blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
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value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
87f603b715a1859ca1275bcf28cd6c2565bf93a0 | [
"self.initial_date = initial_date\nself.until_date = until_date\nlog.debug('self.initial_date: {}'.format(self.initial_date))\nlog.debug('self.until_date: {}'.format(self.until_date))",
"log.debug('Build all')\nprint('Building...')\nlog.debug('Detail')\nprint('\\nAdding to details table for:')\nself.dict_parse('D... | <|body_start_0|>
self.initial_date = initial_date
self.until_date = until_date
log.debug('self.initial_date: {}'.format(self.initial_date))
log.debug('self.until_date: {}'.format(self.until_date))
<|end_body_0|>
<|body_start_1|>
log.debug('Build all')
print('Building...'... | Take structured data and enter into database. | Build | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Build:
"""Take structured data and enter into database."""
def __init__(self, initial_date=None, until_date=None):
"""Create class variables for date range and connect to database."""
<|body_0|>
def build_all(self):
"""Run through all of the building methods."""
... | stack_v2_sparse_classes_36k_train_032400 | 4,162 | no_license | [
{
"docstring": "Create class variables for date range and connect to database.",
"name": "__init__",
"signature": "def __init__(self, initial_date=None, until_date=None)"
},
{
"docstring": "Run through all of the building methods.",
"name": "build_all",
"signature": "def build_all(self)"... | 5 | stack_v2_sparse_classes_30k_train_002075 | Implement the Python class `Build` described below.
Class description:
Take structured data and enter into database.
Method signatures and docstrings:
- def __init__(self, initial_date=None, until_date=None): Create class variables for date range and connect to database.
- def build_all(self): Run through all of the ... | Implement the Python class `Build` described below.
Class description:
Take structured data and enter into database.
Method signatures and docstrings:
- def __init__(self, initial_date=None, until_date=None): Create class variables for date range and connect to database.
- def build_all(self): Run through all of the ... | 4ad7c77ab56681e9ca8e1dd1033a32c21c498d75 | <|skeleton|>
class Build:
"""Take structured data and enter into database."""
def __init__(self, initial_date=None, until_date=None):
"""Create class variables for date range and connect to database."""
<|body_0|>
def build_all(self):
"""Run through all of the building methods."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Build:
"""Take structured data and enter into database."""
def __init__(self, initial_date=None, until_date=None):
"""Create class variables for date range and connect to database."""
self.initial_date = initial_date
self.until_date = until_date
log.debug('self.initial_dat... | the_stack_v2_python_sparse | scripts/build.py | TheLens/realestate | train | 1 |
39b727e43856d43058508816cc79c393404aa2a8 | [
"self._max_displacement = kwargs.pop('max_displacement', 0.0)\nself._views_per_segment = kwargs.pop('views_per_segment', 1)\nsuper().__init__(*args, **kwargs)\nif self._phases is not None:\n raise ValueError(f'Layer {self.__class__.__name__} does not support multiple phases.')\nif isinstance(self._max_displaceme... | <|body_start_0|>
self._max_displacement = kwargs.pop('max_displacement', 0.0)
self._views_per_segment = kwargs.pop('views_per_segment', 1)
super().__init__(*args, **kwargs)
if self._phases is not None:
raise ValueError(f'Layer {self.__class__.__name__} does not support multip... | K-space resampling layer with motion. Accepts the same arguments as `KSpaceResampling`, plus those defined below. Args: max_displacement: A list of floats defining the maximum displacement (in pixels) along each spatial dimension. If a scalar is given, the same displacement will be used in all dimensions. Each element ... | KSpaceResamplingWithMotion | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KSpaceResamplingWithMotion:
"""K-space resampling layer with motion. Accepts the same arguments as `KSpaceResampling`, plus those defined below. Args: max_displacement: A list of floats defining the maximum displacement (in pixels) along each spatial dimension. If a scalar is given, the same disp... | stack_v2_sparse_classes_36k_train_032401 | 4,786 | permissive | [
{
"docstring": "Initializes the layer.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Adds motion to k-space. Args: kspace: The input k-space. Returns: The processed k-space. Raises: ValueError: If `kspace` does not have rank 2.",
"name": "process... | 3 | stack_v2_sparse_classes_30k_test_000731 | Implement the Python class `KSpaceResamplingWithMotion` described below.
Class description:
K-space resampling layer with motion. Accepts the same arguments as `KSpaceResampling`, plus those defined below. Args: max_displacement: A list of floats defining the maximum displacement (in pixels) along each spatial dimensi... | Implement the Python class `KSpaceResamplingWithMotion` described below.
Class description:
K-space resampling layer with motion. Accepts the same arguments as `KSpaceResampling`, plus those defined below. Args: max_displacement: A list of floats defining the maximum displacement (in pixels) along each spatial dimensi... | cfd8930ee5281e7f6dceb17c4a5acaf625fd3243 | <|skeleton|>
class KSpaceResamplingWithMotion:
"""K-space resampling layer with motion. Accepts the same arguments as `KSpaceResampling`, plus those defined below. Args: max_displacement: A list of floats defining the maximum displacement (in pixels) along each spatial dimension. If a scalar is given, the same disp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KSpaceResamplingWithMotion:
"""K-space resampling layer with motion. Accepts the same arguments as `KSpaceResampling`, plus those defined below. Args: max_displacement: A list of floats defining the maximum displacement (in pixels) along each spatial dimension. If a scalar is given, the same displacement will... | the_stack_v2_python_sparse | tensorflow_mri/python/experimental/layers.py | mrphys/tensorflow-mri | train | 29 |
5428bac5c6596defc999771d5be27ceeb6966afb | [
"if user_id is None or type(user_id) != str:\n return None\nsession_id = str(uuid4())\nself.user_id_by_session_id[session_id] = user_id\nreturn session_id",
"if session_id is None or type(session_id) != str:\n return None\nreturn self.user_id_by_session_id.get(session_id)",
"sesh_cookie = self.session_coo... | <|body_start_0|>
if user_id is None or type(user_id) != str:
return None
session_id = str(uuid4())
self.user_id_by_session_id[session_id] = user_id
return session_id
<|end_body_0|>
<|body_start_1|>
if session_id is None or type(session_id) != str:
return ... | inherits from auth | SessionAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionAuth:
"""inherits from auth"""
def create_session(self, user_id: str=None) -> str:
"""creates a session id"""
<|body_0|>
def user_id_for_session_id(self, session_id: str=None) -> str:
"""get a user id from session id"""
<|body_1|>
def current_... | stack_v2_sparse_classes_36k_train_032402 | 1,573 | no_license | [
{
"docstring": "creates a session id",
"name": "create_session",
"signature": "def create_session(self, user_id: str=None) -> str"
},
{
"docstring": "get a user id from session id",
"name": "user_id_for_session_id",
"signature": "def user_id_for_session_id(self, session_id: str=None) -> ... | 4 | stack_v2_sparse_classes_30k_train_010508 | Implement the Python class `SessionAuth` described below.
Class description:
inherits from auth
Method signatures and docstrings:
- def create_session(self, user_id: str=None) -> str: creates a session id
- def user_id_for_session_id(self, session_id: str=None) -> str: get a user id from session id
- def current_user... | Implement the Python class `SessionAuth` described below.
Class description:
inherits from auth
Method signatures and docstrings:
- def create_session(self, user_id: str=None) -> str: creates a session id
- def user_id_for_session_id(self, session_id: str=None) -> str: get a user id from session id
- def current_user... | c0182a227da7a47fd641b3d9e085243b36b626db | <|skeleton|>
class SessionAuth:
"""inherits from auth"""
def create_session(self, user_id: str=None) -> str:
"""creates a session id"""
<|body_0|>
def user_id_for_session_id(self, session_id: str=None) -> str:
"""get a user id from session id"""
<|body_1|>
def current_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SessionAuth:
"""inherits from auth"""
def create_session(self, user_id: str=None) -> str:
"""creates a session id"""
if user_id is None or type(user_id) != str:
return None
session_id = str(uuid4())
self.user_id_by_session_id[session_id] = user_id
retur... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_auth.py | Jilroge7/holbertonschool-web_back_end | train | 0 |
7f3bb12b0768465457da27b44b2ab3cbbea5df9d | [
"super().__init__()\nself.N = N\nself.dm = dm\nself.embedding = tf.keras.layers.Embedding(target_vocab, dm)\nself.positional_encoding = positional_encoding(max_seq_len, dm)\nself.blocks = [DecoderBlock(dm, h, hidden, drop_rate) for _ in range(N)]\nself.dropout = tf.keras.layers.Dropout(drop_rate)",
"seq_len = x.s... | <|body_start_0|>
super().__init__()
self.N = N
self.dm = dm
self.embedding = tf.keras.layers.Embedding(target_vocab, dm)
self.positional_encoding = positional_encoding(max_seq_len, dm)
self.blocks = [DecoderBlock(dm, h, hidden, drop_rate) for _ in range(N)]
self.d... | the decoder for a transformer: | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""the decoder for a transformer:"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Args: -dm - the dimensionality of the model -h - the number of heads -hidden - the number of hidden units in the fully connected layer -target_vocab - the ... | stack_v2_sparse_classes_36k_train_032403 | 2,490 | no_license | [
{
"docstring": "Args: -dm - the dimensionality of the model -h - the number of heads -hidden - the number of hidden units in the fully connected layer -target_vocab - the size of the target vocabulary -max_seq_len - the maximum sequence length possible -drop_rate - the dropout rate",
"name": "__init__",
... | 2 | stack_v2_sparse_classes_30k_train_007824 | Implement the Python class `Decoder` described below.
Class description:
the decoder for a transformer:
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1): Args: -dm - the dimensionality of the model -h - the number of heads -hidden - the number of hidde... | Implement the Python class `Decoder` described below.
Class description:
the decoder for a transformer:
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1): Args: -dm - the dimensionality of the model -h - the number of heads -hidden - the number of hidde... | 7dafc37d306fcf2ea0f5af5bd97dfd78d388100c | <|skeleton|>
class Decoder:
"""the decoder for a transformer:"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Args: -dm - the dimensionality of the model -h - the number of heads -hidden - the number of hidden units in the fully connected layer -target_vocab - the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decoder:
"""the decoder for a transformer:"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Args: -dm - the dimensionality of the model -h - the number of heads -hidden - the number of hidden units in the fully connected layer -target_vocab - the size of the t... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/10-transformer_decoder.py | AndresSern/holbertonschool-machine_learning-1 | train | 0 |
bea455fe7a70fbb28bed089de125be7eedbc3c20 | [
"self.__wrapped = wrapped\nself.__retry_if = retry_if\nself.__backoff = backoff\nif self.__backoff <= 0:\n raise ValueError('backoff must be positive')\nself.__multiplier = multiplier\nif self.__multiplier < 1:\n raise ValueError('multiplier must be at least one!')\nself.__max_tries = max_tries\nself.__max_ba... | <|body_start_0|>
self.__wrapped = wrapped
self.__retry_if = retry_if
self.__backoff = backoff
if self.__backoff <= 0:
raise ValueError('backoff must be positive')
self.__multiplier = multiplier
if self.__multiplier < 1:
raise ValueError('multiplier... | Handle transient errors, with configurable backoff. This class can wrap any object. The wrapped object will behave like the original one, except that if you call a function and it raises a retriable exception, we'll back off for a certain number of seconds and call the function again, until it succeeds or we get a non-... | RetryWrapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetryWrapper:
"""Handle transient errors, with configurable backoff. This class can wrap any object. The wrapped object will behave like the original one, except that if you call a function and it raises a retriable exception, we'll back off for a certain number of seconds and call the function a... | stack_v2_sparse_classes_36k_train_032404 | 4,804 | permissive | [
{
"docstring": "Wrap the given object. :param wrapped: the object to wrap :param retry_if: a method that takes an exception, and returns whether we should retry :type backoff: float :param backoff: the number of seconds to wait the first time we get a retriable error :type multiplier: float :param multiplier: i... | 3 | stack_v2_sparse_classes_30k_train_020322 | Implement the Python class `RetryWrapper` described below.
Class description:
Handle transient errors, with configurable backoff. This class can wrap any object. The wrapped object will behave like the original one, except that if you call a function and it raises a retriable exception, we'll back off for a certain nu... | Implement the Python class `RetryWrapper` described below.
Class description:
Handle transient errors, with configurable backoff. This class can wrap any object. The wrapped object will behave like the original one, except that if you call a function and it raises a retriable exception, we'll back off for a certain nu... | fe21995e0402878437a828c6a4244025eac8c43b | <|skeleton|>
class RetryWrapper:
"""Handle transient errors, with configurable backoff. This class can wrap any object. The wrapped object will behave like the original one, except that if you call a function and it raises a retriable exception, we'll back off for a certain number of seconds and call the function a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RetryWrapper:
"""Handle transient errors, with configurable backoff. This class can wrap any object. The wrapped object will behave like the original one, except that if you call a function and it raises a retriable exception, we'll back off for a certain number of seconds and call the function again, until i... | the_stack_v2_python_sparse | python_modules/libraries/dagster-aws/dagster_aws/utils/mrjob/retry.py | dagster-io/dagster | train | 8,565 |
d412ec8ddcc4a76fcedf9d8f1cb3534559652fbd | [
"g_circuits, g_parameter_values, g_parameters = self._preprocess(circuits, parameter_values, parameters, self.SUPPORTED_GATES)\nresults = self._run_unique(g_circuits, observables, g_parameter_values, g_parameters, **options)\nreturn self._postprocess(results, circuits, parameter_values, parameters)",
"job_circuit... | <|body_start_0|>
g_circuits, g_parameter_values, g_parameters = self._preprocess(circuits, parameter_values, parameters, self.SUPPORTED_GATES)
results = self._run_unique(g_circuits, observables, g_parameter_values, g_parameters, **options)
return self._postprocess(results, circuits, parameter_va... | Compute the gradients of the expectation values by the parameter shift rule [1]. **Reference:** [1] Schuld, M., Bergholm, V., Gogolin, C., Izaac, J., and Killoran, N. Evaluating analytic gradients on quantum hardware, `DOI <https://doi.org/10.1103/PhysRevA.99.032331>`_ | ParamShiftEstimatorGradient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParamShiftEstimatorGradient:
"""Compute the gradients of the expectation values by the parameter shift rule [1]. **Reference:** [1] Schuld, M., Bergholm, V., Gogolin, C., Izaac, J., and Killoran, N. Evaluating analytic gradients on quantum hardware, `DOI <https://doi.org/10.1103/PhysRevA.99.03233... | stack_v2_sparse_classes_36k_train_032405 | 4,346 | permissive | [
{
"docstring": "Compute the gradients of the expectation values by the parameter shift rule.",
"name": "_run",
"signature": "def _run(self, circuits: Sequence[QuantumCircuit], observables: Sequence[BaseOperator | PauliSumOp], parameter_values: Sequence[Sequence[float]], parameters: Sequence[Sequence[Par... | 2 | null | Implement the Python class `ParamShiftEstimatorGradient` described below.
Class description:
Compute the gradients of the expectation values by the parameter shift rule [1]. **Reference:** [1] Schuld, M., Bergholm, V., Gogolin, C., Izaac, J., and Killoran, N. Evaluating analytic gradients on quantum hardware, `DOI <ht... | Implement the Python class `ParamShiftEstimatorGradient` described below.
Class description:
Compute the gradients of the expectation values by the parameter shift rule [1]. **Reference:** [1] Schuld, M., Bergholm, V., Gogolin, C., Izaac, J., and Killoran, N. Evaluating analytic gradients on quantum hardware, `DOI <ht... | 0b51250e219ca303654fc28a318c21366584ccd3 | <|skeleton|>
class ParamShiftEstimatorGradient:
"""Compute the gradients of the expectation values by the parameter shift rule [1]. **Reference:** [1] Schuld, M., Bergholm, V., Gogolin, C., Izaac, J., and Killoran, N. Evaluating analytic gradients on quantum hardware, `DOI <https://doi.org/10.1103/PhysRevA.99.03233... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParamShiftEstimatorGradient:
"""Compute the gradients of the expectation values by the parameter shift rule [1]. **Reference:** [1] Schuld, M., Bergholm, V., Gogolin, C., Izaac, J., and Killoran, N. Evaluating analytic gradients on quantum hardware, `DOI <https://doi.org/10.1103/PhysRevA.99.032331>`_"""
... | the_stack_v2_python_sparse | qiskit/algorithms/gradients/param_shift/param_shift_estimator_gradient.py | 1ucian0/qiskit-terra | train | 6 |
e4e134af1fc2cc25a64983c1c94a2ed4c44d1373 | [
"self.n_bins = n_bins\nself.bins = np.linspace(0, 255, n_bins + 1)\nself.alpha = alpha",
"rgb_image = image.convert('RGB').resize((50, 50), resample=Image.NEAREST)\npixel_array = np.array(rgb_image).reshape(-1, 3)\nrepeated_pixel_array = np.repeat(pixel_array, 10, axis=0)\nnoise = np.random.normal(0, self.alpha, ... | <|body_start_0|>
self.n_bins = n_bins
self.bins = np.linspace(0, 255, n_bins + 1)
self.alpha = alpha
<|end_body_0|>
<|body_start_1|>
rgb_image = image.convert('RGB').resize((50, 50), resample=Image.NEAREST)
pixel_array = np.array(rgb_image).reshape(-1, 3)
repeated_pixel_... | A class for embedding color information from an image. | ColorEmbedder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColorEmbedder:
"""A class for embedding color information from an image."""
def __init__(self, n_bins: int=8, alpha: float=5):
"""Initialize the ColorEmbedder object. Args: n_bins (int): Number of color bins to use. alpha (float): Standard deviation of the noise added to each pixel."... | stack_v2_sparse_classes_36k_train_032406 | 2,172 | permissive | [
{
"docstring": "Initialize the ColorEmbedder object. Args: n_bins (int): Number of color bins to use. alpha (float): Standard deviation of the noise added to each pixel.",
"name": "__init__",
"signature": "def __init__(self, n_bins: int=8, alpha: float=5)"
},
{
"docstring": "Embed color informat... | 2 | stack_v2_sparse_classes_30k_train_011930 | Implement the Python class `ColorEmbedder` described below.
Class description:
A class for embedding color information from an image.
Method signatures and docstrings:
- def __init__(self, n_bins: int=8, alpha: float=5): Initialize the ColorEmbedder object. Args: n_bins (int): Number of color bins to use. alpha (floa... | Implement the Python class `ColorEmbedder` described below.
Class description:
A class for embedding color information from an image.
Method signatures and docstrings:
- def __init__(self, n_bins: int=8, alpha: float=5): Initialize the ColorEmbedder object. Args: n_bins (int): Number of color bins to use. alpha (floa... | f5d158de6d4d652e7264093c64420288ecb6a85b | <|skeleton|>
class ColorEmbedder:
"""A class for embedding color information from an image."""
def __init__(self, n_bins: int=8, alpha: float=5):
"""Initialize the ColorEmbedder object. Args: n_bins (int): Number of color bins to use. alpha (float): Standard deviation of the noise added to each pixel."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ColorEmbedder:
"""A class for embedding color information from an image."""
def __init__(self, n_bins: int=8, alpha: float=5):
"""Initialize the ColorEmbedder object. Args: n_bins (int): Number of color bins to use. alpha (float): Standard deviation of the noise added to each pixel."""
se... | the_stack_v2_python_sparse | knn-colours/pipeline/src/embedder.py | wellcomecollection/data-science | train | 7 |
2a9498ee61aef7e05d13ba8ff8ef989ad3c603ac | [
"basket = Inventory()\ndrsim = SouthAsian()\nhadji = MiddleEastern()\njonny = American()\nfor n in range(2):\n basket.add_coconut(drsim)\nfor n in range(1):\n basket.add_coconut(hadji)\nfor n in range(3):\n basket.add_coconut(jonny)\nexpected = 19.0\nresult = basket.total_weight()\nself.assertEqual(result,... | <|body_start_0|>
basket = Inventory()
drsim = SouthAsian()
hadji = MiddleEastern()
jonny = American()
for n in range(2):
basket.add_coconut(drsim)
for n in range(1):
basket.add_coconut(hadji)
for n in range(3):
basket.add_coconu... | Tests add_coconut(), total_weight() methods and tests that weights for each coconut type are different | TestCocoNuts | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCocoNuts:
"""Tests add_coconut(), total_weight() methods and tests that weights for each coconut type are different"""
def test_weight(self):
"""Ensures that given defined weights, the total_weight() method returns the correct total weight. Add following coconut numbers: South As... | stack_v2_sparse_classes_36k_train_032407 | 1,940 | no_license | [
{
"docstring": "Ensures that given defined weights, the total_weight() method returns the correct total weight. Add following coconut numbers: South Asian=2, Middle Eastern=1, American=3",
"name": "test_weight",
"signature": "def test_weight(self)"
},
{
"docstring": "Ensure that add_coconut() th... | 3 | null | Implement the Python class `TestCocoNuts` described below.
Class description:
Tests add_coconut(), total_weight() methods and tests that weights for each coconut type are different
Method signatures and docstrings:
- def test_weight(self): Ensures that given defined weights, the total_weight() method returns the corr... | Implement the Python class `TestCocoNuts` described below.
Class description:
Tests add_coconut(), total_weight() methods and tests that weights for each coconut type are different
Method signatures and docstrings:
- def test_weight(self): Ensures that given defined weights, the total_weight() method returns the corr... | b32f83aa1b705a5ad384b73c618f04f7d2622753 | <|skeleton|>
class TestCocoNuts:
"""Tests add_coconut(), total_weight() methods and tests that weights for each coconut type are different"""
def test_weight(self):
"""Ensures that given defined weights, the total_weight() method returns the correct total weight. Add following coconut numbers: South As... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCocoNuts:
"""Tests add_coconut(), total_weight() methods and tests that weights for each coconut type are different"""
def test_weight(self):
"""Ensures that given defined weights, the total_weight() method returns the correct total weight. Add following coconut numbers: South Asian=2, Middle... | the_stack_v2_python_sparse | ostPython3/test_coconuts.py | deepbsd/OST_Python | train | 1 |
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_36k_train_032408 | 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_020307 | 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_36k | 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 |
e944f9e3128a9961c73d637627ed381829741cc9 | [
"from real_time_detection.GUI.EmotivDeviceReader import EmotivDeviceReader\nself.emotiv_reader = EmotivDeviceReader()\nself.input_type = input_type\nif self.input_type == 'file':\n self.raw_EEG_obj = mne.io.read_raw_fif(file_path, preload=True)\n max_time = self.raw_EEG_obj.times.max()\n self.raw_EEG_obj.c... | <|body_start_0|>
from real_time_detection.GUI.EmotivDeviceReader import EmotivDeviceReader
self.emotiv_reader = EmotivDeviceReader()
self.input_type = input_type
if self.input_type == 'file':
self.raw_EEG_obj = mne.io.read_raw_fif(file_path, preload=True)
max_time... | This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features. | EEGReader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EEGReader:
"""This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features."""
def __init__(self, input_type, file_path=None):
"""Arguments: input_type: 'f... | stack_v2_sparse_classes_36k_train_032409 | 3,357 | permissive | [
{
"docstring": "Arguments: input_type: 'file' indicates that the stream is from file. In other case, the stream will from the 'Emotiv insight' device.",
"name": "__init__",
"signature": "def __init__(self, input_type, file_path=None)"
},
{
"docstring": "Return: EEG data: the EEG data timestamp: ... | 2 | stack_v2_sparse_classes_30k_train_000613 | Implement the Python class `EEGReader` described below.
Class description:
This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features.
Method signatures and docstrings:
- def __init__(sel... | Implement the Python class `EEGReader` described below.
Class description:
This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features.
Method signatures and docstrings:
- def __init__(sel... | 531f646dcb493dce2575af3b9d77403ebc1f4a35 | <|skeleton|>
class EEGReader:
"""This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features."""
def __init__(self, input_type, file_path=None):
"""Arguments: input_type: 'f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EEGReader:
"""This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features."""
def __init__(self, input_type, file_path=None):
"""Arguments: input_type: 'file' indicate... | the_stack_v2_python_sparse | MindLink-Eumpy/real_time_detection/GUI/MLE_tool/EEGReader.py | wozu-dichter/MindLink-Explorer | train | 0 |
b48d59d7b7a056a8b4205d195d05553063970467 | [
"global maxArea\nmaxArea = 0\n\ndef dp(height):\n global maxArea\n if len(height) < 2:\n return maxArea\n if height[0] > height[-1]:\n area = (len(height) - 1) * height[-1]\n maxArea = max(maxArea, area)\n height.pop(-1)\n else:\n area = (len(height) - 1) * height[0]\n... | <|body_start_0|>
global maxArea
maxArea = 0
def dp(height):
global maxArea
if len(height) < 2:
return maxArea
if height[0] > height[-1]:
area = (len(height) - 1) * height[-1]
maxArea = max(maxArea, area)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
global maxArea
maxArea = 0
d... | stack_v2_sparse_classes_36k_train_032410 | 901 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea",
"signature": "def maxArea(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea",
"signature": "def maxArea(self, height)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height): :type height: List[int] :rtype: int
- def maxArea(self, height): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height): :type height: List[int] :rtype: int
- def maxArea(self, height): :type height: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxArea(sel... | 5915e039868527d624ee4f0ad431d23c6ed2d8bd | <|skeleton|>
class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
global maxArea
maxArea = 0
def dp(height):
global maxArea
if len(height) < 2:
return maxArea
if height[0] > height[-1]:
area = (le... | the_stack_v2_python_sparse | leetcode/maxArea.py | xy2333/Leetcode | train | 1 | |
6a97a5052d78fbfc93b3b862ecde736778d3a3ab | [
"self.name = name\nself.cover_page_setting = cover_page_setting\nself.add_list_of_signatures_on_last_page_of_existing_pdf = add_list_of_signatures_on_last_page_of_existing_pdf\nself.cover_page_html = cover_page_html\nself.details_page_html = details_page_html\nself.verified_template = verified_template\nself.labels... | <|body_start_0|>
self.name = name
self.cover_page_setting = cover_page_setting
self.add_list_of_signatures_on_last_page_of_existing_pdf = add_list_of_signatures_on_last_page_of_existing_pdf
self.cover_page_html = cover_page_html
self.details_page_html = details_page_html
... | Implementation of the 'CreatePdfTemplate' model. Create a new Pdf template Attributes: name (string): The name of the Pdf template cover_page_setting (CoverPageSetting): Coverpage is the page added to the document at the beginning or end that show a list of the signers. This settings hides that page or put it first or ... | CreatePdfTemplate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreatePdfTemplate:
"""Implementation of the 'CreatePdfTemplate' model. Create a new Pdf template Attributes: name (string): The name of the Pdf template cover_page_setting (CoverPageSetting): Coverpage is the page added to the document at the beginning or end that show a list of the signers. This... | stack_v2_sparse_classes_36k_train_032411 | 5,723 | permissive | [
{
"docstring": "Constructor for the CreatePdfTemplate class",
"name": "__init__",
"signature": "def __init__(self, name=None, cover_page_setting=None, add_list_of_signatures_on_last_page_of_existing_pdf=None, cover_page_html=None, details_page_html=None, verified_template=None, labels=None, include_logo... | 2 | stack_v2_sparse_classes_30k_train_006079 | Implement the Python class `CreatePdfTemplate` described below.
Class description:
Implementation of the 'CreatePdfTemplate' model. Create a new Pdf template Attributes: name (string): The name of the Pdf template cover_page_setting (CoverPageSetting): Coverpage is the page added to the document at the beginning or en... | Implement the Python class `CreatePdfTemplate` described below.
Class description:
Implementation of the 'CreatePdfTemplate' model. Create a new Pdf template Attributes: name (string): The name of the Pdf template cover_page_setting (CoverPageSetting): Coverpage is the page added to the document at the beginning or en... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class CreatePdfTemplate:
"""Implementation of the 'CreatePdfTemplate' model. Create a new Pdf template Attributes: name (string): The name of the Pdf template cover_page_setting (CoverPageSetting): Coverpage is the page added to the document at the beginning or end that show a list of the signers. This... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreatePdfTemplate:
"""Implementation of the 'CreatePdfTemplate' model. Create a new Pdf template Attributes: name (string): The name of the Pdf template cover_page_setting (CoverPageSetting): Coverpage is the page added to the document at the beginning or end that show a list of the signers. This settings hid... | the_stack_v2_python_sparse | idfy_rest_client/models/create_pdf_template.py | dealflowteam/Idfy | train | 0 |
6c6194253acf95e9710beacd24f5cd93b5814b53 | [
"import htcondor as HTC\nself._collector = HTC.Collector()\nself._schedd = HTC.Schedd()\nself._security = HTC.SecMan()",
"status_counts = {'job_total': 0}\nfor job_status in Job_status:\n status_counts[job_status.name] = 0\nfor job in self._schedd.xquery(projection=['ClusterId', 'ProcId', 'JobStatus']):\n s... | <|body_start_0|>
import htcondor as HTC
self._collector = HTC.Collector()
self._schedd = HTC.Schedd()
self._security = HTC.SecMan()
<|end_body_0|>
<|body_start_1|>
status_counts = {'job_total': 0}
for job_status in Job_status:
status_counts[job_status.name] =... | Condor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Condor:
def __init__(self):
"""Init the htcondor connections on this node Args: None Returns: None Raises: None"""
<|body_0|>
def job_counts(self):
"""get the number of active jobs in the queue and group them by status The following are the states a job can be in: id... | stack_v2_sparse_classes_36k_train_032412 | 7,261 | permissive | [
{
"docstring": "Init the htcondor connections on this node Args: None Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "get the number of active jobs in the queue and group them by status The following are the states a job can be in: idle, runn... | 4 | stack_v2_sparse_classes_30k_test_001146 | Implement the Python class `Condor` described below.
Class description:
Implement the Condor class.
Method signatures and docstrings:
- def __init__(self): Init the htcondor connections on this node Args: None Returns: None Raises: None
- def job_counts(self): get the number of active jobs in the queue and group them... | Implement the Python class `Condor` described below.
Class description:
Implement the Condor class.
Method signatures and docstrings:
- def __init__(self): Init the htcondor connections on this node Args: None Returns: None Raises: None
- def job_counts(self): get the number of active jobs in the queue and group them... | bb0f7a539b0962afdcb237fb79d2f046542d8988 | <|skeleton|>
class Condor:
def __init__(self):
"""Init the htcondor connections on this node Args: None Returns: None Raises: None"""
<|body_0|>
def job_counts(self):
"""get the number of active jobs in the queue and group them by status The following are the states a job can be in: id... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Condor:
def __init__(self):
"""Init the htcondor connections on this node Args: None Returns: None Raises: None"""
import htcondor as HTC
self._collector = HTC.Collector()
self._schedd = HTC.Schedd()
self._security = HTC.SecMan()
def job_counts(self):
"""ge... | the_stack_v2_python_sparse | ehos/htcondor.py | elixir-no-nels/ehos-python | train | 2 | |
95403b243f6285e44a78120a04ea480953f67d5d | [
"sum_1 = 0\nl = len(nums)\nnums = sorted(nums)\nfor i in range(l - 2):\n for j in range(i + 1, l - 1):\n k = nums[i] + nums[j]\n a = bisect.bisect_left(nums[j + 1:], k)\n sum_1 += a\n print(a, nums[i], nums[j], nums[j + 1:])\nreturn sum_1",
"sum_1 = 0\nl = len(nums)\nnums = sorted(n... | <|body_start_0|>
sum_1 = 0
l = len(nums)
nums = sorted(nums)
for i in range(l - 2):
for j in range(i + 1, l - 1):
k = nums[i] + nums[j]
a = bisect.bisect_left(nums[j + 1:], k)
sum_1 += a
print(a, nums[i], nums[j]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def triangleNumber(self, nums):
""":type nums: List[int] :rtype: int 2078ms"""
<|body_0|>
def triangleNumber_1(self, nums):
""":type nums: List[int] :rtype: int 315ms"""
<|body_1|>
def triangleNumber_2(self, nums):
""":type nums: List[i... | stack_v2_sparse_classes_36k_train_032413 | 2,014 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int 2078ms",
"name": "triangleNumber",
"signature": "def triangleNumber(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int 315ms",
"name": "triangleNumber_1",
"signature": "def triangleNumber_1(self, nums)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_012420 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def triangleNumber(self, nums): :type nums: List[int] :rtype: int 2078ms
- def triangleNumber_1(self, nums): :type nums: List[int] :rtype: int 315ms
- def triangleNumber_2(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def triangleNumber(self, nums): :type nums: List[int] :rtype: int 2078ms
- def triangleNumber_1(self, nums): :type nums: List[int] :rtype: int 315ms
- def triangleNumber_2(self, ... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def triangleNumber(self, nums):
""":type nums: List[int] :rtype: int 2078ms"""
<|body_0|>
def triangleNumber_1(self, nums):
""":type nums: List[int] :rtype: int 315ms"""
<|body_1|>
def triangleNumber_2(self, nums):
""":type nums: List[i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def triangleNumber(self, nums):
""":type nums: List[int] :rtype: int 2078ms"""
sum_1 = 0
l = len(nums)
nums = sorted(nums)
for i in range(l - 2):
for j in range(i + 1, l - 1):
k = nums[i] + nums[j]
a = bisect.bisect_... | the_stack_v2_python_sparse | ValidTriangleNumber_MID_611.py | 953250587/leetcode-python | train | 2 | |
915c73b34b15957da4d5299da9e07be1830d48c8 | [
"if digestAlgorithm != DigestAlgorithm.SHA256:\n raise SecurityException('FilePrivateKeyStorage.sign: Unsupported digest algorithm')\nder = self.getPrivateKey(keyName)\nprivateKey = RSA.importKey(der.toRawStr())\nif sys.version_info[0] == 2:\n data = Blob(data, False).toRawStr()\nsignature = PKCS1_v1_5.new(pr... | <|body_start_0|>
if digestAlgorithm != DigestAlgorithm.SHA256:
raise SecurityException('FilePrivateKeyStorage.sign: Unsupported digest algorithm')
der = self.getPrivateKey(keyName)
privateKey = RSA.importKey(der.toRawStr())
if sys.version_info[0] == 2:
data = Blob... | IotPrivateKeyStorage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IotPrivateKeyStorage:
def sign(self, data, keyName, digestAlgorithm=DigestAlgorithm.SHA256):
"""Fetch the private key for keyName and sign the data, returning a signature Blob. :param data: Pointer the input byte buffer to sign. :type data: An array type with int elements :param Name key... | stack_v2_sparse_classes_36k_train_032414 | 5,142 | no_license | [
{
"docstring": "Fetch the private key for keyName and sign the data, returning a signature Blob. :param data: Pointer the input byte buffer to sign. :type data: An array type with int elements :param Name keyName: The name of the signing key. :param digestAlgorithm: (optional) the digest algorithm. If omitted, ... | 4 | stack_v2_sparse_classes_30k_train_016579 | Implement the Python class `IotPrivateKeyStorage` described below.
Class description:
Implement the IotPrivateKeyStorage class.
Method signatures and docstrings:
- def sign(self, data, keyName, digestAlgorithm=DigestAlgorithm.SHA256): Fetch the private key for keyName and sign the data, returning a signature Blob. :p... | Implement the Python class `IotPrivateKeyStorage` described below.
Class description:
Implement the IotPrivateKeyStorage class.
Method signatures and docstrings:
- def sign(self, data, keyName, digestAlgorithm=DigestAlgorithm.SHA256): Fetch the private key for keyName and sign the data, returning a signature Blob. :p... | 8236cecc964ebef275e260a790a0e74583940f8f | <|skeleton|>
class IotPrivateKeyStorage:
def sign(self, data, keyName, digestAlgorithm=DigestAlgorithm.SHA256):
"""Fetch the private key for keyName and sign the data, returning a signature Blob. :param data: Pointer the input byte buffer to sign. :type data: An array type with int elements :param Name key... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IotPrivateKeyStorage:
def sign(self, data, keyName, digestAlgorithm=DigestAlgorithm.SHA256):
"""Fetch the private key for keyName and sign the data, returning a signature Blob. :param data: Pointer the input byte buffer to sign. :type data: An array type with int elements :param Name keyName: The name... | the_stack_v2_python_sparse | ndn_pi/security/iot_private_key_storage.py | remap/ndn-pi | train | 15 | |
e67798b7784da6f8b6081634c35519704c46a618 | [
"self.name = name\nnet = nef.Network(self, seed=HRLutils.SEED, quick=False)\nself.N = N\nself.learningrate = learningrate\nself.supervision = 1.0\nself.tauPSC = 0.007\nmodterms = []\nlearnterms = []\noutput = net.make('output', 1, len(actions), mode='direct')\noutput.fixMode()\nfor i, action in enumerate(actions):\... | <|body_start_0|>
self.name = name
net = nef.Network(self, seed=HRLutils.SEED, quick=False)
self.N = N
self.learningrate = learningrate
self.supervision = 1.0
self.tauPSC = 0.007
modterms = []
learnterms = []
output = net.make('output', 1, len(actio... | A network that learns/outputs the Q values for a fixed set of actions, given some state input. Note: this has been replaced in practice by the decoder learning mechanism, but keeping this here in case we ever want to return to synaptic weight learning. :input state: the output of the state population (neural activities... | ActionValues | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionValues:
"""A network that learns/outputs the Q values for a fixed set of actions, given some state input. Note: this has been replaced in practice by the decoder learning mechanism, but keeping this here in case we ever want to return to synaptic weight learning. :input state: the output of... | stack_v2_sparse_classes_36k_train_032415 | 5,706 | no_license | [
{
"docstring": "Build ActionValues network. :param name: name of Network :param N: base number of neurons :param stateN: number of neurons in state population :param actions: actions available to the system :type actions: list of tuples (action_name,action_vector) :param learningrate: learning rate for PES rule... | 3 | stack_v2_sparse_classes_30k_train_020906 | Implement the Python class `ActionValues` described below.
Class description:
A network that learns/outputs the Q values for a fixed set of actions, given some state input. Note: this has been replaced in practice by the decoder learning mechanism, but keeping this here in case we ever want to return to synaptic weigh... | Implement the Python class `ActionValues` described below.
Class description:
A network that learns/outputs the Q values for a fixed set of actions, given some state input. Note: this has been replaced in practice by the decoder learning mechanism, but keeping this here in case we ever want to return to synaptic weigh... | 09668925404454997bac63cf56c176cde381f614 | <|skeleton|>
class ActionValues:
"""A network that learns/outputs the Q values for a fixed set of actions, given some state input. Note: this has been replaced in practice by the decoder learning mechanism, but keeping this here in case we ever want to return to synaptic weight learning. :input state: the output of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActionValues:
"""A network that learns/outputs the Q values for a fixed set of actions, given some state input. Note: this has been replaced in practice by the decoder learning mechanism, but keeping this here in case we ever want to return to synaptic weight learning. :input state: the output of the state po... | the_stack_v2_python_sparse | hrlproject/agent/actionvalues.py | amoliu/nhrlmodel | train | 0 |
06266b27143312b718530dcc5db646bd59a37831 | [
"self.env_step_time = 0.0\nself.inference_time = 0.0\nself.iters = 0.0",
"ret = {'mean_env_step_time_ms': self.env_step_time * 1000 / self.iters, 'mean_inference_time_ms': self.inference_time * 1000 / self.iters, 'iters': self.iters}\nself.reset()\nreturn ret",
"self.env_step_time = 0.0\nself.inference_time = 0... | <|body_start_0|>
self.env_step_time = 0.0
self.inference_time = 0.0
self.iters = 0.0
<|end_body_0|>
<|body_start_1|>
ret = {'mean_env_step_time_ms': self.env_step_time * 1000 / self.iters, 'mean_inference_time_ms': self.inference_time * 1000 / self.iters, 'iters': self.iters}
se... | Agent status records handle the env.step and inference time of Agent | AgentStats | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AgentStats:
"""Agent status records handle the env.step and inference time of Agent"""
def __init__(self):
"""init with default value"""
<|body_0|>
def get(self):
"""get agent status and clear the buffer"""
<|body_1|>
def reset(self):
"""rese... | stack_v2_sparse_classes_36k_train_032416 | 5,319 | permissive | [
{
"docstring": "init with default value",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "get agent status and clear the buffer",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "reset buffer",
"name": "reset",
"signature": "def rese... | 3 | null | Implement the Python class `AgentStats` described below.
Class description:
Agent status records handle the env.step and inference time of Agent
Method signatures and docstrings:
- def __init__(self): init with default value
- def get(self): get agent status and clear the buffer
- def reset(self): reset buffer | Implement the Python class `AgentStats` described below.
Class description:
Agent status records handle the env.step and inference time of Agent
Method signatures and docstrings:
- def __init__(self): init with default value
- def get(self): get agent status and clear the buffer
- def reset(self): reset buffer
<|ske... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class AgentStats:
"""Agent status records handle the env.step and inference time of Agent"""
def __init__(self):
"""init with default value"""
<|body_0|>
def get(self):
"""get agent status and clear the buffer"""
<|body_1|>
def reset(self):
"""rese... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AgentStats:
"""Agent status records handle the env.step and inference time of Agent"""
def __init__(self):
"""init with default value"""
self.env_step_time = 0.0
self.inference_time = 0.0
self.iters = 0.0
def get(self):
"""get agent status and clear the buffer... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/reinforcement-learning/ModelZoo_QMIX_TensorFlow/xt/util/profile_stats.py | Huawei-Ascend/modelzoo | train | 1 |
45d14b01a6b7ff28047d0a2e5816c7d42e9d67a2 | [
"if not id_tar:\n raise ValueError('Invalid ID')\nresponse, _ = self._api.post(path='{}/accept'.format(id_tar))\nreturn self.model_class.deserialize(response)",
"if not id_tar:\n raise ValueError('Invalid ID')\nresponse, _ = self._api.post(path='{}/ignore'.format(id_tar), json={'reason': reason})\nreturn se... | <|body_start_0|>
if not id_tar:
raise ValueError('Invalid ID')
response, _ = self._api.post(path='{}/accept'.format(id_tar))
return self.model_class.deserialize(response)
<|end_body_0|>
<|body_start_1|>
if not id_tar:
raise ValueError('Invalid ID')
respon... | Tier Account Request Resource. | TierAccountRequestResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TierAccountRequestResource:
"""Tier Account Request Resource."""
def accept(self, id_tar):
"""Accept a Tier Configuration Request. :param str id_tar: Primary key of the tier configuration request to accept. :return: Tier Account Request object."""
<|body_0|>
def ignore(s... | stack_v2_sparse_classes_36k_train_032417 | 1,523 | permissive | [
{
"docstring": "Accept a Tier Configuration Request. :param str id_tar: Primary key of the tier configuration request to accept. :return: Tier Account Request object.",
"name": "accept",
"signature": "def accept(self, id_tar)"
},
{
"docstring": "Ignore a Tier Configuration Request :param str id_... | 2 | stack_v2_sparse_classes_30k_train_000023 | Implement the Python class `TierAccountRequestResource` described below.
Class description:
Tier Account Request Resource.
Method signatures and docstrings:
- def accept(self, id_tar): Accept a Tier Configuration Request. :param str id_tar: Primary key of the tier configuration request to accept. :return: Tier Accoun... | Implement the Python class `TierAccountRequestResource` described below.
Class description:
Tier Account Request Resource.
Method signatures and docstrings:
- def accept(self, id_tar): Accept a Tier Configuration Request. :param str id_tar: Primary key of the tier configuration request to accept. :return: Tier Accoun... | 656d653e4065637e2cc5768d7d554de17d0120eb | <|skeleton|>
class TierAccountRequestResource:
"""Tier Account Request Resource."""
def accept(self, id_tar):
"""Accept a Tier Configuration Request. :param str id_tar: Primary key of the tier configuration request to accept. :return: Tier Account Request object."""
<|body_0|>
def ignore(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TierAccountRequestResource:
"""Tier Account Request Resource."""
def accept(self, id_tar):
"""Accept a Tier Configuration Request. :param str id_tar: Primary key of the tier configuration request to accept. :return: Tier Account Request object."""
if not id_tar:
raise ValueErr... | the_stack_v2_python_sparse | connect/resources/tier_account.py | cloudblue/connect-python-sdk | train | 13 |
a0b2db2c0c5c063fca43e25a63136511efdfab2b | [
"data = request.get_json()\nsale_attendant = get_jwt_identity()['email']\nname = InputValidator.valid_string(data['name'].strip())\nquantity_to_sell = InputValidator.valid_number(data['quantity'])\npayload = ['name', 'quantity']\nfor item in data.keys():\n if item not in payload:\n return ({'message': f'T... | <|body_start_0|>
data = request.get_json()
sale_attendant = get_jwt_identity()['email']
name = InputValidator.valid_string(data['name'].strip())
quantity_to_sell = InputValidator.valid_number(data['quantity'])
payload = ['name', 'quantity']
for item in data.keys():
... | SalesRecordEnpoint | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SalesRecordEnpoint:
def post(self):
"""Post a sale_record"""
<|body_0|>
def get(self, sale_id):
"""Retrieve a single sales"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = request.get_json()
sale_attendant = get_jwt_identity()['email']... | stack_v2_sparse_classes_36k_train_032418 | 3,516 | no_license | [
{
"docstring": "Post a sale_record",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Retrieve a single sales",
"name": "get",
"signature": "def get(self, sale_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014879 | Implement the Python class `SalesRecordEnpoint` described below.
Class description:
Implement the SalesRecordEnpoint class.
Method signatures and docstrings:
- def post(self): Post a sale_record
- def get(self, sale_id): Retrieve a single sales | Implement the Python class `SalesRecordEnpoint` described below.
Class description:
Implement the SalesRecordEnpoint class.
Method signatures and docstrings:
- def post(self): Post a sale_record
- def get(self, sale_id): Retrieve a single sales
<|skeleton|>
class SalesRecordEnpoint:
def post(self):
"""P... | d29dfcb5851e107921d6b1d06bb6ece761e7f2b9 | <|skeleton|>
class SalesRecordEnpoint:
def post(self):
"""Post a sale_record"""
<|body_0|>
def get(self, sale_id):
"""Retrieve a single sales"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SalesRecordEnpoint:
def post(self):
"""Post a sale_record"""
data = request.get_json()
sale_attendant = get_jwt_identity()['email']
name = InputValidator.valid_string(data['name'].strip())
quantity_to_sell = InputValidator.valid_number(data['quantity'])
payload ... | the_stack_v2_python_sparse | app/resources/sales_endpoints.py | JoshuaKodhe/Store-Manager-Api-V2 | train | 1 | |
d56a6c9ecb270ba3e02b9334a357fe6a1c389831 | [
"if isinstance(value, libpydescriptors.Distribution):\n return value\nif value is None or len(value) == 0:\n return None\nelse:\n temp = libpydescriptors.Distribution()\n temp.serialized_data = value.__str__()\n return temp",
"if isinstance(value, libpydescriptors.Distribution):\n return value.s... | <|body_start_0|>
if isinstance(value, libpydescriptors.Distribution):
return value
if value is None or len(value) == 0:
return None
else:
temp = libpydescriptors.Distribution()
temp.serialized_data = value.__str__()
return temp
<|end_bo... | Custom field to store a ShapeDistribution object. | DistributionField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DistributionField:
"""Custom field to store a ShapeDistribution object."""
def to_python(self, value):
"""Recreate python object from db."""
<|body_0|>
def get_prep_value(self, value):
"""Serialize python object to be stored in db."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_032419 | 1,587 | no_license | [
{
"docstring": "Recreate python object from db.",
"name": "to_python",
"signature": "def to_python(self, value)"
},
{
"docstring": "Serialize python object to be stored in db.",
"name": "get_prep_value",
"signature": "def get_prep_value(self, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012029 | Implement the Python class `DistributionField` described below.
Class description:
Custom field to store a ShapeDistribution object.
Method signatures and docstrings:
- def to_python(self, value): Recreate python object from db.
- def get_prep_value(self, value): Serialize python object to be stored in db. | Implement the Python class `DistributionField` described below.
Class description:
Custom field to store a ShapeDistribution object.
Method signatures and docstrings:
- def to_python(self, value): Recreate python object from db.
- def get_prep_value(self, value): Serialize python object to be stored in db.
<|skeleto... | 13d58da77ceef6282948e56e83ff7f5fbe22d57f | <|skeleton|>
class DistributionField:
"""Custom field to store a ShapeDistribution object."""
def to_python(self, value):
"""Recreate python object from db."""
<|body_0|>
def get_prep_value(self, value):
"""Serialize python object to be stored in db."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DistributionField:
"""Custom field to store a ShapeDistribution object."""
def to_python(self, value):
"""Recreate python object from db."""
if isinstance(value, libpydescriptors.Distribution):
return value
if value is None or len(value) == 0:
return None
... | the_stack_v2_python_sparse | django_server/shape_distribution/models.py | julfla/master_project | train | 0 |
ef6b73ad4022308c6072298ae6577084698cba77 | [
"Component.__init__(self, bot)\nself.bot = bot\nself.logger = logging.getLogger('components.topic')\nself.persistence = self.bot.get_subsystem('local-persistence')",
"added_at = date.today()\naddition = TopicAddition(date=added_at, text=text, user=user)\nsession = self.persistence.get_session()\nsession.add(addit... | <|body_start_0|>
Component.__init__(self, bot)
self.bot = bot
self.logger = logging.getLogger('components.topic')
self.persistence = self.bot.get_subsystem('local-persistence')
<|end_body_0|>
<|body_start_1|>
added_at = date.today()
addition = TopicAddition(date=added_at... | TopicComponent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TopicComponent:
def __init__(self, bot):
"""Initialize all required variables."""
<|body_0|>
def insert_addition(self, text, user):
"""Insert a new addition to database. @param text: the real addition text @param user: the person who likes to add the addition @return... | stack_v2_sparse_classes_36k_train_032420 | 4,482 | permissive | [
{
"docstring": "Initialize all required variables.",
"name": "__init__",
"signature": "def __init__(self, bot)"
},
{
"docstring": "Insert a new addition to database. @param text: the real addition text @param user: the person who likes to add the addition @return: None",
"name": "insert_addi... | 6 | stack_v2_sparse_classes_30k_train_017747 | Implement the Python class `TopicComponent` described below.
Class description:
Implement the TopicComponent class.
Method signatures and docstrings:
- def __init__(self, bot): Initialize all required variables.
- def insert_addition(self, text, user): Insert a new addition to database. @param text: the real addition... | Implement the Python class `TopicComponent` described below.
Class description:
Implement the TopicComponent class.
Method signatures and docstrings:
- def __init__(self, bot): Initialize all required variables.
- def insert_addition(self, text, user): Insert a new addition to database. @param text: the real addition... | 064164dcd3baa867f276a5791eaf8050d568fc3f | <|skeleton|>
class TopicComponent:
def __init__(self, bot):
"""Initialize all required variables."""
<|body_0|>
def insert_addition(self, text, user):
"""Insert a new addition to database. @param text: the real addition text @param user: the person who likes to add the addition @return... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TopicComponent:
def __init__(self, bot):
"""Initialize all required variables."""
Component.__init__(self, bot)
self.bot = bot
self.logger = logging.getLogger('components.topic')
self.persistence = self.bot.get_subsystem('local-persistence')
def insert_addition(sel... | the_stack_v2_python_sparse | src/python/components/topic.py | msteinhoff/foption-bot | train | 0 | |
850f6b637d7e61d3ff78db91a8d5399b0597c28b | [
"self.arest = arest\nself._attr_name = f'{location.title()} {name.title()}'\nself._variable = variable\nself._attr_native_unit_of_measurement = unit_of_measurement\nself._renderer = renderer\nif pin is not None:\n request = requests.get(f'{resource}/mode/{pin}/i', timeout=10)\n if request.status_code != HTTPS... | <|body_start_0|>
self.arest = arest
self._attr_name = f'{location.title()} {name.title()}'
self._variable = variable
self._attr_native_unit_of_measurement = unit_of_measurement
self._renderer = renderer
if pin is not None:
request = requests.get(f'{resource}/m... | Implementation of an aREST sensor for exposed variables. | ArestSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArestSensor:
"""Implementation of an aREST sensor for exposed variables."""
def __init__(self, arest, resource, location, name, variable=None, pin=None, unit_of_measurement=None, renderer=None):
"""Initialize the sensor."""
<|body_0|>
def update(self) -> None:
""... | stack_v2_sparse_classes_36k_train_032421 | 6,651 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, arest, resource, location, name, variable=None, pin=None, unit_of_measurement=None, renderer=None)"
},
{
"docstring": "Get the latest data from aREST API.",
"name": "update",
"signature": "def u... | 2 | stack_v2_sparse_classes_30k_train_008629 | Implement the Python class `ArestSensor` described below.
Class description:
Implementation of an aREST sensor for exposed variables.
Method signatures and docstrings:
- def __init__(self, arest, resource, location, name, variable=None, pin=None, unit_of_measurement=None, renderer=None): Initialize the sensor.
- def ... | Implement the Python class `ArestSensor` described below.
Class description:
Implementation of an aREST sensor for exposed variables.
Method signatures and docstrings:
- def __init__(self, arest, resource, location, name, variable=None, pin=None, unit_of_measurement=None, renderer=None): Initialize the sensor.
- def ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ArestSensor:
"""Implementation of an aREST sensor for exposed variables."""
def __init__(self, arest, resource, location, name, variable=None, pin=None, unit_of_measurement=None, renderer=None):
"""Initialize the sensor."""
<|body_0|>
def update(self) -> None:
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArestSensor:
"""Implementation of an aREST sensor for exposed variables."""
def __init__(self, arest, resource, location, name, variable=None, pin=None, unit_of_measurement=None, renderer=None):
"""Initialize the sensor."""
self.arest = arest
self._attr_name = f'{location.title()}... | the_stack_v2_python_sparse | homeassistant/components/arest/sensor.py | home-assistant/core | train | 35,501 |
6d071a9a871921152465d1ee0ed046db1f9eb592 | [
"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... | Missing associated documentation comment in .proto file. | PermissionAppServiceServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PermissionAppServiceServicer:
"""Missing associated documentation comment in .proto file."""
def permission_by_name(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def permission_by_id(self, request, context):
""... | stack_v2_sparse_classes_36k_train_032422 | 10,560 | no_license | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "permission_by_name",
"signature": "def permission_by_name(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "permission_by_id",
"signature": "d... | 5 | null | Implement the Python class `PermissionAppServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def permission_by_name(self, request, context): Missing associated documentation comment in .proto file.
- def permission_by_id(sel... | Implement the Python class `PermissionAppServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def permission_by_name(self, request, context): Missing associated documentation comment in .proto file.
- def permission_by_id(sel... | 55d36c068e26e13ee5bae5c033e2e17784c63feb | <|skeleton|>
class PermissionAppServiceServicer:
"""Missing associated documentation comment in .proto file."""
def permission_by_name(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def permission_by_id(self, request, context):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PermissionAppServiceServicer:
"""Missing associated documentation comment in .proto file."""
def permission_by_name(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method n... | the_stack_v2_python_sparse | src/resource/proto/_generated/identity/permission_app_service_pb2_grpc.py | arkanmgerges/cafm.identity | train | 0 |
8c59089a4194e700ad0b78eb4f9150753f24d4e4 | [
"if type(rho) is type(1):\n self.order = rho\n self.rho = np.zeros(self.order, np.float64)\nelse:\n self.rho = np.squeeze(np.asarray(rho))\n if len(self.rho.shape) not in [0, 1]:\n raise ValueError('AR parameters must be a scalar or a vector')\n if self.rho.shape == ():\n self.rho.shape... | <|body_start_0|>
if type(rho) is type(1):
self.order = rho
self.rho = np.zeros(self.order, np.float64)
else:
self.rho = np.squeeze(np.asarray(rho))
if len(self.rho.shape) not in [0, 1]:
raise ValueError('AR parameters must be a scalar or a ... | A regression model with an AR(p) covariance structure. In terms of a LikelihoodModel, the parameters are beta, the usual regression parameters, and sigma, a scalar nuisance parameter that shows up as multiplier in front of the AR(p) covariance. The linear autoregressive process of order p--AR(p)--is defined as: TODO Ex... | ARModel | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ARModel:
"""A regression model with an AR(p) covariance structure. In terms of a LikelihoodModel, the parameters are beta, the usual regression parameters, and sigma, a scalar nuisance parameter that shows up as multiplier in front of the AR(p) covariance. The linear autoregressive process of ord... | stack_v2_sparse_classes_36k_train_032423 | 29,072 | permissive | [
{
"docstring": "Initialize AR model instance Parameters ---------- design : ndarray 2D array with design matrix rho : int or array-like If int, gives order of model, and initializes rho to zeros. If ndarray, gives initial estimate of rho. Be careful as ``ARModel(X, 1) != ARModel(X, 1.0)``.",
"name": "__init... | 3 | stack_v2_sparse_classes_30k_train_009688 | Implement the Python class `ARModel` described below.
Class description:
A regression model with an AR(p) covariance structure. In terms of a LikelihoodModel, the parameters are beta, the usual regression parameters, and sigma, a scalar nuisance parameter that shows up as multiplier in front of the AR(p) covariance. T... | Implement the Python class `ARModel` described below.
Class description:
A regression model with an AR(p) covariance structure. In terms of a LikelihoodModel, the parameters are beta, the usual regression parameters, and sigma, a scalar nuisance parameter that shows up as multiplier in front of the AR(p) covariance. T... | 7eede02471567487e454016c1e7cf637d3afac9e | <|skeleton|>
class ARModel:
"""A regression model with an AR(p) covariance structure. In terms of a LikelihoodModel, the parameters are beta, the usual regression parameters, and sigma, a scalar nuisance parameter that shows up as multiplier in front of the AR(p) covariance. The linear autoregressive process of ord... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ARModel:
"""A regression model with an AR(p) covariance structure. In terms of a LikelihoodModel, the parameters are beta, the usual regression parameters, and sigma, a scalar nuisance parameter that shows up as multiplier in front of the AR(p) covariance. The linear autoregressive process of order p--AR(p)--... | the_stack_v2_python_sparse | nipy/algorithms/statistics/models/regression.py | nipy/nipy | train | 275 |
7eacd849af4280a35015325c03f80a54340f8374 | [
"cu = Change_Param(username, password, prod)\ngu = cu.get_params()\nself.suffix = self.c.get_value('Member', 'members_collection_goods')\nself.url = self.url_joint(prod) + gu[1]\nlogs.info('test url:%s' % self.url)\nreturn self.get_requests(self.url, gu[0], data)",
"cu = Change_Param(username, password, prod)\ngu... | <|body_start_0|>
cu = Change_Param(username, password, prod)
gu = cu.get_params()
self.suffix = self.c.get_value('Member', 'members_collection_goods')
self.url = self.url_joint(prod) + gu[1]
logs.info('test url:%s' % self.url)
return self.get_requests(self.url, gu[0], dat... | Member_Collection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Member_Collection:
def get_member_collection_goods(self, username=None, password=None, data=None, prod=None):
"""相关参数有: page_no 页码 page_size 每页显示数量"""
<|body_0|>
def post_member_collection_goods(self, username=None, password=None, data=None, prod=None):
"""相关参数有: goo... | stack_v2_sparse_classes_36k_train_032424 | 3,368 | no_license | [
{
"docstring": "相关参数有: page_no 页码 page_size 每页显示数量",
"name": "get_member_collection_goods",
"signature": "def get_member_collection_goods(self, username=None, password=None, data=None, prod=None)"
},
{
"docstring": "相关参数有: goods_id 商品id",
"name": "post_member_collection_goods",
"signatur... | 4 | null | Implement the Python class `Member_Collection` described below.
Class description:
Implement the Member_Collection class.
Method signatures and docstrings:
- def get_member_collection_goods(self, username=None, password=None, data=None, prod=None): 相关参数有: page_no 页码 page_size 每页显示数量
- def post_member_collection_goods... | Implement the Python class `Member_Collection` described below.
Class description:
Implement the Member_Collection class.
Method signatures and docstrings:
- def get_member_collection_goods(self, username=None, password=None, data=None, prod=None): 相关参数有: page_no 页码 page_size 每页显示数量
- def post_member_collection_goods... | 235200a67c1fb125f75f9771808f6655a7b14202 | <|skeleton|>
class Member_Collection:
def get_member_collection_goods(self, username=None, password=None, data=None, prod=None):
"""相关参数有: page_no 页码 page_size 每页显示数量"""
<|body_0|>
def post_member_collection_goods(self, username=None, password=None, data=None, prod=None):
"""相关参数有: goo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Member_Collection:
def get_member_collection_goods(self, username=None, password=None, data=None, prod=None):
"""相关参数有: page_no 页码 page_size 每页显示数量"""
cu = Change_Param(username, password, prod)
gu = cu.get_params()
self.suffix = self.c.get_value('Member', 'members_collection_g... | the_stack_v2_python_sparse | business/member/member_collection.py | vothin/requsets_test | train | 0 | |
038049f3079be001499757f663419da2dfd6faeb | [
"def postorder(node):\n return postorder(node.left) + postorder(node.right) + [node.val] if node else []\nserialize_data = ' '.join(map(str, postorder(root)))\nreturn serialize_data",
"def helper(lower=float('-inf'), upper=float('inf')):\n if not data or data[-1] < lower or data[-1] > upper:\n return... | <|body_start_0|>
def postorder(node):
return postorder(node.left) + postorder(node.right) + [node.val] if node else []
serialize_data = ' '.join(map(str, postorder(root)))
return serialize_data
<|end_body_0|>
<|body_start_1|>
def helper(lower=float('-inf'), upper=float('inf'... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_032425 | 1,609 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_005079 | 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:... | f93380721b8383817fe2b0d728deca1321c9ef45 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def postorder(node):
return postorder(node.left) + postorder(node.right) + [node.val] if node else []
serialize_data = ' '.join(map(str, postorder(root)))
ret... | the_stack_v2_python_sparse | explore/2020/october/Serialize_and_Deserialize_BST.py | lixiang2017/leetcode | train | 5 | |
3b08750108e602ee1a2738e031c57d1854f32304 | [
"import collections\ndicts = collections.defaultdict(set)\nfor allow in allowed:\n dicts[allow[0:2]].add(allow[-1])\n\ndef dfs(s, c):\n if len(s) == 1 and s + c in dicts:\n return True\n for i in dicts[s[-1] + c]:\n for j in dicts[s]:\n dicts[s + c].add(j + i)\n for i in dicts[s... | <|body_start_0|>
import collections
dicts = collections.defaultdict(set)
for allow in allowed:
dicts[allow[0:2]].add(allow[-1])
def dfs(s, c):
if len(s) == 1 and s + c in dicts:
return True
for i in dicts[s[-1] + c]:
fo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
<|body_0|>
def pyramidTransition_1(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool 85ms worry ans"""
<|bod... | stack_v2_sparse_classes_36k_train_032426 | 4,317 | no_license | [
{
"docstring": ":type bottom: str :type allowed: List[str] :rtype: bool",
"name": "pyramidTransition",
"signature": "def pyramidTransition(self, bottom, allowed)"
},
{
"docstring": ":type bottom: str :type allowed: List[str] :rtype: bool 85ms worry ans",
"name": "pyramidTransition_1",
"s... | 2 | stack_v2_sparse_classes_30k_train_017404 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pyramidTransition(self, bottom, allowed): :type bottom: str :type allowed: List[str] :rtype: bool
- def pyramidTransition_1(self, bottom, allowed): :type bottom: str :type al... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pyramidTransition(self, bottom, allowed): :type bottom: str :type allowed: List[str] :rtype: bool
- def pyramidTransition_1(self, bottom, allowed): :type bottom: str :type al... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
<|body_0|>
def pyramidTransition_1(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool 85ms worry ans"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
import collections
dicts = collections.defaultdict(set)
for allow in allowed:
dicts[allow[0:2]].add(allow[-1])
def dfs(s, c):
i... | the_stack_v2_python_sparse | PyramidTransitionMatrix_MID_757.py | 953250587/leetcode-python | train | 2 | |
c35f6c3aedd55265c652655f14298b9df65a1a4d | [
"if not root:\n return []\nret = []\nq = [root]\nwhile q:\n tmp = q.pop(0)\n if tmp:\n ret.append(tmp.val)\n q.append(tmp.left)\n q.append(tmp.right)\n else:\n ret.append(None)\nwhile ret[-1] == None:\n ret.pop()\nreturn ret",
"if not data:\n return None\nroot = data.... | <|body_start_0|>
if not root:
return []
ret = []
q = [root]
while q:
tmp = q.pop(0)
if tmp:
ret.append(tmp.val)
q.append(tmp.left)
q.append(tmp.right)
else:
ret.append(None)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_032427 | 1,530 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_002256 | 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:... | c343ad45403d5f7f947abc9a82447d593c4938bc | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return []
ret = []
q = [root]
while q:
tmp = q.pop(0)
if tmp:
ret.append(tmp.val)
... | the_stack_v2_python_sparse | 297 Serialize and Deserialize Binary Tree/untitled.py | fangpings/Leetcode | train | 0 | |
39685c1099f7c955dc954dd226f6e3ac9bded848 | [
"self.buildings = [3, 5, 4, 4, 3, 1, 3, 2]\nself.direction = 'EAST'\nself.output = [1, 3, 6, 7]\nreturn (self.buildings, self.direction, self.output)",
"buildings, direction, proper_out = self.setUp()\noutput = sunsetViews(buildings, direction)\nself.assertEqual(output, proper_out)"
] | <|body_start_0|>
self.buildings = [3, 5, 4, 4, 3, 1, 3, 2]
self.direction = 'EAST'
self.output = [1, 3, 6, 7]
return (self.buildings, self.direction, self.output)
<|end_body_0|>
<|body_start_1|>
buildings, direction, proper_out = self.setUp()
output = sunsetViews(buildin... | Class with unittests for SunsetViews.py | test_SunsetViews | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_SunsetViews:
"""Class with unittests for SunsetViews.py"""
def setUp(self):
"""SetUp array for tests."""
<|body_0|>
def test_ExpectedOutput(self):
"""Checks if returned output is as expected."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_032428 | 925 | no_license | [
{
"docstring": "SetUp array for tests.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Checks if returned output is as expected.",
"name": "test_ExpectedOutput",
"signature": "def test_ExpectedOutput(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005254 | Implement the Python class `test_SunsetViews` described below.
Class description:
Class with unittests for SunsetViews.py
Method signatures and docstrings:
- def setUp(self): SetUp array for tests.
- def test_ExpectedOutput(self): Checks if returned output is as expected. | Implement the Python class `test_SunsetViews` described below.
Class description:
Class with unittests for SunsetViews.py
Method signatures and docstrings:
- def setUp(self): SetUp array for tests.
- def test_ExpectedOutput(self): Checks if returned output is as expected.
<|skeleton|>
class test_SunsetViews:
"""... | 3aa62ad36c3b06b2a3b05f1f8e2a9e21d68b371f | <|skeleton|>
class test_SunsetViews:
"""Class with unittests for SunsetViews.py"""
def setUp(self):
"""SetUp array for tests."""
<|body_0|>
def test_ExpectedOutput(self):
"""Checks if returned output is as expected."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test_SunsetViews:
"""Class with unittests for SunsetViews.py"""
def setUp(self):
"""SetUp array for tests."""
self.buildings = [3, 5, 4, 4, 3, 1, 3, 2]
self.direction = 'EAST'
self.output = [1, 3, 6, 7]
return (self.buildings, self.direction, self.output)
def ... | the_stack_v2_python_sparse | AlgoExpert_algorithms/Medium/SunsetViews/test_SunsetViews.py | JakubKazimierski/PythonPortfolio | train | 9 |
6a4c7d9de2fb4427b9eaa4ddbe0d499158310345 | [
"self.size = 0\nself.capacity = capacity\nself.dict = {}\nself.head, self.tail = (Node(-1, -1), Node(-1, -1))\nself.head.next, self.tail.prev = (self.tail, self.head)",
"if key in self.dict:\n node = self.dict[key]\n self._remove(node)\n node.value = value\n self._insert(node)\nelse:\n if self.size... | <|body_start_0|>
self.size = 0
self.capacity = capacity
self.dict = {}
self.head, self.tail = (Node(-1, -1), Node(-1, -1))
self.head.next, self.tail.prev = (self.tail, self.head)
<|end_body_0|>
<|body_start_1|>
if key in self.dict:
node = self.dict[key]
... | . | LRUCache | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
"""."""
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_1|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_... | stack_v2_sparse_classes_36k_train_032429 | 3,156 | permissive | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :type value: int :rtype: void",
"name": "put",
"signature": "def put(self, key, value)"
},
{
"docstring": ":type key: int :rtype: int",
"nam... | 5 | stack_v2_sparse_classes_30k_train_018170 | Implement the Python class `LRUCache` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def put(self, key, value): :type key: int :type value: int :rtype: void
- def get(self, key): :type key: int :rtype: int
- def _insert(self, node): :type ... | Implement the Python class `LRUCache` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def put(self, key, value): :type key: int :type value: int :rtype: void
- def get(self, key): :type key: int :rtype: int
- def _insert(self, node): :type ... | 8f4c7657db81326f186b8fd75c1b5d26e1a654b8 | <|skeleton|>
class LRUCache:
"""."""
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_1|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
"""."""
def __init__(self, capacity):
""":type capacity: int"""
self.size = 0
self.capacity = capacity
self.dict = {}
self.head, self.tail = (Node(-1, -1), Node(-1, -1))
self.head.next, self.tail.prev = (self.tail, self.head)
def put(self, ke... | the_stack_v2_python_sparse | dynamic_programming/ds_lrc_lc146.py | han8909227/leetcode | train | 2 |
3288b8ca2a0ad50d62e7def01d025312649510d7 | [
"super().add_args(parser)\nfor param in om.computations_params[self.computation_name]:\n add_argument_kwargs = {key: param.get(key) for key in ['action', 'nargs', 'const', 'type', 'choices', 'help', 'metavar', 'dest'] if param.get(key) is not None}\n if 'help' in add_argument_kwargs:\n arg_name = f\"--... | <|body_start_0|>
super().add_args(parser)
for param in om.computations_params[self.computation_name]:
add_argument_kwargs = {key: param.get(key) for key in ['action', 'nargs', 'const', 'type', 'choices', 'help', 'metavar', 'dest'] if param.get(key) is not None}
if 'help' in add_a... | Eventually, the Parent class for all Oasis Computation Command create the command line interface from parameter define in the associated computation step | OasisComputationCommand | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OasisComputationCommand:
"""Eventually, the Parent class for all Oasis Computation Command create the command line interface from parameter define in the associated computation step"""
def add_args(self, parser):
"""Adds arguments to the argument parser. :param parser: The argument p... | stack_v2_sparse_classes_36k_train_032430 | 5,012 | permissive | [
{
"docstring": "Adds arguments to the argument parser. :param parser: The argument parser object :type parser: ArgumentParser",
"name": "add_args",
"signature": "def add_args(self, parser)"
},
{
"docstring": "Generic method that call the correct manager method from the child class computation_na... | 2 | null | Implement the Python class `OasisComputationCommand` described below.
Class description:
Eventually, the Parent class for all Oasis Computation Command create the command line interface from parameter define in the associated computation step
Method signatures and docstrings:
- def add_args(self, parser): Adds argume... | Implement the Python class `OasisComputationCommand` described below.
Class description:
Eventually, the Parent class for all Oasis Computation Command create the command line interface from parameter define in the associated computation step
Method signatures and docstrings:
- def add_args(self, parser): Adds argume... | 23e704c335629ccd010969b1090446cfa3f384d5 | <|skeleton|>
class OasisComputationCommand:
"""Eventually, the Parent class for all Oasis Computation Command create the command line interface from parameter define in the associated computation step"""
def add_args(self, parser):
"""Adds arguments to the argument parser. :param parser: The argument p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OasisComputationCommand:
"""Eventually, the Parent class for all Oasis Computation Command create the command line interface from parameter define in the associated computation step"""
def add_args(self, parser):
"""Adds arguments to the argument parser. :param parser: The argument parser object ... | the_stack_v2_python_sparse | oasislmf/cli/command.py | OasisLMF/OasisLMF | train | 122 |
abf103845299e7eb8edd6df81b7b2244f466e5d9 | [
"tf.reset_default_graph()\noptim = tf.train.GradientDescentOptimizer(0.001)\nsparse_optim = sparse_optimizers.SparseDNWOptimizer(optim, default_sparsity, mask_init_method, custom_sparsity_map=custom_sparsity_map)\ninp_values = np.arange(1, n_inp + 1)\nscale_vector_values = np.random.uniform(size=(n_out,)) - 0.5\nex... | <|body_start_0|>
tf.reset_default_graph()
optim = tf.train.GradientDescentOptimizer(0.001)
sparse_optim = sparse_optimizers.SparseDNWOptimizer(optim, default_sparsity, mask_init_method, custom_sparsity_map=custom_sparsity_map)
inp_values = np.arange(1, n_inp + 1)
scale_vector_val... | SparseDNWOptimizerTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparseDNWOptimizerTest:
def _setup_graph(self, default_sparsity, mask_init_method, custom_sparsity_map, n_inp=3, n_out=5):
"""Setups a trivial training procedure for sparse training."""
<|body_0|>
def testDNWSparsity(self, n_inp, n_out, default_sparsity):
"""Checking... | stack_v2_sparse_classes_36k_train_032431 | 25,606 | permissive | [
{
"docstring": "Setups a trivial training procedure for sparse training.",
"name": "_setup_graph",
"signature": "def _setup_graph(self, default_sparsity, mask_init_method, custom_sparsity_map, n_inp=3, n_out=5)"
},
{
"docstring": "Checking whether masked_grad is calculated after apply_gradients.... | 6 | null | Implement the Python class `SparseDNWOptimizerTest` described below.
Class description:
Implement the SparseDNWOptimizerTest class.
Method signatures and docstrings:
- def _setup_graph(self, default_sparsity, mask_init_method, custom_sparsity_map, n_inp=3, n_out=5): Setups a trivial training procedure for sparse trai... | Implement the Python class `SparseDNWOptimizerTest` described below.
Class description:
Implement the SparseDNWOptimizerTest class.
Method signatures and docstrings:
- def _setup_graph(self, default_sparsity, mask_init_method, custom_sparsity_map, n_inp=3, n_out=5): Setups a trivial training procedure for sparse trai... | d39fc7d46505cb3196cb1edeb32ed0b6dd44c0f9 | <|skeleton|>
class SparseDNWOptimizerTest:
def _setup_graph(self, default_sparsity, mask_init_method, custom_sparsity_map, n_inp=3, n_out=5):
"""Setups a trivial training procedure for sparse training."""
<|body_0|>
def testDNWSparsity(self, n_inp, n_out, default_sparsity):
"""Checking... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SparseDNWOptimizerTest:
def _setup_graph(self, default_sparsity, mask_init_method, custom_sparsity_map, n_inp=3, n_out=5):
"""Setups a trivial training procedure for sparse training."""
tf.reset_default_graph()
optim = tf.train.GradientDescentOptimizer(0.001)
sparse_optim = spa... | the_stack_v2_python_sparse | rigl/sparse_optimizers_test.py | google-research/rigl | train | 324 | |
a3bb547927e59ee7680f566fa921e4173e245150 | [
"can_edit_player(player_id)\ntickets = g.db.query(Ticket).filter(Ticket.player_id == player_id, Ticket.used_date == None)\nreturn tickets",
"args = request.json\nissuer_id = args.get('issuer_id')\nticket_type = args.get('ticket_type')\ndetails = args.get('details')\nexternal_id = args.get('external_id')\nticket_i... | <|body_start_0|>
can_edit_player(player_id)
tickets = g.db.query(Ticket).filter(Ticket.player_id == player_id, Ticket.used_date == None)
return tickets
<|end_body_0|>
<|body_start_1|>
args = request.json
issuer_id = args.get('issuer_id')
ticket_type = args.get('ticket_ty... | TicketsEndpoint | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TicketsEndpoint:
def get(self, player_id):
"""List of tickets Get a list of outstanding tickets for the player"""
<|body_0|>
def post(self, player_id):
"""Create ticket Create a ticket for a player. Only available to services"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_032432 | 5,287 | permissive | [
{
"docstring": "List of tickets Get a list of outstanding tickets for the player",
"name": "get",
"signature": "def get(self, player_id)"
},
{
"docstring": "Create ticket Create a ticket for a player. Only available to services",
"name": "post",
"signature": "def post(self, player_id)"
... | 2 | stack_v2_sparse_classes_30k_train_019617 | Implement the Python class `TicketsEndpoint` described below.
Class description:
Implement the TicketsEndpoint class.
Method signatures and docstrings:
- def get(self, player_id): List of tickets Get a list of outstanding tickets for the player
- def post(self, player_id): Create ticket Create a ticket for a player. ... | Implement the Python class `TicketsEndpoint` described below.
Class description:
Implement the TicketsEndpoint class.
Method signatures and docstrings:
- def get(self, player_id): List of tickets Get a list of outstanding tickets for the player
- def post(self, player_id): Create ticket Create a ticket for a player. ... | 9825cb22b26b577b715f2ce95453363bf90ecc7e | <|skeleton|>
class TicketsEndpoint:
def get(self, player_id):
"""List of tickets Get a list of outstanding tickets for the player"""
<|body_0|>
def post(self, player_id):
"""Create ticket Create a ticket for a player. Only available to services"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TicketsEndpoint:
def get(self, player_id):
"""List of tickets Get a list of outstanding tickets for the player"""
can_edit_player(player_id)
tickets = g.db.query(Ticket).filter(Ticket.player_id == player_id, Ticket.used_date == None)
return tickets
def post(self, player_id... | the_stack_v2_python_sparse | driftbase/api/players/tickets.py | dgnorth/drift-base | train | 1 | |
64a05d95283cff7199d76904fb0385ab5412cd25 | [
"most = 0\nfor idx, h in enumerate(height):\n for ridx, rh in enumerate(height[idx:]):\n most = max(ridx * min(h, rh), most)\nreturn most",
"if not height[1:]:\n return 0\nleft = 0\nright = len(height) - 1\nmost = 0\nwhile left < right:\n most = max(most, min(height[left], height[right]) * (right ... | <|body_start_0|>
most = 0
for idx, h in enumerate(height):
for ridx, rh in enumerate(height[idx:]):
most = max(ridx * min(h, rh), most)
return most
<|end_body_0|>
<|body_start_1|>
if not height[1:]:
return 0
left = 0
right = len(he... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea2(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
most = 0
for idx, h in enumerate(hei... | stack_v2_sparse_classes_36k_train_032433 | 2,247 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea2",
"signature": "def maxArea2(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea",
"signature": "def maxArea(self, height)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea2(self, height): :type height: List[int] :rtype: int
- def maxArea(self, height): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea2(self, height): :type height: List[int] :rtype: int
- def maxArea(self, height): :type height: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxArea2(s... | d2e8b2dca40fc955045eb62e576c776bad8ee5f1 | <|skeleton|>
class Solution:
def maxArea2(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxArea2(self, height):
""":type height: List[int] :rtype: int"""
most = 0
for idx, h in enumerate(height):
for ridx, rh in enumerate(height[idx:]):
most = max(ridx * min(h, rh), most)
return most
def maxArea(self, height):
... | the_stack_v2_python_sparse | container-with-most-water/solution.py | childe/leetcode | train | 2 | |
0e0e221b9cb29867a5f26effa1eb6d6f5b5c8df9 | [
"rest_kwargs = {'use_document_model': False, 'include_user_agent': True}\nif api_key is not None:\n rest_kwargs['api_key'] = api_key\nwith MPRester(**rest_kwargs) as mpr:\n results = mpr.summary.search(chemsys=chemsys, **kwargs, fields=['structure', 'material_id'])\nreturn MPQueryResults(results)",
"rest_kw... | <|body_start_0|>
rest_kwargs = {'use_document_model': False, 'include_user_agent': True}
if api_key is not None:
rest_kwargs['api_key'] = api_key
with MPRester(**rest_kwargs) as mpr:
results = mpr.summary.search(chemsys=chemsys, **kwargs, fields=['structure', 'material_id... | Convenience interface to the Materials Project Structure Database. Usage is only possible with an API key obtained from the Materials Project. To do this, create an account with them, login and access `this webpage <https://next-gen.materialsproject.org/api#api-key>`. Once you have a key, either pass it as the `api_key... | MaterialsProjectFactory | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaterialsProjectFactory:
"""Convenience interface to the Materials Project Structure Database. Usage is only possible with an API key obtained from the Materials Project. To do this, create an account with them, login and access `this webpage <https://next-gen.materialsproject.org/api#api-key>`. ... | stack_v2_sparse_classes_36k_train_032434 | 7,091 | permissive | [
{
"docstring": "Search the database for all structures matching the given query. Note that `chemsys` takes distint values for unaries, binaries and so! A query with `chemsys=[\"Fe\", \"O\"]` will return iron structures and oxygen structures, but no iron oxide structures. Similarily `chemsys=[\"Fe-O\"]` will not... | 2 | null | Implement the Python class `MaterialsProjectFactory` described below.
Class description:
Convenience interface to the Materials Project Structure Database. Usage is only possible with an API key obtained from the Materials Project. To do this, create an account with them, login and access `this webpage <https://next-g... | Implement the Python class `MaterialsProjectFactory` described below.
Class description:
Convenience interface to the Materials Project Structure Database. Usage is only possible with an API key obtained from the Materials Project. To do this, create an account with them, login and access `this webpage <https://next-g... | 4bebd2dd19df34f94bc043f78d497a890dc47fa7 | <|skeleton|>
class MaterialsProjectFactory:
"""Convenience interface to the Materials Project Structure Database. Usage is only possible with an API key obtained from the Materials Project. To do this, create an account with them, login and access `this webpage <https://next-gen.materialsproject.org/api#api-key>`. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MaterialsProjectFactory:
"""Convenience interface to the Materials Project Structure Database. Usage is only possible with an API key obtained from the Materials Project. To do this, create an account with them, login and access `this webpage <https://next-gen.materialsproject.org/api#api-key>`. Once you have... | the_stack_v2_python_sparse | pyiron_atomistics/atomistics/structure/factories/materialsproject.py | pyiron/pyiron_atomistics | train | 33 |
6ff64ae7e40eb6b443ab4c56906483e0a4c218de | [
"requests = get_client_pending_requests(current_identity.id)\nrequest_schema = BaseRequestJsonSchema(many=True)\nreturn request_schema.dump(requests).data",
"args = priority_parser.parse_args()\nrequests = update_client_priority_list(args.requests_id, current_identity.id)\nrequest_schema = BaseRequestJsonSchema(m... | <|body_start_0|>
requests = get_client_pending_requests(current_identity.id)
request_schema = BaseRequestJsonSchema(many=True)
return request_schema.dump(requests).data
<|end_body_0|>
<|body_start_1|>
args = priority_parser.parse_args()
requests = update_client_priority_list(arg... | An API to get all requests pending by a client. | RequestsPendingMeAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequestsPendingMeAPI:
"""An API to get all requests pending by a client."""
def get(self):
"""HTTP GET. Get all pending requests. :returns: all pendings request."""
<|body_0|>
def post(self):
"""HTTP POST. re order the priority list :returns: One or all available... | stack_v2_sparse_classes_36k_train_032435 | 7,523 | permissive | [
{
"docstring": "HTTP GET. Get all pending requests. :returns: all pendings request.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "HTTP POST. re order the priority list :returns: One or all available requests.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009021 | Implement the Python class `RequestsPendingMeAPI` described below.
Class description:
An API to get all requests pending by a client.
Method signatures and docstrings:
- def get(self): HTTP GET. Get all pending requests. :returns: all pendings request.
- def post(self): HTTP POST. re order the priority list :returns:... | Implement the Python class `RequestsPendingMeAPI` described below.
Class description:
An API to get all requests pending by a client.
Method signatures and docstrings:
- def get(self): HTTP GET. Get all pending requests. :returns: all pendings request.
- def post(self): HTTP POST. re order the priority list :returns:... | a8f04991deca85cf615df72db12e082aaa543cfa | <|skeleton|>
class RequestsPendingMeAPI:
"""An API to get all requests pending by a client."""
def get(self):
"""HTTP GET. Get all pending requests. :returns: all pendings request."""
<|body_0|>
def post(self):
"""HTTP POST. re order the priority list :returns: One or all available... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequestsPendingMeAPI:
"""An API to get all requests pending by a client."""
def get(self):
"""HTTP GET. Get all pending requests. :returns: all pendings request."""
requests = get_client_pending_requests(current_identity.id)
request_schema = BaseRequestJsonSchema(many=True)
... | the_stack_v2_python_sparse | flaskiwsapp/api/v1/views/requestViews.py | rtorresve/EngineeringMidLevel | train | 0 |
d10467e56e508f04b1804b6c9a068dd6f1a5b2de | [
"print('test_login1_normal is start test...')\npo = LoginPage(self.driver)\npo.Login_action(u'鹿太太', 123456)\nsleep(3)\nself.assertEqual(po.type_loginPass_hint(), u'我的空间')\nfunction.insert_img(self.driver, '51zxw_login1_nomal.jpg')\nprint('test_login1_normal test end')",
"print('test_login2_passworderror is start ... | <|body_start_0|>
print('test_login1_normal is start test...')
po = LoginPage(self.driver)
po.Login_action(u'鹿太太', 123456)
sleep(3)
self.assertEqual(po.type_loginPass_hint(), u'我的空间')
function.insert_img(self.driver, '51zxw_login1_nomal.jpg')
print('test_login1_nor... | LoginTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginTest:
def test_login1_normal(self):
"""username and password is normal"""
<|body_0|>
def test_login2_PasswordError(self):
"""username and password is error"""
<|body_1|>
def test_login3_empty(self):
"""username and passwd is empty"""
... | stack_v2_sparse_classes_36k_train_032436 | 1,453 | no_license | [
{
"docstring": "username and password is normal",
"name": "test_login1_normal",
"signature": "def test_login1_normal(self)"
},
{
"docstring": "username and password is error",
"name": "test_login2_PasswordError",
"signature": "def test_login2_PasswordError(self)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_train_015348 | Implement the Python class `LoginTest` described below.
Class description:
Implement the LoginTest class.
Method signatures and docstrings:
- def test_login1_normal(self): username and password is normal
- def test_login2_PasswordError(self): username and password is error
- def test_login3_empty(self): username and ... | Implement the Python class `LoginTest` described below.
Class description:
Implement the LoginTest class.
Method signatures and docstrings:
- def test_login1_normal(self): username and password is normal
- def test_login2_PasswordError(self): username and password is error
- def test_login3_empty(self): username and ... | 8f41650e31f856f944d9c61a9b8e35f7875f6c03 | <|skeleton|>
class LoginTest:
def test_login1_normal(self):
"""username and password is normal"""
<|body_0|>
def test_login2_PasswordError(self):
"""username and password is error"""
<|body_1|>
def test_login3_empty(self):
"""username and passwd is empty"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginTest:
def test_login1_normal(self):
"""username and password is normal"""
print('test_login1_normal is start test...')
po = LoginPage(self.driver)
po.Login_action(u'鹿太太', 123456)
sleep(3)
self.assertEqual(po.type_loginPass_hint(), u'我的空间')
function.... | the_stack_v2_python_sparse | webdriver/AutoTest_Project/Website/test_case/test_login.py | lutaitai/selenium-python | train | 0 | |
89dfca279728b505935a6ce367bdf7e3bdb79c92 | [
"try:\n account = account or self._server.myPlexAccount()\nexcept AttributeError:\n account = self._server\nreturn account.onWatchlist(self)",
"try:\n account = account or self._server.myPlexAccount()\nexcept AttributeError:\n account = self._server\naccount.addToWatchlist(self)\nreturn self",
"try:... | <|body_start_0|>
try:
account = account or self._server.myPlexAccount()
except AttributeError:
account = self._server
return account.onWatchlist(self)
<|end_body_0|>
<|body_start_1|>
try:
account = account or self._server.myPlexAccount()
excep... | Mixin for Plex objects that can be added to a user's watchlist. | WatchlistMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WatchlistMixin:
"""Mixin for Plex objects that can be added to a user's watchlist."""
def onWatchlist(self, account=None):
"""Returns True if the item is on the user's watchlist. Also see :func:`~plexapi.myplex.MyPlexAccount.onWatchlist`. Parameters: account (:class:`~plexapi.myplex.... | stack_v2_sparse_classes_36k_train_032437 | 43,885 | permissive | [
{
"docstring": "Returns True if the item is on the user's watchlist. Also see :func:`~plexapi.myplex.MyPlexAccount.onWatchlist`. Parameters: account (:class:`~plexapi.myplex.MyPlexAccount`, optional): Account to check item on the watchlist. Note: This is required if you are not connected to a Plex server instan... | 4 | stack_v2_sparse_classes_30k_test_001105 | Implement the Python class `WatchlistMixin` described below.
Class description:
Mixin for Plex objects that can be added to a user's watchlist.
Method signatures and docstrings:
- def onWatchlist(self, account=None): Returns True if the item is on the user's watchlist. Also see :func:`~plexapi.myplex.MyPlexAccount.on... | Implement the Python class `WatchlistMixin` described below.
Class description:
Mixin for Plex objects that can be added to a user's watchlist.
Method signatures and docstrings:
- def onWatchlist(self, account=None): Returns True if the item is on the user's watchlist. Also see :func:`~plexapi.myplex.MyPlexAccount.on... | 7da49eb711663f8b4e2cebcac41298c6324c1427 | <|skeleton|>
class WatchlistMixin:
"""Mixin for Plex objects that can be added to a user's watchlist."""
def onWatchlist(self, account=None):
"""Returns True if the item is on the user's watchlist. Also see :func:`~plexapi.myplex.MyPlexAccount.onWatchlist`. Parameters: account (:class:`~plexapi.myplex.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WatchlistMixin:
"""Mixin for Plex objects that can be added to a user's watchlist."""
def onWatchlist(self, account=None):
"""Returns True if the item is on the user's watchlist. Also see :func:`~plexapi.myplex.MyPlexAccount.onWatchlist`. Parameters: account (:class:`~plexapi.myplex.MyPlexAccount... | the_stack_v2_python_sparse | plexapi/mixins.py | pkkid/python-plexapi | train | 963 |
0a84b4b2b81fc0a0568cbaae984cdb85159c8a34 | [
"if attrs['password'] != attrs['password2']:\n raise serializers.ValidationError('两次密码不一致')\nallow = User.check_set_password_token(attrs['access_token'], self.context['view'].kwargs['pk'])\nif not allow:\n raise serializers.ValidationError('无效的access token')\nreturn attrs",
"instance.set_password(validated_... | <|body_start_0|>
if attrs['password'] != attrs['password2']:
raise serializers.ValidationError('两次密码不一致')
allow = User.check_set_password_token(attrs['access_token'], self.context['view'].kwargs['pk'])
if not allow:
raise serializers.ValidationError('无效的access token')
... | 重置密码序列化器 | CheckPasswordTokenSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckPasswordTokenSerializer:
"""重置密码序列化器"""
def validate(self, attrs):
"""校验数据"""
<|body_0|>
def update(self, instance, validated_data):
"""更新密码 :param instance: 根据pk对应的User模型对象 :param validated_data: 验证完成以后的数据 :return:"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_032438 | 19,382 | no_license | [
{
"docstring": "校验数据",
"name": "validate",
"signature": "def validate(self, attrs)"
},
{
"docstring": "更新密码 :param instance: 根据pk对应的User模型对象 :param validated_data: 验证完成以后的数据 :return:",
"name": "update",
"signature": "def update(self, instance, validated_data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010606 | Implement the Python class `CheckPasswordTokenSerializer` described below.
Class description:
重置密码序列化器
Method signatures and docstrings:
- def validate(self, attrs): 校验数据
- def update(self, instance, validated_data): 更新密码 :param instance: 根据pk对应的User模型对象 :param validated_data: 验证完成以后的数据 :return: | Implement the Python class `CheckPasswordTokenSerializer` described below.
Class description:
重置密码序列化器
Method signatures and docstrings:
- def validate(self, attrs): 校验数据
- def update(self, instance, validated_data): 更新密码 :param instance: 根据pk对应的User模型对象 :param validated_data: 验证完成以后的数据 :return:
<|skeleton|>
class C... | c4d9b124a50e96ce01dfd83073cbe4435cb07266 | <|skeleton|>
class CheckPasswordTokenSerializer:
"""重置密码序列化器"""
def validate(self, attrs):
"""校验数据"""
<|body_0|>
def update(self, instance, validated_data):
"""更新密码 :param instance: 根据pk对应的User模型对象 :param validated_data: 验证完成以后的数据 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckPasswordTokenSerializer:
"""重置密码序列化器"""
def validate(self, attrs):
"""校验数据"""
if attrs['password'] != attrs['password2']:
raise serializers.ValidationError('两次密码不一致')
allow = User.check_set_password_token(attrs['access_token'], self.context['view'].kwargs['pk'])
... | the_stack_v2_python_sparse | apps/users/serializer/serializers_front.py | wuhaihua1989/magic1 | train | 0 |
99c67e91df42f2e8a65bcd192ba5f7915b6609ea | [
"code = request.query_params.get('code')\nif code is None:\n return Response(status=status.HTTP_400_BAD_REQUEST)\nweiboauth = OAuthWeibo(client_id=settings.WEIBO_CLIENT_ID, client_secret=settings.WEIBO_CLIENT_SECRET, redirect_uri=settings.WEIBO_REDIRECT_URI, state=next)\naccess_token = weiboauth.get_access_token... | <|body_start_0|>
code = request.query_params.get('code')
if code is None:
return Response(status=status.HTTP_400_BAD_REQUEST)
weiboauth = OAuthWeibo(client_id=settings.WEIBO_CLIENT_ID, client_secret=settings.WEIBO_CLIENT_SECRET, redirect_uri=settings.WEIBO_REDIRECT_URI, state=next)
... | 验证微博登录 | WeiboOauthView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeiboOauthView:
"""验证微博登录"""
def get(self, request):
"""第三方登录检查 oauth/sina/user/ ?code=0e67548e9e075577630cc983ff79fa6a :param request: :return: pass"""
<|body_0|>
def post(self, request):
"""微博用户未绑定,绑定微博用户 :return:"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_032439 | 9,593 | no_license | [
{
"docstring": "第三方登录检查 oauth/sina/user/ ?code=0e67548e9e075577630cc983ff79fa6a :param request: :return: pass",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "微博用户未绑定,绑定微博用户 :return:",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011392 | Implement the Python class `WeiboOauthView` described below.
Class description:
验证微博登录
Method signatures and docstrings:
- def get(self, request): 第三方登录检查 oauth/sina/user/ ?code=0e67548e9e075577630cc983ff79fa6a :param request: :return: pass
- def post(self, request): 微博用户未绑定,绑定微博用户 :return: | Implement the Python class `WeiboOauthView` described below.
Class description:
验证微博登录
Method signatures and docstrings:
- def get(self, request): 第三方登录检查 oauth/sina/user/ ?code=0e67548e9e075577630cc983ff79fa6a :param request: :return: pass
- def post(self, request): 微博用户未绑定,绑定微博用户 :return:
<|skeleton|>
class WeiboO... | 93f5c1159de7c2fcb5a4de0cfeee15b19529abf5 | <|skeleton|>
class WeiboOauthView:
"""验证微博登录"""
def get(self, request):
"""第三方登录检查 oauth/sina/user/ ?code=0e67548e9e075577630cc983ff79fa6a :param request: :return: pass"""
<|body_0|>
def post(self, request):
"""微博用户未绑定,绑定微博用户 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WeiboOauthView:
"""验证微博登录"""
def get(self, request):
"""第三方登录检查 oauth/sina/user/ ?code=0e67548e9e075577630cc983ff79fa6a :param request: :return: pass"""
code = request.query_params.get('code')
if code is None:
return Response(status=status.HTTP_400_BAD_REQUEST)
... | the_stack_v2_python_sparse | mall/apps/oauth/views.py | studygroupfirst/meiduoshangcheng | train | 0 |
e73fb9f7c5c3526de6839da18e5b41b1db754e04 | [
"self.cluster_count = cluster_count\nself.cluster_match_string = cluster_match_string\nself.cookie = cookie\nself.end_time_usecs = end_time_usecs\nself.error = error\nself.job_count = job_count\nself.job_match_string = job_match_string\nself.protection_jobs = protection_jobs\nself.search_job_status = search_job_sta... | <|body_start_0|>
self.cluster_count = cluster_count
self.cluster_match_string = cluster_match_string
self.cookie = cookie
self.end_time_usecs = end_time_usecs
self.error = error
self.job_count = job_count
self.job_match_string = job_match_string
self.prote... | Implementation of the 'RemoteVaultSearchJobResults' model. Specifies detailed information about Job Runs of Protection Jobs found by a search Job when searching a remote Vault for archived data. Attributes: cluster_count (int): Specifies number of Clusters that have archived to the remote Vault that match the criteria ... | RemoteVaultSearchJobResults | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteVaultSearchJobResults:
"""Implementation of the 'RemoteVaultSearchJobResults' model. Specifies detailed information about Job Runs of Protection Jobs found by a search Job when searching a remote Vault for archived data. Attributes: cluster_count (int): Specifies number of Clusters that hav... | stack_v2_sparse_classes_36k_train_032440 | 7,245 | permissive | [
{
"docstring": "Constructor for the RemoteVaultSearchJobResults class",
"name": "__init__",
"signature": "def __init__(self, cluster_count=None, cluster_match_string=None, cookie=None, end_time_usecs=None, error=None, job_count=None, job_match_string=None, protection_jobs=None, search_job_status=None, s... | 2 | stack_v2_sparse_classes_30k_train_017813 | Implement the Python class `RemoteVaultSearchJobResults` described below.
Class description:
Implementation of the 'RemoteVaultSearchJobResults' model. Specifies detailed information about Job Runs of Protection Jobs found by a search Job when searching a remote Vault for archived data. Attributes: cluster_count (int)... | Implement the Python class `RemoteVaultSearchJobResults` described below.
Class description:
Implementation of the 'RemoteVaultSearchJobResults' model. Specifies detailed information about Job Runs of Protection Jobs found by a search Job when searching a remote Vault for archived data. Attributes: cluster_count (int)... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RemoteVaultSearchJobResults:
"""Implementation of the 'RemoteVaultSearchJobResults' model. Specifies detailed information about Job Runs of Protection Jobs found by a search Job when searching a remote Vault for archived data. Attributes: cluster_count (int): Specifies number of Clusters that hav... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RemoteVaultSearchJobResults:
"""Implementation of the 'RemoteVaultSearchJobResults' model. Specifies detailed information about Job Runs of Protection Jobs found by a search Job when searching a remote Vault for archived data. Attributes: cluster_count (int): Specifies number of Clusters that have archived to... | the_stack_v2_python_sparse | cohesity_management_sdk/models/remote_vault_search_job_results.py | cohesity/management-sdk-python | train | 24 |
38e93468f35782a73e204ee3e21215108f1be936 | [
"if args:\n self.message = args[0]\nelse:\n self.message = None",
"print('calling str')\nif self.message:\n return 'MyCustomError, {0} '.format(self.message)\nelse:\n return 'MyCustomError has been raised'"
] | <|body_start_0|>
if args:
self.message = args[0]
else:
self.message = None
<|end_body_0|>
<|body_start_1|>
print('calling str')
if self.message:
return 'MyCustomError, {0} '.format(self.message)
else:
return 'MyCustomError has been... | Documentation for a class. Herit from Exception @throws Exception | MyCustomError | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyCustomError:
"""Documentation for a class. Herit from Exception @throws Exception"""
def __init__(self, *args):
"""Documentation for a function. Constructor"""
<|body_0|>
def __str__(self):
"""Documentation for a function. @return string that triggers Exception... | stack_v2_sparse_classes_36k_train_032441 | 2,814 | permissive | [
{
"docstring": "Documentation for a function. Constructor",
"name": "__init__",
"signature": "def __init__(self, *args)"
},
{
"docstring": "Documentation for a function. @return string that triggers Exception",
"name": "__str__",
"signature": "def __str__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006115 | Implement the Python class `MyCustomError` described below.
Class description:
Documentation for a class. Herit from Exception @throws Exception
Method signatures and docstrings:
- def __init__(self, *args): Documentation for a function. Constructor
- def __str__(self): Documentation for a function. @return string th... | Implement the Python class `MyCustomError` described below.
Class description:
Documentation for a class. Herit from Exception @throws Exception
Method signatures and docstrings:
- def __init__(self, *args): Documentation for a function. Constructor
- def __str__(self): Documentation for a function. @return string th... | 1a20978a29ab285f80a35c7b55fc484c40d20bbb | <|skeleton|>
class MyCustomError:
"""Documentation for a class. Herit from Exception @throws Exception"""
def __init__(self, *args):
"""Documentation for a function. Constructor"""
<|body_0|>
def __str__(self):
"""Documentation for a function. @return string that triggers Exception... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyCustomError:
"""Documentation for a class. Herit from Exception @throws Exception"""
def __init__(self, *args):
"""Documentation for a function. Constructor"""
if args:
self.message = args[0]
else:
self.message = None
def __str__(self):
"""Do... | the_stack_v2_python_sparse | Includes/personnal/except.py | WikiLibs/Parser | train | 0 |
ca12abef2b82c34bef6c15b6bf77f568ac0aa3bf | [
"self.condition_tissue = ConditionTissue.query.filter(ConditionTissue.in_tree == 1).all()\nmerged_conditions = list(merge(*[json.loads(ct.data)['order'] for ct in self.condition_tissue]))\nself.conditions = list(reversed(list(OrderedDict.fromkeys(reversed(merged_conditions)))))\nself.species_to_condition = {ct.spec... | <|body_start_0|>
self.condition_tissue = ConditionTissue.query.filter(ConditionTissue.in_tree == 1).all()
merged_conditions = list(merge(*[json.loads(ct.data)['order'] for ct in self.condition_tissue]))
self.conditions = list(reversed(list(OrderedDict.fromkeys(reversed(merged_conditions)))))
... | CrossSpeciesExpressionProfile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CrossSpeciesExpressionProfile:
def __init__(self):
"""Function that gets required data, checks for which species there is a comparative profile available and stores details to convert the profiles for that species."""
<|body_0|>
def get_data(self, *sequence_ids):
"""... | stack_v2_sparse_classes_36k_train_032442 | 5,795 | permissive | [
{
"docstring": "Function that gets required data, checks for which species there is a comparative profile available and stores details to convert the profiles for that species.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Gets comparative profiles for a set of seque... | 3 | stack_v2_sparse_classes_30k_train_018569 | Implement the Python class `CrossSpeciesExpressionProfile` described below.
Class description:
Implement the CrossSpeciesExpressionProfile class.
Method signatures and docstrings:
- def __init__(self): Function that gets required data, checks for which species there is a comparative profile available and stores detai... | Implement the Python class `CrossSpeciesExpressionProfile` described below.
Class description:
Implement the CrossSpeciesExpressionProfile class.
Method signatures and docstrings:
- def __init__(self): Function that gets required data, checks for which species there is a comparative profile available and stores detai... | 25d0187030bcb85bb99125af4fd0c0c11aa012cb | <|skeleton|>
class CrossSpeciesExpressionProfile:
def __init__(self):
"""Function that gets required data, checks for which species there is a comparative profile available and stores details to convert the profiles for that species."""
<|body_0|>
def get_data(self, *sequence_ids):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CrossSpeciesExpressionProfile:
def __init__(self):
"""Function that gets required data, checks for which species there is a comparative profile available and stores details to convert the profiles for that species."""
self.condition_tissue = ConditionTissue.query.filter(ConditionTissue.in_tree... | the_stack_v2_python_sparse | conekt/models/expression/cross_species_profile.py | sepro/CoNekT | train | 23 | |
9872b2fb4032a2095c6cd89f10139dc9200549e5 | [
"try:\n license_path = user_info.get('license_path', '')\n id_card_path = user_info.get('id_card_path', '')\n user_company_name = user_info.get('user_company_name', '')\n user_type = user_info.get('user_type', '')\n user_address = user_info.get('user_address', '')\n province = user_info.get('provi... | <|body_start_0|>
try:
license_path = user_info.get('license_path', '')
id_card_path = user_info.get('id_card_path', '')
user_company_name = user_info.get('user_company_name', '')
user_type = user_info.get('user_type', '')
user_address = user_info.get('... | Complete_material | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Complete_material:
def completeUserInfo(self, user_id, user_info):
""":param user_id: :param user_info: :return: 正常插入，返回666；更新失败，返回0"""
<|body_0|>
def editUserInfo(self, user_id, user_info):
""":param user_id: :param user_info: :return: 正常更新，返回666；更新失败，返回0"""
... | stack_v2_sparse_classes_36k_train_032443 | 5,775 | no_license | [
{
"docstring": ":param user_id: :param user_info: :return: 正常插入，返回666；更新失败，返回0",
"name": "completeUserInfo",
"signature": "def completeUserInfo(self, user_id, user_info)"
},
{
"docstring": ":param user_id: :param user_info: :return: 正常更新，返回666；更新失败，返回0",
"name": "editUserInfo",
"signatur... | 3 | stack_v2_sparse_classes_30k_train_006218 | Implement the Python class `Complete_material` described below.
Class description:
Implement the Complete_material class.
Method signatures and docstrings:
- def completeUserInfo(self, user_id, user_info): :param user_id: :param user_info: :return: 正常插入，返回666；更新失败，返回0
- def editUserInfo(self, user_id, user_info): :pa... | Implement the Python class `Complete_material` described below.
Class description:
Implement the Complete_material class.
Method signatures and docstrings:
- def completeUserInfo(self, user_id, user_info): :param user_id: :param user_info: :return: 正常插入，返回666；更新失败，返回0
- def editUserInfo(self, user_id, user_info): :pa... | 9e47e4eb0e65a0a849cc351c79bc0f2b07ac37ae | <|skeleton|>
class Complete_material:
def completeUserInfo(self, user_id, user_info):
""":param user_id: :param user_info: :return: 正常插入，返回666；更新失败，返回0"""
<|body_0|>
def editUserInfo(self, user_id, user_info):
""":param user_id: :param user_info: :return: 正常更新，返回666；更新失败，返回0"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Complete_material:
def completeUserInfo(self, user_id, user_info):
""":param user_id: :param user_info: :return: 正常插入，返回666；更新失败，返回0"""
try:
license_path = user_info.get('license_path', '')
id_card_path = user_info.get('id_card_path', '')
user_company_name =... | the_stack_v2_python_sparse | guyj319/B2B_v1/account/my_materials/complete_info.py | songting77/newB2B_v1 | train | 0 | |
3696505db2cfbda4e2d94e6db7116570b81bdd7f | [
"assert op.node_def.op == 'MatMul'\nself.op = op\nself.colocate_gradients_with_ops = colocate_gradients_with_ops\nself.gate_gradients = gate_gradients",
"idx = list(self.op.inputs).index(x)\nassert idx != -1\nassert len(z_grads) == len(self.op.outputs)\nassert idx == 1\nx, _ = self.op.inputs\nz_grads, = z_grads\n... | <|body_start_0|>
assert op.node_def.op == 'MatMul'
self.op = op
self.colocate_gradients_with_ops = colocate_gradients_with_ops
self.gate_gradients = gate_gradients
<|end_body_0|>
<|body_start_1|>
idx = list(self.op.inputs).index(x)
assert idx != -1
assert len(z_g... | Per-example gradient rule for MatMul op. | MatMulPXG | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MatMulPXG:
"""Per-example gradient rule for MatMul op."""
def __init__(self, op, colocate_gradients_with_ops=False, gate_gradients=False):
"""Construct an instance of the rule for `op`. Args: op: The Operation to differentiate through. colocate_gradients_with_ops: currently unsupport... | stack_v2_sparse_classes_36k_train_032444 | 12,247 | permissive | [
{
"docstring": "Construct an instance of the rule for `op`. Args: op: The Operation to differentiate through. colocate_gradients_with_ops: currently unsupported gate_gradients: currently unsupported",
"name": "__init__",
"signature": "def __init__(self, op, colocate_gradients_with_ops=False, gate_gradie... | 2 | stack_v2_sparse_classes_30k_train_016059 | Implement the Python class `MatMulPXG` described below.
Class description:
Per-example gradient rule for MatMul op.
Method signatures and docstrings:
- def __init__(self, op, colocate_gradients_with_ops=False, gate_gradients=False): Construct an instance of the rule for `op`. Args: op: The Operation to differentiate ... | Implement the Python class `MatMulPXG` described below.
Class description:
Per-example gradient rule for MatMul op.
Method signatures and docstrings:
- def __init__(self, op, colocate_gradients_with_ops=False, gate_gradients=False): Construct an instance of the rule for `op`. Args: op: The Operation to differentiate ... | 92ec5ec3efeee852aec5c057798298cd3a8e58ae | <|skeleton|>
class MatMulPXG:
"""Per-example gradient rule for MatMul op."""
def __init__(self, op, colocate_gradients_with_ops=False, gate_gradients=False):
"""Construct an instance of the rule for `op`. Args: op: The Operation to differentiate through. colocate_gradients_with_ops: currently unsupport... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MatMulPXG:
"""Per-example gradient rule for MatMul op."""
def __init__(self, op, colocate_gradients_with_ops=False, gate_gradients=False):
"""Construct an instance of the rule for `op`. Args: op: The Operation to differentiate through. colocate_gradients_with_ops: currently unsupported gate_gradi... | the_stack_v2_python_sparse | model_zoo/models/differential_privacy/dp_sgd/per_example_gradients/per_example_gradients.py | coderSkyChen/Action_Recognition_Zoo | train | 246 |
0ca18030f0d39e6fba58c4ddb1ac45ccc277e674 | [
"if settings.DEBUG:\n return True\nelse:\n return False",
"if settings.DEBUG:\n return True\nelse:\n return False"
] | <|body_start_0|>
if settings.DEBUG:
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
if settings.DEBUG:
return True
else:
return False
<|end_body_1|>
| ContactsAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContactsAdmin:
def has_add_permission(self, *args, **kwargs):
"""Запрещаем добавлять новые экземпляры Contacts при DEBUG=False"""
<|body_0|>
def has_delete_permission(self, *args, **kwargs):
"""Запрещаем удалять экземпляры Contacts при DEBUG=False"""
<|body_1... | stack_v2_sparse_classes_36k_train_032445 | 1,855 | no_license | [
{
"docstring": "Запрещаем добавлять новые экземпляры Contacts при DEBUG=False",
"name": "has_add_permission",
"signature": "def has_add_permission(self, *args, **kwargs)"
},
{
"docstring": "Запрещаем удалять экземпляры Contacts при DEBUG=False",
"name": "has_delete_permission",
"signatur... | 2 | stack_v2_sparse_classes_30k_val_001151 | Implement the Python class `ContactsAdmin` described below.
Class description:
Implement the ContactsAdmin class.
Method signatures and docstrings:
- def has_add_permission(self, *args, **kwargs): Запрещаем добавлять новые экземпляры Contacts при DEBUG=False
- def has_delete_permission(self, *args, **kwargs): Запреща... | Implement the Python class `ContactsAdmin` described below.
Class description:
Implement the ContactsAdmin class.
Method signatures and docstrings:
- def has_add_permission(self, *args, **kwargs): Запрещаем добавлять новые экземпляры Contacts при DEBUG=False
- def has_delete_permission(self, *args, **kwargs): Запреща... | c76996698bbbd88309ed35f47d19e09fec19eb94 | <|skeleton|>
class ContactsAdmin:
def has_add_permission(self, *args, **kwargs):
"""Запрещаем добавлять новые экземпляры Contacts при DEBUG=False"""
<|body_0|>
def has_delete_permission(self, *args, **kwargs):
"""Запрещаем удалять экземпляры Contacts при DEBUG=False"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContactsAdmin:
def has_add_permission(self, *args, **kwargs):
"""Запрещаем добавлять новые экземпляры Contacts при DEBUG=False"""
if settings.DEBUG:
return True
else:
return False
def has_delete_permission(self, *args, **kwargs):
"""Запрещаем удалят... | the_stack_v2_python_sparse | www/contacts/admin.py | boogiiieee/Victoria | train | 0 | |
cf2abb2da66eb777a9103819f2f2ec2a871a5453 | [
"self._validator = None\nself.logger = logger\nif api_spec_path is not None:\n try:\n api_spec_dict = read_yaml_file(api_spec_path)\n if server is not None:\n api_spec_dict['servers'] = [{'url': server}]\n api_spec = create_spec(api_spec_dict)\n self._validator = RequestVal... | <|body_start_0|>
self._validator = None
self.logger = logger
if api_spec_path is not None:
try:
api_spec_dict = read_yaml_file(api_spec_path)
if server is not None:
api_spec_dict['servers'] = [{'url': server}]
api_sp... | API Spec class to verify a request against an OpenAPI/Swagger spec. | APISpec | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class APISpec:
"""API Spec class to verify a request against an OpenAPI/Swagger spec."""
def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger):
"""Initialize the API spec. :param api_spec_path: Directory API path and filen... | stack_v2_sparse_classes_36k_train_032446 | 21,668 | permissive | [
{
"docstring": "Initialize the API spec. :param api_spec_path: Directory API path and filename of the API spec YAML source file. :param server: the server url :param logger: the logger",
"name": "__init__",
"signature": "def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, l... | 2 | stack_v2_sparse_classes_30k_train_017784 | Implement the Python class `APISpec` described below.
Class description:
API Spec class to verify a request against an OpenAPI/Swagger spec.
Method signatures and docstrings:
- def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger): Initialize the API... | Implement the Python class `APISpec` described below.
Class description:
API Spec class to verify a request against an OpenAPI/Swagger spec.
Method signatures and docstrings:
- def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger): Initialize the API... | bec49adaeba661d8d0f03ac9935dc89f39d95a0d | <|skeleton|>
class APISpec:
"""API Spec class to verify a request against an OpenAPI/Swagger spec."""
def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger):
"""Initialize the API spec. :param api_spec_path: Directory API path and filen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class APISpec:
"""API Spec class to verify a request against an OpenAPI/Swagger spec."""
def __init__(self, api_spec_path: Optional[str]=None, server: Optional[str]=None, logger: logging.Logger=_default_logger):
"""Initialize the API spec. :param api_spec_path: Directory API path and filename of the AP... | the_stack_v2_python_sparse | packages/fetchai/connections/http_server/connection.py | fetchai/agents-aea | train | 192 |
8467dcdd46c26c027ca3888d2f2c2983aa9fe9d6 | [
"n = len(A)\nindices = sorted(range(n), key=lambda i: A[i])\nres = 0\npre = n\nfor i in indices:\n if i < pre:\n pre = i\n else:\n res = max(res, i - pre)\nreturn res",
"stack = []\nfor i, a in enumerate(A):\n if not stack or (stack and A[stack[-1]] > a):\n stack.append(i)\nres = 0\n... | <|body_start_0|>
n = len(A)
indices = sorted(range(n), key=lambda i: A[i])
res = 0
pre = n
for i in indices:
if i < pre:
pre = i
else:
res = max(res, i - pre)
return res
<|end_body_0|>
<|body_start_1|>
stack... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxWidthRamp1(self, A: List[int]) -> int:
"""求一个最长的上坡 索引排序 @param A: @return:"""
<|body_0|>
def maxWidthRamp2(self, A: List[int]) -> int:
"""单调栈 @param A: @return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(A)
indi... | stack_v2_sparse_classes_36k_train_032447 | 1,773 | no_license | [
{
"docstring": "求一个最长的上坡 索引排序 @param A: @return:",
"name": "maxWidthRamp1",
"signature": "def maxWidthRamp1(self, A: List[int]) -> int"
},
{
"docstring": "单调栈 @param A: @return:",
"name": "maxWidthRamp2",
"signature": "def maxWidthRamp2(self, A: List[int]) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_009657 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxWidthRamp1(self, A: List[int]) -> int: 求一个最长的上坡 索引排序 @param A: @return:
- def maxWidthRamp2(self, A: List[int]) -> int: 单调栈 @param A: @return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxWidthRamp1(self, A: List[int]) -> int: 求一个最长的上坡 索引排序 @param A: @return:
- def maxWidthRamp2(self, A: List[int]) -> int: 单调栈 @param A: @return:
<|skeleton|>
class Solution... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def maxWidthRamp1(self, A: List[int]) -> int:
"""求一个最长的上坡 索引排序 @param A: @return:"""
<|body_0|>
def maxWidthRamp2(self, A: List[int]) -> int:
"""单调栈 @param A: @return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxWidthRamp1(self, A: List[int]) -> int:
"""求一个最长的上坡 索引排序 @param A: @return:"""
n = len(A)
indices = sorted(range(n), key=lambda i: A[i])
res = 0
pre = n
for i in indices:
if i < pre:
pre = i
else:
... | the_stack_v2_python_sparse | LeetCode/栈/单调栈(Monotone Stack)/962. 最大宽度坡.py | yiming1012/MyLeetCode | train | 2 | |
ad381d7110cf0b80a9a83f67b9019fab7d3fabbb | [
"super(AttentionModule, self).__init__()\nself.encoder_att = nn.Linear(encoder_dim, attention_dim)\nself.decoder_att = nn.Linear(decoder_dim, attention_dim)\nself.full_att = nn.Linear(attention_dim, 1)\nself.relu = nn.ReLU()\nself.softmax = nn.Softmax(dim=1)",
"att1 = self.encoder_att(encoder_out)\natt2 = self.de... | <|body_start_0|>
super(AttentionModule, self).__init__()
self.encoder_att = nn.Linear(encoder_dim, attention_dim)
self.decoder_att = nn.Linear(decoder_dim, attention_dim)
self.full_att = nn.Linear(attention_dim, 1)
self.relu = nn.ReLU()
self.softmax = nn.Softmax(dim=1)
<|... | AttentionModule | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttentionModule:
def __init__(self, encoder_dim, decoder_dim, attention_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
<|body_0|>
def forward(self, encoder_out, deco... | stack_v2_sparse_classes_36k_train_032448 | 8,057 | permissive | [
{
"docstring": ":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network",
"name": "__init__",
"signature": "def __init__(self, encoder_dim, decoder_dim, attention_dim)"
},
{
"docstring": "Forward propagation... | 2 | stack_v2_sparse_classes_30k_train_018318 | Implement the Python class `AttentionModule` described below.
Class description:
Implement the AttentionModule class.
Method signatures and docstrings:
- def __init__(self, encoder_dim, decoder_dim, attention_dim): :param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param att... | Implement the Python class `AttentionModule` described below.
Class description:
Implement the AttentionModule class.
Method signatures and docstrings:
- def __init__(self, encoder_dim, decoder_dim, attention_dim): :param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param att... | 355c68597545dbd7d01de4ea19263d09ddb644d3 | <|skeleton|>
class AttentionModule:
def __init__(self, encoder_dim, decoder_dim, attention_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
<|body_0|>
def forward(self, encoder_out, deco... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttentionModule:
def __init__(self, encoder_dim, decoder_dim, attention_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
super(AttentionModule, self).__init__()
self.encoder_att ... | the_stack_v2_python_sparse | models/show_attend_tell.py | mitjanikolaus/compositional-image-captioning | train | 25 | |
3b555cb625e7e6671615bd9aac69edac0239edb4 | [
"if request.args.get('number'):\n data = db.session.query(Room).filter(Room.number == request.args.get('number')).first()\n return marshal(data, r_struct) if data else 'No such room!'\nif request.args.get('status'):\n data = db.session.query(Room).filter(Room.status == request.args.get('status')).all()\n ... | <|body_start_0|>
if request.args.get('number'):
data = db.session.query(Room).filter(Room.number == request.args.get('number')).first()
return marshal(data, r_struct) if data else 'No such room!'
if request.args.get('status'):
data = db.session.query(Room).filter(Room... | RoomsRes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoomsRes:
def get(self):
"""Get info about all rooms if no query string parameters added. Get info about particular rooms if '?number=' added Get info about all rooms with specified status if '?status=' added :return:"""
<|body_0|>
def post(self):
"""Add a new room. ... | stack_v2_sparse_classes_36k_train_032449 | 2,397 | no_license | [
{
"docstring": "Get info about all rooms if no query string parameters added. Get info about particular rooms if '?number=' added Get info about all rooms with specified status if '?status=' added :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Add a new room. :return:"... | 4 | stack_v2_sparse_classes_30k_train_014336 | Implement the Python class `RoomsRes` described below.
Class description:
Implement the RoomsRes class.
Method signatures and docstrings:
- def get(self): Get info about all rooms if no query string parameters added. Get info about particular rooms if '?number=' added Get info about all rooms with specified status if... | Implement the Python class `RoomsRes` described below.
Class description:
Implement the RoomsRes class.
Method signatures and docstrings:
- def get(self): Get info about all rooms if no query string parameters added. Get info about particular rooms if '?number=' added Get info about all rooms with specified status if... | d3759f773f9abc0e917e75c174c28feb7d4a0692 | <|skeleton|>
class RoomsRes:
def get(self):
"""Get info about all rooms if no query string parameters added. Get info about particular rooms if '?number=' added Get info about all rooms with specified status if '?status=' added :return:"""
<|body_0|>
def post(self):
"""Add a new room. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoomsRes:
def get(self):
"""Get info about all rooms if no query string parameters added. Get info about particular rooms if '?number=' added Get info about all rooms with specified status if '?status=' added :return:"""
if request.args.get('number'):
data = db.session.query(Room).... | the_stack_v2_python_sparse | rest_alchemy/rooms/routes.py | serhiihoriaiev/common | train | 0 | |
2ec8540eac3048cc7295d9923e719fc08970a3b2 | [
"cnt = {}\nn = len(nums)\nfor i in nums:\n if cnt.get(i, 0) == 0:\n cnt[i] = 1\n else:\n cnt[i] += 1\n if cnt[i] > n // 2:\n return i\nif n == 1:\n return nums[0]",
"count = 0\ncandidate = None\nfor i in nums:\n if count == 0:\n candidate = i\n count += 1 if i... | <|body_start_0|>
cnt = {}
n = len(nums)
for i in nums:
if cnt.get(i, 0) == 0:
cnt[i] = 1
else:
cnt[i] += 1
if cnt[i] > n // 2:
return i
if n == 1:
return nums[0]
<|end_body_0|>
<|body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def majorityElement(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def majorityElement(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cnt = {}
n = len(nums)
... | stack_v2_sparse_classes_36k_train_032450 | 776 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "majorityElement",
"signature": "def majorityElement(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "majorityElement",
"signature": "def majorityElement(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000260 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majorityElement(self, nums): :type nums: List[int] :rtype: int
- def majorityElement(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majorityElement(self, nums): :type nums: List[int] :rtype: int
- def majorityElement(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def maj... | b7d9238d692b1b2f5ab8f73a76d02228a71a4d15 | <|skeleton|>
class Solution:
def majorityElement(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def majorityElement(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def majorityElement(self, nums):
""":type nums: List[int] :rtype: int"""
cnt = {}
n = len(nums)
for i in nums:
if cnt.get(i, 0) == 0:
cnt[i] = 1
else:
cnt[i] += 1
if cnt[i] > n // 2:
... | the_stack_v2_python_sparse | 169-Majority-Element.py | liuspencersjtu/MyLeetCode | train | 0 | |
0fdc22174c851eae455e155342136a58e8714159 | [
"try:\n if altura == '':\n raise custom_exceptions.ErrorDeNegocio(origen='neogocio_direccion.alta_pd()', msj_adicional='Error al validar una dirección. La altura no puede quedar vacía.')\n elif not isinstance(int(altura), int):\n raise custom_exceptions.ErrorDeNegocio(origen='neogocio_direccion.... | <|body_start_0|>
try:
if altura == '':
raise custom_exceptions.ErrorDeNegocio(origen='neogocio_direccion.alta_pd()', msj_adicional='Error al validar una dirección. La altura no puede quedar vacía.')
elif not isinstance(int(altura), int):
raise custom_excep... | NegocioDireccion | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NegocioDireccion:
def valida_direccion(cls, calle, altura, ciudad, provincia, pais):
"""Realiza las validaciones de negocio de una direccion."""
<|body_0|>
def alta_direccion(cls, calle, altura, ciudad, provincia, pais, validar=False):
"""Añade una dirección a la BD.... | stack_v2_sparse_classes_36k_train_032451 | 4,578 | no_license | [
{
"docstring": "Realiza las validaciones de negocio de una direccion.",
"name": "valida_direccion",
"signature": "def valida_direccion(cls, calle, altura, ciudad, provincia, pais)"
},
{
"docstring": "Añade una dirección a la BD.",
"name": "alta_direccion",
"signature": "def alta_direccio... | 3 | stack_v2_sparse_classes_30k_train_015902 | Implement the Python class `NegocioDireccion` described below.
Class description:
Implement the NegocioDireccion class.
Method signatures and docstrings:
- def valida_direccion(cls, calle, altura, ciudad, provincia, pais): Realiza las validaciones de negocio de una direccion.
- def alta_direccion(cls, calle, altura, ... | Implement the Python class `NegocioDireccion` described below.
Class description:
Implement the NegocioDireccion class.
Method signatures and docstrings:
- def valida_direccion(cls, calle, altura, ciudad, provincia, pais): Realiza las validaciones de negocio de una direccion.
- def alta_direccion(cls, calle, altura, ... | 57ca674dba4dabd2526c450ba7210933240f19c5 | <|skeleton|>
class NegocioDireccion:
def valida_direccion(cls, calle, altura, ciudad, provincia, pais):
"""Realiza las validaciones de negocio de una direccion."""
<|body_0|>
def alta_direccion(cls, calle, altura, ciudad, provincia, pais, validar=False):
"""Añade una dirección a la BD.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NegocioDireccion:
def valida_direccion(cls, calle, altura, ciudad, provincia, pais):
"""Realiza las validaciones de negocio de una direccion."""
try:
if altura == '':
raise custom_exceptions.ErrorDeNegocio(origen='neogocio_direccion.alta_pd()', msj_adicional='Error ... | the_stack_v2_python_sparse | negocio/negocio_direccion.py | JoaquinCardonaRuiz/proyecto-final | train | 0 | |
2bd18ed86d723b8d85d26c87a9aa5a664d7d3498 | [
"if not features.has(READ_FEATURE, organization, actor=request.user):\n return Response(status=404)\nif isinstance(dashboard, dict):\n return self.respond(dashboard)\nreturn self.respond(serialize(dashboard, request.user))",
"if not features.has(EDIT_FEATURE, organization, actor=request.user):\n return R... | <|body_start_0|>
if not features.has(READ_FEATURE, organization, actor=request.user):
return Response(status=404)
if isinstance(dashboard, dict):
return self.respond(dashboard)
return self.respond(serialize(dashboard, request.user))
<|end_body_0|>
<|body_start_1|>
... | OrganizationDashboardDetailsEndpoint | [
"BUSL-1.1",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationDashboardDetailsEndpoint:
def get(self, request, organization, dashboard):
"""Retrieve an Organization's Dashboard ```````````````````````````````````` Return details on an individual organization's dashboard. :pparam string organization_slug: the slug of the organization the... | stack_v2_sparse_classes_36k_train_032452 | 4,100 | permissive | [
{
"docstring": "Retrieve an Organization's Dashboard ```````````````````````````````````` Return details on an individual organization's dashboard. :pparam string organization_slug: the slug of the organization the dashboard belongs to. :pparam int dashboard_id: the id of the dashboard. :auth: required",
"n... | 3 | null | Implement the Python class `OrganizationDashboardDetailsEndpoint` described below.
Class description:
Implement the OrganizationDashboardDetailsEndpoint class.
Method signatures and docstrings:
- def get(self, request, organization, dashboard): Retrieve an Organization's Dashboard ````````````````````````````````````... | Implement the Python class `OrganizationDashboardDetailsEndpoint` described below.
Class description:
Implement the OrganizationDashboardDetailsEndpoint class.
Method signatures and docstrings:
- def get(self, request, organization, dashboard): Retrieve an Organization's Dashboard ````````````````````````````````````... | 63d698f5294f64a8c206b4c741e2a11be1f9a9be | <|skeleton|>
class OrganizationDashboardDetailsEndpoint:
def get(self, request, organization, dashboard):
"""Retrieve an Organization's Dashboard ```````````````````````````````````` Return details on an individual organization's dashboard. :pparam string organization_slug: the slug of the organization the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrganizationDashboardDetailsEndpoint:
def get(self, request, organization, dashboard):
"""Retrieve an Organization's Dashboard ```````````````````````````````````` Return details on an individual organization's dashboard. :pparam string organization_slug: the slug of the organization the dashboard bel... | the_stack_v2_python_sparse | src/sentry/api/endpoints/organization_dashboard_details.py | kaozdl/sentry | train | 0 | |
8f3980fbee59969dccd76ce8972a9f44a6d6e07e | [
"self.cloud_deploy_entity_vec = cloud_deploy_entity_vec\nself.is_incremental = is_incremental\nself.restore_info = restore_info\nself.target_type = target_type\nself.total_bytes_transferred_to_source = total_bytes_transferred_to_source\nself.mtype = mtype\nself.warnings = warnings",
"if dictionary is None:\n r... | <|body_start_0|>
self.cloud_deploy_entity_vec = cloud_deploy_entity_vec
self.is_incremental = is_incremental
self.restore_info = restore_info
self.target_type = target_type
self.total_bytes_transferred_to_source = total_bytes_transferred_to_source
self.mtype = mtype
... | Implementation of the 'CloudDeployInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. The extension applies to both CloudDeployInfoProto as well as CloudDeployEntity. CloudDeployInfoProto extension Location Extension ... | CloudDeployInfoProto | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CloudDeployInfoProto:
"""Implementation of the 'CloudDeployInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. The extension applies to both CloudDeployInfoProto as well as CloudDeployEntity. Cl... | stack_v2_sparse_classes_36k_train_032453 | 6,086 | permissive | [
{
"docstring": "Constructor for the CloudDeployInfoProto class",
"name": "__init__",
"signature": "def __init__(self, cloud_deploy_entity_vec=None, is_incremental=None, restore_info=None, target_type=None, total_bytes_transferred_to_source=None, mtype=None, warnings=None)"
},
{
"docstring": "Cre... | 2 | null | Implement the Python class `CloudDeployInfoProto` described below.
Class description:
Implementation of the 'CloudDeployInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. The extension applies to both CloudDeployInf... | Implement the Python class `CloudDeployInfoProto` described below.
Class description:
Implementation of the 'CloudDeployInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. The extension applies to both CloudDeployInf... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CloudDeployInfoProto:
"""Implementation of the 'CloudDeployInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. The extension applies to both CloudDeployInfoProto as well as CloudDeployEntity. Cl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CloudDeployInfoProto:
"""Implementation of the 'CloudDeployInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. The extension applies to both CloudDeployInfoProto as well as CloudDeployEntity. CloudDeployInfo... | the_stack_v2_python_sparse | cohesity_management_sdk/models/cloud_deploy_info_proto.py | cohesity/management-sdk-python | train | 24 |
6bdf2d645cedbc94e6663e4c736aa60bc558bb8c | [
"self.checkpoint_dir = os.getcwd()\nif checkpoint_dir is not None:\n self.checkpoint_dir = checkpoint_dir\nself.name = '{}.pth.tar'\nself.latest = 'last'\nself.best = 'best'\nself.logger = Logger.get()",
"if not os.path.isdir(self.checkpoint_dir):\n msg = 'Checkpoint Directory does not exist! Making directo... | <|body_start_0|>
self.checkpoint_dir = os.getcwd()
if checkpoint_dir is not None:
self.checkpoint_dir = checkpoint_dir
self.name = '{}.pth.tar'
self.latest = 'last'
self.best = 'best'
self.logger = Logger.get()
<|end_body_0|>
<|body_start_1|>
if not o... | Save/load the model and optimizer parameters. | Serialization | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Serialization:
"""Save/load the model and optimizer parameters."""
def __init__(self, checkpoint_dir=None):
"""Args: checkpoint_dir (path): the directory of checkpoint files."""
<|body_0|>
def serialize(self, model, epoch, optimizer=None, checkpoint='last', is_best=False... | stack_v2_sparse_classes_36k_train_032454 | 16,358 | no_license | [
{
"docstring": "Args: checkpoint_dir (path): the directory of checkpoint files.",
"name": "__init__",
"signature": "def __init__(self, checkpoint_dir=None)"
},
{
"docstring": "Save model, optimizer and other parameters to file. Args: epoch (int): the epoch of training. checkpoint (str): the name... | 3 | stack_v2_sparse_classes_30k_train_008214 | Implement the Python class `Serialization` described below.
Class description:
Save/load the model and optimizer parameters.
Method signatures and docstrings:
- def __init__(self, checkpoint_dir=None): Args: checkpoint_dir (path): the directory of checkpoint files.
- def serialize(self, model, epoch, optimizer=None, ... | Implement the Python class `Serialization` described below.
Class description:
Save/load the model and optimizer parameters.
Method signatures and docstrings:
- def __init__(self, checkpoint_dir=None): Args: checkpoint_dir (path): the directory of checkpoint files.
- def serialize(self, model, epoch, optimizer=None, ... | e953a54cd4599cfbfad11f88de7b354239cb558c | <|skeleton|>
class Serialization:
"""Save/load the model and optimizer parameters."""
def __init__(self, checkpoint_dir=None):
"""Args: checkpoint_dir (path): the directory of checkpoint files."""
<|body_0|>
def serialize(self, model, epoch, optimizer=None, checkpoint='last', is_best=False... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Serialization:
"""Save/load the model and optimizer parameters."""
def __init__(self, checkpoint_dir=None):
"""Args: checkpoint_dir (path): the directory of checkpoint files."""
self.checkpoint_dir = os.getcwd()
if checkpoint_dir is not None:
self.checkpoint_dir = chec... | the_stack_v2_python_sparse | pytorch_startup/utils.py | wikty/MachineLearningExamples | train | 0 |
9f2f7bdbe644fc84c68066666508221cd7e6e9bc | [
"super().__init__(**kwargs)\nself.conv1 = keras.layers.Conv2D(16, 3, padding='same', activation='relu')\nself.maxpool1 = keras.layers.MaxPool2D(pool_size=(2, 2), strides=2)\nself.conv2 = keras.layers.Conv2D(8, 3, padding='same', activation='relu')\nself.maxpool2 = keras.layers.MaxPool2D(pool_size=(2, 2), strides=2)... | <|body_start_0|>
super().__init__(**kwargs)
self.conv1 = keras.layers.Conv2D(16, 3, padding='same', activation='relu')
self.maxpool1 = keras.layers.MaxPool2D(pool_size=(2, 2), strides=2)
self.conv2 = keras.layers.Conv2D(8, 3, padding='same', activation='relu')
self.maxpool2 = ker... | MNIST encoder used in the experiments for the Counterfactual with Reinforcement Learning. The model consists of 3 convolutional layers having 16, 8 and 8 channels and a kernel size of 3, with ReLU nonlinearities. Each convolutional layer is followed by a maxpooling layer of size 2. Finally, a fully connected layer foll... | MNISTEncoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MNISTEncoder:
"""MNIST encoder used in the experiments for the Counterfactual with Reinforcement Learning. The model consists of 3 convolutional layers having 16, 8 and 8 channels and a kernel size of 3, with ReLU nonlinearities. Each convolutional layer is followed by a maxpooling layer of size ... | stack_v2_sparse_classes_36k_train_032455 | 8,692 | permissive | [
{
"docstring": "Constructor. Parameters ---------- latent_dim Latent dimension.",
"name": "__init__",
"signature": "def __init__(self, latent_dim: int, **kwargs) -> None"
},
{
"docstring": "Forward pass. Parameters ---------- x Input tensor. **kwargs Other arguments. Not used. Returns ------- En... | 2 | null | Implement the Python class `MNISTEncoder` described below.
Class description:
MNIST encoder used in the experiments for the Counterfactual with Reinforcement Learning. The model consists of 3 convolutional layers having 16, 8 and 8 channels and a kernel size of 3, with ReLU nonlinearities. Each convolutional layer is ... | Implement the Python class `MNISTEncoder` described below.
Class description:
MNIST encoder used in the experiments for the Counterfactual with Reinforcement Learning. The model consists of 3 convolutional layers having 16, 8 and 8 channels and a kernel size of 3, with ReLU nonlinearities. Each convolutional layer is ... | 54d0c957fb01c7ebba4e2a0d28fcbde52d9c6718 | <|skeleton|>
class MNISTEncoder:
"""MNIST encoder used in the experiments for the Counterfactual with Reinforcement Learning. The model consists of 3 convolutional layers having 16, 8 and 8 channels and a kernel size of 3, with ReLU nonlinearities. Each convolutional layer is followed by a maxpooling layer of size ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MNISTEncoder:
"""MNIST encoder used in the experiments for the Counterfactual with Reinforcement Learning. The model consists of 3 convolutional layers having 16, 8 and 8 channels and a kernel size of 3, with ReLU nonlinearities. Each convolutional layer is followed by a maxpooling layer of size 2. Finally, a... | the_stack_v2_python_sparse | alibi/models/tensorflow/cfrl_models.py | SeldonIO/alibi | train | 2,143 |
59d39fdcc2b24b90dceb996c889af5de25eb65da | [
"\"\"\"\n Thoughts:\n 这个方法没有left和right子树为None的情况进行对比会出现问题.\n \"\"\"\nif not self.isEqualNode(root1, root2):\n return False\nif not self.isEqualNode(root1.left, root2.left):\n root1.left, root1.right = (root1.right, root1.left)\nreturn self.flipEquiv(root1.left, root2.left) and self.flipEq... | <|body_start_0|>
"""
Thoughts:
这个方法没有left和right子树为None的情况进行对比会出现问题.
"""
if not self.isEqualNode(root1, root2):
return False
if not self.isEqualNode(root1.left, root2.left):
root1.left, root1.right = (root1.right, root1.left)... | Solution_1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_1:
def flipEquiv(self, root1, root2):
""":type root1: TreeNode :type root2: TreeNode :rtype: bool"""
<|body_0|>
def isEqualNode(self, root1, root2):
"""return True if root1.val == root2.val"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
""... | stack_v2_sparse_classes_36k_train_032456 | 3,565 | no_license | [
{
"docstring": ":type root1: TreeNode :type root2: TreeNode :rtype: bool",
"name": "flipEquiv",
"signature": "def flipEquiv(self, root1, root2)"
},
{
"docstring": "return True if root1.val == root2.val",
"name": "isEqualNode",
"signature": "def isEqualNode(self, root1, root2)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000843 | Implement the Python class `Solution_1` described below.
Class description:
Implement the Solution_1 class.
Method signatures and docstrings:
- def flipEquiv(self, root1, root2): :type root1: TreeNode :type root2: TreeNode :rtype: bool
- def isEqualNode(self, root1, root2): return True if root1.val == root2.val | Implement the Python class `Solution_1` described below.
Class description:
Implement the Solution_1 class.
Method signatures and docstrings:
- def flipEquiv(self, root1, root2): :type root1: TreeNode :type root2: TreeNode :rtype: bool
- def isEqualNode(self, root1, root2): return True if root1.val == root2.val
<|sk... | f96a2273c6831a8035e1adacfa452f73c599ae16 | <|skeleton|>
class Solution_1:
def flipEquiv(self, root1, root2):
""":type root1: TreeNode :type root2: TreeNode :rtype: bool"""
<|body_0|>
def isEqualNode(self, root1, root2):
"""return True if root1.val == root2.val"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution_1:
def flipEquiv(self, root1, root2):
""":type root1: TreeNode :type root2: TreeNode :rtype: bool"""
"""
Thoughts:
这个方法没有left和right子树为None的情况进行对比会出现问题.
"""
if not self.isEqualNode(root1, root2):
return False
i... | the_stack_v2_python_sparse | Python/FlipEquivalentBinaryTrees.py | here0009/LeetCode | train | 1 | |
d44b0d52e4cfa37e936664595b8a13b265f96a6a | [
"queue = deque([(n, 0)])\nvisited = set()\nwhile queue:\n num, step = queue.popleft()\n remains = [num - n * n for n in range(1, int(num ** 0.5) + 1)]\n for i in remains:\n if i == 0:\n return step + 1\n if i not in visited:\n queue.append((i, step + 1))\n vis... | <|body_start_0|>
queue = deque([(n, 0)])
visited = set()
while queue:
num, step = queue.popleft()
remains = [num - n * n for n in range(1, int(num ** 0.5) + 1)]
for i in remains:
if i == 0:
return step + 1
if... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def num_squares(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def num_squares_2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
queue = deque([(n, 0)])
visited = set()
while queue... | stack_v2_sparse_classes_36k_train_032457 | 1,571 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "num_squares",
"signature": "def num_squares(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "num_squares_2",
"signature": "def num_squares_2(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011736 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def num_squares(self, n): :type n: int :rtype: int
- def num_squares_2(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 num_squares(self, n): :type n: int :rtype: int
- def num_squares_2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def num_squares(self, n):
"""... | cc7740026c3774be21ab924b99ae7596ef20d0e4 | <|skeleton|>
class Solution:
def num_squares(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def num_squares_2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def num_squares(self, n):
""":type n: int :rtype: int"""
queue = deque([(n, 0)])
visited = set()
while queue:
num, step = queue.popleft()
remains = [num - n * n for n in range(1, int(num ** 0.5) + 1)]
for i in remains:
... | the_stack_v2_python_sparse | data_structure/queues_and_stacks/279_num_squares.py | yangtao0304/hands-on-programming-exercise | train | 0 | |
c6e1b2e3f9b1b14f4881ee9baa0e1999835e5ac2 | [
"units = Unit('hour')\nwidth = 5\nweights_instance = ChooseDefaultWeightsTriangular(width, units=units)\nexpected_width = 5\nexpected_unit = units\nself.assertEqual(weights_instance.width, expected_width)\nself.assertEqual(weights_instance.parameters_units, expected_unit)",
"units = 'hour'\nwidth = 5\nweights_ins... | <|body_start_0|>
units = Unit('hour')
width = 5
weights_instance = ChooseDefaultWeightsTriangular(width, units=units)
expected_width = 5
expected_unit = units
self.assertEqual(weights_instance.width, expected_width)
self.assertEqual(weights_instance.parameters_uni... | Tests for the __init__ method in ChooseDefaultWeightsTriangular class | Test___init__ | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test___init__:
"""Tests for the __init__ method in ChooseDefaultWeightsTriangular class"""
def test_cf_unit_input(self):
"""Test the case where an instance of cf_units.Unit is passed in"""
<|body_0|>
def test_string_input(self):
"""Test the case where a string is... | stack_v2_sparse_classes_36k_train_032458 | 13,166 | permissive | [
{
"docstring": "Test the case where an instance of cf_units.Unit is passed in",
"name": "test_cf_unit_input",
"signature": "def test_cf_unit_input(self)"
},
{
"docstring": "Test the case where a string is passed and gets converted to a Unit instance",
"name": "test_string_input",
"signat... | 2 | stack_v2_sparse_classes_30k_train_012378 | Implement the Python class `Test___init__` described below.
Class description:
Tests for the __init__ method in ChooseDefaultWeightsTriangular class
Method signatures and docstrings:
- def test_cf_unit_input(self): Test the case where an instance of cf_units.Unit is passed in
- def test_string_input(self): Test the c... | Implement the Python class `Test___init__` described below.
Class description:
Tests for the __init__ method in ChooseDefaultWeightsTriangular class
Method signatures and docstrings:
- def test_cf_unit_input(self): Test the case where an instance of cf_units.Unit is passed in
- def test_string_input(self): Test the c... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test___init__:
"""Tests for the __init__ method in ChooseDefaultWeightsTriangular class"""
def test_cf_unit_input(self):
"""Test the case where an instance of cf_units.Unit is passed in"""
<|body_0|>
def test_string_input(self):
"""Test the case where a string is... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test___init__:
"""Tests for the __init__ method in ChooseDefaultWeightsTriangular class"""
def test_cf_unit_input(self):
"""Test the case where an instance of cf_units.Unit is passed in"""
units = Unit('hour')
width = 5
weights_instance = ChooseDefaultWeightsTriangular(wid... | the_stack_v2_python_sparse | improver_tests/blending/weights/test_ChooseDefaultWeightsTriangular.py | metoppv/improver | train | 101 |
57c8d89c5fe7d7cc1b22dfa42621f5973c49d526 | [
"if len(input) == 0:\n return input\nrecord = []\nfor i in range(len(input)):\n record.append([(0, '')] * len(input))\nfor i in range(len(input)):\n record[i][i] = (1, input[i])\nfor c in range(2, len(input) + 1):\n for i in range(len(input) - c + 1):\n j = i + c - 1\n if input[i] == input... | <|body_start_0|>
if len(input) == 0:
return input
record = []
for i in range(len(input)):
record.append([(0, '')] * len(input))
for i in range(len(input)):
record[i][i] = (1, input[i])
for c in range(2, len(input) + 1):
for i in ran... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, input):
"""input: string input return: string"""
<|body_0|>
def longestPalindrome_1(self, input):
"""input: string input return: string"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(input) == 0:
... | stack_v2_sparse_classes_36k_train_032459 | 3,919 | no_license | [
{
"docstring": "input: string input return: string",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, input)"
},
{
"docstring": "input: string input return: string",
"name": "longestPalindrome_1",
"signature": "def longestPalindrome_1(self, input)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000896 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, input): input: string input return: string
- def longestPalindrome_1(self, input): input: string input return: string | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, input): input: string input return: string
- def longestPalindrome_1(self, input): input: string input return: string
<|skeleton|>
class Solution:
... | 8d9eb98fa5e897602eae9c37b47fd8abae72b1dc | <|skeleton|>
class Solution:
def longestPalindrome(self, input):
"""input: string input return: string"""
<|body_0|>
def longestPalindrome_1(self, input):
"""input: string input return: string"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome(self, input):
"""input: string input return: string"""
if len(input) == 0:
return input
record = []
for i in range(len(input)):
record.append([(0, '')] * len(input))
for i in range(len(input)):
record[i... | the_stack_v2_python_sparse | dynamic_programming/word_matching/longest_palindromic_subsequence.py | wanlipu/coding-python | train | 0 | |
0253a1abeaa438a51e1fdcc8141b1615475d9bd1 | [
"if isinstance(models, dict):\n included_models = {model: val for model, val in models.items() if model in included_model_types}\n missing_models = set(included_model_types) - set(included_models.keys())\nelif isinstance(models, list):\n included_models = [model for model in models if model in included_mod... | <|body_start_0|>
if isinstance(models, dict):
included_models = {model: val for model, val in models.items() if model in included_model_types}
missing_models = set(included_model_types) - set(included_models.keys())
elif isinstance(models, list):
included_models = [mo... | Class to filter models given user requirements | ModelFilter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelFilter:
"""Class to filter models given user requirements"""
def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]:
"""Only include models specified in `included_model_types`, other models will be remove... | stack_v2_sparse_classes_36k_train_032460 | 4,609 | permissive | [
{
"docstring": "Only include models specified in `included_model_types`, other models will be removed If model specified in `included_model_types` doesn't present in `models`, will warn users and ignore Parameters ---------- models: Union[Dict[str, Any], List[str]] A dictionary containing models and their hyper... | 3 | stack_v2_sparse_classes_30k_train_000699 | Implement the Python class `ModelFilter` described below.
Class description:
Class to filter models given user requirements
Method signatures and docstrings:
- def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]: Only include models specifi... | Implement the Python class `ModelFilter` described below.
Class description:
Class to filter models given user requirements
Method signatures and docstrings:
- def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]: Only include models specifi... | 6af92e149491f6e5062495d87306b3625d12d992 | <|skeleton|>
class ModelFilter:
"""Class to filter models given user requirements"""
def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]:
"""Only include models specified in `included_model_types`, other models will be remove... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelFilter:
"""Class to filter models given user requirements"""
def include_models(models: Union[Dict[str, Any], List[str]], included_model_types: List[str]) -> Union[Dict[str, Any], List[str]]:
"""Only include models specified in `included_model_types`, other models will be removed If model sp... | the_stack_v2_python_sparse | common/src/autogluon/common/model_filter/_model_filter.py | stjordanis/autogluon | train | 0 |
dd8314ef381c9e1a8bb5c306ce3602338178e0f0 | [
"context = super(CollectorCreateView, self).get_context_data(**kwargs)\ncontext['page_title'] = u'Создание нового коллекционера'\nreturn context",
"message = super(CollectorCreateView, self).form_valid(form)\nmes = u'Коллекционер {} {} успешно добавлен.'.format(self.object.name, self.object.surname)\nmessages.suc... | <|body_start_0|>
context = super(CollectorCreateView, self).get_context_data(**kwargs)
context['page_title'] = u'Создание нового коллекционера'
return context
<|end_body_0|>
<|body_start_1|>
message = super(CollectorCreateView, self).form_valid(form)
mes = u'Коллекционер {} {} у... | Add new collector | CollectorCreateView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectorCreateView:
"""Add new collector"""
def get_context_data(self, **kwargs):
"""Extends context data :param kwargs: :return: context"""
<|body_0|>
def form_valid(self, form):
"""The successful addition of new collector :param form: :return: message"""
... | stack_v2_sparse_classes_36k_train_032461 | 4,445 | no_license | [
{
"docstring": "Extends context data :param kwargs: :return: context",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstring": "The successful addition of new collector :param form: :return: message",
"name": "form_valid",
"signature": "def form_... | 2 | stack_v2_sparse_classes_30k_train_006323 | Implement the Python class `CollectorCreateView` described below.
Class description:
Add new collector
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Extends context data :param kwargs: :return: context
- def form_valid(self, form): The successful addition of new collector :param form: :ret... | Implement the Python class `CollectorCreateView` described below.
Class description:
Add new collector
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Extends context data :param kwargs: :return: context
- def form_valid(self, form): The successful addition of new collector :param form: :ret... | 8eb18b831e034302f90585a179110336bb18af45 | <|skeleton|>
class CollectorCreateView:
"""Add new collector"""
def get_context_data(self, **kwargs):
"""Extends context data :param kwargs: :return: context"""
<|body_0|>
def form_valid(self, form):
"""The successful addition of new collector :param form: :return: message"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollectorCreateView:
"""Add new collector"""
def get_context_data(self, **kwargs):
"""Extends context data :param kwargs: :return: context"""
context = super(CollectorCreateView, self).get_context_data(**kwargs)
context['page_title'] = u'Создание нового коллекционера'
retu... | the_stack_v2_python_sparse | collector/views.py | YevheniiaSmyrnova/butterflies | train | 0 |
fb6f485fb920eaac93d34bfdccb8ecab1a99840f | [
"logger.debug('---------- workbench application ----------')\ngui = self.gui\nif self.start():\n window = self.workbench.create_window(position=self.window_position, size=self.window_size)\n window.open()\n self.workbench.on_trait_change(self._on_workbench_exited, 'exited')\n if self.start_gui_event_loo... | <|body_start_0|>
logger.debug('---------- workbench application ----------')
gui = self.gui
if self.start():
window = self.workbench.create_window(position=self.window_position, size=self.window_size)
window.open()
self.workbench.on_trait_change(self._on_workb... | The mayavi application. | MayaviWorkbenchApplication | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MayaviWorkbenchApplication:
"""The mayavi application."""
def run(self):
"""Run the application. This does the following: 1) Starts the application 2) Creates and opens a workbench window 3) Starts the GUI event loop (only if start_gui_event_loop is True) 4) When the event loop termi... | stack_v2_sparse_classes_36k_train_032462 | 4,424 | no_license | [
{
"docstring": "Run the application. This does the following: 1) Starts the application 2) Creates and opens a workbench window 3) Starts the GUI event loop (only if start_gui_event_loop is True) 4) When the event loop terminates, stops the application This particular method is overridden from the parent class ... | 3 | stack_v2_sparse_classes_30k_test_001131 | Implement the Python class `MayaviWorkbenchApplication` described below.
Class description:
The mayavi application.
Method signatures and docstrings:
- def run(self): Run the application. This does the following: 1) Starts the application 2) Creates and opens a workbench window 3) Starts the GUI event loop (only if s... | Implement the Python class `MayaviWorkbenchApplication` described below.
Class description:
The mayavi application.
Method signatures and docstrings:
- def run(self): Run the application. This does the following: 1) Starts the application 2) Creates and opens a workbench window 3) Starts the GUI event loop (only if s... | 5466f5858dbd2f1f082fa0d7417b57c8fb068fad | <|skeleton|>
class MayaviWorkbenchApplication:
"""The mayavi application."""
def run(self):
"""Run the application. This does the following: 1) Starts the application 2) Creates and opens a workbench window 3) Starts the GUI event loop (only if start_gui_event_loop is True) 4) When the event loop termi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MayaviWorkbenchApplication:
"""The mayavi application."""
def run(self):
"""Run the application. This does the following: 1) Starts the application 2) Creates and opens a workbench window 3) Starts the GUI event loop (only if start_gui_event_loop is True) 4) When the event loop terminates, stops ... | the_stack_v2_python_sparse | maps/build/mayavi/enthought/mayavi/plugins/mayavi_workbench_application.py | m-elhussieny/code | train | 0 |
91ff036f6c97b605a72a9b5abf1bbfc31a53e774 | [
"self.em = EventManager('wikidata', url='https://www.wikidata.org/wiki/Wikidata:Main_Page', title='Wikidata', config=config)\nself.debug = self.em.config.debug\nself.profile = self.em.config.profile\npath = os.path.dirname(__file__)\nself.sampledir = path + '/../sampledata/'\nself.sampleFilePath = self.sampledir + ... | <|body_start_0|>
self.em = EventManager('wikidata', url='https://www.wikidata.org/wiki/Wikidata:Main_Page', title='Wikidata', config=config)
self.debug = self.em.config.debug
self.profile = self.em.config.profile
path = os.path.dirname(__file__)
self.sampledir = path + '/../sampl... | WikiData proceedings titles event source | WikiData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WikiData:
"""WikiData proceedings titles event source"""
def __init__(self, config=None):
"""Constructor Args: config(StorageConfig): the storage configuration to use"""
<|body_0|>
def cacheEvents(self, limit=1000000, batchSize=500):
"""initialize me from my samp... | stack_v2_sparse_classes_36k_train_032463 | 2,035 | permissive | [
{
"docstring": "Constructor Args: config(StorageConfig): the storage configuration to use",
"name": "__init__",
"signature": "def __init__(self, config=None)"
},
{
"docstring": "initialize me from my sample file Args: limit(int): the maximum number of events to cache batchSize(int): the batchSiz... | 3 | stack_v2_sparse_classes_30k_train_014375 | Implement the Python class `WikiData` described below.
Class description:
WikiData proceedings titles event source
Method signatures and docstrings:
- def __init__(self, config=None): Constructor Args: config(StorageConfig): the storage configuration to use
- def cacheEvents(self, limit=1000000, batchSize=500): initi... | Implement the Python class `WikiData` described below.
Class description:
WikiData proceedings titles event source
Method signatures and docstrings:
- def __init__(self, config=None): Constructor Args: config(StorageConfig): the storage configuration to use
- def cacheEvents(self, limit=1000000, batchSize=500): initi... | b48832e9032e41785f61338f6ff2f5cac91aba0e | <|skeleton|>
class WikiData:
"""WikiData proceedings titles event source"""
def __init__(self, config=None):
"""Constructor Args: config(StorageConfig): the storage configuration to use"""
<|body_0|>
def cacheEvents(self, limit=1000000, batchSize=500):
"""initialize me from my samp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WikiData:
"""WikiData proceedings titles event source"""
def __init__(self, config=None):
"""Constructor Args: config(StorageConfig): the storage configuration to use"""
self.em = EventManager('wikidata', url='https://www.wikidata.org/wiki/Wikidata:Main_Page', title='Wikidata', config=con... | the_stack_v2_python_sparse | ptp/wikidata.py | MusaabKh/ProceedingsTitleParser | train | 0 |
c1852e0693ae823da489641071957d58601de86a | [
"if 'item' not in orderby_item:\n return 0\nval = orderby_item['item']\nif val is None:\n return 1\nif isinstance(val, bool):\n return 2\nif isinstance(val, numbers.Number):\n return 4\nif isinstance(val, str):\n return 5\nraise TypeError('unknown type' + str(val))",
"if 'item' not in orderby_item:... | <|body_start_0|>
if 'item' not in orderby_item:
return 0
val = orderby_item['item']
if val is None:
return 1
if isinstance(val, bool):
return 2
if isinstance(val, numbers.Number):
return 4
if isinstance(val, str):
... | _OrderByHelper | [
"LicenseRef-scancode-generic-cla",
"MIT",
"LGPL-2.1-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _OrderByHelper:
def getTypeOrd(orderby_item):
"""Returns the ordinal of the value of the item pair in the dictionary. :param dict orderby_item: :return: 0 if the item_pair doesn't have any 'item' key 1 if the value is undefined 2 if the value is a boolean 4 if the value is a number 5 if ... | stack_v2_sparse_classes_36k_train_032464 | 9,259 | permissive | [
{
"docstring": "Returns the ordinal of the value of the item pair in the dictionary. :param dict orderby_item: :return: 0 if the item_pair doesn't have any 'item' key 1 if the value is undefined 2 if the value is a boolean 4 if the value is a number 5 if the value is a str or a unicode :rtype: int",
"name":... | 3 | null | Implement the Python class `_OrderByHelper` described below.
Class description:
Implement the _OrderByHelper class.
Method signatures and docstrings:
- def getTypeOrd(orderby_item): Returns the ordinal of the value of the item pair in the dictionary. :param dict orderby_item: :return: 0 if the item_pair doesn't have ... | Implement the Python class `_OrderByHelper` described below.
Class description:
Implement the _OrderByHelper class.
Method signatures and docstrings:
- def getTypeOrd(orderby_item): Returns the ordinal of the value of the item pair in the dictionary. :param dict orderby_item: :return: 0 if the item_pair doesn't have ... | c2ca191e736bb06bfbbbc9493e8325763ba990bb | <|skeleton|>
class _OrderByHelper:
def getTypeOrd(orderby_item):
"""Returns the ordinal of the value of the item pair in the dictionary. :param dict orderby_item: :return: 0 if the item_pair doesn't have any 'item' key 1 if the value is undefined 2 if the value is a boolean 4 if the value is a number 5 if ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _OrderByHelper:
def getTypeOrd(orderby_item):
"""Returns the ordinal of the value of the item pair in the dictionary. :param dict orderby_item: :return: 0 if the item_pair doesn't have any 'item' key 1 if the value is undefined 2 if the value is a boolean 4 if the value is a number 5 if the value is a... | the_stack_v2_python_sparse | sdk/cosmos/azure-cosmos/azure/cosmos/_execution_context/document_producer.py | Azure/azure-sdk-for-python | train | 4,046 | |
aa2ef6e8768916126ed2582c667b7a46e6f53866 | [
"@mb.program(input_specs=[mb.TensorSpec(shape=(1, 3, 20))])\ndef prog(x):\n y1 = mb.relu(x=x, name='var_1!')\n y2 = mb.relu(x=x, name='1')\n z = mb.add(x=y1, y=y2, name='3')\n return z\nPASS_REGISTRY['mil_backend::sanitize_name_strings'](prog)\nblock = prog.functions['main']\nassert block.find_ops(op_ty... | <|body_start_0|>
@mb.program(input_specs=[mb.TensorSpec(shape=(1, 3, 20))])
def prog(x):
y1 = mb.relu(x=x, name='var_1!')
y2 = mb.relu(x=x, name='1')
z = mb.add(x=y1, y=y2, name='3')
return z
PASS_REGISTRY['mil_backend::sanitize_name_strings'](prog... | TestSanitizerPass | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSanitizerPass:
def test_sanitize_numeric_var_names(self):
"""Input: main(%x: (1, 3, 20, fp32)(Tensor)) { block0() { %var_1!: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name="var_1!") %1: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name="1") %3: (1, 3, 20, fp32)(Tensor) = add(x=%Var_1!, y=%1, na... | stack_v2_sparse_classes_36k_train_032465 | 39,733 | permissive | [
{
"docstring": "Input: main(%x: (1, 3, 20, fp32)(Tensor)) { block0() { %var_1!: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name=\"var_1!\") %1: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name=\"1\") %3: (1, 3, 20, fp32)(Tensor) = add(x=%Var_1!, y=%1, name=\"3\") } -> (%3) } Output: main(%x: (1, 3, 20, fp32)(Tensor)) { bl... | 2 | null | Implement the Python class `TestSanitizerPass` described below.
Class description:
Implement the TestSanitizerPass class.
Method signatures and docstrings:
- def test_sanitize_numeric_var_names(self): Input: main(%x: (1, 3, 20, fp32)(Tensor)) { block0() { %var_1!: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name="var_1!") ... | Implement the Python class `TestSanitizerPass` described below.
Class description:
Implement the TestSanitizerPass class.
Method signatures and docstrings:
- def test_sanitize_numeric_var_names(self): Input: main(%x: (1, 3, 20, fp32)(Tensor)) { block0() { %var_1!: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name="var_1!") ... | feed174188f7773631a3d574e1ff9889a135c986 | <|skeleton|>
class TestSanitizerPass:
def test_sanitize_numeric_var_names(self):
"""Input: main(%x: (1, 3, 20, fp32)(Tensor)) { block0() { %var_1!: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name="var_1!") %1: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name="1") %3: (1, 3, 20, fp32)(Tensor) = add(x=%Var_1!, y=%1, na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSanitizerPass:
def test_sanitize_numeric_var_names(self):
"""Input: main(%x: (1, 3, 20, fp32)(Tensor)) { block0() { %var_1!: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name="var_1!") %1: (1, 3, 20, fp32)(Tensor) = relu(x=%x, name="1") %3: (1, 3, 20, fp32)(Tensor) = add(x=%Var_1!, y=%1, name="3") } -> (... | the_stack_v2_python_sparse | coremltools/converters/mil/backend/mil/passes/test_passes.py | apple/coremltools | train | 3,742 | |
31062ba2f3aa096bc585542d03bf620894f72ab7 | [
"self.first_name = first_name\nself.last_name = last_name\nself.salary = salary",
"if bonus:\n self.salary += bonus\nelse:\n self.salary += 5000"
] | <|body_start_0|>
self.first_name = first_name
self.last_name = last_name
self.salary = salary
<|end_body_0|>
<|body_start_1|>
if bonus:
self.salary += bonus
else:
self.salary += 5000
<|end_body_1|>
| Object representing an employee and salary | Employee | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Employee:
"""Object representing an employee and salary"""
def __init__(self, first_name, last_name, salary):
"""Initialize employee attributes"""
<|body_0|>
def give_raise(self, bonus=''):
"""Method to give raise (bonus) to employee. $5000 is the default amount.... | stack_v2_sparse_classes_36k_train_032466 | 698 | no_license | [
{
"docstring": "Initialize employee attributes",
"name": "__init__",
"signature": "def __init__(self, first_name, last_name, salary)"
},
{
"docstring": "Method to give raise (bonus) to employee. $5000 is the default amount.",
"name": "give_raise",
"signature": "def give_raise(self, bonus... | 2 | null | Implement the Python class `Employee` described below.
Class description:
Object representing an employee and salary
Method signatures and docstrings:
- def __init__(self, first_name, last_name, salary): Initialize employee attributes
- def give_raise(self, bonus=''): Method to give raise (bonus) to employee. $5000 i... | Implement the Python class `Employee` described below.
Class description:
Object representing an employee and salary
Method signatures and docstrings:
- def __init__(self, first_name, last_name, salary): Initialize employee attributes
- def give_raise(self, bonus=''): Method to give raise (bonus) to employee. $5000 i... | b93c3cd5e1c1b91079db2281137a8451f2566885 | <|skeleton|>
class Employee:
"""Object representing an employee and salary"""
def __init__(self, first_name, last_name, salary):
"""Initialize employee attributes"""
<|body_0|>
def give_raise(self, bonus=''):
"""Method to give raise (bonus) to employee. $5000 is the default amount.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Employee:
"""Object representing an employee and salary"""
def __init__(self, first_name, last_name, salary):
"""Initialize employee attributes"""
self.first_name = first_name
self.last_name = last_name
self.salary = salary
def give_raise(self, bonus=''):
"""M... | the_stack_v2_python_sparse | Crash Course/ch11-Testing/employee.py | jpc0016/Python-Examples | train | 1 |
188fc91b52a6cdb507ba49a92c0f02a82571c728 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Session()",
"from ..entity import Entity\nfrom .endpoint import Endpoint\nfrom .failure_info import FailureInfo\nfrom .modality import Modality\nfrom .segment import Segment\nfrom ..entity import Entity\nfrom .endpoint import Endpoint\... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Session()
<|end_body_0|>
<|body_start_1|>
from ..entity import Entity
from .endpoint import Endpoint
from .failure_info import FailureInfo
from .modality import Modality
... | Session | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Session:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Session:
"""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: Session"""... | stack_v2_sparse_classes_36k_train_032467 | 4,761 | 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: Session",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse... | 3 | null | Implement the Python class `Session` described below.
Class description:
Implement the Session class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Session: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | Implement the Python class `Session` described below.
Class description:
Implement the Session class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Session: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Session:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Session:
"""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: Session"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Session:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Session:
"""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: Session"""
if no... | the_stack_v2_python_sparse | msgraph/generated/models/call_records/session.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
ac61d3b27baf2259e82640fc1992ec1f645d82be | [
"self.cache = {}\nself.capacity = capacity\nself.i = 0",
"if key not in self.cache:\n return -1\nself.i += 1\nself.cache[key] = (self.cache[key][0], self.i)\nreturn self.cache[key][0]",
"if key not in self.cache and len(self.cache) >= self.capacity:\n minValue = sys.maxint\n for i in self.cache:\n ... | <|body_start_0|>
self.cache = {}
self.capacity = capacity
self.i = 0
<|end_body_0|>
<|body_start_1|>
if key not in self.cache:
return -1
self.i += 1
self.cache[key] = (self.cache[key][0], self.i)
return self.cache[key][0]
<|end_body_1|>
<|body_start_... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_032468 | 1,532 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: void",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void
<|sk... | 5f4bde4c1799b0c2c29e9d790fe720d5ba691c75 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.cache = {}
self.capacity = capacity
self.i = 0
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.cache:
return -1
self.i += 1
self.cache... | the_stack_v2_python_sparse | Interview-Questions.py | Darthpwner/Tech-Company-Interviews | train | 1 | |
1222c2257264acc5977f5b45d0e10973917a5c8b | [
"m = len(word1)\nn = len(word2)\nif m == 0:\n return n\nif n == 0:\n return m\nif word1 == word2:\n return 0\ndp = []\nfor i in range(m + 1):\n dp.append([0] * (n + 1))\ndp[0][0] = 0\nfor i in range(m + 1):\n dp[i][0] = i\nfor j in range(n + 1):\n dp[0][j] = j\nfor i in range(1, m + 1):\n for j... | <|body_start_0|>
m = len(word1)
n = len(word2)
if m == 0:
return n
if n == 0:
return m
if word1 == word2:
return 0
dp = []
for i in range(m + 1):
dp.append([0] * (n + 1))
dp[0][0] = 0
for i in range(m... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDistance_3op(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_0|>
def minDistance(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
def minimumDeleteSum(self, word1, word2)... | stack_v2_sparse_classes_36k_train_032469 | 2,559 | no_license | [
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "minDistance_3op",
"signature": "def minDistance_3op(self, word1, word2)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "minDistance",
"signature": "def minDistance(self, word1, word2)"
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance_3op(self, word1, word2): :type word1: str :type word2: str :rtype: int
- def minDistance(self, word1, word2): :type word1: str :type word2: str :rtype: int
- def ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance_3op(self, word1, word2): :type word1: str :type word2: str :rtype: int
- def minDistance(self, word1, word2): :type word1: str :type word2: str :rtype: int
- def ... | 176cc1db3291843fb068f06d0180766dd8c3122c | <|skeleton|>
class Solution:
def minDistance_3op(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_0|>
def minDistance(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
def minimumDeleteSum(self, word1, word2)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minDistance_3op(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
m = len(word1)
n = len(word2)
if m == 0:
return n
if n == 0:
return m
if word1 == word2:
return 0
dp = []
f... | the_stack_v2_python_sparse | 2019/dynamic_programming/edit_distance_72.py | yehongyu/acode | train | 0 | |
fb63a824c4bf5f1ab1b465f2c9269fa7ccd1568c | [
"need, missing = (collections.Counter(t), len(t))\ncur_left = res_left = res_right = 0\nfor cur_right, c in enumerate(s, 1):\n missing -= need[c] > 0\n need[c] -= 1\n if not missing:\n while cur_left < cur_right and need[s[cur_left]] < 0:\n need[s[cur_left]] += 1\n cur_left += ... | <|body_start_0|>
need, missing = (collections.Counter(t), len(t))
cur_left = res_left = res_right = 0
for cur_right, c in enumerate(s, 1):
missing -= need[c] > 0
need[c] -= 1
if not missing:
while cur_left < cur_right and need[s[cur_left]] < 0:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str current window is s[cur_left:cur_right] and the result window is s[res_left:res_right]. In need[c] I store how many times I need character c (can be negative) and missing tells how many characters are still mis... | stack_v2_sparse_classes_36k_train_032470 | 2,478 | no_license | [
{
"docstring": ":type s: str :type t: str :rtype: str current window is s[cur_left:cur_right] and the result window is s[res_left:res_right]. In need[c] I store how many times I need character c (can be negative) and missing tells how many characters are still missing. In the loop, first add the new character t... | 2 | stack_v2_sparse_classes_30k_train_018296 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minWindow(self, s, t): :type s: str :type t: str :rtype: str current window is s[cur_left:cur_right] and the result window is s[res_left:res_right]. In need[c] I store how ma... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minWindow(self, s, t): :type s: str :type t: str :rtype: str current window is s[cur_left:cur_right] and the result window is s[res_left:res_right]. In need[c] I store how ma... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str current window is s[cur_left:cur_right] and the result window is s[res_left:res_right]. In need[c] I store how many times I need character c (can be negative) and missing tells how many characters are still mis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minWindow(self, s, t):
""":type s: str :type t: str :rtype: str current window is s[cur_left:cur_right] and the result window is s[res_left:res_right]. In need[c] I store how many times I need character c (can be negative) and missing tells how many characters are still missing. In the l... | the_stack_v2_python_sparse | LeetCode/076_minimum_window_substring.py | yao23/Machine_Learning_Playground | train | 12 | |
e40dfe8842447f0b300d65d0d3bba224bc86ff73 | [
"from collections import defaultdict\nd = defaultdict(list)\n\ndef f(r, i):\n if r:\n d[i].append(r.val)\n f(r.left, i + 1)\n f(r.right, i + 1)\nf(root, 0)\nreturn [i for i in d.values()]",
"if not root:\n return []\nfrom collections import deque\nres = []\nq = deque()\nq.append(root)\n... | <|body_start_0|>
from collections import defaultdict
d = defaultdict(list)
def f(r, i):
if r:
d[i].append(r.val)
f(r.left, i + 1)
f(r.right, i + 1)
f(root, 0)
return [i for i in d.values()]
<|end_body_0|>
<|body_start_... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]] 1, 先把树转换成list(前序遍历) 2，再根据切片层序遍历"""
<|body_0|>
def levelOrder1(self, root):
""":param root: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from collectio... | stack_v2_sparse_classes_36k_train_032471 | 1,556 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[List[int]] 1, 先把树转换成list(前序遍历) 2，再根据切片层序遍历",
"name": "levelOrder",
"signature": "def levelOrder(self, root)"
},
{
"docstring": ":param root: :return:",
"name": "levelOrder1",
"signature": "def levelOrder1(self, root)"
}
] | 2 | null | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def levelOrder(self, root): :type root: TreeNode :rtype: List[List[int]] 1, 先把树转换成list(前序遍历) 2，再根据切片层序遍历
- def levelOrder1(self, root): :param root: :return: | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def levelOrder(self, root): :type root: TreeNode :rtype: List[List[int]] 1, 先把树转换成list(前序遍历) 2，再根据切片层序遍历
- def levelOrder1(self, root): :param root: :return:
<|skeleton|>
clas... | a3a1556abc5adb9325de54d64f9814e64b96db0f | <|skeleton|>
class Solution1:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]] 1, 先把树转换成list(前序遍历) 2，再根据切片层序遍历"""
<|body_0|>
def levelOrder1(self, root):
""":param root: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution1:
def levelOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]] 1, 先把树转换成list(前序遍历) 2，再根据切片层序遍历"""
from collections import defaultdict
d = defaultdict(list)
def f(r, i):
if r:
d[i].append(r.val)
f(r.left, i + 1... | the_stack_v2_python_sparse | leetcode/tree/*levelOrder.py | BigerWANG/geek_algorithm | train | 0 | |
2d2338edd7a7fa8e2c78baf903a06864fb9ab742 | [
"self.serie = Series(serie_path)\nself.serie.get_instances_ordered()\nself.serie_data = self.serie.get_series_details()\nself.instance_uid_serie = self.serie.get_all_SOPInstanceIUD()\nself.matrix_size = self.serie.get_size_matrix()\nself.instances = self.serie.get_instances_ordered()\nself.image_position = self.ins... | <|body_start_0|>
self.serie = Series(serie_path)
self.serie.get_instances_ordered()
self.serie_data = self.serie.get_series_details()
self.instance_uid_serie = self.serie.get_all_SOPInstanceIUD()
self.matrix_size = self.serie.get_size_matrix()
self.instances = self.serie.... | a class to build an ndarray mask from a RTSS File | MaskBuilder_RTSS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaskBuilder_RTSS:
"""a class to build an ndarray mask from a RTSS File"""
def __init__(self, rtss_path: str, serie_path: str):
"""constructor Args: rtss_path (str): [file path of RTSTRUCT dicom file] serie_path (str): [directory path of associated serie]"""
<|body_0|>
de... | stack_v2_sparse_classes_36k_train_032472 | 5,496 | permissive | [
{
"docstring": "constructor Args: rtss_path (str): [file path of RTSTRUCT dicom file] serie_path (str): [directory path of associated serie]",
"name": "__init__",
"signature": "def __init__(self, rtss_path: str, serie_path: str)"
},
{
"docstring": "check if every SOPInstanceUID from RTSTRUCT cor... | 6 | stack_v2_sparse_classes_30k_train_010378 | Implement the Python class `MaskBuilder_RTSS` described below.
Class description:
a class to build an ndarray mask from a RTSS File
Method signatures and docstrings:
- def __init__(self, rtss_path: str, serie_path: str): constructor Args: rtss_path (str): [file path of RTSTRUCT dicom file] serie_path (str): [director... | Implement the Python class `MaskBuilder_RTSS` described below.
Class description:
a class to build an ndarray mask from a RTSS File
Method signatures and docstrings:
- def __init__(self, rtss_path: str, serie_path: str): constructor Args: rtss_path (str): [file path of RTSTRUCT dicom file] serie_path (str): [director... | 56619b47877ad912d7fe33616d6596ce542705bb | <|skeleton|>
class MaskBuilder_RTSS:
"""a class to build an ndarray mask from a RTSS File"""
def __init__(self, rtss_path: str, serie_path: str):
"""constructor Args: rtss_path (str): [file path of RTSTRUCT dicom file] serie_path (str): [directory path of associated serie]"""
<|body_0|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MaskBuilder_RTSS:
"""a class to build an ndarray mask from a RTSS File"""
def __init__(self, rtss_path: str, serie_path: str):
"""constructor Args: rtss_path (str): [file path of RTSTRUCT dicom file] serie_path (str): [directory path of associated serie]"""
self.serie = Series(serie_path)... | the_stack_v2_python_sparse | dicom_to_cnn/model/segmentation/MaskBuilder_RTSS.py | wendyrvllr/Dicom-To-CNN | train | 0 |
1e4f57fd43102995def013c4e353cc922058582b | [
"super(BIM, self).__init__(model, device)\nself.device = device\nself.eps = eps\nself.loss = CrossEntropyLoss()\nself.itr_numbers = itr_numbers",
"xs = xs.to(self.device)\nperturbtion = torch.zeros(xs.shape).to(self.device)\nxs.requires_grad = True\nfor i in range(self.itr_numbers):\n output = self.model_forwa... | <|body_start_0|>
super(BIM, self).__init__(model, device)
self.device = device
self.eps = eps
self.loss = CrossEntropyLoss()
self.itr_numbers = itr_numbers
<|end_body_0|>
<|body_start_1|>
xs = xs.to(self.device)
perturbtion = torch.zeros(xs.shape).to(self.device)... | BIM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BIM:
def __init__(self, model, device, eps=0.001, itr_numbers=20):
"""Initializing the BIM class. Args: model: victim model device: torch.device eps: float, epsilon itr_numbers: int, iteration number"""
<|body_0|>
def attack(self, xs: torch.tensor, ys: torch.tensor):
... | stack_v2_sparse_classes_36k_train_032473 | 2,821 | permissive | [
{
"docstring": "Initializing the BIM class. Args: model: victim model device: torch.device eps: float, epsilon itr_numbers: int, iteration number",
"name": "__init__",
"signature": "def __init__(self, model, device, eps=0.001, itr_numbers=20)"
},
{
"docstring": "Attacking the victim model by add... | 2 | stack_v2_sparse_classes_30k_train_007624 | Implement the Python class `BIM` described below.
Class description:
Implement the BIM class.
Method signatures and docstrings:
- def __init__(self, model, device, eps=0.001, itr_numbers=20): Initializing the BIM class. Args: model: victim model device: torch.device eps: float, epsilon itr_numbers: int, iteration num... | Implement the Python class `BIM` described below.
Class description:
Implement the BIM class.
Method signatures and docstrings:
- def __init__(self, model, device, eps=0.001, itr_numbers=20): Initializing the BIM class. Args: model: victim model device: torch.device eps: float, epsilon itr_numbers: int, iteration num... | 3230044473614d2dd931d96cbd6a3bc974eff926 | <|skeleton|>
class BIM:
def __init__(self, model, device, eps=0.001, itr_numbers=20):
"""Initializing the BIM class. Args: model: victim model device: torch.device eps: float, epsilon itr_numbers: int, iteration number"""
<|body_0|>
def attack(self, xs: torch.tensor, ys: torch.tensor):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BIM:
def __init__(self, model, device, eps=0.001, itr_numbers=20):
"""Initializing the BIM class. Args: model: victim model device: torch.device eps: float, epsilon itr_numbers: int, iteration number"""
super(BIM, self).__init__(model, device)
self.device = device
self.eps = ep... | the_stack_v2_python_sparse | advt/attack/bim.py | WindFantasy98/ADVT | train | 0 | |
27fd62b1419ea6cbed06f69608b3a50473f808aa | [
"for func in reversed(self.mime_func):\n codename = func(mime)\n if codename is not None:\n return codename",
"assert mime is not None or cls is not None\nif mime is not None:\n cls = self.factories[self.get_type(mime)]\nreturn super(MIMETemplateLoader, self).load(path, cls=cls, relative_to=relati... | <|body_start_0|>
for func in reversed(self.mime_func):
codename = func(mime)
if codename is not None:
return codename
<|end_body_0|>
<|body_start_1|>
assert mime is not None or cls is not None
if mime is not None:
cls = self.factories[self.get... | This subclass of TemplateLoader use mimetypes to search and find templates to load. | MIMETemplateLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MIMETemplateLoader:
"""This subclass of TemplateLoader use mimetypes to search and find templates to load."""
def get_type(self, mime):
"""finds the codename used by relatorio to work on a mimetype"""
<|body_0|>
def load(self, path, mime=None, relative_to=None, cls=None)... | stack_v2_sparse_classes_36k_train_032474 | 5,592 | no_license | [
{
"docstring": "finds the codename used by relatorio to work on a mimetype",
"name": "get_type",
"signature": "def get_type(self, mime)"
},
{
"docstring": "returns a template object based on path",
"name": "load",
"signature": "def load(self, path, mime=None, relative_to=None, cls=None)"... | 3 | null | Implement the Python class `MIMETemplateLoader` described below.
Class description:
This subclass of TemplateLoader use mimetypes to search and find templates to load.
Method signatures and docstrings:
- def get_type(self, mime): finds the codename used by relatorio to work on a mimetype
- def load(self, path, mime=N... | Implement the Python class `MIMETemplateLoader` described below.
Class description:
This subclass of TemplateLoader use mimetypes to search and find templates to load.
Method signatures and docstrings:
- def get_type(self, mime): finds the codename used by relatorio to work on a mimetype
- def load(self, path, mime=N... | 8d1ec4f2b623f7ca48f38bfda2ac15c01ded35a7 | <|skeleton|>
class MIMETemplateLoader:
"""This subclass of TemplateLoader use mimetypes to search and find templates to load."""
def get_type(self, mime):
"""finds the codename used by relatorio to work on a mimetype"""
<|body_0|>
def load(self, path, mime=None, relative_to=None, cls=None)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MIMETemplateLoader:
"""This subclass of TemplateLoader use mimetypes to search and find templates to load."""
def get_type(self, mime):
"""finds the codename used by relatorio to work on a mimetype"""
for func in reversed(self.mime_func):
codename = func(mime)
if c... | the_stack_v2_python_sparse | lib/python3.8/site-packages/relatorio/reporting.py | Davidoff2103/tryton-training | train | 0 |
21f000f7acfefa0825b51beab94c8f125ac32994 | [
"parser = argparse.ArgumentParser(description='momilp instance generator app')\nparser.add_argument('-c', '--configuration', help='sets the path to the configuration json file')\nparser.add_argument('-s', '--solver-package', choices=[SolverPackage.GUROBI.value], help='sets the solver package to use')\nparser.add_ar... | <|body_start_0|>
parser = argparse.ArgumentParser(description='momilp instance generator app')
parser.add_argument('-c', '--configuration', help='sets the path to the configuration json file')
parser.add_argument('-s', '--solver-package', choices=[SolverPackage.GUROBI.value], help='sets the solv... | Implements the command line application for the momilp instance generation | InstanceGeneratorApp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceGeneratorApp:
"""Implements the command line application for the momilp instance generation"""
def _parse_args(self):
"""Parses and returns the arguments"""
<|body_0|>
def run(self):
"""Runs the command line application NOTE: Instance generation supports ... | stack_v2_sparse_classes_36k_train_032475 | 2,101 | permissive | [
{
"docstring": "Parses and returns the arguments",
"name": "_parse_args",
"signature": "def _parse_args(self)"
},
{
"docstring": "Runs the command line application NOTE: Instance generation supports only Gurobi solver currently.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004123 | Implement the Python class `InstanceGeneratorApp` described below.
Class description:
Implements the command line application for the momilp instance generation
Method signatures and docstrings:
- def _parse_args(self): Parses and returns the arguments
- def run(self): Runs the command line application NOTE: Instance... | Implement the Python class `InstanceGeneratorApp` described below.
Class description:
Implements the command line application for the momilp instance generation
Method signatures and docstrings:
- def _parse_args(self): Parses and returns the arguments
- def run(self): Runs the command line application NOTE: Instance... | 465ea7aaa62157411f9f181b994f4d7e6b8a2e33 | <|skeleton|>
class InstanceGeneratorApp:
"""Implements the command line application for the momilp instance generation"""
def _parse_args(self):
"""Parses and returns the arguments"""
<|body_0|>
def run(self):
"""Runs the command line application NOTE: Instance generation supports ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstanceGeneratorApp:
"""Implements the command line application for the momilp instance generation"""
def _parse_args(self):
"""Parses and returns the arguments"""
parser = argparse.ArgumentParser(description='momilp instance generator app')
parser.add_argument('-c', '--configura... | the_stack_v2_python_sparse | src/instance_generator/executor.py | gokhanceyhan/momilp | train | 2 |
cd492b56420513be826ae2ecc5b739ba9a262bc3 | [
"re = cloudparking_service(centerMonitorLogin).mockCarInOut(send_data['carNum'], 0, send_data['inClientID'])\nresult = re\nAssertions().assert_in_text(result, expect['mockCarInMsg'])",
"re = CarInOutHandle(centerMonitorLogin).adjustCarNum(send_data['carNum'], send_data['correctCarNum'])\nresult = re\nAssertions()... | <|body_start_0|>
re = cloudparking_service(centerMonitorLogin).mockCarInOut(send_data['carNum'], 0, send_data['inClientID'])
result = re
Assertions().assert_in_text(result, expect['mockCarInMsg'])
<|end_body_0|>
<|body_start_1|>
re = CarInOutHandle(centerMonitorLogin).adjustCarNum(send_... | TestDutyRoomAdjustCarNum | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDutyRoomAdjustCarNum:
def test_mockCarIn(self, centerMonitorLogin, send_data, expect):
"""模拟车辆进场"""
<|body_0|>
def test_dutyRoomAdjustCarNum(self, centerMonitorLogin, send_data, expect):
"""校正车牌"""
<|body_1|>
def test_dutyRoomCheckCarIn(self, centerM... | stack_v2_sparse_classes_36k_train_032476 | 2,059 | no_license | [
{
"docstring": "模拟车辆进场",
"name": "test_mockCarIn",
"signature": "def test_mockCarIn(self, centerMonitorLogin, send_data, expect)"
},
{
"docstring": "校正车牌",
"name": "test_dutyRoomAdjustCarNum",
"signature": "def test_dutyRoomAdjustCarNum(self, centerMonitorLogin, send_data, expect)"
},
... | 4 | null | Implement the Python class `TestDutyRoomAdjustCarNum` described below.
Class description:
Implement the TestDutyRoomAdjustCarNum class.
Method signatures and docstrings:
- def test_mockCarIn(self, centerMonitorLogin, send_data, expect): 模拟车辆进场
- def test_dutyRoomAdjustCarNum(self, centerMonitorLogin, send_data, expec... | Implement the Python class `TestDutyRoomAdjustCarNum` described below.
Class description:
Implement the TestDutyRoomAdjustCarNum class.
Method signatures and docstrings:
- def test_mockCarIn(self, centerMonitorLogin, send_data, expect): 模拟车辆进场
- def test_dutyRoomAdjustCarNum(self, centerMonitorLogin, send_data, expec... | 34c368c109867da26d9256bca85f872b0fac2ea7 | <|skeleton|>
class TestDutyRoomAdjustCarNum:
def test_mockCarIn(self, centerMonitorLogin, send_data, expect):
"""模拟车辆进场"""
<|body_0|>
def test_dutyRoomAdjustCarNum(self, centerMonitorLogin, send_data, expect):
"""校正车牌"""
<|body_1|>
def test_dutyRoomCheckCarIn(self, centerM... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDutyRoomAdjustCarNum:
def test_mockCarIn(self, centerMonitorLogin, send_data, expect):
"""模拟车辆进场"""
re = cloudparking_service(centerMonitorLogin).mockCarInOut(send_data['carNum'], 0, send_data['inClientID'])
result = re
Assertions().assert_in_text(result, expect['mockCarInM... | the_stack_v2_python_sparse | test_suite/centerMonitorRoom/carInOutHandle/test_dutyRoomAdjustCarNum.py | oyebino/pomp_api | train | 1 | |
11b033f2ebdcae13a257011d04eed5461f13c4be | [
"connection.use_debug_cursor = True\nself.start = time()\nreturn None",
"self.queries = len(connection.queries)\nself.elapsed = time() - self.start\nself.db_time = reduce(add, [float(q['time']) for q in connection.queries]) if connection.queries else 0.0\nself.py_time = self.elapsed - self.db_time\nstats = {'elap... | <|body_start_0|>
connection.use_debug_cursor = True
self.start = time()
return None
<|end_body_0|>
<|body_start_1|>
self.queries = len(connection.queries)
self.elapsed = time() - self.start
self.db_time = reduce(add, [float(q['time']) for q in connection.queries]) if con... | Middleware de statistiques de performance de la page | PageStatsMiddleware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PageStatsMiddleware:
"""Middleware de statistiques de performance de la page"""
def process_request(self, request):
"""Traiter la requête"""
<|body_0|>
def process_response(self, request, response):
"""Traiter la réponse"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_032477 | 6,111 | no_license | [
{
"docstring": "Traiter la requête",
"name": "process_request",
"signature": "def process_request(self, request)"
},
{
"docstring": "Traiter la réponse",
"name": "process_response",
"signature": "def process_response(self, request, response)"
}
] | 2 | null | Implement the Python class `PageStatsMiddleware` described below.
Class description:
Middleware de statistiques de performance de la page
Method signatures and docstrings:
- def process_request(self, request): Traiter la requête
- def process_response(self, request, response): Traiter la réponse | Implement the Python class `PageStatsMiddleware` described below.
Class description:
Middleware de statistiques de performance de la page
Method signatures and docstrings:
- def process_request(self, request): Traiter la requête
- def process_response(self, request, response): Traiter la réponse
<|skeleton|>
class P... | 8cef6f6e89c1990e2b25f83e54e0c3481d83b6d7 | <|skeleton|>
class PageStatsMiddleware:
"""Middleware de statistiques de performance de la page"""
def process_request(self, request):
"""Traiter la requête"""
<|body_0|>
def process_response(self, request, response):
"""Traiter la réponse"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PageStatsMiddleware:
"""Middleware de statistiques de performance de la page"""
def process_request(self, request):
"""Traiter la requête"""
connection.use_debug_cursor = True
self.start = time()
return None
def process_response(self, request, response):
"""Tr... | the_stack_v2_python_sparse | scoop/core/middleware/profiling.py | artscoop/scoop | train | 0 |
18e19da44ef0e582dbc8b515f87ad6baac224937 | [
"qs = Q()\nfilter_params = self.get_filter()\nif 'q' in filter_params:\n qs.add(Q(log__contains=filter_params['q']), Q.OR)\n ps.add(Q(params__contains=filter_params['q']), Q.OR)\nreturn Batch.objects.filter(qs).distinct().order_by(self.get_sort())",
"serializer.save()\nbatch_id = serializer['id'].value\nif ... | <|body_start_0|>
qs = Q()
filter_params = self.get_filter()
if 'q' in filter_params:
qs.add(Q(log__contains=filter_params['q']), Q.OR)
ps.add(Q(params__contains=filter_params['q']), Q.OR)
return Batch.objects.filter(qs).distinct().order_by(self.get_sort())
<|end_b... | BatchViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BatchViewSet:
def get_queryset(self):
"""define queryset"""
<|body_0|>
def perform_create(self, serializer):
"""save queue"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
qs = Q()
filter_params = self.get_filter()
if 'q' in filter_pa... | stack_v2_sparse_classes_36k_train_032478 | 1,629 | no_license | [
{
"docstring": "define queryset",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "save queue",
"name": "perform_create",
"signature": "def perform_create(self, serializer)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017575 | Implement the Python class `BatchViewSet` described below.
Class description:
Implement the BatchViewSet class.
Method signatures and docstrings:
- def get_queryset(self): define queryset
- def perform_create(self, serializer): save queue | Implement the Python class `BatchViewSet` described below.
Class description:
Implement the BatchViewSet class.
Method signatures and docstrings:
- def get_queryset(self): define queryset
- def perform_create(self, serializer): save queue
<|skeleton|>
class BatchViewSet:
def get_queryset(self):
"""defin... | db7b1c75183d8dd9f5e8ee6751b1c44641413c6c | <|skeleton|>
class BatchViewSet:
def get_queryset(self):
"""define queryset"""
<|body_0|>
def perform_create(self, serializer):
"""save queue"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BatchViewSet:
def get_queryset(self):
"""define queryset"""
qs = Q()
filter_params = self.get_filter()
if 'q' in filter_params:
qs.add(Q(log__contains=filter_params['q']), Q.OR)
ps.add(Q(params__contains=filter_params['q']), Q.OR)
return Batch.ob... | the_stack_v2_python_sparse | dashboard/tools/api/batches.py | fuxlab/datafrontend | train | 0 | |
7cdf23278627b02ade640e880f7d7d53818f3bed | [
"self._fixed_length_left = fixed_length_left\nself._fixed_length_right = fixed_length_right\nself._pad_word_value = pad_word_value\nself._pad_word_mode = pad_word_mode\nself._with_ngram = with_ngram\nself._fixed_ngram_length = fixed_ngram_length\nself._pad_ngram_value = pad_ngram_value\nself._pad_ngram_mode = pad_n... | <|body_start_0|>
self._fixed_length_left = fixed_length_left
self._fixed_length_right = fixed_length_right
self._pad_word_value = pad_word_value
self._pad_word_mode = pad_word_mode
self._with_ngram = with_ngram
self._fixed_ngram_length = fixed_ngram_length
self._p... | Pad data for basic preprocessor. :param fixed_length_left: Integer. If set, `text_left` will be padded to this length. :param fixed_length_right: Integer. If set, `text_right` will be padded to this length. :param pad_word_value: the value to fill text. :param pad_word_mode: String, `pre` or `post`: pad either before o... | BasicPadding | [
"MIT",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-proprietary-license",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference",
"LGPL-2.1-or-later",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicPadding:
"""Pad data for basic preprocessor. :param fixed_length_left: Integer. If set, `text_left` will be padded to this length. :param fixed_length_right: Integer. If set, `text_right` will be padded to this length. :param pad_word_value: the value to fill text. :param pad_word_mode: Stri... | stack_v2_sparse_classes_36k_train_032479 | 10,301 | permissive | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, fixed_length_left: int=None, fixed_length_right: int=None, pad_word_value: typing.Union[int, str]=0, pad_word_mode: str='pre', with_ngram: bool=False, fixed_ngram_length: int=None, pad_ngram_value: typing.Union[int, str]=0, pad... | 2 | stack_v2_sparse_classes_30k_test_000087 | Implement the Python class `BasicPadding` described below.
Class description:
Pad data for basic preprocessor. :param fixed_length_left: Integer. If set, `text_left` will be padded to this length. :param fixed_length_right: Integer. If set, `text_right` will be padded to this length. :param pad_word_value: the value t... | Implement the Python class `BasicPadding` described below.
Class description:
Pad data for basic preprocessor. :param fixed_length_left: Integer. If set, `text_left` will be padded to this length. :param fixed_length_right: Integer. If set, `text_right` will be padded to this length. :param pad_word_value: the value t... | 4198ebce942f4afe7ddca6a96ab6f4464ade4518 | <|skeleton|>
class BasicPadding:
"""Pad data for basic preprocessor. :param fixed_length_left: Integer. If set, `text_left` will be padded to this length. :param fixed_length_right: Integer. If set, `text_right` will be padded to this length. :param pad_word_value: the value to fill text. :param pad_word_mode: Stri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicPadding:
"""Pad data for basic preprocessor. :param fixed_length_left: Integer. If set, `text_left` will be padded to this length. :param fixed_length_right: Integer. If set, `text_right` will be padded to this length. :param pad_word_value: the value to fill text. :param pad_word_mode: String, `pre` or ... | the_stack_v2_python_sparse | poset_decoding/traversal_path_prediction/MatchZoo-py/matchzoo/dataloader/callbacks/padding.py | microsoft/ContextualSP | train | 332 |
e359c8709e051819e0c74870248b4176aee02446 | [
"self.http_headers = http_headers\nself.request_id = request_id\nself.arguments = arguments\nself.errors = errors\nself.request_processing_time = request_processing_time",
"if dictionary is None:\n return None\nhttp_headers = awsecommerceservice.models.http_headers.HTTPHeaders.from_dictionary(dictionary.get('H... | <|body_start_0|>
self.http_headers = http_headers
self.request_id = request_id
self.arguments = arguments
self.errors = errors
self.request_processing_time = request_processing_time
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
ht... | Implementation of the 'OperationRequest' model. TODO: type model description here. Attributes: http_headers (HTTPHeaders): TODO: type description here. request_id (string): TODO: type description here. arguments (Arguments): TODO: type description here. errors (Errors): TODO: type description here. request_processing_t... | OperationRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OperationRequest:
"""Implementation of the 'OperationRequest' model. TODO: type model description here. Attributes: http_headers (HTTPHeaders): TODO: type description here. request_id (string): TODO: type description here. arguments (Arguments): TODO: type description here. errors (Errors): TODO:... | stack_v2_sparse_classes_36k_train_032480 | 2,898 | permissive | [
{
"docstring": "Constructor for the OperationRequest class",
"name": "__init__",
"signature": "def __init__(self, http_headers=None, request_id=None, arguments=None, errors=None, request_processing_time=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionar... | 2 | stack_v2_sparse_classes_30k_train_005043 | Implement the Python class `OperationRequest` described below.
Class description:
Implementation of the 'OperationRequest' model. TODO: type model description here. Attributes: http_headers (HTTPHeaders): TODO: type description here. request_id (string): TODO: type description here. arguments (Arguments): TODO: type d... | Implement the Python class `OperationRequest` described below.
Class description:
Implementation of the 'OperationRequest' model. TODO: type model description here. Attributes: http_headers (HTTPHeaders): TODO: type description here. request_id (string): TODO: type description here. arguments (Arguments): TODO: type d... | 26ea1019115a1de3b1b37a4b830525e164ac55ce | <|skeleton|>
class OperationRequest:
"""Implementation of the 'OperationRequest' model. TODO: type model description here. Attributes: http_headers (HTTPHeaders): TODO: type description here. request_id (string): TODO: type description here. arguments (Arguments): TODO: type description here. errors (Errors): TODO:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OperationRequest:
"""Implementation of the 'OperationRequest' model. TODO: type model description here. Attributes: http_headers (HTTPHeaders): TODO: type description here. request_id (string): TODO: type description here. arguments (Arguments): TODO: type description here. errors (Errors): TODO: type descrip... | the_stack_v2_python_sparse | awsecommerceservice/models/operation_request.py | nidaizamir/Test-PY | train | 0 |
b453a731f1d44a7e4ab25f462a729959e6262f6a | [
"pool = Pool()\namount = 0\ncomputerloan = pool.get('computer.loan')\ncomputer_loan = computerloan.search([('employee', '=', employee), ('salary_code', '=', employee.salary_code), ('state', '=', 'approve')])\nprint(computer_loan, 'computer_loan')\nif computer_loan:\n for loan in computer_loan:\n mydate = ... | <|body_start_0|>
pool = Pool()
amount = 0
computerloan = pool.get('computer.loan')
computer_loan = computerloan.search([('employee', '=', employee), ('salary_code', '=', employee.salary_code), ('state', '=', 'approve')])
print(computer_loan, 'computer_loan')
if computer_l... | SalaryRule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SalaryRule:
def calculate_COM_Loan(self, payslip, employee, contract):
"""Calcualte this method for computer loan"""
<|body_0|>
def calculate_HBA_Loan(self, payslip, employee, contract):
"""Calcualte this method for HBA Loan"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_032481 | 4,077 | no_license | [
{
"docstring": "Calcualte this method for computer loan",
"name": "calculate_COM_Loan",
"signature": "def calculate_COM_Loan(self, payslip, employee, contract)"
},
{
"docstring": "Calcualte this method for HBA Loan",
"name": "calculate_HBA_Loan",
"signature": "def calculate_HBA_Loan(self... | 2 | stack_v2_sparse_classes_30k_train_021121 | Implement the Python class `SalaryRule` described below.
Class description:
Implement the SalaryRule class.
Method signatures and docstrings:
- def calculate_COM_Loan(self, payslip, employee, contract): Calcualte this method for computer loan
- def calculate_HBA_Loan(self, payslip, employee, contract): Calcualte this... | Implement the Python class `SalaryRule` described below.
Class description:
Implement the SalaryRule class.
Method signatures and docstrings:
- def calculate_COM_Loan(self, payslip, employee, contract): Calcualte this method for computer loan
- def calculate_HBA_Loan(self, payslip, employee, contract): Calcualte this... | cd392bf0e80d71c4742568e9c1dd5e5211da56a9 | <|skeleton|>
class SalaryRule:
def calculate_COM_Loan(self, payslip, employee, contract):
"""Calcualte this method for computer loan"""
<|body_0|>
def calculate_HBA_Loan(self, payslip, employee, contract):
"""Calcualte this method for HBA Loan"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SalaryRule:
def calculate_COM_Loan(self, payslip, employee, contract):
"""Calcualte this method for computer loan"""
pool = Pool()
amount = 0
computerloan = pool.get('computer.loan')
computer_loan = computerloan.search([('employee', '=', employee), ('salary_code', '=', ... | the_stack_v2_python_sparse | src/modules/customised/payroll_test_2/payroll_copy/hr_payroll_loan/hr_payroll_loan.py | kakamble-aiims/work | train | 0 | |
e56b1cf13574e362df8cd5785b9816c1507793f6 | [
"log_as_info('\\nToggleNoteDirective.run')\nif len(self.arguments) > 0:\n toggle_start = self.arguments[0]\nelse:\n toggle_start = 'expanded'\nif len(self.arguments) > 1:\n extra_title_text = self.arguments[1]\nelse:\n extra_title_text = ''\nself.assert_has_content()\ntext = '\\n'.join(self.content)\nno... | <|body_start_0|>
log_as_info('\nToggleNoteDirective.run')
if len(self.arguments) > 0:
toggle_start = self.arguments[0]
else:
toggle_start = 'expanded'
if len(self.arguments) > 1:
extra_title_text = self.arguments[1]
else:
extra_titl... | Implements a note directive that allows the content of the note to be collapsed by the browser user. Usage: .\\. astutus_toggle_note:: [ expanded|collapsed [extra_title_text]] indented block of text for note ... If the first argument is omitted, it defaults to expanded. If extra_title_text is to be provided, the author... | ToggleNoteDirective | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ToggleNoteDirective:
"""Implements a note directive that allows the content of the note to be collapsed by the browser user. Usage: .\\. astutus_toggle_note:: [ expanded|collapsed [extra_title_text]] indented block of text for note ... If the first argument is omitted, it defaults to expanded. If... | stack_v2_sparse_classes_36k_train_032482 | 16,710 | permissive | [
{
"docstring": "Parses the directive when encountered in a \\\\*.rst file. At the time this method is called, the arguments, options, and content for the directive have been store in initializing the directive object. This method returns a list containing any nodes to be inserted into the Docutils document. For... | 2 | stack_v2_sparse_classes_30k_train_011649 | Implement the Python class `ToggleNoteDirective` described below.
Class description:
Implements a note directive that allows the content of the note to be collapsed by the browser user. Usage: .\\. astutus_toggle_note:: [ expanded|collapsed [extra_title_text]] indented block of text for note ... If the first argument ... | Implement the Python class `ToggleNoteDirective` described below.
Class description:
Implements a note directive that allows the content of the note to be collapsed by the browser user. Usage: .\\. astutus_toggle_note:: [ expanded|collapsed [extra_title_text]] indented block of text for note ... If the first argument ... | 46a11295394093de3a23cb8dec1e2e76eac752e8 | <|skeleton|>
class ToggleNoteDirective:
"""Implements a note directive that allows the content of the note to be collapsed by the browser user. Usage: .\\. astutus_toggle_note:: [ expanded|collapsed [extra_title_text]] indented block of text for note ... If the first argument is omitted, it defaults to expanded. If... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ToggleNoteDirective:
"""Implements a note directive that allows the content of the note to be collapsed by the browser user. Usage: .\\. astutus_toggle_note:: [ expanded|collapsed [extra_title_text]] indented block of text for note ... If the first argument is omitted, it defaults to expanded. If extra_title_... | the_stack_v2_python_sparse | src/astutus/sphinx/dyn_pages.py | rich-dobbs-13440/astutus | train | 0 |
c76fba554f512659a11a840dc3882b22a4bd8eef | [
"sizes = list(input.size())\nsizes[0] = total_batch_size\noutput = input.new_zeros(*sizes)\noutput.index_copy_(0, non_pad_indices, input)\nctx.save_for_backward(non_pad_indices)\nreturn output",
"non_pad_indices, = ctx.saved_tensors\ngrad_input = output_grads.index_select(0, non_pad_indices)\nreturn (grad_input, ... | <|body_start_0|>
sizes = list(input.size())
sizes[0] = total_batch_size
output = input.new_zeros(*sizes)
output.index_copy_(0, non_pad_indices, input)
ctx.save_for_backward(non_pad_indices)
return output
<|end_body_0|>
<|body_start_1|>
non_pad_indices, = ctx.save... | This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor | IndexCopy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexCopy:
"""This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor"""
def forward(ctx, input, non_pad_indices, total_batch_size):
""":param ctx: :param input: 2D [bsz x ... ] bsz is the total number of elements ... | stack_v2_sparse_classes_36k_train_032483 | 45,662 | permissive | [
{
"docstring": ":param ctx: :param input: 2D [bsz x ... ] bsz is the total number of elements after unpadding :param non_pad_indices: bsz * seq_len :param total_batch_size: (int) bsz * seq_len (before unpadding) > bsz :return: In the forward pass we create a new zero tensor and copy the inputs into it based on ... | 2 | stack_v2_sparse_classes_30k_train_001958 | Implement the Python class `IndexCopy` described below.
Class description:
This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor
Method signatures and docstrings:
- def forward(ctx, input, non_pad_indices, total_batch_size): :param ctx: :param in... | Implement the Python class `IndexCopy` described below.
Class description:
This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor
Method signatures and docstrings:
- def forward(ctx, input, non_pad_indices, total_batch_size): :param ctx: :param in... | 5e1e424d0d9c2135a456e372a2ea9ee49de5bd2c | <|skeleton|>
class IndexCopy:
"""This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor"""
def forward(ctx, input, non_pad_indices, total_batch_size):
""":param ctx: :param input: 2D [bsz x ... ] bsz is the total number of elements ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IndexCopy:
"""This function is kinda similar to rnn pad_packed_sequence It remaps nonpadded values for a (N-1)-d tensor into a (N)-d tensor"""
def forward(ctx, input, non_pad_indices, total_batch_size):
""":param ctx: :param input: 2D [bsz x ... ] bsz is the total number of elements after unpaddi... | the_stack_v2_python_sparse | pretrain_module/modeling_deltalm.py | quanpn90/NMTGMinor | train | 92 |
0dc33bcbe4149fa732d77d90a76e1ace8da2540c | [
"n = len(A)\nans = 0\nlast_of = -1\nlast_leader = -1\nfor i in xrange(n):\n if A[i] > R:\n if last_leader != -1:\n ans += i - max(last_of, last_leader) - 1\n last_of = i\n elif A[i] >= L:\n last_leader = i\n ans += i - last_of\nreturn ans",
"n = len(A)\nans = 0\nlast_o... | <|body_start_0|>
n = len(A)
ans = 0
last_of = -1
last_leader = -1
for i in xrange(n):
if A[i] > R:
if last_leader != -1:
ans += i - max(last_of, last_leader) - 1
last_of = i
elif A[i] >= L:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numSubarrayBoundedMaxWA(self, A, L, R):
""":type A: List[int] :type L: int :type R: int :rtype: int"""
<|body_0|>
def numSubarrayBoundedMaxWA2(self, A, L, R):
""":type A: List[int] :type L: int :type R: int :rtype: int"""
<|body_1|>
def num... | stack_v2_sparse_classes_36k_train_032484 | 3,047 | no_license | [
{
"docstring": ":type A: List[int] :type L: int :type R: int :rtype: int",
"name": "numSubarrayBoundedMaxWA",
"signature": "def numSubarrayBoundedMaxWA(self, A, L, R)"
},
{
"docstring": ":type A: List[int] :type L: int :type R: int :rtype: int",
"name": "numSubarrayBoundedMaxWA2",
"signa... | 3 | stack_v2_sparse_classes_30k_train_001967 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSubarrayBoundedMaxWA(self, A, L, R): :type A: List[int] :type L: int :type R: int :rtype: int
- def numSubarrayBoundedMaxWA2(self, A, L, R): :type A: List[int] :type L: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSubarrayBoundedMaxWA(self, A, L, R): :type A: List[int] :type L: int :type R: int :rtype: int
- def numSubarrayBoundedMaxWA2(self, A, L, R): :type A: List[int] :type L: in... | 02ebe56cd92b9f4baeee132c5077892590018650 | <|skeleton|>
class Solution:
def numSubarrayBoundedMaxWA(self, A, L, R):
""":type A: List[int] :type L: int :type R: int :rtype: int"""
<|body_0|>
def numSubarrayBoundedMaxWA2(self, A, L, R):
""":type A: List[int] :type L: int :type R: int :rtype: int"""
<|body_1|>
def num... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numSubarrayBoundedMaxWA(self, A, L, R):
""":type A: List[int] :type L: int :type R: int :rtype: int"""
n = len(A)
ans = 0
last_of = -1
last_leader = -1
for i in xrange(n):
if A[i] > R:
if last_leader != -1:
... | the_stack_v2_python_sparse | python/leetcode.795.py | CalvinNeo/LeetCode | train | 3 | |
e661e1b6676516bd4732d842f6b1c93295cf2fac | [
"if self.from_version:\n if LooseVersion(self.from_version) >= LooseVersion(FROM_VERSION_LAYOUTS_CONTAINER):\n error_message, error_code = Errors.invalid_version_in_layout('fromVersion')\n if self.handle_error(error_message, error_code, file_path=self.file_path):\n return False\nreturn T... | <|body_start_0|>
if self.from_version:
if LooseVersion(self.from_version) >= LooseVersion(FROM_VERSION_LAYOUTS_CONTAINER):
error_message, error_code = Errors.invalid_version_in_layout('fromVersion')
if self.handle_error(error_message, error_code, file_path=self.file_p... | LayoutValidator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayoutValidator:
def is_valid_from_version(self) -> bool:
"""Checks if from version field is valid. Returns: bool. True if from version field is valid, else False."""
<|body_0|>
def is_valid_to_version(self) -> bool:
"""Checks if to version field is valid. Returns: b... | stack_v2_sparse_classes_36k_train_032485 | 4,349 | permissive | [
{
"docstring": "Checks if from version field is valid. Returns: bool. True if from version field is valid, else False.",
"name": "is_valid_from_version",
"signature": "def is_valid_from_version(self) -> bool"
},
{
"docstring": "Checks if to version field is valid. Returns: bool. True if to versi... | 2 | stack_v2_sparse_classes_30k_train_020484 | Implement the Python class `LayoutValidator` described below.
Class description:
Implement the LayoutValidator class.
Method signatures and docstrings:
- def is_valid_from_version(self) -> bool: Checks if from version field is valid. Returns: bool. True if from version field is valid, else False.
- def is_valid_to_ve... | Implement the Python class `LayoutValidator` described below.
Class description:
Implement the LayoutValidator class.
Method signatures and docstrings:
- def is_valid_from_version(self) -> bool: Checks if from version field is valid. Returns: bool. True if from version field is valid, else False.
- def is_valid_to_ve... | a17e868e6fc5153f09e7a329801de85aa60cc752 | <|skeleton|>
class LayoutValidator:
def is_valid_from_version(self) -> bool:
"""Checks if from version field is valid. Returns: bool. True if from version field is valid, else False."""
<|body_0|>
def is_valid_to_version(self) -> bool:
"""Checks if to version field is valid. Returns: b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LayoutValidator:
def is_valid_from_version(self) -> bool:
"""Checks if from version field is valid. Returns: bool. True if from version field is valid, else False."""
if self.from_version:
if LooseVersion(self.from_version) >= LooseVersion(FROM_VERSION_LAYOUTS_CONTAINER):
... | the_stack_v2_python_sparse | demisto_sdk/commands/common/hook_validations/layout.py | SukhnandanMalhotra/demisto-sdk | train | 0 | |
ef55ad3316a3e1696397337f832decfe66cee82b | [
"self.k_min = k_min\nself.k_max = k_max\nself.s0 = canonical_scale\nself.lvl0 = canonical_level\nself.eps = eps",
"s = torch.sqrt(cat([boxlist.area() for boxlist in boxlists]))\ntarget_lvls = torch.floor(self.lvl0 + torch.log2(s / self.s0 + self.eps))\ntarget_lvls = torch.clamp(target_lvls, min=self.k_min, max=se... | <|body_start_0|>
self.k_min = k_min
self.k_max = k_max
self.s0 = canonical_scale
self.lvl0 = canonical_level
self.eps = eps
<|end_body_0|>
<|body_start_1|>
s = torch.sqrt(cat([boxlist.area() for boxlist in boxlists]))
target_lvls = torch.floor(self.lvl0 + torch.l... | Determine which FPN level each RoI in a set of RoIs should map to based on the heuristic in the FPN paper. | LevelMapper | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LevelMapper:
"""Determine which FPN level each RoI in a set of RoIs should map to based on the heuristic in the FPN paper."""
def __init__(self, k_min, k_max, canonical_scale=224, canonical_level=4, eps=1e-06):
"""Arguments: k_min (int) k_max (int) canonical_scale (int) canonical_lev... | stack_v2_sparse_classes_36k_train_032486 | 4,534 | permissive | [
{
"docstring": "Arguments: k_min (int) k_max (int) canonical_scale (int) canonical_level (int) eps (float)",
"name": "__init__",
"signature": "def __init__(self, k_min, k_max, canonical_scale=224, canonical_level=4, eps=1e-06)"
},
{
"docstring": "Arguments: boxlists (list[BoxList])",
"name":... | 2 | null | Implement the Python class `LevelMapper` described below.
Class description:
Determine which FPN level each RoI in a set of RoIs should map to based on the heuristic in the FPN paper.
Method signatures and docstrings:
- def __init__(self, k_min, k_max, canonical_scale=224, canonical_level=4, eps=1e-06): Arguments: k_... | Implement the Python class `LevelMapper` described below.
Class description:
Determine which FPN level each RoI in a set of RoIs should map to based on the heuristic in the FPN paper.
Method signatures and docstrings:
- def __init__(self, k_min, k_max, canonical_scale=224, canonical_level=4, eps=1e-06): Arguments: k_... | a5388a45f71a949639b35cc5b990bd130d2d8164 | <|skeleton|>
class LevelMapper:
"""Determine which FPN level each RoI in a set of RoIs should map to based on the heuristic in the FPN paper."""
def __init__(self, k_min, k_max, canonical_scale=224, canonical_level=4, eps=1e-06):
"""Arguments: k_min (int) k_max (int) canonical_scale (int) canonical_lev... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LevelMapper:
"""Determine which FPN level each RoI in a set of RoIs should map to based on the heuristic in the FPN paper."""
def __init__(self, k_min, k_max, canonical_scale=224, canonical_level=4, eps=1e-06):
"""Arguments: k_min (int) k_max (int) canonical_scale (int) canonical_level (int) eps ... | the_stack_v2_python_sparse | PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/modeling/poolers.py | NVIDIA/DeepLearningExamples | train | 11,838 |
7890bd6608237e7cb033978ab263bd06e899f1ba | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('sbrz_nedg', 'sbrz_nedg')\ndb = client.repo\ncollege_coords_collection = db['sbrz_nedg.college_coords']\nhubway_coords_collection = db['sbrz_nedg.hubway']\ncollege_coords = college_coords_collection.find(... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('sbrz_nedg', 'sbrz_nedg')
db = client.repo
college_coords_collection = db['sbrz_nedg.college_coords']
hubway_coords_collection = db['sbrz_n... | unionCollegesHubway | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class unionCollegesHubway:
def execute(trial=False):
"""Retrieve Boston property assessment data set."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in this script... | stack_v2_sparse_classes_36k_train_032487 | 4,029 | no_license | [
{
"docstring": "Retrieve Boston property assessment data set.",
"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 document describing that invocat... | 2 | null | Implement the Python class `unionCollegesHubway` described below.
Class description:
Implement the unionCollegesHubway class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve Boston property assessment data set.
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Creat... | Implement the Python class `unionCollegesHubway` described below.
Class description:
Implement the unionCollegesHubway class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve Boston property assessment data set.
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Creat... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class unionCollegesHubway:
def execute(trial=False):
"""Retrieve Boston property assessment data set."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in this script... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class unionCollegesHubway:
def execute(trial=False):
"""Retrieve Boston property assessment data set."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('sbrz_nedg', 'sbrz_nedg')
db = client.repo
coll... | the_stack_v2_python_sparse | sbrz_nedg/unionCollegesHubway.py | ROODAY/course-2017-fal-proj | train | 3 | |
8dc73142435714548eed0166c7a53a590dd575e0 | [
"used = set()\n\ndef dfs(room_i):\n used.add(room_i)\n for key in rooms[room_i]:\n if key not in used:\n dfs(key)\nl = len(rooms)\ndfs(0)\ns = sum(used)\nif s == l * (l - 1) // 2:\n return True\nreturn False",
"dfs = [0]\nseen = set(dfs)\nwhile dfs:\n i = dfs.pop()\n for j in room... | <|body_start_0|>
used = set()
def dfs(room_i):
used.add(room_i)
for key in rooms[room_i]:
if key not in used:
dfs(key)
l = len(rooms)
dfs(0)
s = sum(used)
if s == l * (l - 1) // 2:
return True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canVisitAllRooms(self, rooms):
""":type rooms: List[List[int]] :rtype: bool 39 ms"""
<|body_0|>
def canVisitAllRooms_1(self, rooms):
"""37ms :param rooms: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
used = set()
d... | stack_v2_sparse_classes_36k_train_032488 | 2,037 | no_license | [
{
"docstring": ":type rooms: List[List[int]] :rtype: bool 39 ms",
"name": "canVisitAllRooms",
"signature": "def canVisitAllRooms(self, rooms)"
},
{
"docstring": "37ms :param rooms: :return:",
"name": "canVisitAllRooms_1",
"signature": "def canVisitAllRooms_1(self, rooms)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canVisitAllRooms(self, rooms): :type rooms: List[List[int]] :rtype: bool 39 ms
- def canVisitAllRooms_1(self, rooms): 37ms :param rooms: :return: | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canVisitAllRooms(self, rooms): :type rooms: List[List[int]] :rtype: bool 39 ms
- def canVisitAllRooms_1(self, rooms): 37ms :param rooms: :return:
<|skeleton|>
class Solution... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def canVisitAllRooms(self, rooms):
""":type rooms: List[List[int]] :rtype: bool 39 ms"""
<|body_0|>
def canVisitAllRooms_1(self, rooms):
"""37ms :param rooms: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canVisitAllRooms(self, rooms):
""":type rooms: List[List[int]] :rtype: bool 39 ms"""
used = set()
def dfs(room_i):
used.add(room_i)
for key in rooms[room_i]:
if key not in used:
dfs(key)
l = len(rooms)
... | the_stack_v2_python_sparse | KeysAndRooms_MID_841.py | 953250587/leetcode-python | train | 2 | |
fca2409a7c596de6c5b4471c7e68430660d1ef7f | [
"super(ConvQNet, self).__init__()\ninput_shape = (3, 7, 7)\nconv_output_dim = 16 * 2 * 2\nvect_state_size = vect_state_size\nself.conv_modules = nn.Sequential(nn.Conv2d(channel_dim, 32, kernel_size=5, stride=1, padding=0), nn.ReLU(), nn.MaxPool2d(kernel_size=5), nn.Conv2d(32, 32, kernel_size=2, stride=1, padding=0)... | <|body_start_0|>
super(ConvQNet, self).__init__()
input_shape = (3, 7, 7)
conv_output_dim = 16 * 2 * 2
vect_state_size = vect_state_size
self.conv_modules = nn.Sequential(nn.Conv2d(channel_dim, 32, kernel_size=5, stride=1, padding=0), nn.ReLU(), nn.MaxPool2d(kernel_size=5), nn.Co... | ConvQNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvQNet:
def __init__(self, channel_dim, action_dim, vect_state_size):
"""Init the Q-Network: Q(s) = r_a. The Q-Net returns the expected reward for all actions at the current time step. :param channel_dim: The number of channel of input. i.e The number of most recent frames stacked toge... | stack_v2_sparse_classes_36k_train_032489 | 2,457 | no_license | [
{
"docstring": "Init the Q-Network: Q(s) = r_a. The Q-Net returns the expected reward for all actions at the current time step. :param channel_dim: The number of channel of input. i.e The number of most recent frames stacked together. :param action_dim: Number of action-values to output, one-to-one corresponden... | 2 | stack_v2_sparse_classes_30k_train_011089 | Implement the Python class `ConvQNet` described below.
Class description:
Implement the ConvQNet class.
Method signatures and docstrings:
- def __init__(self, channel_dim, action_dim, vect_state_size): Init the Q-Network: Q(s) = r_a. The Q-Net returns the expected reward for all actions at the current time step. :par... | Implement the Python class `ConvQNet` described below.
Class description:
Implement the ConvQNet class.
Method signatures and docstrings:
- def __init__(self, channel_dim, action_dim, vect_state_size): Init the Q-Network: Q(s) = r_a. The Q-Net returns the expected reward for all actions at the current time step. :par... | 8296c40c004f908d792ea8a496bcd16227ac81c1 | <|skeleton|>
class ConvQNet:
def __init__(self, channel_dim, action_dim, vect_state_size):
"""Init the Q-Network: Q(s) = r_a. The Q-Net returns the expected reward for all actions at the current time step. :param channel_dim: The number of channel of input. i.e The number of most recent frames stacked toge... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvQNet:
def __init__(self, channel_dim, action_dim, vect_state_size):
"""Init the Q-Network: Q(s) = r_a. The Q-Net returns the expected reward for all actions at the current time step. :param channel_dim: The number of channel of input. i.e The number of most recent frames stacked together. :param a... | the_stack_v2_python_sparse | src/agents/agent_smith_beta/qnet_conv.py | leorychly/SC2-Game-AI | train | 0 | |
268519c40c5ddca2f9bd17416f6b86f28316806a | [
"self.name = name\nself.env = None\nself.reward_fn = get_reward_fn(task_name=task_name, layout_id=layout_id, is_planning=is_planning)\nself.history = []",
"assert self.env.prev_obs_data is not None\nassert self.env.obs_data is not None\nreward, termination = self.reward_fn(self.env.prev_obs_data, self.env.obs_dat... | <|body_start_0|>
self.name = name
self.env = None
self.reward_fn = get_reward_fn(task_name=task_name, layout_id=layout_id, is_planning=is_planning)
self.history = []
<|end_body_0|>
<|body_start_1|>
assert self.env.prev_obs_data is not None
assert self.env.obs_data is not... | Reward function of the pushing tasks. | PushReward | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PushReward:
"""Reward function of the pushing tasks."""
def __init__(self, name, task_name, layout_id, is_planning=False):
"""Initialize."""
<|body_0|>
def get_reward(self):
"""Returns the reward value of the current step."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_032490 | 13,137 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, name, task_name, layout_id, is_planning=False)"
},
{
"docstring": "Returns the reward value of the current step.",
"name": "get_reward",
"signature": "def get_reward(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020271 | Implement the Python class `PushReward` described below.
Class description:
Reward function of the pushing tasks.
Method signatures and docstrings:
- def __init__(self, name, task_name, layout_id, is_planning=False): Initialize.
- def get_reward(self): Returns the reward value of the current step. | Implement the Python class `PushReward` described below.
Class description:
Reward function of the pushing tasks.
Method signatures and docstrings:
- def __init__(self, name, task_name, layout_id, is_planning=False): Initialize.
- def get_reward(self): Returns the reward value of the current step.
<|skeleton|>
class... | c333ce7f1d7b156bedf28c3b09793f5487b6690a | <|skeleton|>
class PushReward:
"""Reward function of the pushing tasks."""
def __init__(self, name, task_name, layout_id, is_planning=False):
"""Initialize."""
<|body_0|>
def get_reward(self):
"""Returns the reward value of the current step."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PushReward:
"""Reward function of the pushing tasks."""
def __init__(self, name, task_name, layout_id, is_planning=False):
"""Initialize."""
self.name = name
self.env = None
self.reward_fn = get_reward_fn(task_name=task_name, layout_id=layout_id, is_planning=is_planning)
... | the_stack_v2_python_sparse | robovat/reward_fns/push_reward.py | UT-Austin-RPL/robovat | train | 7 |
93dfb7f205faacc4290127bb99d058ee0f466153 | [
"gst_data = mongoUtils.index('gst')\nreturn_data = []\nfor gst in gst_data:\n return_data.append(dict(_id=gst['_id']))\nreturn (dumps(return_data), 200)",
"data = mongoUtils.get('gst', uuid)\nif data:\n return (dumps(data), 200)\nelse:\n return ('Not Found', 404)"
] | <|body_start_0|>
gst_data = mongoUtils.index('gst')
return_data = []
for gst in gst_data:
return_data.append(dict(_id=gst['_id']))
return (dumps(return_data), 200)
<|end_body_0|>
<|body_start_1|>
data = mongoUtils.get('gst', uuid)
if data:
return ... | GstView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GstView:
def index(self):
"""Returns a list of GST and their details, used by: `katana gst ls`"""
<|body_0|>
def get(self, uuid):
"""Returns the details of specific GST, used by: `katana gst inspect [uuid]`"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_032491 | 1,388 | permissive | [
{
"docstring": "Returns a list of GST and their details, used by: `katana gst ls`",
"name": "index",
"signature": "def index(self)"
},
{
"docstring": "Returns the details of specific GST, used by: `katana gst inspect [uuid]`",
"name": "get",
"signature": "def get(self, uuid)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000788 | Implement the Python class `GstView` described below.
Class description:
Implement the GstView class.
Method signatures and docstrings:
- def index(self): Returns a list of GST and their details, used by: `katana gst ls`
- def get(self, uuid): Returns the details of specific GST, used by: `katana gst inspect [uuid]` | Implement the Python class `GstView` described below.
Class description:
Implement the GstView class.
Method signatures and docstrings:
- def index(self): Returns a list of GST and their details, used by: `katana gst ls`
- def get(self, uuid): Returns the details of specific GST, used by: `katana gst inspect [uuid]`
... | 2e7a14a41fc85bd7188d71ef9beaf51acc94015c | <|skeleton|>
class GstView:
def index(self):
"""Returns a list of GST and their details, used by: `katana gst ls`"""
<|body_0|>
def get(self, uuid):
"""Returns the details of specific GST, used by: `katana gst inspect [uuid]`"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GstView:
def index(self):
"""Returns a list of GST and their details, used by: `katana gst ls`"""
gst_data = mongoUtils.index('gst')
return_data = []
for gst in gst_data:
return_data.append(dict(_id=gst['_id']))
return (dumps(return_data), 200)
def get(... | the_stack_v2_python_sparse | katana-nbi/katana/api/gst.py | tgogos/katana-slice_manager | train | 0 | |
2ee2a923bcc8c4ec179eacb10bea1f2a437c4314 | [
"args = image_all.parse_args()\nsize = args['size']\npage = args['page']\ncategory = args['category']\npath = os.path.join(Config.STYLE_DIRECTORY, category)\nif not os.path.exists(path):\n style_ids = []\nelse:\n style_ids = os.listdir(path)\ntotal = len(style_ids)\npages = int(total / size)\npage_style_ids =... | <|body_start_0|>
args = image_all.parse_args()
size = args['size']
page = args['page']
category = args['category']
path = os.path.join(Config.STYLE_DIRECTORY, category)
if not os.path.exists(path):
style_ids = []
else:
style_ids = os.listdi... | Styles | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Styles:
def get(self):
"""Returns pageable content image"""
<|body_0|>
def post(self):
"""Creates an image"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = image_all.parse_args()
size = args['size']
page = args['page']
... | stack_v2_sparse_classes_36k_train_032492 | 4,352 | permissive | [
{
"docstring": "Returns pageable content image",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Creates an image",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002995 | Implement the Python class `Styles` described below.
Class description:
Implement the Styles class.
Method signatures and docstrings:
- def get(self): Returns pageable content image
- def post(self): Creates an image | Implement the Python class `Styles` described below.
Class description:
Implement the Styles class.
Method signatures and docstrings:
- def get(self): Returns pageable content image
- def post(self): Creates an image
<|skeleton|>
class Styles:
def get(self):
"""Returns pageable content image"""
... | f3da89887420b4a3907e15f266442048029d36b4 | <|skeleton|>
class Styles:
def get(self):
"""Returns pageable content image"""
<|body_0|>
def post(self):
"""Creates an image"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Styles:
def get(self):
"""Returns pageable content image"""
args = image_all.parse_args()
size = args['size']
page = args['page']
category = args['category']
path = os.path.join(Config.STYLE_DIRECTORY, category)
if not os.path.exists(path):
s... | the_stack_v2_python_sparse | api/styles.py | LuletterSoul/sast_backend | train | 0 | |
68a6ada51916da01cfa504b14c7168c4209b108a | [
"s = Selector(response)\njobs = s.css(self.job_selector)\nfor job in jobs:\n joblink = job.xpath('h2/a/@href').extract_first()\n if not joblink:\n continue\n item = JobItem()\n item['url'] = urljoin(self.root, joblink)\n item['title'] = job.xpath('h2/a/@title').extract_first()\n item['text'... | <|body_start_0|>
s = Selector(response)
jobs = s.css(self.job_selector)
for job in jobs:
joblink = job.xpath('h2/a/@href').extract_first()
if not joblink:
continue
item = JobItem()
item['url'] = urljoin(self.root, joblink)
... | Spider for indeed.com This is a simple site with a single page of jobs, with links to the ads. | IndeedSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndeedSpider:
"""Spider for indeed.com This is a simple site with a single page of jobs, with links to the ads."""
def parse(self, response):
"""Get the joblinks and hand them off."""
<|body_0|>
def parse_job(self, response):
"""Parse a joblink into a JobItem."""... | stack_v2_sparse_classes_36k_train_032493 | 1,990 | no_license | [
{
"docstring": "Get the joblinks and hand them off.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Parse a joblink into a JobItem.",
"name": "parse_job",
"signature": "def parse_job(self, response)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016381 | Implement the Python class `IndeedSpider` described below.
Class description:
Spider for indeed.com This is a simple site with a single page of jobs, with links to the ads.
Method signatures and docstrings:
- def parse(self, response): Get the joblinks and hand them off.
- def parse_job(self, response): Parse a jobli... | Implement the Python class `IndeedSpider` described below.
Class description:
Spider for indeed.com This is a simple site with a single page of jobs, with links to the ads.
Method signatures and docstrings:
- def parse(self, response): Get the joblinks and hand them off.
- def parse_job(self, response): Parse a jobli... | f6a8415d4812d7e52760bff5002b14a748f496ca | <|skeleton|>
class IndeedSpider:
"""Spider for indeed.com This is a simple site with a single page of jobs, with links to the ads."""
def parse(self, response):
"""Get the joblinks and hand them off."""
<|body_0|>
def parse_job(self, response):
"""Parse a joblink into a JobItem."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IndeedSpider:
"""Spider for indeed.com This is a simple site with a single page of jobs, with links to the ads."""
def parse(self, response):
"""Get the joblinks and hand them off."""
s = Selector(response)
jobs = s.css(self.job_selector)
for job in jobs:
jobli... | the_stack_v2_python_sparse | remotor/spiders/indeed.py | rongyj/remotor | train | 0 |
9c9b7fd6797f4b3c2983da347ecf42400b01ef90 | [
"super().__init__()\nself.beta = beta\nself.threshold_input = threshold_input\nself.threshold_target = threshold_target\nself.reduce_fn = reduce_fn\nself.recall = Recall(threshold_input=None, threshold_target=None, dim=dim, reduce_fn=None)\nself.precision = Precision(threshold_input=None, threshold_target=None, dim... | <|body_start_0|>
super().__init__()
self.beta = beta
self.threshold_input = threshold_input
self.threshold_target = threshold_target
self.reduce_fn = reduce_fn
self.recall = Recall(threshold_input=None, threshold_target=None, dim=dim, reduce_fn=None)
self.precisio... | FScore | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FScore:
def __init__(self, threshold_input: Optional[float]=0.5, threshold_target: Optional[float]=0.5, beta: float=1.0, dim: Optional[int]=-1, reduce_fn: Optional[Callable]=torch.mean):
"""FScore metric. (micro). >>> 'FScore = 2 * precision * recall / (recall + precision)' :param thresh... | stack_v2_sparse_classes_36k_train_032494 | 2,150 | permissive | [
{
"docstring": "FScore metric. (micro). >>> 'FScore = 2 * precision * recall / (recall + precision)' :param threshold_input: The threshold value for binarize input vectors. (default: 0.5) :param threshold_target: The threshold value for binarize target vectors. (default: 0.5) :param beta: The beta fscore parame... | 2 | stack_v2_sparse_classes_30k_train_005167 | Implement the Python class `FScore` described below.
Class description:
Implement the FScore class.
Method signatures and docstrings:
- def __init__(self, threshold_input: Optional[float]=0.5, threshold_target: Optional[float]=0.5, beta: float=1.0, dim: Optional[int]=-1, reduce_fn: Optional[Callable]=torch.mean): FSc... | Implement the Python class `FScore` described below.
Class description:
Implement the FScore class.
Method signatures and docstrings:
- def __init__(self, threshold_input: Optional[float]=0.5, threshold_target: Optional[float]=0.5, beta: float=1.0, dim: Optional[int]=-1, reduce_fn: Optional[Callable]=torch.mean): FSc... | 91aa907a3f820e53902578c3d0110fe9a01c88e7 | <|skeleton|>
class FScore:
def __init__(self, threshold_input: Optional[float]=0.5, threshold_target: Optional[float]=0.5, beta: float=1.0, dim: Optional[int]=-1, reduce_fn: Optional[Callable]=torch.mean):
"""FScore metric. (micro). >>> 'FScore = 2 * precision * recall / (recall + precision)' :param thresh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FScore:
def __init__(self, threshold_input: Optional[float]=0.5, threshold_target: Optional[float]=0.5, beta: float=1.0, dim: Optional[int]=-1, reduce_fn: Optional[Callable]=torch.mean):
"""FScore metric. (micro). >>> 'FScore = 2 * precision * recall / (recall + precision)' :param threshold_input: The... | the_stack_v2_python_sparse | mlu/metrics/classification/fscore.py | Labbeti/MLU | train | 2 | |
8901fcce99cdfd94525b3892d9f5d2948c0e33ca | [
"results_per_page = min(max(results_per_page, 1), 50)\nquery = models.Event.query\nif since_id:\n after = first_or_abort(models.Event.query.filter(models.Event.id == since_id), 409)\n query = query.filter(models.Event.cursor > after.cursor)\nelif max_id:\n before = first_or_abort(models.Event.query.filter(... | <|body_start_0|>
results_per_page = min(max(results_per_page, 1), 50)
query = models.Event.query
if since_id:
after = first_or_abort(models.Event.query.filter(models.Event.id == since_id), 409)
query = query.filter(models.Event.cursor > after.cursor)
elif max_id:
... | Events | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Events:
def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None):
"""--- description: Retrieve a collection of event types. parameters: - api_version - results_per_page - in: query name: event_type_slug type: string description: slug of event_type this event c... | stack_v2_sparse_classes_36k_train_032495 | 15,999 | no_license | [
{
"docstring": "--- description: Retrieve a collection of event types. parameters: - api_version - results_per_page - in: query name: event_type_slug type: string description: slug of event_type this event conforms to. - in: query name: since_id type: string format: uuid description: get all events since this e... | 2 | stack_v2_sparse_classes_30k_train_008150 | Implement the Python class `Events` described below.
Class description:
Implement the Events class.
Method signatures and docstrings:
- def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None): --- description: Retrieve a collection of event types. parameters: - api_version - results_per_p... | Implement the Python class `Events` described below.
Class description:
Implement the Events class.
Method signatures and docstrings:
- def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None): --- description: Retrieve a collection of event types. parameters: - api_version - results_per_p... | dbba9f3b292ffef6ea924608fa54237171f0aaeb | <|skeleton|>
class Events:
def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None):
"""--- description: Retrieve a collection of event types. parameters: - api_version - results_per_page - in: query name: event_type_slug type: string description: slug of event_type this event c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Events:
def get(self, results_per_page=50, event_type_slug=None, since_id=None, max_id=None):
"""--- description: Retrieve a collection of event types. parameters: - api_version - results_per_page - in: query name: event_type_slug type: string description: slug of event_type this event conforms to. - ... | the_stack_v2_python_sparse | apis/event/directorofme_event/resources.py | DirectorOfMe/directorof.me | train | 0 | |
07a7f26fcabc5488a5f3907a550fc92af83078ae | [
"with io.open(filename, 'r', encoding='ascii') as file_handle:\n tokens = []\n version = 1\n count = 0\n for count, line in enumerate(file_handle):\n line_tokens = line.split()\n if count == 0:\n if len(line_tokens) > 0 and line_tokens[0] == 'XPARM.XDS':\n version... | <|body_start_0|>
with io.open(filename, 'r', encoding='ascii') as file_handle:
tokens = []
version = 1
count = 0
for count, line in enumerate(file_handle):
line_tokens = line.split()
if count == 0:
if len(line_to... | A class to read the XPARM.XDS/GXPARM.XDS file used in XDS | reader | [
"BSD-3-Clause-LBNL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class reader:
"""A class to read the XPARM.XDS/GXPARM.XDS file used in XDS"""
def find_version(filename):
"""Check the version if the given file is a (G)XPARM.XDS file. If the file contains exactly 11 lines and 42 tokens, it is the old style version 1 file. If the file starts with XPARM.XD... | stack_v2_sparse_classes_36k_train_032496 | 11,104 | permissive | [
{
"docstring": "Check the version if the given file is a (G)XPARM.XDS file. If the file contains exactly 11 lines and 42 tokens, it is the old style version 1 file. If the file starts with XPARM.XDS it is the new style version 2 file. If the file contains segment definitions then it is a version 3 file. Params:... | 5 | stack_v2_sparse_classes_30k_train_002932 | Implement the Python class `reader` described below.
Class description:
A class to read the XPARM.XDS/GXPARM.XDS file used in XDS
Method signatures and docstrings:
- def find_version(filename): Check the version if the given file is a (G)XPARM.XDS file. If the file contains exactly 11 lines and 42 tokens, it is the o... | Implement the Python class `reader` described below.
Class description:
A class to read the XPARM.XDS/GXPARM.XDS file used in XDS
Method signatures and docstrings:
- def find_version(filename): Check the version if the given file is a (G)XPARM.XDS file. If the file contains exactly 11 lines and 42 tokens, it is the o... | 7f4dfb6c873fd560920f697cbfd8a5ff6eed82fa | <|skeleton|>
class reader:
"""A class to read the XPARM.XDS/GXPARM.XDS file used in XDS"""
def find_version(filename):
"""Check the version if the given file is a (G)XPARM.XDS file. If the file contains exactly 11 lines and 42 tokens, it is the old style version 1 file. If the file starts with XPARM.XD... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class reader:
"""A class to read the XPARM.XDS/GXPARM.XDS file used in XDS"""
def find_version(filename):
"""Check the version if the given file is a (G)XPARM.XDS file. If the file contains exactly 11 lines and 42 tokens, it is the old style version 1 file. If the file starts with XPARM.XDS it is the n... | the_stack_v2_python_sparse | iotbx/xds/xparm.py | cctbx/cctbx_project | train | 206 |
03552df16e08dcec3d6d64c3af186a7a63215ab1 | [
"def helper(left, right):\n if left > right:\n return None\n mid = (left + right) // 2\n root = TreeNode(nums[mid])\n root.left = helper(left, mid - 1)\n root.right = helper(mid + 1, right)\n return root\nreturn helper(0, len(nums) - 1)",
"def helper(left, right):\n if left > right:\n ... | <|body_start_0|>
def helper(left, right):
if left > right:
return None
mid = (left + right) // 2
root = TreeNode(nums[mid])
root.left = helper(left, mid - 1)
root.right = helper(mid + 1, right)
return root
return hel... | ListToBST | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListToBST:
def converter_(self, nums: List) -> TreeNode:
"""In-order traversal Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:"""
<|body_0|>
def converter_2(self, nums: List[int]) -> TreeNode:
"""In-order traversal with mid element to be always rig... | stack_v2_sparse_classes_36k_train_032497 | 2,159 | no_license | [
{
"docstring": "In-order traversal Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:",
"name": "converter_",
"signature": "def converter_(self, nums: List) -> TreeNode"
},
{
"docstring": "In-order traversal with mid element to be always right. Time Complexity: O(N) Space Complex... | 3 | null | Implement the Python class `ListToBST` described below.
Class description:
Implement the ListToBST class.
Method signatures and docstrings:
- def converter_(self, nums: List) -> TreeNode: In-order traversal Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:
- def converter_2(self, nums: List[int]) -> ... | Implement the Python class `ListToBST` described below.
Class description:
Implement the ListToBST class.
Method signatures and docstrings:
- def converter_(self, nums: List) -> TreeNode: In-order traversal Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:
- def converter_2(self, nums: List[int]) -> ... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class ListToBST:
def converter_(self, nums: List) -> TreeNode:
"""In-order traversal Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:"""
<|body_0|>
def converter_2(self, nums: List[int]) -> TreeNode:
"""In-order traversal with mid element to be always rig... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListToBST:
def converter_(self, nums: List) -> TreeNode:
"""In-order traversal Time Complexity: O(N) Space Complexity: O(N) :param nums: :return:"""
def helper(left, right):
if left > right:
return None
mid = (left + right) // 2
root = TreeNo... | the_stack_v2_python_sparse | data_structures/tree_node/sorted_array_to_bst.py | Shiv2157k/leet_code | train | 1 | |
1e6d33b3d2b4bdf7607f156c538ec5bca16e5041 | [
"content_type = ContentType.objects.get_for_model(obj)\nsql = 'SELECT SUM(amount * %s) FROM %s WHERE target_id = %s AND target_ct_id = %s' % (RATINGS_COEFICIENT, connection.ops.quote_name(Rating._meta.db_table), obj.id, content_type.id)\ncursor = connection.cursor()\ncursor.execute(sql, ())\nresult = cursor.fetchon... | <|body_start_0|>
content_type = ContentType.objects.get_for_model(obj)
sql = 'SELECT SUM(amount * %s) FROM %s WHERE target_id = %s AND target_ct_id = %s' % (RATINGS_COEFICIENT, connection.ops.quote_name(Rating._meta.db_table), obj.id, content_type.id)
cursor = connection.cursor()
cursor.... | RatingManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RatingManager:
def get_for_object(self, obj):
"""Return the rating for a given object. Params: obj: object to work with"""
<|body_0|>
def copy_rate_to_agg(self, time_limit, time_format, time_period):
"""Coppy aggregated Rating to table Agg time_limit: limit for time ... | stack_v2_sparse_classes_36k_train_032498 | 15,410 | no_license | [
{
"docstring": "Return the rating for a given object. Params: obj: object to work with",
"name": "get_for_object",
"signature": "def get_for_object(self, obj)"
},
{
"docstring": "Coppy aggregated Rating to table Agg time_limit: limit for time of transfering data time_format: format for destiny D... | 2 | null | Implement the Python class `RatingManager` described below.
Class description:
Implement the RatingManager class.
Method signatures and docstrings:
- def get_for_object(self, obj): Return the rating for a given object. Params: obj: object to work with
- def copy_rate_to_agg(self, time_limit, time_format, time_period)... | Implement the Python class `RatingManager` described below.
Class description:
Implement the RatingManager class.
Method signatures and docstrings:
- def get_for_object(self, obj): Return the rating for a given object. Params: obj: object to work with
- def copy_rate_to_agg(self, time_limit, time_format, time_period)... | edcae8ac03816631cf8fbae98b7730479f4c41b6 | <|skeleton|>
class RatingManager:
def get_for_object(self, obj):
"""Return the rating for a given object. Params: obj: object to work with"""
<|body_0|>
def copy_rate_to_agg(self, time_limit, time_format, time_period):
"""Coppy aggregated Rating to table Agg time_limit: limit for time ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RatingManager:
def get_for_object(self, obj):
"""Return the rating for a given object. Params: obj: object to work with"""
content_type = ContentType.objects.get_for_model(obj)
sql = 'SELECT SUM(amount * %s) FROM %s WHERE target_id = %s AND target_ct_id = %s' % (RATINGS_COEFICIENT, con... | the_stack_v2_python_sparse | ella/ratings/models.py | majerm/ella | train | 1 | |
a0375a14808ca2ec406e1aacfc95c2b68d9e19d8 | [
"self.seed = 33\nreset(self.seed)\nself.testing = testing\nself.layer = layer\nself.case = case\nself.model_dtype = self.testing.get('model_dtype')\npaddle.set_default_dtype(self.model_dtype)\nself.layer_name = self.layer.get('Layer').get('layer_name')\nself.layer_param = self.layer.get('Layer').get('params')\nself... | <|body_start_0|>
self.seed = 33
reset(self.seed)
self.testing = testing
self.layer = layer
self.case = case
self.model_dtype = self.testing.get('model_dtype')
paddle.set_default_dtype(self.model_dtype)
self.layer_name = self.layer.get('Layer').get('layer_n... | 构建Layer训练的通用类 | LayerTrain | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerTrain:
"""构建Layer训练的通用类"""
def __init__(self, testing, case, layer):
"""初始化"""
<|body_0|>
def dy_train(self):
"""dygraph train"""
<|body_1|>
def dy_train_dl(self):
"""dygraph train with dataloader"""
<|body_2|>
def dy2st_tra... | stack_v2_sparse_classes_36k_train_032499 | 6,570 | no_license | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self, testing, case, layer)"
},
{
"docstring": "dygraph train",
"name": "dy_train",
"signature": "def dy_train(self)"
},
{
"docstring": "dygraph train with dataloader",
"name": "dy_train_dl",
"signature"... | 6 | stack_v2_sparse_classes_30k_train_005078 | Implement the Python class `LayerTrain` described below.
Class description:
构建Layer训练的通用类
Method signatures and docstrings:
- def __init__(self, testing, case, layer): 初始化
- def dy_train(self): dygraph train
- def dy_train_dl(self): dygraph train with dataloader
- def dy2st_train(self): dy2st train
- def dy2st_train_... | Implement the Python class `LayerTrain` described below.
Class description:
构建Layer训练的通用类
Method signatures and docstrings:
- def __init__(self, testing, case, layer): 初始化
- def dy_train(self): dygraph train
- def dy_train_dl(self): dygraph train with dataloader
- def dy2st_train(self): dy2st train
- def dy2st_train_... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class LayerTrain:
"""构建Layer训练的通用类"""
def __init__(self, testing, case, layer):
"""初始化"""
<|body_0|>
def dy_train(self):
"""dygraph train"""
<|body_1|>
def dy_train_dl(self):
"""dygraph train with dataloader"""
<|body_2|>
def dy2st_tra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LayerTrain:
"""构建Layer训练的通用类"""
def __init__(self, testing, case, layer):
"""初始化"""
self.seed = 33
reset(self.seed)
self.testing = testing
self.layer = layer
self.case = case
self.model_dtype = self.testing.get('model_dtype')
paddle.set_defa... | the_stack_v2_python_sparse | framework/e2e/paddleLT/engine/train.py | PaddlePaddle/PaddleTest | train | 42 |
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