, right_filter, left_rect, right_rect)"
},
{
"docstring": "@param... | 4 | stack_v2_sparse_classes_30k_train_001092 | Implement the Python class `OpenCVFilterEyeLocator` described below.
Class description:
This class is used for someone only interested in locating the eyes in an image using correlation filters. This class does not include any support for training correlation filters. For training see ASEF. This class is written only ... | Implement the Python class `OpenCVFilterEyeLocator` described below.
Class description:
This class is used for someone only interested in locating the eyes in an image using correlation filters. This class does not include any support for training correlation filters. For training see ASEF. This class is written only ... | caa4e0254f55c5c8f3464807556b9414ea731293 | <|skeleton|>
class OpenCVFilterEyeLocator:
"""This class is used for someone only interested in locating the eyes in an image using correlation filters. This class does not include any support for training correlation filters. For training see ASEF. This class is written only using OpenCV and is much faster than th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OpenCVFilterEyeLocator:
"""This class is used for someone only interested in locating the eyes in an image using correlation filters. This class does not include any support for training correlation filters. For training see ASEF. This class is written only using OpenCV and is much faster than the ASEF class.... | the_stack_v2_python_sparse | src/pyvision/face/FilterEyeLocator.py | bolme/pyvision | train | 47 |
df559ebb20da446d3e89da980481ae63899edc62 | [
"if n == 3 or n == 2:\n return 2\nelif n == 1:\n return 1\nelse:\n base = 4 * self.lastRemaining_(n / 4)\n if n % 4 == 0 or n % 4 == 1:\n return base - 2\n else:\n return base",
"a = p = 1\ncnt = 0\nwhile n > 1:\n n /= 2\n cnt += 1\n p *= 2\n if cnt % 2:\n a += p / ... | <|body_start_0|>
if n == 3 or n == 2:
return 2
elif n == 1:
return 1
else:
base = 4 * self.lastRemaining_(n / 4)
if n % 4 == 0 or n % 4 == 1:
return base - 2
else:
return base
<|end_body_0|>
<|body_start... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lastRemaining_(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def lastRemaining(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 3 or n == 2:
return 2
elif n == 1:
... | stack_v2_sparse_classes_10k_train_006808 | 1,529 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "lastRemaining_",
"signature": "def lastRemaining_(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "lastRemaining",
"signature": "def lastRemaining(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lastRemaining_(self, n): :type n: int :rtype: int
- def lastRemaining(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lastRemaining_(self, n): :type n: int :rtype: int
- def lastRemaining(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def lastRemaining_(self, n):
... | 1520e1e9bb0c428797a3e5234e5b328110472c20 | <|skeleton|>
class Solution:
def lastRemaining_(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def lastRemaining(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def lastRemaining_(self, n):
""":type n: int :rtype: int"""
if n == 3 or n == 2:
return 2
elif n == 1:
return 1
else:
base = 4 * self.lastRemaining_(n / 4)
if n % 4 == 0 or n % 4 == 1:
return base - 2
... | the_stack_v2_python_sparse | simulation/390. Elimination Game.py | tinkle1129/Leetcode_Solution | train | 0 | |
85945abf96e9e65965011588448b15a8942286ea | [
"self._data_access = data_access\nself._scenario_info = scenario_info\nself.backup_config = server_setup.PathConfig(server_setup.BACKUP_DATA_ROOT_DIR)\nself.server_config = server_setup.PathConfig(server_setup.DATA_ROOT_DIR)",
"print('--> Moving scenario input data to backup disk')\nsource = posixpath.join(self.s... | <|body_start_0|>
self._data_access = data_access
self._scenario_info = scenario_info
self.backup_config = server_setup.PathConfig(server_setup.BACKUP_DATA_ROOT_DIR)
self.server_config = server_setup.PathConfig(server_setup.DATA_ROOT_DIR)
<|end_body_0|>
<|body_start_1|>
print('--... | Back up scenario data to backup disk mounted on server. :param powersimdata.data_access.data_access.DataAccess data_access: data access object. :param dict scenario: scenario information. | BackUpDisk | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackUpDisk:
"""Back up scenario data to backup disk mounted on server. :param powersimdata.data_access.data_access.DataAccess data_access: data access object. :param dict scenario: scenario information."""
def __init__(self, data_access, scenario_info):
"""Constructor."""
<|b... | stack_v2_sparse_classes_10k_train_006809 | 4,029 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, data_access, scenario_info)"
},
{
"docstring": "Moves input data.",
"name": "move_input_data",
"signature": "def move_input_data(self)"
},
{
"docstring": "Copies base profile",
"name": "copy_b... | 5 | stack_v2_sparse_classes_30k_train_003709 | Implement the Python class `BackUpDisk` described below.
Class description:
Back up scenario data to backup disk mounted on server. :param powersimdata.data_access.data_access.DataAccess data_access: data access object. :param dict scenario: scenario information.
Method signatures and docstrings:
- def __init__(self,... | Implement the Python class `BackUpDisk` described below.
Class description:
Back up scenario data to backup disk mounted on server. :param powersimdata.data_access.data_access.DataAccess data_access: data access object. :param dict scenario: scenario information.
Method signatures and docstrings:
- def __init__(self,... | 59f10383eca9f89be6ca606a4eed5bcc9a00a9be | <|skeleton|>
class BackUpDisk:
"""Back up scenario data to backup disk mounted on server. :param powersimdata.data_access.data_access.DataAccess data_access: data access object. :param dict scenario: scenario information."""
def __init__(self, data_access, scenario_info):
"""Constructor."""
<|b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BackUpDisk:
"""Back up scenario data to backup disk mounted on server. :param powersimdata.data_access.data_access.DataAccess data_access: data access object. :param dict scenario: scenario information."""
def __init__(self, data_access, scenario_info):
"""Constructor."""
self._data_acces... | the_stack_v2_python_sparse | powersimdata/scenario/move.py | eliasidanimas/PowerSimData | train | 0 |
e0fe56975cc73becdc5b8364b51699dd7c60ce9c | [
"if self.request.user.is_superuser:\n return models.Workflow.objects.all()\nreturn models.Workflow.objects.filter(Q(user=self.request.user) | Q(shared=self.request.user)).distinct()",
"if self.request.user.is_superuser:\n serializer.save()\nelse:\n serializer.save(user=self.request.user)"
] | <|body_start_0|>
if self.request.user.is_superuser:
return models.Workflow.objects.all()
return models.Workflow.objects.filter(Q(user=self.request.user) | Q(shared=self.request.user)).distinct()
<|end_body_0|>
<|body_start_1|>
if self.request.user.is_superuser:
serialize... | Access the workflow. get: Return a list of available workflows post: Create a new workflow given name, description and attributes | WorkflowAPIListCreate | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkflowAPIListCreate:
"""Access the workflow. get: Return a list of available workflows post: Create a new workflow given name, description and attributes"""
def get_queryset(self):
"""Access the required workflow."""
<|body_0|>
def perform_create(self, serializer):
... | stack_v2_sparse_classes_10k_train_006810 | 4,435 | permissive | [
{
"docstring": "Access the required workflow.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Create the new workflow.",
"name": "perform_create",
"signature": "def perform_create(self, serializer)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002409 | Implement the Python class `WorkflowAPIListCreate` described below.
Class description:
Access the workflow. get: Return a list of available workflows post: Create a new workflow given name, description and attributes
Method signatures and docstrings:
- def get_queryset(self): Access the required workflow.
- def perfo... | Implement the Python class `WorkflowAPIListCreate` described below.
Class description:
Access the workflow. get: Return a list of available workflows post: Create a new workflow given name, description and attributes
Method signatures and docstrings:
- def get_queryset(self): Access the required workflow.
- def perfo... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class WorkflowAPIListCreate:
"""Access the workflow. get: Return a list of available workflows post: Create a new workflow given name, description and attributes"""
def get_queryset(self):
"""Access the required workflow."""
<|body_0|>
def perform_create(self, serializer):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WorkflowAPIListCreate:
"""Access the workflow. get: Return a list of available workflows post: Create a new workflow given name, description and attributes"""
def get_queryset(self):
"""Access the required workflow."""
if self.request.user.is_superuser:
return models.Workflow.... | the_stack_v2_python_sparse | ontask/workflow/api.py | abelardopardo/ontask_b | train | 43 |
fd05645598835592fb1e9c22e8857f6c99964232 | [
"self.path = self.__default_filepath if filepath is None else filepath\nself.parser = configparser.ConfigParser()\nif self.__section_default not in self.parser.sections():\n self.parser.add_section(self.__section_default)\nself.parser.read(self.path)",
"if self.parser.has_option(section, name):\n return sel... | <|body_start_0|>
self.path = self.__default_filepath if filepath is None else filepath
self.parser = configparser.ConfigParser()
if self.__section_default not in self.parser.sections():
self.parser.add_section(self.__section_default)
self.parser.read(self.path)
<|end_body_0|>... | A controller class for getting and setting key/value pairs in the config file | Controller | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""A controller class for getting and setting key/value pairs in the config file"""
def __init__(self, filepath=None):
"""Create an instance of a config controller for getting and setting information"""
<|body_0|>
def get(self, name, section=__section_default... | stack_v2_sparse_classes_10k_train_006811 | 2,040 | permissive | [
{
"docstring": "Create an instance of a config controller for getting and setting information",
"name": "__init__",
"signature": "def __init__(self, filepath=None)"
},
{
"docstring": "Returns a value with a given name from the configuration file.",
"name": "get",
"signature": "def get(se... | 4 | stack_v2_sparse_classes_30k_train_002808 | Implement the Python class `Controller` described below.
Class description:
A controller class for getting and setting key/value pairs in the config file
Method signatures and docstrings:
- def __init__(self, filepath=None): Create an instance of a config controller for getting and setting information
- def get(self,... | Implement the Python class `Controller` described below.
Class description:
A controller class for getting and setting key/value pairs in the config file
Method signatures and docstrings:
- def __init__(self, filepath=None): Create an instance of a config controller for getting and setting information
- def get(self,... | 25bc6118427f3b369fb61ba0bd38c977be05644f | <|skeleton|>
class Controller:
"""A controller class for getting and setting key/value pairs in the config file"""
def __init__(self, filepath=None):
"""Create an instance of a config controller for getting and setting information"""
<|body_0|>
def get(self, name, section=__section_default... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Controller:
"""A controller class for getting and setting key/value pairs in the config file"""
def __init__(self, filepath=None):
"""Create an instance of a config controller for getting and setting information"""
self.path = self.__default_filepath if filepath is None else filepath
... | the_stack_v2_python_sparse | apiwrapper/config/controller.py | OGKevin/ComBunqWebApp | train | 31 |
dcad37a8101e1054ceb0404e5dcec42041a1f2a3 | [
"BaseController.__init__(self, veh_id, car_following_params, delay=time_delay, fail_safe=fail_safe, noise=noise)\nself.veh_id = veh_id\nself.v_max = v_max\nself.adaptation = adaptation\nself.h_st = h_st",
"this_vel = env.k.vehicle.get_speed(self.veh_id)\nh = env.k.vehicle.get_headway(self.veh_id)\nalpha = 1.689\n... | <|body_start_0|>
BaseController.__init__(self, veh_id, car_following_params, delay=time_delay, fail_safe=fail_safe, noise=noise)
self.veh_id = veh_id
self.v_max = v_max
self.adaptation = adaptation
self.h_st = h_st
<|end_body_0|>
<|body_start_1|>
this_vel = env.k.vehicle... | Linear OVM controller. Usage ----- See BaseController for usage example. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class v_max : float max velocity (default: 30) adaptation : float adaptation constant (default: 0.65) h... | LinearOVM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearOVM:
"""Linear OVM controller. Usage ----- See BaseController for usage example. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class v_max : float max velocity (default: 30) adaptation : float ... | stack_v2_sparse_classes_10k_train_006812 | 17,548 | permissive | [
{
"docstring": "Instantiate a Linear OVM controller.",
"name": "__init__",
"signature": "def __init__(self, veh_id, car_following_params, v_max=30, adaptation=0.65, h_st=5, time_delay=0.0, noise=0, fail_safe=None)"
},
{
"docstring": "See parent class.",
"name": "get_accel",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_003259 | Implement the Python class `LinearOVM` described below.
Class description:
Linear OVM controller. Usage ----- See BaseController for usage example. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class v_max : float max vel... | Implement the Python class `LinearOVM` described below.
Class description:
Linear OVM controller. Usage ----- See BaseController for usage example. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class v_max : float max vel... | badac3da17f04d8d8ae5691ee8ba2af9d56fac35 | <|skeleton|>
class LinearOVM:
"""Linear OVM controller. Usage ----- See BaseController for usage example. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class v_max : float max velocity (default: 30) adaptation : float ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LinearOVM:
"""Linear OVM controller. Usage ----- See BaseController for usage example. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class v_max : float max velocity (default: 30) adaptation : float adaptation co... | the_stack_v2_python_sparse | flow/controllers/car_following_models.py | parthjaggi/flow | train | 6 |
989875b13851df27bc8654709f1cf23c065a5cd3 | [
"print('before init')\nsuper().__init__()\nprint('before get')\nresnet = get_visn_arch(arch)(pretrained=pretrained)\nprint('after get')\nfor param in resnet.parameters():\n param.requires_grad = False\nresnet.fc = nn.Identity()\nself.backbone = resnet",
"x = self.backbone(img)\nx = x.detach()\nreturn x"
] | <|body_start_0|>
print('before init')
super().__init__()
print('before get')
resnet = get_visn_arch(arch)(pretrained=pretrained)
print('after get')
for param in resnet.parameters():
param.requires_grad = False
resnet.fc = nn.Identity()
self.bac... | VisnModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VisnModel:
def __init__(self, arch='resnet50', pretrained=True):
""":param dim: dimension of the output :param arch: backbone architecture, :param pretrained: load feature with pre-trained vector :param finetuning: finetune the model"""
<|body_0|>
def forward(self, img):
... | stack_v2_sparse_classes_10k_train_006813 | 11,557 | permissive | [
{
"docstring": ":param dim: dimension of the output :param arch: backbone architecture, :param pretrained: load feature with pre-trained vector :param finetuning: finetune the model",
"name": "__init__",
"signature": "def __init__(self, arch='resnet50', pretrained=True)"
},
{
"docstring": ":para... | 2 | stack_v2_sparse_classes_30k_train_002241 | Implement the Python class `VisnModel` described below.
Class description:
Implement the VisnModel class.
Method signatures and docstrings:
- def __init__(self, arch='resnet50', pretrained=True): :param dim: dimension of the output :param arch: backbone architecture, :param pretrained: load feature with pre-trained v... | Implement the Python class `VisnModel` described below.
Class description:
Implement the VisnModel class.
Method signatures and docstrings:
- def __init__(self, arch='resnet50', pretrained=True): :param dim: dimension of the output :param arch: backbone architecture, :param pretrained: load feature with pre-trained v... | 51ac07d1de564c26fbf038b07031a55660bbcb27 | <|skeleton|>
class VisnModel:
def __init__(self, arch='resnet50', pretrained=True):
""":param dim: dimension of the output :param arch: backbone architecture, :param pretrained: load feature with pre-trained vector :param finetuning: finetune the model"""
<|body_0|>
def forward(self, img):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VisnModel:
def __init__(self, arch='resnet50', pretrained=True):
""":param dim: dimension of the output :param arch: backbone architecture, :param pretrained: load feature with pre-trained vector :param finetuning: finetune the model"""
print('before init')
super().__init__()
p... | the_stack_v2_python_sparse | retrieval_model/vokenization/tmp_extract_vision_keys.py | CJJ2923/Maria | train | 0 | |
2d1f12bafaf2f46d5a0e394435f9da2eefa1eaa6 | [
"search = data.get('search', None)\noffset = int(data.get('offset', 0))\nlimit = int(data.get('limit', 0))\ntime_from = int(data.get('from', 0))\ntime_until = int(data.get('until', 0))\nstatus = data.get('status', None)\ntitle = data.get('title', None)\ndevice_id = data.get('device_id', None)\nalert_id = data.get('... | <|body_start_0|>
search = data.get('search', None)
offset = int(data.get('offset', 0))
limit = int(data.get('limit', 0))
time_from = int(data.get('from', 0))
time_until = int(data.get('until', 0))
status = data.get('status', None)
title = data.get('title', None)
... | AlertsHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlertsHandler:
def do_get(self, data):
"""获取告警"""
<|body_0|>
def do_put(self, data):
"""确认告警"""
<|body_1|>
def do_delete(self, data):
"""关闭告警"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
search = data.get('search', None)
... | stack_v2_sparse_classes_10k_train_006814 | 6,220 | no_license | [
{
"docstring": "获取告警",
"name": "do_get",
"signature": "def do_get(self, data)"
},
{
"docstring": "确认告警",
"name": "do_put",
"signature": "def do_put(self, data)"
},
{
"docstring": "关闭告警",
"name": "do_delete",
"signature": "def do_delete(self, data)"
}
] | 3 | stack_v2_sparse_classes_30k_train_002033 | Implement the Python class `AlertsHandler` described below.
Class description:
Implement the AlertsHandler class.
Method signatures and docstrings:
- def do_get(self, data): 获取告警
- def do_put(self, data): 确认告警
- def do_delete(self, data): 关闭告警 | Implement the Python class `AlertsHandler` described below.
Class description:
Implement the AlertsHandler class.
Method signatures and docstrings:
- def do_get(self, data): 获取告警
- def do_put(self, data): 确认告警
- def do_delete(self, data): 关闭告警
<|skeleton|>
class AlertsHandler:
def do_get(self, data):
""... | 94dc54ddbacc0282a6339b06e76ed6bf646bcd2b | <|skeleton|>
class AlertsHandler:
def do_get(self, data):
"""获取告警"""
<|body_0|>
def do_put(self, data):
"""确认告警"""
<|body_1|>
def do_delete(self, data):
"""关闭告警"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AlertsHandler:
def do_get(self, data):
"""获取告警"""
search = data.get('search', None)
offset = int(data.get('offset', 0))
limit = int(data.get('limit', 0))
time_from = int(data.get('from', 0))
time_until = int(data.get('until', 0))
status = data.get('statu... | the_stack_v2_python_sparse | backend/handlers/alerts.py | alabizz/w2s | train | 0 | |
f33dd088b2f7f3fe2b3635e3733ea0f8fe2572dd | [
"geo_api = GeoNamesAPI()\nresults = geo_api.search(self.q, max_rows=50)\nreturn JsonResponse({'results': [dict(id=geo_api.uri_from_id(item['geonameId']), text=self.get_label(item), name=item['name'], lat=item['lat'], lng=item['lng']) for item in results]})",
"if 'countryName' in item:\n return '%(name)s, %(cou... | <|body_start_0|>
geo_api = GeoNamesAPI()
results = geo_api.search(self.q, max_rows=50)
return JsonResponse({'results': [dict(id=geo_api.uri_from_id(item['geonameId']), text=self.get_label(item), name=item['name'], lat=item['lat'], lng=item['lng']) for item in results]})
<|end_body_0|>
<|body_st... | GeoNames ajax lookup for use as autocomplete. Currently restricted to staff only. | GeonamesLookup | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeonamesLookup:
"""GeoNames ajax lookup for use as autocomplete. Currently restricted to staff only."""
def get(self, request, *args, **kwargs):
"""Return option list json response."""
<|body_0|>
def get_label(self, item):
"""Display country name as part of label... | stack_v2_sparse_classes_10k_train_006815 | 1,477 | permissive | [
{
"docstring": "Return option list json response.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Display country name as part of label for context.",
"name": "get_label",
"signature": "def get_label(self, item)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006245 | Implement the Python class `GeonamesLookup` described below.
Class description:
GeoNames ajax lookup for use as autocomplete. Currently restricted to staff only.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Return option list json response.
- def get_label(self, item): Display country ... | Implement the Python class `GeonamesLookup` described below.
Class description:
GeoNames ajax lookup for use as autocomplete. Currently restricted to staff only.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Return option list json response.
- def get_label(self, item): Display country ... | 6371bb1266d7751af59aeaa3426ef7ac02a1fe17 | <|skeleton|>
class GeonamesLookup:
"""GeoNames ajax lookup for use as autocomplete. Currently restricted to staff only."""
def get(self, request, *args, **kwargs):
"""Return option list json response."""
<|body_0|>
def get_label(self, item):
"""Display country name as part of label... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GeonamesLookup:
"""GeoNames ajax lookup for use as autocomplete. Currently restricted to staff only."""
def get(self, request, *args, **kwargs):
"""Return option list json response."""
geo_api = GeoNamesAPI()
results = geo_api.search(self.q, max_rows=50)
return JsonRespons... | the_stack_v2_python_sparse | derrida/places/views.py | Princeton-CDH/derrida-django | train | 13 |
f5ea304ad1602160cf832cf52fcc9ad701f3fc09 | [
"super(EmBLeafMerge, self).__init__()\nsuper(EmBLeafScenario, self).__init__()\nself.service = GlobalModule.SERVICE_B_LEAF\nself._xml_ns = '{%s}' % GlobalModule.EM_NAME_SPACES[self.service]\nself._scenario_name = 'B-LeafMerge'\nself.device_type = 'device'",
"xml_elm = etree.fromstring(device_message)\nGlobalModul... | <|body_start_0|>
super(EmBLeafMerge, self).__init__()
super(EmBLeafScenario, self).__init__()
self.service = GlobalModule.SERVICE_B_LEAF
self._xml_ns = '{%s}' % GlobalModule.EM_NAME_SPACES[self.service]
self._scenario_name = 'B-LeafMerge'
self.device_type = 'device'
<|end... | B-Leaf expansion class (take-over from Leaf expansion scenario) | EmBLeafMerge | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmBLeafMerge:
"""B-Leaf expansion class (take-over from Leaf expansion scenario)"""
def __init__(self):
"""Constructor"""
<|body_0|>
def _creating_json(self, device_message):
"""Convert EC message (XML) divided for each device into JSON. Explanation about paramet... | stack_v2_sparse_classes_10k_train_006816 | 2,172 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Convert EC message (XML) divided for each device into JSON. Explanation about parameter： device_message: Message for each device Explanation about return value device_json_message: JSON message... | 2 | stack_v2_sparse_classes_30k_train_005673 | Implement the Python class `EmBLeafMerge` described below.
Class description:
B-Leaf expansion class (take-over from Leaf expansion scenario)
Method signatures and docstrings:
- def __init__(self): Constructor
- def _creating_json(self, device_message): Convert EC message (XML) divided for each device into JSON. Expl... | Implement the Python class `EmBLeafMerge` described below.
Class description:
B-Leaf expansion class (take-over from Leaf expansion scenario)
Method signatures and docstrings:
- def __init__(self): Constructor
- def _creating_json(self, device_message): Convert EC message (XML) divided for each device into JSON. Expl... | e550d1b5ec9419f1fb3eb6e058ce46b57c92ee2f | <|skeleton|>
class EmBLeafMerge:
"""B-Leaf expansion class (take-over from Leaf expansion scenario)"""
def __init__(self):
"""Constructor"""
<|body_0|>
def _creating_json(self, device_message):
"""Convert EC message (XML) divided for each device into JSON. Explanation about paramet... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EmBLeafMerge:
"""B-Leaf expansion class (take-over from Leaf expansion scenario)"""
def __init__(self):
"""Constructor"""
super(EmBLeafMerge, self).__init__()
super(EmBLeafScenario, self).__init__()
self.service = GlobalModule.SERVICE_B_LEAF
self._xml_ns = '{%s}' %... | the_stack_v2_python_sparse | lib/Scenario/EmBLeafMerge.py | lixiaochun/element-manager | train | 0 |
e1f4be9e5cd9c0f2196045d9eae82e270c395ef3 | [
"opening, count = (0, 0)\nfor ch in S:\n if ch == '(':\n opening += 1\n elif opening > 0:\n opening -= 1\n else:\n count += 1\nreturn count + opening",
"dq = collections.deque()\nl = []\nstackEmpty = True\nfor ch in S:\n if ch == ')':\n if len(dq) == 0:\n l.appen... | <|body_start_0|>
opening, count = (0, 0)
for ch in S:
if ch == '(':
opening += 1
elif opening > 0:
opening -= 1
else:
count += 1
return count + opening
<|end_body_0|>
<|body_start_1|>
dq = collections.de... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minAddToMakeValid(self, S):
""":type S: str :rtype: int"""
<|body_0|>
def minAddToMakeValid2(self, S):
""":type S: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
opening, count = (0, 0)
for ch in S:
... | stack_v2_sparse_classes_10k_train_006817 | 1,042 | no_license | [
{
"docstring": ":type S: str :rtype: int",
"name": "minAddToMakeValid",
"signature": "def minAddToMakeValid(self, S)"
},
{
"docstring": ":type S: str :rtype: int",
"name": "minAddToMakeValid2",
"signature": "def minAddToMakeValid2(self, S)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minAddToMakeValid(self, S): :type S: str :rtype: int
- def minAddToMakeValid2(self, S): :type S: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minAddToMakeValid(self, S): :type S: str :rtype: int
- def minAddToMakeValid2(self, S): :type S: str :rtype: int
<|skeleton|>
class Solution:
def minAddToMakeValid(self... | 813235789ce422a3bab198317aafc46fbc61625e | <|skeleton|>
class Solution:
def minAddToMakeValid(self, S):
""":type S: str :rtype: int"""
<|body_0|>
def minAddToMakeValid2(self, S):
""":type S: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def minAddToMakeValid(self, S):
""":type S: str :rtype: int"""
opening, count = (0, 0)
for ch in S:
if ch == '(':
opening += 1
elif opening > 0:
opening -= 1
else:
count += 1
return co... | the_stack_v2_python_sparse | 11. STRING MANIP/921_Minimum Add to Make Parentheses Valid/solution.py | kimmyoo/python_leetcode | train | 1 | |
9bc991fe583a01460701d2176a8083bcf2b5f7ab | [
"left = 0\nright = len(nums)\nwhile left < right:\n mid = (left + right) // 2\n if mid - 1 < 0:\n l_value = -2 ** 31\n else:\n l_value = nums[mid - 1]\n if mid + 1 >= len(nums):\n r_value = -2 ** 31\n else:\n r_value = nums[mid + 1]\n if nums[mid] > l_value and nums[mid... | <|body_start_0|>
left = 0
right = len(nums)
while left < right:
mid = (left + right) // 2
if mid - 1 < 0:
l_value = -2 ** 31
else:
l_value = nums[mid - 1]
if mid + 1 >= len(nums):
r_value = -2 ** 31
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findPeakElement_myself(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findPeakElement_v2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def findPeakElement(self, nums):
""":type nums: List[int] ... | stack_v2_sparse_classes_10k_train_006818 | 5,191 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findPeakElement_myself",
"signature": "def findPeakElement_myself(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findPeakElement_v2",
"signature": "def findPeakElement_v2(self, nums)"
},
{
... | 3 | stack_v2_sparse_classes_30k_val_000358 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPeakElement_myself(self, nums): :type nums: List[int] :rtype: int
- def findPeakElement_v2(self, nums): :type nums: List[int] :rtype: int
- def findPeakElement(self, nums... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPeakElement_myself(self, nums): :type nums: List[int] :rtype: int
- def findPeakElement_v2(self, nums): :type nums: List[int] :rtype: int
- def findPeakElement(self, nums... | 93266095329e2e8e949a72371b88b07382a60e0d | <|skeleton|>
class Solution:
def findPeakElement_myself(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findPeakElement_v2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def findPeakElement(self, nums):
""":type nums: List[int] ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findPeakElement_myself(self, nums):
""":type nums: List[int] :rtype: int"""
left = 0
right = len(nums)
while left < right:
mid = (left + right) // 2
if mid - 1 < 0:
l_value = -2 ** 31
else:
l_valu... | the_stack_v2_python_sparse | findPeakElement.py | shivangi-prog/leetcode | train | 0 | |
777f59068da91a2689ace0b31b53a77b956cd0ca | [
"password1 = self.cleaned_data.get('password1')\npassword2 = self.cleaned_data.get('password2')\nif password1 and password2 and (password1 != password2):\n raise forms.ValidationError('Passwords do not match')\nreturn password2",
"user = super(UserCreationForm, self).save(commit=False)\nuser.set_password(self.... | <|body_start_0|>
password1 = self.cleaned_data.get('password1')
password2 = self.cleaned_data.get('password2')
if password1 and password2 and (password1 != password2):
raise forms.ValidationError('Passwords do not match')
return password2
<|end_body_0|>
<|body_start_1|>
... | A form for creating new users with a password confirmation field. | UserCreationForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCreationForm:
"""A form for creating new users with a password confirmation field."""
def clean_password(self):
"""Checks that both of the passwords match :return: String - Password or Boolean False otherwise"""
<|body_0|>
def save(self, commit=True):
"""Save... | stack_v2_sparse_classes_10k_train_006819 | 4,010 | no_license | [
{
"docstring": "Checks that both of the passwords match :return: String - Password or Boolean False otherwise",
"name": "clean_password",
"signature": "def clean_password(self)"
},
{
"docstring": "Save data, mostly the password, in a hashed form :param commit: Whether or not to commit the change... | 2 | stack_v2_sparse_classes_30k_train_003151 | Implement the Python class `UserCreationForm` described below.
Class description:
A form for creating new users with a password confirmation field.
Method signatures and docstrings:
- def clean_password(self): Checks that both of the passwords match :return: String - Password or Boolean False otherwise
- def save(sel... | Implement the Python class `UserCreationForm` described below.
Class description:
A form for creating new users with a password confirmation field.
Method signatures and docstrings:
- def clean_password(self): Checks that both of the passwords match :return: String - Password or Boolean False otherwise
- def save(sel... | 167a39307fe3d978d3eee4b3fcd53c27143f5924 | <|skeleton|>
class UserCreationForm:
"""A form for creating new users with a password confirmation field."""
def clean_password(self):
"""Checks that both of the passwords match :return: String - Password or Boolean False otherwise"""
<|body_0|>
def save(self, commit=True):
"""Save... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserCreationForm:
"""A form for creating new users with a password confirmation field."""
def clean_password(self):
"""Checks that both of the passwords match :return: String - Password or Boolean False otherwise"""
password1 = self.cleaned_data.get('password1')
password2 = self.c... | the_stack_v2_python_sparse | summit/libs/auth/admin.py | NAU-CCL/cpcesu-summit | train | 0 |
3823ba7e4e5dd3cebbb0c86c4be674cfdbd4cc70 | [
"if location is None:\n self.location = [0, 0]\nelse:\n self.location = double_gis_util.validate_location(location)\nself.radius = int(radius)\nself.popup = popup.replace(\"'\", '^') if isinstance(popup, str) else popup\nself.tooltip = tooltip.replace(\"'\", '^') if isinstance(tooltip, str) else tooltip\nself... | <|body_start_0|>
if location is None:
self.location = [0, 0]
else:
self.location = double_gis_util.validate_location(location)
self.radius = int(radius)
self.popup = popup.replace("'", '^') if isinstance(popup, str) else popup
self.tooltip = tooltip.replac... | Circle marker. | iq2GISCircleMarker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class iq2GISCircleMarker:
"""Circle marker."""
def __init__(self, location, radius=10, popup=None, tooltip=None, color='blue', fill=True, fill_color='blue', **kwargs):
"""Constructor. :param location: Marker geolocation. :param radius: Marker circle radius. :param color: Circle color. :par... | stack_v2_sparse_classes_10k_train_006820 | 2,846 | no_license | [
{
"docstring": "Constructor. :param location: Marker geolocation. :param radius: Marker circle radius. :param color: Circle color. :param fill: Fill the inner area of the circle? :param fill_color: The fill color of the circle. :param popup: Marker pop-up text. A tooltip appears by clicking on the marker. :para... | 3 | stack_v2_sparse_classes_30k_train_004129 | Implement the Python class `iq2GISCircleMarker` described below.
Class description:
Circle marker.
Method signatures and docstrings:
- def __init__(self, location, radius=10, popup=None, tooltip=None, color='blue', fill=True, fill_color='blue', **kwargs): Constructor. :param location: Marker geolocation. :param radiu... | Implement the Python class `iq2GISCircleMarker` described below.
Class description:
Circle marker.
Method signatures and docstrings:
- def __init__(self, location, radius=10, popup=None, tooltip=None, color='blue', fill=True, fill_color='blue', **kwargs): Constructor. :param location: Marker geolocation. :param radiu... | 7550e242746cb2fb1219474463f8db21f8e3e114 | <|skeleton|>
class iq2GISCircleMarker:
"""Circle marker."""
def __init__(self, location, radius=10, popup=None, tooltip=None, color='blue', fill=True, fill_color='blue', **kwargs):
"""Constructor. :param location: Marker geolocation. :param radius: Marker circle radius. :param color: Circle color. :par... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class iq2GISCircleMarker:
"""Circle marker."""
def __init__(self, location, radius=10, popup=None, tooltip=None, color='blue', fill=True, fill_color='blue', **kwargs):
"""Constructor. :param location: Marker geolocation. :param radius: Marker circle radius. :param color: Circle color. :param fill: Fill... | the_stack_v2_python_sparse | iq/components/doublegis_indicator_manager/circle_marker.py | XHermitOne/iq_framework | train | 1 |
6b3264ea2fa1f419a4a2667f54cd1af1a5707c20 | [
"current_app.logger.debug('Create chat message from DTO')\nnew_message = cls()\nnew_message.project_id = dto.project_id\nnew_message.user_id = dto.user_id\nallowed_tags = ['a', 'b', 'blockquote', 'br', 'code', 'em', 'h1', 'h2', 'h3', 'img', 'i', 'li', 'ol', 'p', 'pre', 'strong', 'ul']\nallowed_atrributes = {'a': ['... | <|body_start_0|>
current_app.logger.debug('Create chat message from DTO')
new_message = cls()
new_message.project_id = dto.project_id
new_message.user_id = dto.user_id
allowed_tags = ['a', 'b', 'blockquote', 'br', 'code', 'em', 'h1', 'h2', 'h3', 'img', 'i', 'li', 'ol', 'p', 'pre'... | Contains all project info localized into supported languages | ProjectChat | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectChat:
"""Contains all project info localized into supported languages"""
def create_from_dto(cls, dto: ChatMessageDTO):
"""Creates a new ProjectInfo class from dto, used from project edit"""
<|body_0|>
def get_messages(project_id: int, page: int, per_page: int=20)... | stack_v2_sparse_classes_10k_train_006821 | 2,959 | permissive | [
{
"docstring": "Creates a new ProjectInfo class from dto, used from project edit",
"name": "create_from_dto",
"signature": "def create_from_dto(cls, dto: ChatMessageDTO)"
},
{
"docstring": "Get all messages on the project",
"name": "get_messages",
"signature": "def get_messages(project_i... | 2 | stack_v2_sparse_classes_30k_train_002636 | Implement the Python class `ProjectChat` described below.
Class description:
Contains all project info localized into supported languages
Method signatures and docstrings:
- def create_from_dto(cls, dto: ChatMessageDTO): Creates a new ProjectInfo class from dto, used from project edit
- def get_messages(project_id: i... | Implement the Python class `ProjectChat` described below.
Class description:
Contains all project info localized into supported languages
Method signatures and docstrings:
- def create_from_dto(cls, dto: ChatMessageDTO): Creates a new ProjectInfo class from dto, used from project edit
- def get_messages(project_id: i... | 45bf3937c74902226096aee5b49e7abea62df524 | <|skeleton|>
class ProjectChat:
"""Contains all project info localized into supported languages"""
def create_from_dto(cls, dto: ChatMessageDTO):
"""Creates a new ProjectInfo class from dto, used from project edit"""
<|body_0|>
def get_messages(project_id: int, page: int, per_page: int=20)... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProjectChat:
"""Contains all project info localized into supported languages"""
def create_from_dto(cls, dto: ChatMessageDTO):
"""Creates a new ProjectInfo class from dto, used from project edit"""
current_app.logger.debug('Create chat message from DTO')
new_message = cls()
... | the_stack_v2_python_sparse | backend/models/postgis/project_chat.py | hotosm/tasking-manager | train | 526 |
8cf24450fcb25e40dcbb6a833c45cccde901a6ee | [
"if not s or k == 0:\n return 0\nmaxheap = []\ninwindow = {}\nj, maxlen = (0, 1)\nfor i in xrange(len(s)):\n ch = s[i]\n if len(inwindow) == k and ch not in inwindow:\n idx, first = heapq.heappop(maxheap)\n del inwindow[first]\n j = idx + 1\n if ch in inwindow:\n for idx in x... | <|body_start_0|>
if not s or k == 0:
return 0
maxheap = []
inwindow = {}
j, maxlen = (0, 1)
for i in xrange(len(s)):
ch = s[i]
if len(inwindow) == k and ch not in inwindow:
idx, first = heapq.heappop(maxheap)
del... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def followup(self, s, k):
"""the question follow up is data char, only can read one char"""
<|body_0|>
def lengthOfLongestSubstringKDistinct(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_006822 | 1,759 | permissive | [
{
"docstring": "the question follow up is data char, only can read one char",
"name": "followup",
"signature": "def followup(self, s, k)"
},
{
"docstring": ":type s: str :type k: int :rtype: int",
"name": "lengthOfLongestSubstringKDistinct",
"signature": "def lengthOfLongestSubstringKDis... | 2 | stack_v2_sparse_classes_30k_train_004965 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def followup(self, s, k): the question follow up is data char, only can read one char
- def lengthOfLongestSubstringKDistinct(self, s, k): :type s: str :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def followup(self, s, k): the question follow up is data char, only can read one char
- def lengthOfLongestSubstringKDistinct(self, s, k): :type s: str :type k: int :rtype: int
... | 86f1cb98de801f58c39d9a48ce9de12df7303d20 | <|skeleton|>
class Solution:
def followup(self, s, k):
"""the question follow up is data char, only can read one char"""
<|body_0|>
def lengthOfLongestSubstringKDistinct(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def followup(self, s, k):
"""the question follow up is data char, only can read one char"""
if not s or k == 0:
return 0
maxheap = []
inwindow = {}
j, maxlen = (0, 1)
for i in xrange(len(s)):
ch = s[i]
if len(inwindo... | the_stack_v2_python_sparse | 340-Longest-Substring-with-At-Most-K-Distinct-Characters/solution.py | Tanych/CodeTracking | train | 0 | |
79bbafce1f0cc501924a33fd47d599bfc9859d0f | [
"self.id = id\nself.server_relativeurl = server_relativeurl\nself.title = title\nself.url = url\nself.webid = webid",
"if dictionary is None:\n return None\nid = dictionary.get('id')\nserver_relativeurl = dictionary.get('serverRelativeurl')\ntitle = dictionary.get('title')\nurl = dictionary.get('url')\nwebid =... | <|body_start_0|>
self.id = id
self.server_relativeurl = server_relativeurl
self.title = title
self.url = url
self.webid = webid
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
id = dictionary.get('id')
server_relativeurl = d... | Implementation of the 'SiteIdentity' model. O365 Sharepoint online Site Identity. These may be obtained by Graph/REST or PnP cmdlets. All fields are case insensitive. Attributes: id (string): Unique guid for the site in SPO. This is a unqiue identifier that can be used to compare sites. server_relativeurl (string): Opt... | SiteIdentity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SiteIdentity:
"""Implementation of the 'SiteIdentity' model. O365 Sharepoint online Site Identity. These may be obtained by Graph/REST or PnP cmdlets. All fields are case insensitive. Attributes: id (string): Unique guid for the site in SPO. This is a unqiue identifier that can be used to compare... | stack_v2_sparse_classes_10k_train_006823 | 2,543 | permissive | [
{
"docstring": "Constructor for the SiteIdentity class",
"name": "__init__",
"signature": "def __init__(self, id=None, server_relativeurl=None, title=None, url=None, webid=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary re... | 2 | null | Implement the Python class `SiteIdentity` described below.
Class description:
Implementation of the 'SiteIdentity' model. O365 Sharepoint online Site Identity. These may be obtained by Graph/REST or PnP cmdlets. All fields are case insensitive. Attributes: id (string): Unique guid for the site in SPO. This is a unqiue... | Implement the Python class `SiteIdentity` described below.
Class description:
Implementation of the 'SiteIdentity' model. O365 Sharepoint online Site Identity. These may be obtained by Graph/REST or PnP cmdlets. All fields are case insensitive. Attributes: id (string): Unique guid for the site in SPO. This is a unqiue... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class SiteIdentity:
"""Implementation of the 'SiteIdentity' model. O365 Sharepoint online Site Identity. These may be obtained by Graph/REST or PnP cmdlets. All fields are case insensitive. Attributes: id (string): Unique guid for the site in SPO. This is a unqiue identifier that can be used to compare... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SiteIdentity:
"""Implementation of the 'SiteIdentity' model. O365 Sharepoint online Site Identity. These may be obtained by Graph/REST or PnP cmdlets. All fields are case insensitive. Attributes: id (string): Unique guid for the site in SPO. This is a unqiue identifier that can be used to compare sites. serve... | the_stack_v2_python_sparse | cohesity_management_sdk/models/site_identity.py | cohesity/management-sdk-python | train | 24 |
fa3883ec7c3de807cd8583290964219c2cde80ed | [
"np.random.seed(cfg.RNG_SEED)\ntorch.manual_seed(cfg.RNG_SEED)\ntorch.backends.cudnn.deterministic = False\ntorch.backends.cudnn.benchmark = True\nif gpu_id is None:\n self.device = get_device(get_local_rank())\nelse:\n self.device = torch.device(f'cuda:{gpu_id}')\nself.model = build_recognizer(cfg, device=se... | <|body_start_0|>
np.random.seed(cfg.RNG_SEED)
torch.manual_seed(cfg.RNG_SEED)
torch.backends.cudnn.deterministic = False
torch.backends.cudnn.benchmark = True
if gpu_id is None:
self.device = get_device(get_local_rank())
else:
self.device = torch.d... | Action Predictor for action recognition. | Predictor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Predictor:
"""Action Predictor for action recognition."""
def __init__(self, cfg, gpu_id=None):
"""Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py."""
<|body_0|>
def __call__(self, task):
"""Returns the prediction results for the... | stack_v2_sparse_classes_10k_train_006824 | 2,292 | permissive | [
{
"docstring": "Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py.",
"name": "__init__",
"signature": "def __init__(self, cfg, gpu_id=None)"
},
{
"docstring": "Returns the prediction results for the current task. Args: task (TaskInfo object): task object that cont... | 2 | stack_v2_sparse_classes_30k_train_005386 | Implement the Python class `Predictor` described below.
Class description:
Action Predictor for action recognition.
Method signatures and docstrings:
- def __init__(self, cfg, gpu_id=None): Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py.
- def __call__(self, task): Returns the predi... | Implement the Python class `Predictor` described below.
Class description:
Action Predictor for action recognition.
Method signatures and docstrings:
- def __init__(self, cfg, gpu_id=None): Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py.
- def __call__(self, task): Returns the predi... | ec6ad668d20f477df44eab7035e2553d95a835f3 | <|skeleton|>
class Predictor:
"""Action Predictor for action recognition."""
def __init__(self, cfg, gpu_id=None):
"""Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py."""
<|body_0|>
def __call__(self, task):
"""Returns the prediction results for the... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Predictor:
"""Action Predictor for action recognition."""
def __init__(self, cfg, gpu_id=None):
"""Args: cfg (CfgNode): configs. Details can be found in slowfast/config/defaults.py."""
np.random.seed(cfg.RNG_SEED)
torch.manual_seed(cfg.RNG_SEED)
torch.backends.cudnn.determ... | the_stack_v2_python_sparse | demo/slowfast/visualization/predictor/predictor.py | ttykelly/TSN | train | 0 |
6de916fb17caf7136b22033461b2ececfa2bfcdf | [
"if key == 'is_verified' and value is False and (self.is_primary is True):\n raise PrimaryElementViolation(\"Can't remove verified status of primary element\")\nsuper().__setattr__(key, value)",
"data = super()._from_dict_transform(data)\nif 'primary' in data:\n data['is_primary'] = data.pop('primary')\nret... | <|body_start_0|>
if key == 'is_verified' and value is False and (self.is_primary is True):
raise PrimaryElementViolation("Can't remove verified status of primary element")
super().__setattr__(key, value)
<|end_body_0|>
<|body_start_1|>
data = super()._from_dict_transform(data)
... | Elements that can be either primary or not. | PrimaryElement | [
"BSD-2-Clause-Views"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrimaryElement:
"""Elements that can be either primary or not."""
def __setattr__(self, key: str, value: Any):
"""raise PrimaryElementViolation when trying to set a primary element as unverified"""
<|body_0|>
def _from_dict_transform(cls: Type[TPrimaryElementSubclass], d... | stack_v2_sparse_classes_10k_train_006825 | 18,109 | permissive | [
{
"docstring": "raise PrimaryElementViolation when trying to set a primary element as unverified",
"name": "__setattr__",
"signature": "def __setattr__(self, key: str, value: Any)"
},
{
"docstring": "Transform data received in eduid format into pythonic format.",
"name": "_from_dict_transfor... | 3 | stack_v2_sparse_classes_30k_train_003173 | Implement the Python class `PrimaryElement` described below.
Class description:
Elements that can be either primary or not.
Method signatures and docstrings:
- def __setattr__(self, key: str, value: Any): raise PrimaryElementViolation when trying to set a primary element as unverified
- def _from_dict_transform(cls: ... | Implement the Python class `PrimaryElement` described below.
Class description:
Elements that can be either primary or not.
Method signatures and docstrings:
- def __setattr__(self, key: str, value: Any): raise PrimaryElementViolation when trying to set a primary element as unverified
- def _from_dict_transform(cls: ... | 5970880caf0b0e2bdee6c23869ef287acc87af2a | <|skeleton|>
class PrimaryElement:
"""Elements that can be either primary or not."""
def __setattr__(self, key: str, value: Any):
"""raise PrimaryElementViolation when trying to set a primary element as unverified"""
<|body_0|>
def _from_dict_transform(cls: Type[TPrimaryElementSubclass], d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrimaryElement:
"""Elements that can be either primary or not."""
def __setattr__(self, key: str, value: Any):
"""raise PrimaryElementViolation when trying to set a primary element as unverified"""
if key == 'is_verified' and value is False and (self.is_primary is True):
raise... | the_stack_v2_python_sparse | src/eduid_userdb/element.py | SUNET/eduid-userdb | train | 0 |
c34a9956a5c34457a5a84eb44044219751221ea4 | [
"graph_def = sess.graph_def\ntoco_flags = toco_flags_pb2.TocoFlags()\ntoco_flags.input_format = toco_flags_pb2.TENSORFLOW_GRAPHDEF\ntoco_flags.output_format = toco_flags_pb2.TFLITE\ntoco_flags.inference_input_type = types_pb2.FLOAT\ntoco_flags.inference_type = types_pb2.FLOAT\ntoco_flags.allow_custom_ops = True\nmo... | <|body_start_0|>
graph_def = sess.graph_def
toco_flags = toco_flags_pb2.TocoFlags()
toco_flags.input_format = toco_flags_pb2.TENSORFLOW_GRAPHDEF
toco_flags.output_format = toco_flags_pb2.TFLITE
toco_flags.inference_input_type = types_pb2.FLOAT
toco_flags.inference_type = ... | TocoFromProtosTest | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TocoFromProtosTest:
def _run(self, sess, in_tensor, out_tensor, should_succeed):
"""Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow session containing graph. in_tensor: TensorFlow tensor to use as input. out_tensor: TensorFlow tensor to use as o... | stack_v2_sparse_classes_10k_train_006826 | 3,767 | permissive | [
{
"docstring": "Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow session containing graph. in_tensor: TensorFlow tensor to use as input. out_tensor: TensorFlow tensor to use as output. should_succeed: Whether this is a valid conversion.",
"name": "_run",
"signat... | 2 | null | Implement the Python class `TocoFromProtosTest` described below.
Class description:
Implement the TocoFromProtosTest class.
Method signatures and docstrings:
- def _run(self, sess, in_tensor, out_tensor, should_succeed): Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow sessio... | Implement the Python class `TocoFromProtosTest` described below.
Class description:
Implement the TocoFromProtosTest class.
Method signatures and docstrings:
- def _run(self, sess, in_tensor, out_tensor, should_succeed): Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow sessio... | a7f3934a67900720af3d3b15389551483bee50b8 | <|skeleton|>
class TocoFromProtosTest:
def _run(self, sess, in_tensor, out_tensor, should_succeed):
"""Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow session containing graph. in_tensor: TensorFlow tensor to use as input. out_tensor: TensorFlow tensor to use as o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TocoFromProtosTest:
def _run(self, sess, in_tensor, out_tensor, should_succeed):
"""Use toco binary to check conversion from graphdef to tflite. Args: sess: Active TensorFlow session containing graph. in_tensor: TensorFlow tensor to use as input. out_tensor: TensorFlow tensor to use as output. should_... | the_stack_v2_python_sparse | tensorflow/lite/toco/python/toco_from_protos_test.py | tensorflow/tensorflow | train | 208,740 | |
9f114b834ef9b9bc326e68b4d85caa4296b60cdb | [
"dims = (wrapper.num_people, wrapper.num_people, wrapper.num_samples)\nsuper().__init__(wrapper, dims)\nself.embedder = embedder\nself.transformer = transformer",
"style_pid, source_pid, source_sid = coords_from_index(index, self.dims)\nsource_audio = self.wrapper.mel_from_ids(source_pid, source_sid)[None, :]\nst... | <|body_start_0|>
dims = (wrapper.num_people, wrapper.num_people, wrapper.num_samples)
super().__init__(wrapper, dims)
self.embedder = embedder
self.transformer = transformer
<|end_body_0|>
<|body_start_1|>
style_pid, source_pid, source_sid = coords_from_index(index, self.dims)
... | A class for training the isvoice discriminator with negative (generated) examples | Isvoice_Dataset_Fake | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Isvoice_Dataset_Fake:
"""A class for training the isvoice discriminator with negative (generated) examples"""
def __init__(self, wrapper, embedder, transformer):
"""There are (people * samples) original "real" files, and (people) possible transformations of each of files."""
... | stack_v2_sparse_classes_10k_train_006827 | 12,382 | no_license | [
{
"docstring": "There are (people * samples) original \"real\" files, and (people) possible transformations of each of files.",
"name": "__init__",
"signature": "def __init__(self, wrapper, embedder, transformer)"
},
{
"docstring": "# TODO Work on some sort of caching if there are speed/memory i... | 2 | stack_v2_sparse_classes_30k_train_001051 | Implement the Python class `Isvoice_Dataset_Fake` described below.
Class description:
A class for training the isvoice discriminator with negative (generated) examples
Method signatures and docstrings:
- def __init__(self, wrapper, embedder, transformer): There are (people * samples) original "real" files, and (peopl... | Implement the Python class `Isvoice_Dataset_Fake` described below.
Class description:
A class for training the isvoice discriminator with negative (generated) examples
Method signatures and docstrings:
- def __init__(self, wrapper, embedder, transformer): There are (people * samples) original "real" files, and (peopl... | ceb1b9580f515df744f7c7bfb94e6a2ae6a18c87 | <|skeleton|>
class Isvoice_Dataset_Fake:
"""A class for training the isvoice discriminator with negative (generated) examples"""
def __init__(self, wrapper, embedder, transformer):
"""There are (people * samples) original "real" files, and (people) possible transformations of each of files."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Isvoice_Dataset_Fake:
"""A class for training the isvoice discriminator with negative (generated) examples"""
def __init__(self, wrapper, embedder, transformer):
"""There are (people * samples) original "real" files, and (people) possible transformations of each of files."""
dims = (wrapp... | the_stack_v2_python_sparse | vocal-mimicry/dataset.py | anlsh/cs4803 | train | 0 |
0950c0a24497879c17bc72802b627d0fffe2d15e | [
"if n < 2:\n return 1\ndp = [0] * (n + 1)\ndp[0], dp[1] = (1, 1)\nfor i in range(2, n + 1):\n dp[i] = dp[i - 1] + dp[i - 2]\nreturn dp[n]",
"if n < 2:\n return n\na, b, sum = (1, 1, 0)\nfor _ in range(2, n + 1):\n sum = a + b\n a = b\n b = sum\nreturn sum"
] | <|body_start_0|>
if n < 2:
return 1
dp = [0] * (n + 1)
dp[0], dp[1] = (1, 1)
for i in range(2, n + 1):
dp[i] = dp[i - 1] + dp[i - 2]
return dp[n]
<|end_body_0|>
<|body_start_1|>
if n < 2:
return n
a, b, sum = (1, 1, 0)
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs(self, n: int) -> int:
"""递归方程：f(n) = f(n-1) + f(n-2)，n >= 2"""
<|body_0|>
def climbStairs1(self, n: int) -> int:
"""空间复杂度：O(1)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n < 2:
return 1
dp = [0] ... | stack_v2_sparse_classes_10k_train_006828 | 1,471 | permissive | [
{
"docstring": "递归方程：f(n) = f(n-1) + f(n-2)，n >= 2",
"name": "climbStairs",
"signature": "def climbStairs(self, n: int) -> int"
},
{
"docstring": "空间复杂度：O(1)",
"name": "climbStairs1",
"signature": "def climbStairs1(self, n: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n: int) -> int: 递归方程：f(n) = f(n-1) + f(n-2)，n >= 2
- def climbStairs1(self, n: int) -> int: 空间复杂度：O(1) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n: int) -> int: 递归方程：f(n) = f(n-1) + f(n-2)，n >= 2
- def climbStairs1(self, n: int) -> int: 空间复杂度：O(1)
<|skeleton|>
class Solution:
def climbStairs(se... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def climbStairs(self, n: int) -> int:
"""递归方程：f(n) = f(n-1) + f(n-2)，n >= 2"""
<|body_0|>
def climbStairs1(self, n: int) -> int:
"""空间复杂度：O(1)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs(self, n: int) -> int:
"""递归方程：f(n) = f(n-1) + f(n-2)，n >= 2"""
if n < 2:
return 1
dp = [0] * (n + 1)
dp[0], dp[1] = (1, 1)
for i in range(2, n + 1):
dp[i] = dp[i - 1] + dp[i - 2]
return dp[n]
def climbStairs... | the_stack_v2_python_sparse | 70-climbing-stairs.py | yuenliou/leetcode | train | 0 | |
580714254fe1d9f3d61703dd554aa4920926446f | [
"self.text_field_key = text_field_key\nself.data = data\nself.cv = None\nself.ngrams_df = pd.DataFrame(['blank'], columns=['Index'])\nself.filtered_ngrams_df = pd.DataFrame(['blank'], columns=['Index'])\nself.ngram_word = None\nself.word_frequency_matrix = pd.DataFrame(['blank'], columns=['Index'])",
"if preproce... | <|body_start_0|>
self.text_field_key = text_field_key
self.data = data
self.cv = None
self.ngrams_df = pd.DataFrame(['blank'], columns=['Index'])
self.filtered_ngrams_df = pd.DataFrame(['blank'], columns=['Index'])
self.ngram_word = None
self.word_frequency_matrix... | The parent class for managing n-gram analysis | NGrams | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NGrams:
"""The parent class for managing n-gram analysis"""
def __init__(self, data, text_field_key='Snippet'):
""":param data: Pandas dataframe containing a text Snippet field and other metadata :param text_field_key: The name of the text field (by default Snippet)"""
<|body... | stack_v2_sparse_classes_10k_train_006829 | 4,267 | permissive | [
{
"docstring": ":param data: Pandas dataframe containing a text Snippet field and other metadata :param text_field_key: The name of the text field (by default Snippet)",
"name": "__init__",
"signature": "def __init__(self, data, text_field_key='Snippet')"
},
{
"docstring": "The primary function ... | 3 | stack_v2_sparse_classes_30k_train_005984 | Implement the Python class `NGrams` described below.
Class description:
The parent class for managing n-gram analysis
Method signatures and docstrings:
- def __init__(self, data, text_field_key='Snippet'): :param data: Pandas dataframe containing a text Snippet field and other metadata :param text_field_key: The name... | Implement the Python class `NGrams` described below.
Class description:
The parent class for managing n-gram analysis
Method signatures and docstrings:
- def __init__(self, data, text_field_key='Snippet'): :param data: Pandas dataframe containing a text Snippet field and other metadata :param text_field_key: The name... | b810c6e1a93a2ecaa9d6351449239d0a1833f971 | <|skeleton|>
class NGrams:
"""The parent class for managing n-gram analysis"""
def __init__(self, data, text_field_key='Snippet'):
""":param data: Pandas dataframe containing a text Snippet field and other metadata :param text_field_key: The name of the text field (by default Snippet)"""
<|body... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NGrams:
"""The parent class for managing n-gram analysis"""
def __init__(self, data, text_field_key='Snippet'):
""":param data: Pandas dataframe containing a text Snippet field and other metadata :param text_field_key: The name of the text field (by default Snippet)"""
self.text_field_key... | the_stack_v2_python_sparse | usherwood_ds/nlp/n_grams/main.py | Usherwood/usherwood_ds | train | 2 |
5aba69e32bace2512f6077f56d4679e82f7c1586 | [
"self.mailbox_vec = mailbox_vec\nself.pst_params = pst_params\nself.skip_mbx_permit_for_pst = skip_mbx_permit_for_pst\nself.target_folder_path = target_folder_path\nself.target_mailbox = target_mailbox",
"if dictionary is None:\n return None\nmailbox_vec = None\nif dictionary.get('mailboxVec') != None:\n ma... | <|body_start_0|>
self.mailbox_vec = mailbox_vec
self.pst_params = pst_params
self.skip_mbx_permit_for_pst = skip_mbx_permit_for_pst
self.target_folder_path = target_folder_path
self.target_mailbox = target_mailbox
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
... | Implementation of the 'RestoreOutlookParams' model. TODO: type description here. Attributes: mailbox_vec (list of RestoreOutlookParams_Mailbox): In a RestoreJob , user will provide the list of mailboxes to be restored. Provision is there for restoring full AND partial mailbox recovery. pst_params (EwsToPstConversionPar... | RestoreOutlookParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreOutlookParams:
"""Implementation of the 'RestoreOutlookParams' model. TODO: type description here. Attributes: mailbox_vec (list of RestoreOutlookParams_Mailbox): In a RestoreJob , user will provide the list of mailboxes to be restored. Provision is there for restoring full AND partial mai... | stack_v2_sparse_classes_10k_train_006830 | 4,261 | permissive | [
{
"docstring": "Constructor for the RestoreOutlookParams class",
"name": "__init__",
"signature": "def __init__(self, mailbox_vec=None, pst_params=None, skip_mbx_permit_for_pst=None, target_folder_path=None, target_mailbox=None)"
},
{
"docstring": "Creates an instance of this model from a dictio... | 2 | stack_v2_sparse_classes_30k_train_001422 | Implement the Python class `RestoreOutlookParams` described below.
Class description:
Implementation of the 'RestoreOutlookParams' model. TODO: type description here. Attributes: mailbox_vec (list of RestoreOutlookParams_Mailbox): In a RestoreJob , user will provide the list of mailboxes to be restored. Provision is t... | Implement the Python class `RestoreOutlookParams` described below.
Class description:
Implementation of the 'RestoreOutlookParams' model. TODO: type description here. Attributes: mailbox_vec (list of RestoreOutlookParams_Mailbox): In a RestoreJob , user will provide the list of mailboxes to be restored. Provision is t... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreOutlookParams:
"""Implementation of the 'RestoreOutlookParams' model. TODO: type description here. Attributes: mailbox_vec (list of RestoreOutlookParams_Mailbox): In a RestoreJob , user will provide the list of mailboxes to be restored. Provision is there for restoring full AND partial mai... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RestoreOutlookParams:
"""Implementation of the 'RestoreOutlookParams' model. TODO: type description here. Attributes: mailbox_vec (list of RestoreOutlookParams_Mailbox): In a RestoreJob , user will provide the list of mailboxes to be restored. Provision is there for restoring full AND partial mailbox recovery... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_outlook_params.py | cohesity/management-sdk-python | train | 24 |
e7c06cc84f7c385ed0ad2e842cb762455e0c8214 | [
"res = ''\nfor i in range(len(strs)):\n new_str = ','.join([str(ord(c)) for c in strs[i]])\n res = res + ':' + new_str\nreturn res",
"if len(s) == 0:\n return []\nif s == ':':\n return ['']\nenc_strs = s.split(':')\nres = []\nfor i in range(1, len(enc_strs)):\n if len(enc_strs[i]) == 0:\n re... | <|body_start_0|>
res = ''
for i in range(len(strs)):
new_str = ','.join([str(ord(c)) for c in strs[i]])
res = res + ':' + new_str
return res
<|end_body_0|>
<|body_start_1|>
if len(s) == 0:
return []
if s == ':':
return ['']
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = ''
... | stack_v2_sparse_classes_10k_train_006831 | 1,491 | no_license | [
{
"docstring": "Encodes a list of strings to a single string.",
"name": "encode",
"signature": "def encode(self, strs: [str]) -> str"
},
{
"docstring": "Decodes a single string to a list of strings.",
"name": "decode",
"signature": "def decode(self, s: str) -> [str]"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings.
<|skeleton|>
cla... | 9cef9b11e16412449a46312d766f7eafcf162724 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
res = ''
for i in range(len(strs)):
new_str = ','.join([str(ord(c)) for c in strs[i]])
res = res + ':' + new_str
return res
def decode(self, s: str) -> ... | the_stack_v2_python_sparse | 271-Encode-and-Decode-Strings.py | zuqqhi2/my-leetcode-answers | train | 0 | |
45a2b73b5b66b0059ee6dcbfeac393737c946a39 | [
"super().__init__(pos_enc_class)\nself.out = nn.Sequential(Linear(idim, odim), LayerNorm(odim, epsilon=1e-12), nn.Dropout(dropout_rate), nn.ReLU())\nself.right_context = 0\nself.subsampling_rate = 1",
"x = self.out(x)\nx, pos_emb = self.pos_enc(x, offset)\nreturn (x, pos_emb, x_mask)"
] | <|body_start_0|>
super().__init__(pos_enc_class)
self.out = nn.Sequential(Linear(idim, odim), LayerNorm(odim, epsilon=1e-12), nn.Dropout(dropout_rate), nn.ReLU())
self.right_context = 0
self.subsampling_rate = 1
<|end_body_0|>
<|body_start_1|>
x = self.out(x)
x, pos_emb ... | Linear transform the input without subsampling. | LinearNoSubsampling | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearNoSubsampling:
"""Linear transform the input without subsampling."""
def __init__(self, idim: int, odim: int, dropout_rate: float, pos_enc_class: nn.Layer=PositionalEncoding):
"""Construct an linear object. Args: idim (int): Input dimension. odim (int): Output dimension. dropou... | stack_v2_sparse_classes_10k_train_006832 | 11,942 | permissive | [
{
"docstring": "Construct an linear object. Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc_class (PositionalEncoding): position encoding class",
"name": "__init__",
"signature": "def __init__(self, idim: int, odim: int, dropout_rate: float, p... | 2 | stack_v2_sparse_classes_30k_train_005667 | Implement the Python class `LinearNoSubsampling` described below.
Class description:
Linear transform the input without subsampling.
Method signatures and docstrings:
- def __init__(self, idim: int, odim: int, dropout_rate: float, pos_enc_class: nn.Layer=PositionalEncoding): Construct an linear object. Args: idim (in... | Implement the Python class `LinearNoSubsampling` described below.
Class description:
Linear transform the input without subsampling.
Method signatures and docstrings:
- def __init__(self, idim: int, odim: int, dropout_rate: float, pos_enc_class: nn.Layer=PositionalEncoding): Construct an linear object. Args: idim (in... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class LinearNoSubsampling:
"""Linear transform the input without subsampling."""
def __init__(self, idim: int, odim: int, dropout_rate: float, pos_enc_class: nn.Layer=PositionalEncoding):
"""Construct an linear object. Args: idim (int): Input dimension. odim (int): Output dimension. dropou... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LinearNoSubsampling:
"""Linear transform the input without subsampling."""
def __init__(self, idim: int, odim: int, dropout_rate: float, pos_enc_class: nn.Layer=PositionalEncoding):
"""Construct an linear object. Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float... | the_stack_v2_python_sparse | paddlespeech/s2t/modules/subsampling.py | anniyanvr/DeepSpeech-1 | train | 0 |
62e60d22a69fdf46dd89ae54de6d03d550b1e42e | [
"ret = []\n\ndef helper(left_nums, k):\n if k <= 1:\n return [[num] for num in left_nums]\n left_ret = []\n for i in range(len(left_nums)):\n now_num = left_nums[i]\n nums_backup = [num for num in left_nums]\n left_nums.remove(now_num)\n for nums in helper(left_nums, k - ... | <|body_start_0|>
ret = []
def helper(left_nums, k):
if k <= 1:
return [[num] for num in left_nums]
left_ret = []
for i in range(len(left_nums)):
now_num = left_nums[i]
nums_backup = [num for num in left_nums]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combine1(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
<|body_0|>
def combine(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = []
de... | stack_v2_sparse_classes_10k_train_006833 | 1,369 | no_license | [
{
"docstring": ":type n: int :type k: int :rtype: List[List[int]]",
"name": "combine1",
"signature": "def combine1(self, n, k)"
},
{
"docstring": ":type n: int :type k: int :rtype: List[List[int]]",
"name": "combine",
"signature": "def combine(self, n, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001451 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combine1(self, n, k): :type n: int :type k: int :rtype: List[List[int]]
- def combine(self, n, k): :type n: int :type k: int :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combine1(self, n, k): :type n: int :type k: int :rtype: List[List[int]]
- def combine(self, n, k): :type n: int :type k: int :rtype: List[List[int]]
<|skeleton|>
class Solut... | 22f208400cd7e13fcf2ebf189e61ccad7e22b098 | <|skeleton|>
class Solution:
def combine1(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
<|body_0|>
def combine(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def combine1(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
ret = []
def helper(left_nums, k):
if k <= 1:
return [[num] for num in left_nums]
left_ret = []
for i in range(len(left_nums)):
... | the_stack_v2_python_sparse | previously_completed/77-Combinations.py | learnerjiahao/leetcode-solve | train | 0 | |
8d47c43dde1380a19c72a1a2863d1d9f05b255d1 | [
"A = sum(machines)\nl = len(machines)\nif A % l != 0:\n return -1\nneed = A // l\ntoLeft = 0\nres = 0\nfor i in range(len(machines)):\n toRight = machines[i] - need - toLeft\n res = max(res, toLeft, toRight, toLeft + toRight)\n toLeft = -toRight\nreturn res",
"s = 0\nl = len(machines)\nfor i in machin... | <|body_start_0|>
A = sum(machines)
l = len(machines)
if A % l != 0:
return -1
need = A // l
toLeft = 0
res = 0
for i in range(len(machines)):
toRight = machines[i] - need - toLeft
res = max(res, toLeft, toRight, toLeft + toRight... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMinMoves(self, machines):
""":type machines: List[int] :rtype: int 51ms"""
<|body_0|>
def findMinMoves_1(self, machines):
""":type machines: List[int] :rtype: int 47ms"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
A = sum(machine... | stack_v2_sparse_classes_10k_train_006834 | 2,247 | no_license | [
{
"docstring": ":type machines: List[int] :rtype: int 51ms",
"name": "findMinMoves",
"signature": "def findMinMoves(self, machines)"
},
{
"docstring": ":type machines: List[int] :rtype: int 47ms",
"name": "findMinMoves_1",
"signature": "def findMinMoves_1(self, machines)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006398 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMinMoves(self, machines): :type machines: List[int] :rtype: int 51ms
- def findMinMoves_1(self, machines): :type machines: List[int] :rtype: int 47ms | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMinMoves(self, machines): :type machines: List[int] :rtype: int 51ms
- def findMinMoves_1(self, machines): :type machines: List[int] :rtype: int 47ms
<|skeleton|>
class ... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def findMinMoves(self, machines):
""":type machines: List[int] :rtype: int 51ms"""
<|body_0|>
def findMinMoves_1(self, machines):
""":type machines: List[int] :rtype: int 47ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findMinMoves(self, machines):
""":type machines: List[int] :rtype: int 51ms"""
A = sum(machines)
l = len(machines)
if A % l != 0:
return -1
need = A // l
toLeft = 0
res = 0
for i in range(len(machines)):
toRi... | the_stack_v2_python_sparse | SuperWashingMachines_HARD_517.py | 953250587/leetcode-python | train | 2 | |
2a9868e6d79a8d00663e85a595dee930ff76314e | [
"online_minions = list()\noffline_minions = list()\nexpired_minions = list()\nfor minion_obj in minions:\n current_datetime = datetime.datetime.utcnow()\n current_datetime = current_datetime.replace(tzinfo=pytz.utc)\n last_seen = minion_obj.last_seen\n try:\n delta_diff = current_datetime - last_... | <|body_start_0|>
online_minions = list()
offline_minions = list()
expired_minions = list()
for minion_obj in minions:
current_datetime = datetime.datetime.utcnow()
current_datetime = current_datetime.replace(tzinfo=pytz.utc)
last_seen = minion_obj.last... | API to list online, office and expired minions URL http://<hostname>/report/minion/all/ Method: GET Returns data in the following format | AllMinionReport | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllMinionReport:
"""API to list online, office and expired minions URL http://<hostname>/report/minion/all/ Method: GET Returns data in the following format"""
def minion_connection_stats(self, minions):
"""To get a list of online, offline and expired minions"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_006835 | 6,377 | no_license | [
{
"docstring": "To get a list of online, offline and expired minions",
"name": "minion_connection_stats",
"signature": "def minion_connection_stats(self, minions)"
},
{
"docstring": "To show the key stats for the minions",
"name": "minion_key_stats",
"signature": "def minion_key_stats(se... | 5 | stack_v2_sparse_classes_30k_train_006923 | Implement the Python class `AllMinionReport` described below.
Class description:
API to list online, office and expired minions URL http://<hostname>/report/minion/all/ Method: GET Returns data in the following format
Method signatures and docstrings:
- def minion_connection_stats(self, minions): To get a list of onl... | Implement the Python class `AllMinionReport` described below.
Class description:
API to list online, office and expired minions URL http://<hostname>/report/minion/all/ Method: GET Returns data in the following format
Method signatures and docstrings:
- def minion_connection_stats(self, minions): To get a list of onl... | 122a172caea82ef660e81a9dfc6377afd731f9cb | <|skeleton|>
class AllMinionReport:
"""API to list online, office and expired minions URL http://<hostname>/report/minion/all/ Method: GET Returns data in the following format"""
def minion_connection_stats(self, minions):
"""To get a list of online, offline and expired minions"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AllMinionReport:
"""API to list online, office and expired minions URL http://<hostname>/report/minion/all/ Method: GET Returns data in the following format"""
def minion_connection_stats(self, minions):
"""To get a list of online, offline and expired minions"""
online_minions = list()
... | the_stack_v2_python_sparse | sso/files/gui/sse/report/views.py | nofxrok/headless | train | 1 |
c22b8a188c46185ce9d9ed85466fabeb59a45d2b | [
"if ax is None:\n fig, ax = plt.subplots()\nlines, markers = plt.triplot(self.tri, **kwargs)",
"vertices = self.node_map(self.tri.triangles)\nget_level = lambda node_id: self.data[label_by].loc[node_id]\nlevels = np.apply_along_axis(get_level, axis=1, arr=vertices)\nget_mode = lambda x: Counter(x).most_common(... | <|body_start_0|>
if ax is None:
fig, ax = plt.subplots()
lines, markers = plt.triplot(self.tri, **kwargs)
<|end_body_0|>
<|body_start_1|>
vertices = self.node_map(self.tri.triangles)
get_level = lambda node_id: self.data[label_by].loc[node_id]
levels = np.apply_along... | Methods for visualizing a Graph instance. | GraphVisualizationMethods | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraphVisualizationMethods:
"""Methods for visualizing a Graph instance."""
def plot_edges(self, ax=None, **kwargs):
"""Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.pyplot.triplot"""
<|body_0|>
def label_triangl... | stack_v2_sparse_classes_10k_train_006836 | 23,136 | permissive | [
{
"docstring": "Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.pyplot.triplot",
"name": "plot_edges",
"signature": "def plot_edges(self, ax=None, **kwargs)"
},
{
"docstring": "Label each triangle with most common node attribute value. Ar... | 4 | stack_v2_sparse_classes_30k_train_003956 | Implement the Python class `GraphVisualizationMethods` described below.
Class description:
Methods for visualizing a Graph instance.
Method signatures and docstrings:
- def plot_edges(self, ax=None, **kwargs): Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.py... | Implement the Python class `GraphVisualizationMethods` described below.
Class description:
Methods for visualizing a Graph instance.
Method signatures and docstrings:
- def plot_edges(self, ax=None, **kwargs): Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.py... | 4a622c3f5fed4456c3b9240f5a96428789fde9bd | <|skeleton|>
class GraphVisualizationMethods:
"""Methods for visualizing a Graph instance."""
def plot_edges(self, ax=None, **kwargs):
"""Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.pyplot.triplot"""
<|body_0|>
def label_triangl... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GraphVisualizationMethods:
"""Methods for visualizing a Graph instance."""
def plot_edges(self, ax=None, **kwargs):
"""Plot triangulation edges. Args: ax (matplotlib.axes.AxesSubplot) kwargs: keyword arguments for matplotlib.pyplot.triplot"""
if ax is None:
fig, ax = plt.subpl... | the_stack_v2_python_sparse | flyqma/annotation/spatial/graphs.py | sbernasek/flyqma | train | 1 |
05a152f09390369a6d9d02a0febe6cec74d508b7 | [
"response = {'success': False, 'message': 'Something bad happened', 'data': []}\nuser = request.user\ntry:\n requestBody = json.loads(request.body)\n label_name = requestBody['name']\n label_updated = Label.objects.get(id=label_id, user_id=user.id)\n label_updated.name = label_name\n label_updated.sa... | <|body_start_0|>
response = {'success': False, 'message': 'Something bad happened', 'data': []}
user = request.user
try:
requestBody = json.loads(request.body)
label_name = requestBody['name']
label_updated = Label.objects.get(id=label_id, user_id=user.id)
... | Summary: -------- Label update class will let authorized user to update or delete label. Methods: -------- put: User will be able to update label. delete: User will able to delete one or more labels. | LabelsUpdate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabelsUpdate:
"""Summary: -------- Label update class will let authorized user to update or delete label. Methods: -------- put: User will be able to update label. delete: User will able to delete one or more labels."""
def put(self, request, label_id):
"""Summary: -------- label wil... | stack_v2_sparse_classes_10k_train_006837 | 30,711 | no_license | [
{
"docstring": "Summary: -------- label will be updated by the User. Exception: ---------- Exception: if anything goes wrong. Returns: -------- response: User will able to updated label or error msg if something goes wrong",
"name": "put",
"signature": "def put(self, request, label_id)"
},
{
"do... | 2 | stack_v2_sparse_classes_30k_train_004793 | Implement the Python class `LabelsUpdate` described below.
Class description:
Summary: -------- Label update class will let authorized user to update or delete label. Methods: -------- put: User will be able to update label. delete: User will able to delete one or more labels.
Method signatures and docstrings:
- def ... | Implement the Python class `LabelsUpdate` described below.
Class description:
Summary: -------- Label update class will let authorized user to update or delete label. Methods: -------- put: User will be able to update label. delete: User will able to delete one or more labels.
Method signatures and docstrings:
- def ... | f4035742d959f493f93a593f49e2fcacb721f85d | <|skeleton|>
class LabelsUpdate:
"""Summary: -------- Label update class will let authorized user to update or delete label. Methods: -------- put: User will be able to update label. delete: User will able to delete one or more labels."""
def put(self, request, label_id):
"""Summary: -------- label wil... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LabelsUpdate:
"""Summary: -------- Label update class will let authorized user to update or delete label. Methods: -------- put: User will be able to update label. delete: User will able to delete one or more labels."""
def put(self, request, label_id):
"""Summary: -------- label will be updated ... | the_stack_v2_python_sparse | note/views.py | nk900600/fundooapp | train | 3 |
07c82af68cd6d99cd537bc4a97438556e37c861c | [
"str = ''\nif root is None:\n return str\nnodes = [root]\nwhile nodes.__len__():\n temp = []\n count = 0\n for node in nodes:\n if node:\n str += '{} '.format(node.val)\n temp.append(node.left)\n temp.append(node.right)\n if node.left:\n ... | <|body_start_0|>
str = ''
if root is None:
return str
nodes = [root]
while nodes.__len__():
temp = []
count = 0
for node in nodes:
if node:
str += '{} '.format(node.val)
temp.append(no... | 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_10k_train_006838 | 2,736 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 055ace9f0ca4fb09326da77ae39e33173b3bde15 | <|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_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
str = ''
if root is None:
return str
nodes = [root]
while nodes.__len__():
temp = []
count = 0
for node in nodes:
... | the_stack_v2_python_sparse | leetcode/0297_H_二叉树的序列化与反序列化.py | CrzRabbit/Python | train | 2 | |
73d6876ab2f4c693c3d9b527025b745ef7541097 | [
"self._nodes = []\nself._edges = []\nself._num_nodes = 0",
"self._num_nodes += 1\nname = 'node{number}'.format(number=self._num_nodes)\ncode = '{name} [label=\"{label}\"];'.format(name=name, label=label)\nself._nodes.append(code)\nreturn name",
"template = '{from_node} -- {to_node};'\ncode = template.format(fro... | <|body_start_0|>
self._nodes = []
self._edges = []
self._num_nodes = 0
<|end_body_0|>
<|body_start_1|>
self._num_nodes += 1
name = 'node{number}'.format(number=self._num_nodes)
code = '{name} [label="{label}"];'.format(name=name, label=label)
self._nodes.append(c... | Clase utilizada para la generación de grafos en formato Graphviz DOT. | DotGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DotGenerator:
"""Clase utilizada para la generación de grafos en formato Graphviz DOT."""
def __init__(self):
"""Esta clase es utilizada en la generación de código Graphivz DOT a partir de un árbol de sintáxis abstracta de un programa Tiger."""
<|body_0|>
def add_node(se... | stack_v2_sparse_classes_10k_train_006839 | 2,786 | permissive | [
{
"docstring": "Esta clase es utilizada en la generación de código Graphivz DOT a partir de un árbol de sintáxis abstracta de un programa Tiger.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Añade un nuevo nodo al grafo actualmente en creación. @type label: C{str} @p... | 4 | stack_v2_sparse_classes_30k_train_004532 | Implement the Python class `DotGenerator` described below.
Class description:
Clase utilizada para la generación de grafos en formato Graphviz DOT.
Method signatures and docstrings:
- def __init__(self): Esta clase es utilizada en la generación de código Graphivz DOT a partir de un árbol de sintáxis abstracta de un p... | Implement the Python class `DotGenerator` described below.
Class description:
Clase utilizada para la generación de grafos en formato Graphviz DOT.
Method signatures and docstrings:
- def __init__(self): Esta clase es utilizada en la generación de código Graphivz DOT a partir de un árbol de sintáxis abstracta de un p... | 35c44d14775bf69ed6689b708b98d6d1ca533ba0 | <|skeleton|>
class DotGenerator:
"""Clase utilizada para la generación de grafos en formato Graphviz DOT."""
def __init__(self):
"""Esta clase es utilizada en la generación de código Graphivz DOT a partir de un árbol de sintáxis abstracta de un programa Tiger."""
<|body_0|>
def add_node(se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DotGenerator:
"""Clase utilizada para la generación de grafos en formato Graphviz DOT."""
def __init__(self):
"""Esta clase es utilizada en la generación de código Graphivz DOT a partir de un árbol de sintáxis abstracta de un programa Tiger."""
self._nodes = []
self._edges = []
... | the_stack_v2_python_sparse | packages/pytiger2c/dot.py | yasserglez/pytiger2c | train | 2 |
74ba213d4fab33b0a7cfabe35671d93818512ca4 | [
"self.mu_g = mu_g\nself.s_g = s_g\nself.s_s = s_s\nself.h = h",
"assert len(f1.shape) == 1, 'input must be 1d ndarray'\nassert len(f2.shape) == 1, 'input must be 1d ndarray'\nassert f1.shape == f2.shape\nn_trial = len(f1)\nf1_ = np.tile(f1, (n_samp, 1)) + self.s_s * np.random.randn(n_samp, n_trial)\ns = (1.0 / se... | <|body_start_0|>
self.mu_g = mu_g
self.s_g = s_g
self.s_s = s_s
self.h = h
<|end_body_0|>
<|body_start_1|>
assert len(f1.shape) == 1, 'input must be 1d ndarray'
assert len(f2.shape) == 1, 'input must be 1d ndarray'
assert f1.shape == f2.shape
n_trial = le... | A model of tone discrimination where - the value of the first tone is inferred from noisy observation - the value of the second tone is noiseless - prior is unigauss | Model | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
"""A model of tone discrimination where - the value of the first tone is inferred from noisy observation - the value of the second tone is noiseless - prior is unigauss"""
def __init__(self, mu_g, s_g, h, s_s):
"""Constructor :param mu_g: mean of gaussian part of unigauss :par... | stack_v2_sparse_classes_10k_train_006840 | 11,426 | no_license | [
{
"docstring": "Constructor :param mu_g: mean of gaussian part of unigauss :param s_g: std of gaussian part of unigauss :param h: weight of flat prior in unigauss mixture assuming unnormalized gaussian p(x) 1/Z*( h + exp((x-mu)/2/s^2) ) :param s_s: std of likelihood",
"name": "__init__",
"signature": "d... | 3 | stack_v2_sparse_classes_30k_train_000397 | Implement the Python class `Model` described below.
Class description:
A model of tone discrimination where - the value of the first tone is inferred from noisy observation - the value of the second tone is noiseless - prior is unigauss
Method signatures and docstrings:
- def __init__(self, mu_g, s_g, h, s_s): Constr... | Implement the Python class `Model` described below.
Class description:
A model of tone discrimination where - the value of the first tone is inferred from noisy observation - the value of the second tone is noiseless - prior is unigauss
Method signatures and docstrings:
- def __init__(self, mu_g, s_g, h, s_s): Constr... | 2a05aa98b501c8633e1fe2baf611d137740709de | <|skeleton|>
class Model:
"""A model of tone discrimination where - the value of the first tone is inferred from noisy observation - the value of the second tone is noiseless - prior is unigauss"""
def __init__(self, mu_g, s_g, h, s_s):
"""Constructor :param mu_g: mean of gaussian part of unigauss :par... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Model:
"""A model of tone discrimination where - the value of the first tone is inferred from noisy observation - the value of the second tone is noiseless - prior is unigauss"""
def __init__(self, mu_g, s_g, h, s_s):
"""Constructor :param mu_g: mean of gaussian part of unigauss :param s_g: std o... | the_stack_v2_python_sparse | model/simple_model.py | ItayLieder/GMM_simulations | train | 0 |
6ebf328484aad8dd6c9f53dc8cdcf9f09b39f53c | [
"cameraDTO = request.json\ncameraManager.postCamera(**cameraDTO)\nreturn make_response({'operation': 'success'}, 200)",
"cameraPath = os.path.join(cfg.UPLOAD_FOLDER, cameraId)\nif not os.path.exists(cameraPath):\n return make_response({'images': [], 'id': cameraId}, 200)\nlastImageDate = os.listdir(cameraPath)... | <|body_start_0|>
cameraDTO = request.json
cameraManager.postCamera(**cameraDTO)
return make_response({'operation': 'success'}, 200)
<|end_body_0|>
<|body_start_1|>
cameraPath = os.path.join(cfg.UPLOAD_FOLDER, cameraId)
if not os.path.exists(cameraPath):
return make_r... | Camera | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Camera:
def post(self, cameraId):
"""Добавить новую камеру"""
<|body_0|>
def get(self, cameraId):
"""Получить информацию о камере"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cameraDTO = request.json
cameraManager.postCamera(**cameraDTO)
... | stack_v2_sparse_classes_10k_train_006841 | 3,745 | permissive | [
{
"docstring": "Добавить новую камеру",
"name": "post",
"signature": "def post(self, cameraId)"
},
{
"docstring": "Получить информацию о камере",
"name": "get",
"signature": "def get(self, cameraId)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006031 | Implement the Python class `Camera` described below.
Class description:
Implement the Camera class.
Method signatures and docstrings:
- def post(self, cameraId): Добавить новую камеру
- def get(self, cameraId): Получить информацию о камере | Implement the Python class `Camera` described below.
Class description:
Implement the Camera class.
Method signatures and docstrings:
- def post(self, cameraId): Добавить новую камеру
- def get(self, cameraId): Получить информацию о камере
<|skeleton|>
class Camera:
def post(self, cameraId):
"""Добавить... | ac6d90da101a5c2f2c305ba21f67369a0f3b786f | <|skeleton|>
class Camera:
def post(self, cameraId):
"""Добавить новую камеру"""
<|body_0|>
def get(self, cameraId):
"""Получить информацию о камере"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Camera:
def post(self, cameraId):
"""Добавить новую камеру"""
cameraDTO = request.json
cameraManager.postCamera(**cameraDTO)
return make_response({'operation': 'success'}, 200)
def get(self, cameraId):
"""Получить информацию о камере"""
cameraPath = os.path... | the_stack_v2_python_sparse | Premier-eye.API/controllers/camera/camera.py | Sapfir0/premier-eye | train | 18 | |
913ea239d7661fce8c90160a40c5b908bf6fe273 | [
"super(CreateBackupTests, cls).setUpClass()\nkey_resp = cls.keypairs_client.create_keypair(rand_name('key'))\nassert key_resp.status_code is 200, 'Create keypair failed with response code {0}'.format(key_resp.status_code)\ncls.key = key_resp.entity\ncls.resources.add(cls.key.name, cls.keypairs_client.delete_keypair... | <|body_start_0|>
super(CreateBackupTests, cls).setUpClass()
key_resp = cls.keypairs_client.create_keypair(rand_name('key'))
assert key_resp.status_code is 200, 'Create keypair failed with response code {0}'.format(key_resp.status_code)
cls.key = key_resp.entity
cls.resources.add(... | CreateBackupTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateBackupTests:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing. The following resources are created during this setup: - A server with defaults defined in server behaviors."""
<|body_0|>
def test_create_backup_for_server(self):
... | stack_v2_sparse_classes_10k_train_006842 | 2,408 | permissive | [
{
"docstring": "Perform actions that setup the necessary resources for testing. The following resources are created during this setup: - A server with defaults defined in server behaviors.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Verify that a backup can be c... | 2 | stack_v2_sparse_classes_30k_train_004344 | Implement the Python class `CreateBackupTests` described below.
Class description:
Implement the CreateBackupTests class.
Method signatures and docstrings:
- def setUpClass(cls): Perform actions that setup the necessary resources for testing. The following resources are created during this setup: - A server with defa... | Implement the Python class `CreateBackupTests` described below.
Class description:
Implement the CreateBackupTests class.
Method signatures and docstrings:
- def setUpClass(cls): Perform actions that setup the necessary resources for testing. The following resources are created during this setup: - A server with defa... | 30f0e64672676c3f90b4a582fe90fac6621475b3 | <|skeleton|>
class CreateBackupTests:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing. The following resources are created during this setup: - A server with defaults defined in server behaviors."""
<|body_0|>
def test_create_backup_for_server(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CreateBackupTests:
def setUpClass(cls):
"""Perform actions that setup the necessary resources for testing. The following resources are created during this setup: - A server with defaults defined in server behaviors."""
super(CreateBackupTests, cls).setUpClass()
key_resp = cls.keypairs_... | the_stack_v2_python_sparse | cloudroast/compute/instance_actions/admin_api/test_create_backup.py | RULCSoft/cloudroast | train | 1 | |
35f10023a22bfdc7236cf747a45c183339c9831b | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('jgrishey', 'jgrishey')\nstations = list(repo['jgrishey.redlineStations'].find(None, ['_id', 'lat', 'lon']))\nfor station in stations:\n url = 'http://api.geonames.org/findNearbyStreetsJSON?lat=%s&lng=... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('jgrishey', 'jgrishey')
stations = list(repo['jgrishey.redlineStations'].find(None, ['_id', 'lat', 'lon']))
for station in stations:
ur... | redlineStreets | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class redlineStreets:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythin... | stack_v2_sparse_classes_10k_train_006843 | 4,285 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | null | Implement the Python class `redlineStreets` described below.
Class description:
Implement the redlineStreets class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None,... | Implement the Python class `redlineStreets` described below.
Class description:
Implement the redlineStreets class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None,... | 0df485d0469c5451ebdcd684bed2a0960ba3ab84 | <|skeleton|>
class redlineStreets:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class redlineStreets:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('jgrishey', 'jgrishey')
stati... | the_stack_v2_python_sparse | jgrishey/redlineStreets.py | lingyigu/course-2017-spr-proj | train | 0 | |
b3142e8642d2a6f5aa3657bc549a46a7b6aab754 | [
"collection: Final[str] = 'profile_armor_map'\nquery = Query(collection, service_id=self._client.service_id)\nquery.add_term(field=self.id_field, value=self.id)\nquery.limit(20)\njoin = query.create_join(ArmourInfo.collection)\njoin.set_fields(ArmourInfo.id_field)\nreturn SequenceProxy(ArmourInfo, query, client=sel... | <|body_start_0|>
collection: Final[str] = 'profile_armor_map'
query = Query(collection, service_id=self._client.service_id)
query.add_term(field=self.id_field, value=self.id)
query.limit(20)
join = query.create_join(ArmourInfo.collection)
join.set_fields(ArmourInfo.id_fie... | An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as other non-static entities such as Cortium nodes or pumpkins. .. attribute:: id... | Profile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Profile:
"""An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as other non-static entities such as Cortium n... | stack_v2_sparse_classes_10k_train_006844 | 5,971 | permissive | [
{
"docstring": "Return the armour info of the profile. This returns a :class:`auraxium.SequenceProxy`.",
"name": "armour_info",
"signature": "def armour_info(self) -> SequenceProxy[ArmourInfo]"
},
{
"docstring": "Return the resist info of the profile. This returns a :class:`auraxium.SequenceProx... | 2 | stack_v2_sparse_classes_30k_test_000358 | Implement the Python class `Profile` described below.
Class description:
An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as othe... | Implement the Python class `Profile` described below.
Class description:
An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as othe... | 23dcf927a199c8d7c917d89fe96b470a34cf4bba | <|skeleton|>
class Profile:
"""An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as other non-static entities such as Cortium n... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Profile:
"""An entity in the game world. This is used to specify the resistance and armour values to apply to a given object. Profiles include faction-specific classes, vehicles, facility infrastructure such as turrets, generators or shields, as well as other non-static entities such as Cortium nodes or pumpk... | the_stack_v2_python_sparse | auraxium/ps2/_profile.py | leonhard-s/auraxium | train | 29 |
d9e65f2deae8aa58a79aa81f6582ca953949d7e2 | [
"os.makedirs(os.path.dirname(cls.path_token), exist_ok=True)\nwith open(cls.path_token, 'w+') as f:\n f.write(token)",
"try:\n with open(cls.path_token, 'r') as f:\n return f.read()\nexcept FileNotFoundError:\n pass",
"try:\n os.remove(cls.path_token)\nexcept FileNotFoundError:\n pass"
] | <|body_start_0|>
os.makedirs(os.path.dirname(cls.path_token), exist_ok=True)
with open(cls.path_token, 'w+') as f:
f.write(token)
<|end_body_0|>
<|body_start_1|>
try:
with open(cls.path_token, 'r') as f:
return f.read()
except FileNotFoundError:
... | HfFolder | [
"LGPL-2.1-or-later",
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HfFolder:
def save_token(cls, token):
"""Save token, creating folder as needed."""
<|body_0|>
def get_token(cls):
"""Get token or None if not existent."""
<|body_1|>
def delete_token(cls):
"""Delete token. Do not fail if token does not exist."""
... | stack_v2_sparse_classes_10k_train_006845 | 5,878 | permissive | [
{
"docstring": "Save token, creating folder as needed.",
"name": "save_token",
"signature": "def save_token(cls, token)"
},
{
"docstring": "Get token or None if not existent.",
"name": "get_token",
"signature": "def get_token(cls)"
},
{
"docstring": "Delete token. Do not fail if ... | 3 | null | Implement the Python class `HfFolder` described below.
Class description:
Implement the HfFolder class.
Method signatures and docstrings:
- def save_token(cls, token): Save token, creating folder as needed.
- def get_token(cls): Get token or None if not existent.
- def delete_token(cls): Delete token. Do not fail if ... | Implement the Python class `HfFolder` described below.
Class description:
Implement the HfFolder class.
Method signatures and docstrings:
- def save_token(cls, token): Save token, creating folder as needed.
- def get_token(cls): Get token or None if not existent.
- def delete_token(cls): Delete token. Do not fail if ... | b60c741f746877293bb85eed6806736fc8fa0ffd | <|skeleton|>
class HfFolder:
def save_token(cls, token):
"""Save token, creating folder as needed."""
<|body_0|>
def get_token(cls):
"""Get token or None if not existent."""
<|body_1|>
def delete_token(cls):
"""Delete token. Do not fail if token does not exist."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HfFolder:
def save_token(cls, token):
"""Save token, creating folder as needed."""
os.makedirs(os.path.dirname(cls.path_token), exist_ok=True)
with open(cls.path_token, 'w+') as f:
f.write(token)
def get_token(cls):
"""Get token or None if not existent."""
... | the_stack_v2_python_sparse | xtune/src/transformers/hf_api.py | microsoft/unilm | train | 15,313 | |
bc948902a4877fcb219627d213bc93d6063e7b5f | [
"self.model_conf = model_conf\nself.inputs = inputs\nself.utils = utils\nself.layer = None",
"with tf.keras.backend.name_scope('GRU'):\n mask = tf.keras.layers.Masking()(self.inputs)\n self.layer = tf.keras.layers.GRU(units=self.model_conf.units_num * 2, return_sequences=True, input_shape=mask.shape)\n o... | <|body_start_0|>
self.model_conf = model_conf
self.inputs = inputs
self.utils = utils
self.layer = None
<|end_body_0|>
<|body_start_1|>
with tf.keras.backend.name_scope('GRU'):
mask = tf.keras.layers.Masking()(self.inputs)
self.layer = tf.keras.layers.GRU... | GRU | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRU:
def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils):
""":param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类"""
<|body_0|>
def build(self):
"""循环层构建参数 :return: 返回循环层的输出层"""
<|bo... | stack_v2_sparse_classes_10k_train_006846 | 2,557 | permissive | [
{
"docstring": ":param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类",
"name": "__init__",
"signature": "def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils)"
},
{
"docstring": "循环层构建参数 :return: 返回循环层的输出层",
"name": "... | 2 | stack_v2_sparse_classes_30k_train_004130 | Implement the Python class `GRU` described below.
Class description:
Implement the GRU class.
Method signatures and docstrings:
- def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils): :param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类
- def... | Implement the Python class `GRU` described below.
Class description:
Implement the GRU class.
Method signatures and docstrings:
- def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils): :param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类
- def... | 6fd35c0c789aaa43130de46d4c04622ec2948052 | <|skeleton|>
class GRU:
def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils):
""":param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类"""
<|body_0|>
def build(self):
"""循环层构建参数 :return: 返回循环层的输出层"""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GRU:
def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils):
""":param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类"""
self.model_conf = model_conf
self.inputs = inputs
self.utils = utils
self.la... | the_stack_v2_python_sparse | network/GRU.py | kerlomz/captcha_trainer | train | 2,977 | |
0fec9cb4b8d86dfaea25aec8c1361f09dd7e1b5d | [
"super(NeRF_albedo, self).__init__()\nself.W = W\nself.in_channels_dir = in_channels_dir\nself.xyz_encoding_final = nn.Linear(W, W)\nself.dir_encoding = nn.Sequential(nn.Linear(W + in_channels_dir, W // 2), nn.ReLU(True))\nself.rgb = nn.Sequential(nn.Linear(W // 2, 3), nn.Sigmoid())",
"xyz_encoding_final = self.x... | <|body_start_0|>
super(NeRF_albedo, self).__init__()
self.W = W
self.in_channels_dir = in_channels_dir
self.xyz_encoding_final = nn.Linear(W, W)
self.dir_encoding = nn.Sequential(nn.Linear(W + in_channels_dir, W // 2), nn.ReLU(True))
self.rgb = nn.Sequential(nn.Linear(W /... | NeRF_albedo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeRF_albedo:
def __init__(self, W=256, in_channels_dir=27):
"""D: number of layers for density (sigma) encoder W: number of hidden units in each layer in_channels_xyz: number of input channels for xyz (3+3*10*2=63 by default) in_channels_dir: number of input channels for direction (3+3*4... | stack_v2_sparse_classes_10k_train_006847 | 18,983 | no_license | [
{
"docstring": "D: number of layers for density (sigma) encoder W: number of hidden units in each layer in_channels_xyz: number of input channels for xyz (3+3*10*2=63 by default) in_channels_dir: number of input channels for direction (3+3*4*2=27 by default) skips: add skip connection in the Dth layer",
"na... | 2 | stack_v2_sparse_classes_30k_train_004827 | Implement the Python class `NeRF_albedo` described below.
Class description:
Implement the NeRF_albedo class.
Method signatures and docstrings:
- def __init__(self, W=256, in_channels_dir=27): D: number of layers for density (sigma) encoder W: number of hidden units in each layer in_channels_xyz: number of input chan... | Implement the Python class `NeRF_albedo` described below.
Class description:
Implement the NeRF_albedo class.
Method signatures and docstrings:
- def __init__(self, W=256, in_channels_dir=27): D: number of layers for density (sigma) encoder W: number of hidden units in each layer in_channels_xyz: number of input chan... | 3b6e9d85e77077d1ad3b669fe88799d6a19e6d99 | <|skeleton|>
class NeRF_albedo:
def __init__(self, W=256, in_channels_dir=27):
"""D: number of layers for density (sigma) encoder W: number of hidden units in each layer in_channels_xyz: number of input channels for xyz (3+3*10*2=63 by default) in_channels_dir: number of input channels for direction (3+3*4... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NeRF_albedo:
def __init__(self, W=256, in_channels_dir=27):
"""D: number of layers for density (sigma) encoder W: number of hidden units in each layer in_channels_xyz: number of input channels for xyz (3+3*10*2=63 by default) in_channels_dir: number of input channels for direction (3+3*4*2=27 by defau... | the_stack_v2_python_sparse | models/nert.py | jcn16/nert | train | 0 | |
0df171673b8338464d988aacc90d42ec6dc03b02 | [
"policy = policy_fn(ACT_SPACE_SIZE, **policy_fn_arguments)\nobs = fake_observations(BATCH_SIZE)\ndata = policy(obs)\nself.assertIsNotNone(data)\nself.assertEqual(len(data), 3)\naction, log_prob, entropy = data\nself.assertEqual(log_prob.shape, (BATCH_SIZE,))\nself.assertEqual(entropy.shape, (BATCH_SIZE,))\nif polic... | <|body_start_0|>
policy = policy_fn(ACT_SPACE_SIZE, **policy_fn_arguments)
obs = fake_observations(BATCH_SIZE)
data = policy(obs)
self.assertIsNotNone(data)
self.assertEqual(len(data), 3)
action, log_prob, entropy = data
self.assertEqual(log_prob.shape, (BATCH_SIZ... | Common class to run tests for policies. | PoliciesTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PoliciesTest:
"""Common class to run tests for policies."""
def test_policy(self, policy_fn, policy_fn_arguments, policy_type):
"""Test if policy return types are good."""
<|body_0|>
def test_normal_policies_learnable_variables(self):
"""Make sure that fixed_std ... | stack_v2_sparse_classes_10k_train_006848 | 3,873 | permissive | [
{
"docstring": "Test if policy return types are good.",
"name": "test_policy",
"signature": "def test_policy(self, policy_fn, policy_fn_arguments, policy_type)"
},
{
"docstring": "Make sure that fixed_std will not learn the standard deviation.",
"name": "test_normal_policies_learnable_variab... | 2 | stack_v2_sparse_classes_30k_train_005394 | Implement the Python class `PoliciesTest` described below.
Class description:
Common class to run tests for policies.
Method signatures and docstrings:
- def test_policy(self, policy_fn, policy_fn_arguments, policy_type): Test if policy return types are good.
- def test_normal_policies_learnable_variables(self): Make... | Implement the Python class `PoliciesTest` described below.
Class description:
Common class to run tests for policies.
Method signatures and docstrings:
- def test_policy(self, policy_fn, policy_fn_arguments, policy_type): Test if policy return types are good.
- def test_normal_policies_learnable_variables(self): Make... | 96c99bc67ce40559c61bdb6110f625671fc96055 | <|skeleton|>
class PoliciesTest:
"""Common class to run tests for policies."""
def test_policy(self, policy_fn, policy_fn_arguments, policy_type):
"""Test if policy return types are good."""
<|body_0|>
def test_normal_policies_learnable_variables(self):
"""Make sure that fixed_std ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PoliciesTest:
"""Common class to run tests for policies."""
def test_policy(self, policy_fn, policy_fn_arguments, policy_type):
"""Test if policy return types are good."""
policy = policy_fn(ACT_SPACE_SIZE, **policy_fn_arguments)
obs = fake_observations(BATCH_SIZE)
data = ... | the_stack_v2_python_sparse | eager_pg/policies_test.py | muskanmahajan37/policy-learning-landscape | train | 0 |
665eee76936ab9e8590109589fb58e8fcc553d62 | [
"always_excluded_fields = ('cache',)\nexcluded_fields = list(super().get_exclude(request, obj=obj) or [])\nif obj:\n for excluded_field in always_excluded_fields:\n if hasattr(obj, excluded_field):\n excluded_fields.append(excluded_field)\nreturn list(set(excluded_fields))",
"search_term = se... | <|body_start_0|>
always_excluded_fields = ('cache',)
excluded_fields = list(super().get_exclude(request, obj=obj) or [])
if obj:
for excluded_field in always_excluded_fields:
if hasattr(obj, excluded_field):
excluded_fields.append(excluded_field)
... | Base admin class for ModularHistory's models. | ExtendedModelAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtendedModelAdmin:
"""Base admin class for ModularHistory's models."""
def get_exclude(self, request: HttpRequest, obj: Optional['Model']=None) -> list[str]:
"""Return the fields to exclude from admin forms."""
<|body_0|>
def get_search_results(self, request: HttpReques... | stack_v2_sparse_classes_10k_train_006849 | 5,673 | no_license | [
{
"docstring": "Return the fields to exclude from admin forms.",
"name": "get_exclude",
"signature": "def get_exclude(self, request: HttpRequest, obj: Optional['Model']=None) -> list[str]"
},
{
"docstring": "Return model instances matching the supplied search term.",
"name": "get_search_resu... | 2 | stack_v2_sparse_classes_30k_train_003746 | Implement the Python class `ExtendedModelAdmin` described below.
Class description:
Base admin class for ModularHistory's models.
Method signatures and docstrings:
- def get_exclude(self, request: HttpRequest, obj: Optional['Model']=None) -> list[str]: Return the fields to exclude from admin forms.
- def get_search_r... | Implement the Python class `ExtendedModelAdmin` described below.
Class description:
Base admin class for ModularHistory's models.
Method signatures and docstrings:
- def get_exclude(self, request: HttpRequest, obj: Optional['Model']=None) -> list[str]: Return the fields to exclude from admin forms.
- def get_search_r... | 8bbdc8eec3622af22c17214051c34e36bea8e05a | <|skeleton|>
class ExtendedModelAdmin:
"""Base admin class for ModularHistory's models."""
def get_exclude(self, request: HttpRequest, obj: Optional['Model']=None) -> list[str]:
"""Return the fields to exclude from admin forms."""
<|body_0|>
def get_search_results(self, request: HttpReques... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExtendedModelAdmin:
"""Base admin class for ModularHistory's models."""
def get_exclude(self, request: HttpRequest, obj: Optional['Model']=None) -> list[str]:
"""Return the fields to exclude from admin forms."""
always_excluded_fields = ('cache',)
excluded_fields = list(super().ge... | the_stack_v2_python_sparse | apps/admin/model_admin.py | abdulwahed-mansour/modularhistory | train | 1 |
2bb48278d4b7da9ea4dd7e94511308f4c56cf7e4 | [
"now = pendulum.now('utc')\nschedules = await models.Schedule.where({'active': {'_eq': True}, 'flow': {'archived': {'_eq': False}}, '_and': [{'_or': [{'schedule_start': {'_lte': str(now.add(days=1))}}, {'schedule_start': {'_is_null': True}}]}, {'_or': [{'schedule_end': {'_gte': str(now)}}, {'schedule_end': {'_is_nu... | <|body_start_0|>
now = pendulum.now('utc')
schedules = await models.Schedule.where({'active': {'_eq': True}, 'flow': {'archived': {'_eq': False}}, '_and': [{'_or': [{'schedule_start': {'_lte': str(now.add(days=1))}}, {'schedule_start': {'_is_null': True}}]}, {'_or': [{'schedule_end': {'_gte': str(now)}}... | The Scheduler is a service that creates new flow runs for flows with active schedules. Schedules that are eligible for scheduling have the following properties: - the schedule has already started, or starts within the next 24 hours - the schedule has not ended - the schedule is active - the schedule's flow is not archi... | Scheduler | [
"LicenseRef-scancode-proprietary-license",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Scheduler:
"""The Scheduler is a service that creates new flow runs for flows with active schedules. Schedules that are eligible for scheduling have the following properties: - the schedule has already started, or starts within the next 24 hours - the schedule has not ended - the schedule is acti... | stack_v2_sparse_classes_10k_train_006850 | 3,674 | permissive | [
{
"docstring": "Args: - n_flows (int): the maximum number of flows to schedule Returns: - int: The number of scheduled runs",
"name": "schedule_flows",
"signature": "async def schedule_flows(self, n_flows=100) -> int"
},
{
"docstring": "Run the scheduler loop one time. As long as `schedule_flows... | 2 | stack_v2_sparse_classes_30k_train_003690 | Implement the Python class `Scheduler` described below.
Class description:
The Scheduler is a service that creates new flow runs for flows with active schedules. Schedules that are eligible for scheduling have the following properties: - the schedule has already started, or starts within the next 24 hours - the schedu... | Implement the Python class `Scheduler` described below.
Class description:
The Scheduler is a service that creates new flow runs for flows with active schedules. Schedules that are eligible for scheduling have the following properties: - the schedule has already started, or starts within the next 24 hours - the schedu... | f2ae050df8258aebfc0a97ffcd3e38344180f53e | <|skeleton|>
class Scheduler:
"""The Scheduler is a service that creates new flow runs for flows with active schedules. Schedules that are eligible for scheduling have the following properties: - the schedule has already started, or starts within the next 24 hours - the schedule has not ended - the schedule is acti... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Scheduler:
"""The Scheduler is a service that creates new flow runs for flows with active schedules. Schedules that are eligible for scheduling have the following properties: - the schedule has already started, or starts within the next 24 hours - the schedule has not ended - the schedule is active - the sche... | the_stack_v2_python_sparse | server/src/prefect_server/services/scheduler/scheduler.py | manesioz/prefect | train | 0 |
360344bffecce399a668c5a77d9d76a15d9dd637 | [
"super().__init__(syncthru, name)\nself._name = f'{name} Output Tray {number}'\nself._number = number\nself._id_suffix = f'_output_tray_{number}'",
"if self.syncthru.is_online():\n self._attributes = self.syncthru.output_tray_status().get(self._number, {})\n self._state = self._attributes.get('status')\n ... | <|body_start_0|>
super().__init__(syncthru, name)
self._name = f'{name} Output Tray {number}'
self._number = number
self._id_suffix = f'_output_tray_{number}'
<|end_body_0|>
<|body_start_1|>
if self.syncthru.is_online():
self._attributes = self.syncthru.output_tray_s... | Implementation of a Samsung Printer input tray sensor platform. | SyncThruOutputTraySensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyncThruOutputTraySensor:
"""Implementation of a Samsung Printer input tray sensor platform."""
def __init__(self, syncthru, name, number):
"""Initialize the sensor."""
<|body_0|>
def update(self):
"""Get the latest data from SyncThru and update the state."""
... | stack_v2_sparse_classes_10k_train_006851 | 8,262 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, syncthru, name, number)"
},
{
"docstring": "Get the latest data from SyncThru and update the state.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | null | Implement the Python class `SyncThruOutputTraySensor` described below.
Class description:
Implementation of a Samsung Printer input tray sensor platform.
Method signatures and docstrings:
- def __init__(self, syncthru, name, number): Initialize the sensor.
- def update(self): Get the latest data from SyncThru and upd... | Implement the Python class `SyncThruOutputTraySensor` described below.
Class description:
Implementation of a Samsung Printer input tray sensor platform.
Method signatures and docstrings:
- def __init__(self, syncthru, name, number): Initialize the sensor.
- def update(self): Get the latest data from SyncThru and upd... | ed4ab403deaed9e8c95e0db728477fcb012bf4fa | <|skeleton|>
class SyncThruOutputTraySensor:
"""Implementation of a Samsung Printer input tray sensor platform."""
def __init__(self, syncthru, name, number):
"""Initialize the sensor."""
<|body_0|>
def update(self):
"""Get the latest data from SyncThru and update the state."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SyncThruOutputTraySensor:
"""Implementation of a Samsung Printer input tray sensor platform."""
def __init__(self, syncthru, name, number):
"""Initialize the sensor."""
super().__init__(syncthru, name)
self._name = f'{name} Output Tray {number}'
self._number = number
... | the_stack_v2_python_sparse | homeassistant/components/syncthru/sensor.py | tchellomello/home-assistant | train | 8 |
f406b36ad1b669abdba349279daccc8d4db6cc35 | [
"self.enabled = enabled\nself.last_updated_timestamp_secs = last_updated_timestamp_secs\nself.pinned_time_secs = pinned_time_secs",
"if dictionary is None:\n return None\nenabled = dictionary.get('enabled')\nlast_updated_timestamp_secs = dictionary.get('lastUpdatedTimestampSecs')\npinned_time_secs = dictionary... | <|body_start_0|>
self.enabled = enabled
self.last_updated_timestamp_secs = last_updated_timestamp_secs
self.pinned_time_secs = pinned_time_secs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
enabled = dictionary.get('enabled')
last_updated... | Implementation of the 'ViewPinningConfig' model. TODO: type description here. Attributes: enabled (bool, required): Specifies if view pinning is enabled. If set to true, view will be pinned to SSD. last_updated_timestamp_secs (long|int): Specifies the timestamp when view pinning config is last updated. pinned_time_secs... | ViewPinningConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViewPinningConfig:
"""Implementation of the 'ViewPinningConfig' model. TODO: type description here. Attributes: enabled (bool, required): Specifies if view pinning is enabled. If set to true, view will be pinned to SSD. last_updated_timestamp_secs (long|int): Specifies the timestamp when view pin... | stack_v2_sparse_classes_10k_train_006852 | 2,126 | permissive | [
{
"docstring": "Constructor for the ViewPinningConfig class",
"name": "__init__",
"signature": "def __init__(self, enabled=None, last_updated_timestamp_secs=None, pinned_time_secs=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dicti... | 2 | stack_v2_sparse_classes_30k_train_001009 | Implement the Python class `ViewPinningConfig` described below.
Class description:
Implementation of the 'ViewPinningConfig' model. TODO: type description here. Attributes: enabled (bool, required): Specifies if view pinning is enabled. If set to true, view will be pinned to SSD. last_updated_timestamp_secs (long|int)... | Implement the Python class `ViewPinningConfig` described below.
Class description:
Implementation of the 'ViewPinningConfig' model. TODO: type description here. Attributes: enabled (bool, required): Specifies if view pinning is enabled. If set to true, view will be pinned to SSD. last_updated_timestamp_secs (long|int)... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ViewPinningConfig:
"""Implementation of the 'ViewPinningConfig' model. TODO: type description here. Attributes: enabled (bool, required): Specifies if view pinning is enabled. If set to true, view will be pinned to SSD. last_updated_timestamp_secs (long|int): Specifies the timestamp when view pin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ViewPinningConfig:
"""Implementation of the 'ViewPinningConfig' model. TODO: type description here. Attributes: enabled (bool, required): Specifies if view pinning is enabled. If set to true, view will be pinned to SSD. last_updated_timestamp_secs (long|int): Specifies the timestamp when view pinning config i... | the_stack_v2_python_sparse | cohesity_management_sdk/models/view_pinning_config.py | cohesity/management-sdk-python | train | 24 |
b39795708d4d5963a24f4d4d564ecaca3d3cfd45 | [
"is_unenrolled_access_enabled = COURSE_ENABLE_UNENROLLED_ACCESS_FLAG.is_enabled(self.course_key)\nis_course_outline_publicly_visible = full_course_outline.course_visibility in [CourseVisibility.PUBLIC, CourseVisibility.PUBLIC_OUTLINE]\nif is_unenrolled_access_enabled and is_course_outline_publicly_visible:\n ret... | <|body_start_0|>
is_unenrolled_access_enabled = COURSE_ENABLE_UNENROLLED_ACCESS_FLAG.is_enabled(self.course_key)
is_course_outline_publicly_visible = full_course_outline.course_visibility in [CourseVisibility.PUBLIC, CourseVisibility.PUBLIC_OUTLINE]
if is_unenrolled_access_enabled and is_course_... | Simple OutlineProcessor that removes items based on Enrollment and course visibility setting. | EnrollmentOutlineProcessor | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnrollmentOutlineProcessor:
"""Simple OutlineProcessor that removes items based on Enrollment and course visibility setting."""
def usage_keys_to_remove(self, full_course_outline):
"""Return sequences/sections to be removed"""
<|body_0|>
def inaccessible_sequences(self, ... | stack_v2_sparse_classes_10k_train_006853 | 1,997 | permissive | [
{
"docstring": "Return sequences/sections to be removed",
"name": "usage_keys_to_remove",
"signature": "def usage_keys_to_remove(self, full_course_outline)"
},
{
"docstring": "Return a set/frozenset of Sequence UsageKeys that are not accessible.",
"name": "inaccessible_sequences",
"signa... | 2 | stack_v2_sparse_classes_30k_train_004823 | Implement the Python class `EnrollmentOutlineProcessor` described below.
Class description:
Simple OutlineProcessor that removes items based on Enrollment and course visibility setting.
Method signatures and docstrings:
- def usage_keys_to_remove(self, full_course_outline): Return sequences/sections to be removed
- d... | Implement the Python class `EnrollmentOutlineProcessor` described below.
Class description:
Simple OutlineProcessor that removes items based on Enrollment and course visibility setting.
Method signatures and docstrings:
- def usage_keys_to_remove(self, full_course_outline): Return sequences/sections to be removed
- d... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class EnrollmentOutlineProcessor:
"""Simple OutlineProcessor that removes items based on Enrollment and course visibility setting."""
def usage_keys_to_remove(self, full_course_outline):
"""Return sequences/sections to be removed"""
<|body_0|>
def inaccessible_sequences(self, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EnrollmentOutlineProcessor:
"""Simple OutlineProcessor that removes items based on Enrollment and course visibility setting."""
def usage_keys_to_remove(self, full_course_outline):
"""Return sequences/sections to be removed"""
is_unenrolled_access_enabled = COURSE_ENABLE_UNENROLLED_ACCESS... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/djangoapps/content/learning_sequences/api/processors/enrollment.py | luque/better-ways-of-thinking-about-software | train | 3 |
37eb6532ab3d33eaa04cc80491e77a523f1140b9 | [
"if fit_data is None and (a is None or b is None or c is None):\n raise ValueError('Either all the fit parameters or fit_data must be specified.')\nif not (fit_data is None or a is None or b is None or (c is None)):\n raise ValueError('Cannot specify fit parameters when fit_data is specified.')\nself.a = a\ns... | <|body_start_0|>
if fit_data is None and (a is None or b is None or c is None):
raise ValueError('Either all the fit parameters or fit_data must be specified.')
if not (fit_data is None or a is None or b is None or (c is None)):
raise ValueError('Cannot specify fit parameters whe... | Represents the Fundamental Plane (FP) relation between the velocity dispersion, luminosity, and effective radius for elliptical galaxies Luminosity is expressed as apparent magnitude in this form. | FundamentalPlane | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FundamentalPlane:
"""Represents the Fundamental Plane (FP) relation between the velocity dispersion, luminosity, and effective radius for elliptical galaxies Luminosity is expressed as apparent magnitude in this form."""
def __init__(self, a=None, b=None, c=None, intrinsic_scatter=0.0, fit_d... | stack_v2_sparse_classes_10k_train_006854 | 19,262 | permissive | [
{
"docstring": "Parameters ---------- a : float linear slope on the log velocity dispersion, log(vel_disp/(km/s)) b : float linear slope on the V-band apparent magnitude, or m_V/mag c : float intercept, i.e. the log effective radius, or log(R_eff/kpc), when vel_disp = m_V = 0 fit_data : str sample on which a, b... | 3 | stack_v2_sparse_classes_30k_train_005506 | Implement the Python class `FundamentalPlane` described below.
Class description:
Represents the Fundamental Plane (FP) relation between the velocity dispersion, luminosity, and effective radius for elliptical galaxies Luminosity is expressed as apparent magnitude in this form.
Method signatures and docstrings:
- def... | Implement the Python class `FundamentalPlane` described below.
Class description:
Represents the Fundamental Plane (FP) relation between the velocity dispersion, luminosity, and effective radius for elliptical galaxies Luminosity is expressed as apparent magnitude in this form.
Method signatures and docstrings:
- def... | 2a9a1b3eafbafef925bedab4b3137a3505a9b750 | <|skeleton|>
class FundamentalPlane:
"""Represents the Fundamental Plane (FP) relation between the velocity dispersion, luminosity, and effective radius for elliptical galaxies Luminosity is expressed as apparent magnitude in this form."""
def __init__(self, a=None, b=None, c=None, intrinsic_scatter=0.0, fit_d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FundamentalPlane:
"""Represents the Fundamental Plane (FP) relation between the velocity dispersion, luminosity, and effective radius for elliptical galaxies Luminosity is expressed as apparent magnitude in this form."""
def __init__(self, a=None, b=None, c=None, intrinsic_scatter=0.0, fit_data=None):
... | the_stack_v2_python_sparse | baobab/bnn_priors/parameter_models.py | jiwoncpark/baobab | train | 9 |
6ab402c694104d97453357e34ca5a7d75228dcf8 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | The MruV offers service. | MruVOffersServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MruVOffersServiceServicer:
"""The MruV offers service."""
def CreateOffer(self, request, context):
"""Create an offer."""
<|body_0|>
def GetOffer(self, request, context):
"""Get an offer."""
<|body_1|>
def UpdateOffer(self, request, context):
... | stack_v2_sparse_classes_10k_train_006855 | 8,788 | permissive | [
{
"docstring": "Create an offer.",
"name": "CreateOffer",
"signature": "def CreateOffer(self, request, context)"
},
{
"docstring": "Get an offer.",
"name": "GetOffer",
"signature": "def GetOffer(self, request, context)"
},
{
"docstring": "Update an offer.",
"name": "UpdateOff... | 5 | stack_v2_sparse_classes_30k_train_005187 | Implement the Python class `MruVOffersServiceServicer` described below.
Class description:
The MruV offers service.
Method signatures and docstrings:
- def CreateOffer(self, request, context): Create an offer.
- def GetOffer(self, request, context): Get an offer.
- def UpdateOffer(self, request, context): Update an o... | Implement the Python class `MruVOffersServiceServicer` described below.
Class description:
The MruV offers service.
Method signatures and docstrings:
- def CreateOffer(self, request, context): Create an offer.
- def GetOffer(self, request, context): Get an offer.
- def UpdateOffer(self, request, context): Update an o... | 2a640f7667d23f39e50ccc9ba73c98138c6839b5 | <|skeleton|>
class MruVOffersServiceServicer:
"""The MruV offers service."""
def CreateOffer(self, request, context):
"""Create an offer."""
<|body_0|>
def GetOffer(self, request, context):
"""Get an offer."""
<|body_1|>
def UpdateOffer(self, request, context):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MruVOffersServiceServicer:
"""The MruV offers service."""
def CreateOffer(self, request, context):
"""Create an offer."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
... | the_stack_v2_python_sparse | offers/offers_pb2_grpc.py | MruV-RP/mruv-pb_python | train | 0 |
e53fa32c6f7514d55befe19faf7765d0c2746ca9 | [
"first, last = (0, len(nums) - 1)\nwhile first < last:\n if nums[first] % 2 == 1:\n first += 1\n continue\n if nums[last] % 2 == 0:\n last -= 1\n continue\n nums[first], nums[last] = (nums[last], nums[first])\nreturn nums",
"low = fast = 0\nwhile fast < len(nums):\n if nums... | <|body_start_0|>
first, last = (0, len(nums) - 1)
while first < last:
if nums[first] % 2 == 1:
first += 1
continue
if nums[last] % 2 == 0:
last -= 1
continue
nums[first], nums[last] = (nums[last], nums[fi... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def exchange(self, nums: List[int]) -> List[int]:
"""前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)"""
<|body_0|>
def exchange_2(self, nums: List[int]) -> List[int]:
"""快慢双指针法 low与fast同时从首位移动，fast 的作用是向前搜索奇数位置，low 的作用是指向下一个奇数应当存放的位置 时间复杂度：O(n)... | stack_v2_sparse_classes_10k_train_006856 | 2,049 | no_license | [
{
"docstring": "前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)",
"name": "exchange",
"signature": "def exchange(self, nums: List[int]) -> List[int]"
},
{
"docstring": "快慢双指针法 low与fast同时从首位移动，fast 的作用是向前搜索奇数位置，low 的作用是指向下一个奇数应当存放的位置 时间复杂度：O(n) 空间复杂度：O(1)",
"name": "exchange_2",
... | 2 | stack_v2_sparse_classes_30k_train_000380 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def exchange(self, nums: List[int]) -> List[int]: 前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)
- def exchange_2(self, nums: List[int]) -> List[int]: 快慢双指针法 low与fa... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def exchange(self, nums: List[int]) -> List[int]: 前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)
- def exchange_2(self, nums: List[int]) -> List[int]: 快慢双指针法 low与fa... | c92a5ddcc56e3f69be1e6fb25e9c8ed277e57ee0 | <|skeleton|>
class Solution:
def exchange(self, nums: List[int]) -> List[int]:
"""前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)"""
<|body_0|>
def exchange_2(self, nums: List[int]) -> List[int]:
"""快慢双指针法 low与fast同时从首位移动，fast 的作用是向前搜索奇数位置，low 的作用是指向下一个奇数应当存放的位置 时间复杂度：O(n)... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def exchange(self, nums: List[int]) -> List[int]:
"""前后双指针法 first指向第一个，last指向最后一个，两个指针向中间靠拢 时间复杂度：O(n) 空间复杂度：O(1)"""
first, last = (0, len(nums) - 1)
while first < last:
if nums[first] % 2 == 1:
first += 1
continue
if nu... | the_stack_v2_python_sparse | SwordOffer/SwordOffer_21.py | EachenKuang/LeetCode | train | 28 | |
8d8fffdc351023aa2ebd3667b1db3d381da4a3a2 | [
"encoded_str = []\nfor word in strs:\n encoded_str.append(str(len(word)))\n encoded_str.append('/')\n encoded_str.append(word)\nreturn ''.join(encoded_str)",
"words = []\ni = 0\nwhile i < len(s):\n slash_index = s.find('/', i)\n size = int(s[i:slash_index])\n words.append(s[slash_index + 1:slash... | <|body_start_0|>
encoded_str = []
for word in strs:
encoded_str.append(str(len(word)))
encoded_str.append('/')
encoded_str.append(word)
return ''.join(encoded_str)
<|end_body_0|>
<|body_start_1|>
words = []
i = 0
while i < len(s):
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k_train_006857 | 1,009 | no_license | [
{
"docstring": "Encodes a list of strings to a single string. :type strs: List[str] :rtype: str",
"name": "encode",
"signature": "def encode(self, strs)"
},
{
"docstring": "Decodes a single string to a list of strings. :type s: str :rtype: List[str]",
"name": "decode",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_val_000284 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | 9d0ff0f8705451947a6605ab5ef92bb3e27a7147 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
encoded_str = []
for word in strs:
encoded_str.append(str(len(word)))
encoded_str.append('/')
encoded_str.append(word)
return... | the_stack_v2_python_sparse | string/encode_and_decode_strings.py | rayt579/leetcode | train | 0 | |
c4fab6e502614afd2570fdaa365faea9999fc206 | [
"ForwardingRulesMutator.Args(parser)\ntarget = parser.add_mutually_exclusive_group(required=True)\ntarget_instance = target.add_argument('--target-instance', help='The target instance that will receive the traffic.')\ntarget_instance.detailed_help = textwrap.dedent(\" The name of the target instance that wil... | <|body_start_0|>
ForwardingRulesMutator.Args(parser)
target = parser.add_mutually_exclusive_group(required=True)
target_instance = target.add_argument('--target-instance', help='The target instance that will receive the traffic.')
target_instance.detailed_help = textwrap.dedent(" ... | Base class for modifying forwarding rule targets. | ForwardingRulesTargetMutator | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForwardingRulesTargetMutator:
"""Base class for modifying forwarding rule targets."""
def Args(parser, include_beta_targets):
"""Adds common flags for mutating forwarding rule targets."""
<|body_0|>
def GetGlobalTarget(self, args):
"""Return the forwarding target... | stack_v2_sparse_classes_10k_train_006858 | 5,788 | permissive | [
{
"docstring": "Adds common flags for mutating forwarding rule targets.",
"name": "Args",
"signature": "def Args(parser, include_beta_targets)"
},
{
"docstring": "Return the forwarding target for a globally scoped request.",
"name": "GetGlobalTarget",
"signature": "def GetGlobalTarget(se... | 3 | null | Implement the Python class `ForwardingRulesTargetMutator` described below.
Class description:
Base class for modifying forwarding rule targets.
Method signatures and docstrings:
- def Args(parser, include_beta_targets): Adds common flags for mutating forwarding rule targets.
- def GetGlobalTarget(self, args): Return ... | Implement the Python class `ForwardingRulesTargetMutator` described below.
Class description:
Base class for modifying forwarding rule targets.
Method signatures and docstrings:
- def Args(parser, include_beta_targets): Adds common flags for mutating forwarding rule targets.
- def GetGlobalTarget(self, args): Return ... | d379afa2db3582d5c3be652165f0e9e2e0c154c6 | <|skeleton|>
class ForwardingRulesTargetMutator:
"""Base class for modifying forwarding rule targets."""
def Args(parser, include_beta_targets):
"""Adds common flags for mutating forwarding rule targets."""
<|body_0|>
def GetGlobalTarget(self, args):
"""Return the forwarding target... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ForwardingRulesTargetMutator:
"""Base class for modifying forwarding rule targets."""
def Args(parser, include_beta_targets):
"""Adds common flags for mutating forwarding rule targets."""
ForwardingRulesMutator.Args(parser)
target = parser.add_mutually_exclusive_group(required=Tru... | the_stack_v2_python_sparse | y/google-cloud-sdk/lib/googlecloudsdk/compute/lib/forwarding_rules_utils.py | ychen820/microblog | train | 0 |
7d696327500cc75771d42822ae7a22e282acbbe8 | [
"try:\n assert init_ad_manage.get_title() == '广告管理'\n assert '广告管理' in init_ad_manage.get_info_title()\nexcept Exception as e:\n raise e",
"init_search_ad[0].search_ad(ad.api_ad_name)\ntry:\n assert ad.api_ad_name in init_search_ad[0].get_ad_name()\n assert init_search_ad[0].get_status() == 'el-swi... | <|body_start_0|>
try:
assert init_ad_manage.get_title() == '广告管理'
assert '广告管理' in init_ad_manage.get_info_title()
except Exception as e:
raise e
<|end_body_0|>
<|body_start_1|>
init_search_ad[0].search_ad(ad.api_ad_name)
try:
assert ad.ap... | 广告管理 | TestAd | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAd:
"""广告管理"""
def test01_title_name(self, init_ad_manage):
"""网页标题校验 :return:"""
<|body_0|>
def test02_search_ad(self, init_search_ad):
"""广告名称搜索 :return:"""
<|body_1|>
def test03_add_ad(self, init_ad_manage):
"""新增广告 :return:"""
... | stack_v2_sparse_classes_10k_train_006859 | 1,641 | no_license | [
{
"docstring": "网页标题校验 :return:",
"name": "test01_title_name",
"signature": "def test01_title_name(self, init_ad_manage)"
},
{
"docstring": "广告名称搜索 :return:",
"name": "test02_search_ad",
"signature": "def test02_search_ad(self, init_search_ad)"
},
{
"docstring": "新增广告 :return:",
... | 4 | stack_v2_sparse_classes_30k_train_000882 | Implement the Python class `TestAd` described below.
Class description:
广告管理
Method signatures and docstrings:
- def test01_title_name(self, init_ad_manage): 网页标题校验 :return:
- def test02_search_ad(self, init_search_ad): 广告名称搜索 :return:
- def test03_add_ad(self, init_ad_manage): 新增广告 :return:
- def test04_del_ad(self,... | Implement the Python class `TestAd` described below.
Class description:
广告管理
Method signatures and docstrings:
- def test01_title_name(self, init_ad_manage): 网页标题校验 :return:
- def test02_search_ad(self, init_search_ad): 广告名称搜索 :return:
- def test03_add_ad(self, init_ad_manage): 新增广告 :return:
- def test04_del_ad(self,... | b6905b765d84263439e459d6281cd2440e634cef | <|skeleton|>
class TestAd:
"""广告管理"""
def test01_title_name(self, init_ad_manage):
"""网页标题校验 :return:"""
<|body_0|>
def test02_search_ad(self, init_search_ad):
"""广告名称搜索 :return:"""
<|body_1|>
def test03_add_ad(self, init_ad_manage):
"""新增广告 :return:"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestAd:
"""广告管理"""
def test01_title_name(self, init_ad_manage):
"""网页标题校验 :return:"""
try:
assert init_ad_manage.get_title() == '广告管理'
assert '广告管理' in init_ad_manage.get_info_title()
except Exception as e:
raise e
def test02_search_ad(self... | the_stack_v2_python_sparse | TestCases/test_05_ad_page.py | Dake-M/boss_web_framework | train | 0 |
aad0bf99b79d76a1c8563c40a4dd035058c8ae4f | [
"add_failed = kwargs.get('add_failed', False)\nadd_succeeded = kwargs.get('add_succeeded', False)\nbook_list = get_object_or_404(models.List, id=list_id)\nbook_list.raise_visible_to_user(request.user)\nif is_api_request(request):\n return ActivitypubResponse(book_list.to_activity(**request.GET))\nif (redirect_op... | <|body_start_0|>
add_failed = kwargs.get('add_failed', False)
add_succeeded = kwargs.get('add_succeeded', False)
book_list = get_object_or_404(models.List, id=list_id)
book_list.raise_visible_to_user(request.user)
if is_api_request(request):
return ActivitypubResponse... | book list page | List | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class List:
"""book list page"""
def get(self, request, list_id, **kwargs):
"""display a book list"""
<|body_0|>
def post(self, request, list_id):
"""edit a list"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
add_failed = kwargs.get('add_failed', Fal... | stack_v2_sparse_classes_10k_train_006860 | 11,267 | no_license | [
{
"docstring": "display a book list",
"name": "get",
"signature": "def get(self, request, list_id, **kwargs)"
},
{
"docstring": "edit a list",
"name": "post",
"signature": "def post(self, request, list_id)"
}
] | 2 | null | Implement the Python class `List` described below.
Class description:
book list page
Method signatures and docstrings:
- def get(self, request, list_id, **kwargs): display a book list
- def post(self, request, list_id): edit a list | Implement the Python class `List` described below.
Class description:
book list page
Method signatures and docstrings:
- def get(self, request, list_id, **kwargs): display a book list
- def post(self, request, list_id): edit a list
<|skeleton|>
class List:
"""book list page"""
def get(self, request, list_id... | 0f8da5b738047f3c34d60d93f59bdedd8f797224 | <|skeleton|>
class List:
"""book list page"""
def get(self, request, list_id, **kwargs):
"""display a book list"""
<|body_0|>
def post(self, request, list_id):
"""edit a list"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class List:
"""book list page"""
def get(self, request, list_id, **kwargs):
"""display a book list"""
add_failed = kwargs.get('add_failed', False)
add_succeeded = kwargs.get('add_succeeded', False)
book_list = get_object_or_404(models.List, id=list_id)
book_list.raise_vi... | the_stack_v2_python_sparse | bookwyrm/views/list/list.py | bookwyrm-social/bookwyrm | train | 1,398 |
362de0a7a2e1ac1a68f0152e50cdf6d41c3b7598 | [
"self.host = host\nself.username = username\nself.password = password\nself.to_emails = to_emails\nself.subject = subject\nself.content = content",
"msgRoot = MIMEMultipart('related')\nmsgRoot['Subject'] = self.subject\nmsgRoot['From'] = self.username\nmsgRoot['To'] = ','.join(self.to_emails)\nmsgRoot['Date'] = e... | <|body_start_0|>
self.host = host
self.username = username
self.password = password
self.to_emails = to_emails
self.subject = subject
self.content = content
<|end_body_0|>
<|body_start_1|>
msgRoot = MIMEMultipart('related')
msgRoot['Subject'] = self.subje... | MailSender | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailSender:
def __init__(self, host, username, password, to_emails, subject, content):
"""初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param title 标题 @param content 内容"""
<|body_0|>
def send_mail(self):
"""发送邮件"""
... | stack_v2_sparse_classes_10k_train_006861 | 2,042 | permissive | [
{
"docstring": "初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param title 标题 @param content 内容",
"name": "__init__",
"signature": "def __init__(self, host, username, password, to_emails, subject, content)"
},
{
"docstring": "发送邮件",
"name": "send_m... | 2 | stack_v2_sparse_classes_30k_train_005871 | Implement the Python class `MailSender` described below.
Class description:
Implement the MailSender class.
Method signatures and docstrings:
- def __init__(self, host, username, password, to_emails, subject, content): 初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param ti... | Implement the Python class `MailSender` described below.
Class description:
Implement the MailSender class.
Method signatures and docstrings:
- def __init__(self, host, username, password, to_emails, subject, content): 初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param ti... | 931fca8fab9d7397c52cf9e76a76b1c60e190403 | <|skeleton|>
class MailSender:
def __init__(self, host, username, password, to_emails, subject, content):
"""初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param title 标题 @param content 内容"""
<|body_0|>
def send_mail(self):
"""发送邮件"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MailSender:
def __init__(self, host, username, password, to_emails, subject, content):
"""初始化 @param host 邮件服务端host @param username 用户名 @param password 密码 @param to_emails 发送到邮箱列表 @param title 标题 @param content 内容"""
self.host = host
self.username = username
self.password = pas... | the_stack_v2_python_sparse | src/utils/send_email.py | Karmenzind/fp-server | train | 180 | |
820fbc8c0f80aef66fee06ac927ec4a4e7525741 | [
"supported_hashes = ', '.join(cls._SUPPORTED_HASHES)\nargument_group.add_argument('--viper-hash', '--viper_hash', dest='viper_hash', type=str, action='store', choices=cls._SUPPORTED_HASHES, default=cls._DEFAULT_HASH, metavar='HASH', help=f'Type of hash to use to query the Viper server, the default is: {cls._DEFAULT... | <|body_start_0|>
supported_hashes = ', '.join(cls._SUPPORTED_HASHES)
argument_group.add_argument('--viper-hash', '--viper_hash', dest='viper_hash', type=str, action='store', choices=cls._SUPPORTED_HASHES, default=cls._DEFAULT_HASH, metavar='HASH', help=f'Type of hash to use to query the Viper server, th... | Viper analysis plugin CLI arguments helper. | ViperAnalysisArgumentsHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViperAnalysisArgumentsHelper:
"""Viper analysis plugin CLI arguments helper."""
def AddArguments(cls, argument_group):
"""Adds command line arguments the helper supports to an argument group. This function takes an argument parser or an argument group object and adds to it all the co... | stack_v2_sparse_classes_10k_train_006862 | 4,018 | permissive | [
{
"docstring": "Adds command line arguments the helper supports to an argument group. This function takes an argument parser or an argument group object and adds to it all the command line arguments this helper supports. Args: argument_group (argparse._ArgumentGroup|argparse.ArgumentParser): argparse group.",
... | 2 | stack_v2_sparse_classes_30k_train_007254 | Implement the Python class `ViperAnalysisArgumentsHelper` described below.
Class description:
Viper analysis plugin CLI arguments helper.
Method signatures and docstrings:
- def AddArguments(cls, argument_group): Adds command line arguments the helper supports to an argument group. This function takes an argument par... | Implement the Python class `ViperAnalysisArgumentsHelper` described below.
Class description:
Viper analysis plugin CLI arguments helper.
Method signatures and docstrings:
- def AddArguments(cls, argument_group): Adds command line arguments the helper supports to an argument group. This function takes an argument par... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class ViperAnalysisArgumentsHelper:
"""Viper analysis plugin CLI arguments helper."""
def AddArguments(cls, argument_group):
"""Adds command line arguments the helper supports to an argument group. This function takes an argument parser or an argument group object and adds to it all the co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ViperAnalysisArgumentsHelper:
"""Viper analysis plugin CLI arguments helper."""
def AddArguments(cls, argument_group):
"""Adds command line arguments the helper supports to an argument group. This function takes an argument parser or an argument group object and adds to it all the command line ar... | the_stack_v2_python_sparse | plaso/cli/helpers/viper_analysis.py | log2timeline/plaso | train | 1,506 |
019acd180f9ea97c0406f9698e498a47565b3660 | [
"super().__init__()\nself.beta = nn.Parameter(torch.tensor(0.0, dtype=torch.float))\nself.score_no_click = nn.Parameter(torch.tensor(0.0, dtype=torch.float))",
"batch_size = user.shape[0]\ns = torch.einsum('be,bde->bd', user, doc)\ns = s * self.beta\ns = torch.cat([s, self.score_no_click.expand((batch_size, 1))],... | <|body_start_0|>
super().__init__()
self.beta = nn.Parameter(torch.tensor(0.0, dtype=torch.float))
self.score_no_click = nn.Parameter(torch.tensor(0.0, dtype=torch.float))
<|end_body_0|>
<|body_start_1|>
batch_size = user.shape[0]
s = torch.einsum('be,bde->bd', user, doc)
... | The user choice model for SlateQ. This class implements a multinomial logit model for predicting user clicks. Under this model, the click probability of a document is proportional to: .. math:: \\exp( ext{beta} * ext{doc_user_affinity} + ext{score_no_click}) | UserChoiceModel | [
"MIT",
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserChoiceModel:
"""The user choice model for SlateQ. This class implements a multinomial logit model for predicting user clicks. Under this model, the click probability of a document is proportional to: .. math:: \\exp( ext{beta} * ext{doc_user_affinity} + ext{score_no_click})"""
def __init... | stack_v2_sparse_classes_10k_train_006863 | 6,840 | permissive | [
{
"docstring": "Initializes a UserChoiceModel instance.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Evaluate the user choice model. This function outputs user click scores for candidate documents. The exponentials of these scores are proportional user click probabi... | 2 | stack_v2_sparse_classes_30k_test_000329 | Implement the Python class `UserChoiceModel` described below.
Class description:
The user choice model for SlateQ. This class implements a multinomial logit model for predicting user clicks. Under this model, the click probability of a document is proportional to: .. math:: \\exp( ext{beta} * ext{doc_user_affinity} + ... | Implement the Python class `UserChoiceModel` described below.
Class description:
The user choice model for SlateQ. This class implements a multinomial logit model for predicting user clicks. Under this model, the click probability of a document is proportional to: .. math:: \\exp( ext{beta} * ext{doc_user_affinity} + ... | edba68c3e7cf255d1d6479329f305adb7fa4c3ed | <|skeleton|>
class UserChoiceModel:
"""The user choice model for SlateQ. This class implements a multinomial logit model for predicting user clicks. Under this model, the click probability of a document is proportional to: .. math:: \\exp( ext{beta} * ext{doc_user_affinity} + ext{score_no_click})"""
def __init... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserChoiceModel:
"""The user choice model for SlateQ. This class implements a multinomial logit model for predicting user clicks. Under this model, the click probability of a document is proportional to: .. math:: \\exp( ext{beta} * ext{doc_user_affinity} + ext{score_no_click})"""
def __init__(self):
... | the_stack_v2_python_sparse | rllib/algorithms/slateq/slateq_torch_model.py | ray-project/ray | train | 29,482 |
403b4b9ba23ba10354f7848c7a985f2d35c59b54 | [
"summaries = []\nselector = '#ae-content tr'\nrows = self.doc.cssselect(selector)\nassert len(rows)\nfor row in rows:\n children = list(row)\n assert len(children) == 5, [child.text for child in children]\n summaries.append({'appengine_release': Value.from_str(text(children[0])), 'total_instances': Value.f... | <|body_start_0|>
summaries = []
selector = '#ae-content tr'
rows = self.doc.cssselect(selector)
assert len(rows)
for row in rows:
children = list(row)
assert len(children) == 5, [child.text for child in children]
summaries.append({'appengine_re... | An API for the contents of /instance_summary as structured data. | InstanceSummary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceSummary:
"""An API for the contents of /instance_summary as structured data."""
def summaries(self):
"""Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like these, where value is a Value instance whose .text() is shown... | stack_v2_sparse_classes_10k_train_006864 | 15,505 | no_license | [
{
"docstring": "Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like these, where value is a Value instance whose .text() is shown as an example: [{'appengine_release': '1.9.2', 'total_instances': '100 total', 'average_qps': '2.243', 'average_latency': '... | 2 | stack_v2_sparse_classes_30k_train_006754 | Implement the Python class `InstanceSummary` described below.
Class description:
An API for the contents of /instance_summary as structured data.
Method signatures and docstrings:
- def summaries(self): Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like thes... | Implement the Python class `InstanceSummary` described below.
Class description:
An API for the contents of /instance_summary as structured data.
Method signatures and docstrings:
- def summaries(self): Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like thes... | c4ad2ad67b497ce411a9e5d6d6db407ee304491f | <|skeleton|>
class InstanceSummary:
"""An API for the contents of /instance_summary as structured data."""
def summaries(self):
"""Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like these, where value is a Value instance whose .text() is shown... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InstanceSummary:
"""An API for the contents of /instance_summary as structured data."""
def summaries(self):
"""Performance statistics summarized by App Engine release. Returns: A list of one or more dicts with fields like these, where value is a Value instance whose .text() is shown as an exampl... | the_stack_v2_python_sparse | src/gae_dashboard/parsers.py | summer-liu/analytics | train | 1 |
061a058fffce77b9c6c92eaa0c6bce66261fcb2e | [
"self.sent_id_map = {str_i.lower(): i + 1 for i, str_i in enumerate(sentence_ids)}\nself.EOD_index = len(self.sent_id_map)\nself.max_doc_length = max_doc_length + 1\nself.max_sent_length = None\nself.PAD_index = 0",
"numeric_context_docs = []\nfor doc in documents:\n doc = doc.split(' ')\n doc = [self.sent_... | <|body_start_0|>
self.sent_id_map = {str_i.lower(): i + 1 for i, str_i in enumerate(sentence_ids)}
self.EOD_index = len(self.sent_id_map)
self.max_doc_length = max_doc_length + 1
self.max_sent_length = None
self.PAD_index = 0
<|end_body_0|>
<|body_start_1|>
numeric_conte... | Creates numerical representations as input for the CIM model | Processor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Processor:
"""Creates numerical representations as input for the CIM model"""
def __init__(self, sentence_ids, max_doc_length):
"""Stores indexes of sentences, End-of-Sentence index, maximum document and sentence length, and pad index."""
<|body_0|>
def to_numeric_docume... | stack_v2_sparse_classes_10k_train_006865 | 21,540 | no_license | [
{
"docstring": "Stores indexes of sentences, End-of-Sentence index, maximum document and sentence length, and pad index.",
"name": "__init__",
"signature": "def __init__(self, sentence_ids, max_doc_length)"
},
{
"docstring": "Creates numerical representations (sentence ids) for documents (= arti... | 3 | stack_v2_sparse_classes_30k_train_003744 | Implement the Python class `Processor` described below.
Class description:
Creates numerical representations as input for the CIM model
Method signatures and docstrings:
- def __init__(self, sentence_ids, max_doc_length): Stores indexes of sentences, End-of-Sentence index, maximum document and sentence length, and pa... | Implement the Python class `Processor` described below.
Class description:
Creates numerical representations as input for the CIM model
Method signatures and docstrings:
- def __init__(self, sentence_ids, max_doc_length): Stores indexes of sentences, End-of-Sentence index, maximum document and sentence length, and pa... | 400bfa885ddbbc5f1d7c40d3a9e9df37ecc81dc9 | <|skeleton|>
class Processor:
"""Creates numerical representations as input for the CIM model"""
def __init__(self, sentence_ids, max_doc_length):
"""Stores indexes of sentences, End-of-Sentence index, maximum document and sentence length, and pad index."""
<|body_0|>
def to_numeric_docume... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Processor:
"""Creates numerical representations as input for the CIM model"""
def __init__(self, sentence_ids, max_doc_length):
"""Stores indexes of sentences, End-of-Sentence index, maximum document and sentence length, and pad index."""
self.sent_id_map = {str_i.lower(): i + 1 for i, st... | the_stack_v2_python_sparse | experiments/context_inclusive_model.py | vdenberg/context-in-informational-bias-detection | train | 3 |
1cbd42a9439d8a0ae321d906befc6e48993ecb12 | [
"im = cv2.imread('sample_images/exam_1.jpg')\nis_success, im_buf_arr = cv2.imencode('.jpg', im)\nbyte_im = im_buf_arr.tobytes()\nresult = conn.insert_values_test(age=20, gender=1, handedness=1, image=byte_im)\nself.assertEqual(type(result), int, 'Checking output type.')\nself.assertNotEqual(result, 0, 'Incorrect da... | <|body_start_0|>
im = cv2.imread('sample_images/exam_1.jpg')
is_success, im_buf_arr = cv2.imencode('.jpg', im)
byte_im = im_buf_arr.tobytes()
result = conn.insert_values_test(age=20, gender=1, handedness=1, image=byte_im)
self.assertEqual(type(result), int, 'Checking output type.... | Class to test mysql_connection. | MysqlConnectionTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MysqlConnectionTest:
"""Class to test mysql_connection."""
def test_insert_values_test(self):
"""Method to test insert_values_test method in mysql_connection."""
<|body_0|>
def test_insert_result_test_image(self):
"""Method to test insert_values_test_image method... | stack_v2_sparse_classes_10k_train_006866 | 5,327 | no_license | [
{
"docstring": "Method to test insert_values_test method in mysql_connection.",
"name": "test_insert_values_test",
"signature": "def test_insert_values_test(self)"
},
{
"docstring": "Method to test insert_values_test_image method in mysql_connection.",
"name": "test_insert_result_test_image"... | 4 | stack_v2_sparse_classes_30k_train_001766 | Implement the Python class `MysqlConnectionTest` described below.
Class description:
Class to test mysql_connection.
Method signatures and docstrings:
- def test_insert_values_test(self): Method to test insert_values_test method in mysql_connection.
- def test_insert_result_test_image(self): Method to test insert_val... | Implement the Python class `MysqlConnectionTest` described below.
Class description:
Class to test mysql_connection.
Method signatures and docstrings:
- def test_insert_values_test(self): Method to test insert_values_test method in mysql_connection.
- def test_insert_result_test_image(self): Method to test insert_val... | b4943fea82483c6910694d7c4c40e3715f65c3b5 | <|skeleton|>
class MysqlConnectionTest:
"""Class to test mysql_connection."""
def test_insert_values_test(self):
"""Method to test insert_values_test method in mysql_connection."""
<|body_0|>
def test_insert_result_test_image(self):
"""Method to test insert_values_test_image method... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MysqlConnectionTest:
"""Class to test mysql_connection."""
def test_insert_values_test(self):
"""Method to test insert_values_test method in mysql_connection."""
im = cv2.imread('sample_images/exam_1.jpg')
is_success, im_buf_arr = cv2.imencode('.jpg', im)
byte_im = im_buf_... | the_stack_v2_python_sparse | Backend/DetectPD/test_mysql_connection.py | RadhikaRanasinghe/Meraki | train | 5 |
31c7d54cb2ebf974366c31050cedde8cf2113d27 | [
"super(Funnel, self).__init__()\nself.conv_funnel = nn.Conv2d(in_channels, in_channels, 3, 1, 1, groups=in_channels)\nself.bn_funnel = nn.BatchNorm2d(in_channels)",
"tau = self.conv_funnel(input)\ntau = self.bn_funnel(tau)\noutput = torch.max(input, tau)\nreturn output"
] | <|body_start_0|>
super(Funnel, self).__init__()
self.conv_funnel = nn.Conv2d(in_channels, in_channels, 3, 1, 1, groups=in_channels)
self.bn_funnel = nn.BatchNorm2d(in_channels)
<|end_body_0|>
<|body_start_1|>
tau = self.conv_funnel(input)
tau = self.bn_funnel(tau)
output... | Funnel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Funnel:
def __init__(self, in_channels):
"""Init method."""
<|body_0|>
def forward(self, input):
"""Forward pass of the function"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(Funnel, self).__init__()
self.conv_funnel = nn.Conv2d(in_c... | stack_v2_sparse_classes_10k_train_006867 | 32,265 | no_license | [
{
"docstring": "Init method.",
"name": "__init__",
"signature": "def __init__(self, in_channels)"
},
{
"docstring": "Forward pass of the function",
"name": "forward",
"signature": "def forward(self, input)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000025 | Implement the Python class `Funnel` described below.
Class description:
Implement the Funnel class.
Method signatures and docstrings:
- def __init__(self, in_channels): Init method.
- def forward(self, input): Forward pass of the function | Implement the Python class `Funnel` described below.
Class description:
Implement the Funnel class.
Method signatures and docstrings:
- def __init__(self, in_channels): Init method.
- def forward(self, input): Forward pass of the function
<|skeleton|>
class Funnel:
def __init__(self, in_channels):
"""In... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class Funnel:
def __init__(self, in_channels):
"""Init method."""
<|body_0|>
def forward(self, input):
"""Forward pass of the function"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Funnel:
def __init__(self, in_channels):
"""Init method."""
super(Funnel, self).__init__()
self.conv_funnel = nn.Conv2d(in_channels, in_channels, 3, 1, 1, groups=in_channels)
self.bn_funnel = nn.BatchNorm2d(in_channels)
def forward(self, input):
"""Forward pass of ... | the_stack_v2_python_sparse | generated/test_digantamisra98_Echo.py | jansel/pytorch-jit-paritybench | train | 35 | |
69d16ae20e4310f10b9ae804afebc7875377f2a9 | [
"logger.debug('Visiting %s', self.novel_url)\nsoup = self.get_soup(self.novel_url)\nself.novel_title = soup.select_one('.desc h5').text\nlogger.info('Novel title: %s', self.novel_title)\nself.novel_cover = self.absolute_url(soup.select_one('.about-author .row img')['src'])\nlogger.info('Novel cover: %s', self.novel... | <|body_start_0|>
logger.debug('Visiting %s', self.novel_url)
soup = self.get_soup(self.novel_url)
self.novel_title = soup.select_one('.desc h5').text
logger.info('Novel title: %s', self.novel_title)
self.novel_cover = self.absolute_url(soup.select_one('.about-author .row img')['s... | MachineNovelTrans | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MachineNovelTrans:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
<|body_0|>
def download_chapter_body(self, chapter):
"""Download body of a single chapter and return as clean html format."""
<|body_1|>
def format_text(self, text):
... | stack_v2_sparse_classes_10k_train_006868 | 2,664 | permissive | [
{
"docstring": "Get novel title, autor, cover etc",
"name": "read_novel_info",
"signature": "def read_novel_info(self)"
},
{
"docstring": "Download body of a single chapter and return as clean html format.",
"name": "download_chapter_body",
"signature": "def download_chapter_body(self, c... | 3 | stack_v2_sparse_classes_30k_train_000989 | Implement the Python class `MachineNovelTrans` described below.
Class description:
Implement the MachineNovelTrans class.
Method signatures and docstrings:
- def read_novel_info(self): Get novel title, autor, cover etc
- def download_chapter_body(self, chapter): Download body of a single chapter and return as clean h... | Implement the Python class `MachineNovelTrans` described below.
Class description:
Implement the MachineNovelTrans class.
Method signatures and docstrings:
- def read_novel_info(self): Get novel title, autor, cover etc
- def download_chapter_body(self, chapter): Download body of a single chapter and return as clean h... | 451e816ab03c8466be90f6f0b3eaa52d799140ce | <|skeleton|>
class MachineNovelTrans:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
<|body_0|>
def download_chapter_body(self, chapter):
"""Download body of a single chapter and return as clean html format."""
<|body_1|>
def format_text(self, text):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MachineNovelTrans:
def read_novel_info(self):
"""Get novel title, autor, cover etc"""
logger.debug('Visiting %s', self.novel_url)
soup = self.get_soup(self.novel_url)
self.novel_title = soup.select_one('.desc h5').text
logger.info('Novel title: %s', self.novel_title)
... | the_stack_v2_python_sparse | lncrawl/sources/machinetrans.py | NNTin/lightnovel-crawler | train | 2 | |
dfb6dffb0f177d15b329a7ec41cdbdf6521be772 | [
"try:\n serializer = RadiologistPmtSerializers(RadiologistPmt.objects.all(), many=True)\n return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)\nexcept Exception as e:\n info_message = 'Internal Server Error'\n logger.error(info_message, e)\n return JsonResponse({'error'... | <|body_start_0|>
try:
serializer = RadiologistPmtSerializers(RadiologistPmt.objects.all(), many=True)
return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)
except Exception as e:
info_message = 'Internal Server Error'
logger.e... | RadiologistPmtView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RadiologistPmtView:
def get(self, request):
"""Get all Radiologist_Payment"""
<|body_0|>
def post(self, request):
"""Save Radiologist data"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
serializer = RadiologistPmtSerializers(Radiol... | stack_v2_sparse_classes_10k_train_006869 | 31,833 | no_license | [
{
"docstring": "Get all Radiologist_Payment",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Save Radiologist data",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001536 | Implement the Python class `RadiologistPmtView` described below.
Class description:
Implement the RadiologistPmtView class.
Method signatures and docstrings:
- def get(self, request): Get all Radiologist_Payment
- def post(self, request): Save Radiologist data | Implement the Python class `RadiologistPmtView` described below.
Class description:
Implement the RadiologistPmtView class.
Method signatures and docstrings:
- def get(self, request): Get all Radiologist_Payment
- def post(self, request): Save Radiologist data
<|skeleton|>
class RadiologistPmtView:
def get(self... | b63849983a592fd6a1f654191020fd86aa0787ae | <|skeleton|>
class RadiologistPmtView:
def get(self, request):
"""Get all Radiologist_Payment"""
<|body_0|>
def post(self, request):
"""Save Radiologist data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RadiologistPmtView:
def get(self, request):
"""Get all Radiologist_Payment"""
try:
serializer = RadiologistPmtSerializers(RadiologistPmt.objects.all(), many=True)
return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)
except Exceptio... | the_stack_v2_python_sparse | radiologist/views.py | RupeshKurlekar/biocare | train | 1 | |
84afd4eb2a6ea027dde53cc27aedbde599f8c9b8 | [
"aicpu_file_path = os.path.join(self._profiling_dir, self._file_name_aicpu_time.format(self._device_id))\naicpu_file_path = validate_and_normalize_path(aicpu_file_path, raise_key='Invalid aicpu file path.')\nif not os.path.isfile(aicpu_file_path):\n logger.warning('The file <%s> does not exist.', aicpu_file_path... | <|body_start_0|>
aicpu_file_path = os.path.join(self._profiling_dir, self._file_name_aicpu_time.format(self._device_id))
aicpu_file_path = validate_and_normalize_path(aicpu_file_path, raise_key='Invalid aicpu file path.')
if not os.path.isfile(aicpu_file_path):
logger.warning('The fi... | The analyser for analyzing all the AICPU operators. Args: profiling_dir (str): The directory where the parsed profiling files are located. device_id (str): The device ID. Raises: ProfilerPathErrorException: If the profiling dir is invalid. | AicpuDetailAnalyser | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AicpuDetailAnalyser:
"""The analyser for analyzing all the AICPU operators. Args: profiling_dir (str): The directory where the parsed profiling files are located. device_id (str): The device ID. Raises: ProfilerPathErrorException: If the profiling dir is invalid."""
def _load(self):
... | stack_v2_sparse_classes_10k_train_006870 | 25,551 | permissive | [
{
"docstring": "Load data according to the parsed AICPU operator file.",
"name": "_load",
"signature": "def _load(self)"
},
{
"docstring": "Filter the profiling data according to the filter condition. Args: filter_condition (dict): The filter condition.",
"name": "_filter",
"signature": ... | 3 | null | Implement the Python class `AicpuDetailAnalyser` described below.
Class description:
The analyser for analyzing all the AICPU operators. Args: profiling_dir (str): The directory where the parsed profiling files are located. device_id (str): The device ID. Raises: ProfilerPathErrorException: If the profiling dir is inv... | Implement the Python class `AicpuDetailAnalyser` described below.
Class description:
The analyser for analyzing all the AICPU operators. Args: profiling_dir (str): The directory where the parsed profiling files are located. device_id (str): The device ID. Raises: ProfilerPathErrorException: If the profiling dir is inv... | a774d893fb2f21dbc3edb5cd89f9e6eec274ebf1 | <|skeleton|>
class AicpuDetailAnalyser:
"""The analyser for analyzing all the AICPU operators. Args: profiling_dir (str): The directory where the parsed profiling files are located. device_id (str): The device ID. Raises: ProfilerPathErrorException: If the profiling dir is invalid."""
def _load(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AicpuDetailAnalyser:
"""The analyser for analyzing all the AICPU operators. Args: profiling_dir (str): The directory where the parsed profiling files are located. device_id (str): The device ID. Raises: ProfilerPathErrorException: If the profiling dir is invalid."""
def _load(self):
"""Load data ... | the_stack_v2_python_sparse | mindinsight/profiler/analyser/analyser.py | mindspore-ai/mindinsight | train | 224 |
796586866a0924c6e2aae0f964067f7e2af7c499 | [
"kwargs = {}\nkwargs['status'] = 1\ntday = datetime.utcnow().replace(tzinfo=utc)\nkwargs['startingdate__lte'] = datetime(tday.year, tday.month, tday.day, tday.hour, tday.minute, tday.second, tday.microsecond).replace(tzinfo=utc)\nkwargs['expirationdate__gte'] = datetime(tday.year, tday.month, tday.day, tday.hour, t... | <|body_start_0|>
kwargs = {}
kwargs['status'] = 1
tday = datetime.utcnow().replace(tzinfo=utc)
kwargs['startingdate__lte'] = datetime(tday.year, tday.month, tday.day, tday.hour, tday.minute, tday.second, tday.microsecond).replace(tzinfo=utc)
kwargs['expirationdate__gte'] = dateti... | Campaign Manager | CampaignManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CampaignManager:
"""Campaign Manager"""
def get_running_campaign(self):
"""Return all the active campaigns which will be running based on the expiry date, the daily start/stop time and days of the week"""
<|body_0|>
def get_expired_campaign(self):
"""Return all t... | stack_v2_sparse_classes_10k_train_006871 | 27,513 | no_license | [
{
"docstring": "Return all the active campaigns which will be running based on the expiry date, the daily start/stop time and days of the week",
"name": "get_running_campaign",
"signature": "def get_running_campaign(self)"
},
{
"docstring": "Return all the campaigns which are expired or going to... | 2 | stack_v2_sparse_classes_30k_train_005004 | Implement the Python class `CampaignManager` described below.
Class description:
Campaign Manager
Method signatures and docstrings:
- def get_running_campaign(self): Return all the active campaigns which will be running based on the expiry date, the daily start/stop time and days of the week
- def get_expired_campaig... | Implement the Python class `CampaignManager` described below.
Class description:
Campaign Manager
Method signatures and docstrings:
- def get_running_campaign(self): Return all the active campaigns which will be running based on the expiry date, the daily start/stop time and days of the week
- def get_expired_campaig... | 2923a7d974f362af91b7c7c8f2e208cb2353c921 | <|skeleton|>
class CampaignManager:
"""Campaign Manager"""
def get_running_campaign(self):
"""Return all the active campaigns which will be running based on the expiry date, the daily start/stop time and days of the week"""
<|body_0|>
def get_expired_campaign(self):
"""Return all t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CampaignManager:
"""Campaign Manager"""
def get_running_campaign(self):
"""Return all the active campaigns which will be running based on the expiry date, the daily start/stop time and days of the week"""
kwargs = {}
kwargs['status'] = 1
tday = datetime.utcnow().replace(tz... | the_stack_v2_python_sparse | dialer_campaign/models.py | goksie/TheFies | train | 0 |
4dd6533dc0634bca5c0166663869350d57b79e9b | [
"self._arr = arr\nself._n = len(arr)\nself._row = 0\nself._col = 0",
"while self._row < self._n and (not self._arr[self._row]):\n self._row += 1\n self._col = 0\nif self._row >= self._n:\n raise ValueError('No element left')\nanswer = self._arr[self._row][self._col]\nif self._col == len(self._arr[self._r... | <|body_start_0|>
self._arr = arr
self._n = len(arr)
self._row = 0
self._col = 0
<|end_body_0|>
<|body_start_1|>
while self._row < self._n and (not self._arr[self._row]):
self._row += 1
self._col = 0
if self._row >= self._n:
raise Value... | Iterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Iterator:
def __init__(self, arr):
"""initialize Iterator object with an array of arrays"""
<|body_0|>
def next(self):
"""returns the next element in the array of arrays"""
<|body_1|>
def has_next(self):
"""returns whether or not the iterator sti... | stack_v2_sparse_classes_10k_train_006872 | 2,888 | no_license | [
{
"docstring": "initialize Iterator object with an array of arrays",
"name": "__init__",
"signature": "def __init__(self, arr)"
},
{
"docstring": "returns the next element in the array of arrays",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": "returns whether or... | 3 | stack_v2_sparse_classes_30k_train_002083 | Implement the Python class `Iterator` described below.
Class description:
Implement the Iterator class.
Method signatures and docstrings:
- def __init__(self, arr): initialize Iterator object with an array of arrays
- def next(self): returns the next element in the array of arrays
- def has_next(self): returns whethe... | Implement the Python class `Iterator` described below.
Class description:
Implement the Iterator class.
Method signatures and docstrings:
- def __init__(self, arr): initialize Iterator object with an array of arrays
- def next(self): returns the next element in the array of arrays
- def has_next(self): returns whethe... | 4ad9063188e07e27a539d42140dabfdcaca608af | <|skeleton|>
class Iterator:
def __init__(self, arr):
"""initialize Iterator object with an array of arrays"""
<|body_0|>
def next(self):
"""returns the next element in the array of arrays"""
<|body_1|>
def has_next(self):
"""returns whether or not the iterator sti... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Iterator:
def __init__(self, arr):
"""initialize Iterator object with an array of arrays"""
self._arr = arr
self._n = len(arr)
self._row = 0
self._col = 0
def next(self):
"""returns the next element in the array of arrays"""
while self._row < self._... | the_stack_v2_python_sparse | python/166.py | lakshyatyagi24/daily-coding-problems | train | 1 | |
82588d123227f13c92810d0e1840fcb1234044b1 | [
"self.user = user or current_user()\nself.spec = sorted_dict(spec)\nself.created = datetime.now().astimezone()",
"new_spec = ContainerSpec(spec, user)\nexisting = session.query(ContainerSpec)\nexisting = existing.filter(ContainerSpec.user == new_spec.user, ContainerSpec.spec.cast(String) == json.dumps(new_spec.sp... | <|body_start_0|>
self.user = user or current_user()
self.spec = sorted_dict(spec)
self.created = datetime.now().astimezone()
<|end_body_0|>
<|body_start_1|>
new_spec = ContainerSpec(spec, user)
existing = session.query(ContainerSpec)
existing = existing.filter(ContainerS... | caliban container spec This class contains the information specifying how to generate a docker container for use in caliban. Please do not instantiate this class directly via its constructor. Instead, use the ContainerSpec.get_or_create() method, or query the database using a session.query() call. The get_or_create() m... | ContainerSpec | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContainerSpec:
"""caliban container spec This class contains the information specifying how to generate a docker container for use in caliban. Please do not instantiate this class directly via its constructor. Instead, use the ContainerSpec.get_or_create() method, or query the database using a se... | stack_v2_sparse_classes_10k_train_006873 | 18,576 | permissive | [
{
"docstring": "ContainerSpec Args: spec: dictionary containing docker container creation parameters user: username, if None then user is automatically detected",
"name": "__init__",
"signature": "def __init__(self, spec: Dict[str, Any], user: Optional[str]=None)"
},
{
"docstring": "gets an exis... | 2 | stack_v2_sparse_classes_30k_train_000876 | Implement the Python class `ContainerSpec` described below.
Class description:
caliban container spec This class contains the information specifying how to generate a docker container for use in caliban. Please do not instantiate this class directly via its constructor. Instead, use the ContainerSpec.get_or_create() m... | Implement the Python class `ContainerSpec` described below.
Class description:
caliban container spec This class contains the information specifying how to generate a docker container for use in caliban. Please do not instantiate this class directly via its constructor. Instead, use the ContainerSpec.get_or_create() m... | d0e792a8e72fe5cbc186c47a2541e94d5b94c319 | <|skeleton|>
class ContainerSpec:
"""caliban container spec This class contains the information specifying how to generate a docker container for use in caliban. Please do not instantiate this class directly via its constructor. Instead, use the ContainerSpec.get_or_create() method, or query the database using a se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ContainerSpec:
"""caliban container spec This class contains the information specifying how to generate a docker container for use in caliban. Please do not instantiate this class directly via its constructor. Instead, use the ContainerSpec.get_or_create() method, or query the database using a session.query()... | the_stack_v2_python_sparse | caliban/history/types.py | google/caliban | train | 499 |
e21a20afbea56534d5163025dc7f9af39c5520cd | [
"assert len(observation_space.shape) == 1, 'Only flat spaces supported by MLP model'\nassert len(action_space.shape) == 1, 'Only flat action spaces supported by MLP model'\nsuper().__init__(observation_space, action_space, signal_space)\nself.policy_weight = policy_weight\nself.reward_scale = signal_space.span\nsel... | <|body_start_0|>
assert len(observation_space.shape) == 1, 'Only flat spaces supported by MLP model'
assert len(action_space.shape) == 1, 'Only flat action spaces supported by MLP model'
super().__init__(observation_space, action_space, signal_space)
self.policy_weight = policy_weight
... | Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model that given the encoded state and encoded action computes predicts the encode... | MLPICM | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLPICM:
"""Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model that given the encoded state and encoded a... | stack_v2_sparse_classes_10k_train_006874 | 8,668 | permissive | [
{
"docstring": ":param policy_weight: weight to be applied to the ``policy_loss`` in the ``loss`` method. Allows to control how important optimizing policy to optimizing the curiosity module :param signal_space: used for scaling the intrinsic reward returned by this module. Can be used to control how the fluctu... | 4 | stack_v2_sparse_classes_30k_train_007306 | Implement the Python class `MLPICM` described below.
Class description:
Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model tha... | Implement the Python class `MLPICM` described below.
Class description:
Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model tha... | 21e3564696062b67151b013fd5e47df46cf44aa5 | <|skeleton|>
class MLPICM:
"""Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model that given the encoded state and encoded a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MLPICM:
"""Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model that given the encoded state and encoded action compute... | the_stack_v2_python_sparse | neodroidagent/utilities/exploration/intrinsic_signals/torch_isp/curiosity/icm.py | sintefneodroid/agent | train | 9 |
28082e881cd4a9ea3e32d5330da77882be12ba43 | [
"super(CloseButton, self).__init__()\nclose_button_style = \" \\n style 'close_button' {\\n xthickness = 0\\n ythickness = 0\\n }\\n widget '*.close_button' style 'close_button'\\n \"\ngtk.rc_parse_string(close_button_style)\nself.set_name('widge... | <|body_start_0|>
super(CloseButton, self).__init__()
close_button_style = " \n style 'close_button' {\n xthickness = 0\n ythickness = 0\n }\n widget '*.close_button' style 'close_button'\n "
gtk.rc_parse_string(close_button_st... | CloseButton | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CloseButton:
def __init__(self):
"""Constructor."""
<|body_0|>
def __add_icon_to_button(self):
"""Add the close image to this button."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(CloseButton, self).__init__()
close_button_style = " ... | stack_v2_sparse_classes_10k_train_006875 | 2,000 | no_license | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Add the close image to this button.",
"name": "__add_icon_to_button",
"signature": "def __add_icon_to_button(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005911 | Implement the Python class `CloseButton` described below.
Class description:
Implement the CloseButton class.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def __add_icon_to_button(self): Add the close image to this button. | Implement the Python class `CloseButton` described below.
Class description:
Implement the CloseButton class.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def __add_icon_to_button(self): Add the close image to this button.
<|skeleton|>
class CloseButton:
def __init__(self):
"""... | c21ddf8aba58dc83d58a8db960d58d91ee2e5c74 | <|skeleton|>
class CloseButton:
def __init__(self):
"""Constructor."""
<|body_0|>
def __add_icon_to_button(self):
"""Add the close image to this button."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CloseButton:
def __init__(self):
"""Constructor."""
super(CloseButton, self).__init__()
close_button_style = " \n style 'close_button' {\n xthickness = 0\n ythickness = 0\n }\n widget '*.close_button' style 'close_button'\n... | the_stack_v2_python_sparse | tf/widgets/closebutton.py | yurimalheiros/textflow | train | 1 | |
ec2de037caa934fae26890a823a4795a64c0cc2f | [
"try:\n sh.zfs('list', '-t', 'filesystem', self.name)\nexcept sh.ErrorReturnCode_1:\n return False\nreturn True",
"try:\n sh.zfs('create', self.name)\nexcept sh.ErrorReturnCode_1:\n raise\nreturn True",
"if not confirm:\n raise LoggedException('Destroy of storage filesystem requires confirm=True'... | <|body_start_0|>
try:
sh.zfs('list', '-t', 'filesystem', self.name)
except sh.ErrorReturnCode_1:
return False
return True
<|end_body_0|>
<|body_start_1|>
try:
sh.zfs('create', self.name)
except sh.ErrorReturnCode_1:
raise
r... | Filesystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Filesystem:
def exists(self):
"""Checks if filesystem exists. filesystem = Filesystem('dpool/tmp/test0') filesystem.exists()"""
<|body_0|>
def create(self):
"""Creates storage filesystem. filesystem = Filesystem('dpool/tmp/test0') filesystem.create()"""
<|bod... | stack_v2_sparse_classes_10k_train_006876 | 13,193 | no_license | [
{
"docstring": "Checks if filesystem exists. filesystem = Filesystem('dpool/tmp/test0') filesystem.exists()",
"name": "exists",
"signature": "def exists(self)"
},
{
"docstring": "Creates storage filesystem. filesystem = Filesystem('dpool/tmp/test0') filesystem.create()",
"name": "create",
... | 4 | stack_v2_sparse_classes_30k_train_006082 | Implement the Python class `Filesystem` described below.
Class description:
Implement the Filesystem class.
Method signatures and docstrings:
- def exists(self): Checks if filesystem exists. filesystem = Filesystem('dpool/tmp/test0') filesystem.exists()
- def create(self): Creates storage filesystem. filesystem = Fil... | Implement the Python class `Filesystem` described below.
Class description:
Implement the Filesystem class.
Method signatures and docstrings:
- def exists(self): Checks if filesystem exists. filesystem = Filesystem('dpool/tmp/test0') filesystem.exists()
- def create(self): Creates storage filesystem. filesystem = Fil... | 9bc47e6eeff2944f98a0db4fcab32c5dd95fd025 | <|skeleton|>
class Filesystem:
def exists(self):
"""Checks if filesystem exists. filesystem = Filesystem('dpool/tmp/test0') filesystem.exists()"""
<|body_0|>
def create(self):
"""Creates storage filesystem. filesystem = Filesystem('dpool/tmp/test0') filesystem.create()"""
<|bod... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Filesystem:
def exists(self):
"""Checks if filesystem exists. filesystem = Filesystem('dpool/tmp/test0') filesystem.exists()"""
try:
sh.zfs('list', '-t', 'filesystem', self.name)
except sh.ErrorReturnCode_1:
return False
return True
def create(self)... | the_stack_v2_python_sparse | solarsanweb/storage/dataset.py | akatrevorjay/solarsanweb | train | 1 | |
114a946be963339ce6fb775790365727f836c884 | [
"super().__init__()\nself.length = len(inputs[0])\nif not all((len(inp) == self.length for inp in inputs)):\n raise ValueError('Lengths of inputs, i.e. number of fields or embedding size, must be equal.')\nself.inputs = inputs\ninputs = []\nfor idx, inp in enumerate(self.inputs):\n self.add_module(f'Input_{id... | <|body_start_0|>
super().__init__()
self.length = len(inputs[0])
if not all((len(inp) == self.length for inp in inputs)):
raise ValueError('Lengths of inputs, i.e. number of fields or embedding size, must be equal.')
self.inputs = inputs
inputs = []
for idx, i... | Base Input class for stacking of list of Base Input class in column-wise. The shape of output is :math:`(B, N_{1} + ... + N_{k}, E)`, where :math:`N_{i}` is number of fields of inputs class i. | StackedInput | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StackedInput:
"""Base Input class for stacking of list of Base Input class in column-wise. The shape of output is :math:`(B, N_{1} + ... + N_{k}, E)`, where :math:`N_{i}` is number of fields of inputs class i."""
def __init__(self, inputs: List[BaseInput]):
"""Initialize StackedInput... | stack_v2_sparse_classes_10k_train_006877 | 4,892 | permissive | [
{
"docstring": "Initialize StackedInputs Args: inputs (List[BaseInput]): list of input's layers (trs.inputs.Inputs). e.g. .. code-block:: python import torecsys as trs # initialize embedding layers used in StackedInputs single_index_emb_0 = trs.inputs.base.SingleIndexEmbedding(2, 8) single_index_emb_1 = trs.inp... | 3 | stack_v2_sparse_classes_30k_train_005872 | Implement the Python class `StackedInput` described below.
Class description:
Base Input class for stacking of list of Base Input class in column-wise. The shape of output is :math:`(B, N_{1} + ... + N_{k}, E)`, where :math:`N_{i}` is number of fields of inputs class i.
Method signatures and docstrings:
- def __init_... | Implement the Python class `StackedInput` described below.
Class description:
Base Input class for stacking of list of Base Input class in column-wise. The shape of output is :math:`(B, N_{1} + ... + N_{k}, E)`, where :math:`N_{i}` is number of fields of inputs class i.
Method signatures and docstrings:
- def __init_... | 751a43b9cd35e951d81c0d9cf46507b1777bb7ff | <|skeleton|>
class StackedInput:
"""Base Input class for stacking of list of Base Input class in column-wise. The shape of output is :math:`(B, N_{1} + ... + N_{k}, E)`, where :math:`N_{i}` is number of fields of inputs class i."""
def __init__(self, inputs: List[BaseInput]):
"""Initialize StackedInput... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StackedInput:
"""Base Input class for stacking of list of Base Input class in column-wise. The shape of output is :math:`(B, N_{1} + ... + N_{k}, E)`, where :math:`N_{i}` is number of fields of inputs class i."""
def __init__(self, inputs: List[BaseInput]):
"""Initialize StackedInputs Args: input... | the_stack_v2_python_sparse | torecsys/inputs/base/stacked_inp.py | p768lwy3/torecsys | train | 98 |
df1d79e837958e3fdd1db3db4202e775a9a5fabf | [
"super(CWS, self).__init__()\nif model_path is None:\n model_path = model_urls['cws']\nself.load(model_path, device)",
"if not hasattr(self, 'pipeline'):\n raise ValueError('You have to load model first.')\nsentence_list = []\nif isinstance(content, str):\n sentence_list.append(content)\nelif isinstance(... | <|body_start_0|>
super(CWS, self).__init__()
if model_path is None:
model_path = model_urls['cws']
self.load(model_path, device)
<|end_body_0|>
<|body_start_1|>
if not hasattr(self, 'pipeline'):
raise ValueError('You have to load model first.')
sentence_l... | CWS | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CWS:
def __init__(self, model_path=None, device='cpu'):
"""中文分词高级接口。 :param model_path: 当model_path为None，使用默认位置的model。如果默认位置不存在，则自动下载模型 :param device: str，可以为'cpu', 'cuda'或'cuda:0'等。会将模型load到相应device进行推断。"""
<|body_0|>
def predict(self, content):
"""分词接口。 :param cont... | stack_v2_sparse_classes_10k_train_006878 | 11,931 | permissive | [
{
"docstring": "中文分词高级接口。 :param model_path: 当model_path为None，使用默认位置的model。如果默认位置不存在，则自动下载模型 :param device: str，可以为'cpu', 'cuda'或'cuda:0'等。会将模型load到相应device进行推断。",
"name": "__init__",
"signature": "def __init__(self, model_path=None, device='cpu')"
},
{
"docstring": "分词接口。 :param content: str或Li... | 3 | stack_v2_sparse_classes_30k_train_006732 | Implement the Python class `CWS` described below.
Class description:
Implement the CWS class.
Method signatures and docstrings:
- def __init__(self, model_path=None, device='cpu'): 中文分词高级接口。 :param model_path: 当model_path为None，使用默认位置的model。如果默认位置不存在，则自动下载模型 :param device: str，可以为'cpu', 'cuda'或'cuda:0'等。会将模型load到相应dev... | Implement the Python class `CWS` described below.
Class description:
Implement the CWS class.
Method signatures and docstrings:
- def __init__(self, model_path=None, device='cpu'): 中文分词高级接口。 :param model_path: 当model_path为None，使用默认位置的model。如果默认位置不存在，则自动下载模型 :param device: str，可以为'cpu', 'cuda'或'cuda:0'等。会将模型load到相应dev... | 209e0aec44eb100ad5c30c75b84d28711e2968f5 | <|skeleton|>
class CWS:
def __init__(self, model_path=None, device='cpu'):
"""中文分词高级接口。 :param model_path: 当model_path为None，使用默认位置的model。如果默认位置不存在，则自动下载模型 :param device: str，可以为'cpu', 'cuda'或'cuda:0'等。会将模型load到相应device进行推断。"""
<|body_0|>
def predict(self, content):
"""分词接口。 :param cont... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CWS:
def __init__(self, model_path=None, device='cpu'):
"""中文分词高级接口。 :param model_path: 当model_path为None，使用默认位置的model。如果默认位置不存在，则自动下载模型 :param device: str，可以为'cpu', 'cuda'或'cuda:0'等。会将模型load到相应device进行推断。"""
super(CWS, self).__init__()
if model_path is None:
model_path = mo... | the_stack_v2_python_sparse | fastNLP/api/api.py | huziye/fastNLP_fork | train | 4 | |
0d29a47cff4aa8c9d70176e614d8fa386ab03461 | [
"gym.Wrapper.__init__(self, env)\nself.noop_max = noop_max\nself.noop_action = 0\nassert env.unwrapped.get_action_meanings()[0] == 'NOOP'",
"self.env.reset()\nnoops = random.randrange(1, self.noop_max + 1)\nassert noops > 0\nobs = None\nfor _ in range(noops):\n obs, _, done, _ = self.env.step(self.noop_action)... | <|body_start_0|>
gym.Wrapper.__init__(self, env)
self.noop_max = noop_max
self.noop_action = 0
assert env.unwrapped.get_action_meanings()[0] == 'NOOP'
<|end_body_0|>
<|body_start_1|>
self.env.reset()
noops = random.randrange(1, self.noop_max + 1)
assert noops > 0... | NoopResetEnv | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NoopResetEnv:
def __init__(self, env, noop_max=30):
"""Sample initial states by taking random number of no-ops on reset. No-op is assumed to be action 0."""
<|body_0|>
def _reset(self):
"""Do no-op action for a number of steps in [1, noop_max]."""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_006879 | 16,880 | permissive | [
{
"docstring": "Sample initial states by taking random number of no-ops on reset. No-op is assumed to be action 0.",
"name": "__init__",
"signature": "def __init__(self, env, noop_max=30)"
},
{
"docstring": "Do no-op action for a number of steps in [1, noop_max].",
"name": "_reset",
"sig... | 2 | stack_v2_sparse_classes_30k_train_001150 | Implement the Python class `NoopResetEnv` described below.
Class description:
Implement the NoopResetEnv class.
Method signatures and docstrings:
- def __init__(self, env, noop_max=30): Sample initial states by taking random number of no-ops on reset. No-op is assumed to be action 0.
- def _reset(self): Do no-op acti... | Implement the Python class `NoopResetEnv` described below.
Class description:
Implement the NoopResetEnv class.
Method signatures and docstrings:
- def __init__(self, env, noop_max=30): Sample initial states by taking random number of no-ops on reset. No-op is assumed to be action 0.
- def _reset(self): Do no-op acti... | 9eb833f1f5a144f49849d2bc9ab90450b3c8a6dd | <|skeleton|>
class NoopResetEnv:
def __init__(self, env, noop_max=30):
"""Sample initial states by taking random number of no-ops on reset. No-op is assumed to be action 0."""
<|body_0|>
def _reset(self):
"""Do no-op action for a number of steps in [1, noop_max]."""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NoopResetEnv:
def __init__(self, env, noop_max=30):
"""Sample initial states by taking random number of no-ops on reset. No-op is assumed to be action 0."""
gym.Wrapper.__init__(self, env)
self.noop_max = noop_max
self.noop_action = 0
assert env.unwrapped.get_action_mea... | the_stack_v2_python_sparse | rl_a3c_pytorch/environment_for_render.py | doronsobol/Visual_analogies_for_RL_transfer_Learning | train | 2 | |
a905071c08010b848a2f724a92b6d66768ff291e | [
"self.dq = collections.deque([])\nself.size = size\nself.sumval = 0",
"if len(self.dq) < self.size:\n self.sumval += val\n self.dq.append(val)\n return float(self.sumval) / float(len(self.dq))\nelse:\n v = self.dq.popleft()\n self.sumval -= v\n self.sumval += val\n self.dq.append(val)\n re... | <|body_start_0|>
self.dq = collections.deque([])
self.size = size
self.sumval = 0
<|end_body_0|>
<|body_start_1|>
if len(self.dq) < self.size:
self.sumval += val
self.dq.append(val)
return float(self.sumval) / float(len(self.dq))
else:
... | MovingAverage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.dq = collections.deque([])
... | stack_v2_sparse_classes_10k_train_006880 | 816 | permissive | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | null | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | 86f1cb98de801f58c39d9a48ce9de12df7303d20 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.dq = collections.deque([])
self.size = size
self.sumval = 0
def next(self, val):
""":type val: int :rtype: float"""
if len(self.dq) < self.size:
... | the_stack_v2_python_sparse | 346-Moving-Average-from-Data-Stream/solution.py | Tanych/CodeTracking | train | 0 | |
21fbbfcad9794510e944e7cdd41421592ceb719d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn EducationAssignmentResource()",
"from .education_resource import EducationResource\nfrom .entity import Entity\nfrom .education_resource import EducationResource\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return EducationAssignmentResource()
<|end_body_0|>
<|body_start_1|>
from .education_resource import EducationResource
from .entity import Entity
from .education_resource import Educati... | EducationAssignmentResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EducationAssignmentResource:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EducationAssignmentResource:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value a... | stack_v2_sparse_classes_10k_train_006881 | 2,633 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: EducationAssignmentResource",
"name": "create_from_discriminator_value",
"signature": "def create_from_discr... | 3 | null | Implement the Python class `EducationAssignmentResource` described below.
Class description:
Implement the EducationAssignmentResource class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EducationAssignmentResource: Creates a new instance of the appr... | Implement the Python class `EducationAssignmentResource` described below.
Class description:
Implement the EducationAssignmentResource class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EducationAssignmentResource: Creates a new instance of the appr... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class EducationAssignmentResource:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EducationAssignmentResource:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EducationAssignmentResource:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> EducationAssignmentResource:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | the_stack_v2_python_sparse | msgraph/generated/models/education_assignment_resource.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
ec0b4f55127dd62f571acb7541b3adabe5bbad49 | [
"super().__init__(name=name)\nself._embedding_dim = embedding_dim\nif number_of_dom_encoder_layers < 0:\n raise ValueError('Number of DOM encoder layers should be > 0 but got %d' % number_of_dom_encoder_layers)\nif number_of_profile_encoder_layers < 0:\n raise ValueError('Number of profile encoder layers shou... | <|body_start_0|>
super().__init__(name=name)
self._embedding_dim = embedding_dim
if number_of_dom_encoder_layers < 0:
raise ValueError('Number of DOM encoder layers should be > 0 but got %d' % number_of_dom_encoder_layers)
if number_of_profile_encoder_layers < 0:
... | Feed forward DQN for web navigation. | DQNWebFF | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DQNWebFF:
"""Feed forward DQN for web navigation."""
def __init__(self, vocab_size, embedding_dim, latent_dim, number_of_dom_encoder_layers=1, number_of_profile_encoder_layers=1, embedding_initializer=None, profile_value_dropout=0.0, use_select_option_dim=False, name=None, return_state_value... | stack_v2_sparse_classes_10k_train_006882 | 21,865 | permissive | [
{
"docstring": "DQN with feed forward DOM encoder. Profile and DOM are independently encoded into tensors where profile tensor represents field encodings while DOM tensor represents element encodings. These two tensors are used score every element and field pairs. Scores correspond to Q values in DQN or logits ... | 2 | stack_v2_sparse_classes_30k_train_007079 | Implement the Python class `DQNWebFF` described below.
Class description:
Feed forward DQN for web navigation.
Method signatures and docstrings:
- def __init__(self, vocab_size, embedding_dim, latent_dim, number_of_dom_encoder_layers=1, number_of_profile_encoder_layers=1, embedding_initializer=None, profile_value_dro... | Implement the Python class `DQNWebFF` described below.
Class description:
Feed forward DQN for web navigation.
Method signatures and docstrings:
- def __init__(self, vocab_size, embedding_dim, latent_dim, number_of_dom_encoder_layers=1, number_of_profile_encoder_layers=1, embedding_initializer=None, profile_value_dro... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class DQNWebFF:
"""Feed forward DQN for web navigation."""
def __init__(self, vocab_size, embedding_dim, latent_dim, number_of_dom_encoder_layers=1, number_of_profile_encoder_layers=1, embedding_initializer=None, profile_value_dropout=0.0, use_select_option_dim=False, name=None, return_state_value... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DQNWebFF:
"""Feed forward DQN for web navigation."""
def __init__(self, vocab_size, embedding_dim, latent_dim, number_of_dom_encoder_layers=1, number_of_profile_encoder_layers=1, embedding_initializer=None, profile_value_dropout=0.0, use_select_option_dim=False, name=None, return_state_value=False):
... | the_stack_v2_python_sparse | compositional_rl/gwob/CoDE/q_networks.py | Jimmy-INL/google-research | train | 1 |
8f6a372869a9445f5b037d4a036eea48007fc3dd | [
"username = self.cleaned_data['username']\ntry:\n User.objects.get(username=username)\nexcept User.DoesNotExist:\n return username\nraise ValidationError(_('A user with that username already exists.'))",
"password1 = self.cleaned_data.get('password1', '')\npassword2 = self.cleaned_data['password2']\nif pass... | <|body_start_0|>
username = self.cleaned_data['username']
try:
User.objects.get(username=username)
except User.DoesNotExist:
return username
raise ValidationError(_('A user with that username already exists.'))
<|end_body_0|>
<|body_start_1|>
password1 = ... | Form for registering a new user account | RegistrationForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistrationForm:
"""Form for registering a new user account"""
def clean_username(self):
"""Verify username not existed in database"""
<|body_0|>
def clean_password2(self):
"""Verify password2 is the same as password1"""
<|body_1|>
def save(self, co... | stack_v2_sparse_classes_10k_train_006883 | 3,293 | no_license | [
{
"docstring": "Verify username not existed in database",
"name": "clean_username",
"signature": "def clean_username(self)"
},
{
"docstring": "Verify password2 is the same as password1",
"name": "clean_password2",
"signature": "def clean_password2(self)"
},
{
"docstring": "Save U... | 3 | stack_v2_sparse_classes_30k_train_007143 | Implement the Python class `RegistrationForm` described below.
Class description:
Form for registering a new user account
Method signatures and docstrings:
- def clean_username(self): Verify username not existed in database
- def clean_password2(self): Verify password2 is the same as password1
- def save(self, commit... | Implement the Python class `RegistrationForm` described below.
Class description:
Form for registering a new user account
Method signatures and docstrings:
- def clean_username(self): Verify username not existed in database
- def clean_password2(self): Verify password2 is the same as password1
- def save(self, commit... | 04541d41bb2fe3d7217b43202ff0d999c82d1e9e | <|skeleton|>
class RegistrationForm:
"""Form for registering a new user account"""
def clean_username(self):
"""Verify username not existed in database"""
<|body_0|>
def clean_password2(self):
"""Verify password2 is the same as password1"""
<|body_1|>
def save(self, co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RegistrationForm:
"""Form for registering a new user account"""
def clean_username(self):
"""Verify username not existed in database"""
username = self.cleaned_data['username']
try:
User.objects.get(username=username)
except User.DoesNotExist:
retur... | the_stack_v2_python_sparse | apps/account/forms.py | lifepy/myway | train | 2 |
6a0a0783428edc8dca7a1a5f1b7346a6c8d1cfe9 | [
"self.sums = []\nfor weight in w:\n if not self.sums:\n self.sums.append(weight)\n else:\n self.sums.append(weight + self.sums[-1])",
"import bisect\npick = random.uniform(0, self.sums[-1])\nreturn bisect.bisect_left(self.sums, pick)"
] | <|body_start_0|>
self.sums = []
for weight in w:
if not self.sums:
self.sums.append(weight)
else:
self.sums.append(weight + self.sums[-1])
<|end_body_0|>
<|body_start_1|>
import bisect
pick = random.uniform(0, self.sums[-1])
... | Solution_1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_1:
def __init__(self, w):
""":type w: List[int] 176ms"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.sums = []
for weight in w:
if not self.sums:
se... | stack_v2_sparse_classes_10k_train_006884 | 1,901 | no_license | [
{
"docstring": ":type w: List[int] 176ms",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution_1` described below.
Class description:
Implement the Solution_1 class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int] 176ms
- def pickIndex(self): :rtype: int | Implement the Python class `Solution_1` described below.
Class description:
Implement the Solution_1 class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int] 176ms
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution_1:
def __init__(self, w):
""":type w: List[int] 1... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution_1:
def __init__(self, w):
""":type w: List[int] 176ms"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution_1:
def __init__(self, w):
""":type w: List[int] 176ms"""
self.sums = []
for weight in w:
if not self.sums:
self.sums.append(weight)
else:
self.sums.append(weight + self.sums[-1])
def pickIndex(self):
""":rtyp... | the_stack_v2_python_sparse | RandomPickWithWeight_MID_880.py | 953250587/leetcode-python | train | 2 | |
0bc98fe7a9549d9484b78732968681cdd35807d8 | [
"if not matrix or not matrix[0]:\n return 0\nm, n = (len(matrix), len(matrix[0]))\ndp = [[0] * (n + 1) for _ in range(m + 1)]\nfor i in range(1, m + 1):\n for j in range(1, n + 1):\n if matrix[i - 1][j - 1] == '1':\n dp[i][j] = 1 + min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1])\nreturn ma... | <|body_start_0|>
if not matrix or not matrix[0]:
return 0
m, n = (len(matrix), len(matrix[0]))
dp = [[0] * (n + 1) for _ in range(m + 1)]
for i in range(1, m + 1):
for j in range(1, n + 1):
if matrix[i - 1][j - 1] == '1':
dp[i][... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maximalSquare(self, matrix):
"""dp[i][j] i,j为正方形右下角能构成的最大正方形边长 状态转移方程: dp[i][j] = 1 + min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]) :param matrix: :return:"""
<|body_0|>
def maximalSquare2(self, matrix):
"""逻辑写复杂了。 dp[i][j]:i,j能构成的最大正方形边长 遍历矩阵 当[i][... | stack_v2_sparse_classes_10k_train_006885 | 2,223 | no_license | [
{
"docstring": "dp[i][j] i,j为正方形右下角能构成的最大正方形边长 状态转移方程: dp[i][j] = 1 + min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]) :param matrix: :return:",
"name": "maximalSquare",
"signature": "def maximalSquare(self, matrix)"
},
{
"docstring": "逻辑写复杂了。 dp[i][j]:i,j能构成的最大正方形边长 遍历矩阵 当[i][j]是1的时候,看[i-k,j-k... | 2 | stack_v2_sparse_classes_30k_train_003062 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalSquare(self, matrix): dp[i][j] i,j为正方形右下角能构成的最大正方形边长 状态转移方程: dp[i][j] = 1 + min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]) :param matrix: :return:
- def maximalSqua... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalSquare(self, matrix): dp[i][j] i,j为正方形右下角能构成的最大正方形边长 状态转移方程: dp[i][j] = 1 + min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]) :param matrix: :return:
- def maximalSqua... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def maximalSquare(self, matrix):
"""dp[i][j] i,j为正方形右下角能构成的最大正方形边长 状态转移方程: dp[i][j] = 1 + min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]) :param matrix: :return:"""
<|body_0|>
def maximalSquare2(self, matrix):
"""逻辑写复杂了。 dp[i][j]:i,j能构成的最大正方形边长 遍历矩阵 当[i][... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maximalSquare(self, matrix):
"""dp[i][j] i,j为正方形右下角能构成的最大正方形边长 状态转移方程: dp[i][j] = 1 + min(dp[i - 1][j - 1], dp[i - 1][j], dp[i][j - 1]) :param matrix: :return:"""
if not matrix or not matrix[0]:
return 0
m, n = (len(matrix), len(matrix[0]))
dp = [[0] *... | the_stack_v2_python_sparse | 221_最大正方形.py | lovehhf/LeetCode | train | 0 | |
184397e1208d1ff6d2b9eadb44702e7b44781524 | [
"self.api = None\nself._base_url = None\nself._username = None\nself._password = None\nself._existing_entry = None\nself._description_placeholders = None",
"errors = {}\nif user_input is None:\n return self._show_setup_form(user_input, errors)\nreturn await self._validate_and_create_entry(user_input, 'user')",... | <|body_start_0|>
self.api = None
self._base_url = None
self._username = None
self._password = None
self._existing_entry = None
self._description_placeholders = None
<|end_body_0|>
<|body_start_1|>
errors = {}
if user_input is None:
return self... | Handle a FireServiceRota config flow. | FireServiceRotaFlowHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FireServiceRotaFlowHandler:
"""Handle a FireServiceRota config flow."""
def __init__(self):
"""Initialize config flow."""
<|body_0|>
async def async_step_user(self, user_input=None):
"""Handle a flow initiated by the user."""
<|body_1|>
async def _va... | stack_v2_sparse_classes_10k_train_006886 | 4,479 | permissive | [
{
"docstring": "Initialize config flow.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Handle a flow initiated by the user.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input=None)"
},
{
"docstring": "Check if config ... | 6 | null | Implement the Python class `FireServiceRotaFlowHandler` described below.
Class description:
Handle a FireServiceRota config flow.
Method signatures and docstrings:
- def __init__(self): Initialize config flow.
- async def async_step_user(self, user_input=None): Handle a flow initiated by the user.
- async def _valida... | Implement the Python class `FireServiceRotaFlowHandler` described below.
Class description:
Handle a FireServiceRota config flow.
Method signatures and docstrings:
- def __init__(self): Initialize config flow.
- async def async_step_user(self, user_input=None): Handle a flow initiated by the user.
- async def _valida... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class FireServiceRotaFlowHandler:
"""Handle a FireServiceRota config flow."""
def __init__(self):
"""Initialize config flow."""
<|body_0|>
async def async_step_user(self, user_input=None):
"""Handle a flow initiated by the user."""
<|body_1|>
async def _va... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FireServiceRotaFlowHandler:
"""Handle a FireServiceRota config flow."""
def __init__(self):
"""Initialize config flow."""
self.api = None
self._base_url = None
self._username = None
self._password = None
self._existing_entry = None
self._description... | the_stack_v2_python_sparse | homeassistant/components/fireservicerota/config_flow.py | home-assistant/core | train | 35,501 |
337b79b58615d2f18d864d7a01cb1dfa0641c68a | [
"self.middleman = middleman\nself.items = items\nself.keys = items\nself.data = {}\nself.tick = 0\nself.data['tick'] = 0\nfor i, key in enumerate(self.keys):\n self.data[key] = 0",
"for key, val in self.data.items():\n self.data[key] = val + 0.2 * (random() - 0.5)\n if key == 'tick':\n self.data[k... | <|body_start_0|>
self.middleman = middleman
self.items = items
self.keys = items
self.data = {}
self.tick = 0
self.data['tick'] = 0
for i, key in enumerate(self.keys):
self.data[key] = 0
<|end_body_0|>
<|body_start_1|>
for key, val in self.dat... | Market | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Market:
def __init__(self, items, middleman):
"""Dummy market emulator Args: items : List of item keys middleman : A Middleman object"""
<|body_0|>
def update(self):
"""Updates market data and propagates to Bokeh server Note: best to update all at once. Current versi... | stack_v2_sparse_classes_10k_train_006887 | 6,993 | permissive | [
{
"docstring": "Dummy market emulator Args: items : List of item keys middleman : A Middleman object",
"name": "__init__",
"signature": "def __init__(self, items, middleman)"
},
{
"docstring": "Updates market data and propagates to Bokeh server Note: best to update all at once. Current version m... | 2 | stack_v2_sparse_classes_30k_train_004486 | Implement the Python class `Market` described below.
Class description:
Implement the Market class.
Method signatures and docstrings:
- def __init__(self, items, middleman): Dummy market emulator Args: items : List of item keys middleman : A Middleman object
- def update(self): Updates market data and propagates to B... | Implement the Python class `Market` described below.
Class description:
Implement the Market class.
Method signatures and docstrings:
- def __init__(self, items, middleman): Dummy market emulator Args: items : List of item keys middleman : A Middleman object
- def update(self): Updates market data and propagates to B... | 42a5e8b20591f0e4789201b02cbbaf3837352881 | <|skeleton|>
class Market:
def __init__(self, items, middleman):
"""Dummy market emulator Args: items : List of item keys middleman : A Middleman object"""
<|body_0|>
def update(self):
"""Updates market data and propagates to Bokeh server Note: best to update all at once. Current versi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Market:
def __init__(self, items, middleman):
"""Dummy market emulator Args: items : List of item keys middleman : A Middleman object"""
self.middleman = middleman
self.items = items
self.keys = items
self.data = {}
self.tick = 0
self.data['tick'] = 0
... | the_stack_v2_python_sparse | neural_mmo/forge/blade/core/market/new_visualizer.py | alirezanobakht13/neural-mmo | train | 0 | |
5b2de20438b8f1835ceb6d563893c1643416b2d6 | [
"it = iter(test_inputs.split('\\n')) if test_inputs else None\n\ndef uinput():\n return next(it) if it else sys.stdin.readline().rstrip()\n[self.n, self.d] = map(int, uinput().split())\nl, s = (self.n, 2)\ninp = ' '.join((uinput() for i in range(l))).split()\nself.numm = [[int(inp[i]) for i in range(j, l * s, s)... | <|body_start_0|>
it = iter(test_inputs.split('\n')) if test_inputs else None
def uinput():
return next(it) if it else sys.stdin.readline().rstrip()
[self.n, self.d] = map(int, uinput().split())
l, s = (self.n, 2)
inp = ' '.join((uinput() for i in range(l))).split()
... | Company representation | Company | [
"Unlicense",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Company:
"""Company representation"""
def __init__(self, test_inputs=None):
"""Default constructor"""
<|body_0|>
def calculate(self):
"""Main calcualtion function of the class"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
it = iter(test_inputs... | stack_v2_sparse_classes_10k_train_006888 | 3,763 | permissive | [
{
"docstring": "Default constructor",
"name": "__init__",
"signature": "def __init__(self, test_inputs=None)"
},
{
"docstring": "Main calcualtion function of the class",
"name": "calculate",
"signature": "def calculate(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002391 | Implement the Python class `Company` described below.
Class description:
Company representation
Method signatures and docstrings:
- def __init__(self, test_inputs=None): Default constructor
- def calculate(self): Main calcualtion function of the class | Implement the Python class `Company` described below.
Class description:
Company representation
Method signatures and docstrings:
- def __init__(self, test_inputs=None): Default constructor
- def calculate(self): Main calcualtion function of the class
<|skeleton|>
class Company:
"""Company representation"""
... | ae02ea872ca91ef98630cc172a844b82cc56f621 | <|skeleton|>
class Company:
"""Company representation"""
def __init__(self, test_inputs=None):
"""Default constructor"""
<|body_0|>
def calculate(self):
"""Main calcualtion function of the class"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Company:
"""Company representation"""
def __init__(self, test_inputs=None):
"""Default constructor"""
it = iter(test_inputs.split('\n')) if test_inputs else None
def uinput():
return next(it) if it else sys.stdin.readline().rstrip()
[self.n, self.d] = map(int,... | the_stack_v2_python_sparse | codeforces/580B_company.py | snsokolov/contests | train | 1 |
6d8964c999013cf9977488687b806acf9a02c107 | [
"shots = 100\ncircuits = ref_diagonal_gate.diagonal_gate_circuits_deterministic(final_measure=True)\ntargets = ref_diagonal_gate.diagonal_gate_counts_deterministic(shots)\nresult = execute(circuits, self.SIMULATOR, shots=shots).result()\nself.assertTrue(getattr(result, 'success', False))\nself.compare_counts(result... | <|body_start_0|>
shots = 100
circuits = ref_diagonal_gate.diagonal_gate_circuits_deterministic(final_measure=True)
targets = ref_diagonal_gate.diagonal_gate_counts_deterministic(shots)
result = execute(circuits, self.SIMULATOR, shots=shots).result()
self.assertTrue(getattr(result... | QasmSimulator additional tests. | QasmDiagonalGateTests | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QasmDiagonalGateTests:
"""QasmSimulator additional tests."""
def test_diagonal_gate(self):
"""Test simulation with unitary gate circuit instructions."""
<|body_0|>
def test_diagonal_gate_wrapper(self):
"""Test simulation with unitary gate circuit instructions."""... | stack_v2_sparse_classes_10k_train_006889 | 3,511 | permissive | [
{
"docstring": "Test simulation with unitary gate circuit instructions.",
"name": "test_diagonal_gate",
"signature": "def test_diagonal_gate(self)"
},
{
"docstring": "Test simulation with unitary gate circuit instructions.",
"name": "test_diagonal_gate_wrapper",
"signature": "def test_di... | 2 | stack_v2_sparse_classes_30k_train_007051 | Implement the Python class `QasmDiagonalGateTests` described below.
Class description:
QasmSimulator additional tests.
Method signatures and docstrings:
- def test_diagonal_gate(self): Test simulation with unitary gate circuit instructions.
- def test_diagonal_gate_wrapper(self): Test simulation with unitary gate cir... | Implement the Python class `QasmDiagonalGateTests` described below.
Class description:
QasmSimulator additional tests.
Method signatures and docstrings:
- def test_diagonal_gate(self): Test simulation with unitary gate circuit instructions.
- def test_diagonal_gate_wrapper(self): Test simulation with unitary gate cir... | 0c1c805fd5dfce465a8955ee3faf81037023a23e | <|skeleton|>
class QasmDiagonalGateTests:
"""QasmSimulator additional tests."""
def test_diagonal_gate(self):
"""Test simulation with unitary gate circuit instructions."""
<|body_0|>
def test_diagonal_gate_wrapper(self):
"""Test simulation with unitary gate circuit instructions."""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QasmDiagonalGateTests:
"""QasmSimulator additional tests."""
def test_diagonal_gate(self):
"""Test simulation with unitary gate circuit instructions."""
shots = 100
circuits = ref_diagonal_gate.diagonal_gate_circuits_deterministic(final_measure=True)
targets = ref_diagonal... | the_stack_v2_python_sparse | artifacts/old_dataset_versions/original_commits/qiskit-aer/qiskit-aer#707/before/qasm_unitary_gate.py | MattePalte/Bugs-Quantum-Computing-Platforms | train | 4 |
a9043c5406f62bb442227188d58b204dfe1f4493 | [
"if not hasattr(self, '__config_class__'):\n raise NotImplementedError('The subclass extending NotNullSchema must define its own custom __config_class__')\nreturn self.__config_class__(**data)",
"for key in original.keys():\n if key not in output and (not key.startswith('_')):\n output[key] = origina... | <|body_start_0|>
if not hasattr(self, '__config_class__'):
raise NotImplementedError('The subclass extending NotNullSchema must define its own custom __config_class__')
return self.__config_class__(**data)
<|end_body_0|>
<|body_start_1|>
for key in original.keys():
if ke... | Extension of Marshmallow Schema to facilitate implicit removal of null values before serialization. The __config_class__ attribute is utilized to point a Schema to a configuration. It is the responsibility of the child class to define its own __config_class__ to ensure proper serialization/deserialization. Reference: h... | NotNullSchema | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotNullSchema:
"""Extension of Marshmallow Schema to facilitate implicit removal of null values before serialization. The __config_class__ attribute is utilized to point a Schema to a configuration. It is the responsibility of the child class to define its own __config_class__ to ensure proper se... | stack_v2_sparse_classes_10k_train_006890 | 28,002 | permissive | [
{
"docstring": "Hook to convert the schema object into its respective config type. Args: data: The dictionary representation of the configuration object kwargs: Marshmallow-specific kwargs required to maintain hook signature (unused herein) Returns: An instance of configuration class, which subclasses the DictD... | 2 | stack_v2_sparse_classes_30k_train_005190 | Implement the Python class `NotNullSchema` described below.
Class description:
Extension of Marshmallow Schema to facilitate implicit removal of null values before serialization. The __config_class__ attribute is utilized to point a Schema to a configuration. It is the responsibility of the child class to define its o... | Implement the Python class `NotNullSchema` described below.
Class description:
Extension of Marshmallow Schema to facilitate implicit removal of null values before serialization. The __config_class__ attribute is utilized to point a Schema to a configuration. It is the responsibility of the child class to define its o... | b0290e2fd2aa05aec6d7d8871b91cb4478e9501d | <|skeleton|>
class NotNullSchema:
"""Extension of Marshmallow Schema to facilitate implicit removal of null values before serialization. The __config_class__ attribute is utilized to point a Schema to a configuration. It is the responsibility of the child class to define its own __config_class__ to ensure proper se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NotNullSchema:
"""Extension of Marshmallow Schema to facilitate implicit removal of null values before serialization. The __config_class__ attribute is utilized to point a Schema to a configuration. It is the responsibility of the child class to define its own __config_class__ to ensure proper serialization/d... | the_stack_v2_python_sparse | great_expectations/rule_based_profiler/config/base.py | great-expectations/great_expectations | train | 8,931 |
35ebaf649bc0b5900856d6582efda4851f59517c | [
"with tempfile.TemporaryDirectory() as tmp_dir:\n test_repo = test_repos.TEST_REPOS[1]\n self.assertTrue(helper.build_image_impl(test_repo.project_name))\n host_src_dir = build_specified_commit.copy_src_from_docker(test_repo.project_name, tmp_dir)\n test_repo_manager = repo_manager.clone_repo_and_get_ma... | <|body_start_0|>
with tempfile.TemporaryDirectory() as tmp_dir:
test_repo = test_repos.TEST_REPOS[1]
self.assertTrue(helper.build_image_impl(test_repo.project_name))
host_src_dir = build_specified_commit.copy_src_from_docker(test_repo.project_name, tmp_dir)
test_r... | Tests if an image can be built from different states e.g. a commit. | BuildImageIntegrationTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BuildImageIntegrationTest:
"""Tests if an image can be built from different states e.g. a commit."""
def test_build_fuzzers_from_commit(self):
"""Tests if the fuzzers can build at a specified commit. This is done by using a known regression range for a specific test case. The old com... | stack_v2_sparse_classes_10k_train_006891 | 5,754 | permissive | [
{
"docstring": "Tests if the fuzzers can build at a specified commit. This is done by using a known regression range for a specific test case. The old commit should show the error when its fuzzers run and the new one should not.",
"name": "test_build_fuzzers_from_commit",
"signature": "def test_build_fu... | 3 | null | Implement the Python class `BuildImageIntegrationTest` described below.
Class description:
Tests if an image can be built from different states e.g. a commit.
Method signatures and docstrings:
- def test_build_fuzzers_from_commit(self): Tests if the fuzzers can build at a specified commit. This is done by using a kno... | Implement the Python class `BuildImageIntegrationTest` described below.
Class description:
Tests if an image can be built from different states e.g. a commit.
Method signatures and docstrings:
- def test_build_fuzzers_from_commit(self): Tests if the fuzzers can build at a specified commit. This is done by using a kno... | f0275421f84b8f80ee767fb9230134ac97cb687b | <|skeleton|>
class BuildImageIntegrationTest:
"""Tests if an image can be built from different states e.g. a commit."""
def test_build_fuzzers_from_commit(self):
"""Tests if the fuzzers can build at a specified commit. This is done by using a known regression range for a specific test case. The old com... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BuildImageIntegrationTest:
"""Tests if an image can be built from different states e.g. a commit."""
def test_build_fuzzers_from_commit(self):
"""Tests if the fuzzers can build at a specified commit. This is done by using a known regression range for a specific test case. The old commit should sh... | the_stack_v2_python_sparse | infra/build_specified_commit_test.py | google/oss-fuzz | train | 9,438 |
2373044a9e7cddcff1bd79b34500cc44ae84909b | [
"def isPalindrome(i, j) -> bool:\n return s[i:j + 1] == s[i:j + 1][::-1]\ni = 0\ncount = 0\nslen = len(s)\nwhile i < slen:\n j = slen - 1\n while j >= i:\n if isPalindrome(i, j):\n count += 1\n j -= 1\n i += 1\nreturn count",
"count = 0\nslen = len(s)\ni = 0\n\ndef isPalin(i, ... | <|body_start_0|>
def isPalindrome(i, j) -> bool:
return s[i:j + 1] == s[i:j + 1][::-1]
i = 0
count = 0
slen = len(s)
while i < slen:
j = slen - 1
while j >= i:
if isPalindrome(i, j):
count += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countSubString(self, s) -> int:
""":type s: String :return: int"""
<|body_0|>
def countString2(self, s):
"""while (i < len(s) -1) : within while loop : call inner method isPalin(i, j) where i = 0, j = len(s) -1 within isPalin - check if the subArray (i.... | stack_v2_sparse_classes_10k_train_006892 | 1,558 | no_license | [
{
"docstring": ":type s: String :return: int",
"name": "countSubString",
"signature": "def countSubString(self, s) -> int"
},
{
"docstring": "while (i < len(s) -1) : within while loop : call inner method isPalin(i, j) where i = 0, j = len(s) -1 within isPalin - check if the subArray (i.e s[i:j] ... | 2 | stack_v2_sparse_classes_30k_train_002909 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubString(self, s) -> int: :type s: String :return: int
- def countString2(self, s): while (i < len(s) -1) : within while loop : call inner method isPalin(i, j) where i ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSubString(self, s) -> int: :type s: String :return: int
- def countString2(self, s): while (i < len(s) -1) : within while loop : call inner method isPalin(i, j) where i ... | e3e076206b34ff6edf00596a03bc2b5911051cd8 | <|skeleton|>
class Solution:
def countSubString(self, s) -> int:
""":type s: String :return: int"""
<|body_0|>
def countString2(self, s):
"""while (i < len(s) -1) : within while loop : call inner method isPalin(i, j) where i = 0, j = len(s) -1 within isPalin - check if the subArray (i.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def countSubString(self, s) -> int:
""":type s: String :return: int"""
def isPalindrome(i, j) -> bool:
return s[i:j + 1] == s[i:j + 1][::-1]
i = 0
count = 0
slen = len(s)
while i < slen:
j = slen - 1
while j >= i:
... | the_stack_v2_python_sparse | Code/DataStructures/python/leetcode_ds/Py_PalindromicSubstrings_1.py | karanalang/technology | train | 0 | |
a974eccb8e1e0d44c9cfa0b1cb7e0525cab54c81 | [
"if 'L' not in problem_params:\n problem_params['L'] = 1.0\nif 'init_type' not in problem_params:\n problem_params['init_type'] = 'circle'\nessential_keys = ['nvars', 'a', 'kappa', 'rest', 'thresh', 'depol', 'init_type', 'eps']\nfor key in essential_keys:\n if key not in problem_params:\n msg = 'nee... | <|body_start_0|>
if 'L' not in problem_params:
problem_params['L'] = 1.0
if 'init_type' not in problem_params:
problem_params['init_type'] = 'circle'
essential_keys = ['nvars', 'a', 'kappa', 'rest', 'thresh', 'depol', 'init_type', 'eps']
for key in essential_keys:... | Example implementing Allen-Cahn equation in 2D using FFTs for solving linear parts, IMEX time-stepping Attributes: xvalues: grid points in space dx: mesh width lap: spectral operator for Laplacian rfft_object: planned real FFT for forward transformation irfft_object: planned IFFT for backward transformation | monodomain2d_imex | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class monodomain2d_imex:
"""Example implementing Allen-Cahn equation in 2D using FFTs for solving linear parts, IMEX time-stepping Attributes: xvalues: grid points in space dx: mesh width lap: spectral operator for Laplacian rfft_object: planned real FFT for forward transformation irfft_object: planned... | stack_v2_sparse_classes_10k_train_006893 | 5,966 | permissive | [
{
"docstring": "Initialization routine Args: problem_params (dict): custom parameters for the example dtype_u: mesh data type (will be passed to parent class) dtype_f: mesh data type wuth implicit and explicit parts (will be passed to parent class)",
"name": "__init__",
"signature": "def __init__(self, ... | 4 | stack_v2_sparse_classes_30k_train_002796 | Implement the Python class `monodomain2d_imex` described below.
Class description:
Example implementing Allen-Cahn equation in 2D using FFTs for solving linear parts, IMEX time-stepping Attributes: xvalues: grid points in space dx: mesh width lap: spectral operator for Laplacian rfft_object: planned real FFT for forwa... | Implement the Python class `monodomain2d_imex` described below.
Class description:
Example implementing Allen-Cahn equation in 2D using FFTs for solving linear parts, IMEX time-stepping Attributes: xvalues: grid points in space dx: mesh width lap: spectral operator for Laplacian rfft_object: planned real FFT for forwa... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class monodomain2d_imex:
"""Example implementing Allen-Cahn equation in 2D using FFTs for solving linear parts, IMEX time-stepping Attributes: xvalues: grid points in space dx: mesh width lap: spectral operator for Laplacian rfft_object: planned real FFT for forward transformation irfft_object: planned... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class monodomain2d_imex:
"""Example implementing Allen-Cahn equation in 2D using FFTs for solving linear parts, IMEX time-stepping Attributes: xvalues: grid points in space dx: mesh width lap: spectral operator for Laplacian rfft_object: planned real FFT for forward transformation irfft_object: planned IFFT for bac... | the_stack_v2_python_sparse | pySDC/playgrounds/monodomain/Monodomain.py | Parallel-in-Time/pySDC | train | 30 |
e55bfa9c4d6a25e24dfde7a4d9ee0f3718b846d0 | [
"status, error_msg, conn, trans_obj, session_obj = args\nif error_msg == ERROR_MSG_TRANS_ID_NOT_FOUND:\n return make_json_response(success=0, errormsg=error_msg, info='DATAGRID_TRANSACTION_REQUIRED', status=404)\ncolumn_list = []\nif status and conn is not None and (trans_obj is not None) and (session_obj is not... | <|body_start_0|>
status, error_msg, conn, trans_obj, session_obj = args
if error_msg == ERROR_MSG_TRANS_ID_NOT_FOUND:
return make_json_response(success=0, errormsg=error_msg, info='DATAGRID_TRANSACTION_REQUIRED', status=404)
column_list = []
if status and conn is not None and... | FilterDialog | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterDialog:
def get(*args):
"""To fetch the current sorted columns"""
<|body_0|>
def save(*args, **kwargs):
"""To save the sorted columns"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
status, error_msg, conn, trans_obj, session_obj = args
... | stack_v2_sparse_classes_10k_train_006894 | 3,733 | permissive | [
{
"docstring": "To fetch the current sorted columns",
"name": "get",
"signature": "def get(*args)"
},
{
"docstring": "To save the sorted columns",
"name": "save",
"signature": "def save(*args, **kwargs)"
}
] | 2 | null | Implement the Python class `FilterDialog` described below.
Class description:
Implement the FilterDialog class.
Method signatures and docstrings:
- def get(*args): To fetch the current sorted columns
- def save(*args, **kwargs): To save the sorted columns | Implement the Python class `FilterDialog` described below.
Class description:
Implement the FilterDialog class.
Method signatures and docstrings:
- def get(*args): To fetch the current sorted columns
- def save(*args, **kwargs): To save the sorted columns
<|skeleton|>
class FilterDialog:
def get(*args):
... | 2cb4b45dd14a230aa0e800042e893f8dfb23beda | <|skeleton|>
class FilterDialog:
def get(*args):
"""To fetch the current sorted columns"""
<|body_0|>
def save(*args, **kwargs):
"""To save the sorted columns"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FilterDialog:
def get(*args):
"""To fetch the current sorted columns"""
status, error_msg, conn, trans_obj, session_obj = args
if error_msg == ERROR_MSG_TRANS_ID_NOT_FOUND:
return make_json_response(success=0, errormsg=error_msg, info='DATAGRID_TRANSACTION_REQUIRED', status... | the_stack_v2_python_sparse | _MY_ORGS/Web-Dev-Collaborative/blog-research/database/pg-admin/web/pgadmin/tools/sqleditor/utils/filter_dialog.py | bgoonz/UsefulResourceRepo2.0 | train | 10 | |
20239d74b7bf130ec089b9d12ba6bea5ed1c85a9 | [
"if '/' not in value:\n if ';' in value:\n raise errors.DeserializationError('Unexpected semi-colon')\n return cls.PREFIX + value\nreturn value",
"if ';' not in value:\n assert value.startswith(cls.PREFIX)\n return value[len(cls.PREFIX):]\nreturn value"
] | <|body_start_0|>
if '/' not in value:
if ';' in value:
raise errors.DeserializationError('Unexpected semi-colon')
return cls.PREFIX + value
return value
<|end_body_0|>
<|body_start_1|>
if ';' not in value:
assert value.startswith(cls.PREFIX)
... | MediaType field encoder/decoder. | MediaType | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MediaType:
"""MediaType field encoder/decoder."""
def decode(cls, value):
"""Decoder."""
<|body_0|>
def encode(cls, value):
"""Encoder."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if '/' not in value:
if ';' in value:
... | stack_v2_sparse_classes_10k_train_006895 | 14,260 | permissive | [
{
"docstring": "Decoder.",
"name": "decode",
"signature": "def decode(cls, value)"
},
{
"docstring": "Encoder.",
"name": "encode",
"signature": "def encode(cls, value)"
}
] | 2 | null | Implement the Python class `MediaType` described below.
Class description:
MediaType field encoder/decoder.
Method signatures and docstrings:
- def decode(cls, value): Decoder.
- def encode(cls, value): Encoder. | Implement the Python class `MediaType` described below.
Class description:
MediaType field encoder/decoder.
Method signatures and docstrings:
- def decode(cls, value): Decoder.
- def encode(cls, value): Encoder.
<|skeleton|>
class MediaType:
"""MediaType field encoder/decoder."""
def decode(cls, value):
... | 4082346ef8d5e6a8365b05752be41186840dc868 | <|skeleton|>
class MediaType:
"""MediaType field encoder/decoder."""
def decode(cls, value):
"""Decoder."""
<|body_0|>
def encode(cls, value):
"""Encoder."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MediaType:
"""MediaType field encoder/decoder."""
def decode(cls, value):
"""Decoder."""
if '/' not in value:
if ';' in value:
raise errors.DeserializationError('Unexpected semi-colon')
return cls.PREFIX + value
return value
def encode(... | the_stack_v2_python_sparse | desktop/core/ext-py/josepy-1.1.0/src/josepy/jws.py | oyorooms/hue | train | 4 |
34086c3d695312db7a5c06d83c72ed934239bef5 | [
"self.file = None\nself.tmp_file = None\nself.pipe = []\nif file_path:\n try:\n if file_override:\n self.file = open(file_path, 'wt')\n else:\n self.file = open(file_path, 'at')\n except FileNotFoundError as e:\n '\\n 只是特别标注出来这里可能弹出的错误。\\n ... | <|body_start_0|>
self.file = None
self.tmp_file = None
self.pipe = []
if file_path:
try:
if file_override:
self.file = open(file_path, 'wt')
else:
self.file = open(file_path, 'at')
except File... | 重定向输出 | StdoutRedirection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StdoutRedirection:
"""重定向输出"""
def __init__(self, file_path=None, file_override=True):
"""如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。"""
<|body_0|>
def context(self):
"""重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进入with时执行，yield为with语句... | stack_v2_sparse_classes_10k_train_006896 | 4,538 | no_license | [
{
"docstring": "如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。",
"name": "__init__",
"signature": "def __init__(self, file_path=None, file_override=True)"
},
{
"docstring": "重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进入with时执行，yield为with语句返回值，yield后退出with时执行",
"name"... | 2 | stack_v2_sparse_classes_30k_train_005397 | Implement the Python class `StdoutRedirection` described below.
Class description:
重定向输出
Method signatures and docstrings:
- def __init__(self, file_path=None, file_override=True): 如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。
- def context(self): 重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进... | Implement the Python class `StdoutRedirection` described below.
Class description:
重定向输出
Method signatures and docstrings:
- def __init__(self, file_path=None, file_override=True): 如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。
- def context(self): 重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进... | d44f7303bc4ce3764a300830d361115200ad3602 | <|skeleton|>
class StdoutRedirection:
"""重定向输出"""
def __init__(self, file_path=None, file_override=True):
"""如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。"""
<|body_0|>
def context(self):
"""重定向输出的上下文管理器 contextlib.contextmanager装饰器自动将协程转换为上下文管理器 yield前为进入with时执行，yield为with语句... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StdoutRedirection:
"""重定向输出"""
def __init__(self, file_path=None, file_override=True):
"""如果提供了文件目录，就尝试打开文件，稍后将会将输出重定向到文件。 否则将输出重定向到内部列表pipe。"""
self.file = None
self.tmp_file = None
self.pipe = []
if file_path:
try:
if file_override:
... | the_stack_v2_python_sparse | pysh/manage/middleware.py | Arianxx/Pysh | train | 18 |
bc4d46732f75a2a555f9885a97c64260cabaf1c7 | [
"root_to_leaf = curr_sum = 0\nwhile root:\n if root.left:\n predecessor = root.left\n steps = 1\n while predecessor.right and predecessor.right is not root:\n predecessor = predecessor.right\n steps += 1\n if not predecessor.right:\n curr_sum = curr_su... | <|body_start_0|>
root_to_leaf = curr_sum = 0
while root:
if root.left:
predecessor = root.left
steps = 1
while predecessor.right and predecessor.right is not root:
predecessor = predecessor.right
steps +=... | RootToLeaf | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RootToLeaf:
def get_sum(self, root: 'TreeNode') -> int:
"""Approach: Morris Traversal Time Complexity: O(N) Space Complexity: O(1) :param root: :return:"""
<|body_0|>
def get__sum(self, root: 'TreeNode') -> int:
"""Approach: Breadth First Search Time Complexity: O(N)... | stack_v2_sparse_classes_10k_train_006897 | 3,287 | no_license | [
{
"docstring": "Approach: Morris Traversal Time Complexity: O(N) Space Complexity: O(1) :param root: :return:",
"name": "get_sum",
"signature": "def get_sum(self, root: 'TreeNode') -> int"
},
{
"docstring": "Approach: Breadth First Search Time Complexity: O(N) Space Complexity: O(H) :param root:... | 3 | null | Implement the Python class `RootToLeaf` described below.
Class description:
Implement the RootToLeaf class.
Method signatures and docstrings:
- def get_sum(self, root: 'TreeNode') -> int: Approach: Morris Traversal Time Complexity: O(N) Space Complexity: O(1) :param root: :return:
- def get__sum(self, root: 'TreeNode... | Implement the Python class `RootToLeaf` described below.
Class description:
Implement the RootToLeaf class.
Method signatures and docstrings:
- def get_sum(self, root: 'TreeNode') -> int: Approach: Morris Traversal Time Complexity: O(N) Space Complexity: O(1) :param root: :return:
- def get__sum(self, root: 'TreeNode... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class RootToLeaf:
def get_sum(self, root: 'TreeNode') -> int:
"""Approach: Morris Traversal Time Complexity: O(N) Space Complexity: O(1) :param root: :return:"""
<|body_0|>
def get__sum(self, root: 'TreeNode') -> int:
"""Approach: Breadth First Search Time Complexity: O(N)... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RootToLeaf:
def get_sum(self, root: 'TreeNode') -> int:
"""Approach: Morris Traversal Time Complexity: O(N) Space Complexity: O(1) :param root: :return:"""
root_to_leaf = curr_sum = 0
while root:
if root.left:
predecessor = root.left
steps = ... | the_stack_v2_python_sparse | revisited/trees/sum_root_to_leaf_numbers.py | Shiv2157k/leet_code | train | 1 | |
9a271f9b08b3c1b6fd0d99f87872cbeb78d93115 | [
"if db_field.name == 'topic' and (not request.user.is_superuser):\n kwargs['queryset'] = Topic.objects.filter(id__in=request.user.profile.topics.all())\nreturn super(TopicTableAdmin, self).formfield_for_foreignkey(db_field, request, **kwargs)",
"topic = TopicTable.objects.get(id=object_id)\noff_days = [day for... | <|body_start_0|>
if db_field.name == 'topic' and (not request.user.is_superuser):
kwargs['queryset'] = Topic.objects.filter(id__in=request.user.profile.topics.all())
return super(TopicTableAdmin, self).formfield_for_foreignkey(db_field, request, **kwargs)
<|end_body_0|>
<|body_start_1|>
... | TopicTableAdmin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopicTableAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""limits Topics field to user's topics."""
<|body_0|>
def change_view(self, request, object_id, form_url='', extra_context=None):
"""Overrides the change view that displays change_form... | stack_v2_sparse_classes_10k_train_006898 | 9,167 | permissive | [
{
"docstring": "limits Topics field to user's topics.",
"name": "formfield_for_foreignkey",
"signature": "def formfield_for_foreignkey(self, db_field, request, **kwargs)"
},
{
"docstring": "Overrides the change view that displays change_form.html",
"name": "change_view",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_000798 | Implement the Python class `TopicTableAdmin` described below.
Class description:
Implement the TopicTableAdmin class.
Method signatures and docstrings:
- def formfield_for_foreignkey(self, db_field, request, **kwargs): limits Topics field to user's topics.
- def change_view(self, request, object_id, form_url='', extr... | Implement the Python class `TopicTableAdmin` described below.
Class description:
Implement the TopicTableAdmin class.
Method signatures and docstrings:
- def formfield_for_foreignkey(self, db_field, request, **kwargs): limits Topics field to user's topics.
- def change_view(self, request, object_id, form_url='', extr... | 70638c121ea85ff0e6a650c5f2641b0b3b04d6d0 | <|skeleton|>
class TopicTableAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""limits Topics field to user's topics."""
<|body_0|>
def change_view(self, request, object_id, form_url='', extra_context=None):
"""Overrides the change view that displays change_form... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TopicTableAdmin:
def formfield_for_foreignkey(self, db_field, request, **kwargs):
"""limits Topics field to user's topics."""
if db_field.name == 'topic' and (not request.user.is_superuser):
kwargs['queryset'] = Topic.objects.filter(id__in=request.user.profile.topics.all())
... | the_stack_v2_python_sparse | cms/admin.py | Ibrahem3amer/bala7 | train | 0 | |
9ed3c9b3df737c1e17fe1e02aa4f564f81562f9c | [
"self.arr = []\nself.size = maxSize\nself.offset = []",
"if len(self.arr) == self.size:\n return\nself.arr.append(x)\nself.offset.append(0)",
"if not self.arr:\n return -1\nif len(self.offset) > 1:\n self.offset[-2] += self.offset[-1]\nreturn self.arr.pop() + self.offset.pop()",
"if not self.arr:\n ... | <|body_start_0|>
self.arr = []
self.size = maxSize
self.offset = []
<|end_body_0|>
<|body_start_1|>
if len(self.arr) == self.size:
return
self.arr.append(x)
self.offset.append(0)
<|end_body_1|>
<|body_start_2|>
if not self.arr:
return -1
... | CustomStack | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomStack:
def __init__(self, maxSize):
""":type maxSize: int"""
<|body_0|>
def push(self, x):
""":type x: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int"""
<|body_2|>
def increment(self, k, val):
""":type k: ... | stack_v2_sparse_classes_10k_train_006899 | 954 | no_license | [
{
"docstring": ":type maxSize: int",
"name": "__init__",
"signature": "def __init__(self, maxSize)"
},
{
"docstring": ":type x: int :rtype: None",
"name": "push",
"signature": "def push(self, x)"
},
{
"docstring": ":rtype: int",
"name": "pop",
"signature": "def pop(self)"... | 4 | stack_v2_sparse_classes_30k_train_000934 | Implement the Python class `CustomStack` described below.
Class description:
Implement the CustomStack class.
Method signatures and docstrings:
- def __init__(self, maxSize): :type maxSize: int
- def push(self, x): :type x: int :rtype: None
- def pop(self): :rtype: int
- def increment(self, k, val): :type k: int :typ... | Implement the Python class `CustomStack` described below.
Class description:
Implement the CustomStack class.
Method signatures and docstrings:
- def __init__(self, maxSize): :type maxSize: int
- def push(self, x): :type x: int :rtype: None
- def pop(self): :rtype: int
- def increment(self, k, val): :type k: int :typ... | 238995bd23c8a6c40c6035890e94baa2473d4bbc | <|skeleton|>
class CustomStack:
def __init__(self, maxSize):
""":type maxSize: int"""
<|body_0|>
def push(self, x):
""":type x: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int"""
<|body_2|>
def increment(self, k, val):
""":type k: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CustomStack:
def __init__(self, maxSize):
""":type maxSize: int"""
self.arr = []
self.size = maxSize
self.offset = []
def push(self, x):
""":type x: int :rtype: None"""
if len(self.arr) == self.size:
return
self.arr.append(x)
sel... | the_stack_v2_python_sparse | problems/N1381_Design_A_Stack_With_Increment_Operation.py | wan-catherine/Leetcode | train | 5 |
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