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 | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9f616a40590feb6fb45b6f3378064fa83c7f0934 | [
"if not isinstance(gate, Gate):\n raise TypeError('Expected gate object, got %s' % type(gate))\nself.gate = gate\nself.name = 'Dagger(%s)' % gate.get_name()\nself.num_params = gate.get_num_params()\nself.size = gate.get_size()\nself.radixes = gate.get_radixes()\nif self.num_params == 0:\n self.utry = gate.get... | <|body_start_0|>
if not isinstance(gate, Gate):
raise TypeError('Expected gate object, got %s' % type(gate))
self.gate = gate
self.name = 'Dagger(%s)' % gate.get_name()
self.num_params = gate.get_num_params()
self.size = gate.get_size()
self.radixes = gate.get... | The DaggerGate Class. | DaggerGate | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DaggerGate:
"""The DaggerGate Class."""
def __init__(self, gate: Gate) -> None:
"""Create a gate which is the conjugate transpose of another. Args: gate (Gate): The Gate to conjugate transpose."""
<|body_0|>
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMat... | stack_v2_sparse_classes_36k_train_018500 | 2,568 | permissive | [
{
"docstring": "Create a gate which is the conjugate transpose of another. Args: gate (Gate): The Gate to conjugate transpose.",
"name": "__init__",
"signature": "def __init__(self, gate: Gate) -> None"
},
{
"docstring": "Returns the unitary for this gate, see Unitary for more info.",
"name"... | 4 | stack_v2_sparse_classes_30k_train_008049 | Implement the Python class `DaggerGate` described below.
Class description:
The DaggerGate Class.
Method signatures and docstrings:
- def __init__(self, gate: Gate) -> None: Create a gate which is the conjugate transpose of another. Args: gate (Gate): The Gate to conjugate transpose.
- def get_unitary(self, params: S... | Implement the Python class `DaggerGate` described below.
Class description:
The DaggerGate Class.
Method signatures and docstrings:
- def __init__(self, gate: Gate) -> None: Create a gate which is the conjugate transpose of another. Args: gate (Gate): The Gate to conjugate transpose.
- def get_unitary(self, params: S... | 3083218c2f4e3c3ce4ba027d12caa30c384d7665 | <|skeleton|>
class DaggerGate:
"""The DaggerGate Class."""
def __init__(self, gate: Gate) -> None:
"""Create a gate which is the conjugate transpose of another. Args: gate (Gate): The Gate to conjugate transpose."""
<|body_0|>
def get_unitary(self, params: Sequence[float]=[]) -> UnitaryMat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DaggerGate:
"""The DaggerGate Class."""
def __init__(self, gate: Gate) -> None:
"""Create a gate which is the conjugate transpose of another. Args: gate (Gate): The Gate to conjugate transpose."""
if not isinstance(gate, Gate):
raise TypeError('Expected gate object, got %s' % ... | the_stack_v2_python_sparse | bqskit/ir/gates/composed/daggergate.py | mtreinish/bqskit | train | 0 |
14289ae036844bc863dacd0dbd8a4ccd260347b0 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserExperienceAnalyticsWorkFromAnywhereModelPerformance()",
"from .entity import Entity\nfrom .user_experience_analytics_health_state import UserExperienceAnalyticsHealthState\nfrom .entity import Entity\nfrom .user_experience_analytic... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserExperienceAnalyticsWorkFromAnywhereModelPerformance()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .user_experience_analytics_health_state import UserExperienceAna... | The user experience analytics work from anywhere model performance. | UserExperienceAnalyticsWorkFromAnywhereModelPerformance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserExperienceAnalyticsWorkFromAnywhereModelPerformance:
"""The user experience analytics work from anywhere model performance."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsWorkFromAnywhereModelPerformance:
"""Creates a new in... | stack_v2_sparse_classes_36k_train_018501 | 5,738 | 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: UserExperienceAnalyticsWorkFromAnywhereModelPerformance",
"name": "create_from_discriminator_value",
"signat... | 3 | stack_v2_sparse_classes_30k_train_006121 | Implement the Python class `UserExperienceAnalyticsWorkFromAnywhereModelPerformance` described below.
Class description:
The user experience analytics work from anywhere model performance.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAn... | Implement the Python class `UserExperienceAnalyticsWorkFromAnywhereModelPerformance` described below.
Class description:
The user experience analytics work from anywhere model performance.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAn... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserExperienceAnalyticsWorkFromAnywhereModelPerformance:
"""The user experience analytics work from anywhere model performance."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsWorkFromAnywhereModelPerformance:
"""Creates a new in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserExperienceAnalyticsWorkFromAnywhereModelPerformance:
"""The user experience analytics work from anywhere model performance."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsWorkFromAnywhereModelPerformance:
"""Creates a new instance of the... | the_stack_v2_python_sparse | msgraph/generated/models/user_experience_analytics_work_from_anywhere_model_performance.py | microsoftgraph/msgraph-sdk-python | train | 135 |
8d79abd33cd77205b1924d5ba56eeb01e8906a16 | [
"data = {}\nfiltered_data = {key: value for key, value in self.__dict__.items() if key not in self.READ_ONLY}\nfor key, value in filtered_data.items():\n data[key] = self._convert_value(value)\nreturn data",
"if isinstance(value, DataObject):\n value = value.to_dict()\nelif isinstance(value, dict):\n val... | <|body_start_0|>
data = {}
filtered_data = {key: value for key, value in self.__dict__.items() if key not in self.READ_ONLY}
for key, value in filtered_data.items():
data[key] = self._convert_value(value)
return data
<|end_body_0|>
<|body_start_1|>
if isinstance(valu... | Data object representation handling recursive transformation from object to dict | DataObject | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataObject:
"""Data object representation handling recursive transformation from object to dict"""
def to_dict(self) -> Dict:
"""Represent object as dictionary Returns: Dict"""
<|body_0|>
def _convert_value(self, value: Any) -> Any:
"""Convert value based on its ... | stack_v2_sparse_classes_36k_train_018502 | 3,830 | permissive | [
{
"docstring": "Represent object as dictionary Returns: Dict",
"name": "to_dict",
"signature": "def to_dict(self) -> Dict"
},
{
"docstring": "Convert value based on its type Args: value: variable to convert Returns: Converted object",
"name": "_convert_value",
"signature": "def _convert_... | 4 | null | Implement the Python class `DataObject` described below.
Class description:
Data object representation handling recursive transformation from object to dict
Method signatures and docstrings:
- def to_dict(self) -> Dict: Represent object as dictionary Returns: Dict
- def _convert_value(self, value: Any) -> Any: Conver... | Implement the Python class `DataObject` described below.
Class description:
Data object representation handling recursive transformation from object to dict
Method signatures and docstrings:
- def to_dict(self) -> Dict: Represent object as dictionary Returns: Dict
- def _convert_value(self, value: Any) -> Any: Conver... | a5388a45f71a949639b35cc5b990bd130d2d8164 | <|skeleton|>
class DataObject:
"""Data object representation handling recursive transformation from object to dict"""
def to_dict(self) -> Dict:
"""Represent object as dictionary Returns: Dict"""
<|body_0|>
def _convert_value(self, value: Any) -> Any:
"""Convert value based on its ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataObject:
"""Data object representation handling recursive transformation from object to dict"""
def to_dict(self) -> Dict:
"""Represent object as dictionary Returns: Dict"""
data = {}
filtered_data = {key: value for key, value in self.__dict__.items() if key not in self.READ_ON... | the_stack_v2_python_sparse | TensorFlow2/Recommendation/WideAndDeep/triton/runner/core.py | NVIDIA/DeepLearningExamples | train | 11,838 |
6a3a666b24d670f02713c86e1d51973ca7a4def9 | [
"super(QNetwork, self).__init__()\nif norm_in:\n self.in_fn = nn.BatchNorm1d(state_size)\n self.in_fn.weight.data.fill_(1)\n self.in_fn.bias.data.fill_(0)\nelse:\n self.in_fn = lambda x: x\nself.fc1 = nn.Linear(state_size, hidden_dim)\nself.fc2 = nn.Linear(hidden_dim, hidden_dim)\nself.fc3 = nn.Linear(h... | <|body_start_0|>
super(QNetwork, self).__init__()
if norm_in:
self.in_fn = nn.BatchNorm1d(state_size)
self.in_fn.weight.data.fill_(1)
self.in_fn.bias.data.fill_(0)
else:
self.in_fn = lambda x: x
self.fc1 = nn.Linear(state_size, hidden_dim)
... | Deep Q-Network | QNetwork | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QNetwork:
"""Deep Q-Network"""
def __init__(self, state_size, action_size, hidden_dim, dropout_p=0.0, nonlin=F.relu, norm_in=True):
"""Initialize parameters and build model. :param state_size: Dimension of each state :param action_size: Dimension of each action :param hidden_dim: dim... | stack_v2_sparse_classes_36k_train_018503 | 1,565 | no_license | [
{
"docstring": "Initialize parameters and build model. :param state_size: Dimension of each state :param action_size: Dimension of each action :param hidden_dim: dimension of hidden layers :param dropout_p: dropout probability :param nonlin: nonlinearity to use :param norm_in: normalise input first",
"name"... | 2 | stack_v2_sparse_classes_30k_train_019971 | Implement the Python class `QNetwork` described below.
Class description:
Deep Q-Network
Method signatures and docstrings:
- def __init__(self, state_size, action_size, hidden_dim, dropout_p=0.0, nonlin=F.relu, norm_in=True): Initialize parameters and build model. :param state_size: Dimension of each state :param act... | Implement the Python class `QNetwork` described below.
Class description:
Deep Q-Network
Method signatures and docstrings:
- def __init__(self, state_size, action_size, hidden_dim, dropout_p=0.0, nonlin=F.relu, norm_in=True): Initialize parameters and build model. :param state_size: Dimension of each state :param act... | 2afa0a9d83bd66a151c1a19242c5ef22cf4eb1f6 | <|skeleton|>
class QNetwork:
"""Deep Q-Network"""
def __init__(self, state_size, action_size, hidden_dim, dropout_p=0.0, nonlin=F.relu, norm_in=True):
"""Initialize parameters and build model. :param state_size: Dimension of each state :param action_size: Dimension of each action :param hidden_dim: dim... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QNetwork:
"""Deep Q-Network"""
def __init__(self, state_size, action_size, hidden_dim, dropout_p=0.0, nonlin=F.relu, norm_in=True):
"""Initialize parameters and build model. :param state_size: Dimension of each state :param action_size: Dimension of each action :param hidden_dim: dimension of hid... | the_stack_v2_python_sparse | marl_algorithms/iql/model.py | Jarvis-K/MSc_Curiosity_MARL | train | 0 |
e9ff5459df5adb326802b73e7a2c6cde500e1ac0 | [
"super().__init__()\nself._subset = subset\nself._shuffle_data = shuffle_data\nself._data_dir = data_dir or DATA_ROOT\nself._dataset = None\nallowed_versions = ('tokens', 'raw')\nif version not in allowed_versions:\n raise ValueError(f'Version must be one of {allowed_versions}.')\nself._version = version",
"if... | <|body_start_0|>
super().__init__()
self._subset = subset
self._shuffle_data = shuffle_data
self._data_dir = data_dir or DATA_ROOT
self._dataset = None
allowed_versions = ('tokens', 'raw')
if version not in allowed_versions:
raise ValueError(f'Version ... | Raw text dataset for wikitext-103. | RawDataset | [
"Apache-2.0",
"CC-BY-SA-4.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RawDataset:
"""Raw text dataset for wikitext-103."""
def __init__(self, subset: str='train', shuffle_data: bool=False, data_dir: str=None, version: str='tokens'):
"""Constructor. Args: subset: which subset to load, one of {"train", "valid", "test"}. shuffle_data: if set to True the d... | stack_v2_sparse_classes_36k_train_018504 | 7,525 | permissive | [
{
"docstring": "Constructor. Args: subset: which subset to load, one of {\"train\", \"valid\", \"test\"}. shuffle_data: if set to True the data will be randomly shuffled. data_dir: if provided will be used instead of the default `DATA_ROOT` as the directory that contains the data. version: one of {'tokens', 'ra... | 2 | null | Implement the Python class `RawDataset` described below.
Class description:
Raw text dataset for wikitext-103.
Method signatures and docstrings:
- def __init__(self, subset: str='train', shuffle_data: bool=False, data_dir: str=None, version: str='tokens'): Constructor. Args: subset: which subset to load, one of {"tra... | Implement the Python class `RawDataset` described below.
Class description:
Raw text dataset for wikitext-103.
Method signatures and docstrings:
- def __init__(self, subset: str='train', shuffle_data: bool=False, data_dir: str=None, version: str='tokens'): Constructor. Args: subset: which subset to load, one of {"tra... | a6ef8053380d6aa19aaae14b93f013ae9762d057 | <|skeleton|>
class RawDataset:
"""Raw text dataset for wikitext-103."""
def __init__(self, subset: str='train', shuffle_data: bool=False, data_dir: str=None, version: str='tokens'):
"""Constructor. Args: subset: which subset to load, one of {"train", "valid", "test"}. shuffle_data: if set to True the d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RawDataset:
"""Raw text dataset for wikitext-103."""
def __init__(self, subset: str='train', shuffle_data: bool=False, data_dir: str=None, version: str='tokens'):
"""Constructor. Args: subset: which subset to load, one of {"train", "valid", "test"}. shuffle_data: if set to True the data will be r... | the_stack_v2_python_sparse | wikigraphs/wikigraphs/data/wikitext.py | sethuramanio/deepmind-research | train | 1 |
b82ca52e89e3c128090ee089970b7f4510e744a9 | [
"self.frame = frame\nself.max_width = max_width\nself.max_height = max_height\nheight = float(self.frame.shape[0])\nwidth = float(self.frame.shape[1])\nif height <= self.max_height and width <= self.max_width:\n self.scale_factor = 1.0\nelif height >= width:\n self.scale_factor = self.max_height / height\nels... | <|body_start_0|>
self.frame = frame
self.max_width = max_width
self.max_height = max_height
height = float(self.frame.shape[0])
width = float(self.frame.shape[1])
if height <= self.max_height and width <= self.max_width:
self.scale_factor = 1.0
elif he... | Scales down a frame if its size is over a given amount, preserving the original aspect ratio. It can then scale up any detections that have been run on the smaller frame to fit the original frame size. If the frame is under the given amount, nothing is done and the frame is kept the same. Usage Example: >>> clamp = Cla... | Clamp | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Clamp:
"""Scales down a frame if its size is over a given amount, preserving the original aspect ratio. It can then scale up any detections that have been run on the smaller frame to fit the original frame size. If the frame is under the given amount, nothing is done and the frame is kept the sam... | stack_v2_sparse_classes_36k_train_018505 | 14,406 | permissive | [
{
"docstring": ":param frame: The frame to scale :param max_width: The maximum allowed width of the frame :param max_height: The maximum allowed height of the frame",
"name": "__init__",
"signature": "def __init__(self, frame, max_width, max_height)"
},
{
"docstring": ":return: A clamped version... | 3 | stack_v2_sparse_classes_30k_train_012089 | Implement the Python class `Clamp` described below.
Class description:
Scales down a frame if its size is over a given amount, preserving the original aspect ratio. It can then scale up any detections that have been run on the smaller frame to fit the original frame size. If the frame is under the given amount, nothin... | Implement the Python class `Clamp` described below.
Class description:
Scales down a frame if its size is over a given amount, preserving the original aspect ratio. It can then scale up any detections that have been run on the smaller frame to fit the original frame size. If the frame is under the given amount, nothin... | 7412902fed8f91c9c82bd42b0180e07673c38bf1 | <|skeleton|>
class Clamp:
"""Scales down a frame if its size is over a given amount, preserving the original aspect ratio. It can then scale up any detections that have been run on the smaller frame to fit the original frame size. If the frame is under the given amount, nothing is done and the frame is kept the sam... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Clamp:
"""Scales down a frame if its size is over a given amount, preserving the original aspect ratio. It can then scale up any detections that have been run on the smaller frame to fit the original frame size. If the frame is under the given amount, nothing is done and the frame is kept the same. Usage Exam... | the_stack_v2_python_sparse | vcap/vcap/modifiers.py | opencv/open_vision_capsules | train | 124 |
69f45143dbae2ae8b136f12cadcb38a488639527 | [
"allowed_users = []\nfor user in self.targets:\n if not user.is_active:\n continue\n allows_emails = InvenTree.helpers.str2bool(self.usersetting(user))\n if allows_emails:\n allowed_users.append(user)\nreturn EmailAddress.objects.filter(user__in=allowed_users)",
"html_message = render_to_st... | <|body_start_0|>
allowed_users = []
for user in self.targets:
if not user.is_active:
continue
allows_emails = InvenTree.helpers.str2bool(self.usersetting(user))
if allows_emails:
allowed_users.append(user)
return EmailAddress.ob... | Notificationmethod for delivery via Email. | EmailNotification | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmailNotification:
"""Notificationmethod for delivery via Email."""
def get_targets(self):
"""Return a list of target email addresses, only for users which allow email notifications."""
<|body_0|>
def send_bulk(self):
"""Send the notifications out via email."""
... | stack_v2_sparse_classes_36k_train_018506 | 6,053 | permissive | [
{
"docstring": "Return a list of target email addresses, only for users which allow email notifications.",
"name": "get_targets",
"signature": "def get_targets(self)"
},
{
"docstring": "Send the notifications out via email.",
"name": "send_bulk",
"signature": "def send_bulk(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018135 | Implement the Python class `EmailNotification` described below.
Class description:
Notificationmethod for delivery via Email.
Method signatures and docstrings:
- def get_targets(self): Return a list of target email addresses, only for users which allow email notifications.
- def send_bulk(self): Send the notification... | Implement the Python class `EmailNotification` described below.
Class description:
Notificationmethod for delivery via Email.
Method signatures and docstrings:
- def get_targets(self): Return a list of target email addresses, only for users which allow email notifications.
- def send_bulk(self): Send the notification... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class EmailNotification:
"""Notificationmethod for delivery via Email."""
def get_targets(self):
"""Return a list of target email addresses, only for users which allow email notifications."""
<|body_0|>
def send_bulk(self):
"""Send the notifications out via email."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmailNotification:
"""Notificationmethod for delivery via Email."""
def get_targets(self):
"""Return a list of target email addresses, only for users which allow email notifications."""
allowed_users = []
for user in self.targets:
if not user.is_active:
... | the_stack_v2_python_sparse | InvenTree/plugin/builtin/integration/core_notifications.py | inventree/InvenTree | train | 3,077 |
ae4c923a26bf1f8cd1bd8039078c957125ca73ae | [
"super(AITank, self).__init__(tank_id)\nself.state = 'patrolling'\nself.ai_moving = {'prev_angle': self.moving['angle'], 'prev_center': self.tank.rect.center, 'desired_angle': 0, 'back': 0}\nself.max_state_change_frame = 10\nself.state_change_frame = 0\nself.target = self.tank",
"bullet = Bullet(vector, self.tank... | <|body_start_0|>
super(AITank, self).__init__(tank_id)
self.state = 'patrolling'
self.ai_moving = {'prev_angle': self.moving['angle'], 'prev_center': self.tank.rect.center, 'desired_angle': 0, 'back': 0}
self.max_state_change_frame = 10
self.state_change_frame = 0
self.ta... | Tank controlled by AI | AITank | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AITank:
"""Tank controlled by AI"""
def __init__(self, tank_id):
""":param tank_id: tank graphic id"""
<|body_0|>
def laser_target(self, tank, vector):
""":param tank: tank to be targeted :param vector: vector for targeting :return: True if there are no obstacles... | stack_v2_sparse_classes_36k_train_018507 | 21,421 | no_license | [
{
"docstring": ":param tank_id: tank graphic id",
"name": "__init__",
"signature": "def __init__(self, tank_id)"
},
{
"docstring": ":param tank: tank to be targeted :param vector: vector for targeting :return: True if there are no obstacles, False otherwise",
"name": "laser_target",
"sig... | 6 | stack_v2_sparse_classes_30k_train_015156 | Implement the Python class `AITank` described below.
Class description:
Tank controlled by AI
Method signatures and docstrings:
- def __init__(self, tank_id): :param tank_id: tank graphic id
- def laser_target(self, tank, vector): :param tank: tank to be targeted :param vector: vector for targeting :return: True if t... | Implement the Python class `AITank` described below.
Class description:
Tank controlled by AI
Method signatures and docstrings:
- def __init__(self, tank_id): :param tank_id: tank graphic id
- def laser_target(self, tank, vector): :param tank: tank to be targeted :param vector: vector for targeting :return: True if t... | 51a2f2ecc09a05672a2c3deb00ab8c273d3b756b | <|skeleton|>
class AITank:
"""Tank controlled by AI"""
def __init__(self, tank_id):
""":param tank_id: tank graphic id"""
<|body_0|>
def laser_target(self, tank, vector):
""":param tank: tank to be targeted :param vector: vector for targeting :return: True if there are no obstacles... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AITank:
"""Tank controlled by AI"""
def __init__(self, tank_id):
""":param tank_id: tank graphic id"""
super(AITank, self).__init__(tank_id)
self.state = 'patrolling'
self.ai_moving = {'prev_angle': self.moving['angle'], 'prev_center': self.tank.rect.center, 'desired_angle... | the_stack_v2_python_sparse | game_core/game_data.py | asmodeii/tanki | train | 0 |
8d314dcbe006af415ca333f1a610ebd51cf507cd | [
"sessions = request.session.get('sessions', {})\nif environment_id in sessions:\n id = sessions[environment_id]\nelse:\n id = create_session(request, environment_id)\nreturn id",
"sessions = request.session.get('sessions', {})\nclient = api.muranoclient(request)\nif environment_id in sessions:\n id = ses... | <|body_start_0|>
sessions = request.session.get('sessions', {})
if environment_id in sessions:
id = sessions[environment_id]
else:
id = create_session(request, environment_id)
return id
<|end_body_0|>
<|body_start_1|>
sessions = request.session.get('sessi... | Session | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Session:
def get_or_create(request, environment_id):
"""Get an open session id Gets id from already opened session for specified environment, otherwise opens new session and returns its id :param request: :param environment_id: :return: Session Id"""
<|body_0|>
def get_or_cr... | stack_v2_sparse_classes_36k_train_018508 | 17,347 | permissive | [
{
"docstring": "Get an open session id Gets id from already opened session for specified environment, otherwise opens new session and returns its id :param request: :param environment_id: :return: Session Id",
"name": "get_or_create",
"signature": "def get_or_create(request, environment_id)"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_004067 | Implement the Python class `Session` described below.
Class description:
Implement the Session class.
Method signatures and docstrings:
- def get_or_create(request, environment_id): Get an open session id Gets id from already opened session for specified environment, otherwise opens new session and returns its id :pa... | Implement the Python class `Session` described below.
Class description:
Implement the Session class.
Method signatures and docstrings:
- def get_or_create(request, environment_id): Get an open session id Gets id from already opened session for specified environment, otherwise opens new session and returns its id :pa... | 54e2ea8a71385b1c7624b3d2c8056bd8a2c2e2f7 | <|skeleton|>
class Session:
def get_or_create(request, environment_id):
"""Get an open session id Gets id from already opened session for specified environment, otherwise opens new session and returns its id :param request: :param environment_id: :return: Session Id"""
<|body_0|>
def get_or_cr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Session:
def get_or_create(request, environment_id):
"""Get an open session id Gets id from already opened session for specified environment, otherwise opens new session and returns its id :param request: :param environment_id: :return: Session Id"""
sessions = request.session.get('sessions', ... | the_stack_v2_python_sparse | muranodashboard/environments/api.py | openstack/murano-dashboard | train | 38 | |
c3a38c921925b5fe392567fc06a3419bdc8ee4d0 | [
"try:\n obj_kwargs = kwargs.copy()\n obj_kwargs[self.uri_object_key] = object_id\n review_request = resources.review_request.get_object(request, *args, **obj_kwargs)\n user = resources.user.get_object(request, *args, **kwargs)\nexcept (ReviewRequest.DoesNotExist, User.DoesNotExist):\n return DOES_NOT... | <|body_start_0|>
try:
obj_kwargs = kwargs.copy()
obj_kwargs[self.uri_object_key] = object_id
review_request = resources.review_request.get_object(request, *args, **obj_kwargs)
user = resources.user.get_object(request, *args, **kwargs)
except (ReviewRequest... | A base resource for objects archived or muted by a user. | BaseArchivedObjectResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseArchivedObjectResource:
"""A base resource for objects archived or muted by a user."""
def create(self, request, object_id, *args, **kwargs):
"""Handle HTTP POST operations."""
<|body_0|>
def delete(self, request, review_request_id, *args, **kwargs):
"""Handl... | stack_v2_sparse_classes_36k_train_018509 | 3,181 | permissive | [
{
"docstring": "Handle HTTP POST operations.",
"name": "create",
"signature": "def create(self, request, object_id, *args, **kwargs)"
},
{
"docstring": "Handle HTTP DELETE operations.",
"name": "delete",
"signature": "def delete(self, request, review_request_id, *args, **kwargs)"
}
] | 2 | null | Implement the Python class `BaseArchivedObjectResource` described below.
Class description:
A base resource for objects archived or muted by a user.
Method signatures and docstrings:
- def create(self, request, object_id, *args, **kwargs): Handle HTTP POST operations.
- def delete(self, request, review_request_id, *a... | Implement the Python class `BaseArchivedObjectResource` described below.
Class description:
A base resource for objects archived or muted by a user.
Method signatures and docstrings:
- def create(self, request, object_id, *args, **kwargs): Handle HTTP POST operations.
- def delete(self, request, review_request_id, *a... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class BaseArchivedObjectResource:
"""A base resource for objects archived or muted by a user."""
def create(self, request, object_id, *args, **kwargs):
"""Handle HTTP POST operations."""
<|body_0|>
def delete(self, request, review_request_id, *args, **kwargs):
"""Handl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseArchivedObjectResource:
"""A base resource for objects archived or muted by a user."""
def create(self, request, object_id, *args, **kwargs):
"""Handle HTTP POST operations."""
try:
obj_kwargs = kwargs.copy()
obj_kwargs[self.uri_object_key] = object_id
... | the_stack_v2_python_sparse | reviewboard/webapi/resources/base_archived_object.py | reviewboard/reviewboard | train | 1,141 |
e84be0586edee80e04b2403c807a77b2ec25fede | [
"if request.user.is_staff:\n return True\nreturn super().has_permission(request, view)",
"if request.user.is_staff or obj.user == request.user:\n return True\nhas_permission = super().has_permission(request, view)\nif has_permission and request.method in permissions.SAFE_METHODS:\n try:\n org_id =... | <|body_start_0|>
if request.user.is_staff:
return True
return super().has_permission(request, view)
<|end_body_0|>
<|body_start_1|>
if request.user.is_staff or obj.user == request.user:
return True
has_permission = super().has_permission(request, view)
if... | extends DjanoModelPermissions and adds object level perms | IsAdminOwnerOrShared | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsAdminOwnerOrShared:
"""extends DjanoModelPermissions and adds object level perms"""
def has_permission(self, request, view):
"""has permission called before has_object_permission check for is_staff, then check model permissions if all true, then has_object permission called"""
... | stack_v2_sparse_classes_36k_train_018510 | 5,524 | permissive | [
{
"docstring": "has permission called before has_object_permission check for is_staff, then check model permissions if all true, then has_object permission called",
"name": "has_permission",
"signature": "def has_permission(self, request, view)"
},
{
"docstring": "Create not called by this metho... | 2 | stack_v2_sparse_classes_30k_val_000867 | Implement the Python class `IsAdminOwnerOrShared` described below.
Class description:
extends DjanoModelPermissions and adds object level perms
Method signatures and docstrings:
- def has_permission(self, request, view): has permission called before has_object_permission check for is_staff, then check model permissio... | Implement the Python class `IsAdminOwnerOrShared` described below.
Class description:
extends DjanoModelPermissions and adds object level perms
Method signatures and docstrings:
- def has_permission(self, request, view): has permission called before has_object_permission check for is_staff, then check model permissio... | 40d9608295daefc5e1cd83afd84ecb5b0518cc3d | <|skeleton|>
class IsAdminOwnerOrShared:
"""extends DjanoModelPermissions and adds object level perms"""
def has_permission(self, request, view):
"""has permission called before has_object_permission check for is_staff, then check model permissions if all true, then has_object permission called"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IsAdminOwnerOrShared:
"""extends DjanoModelPermissions and adds object level perms"""
def has_permission(self, request, view):
"""has permission called before has_object_permission check for is_staff, then check model permissions if all true, then has_object permission called"""
if reques... | the_stack_v2_python_sparse | app/squac/permissions.py | pnsn/squacapi | train | 7 |
399094d90aed7a1109c9de4ae18e367dd0711324 | [
"self.forms = []\ninstances = instances or []\nfor i, obj in enumerate(instances):\n if isinstance(obj, db.Key):\n obj = db.get(obj)\n form_kwargs = {'instance': obj, 'prefix': '%i' % i}\n if data:\n form_kwargs.update(dict(data=data))\n base_form = self.base_form(**form_kwargs)\n self.... | <|body_start_0|>
self.forms = []
instances = instances or []
for i, obj in enumerate(instances):
if isinstance(obj, db.Key):
obj = db.get(obj)
form_kwargs = {'instance': obj, 'prefix': '%i' % i}
if data:
form_kwargs.update(dict(... | BaseFormSet | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseFormSet:
def __init__(self, data=None, instances=None, extra_forms=2):
"""Testing Concerns: - deleting an item - adding an item - altering the key - altering the value"""
<|body_0|>
def is_valid(self):
"""App engine doesn't support the empty_permitted flag to mod... | stack_v2_sparse_classes_36k_train_018511 | 1,921 | permissive | [
{
"docstring": "Testing Concerns: - deleting an item - adding an item - altering the key - altering the value",
"name": "__init__",
"signature": "def __init__(self, data=None, instances=None, extra_forms=2)"
},
{
"docstring": "App engine doesn't support the empty_permitted flag to model forms, s... | 2 | stack_v2_sparse_classes_30k_train_008816 | Implement the Python class `BaseFormSet` described below.
Class description:
Implement the BaseFormSet class.
Method signatures and docstrings:
- def __init__(self, data=None, instances=None, extra_forms=2): Testing Concerns: - deleting an item - adding an item - altering the key - altering the value
- def is_valid(s... | Implement the Python class `BaseFormSet` described below.
Class description:
Implement the BaseFormSet class.
Method signatures and docstrings:
- def __init__(self, data=None, instances=None, extra_forms=2): Testing Concerns: - deleting an item - adding an item - altering the key - altering the value
- def is_valid(s... | afdc352436f9ce623cfb108caf36cd8bc2590f06 | <|skeleton|>
class BaseFormSet:
def __init__(self, data=None, instances=None, extra_forms=2):
"""Testing Concerns: - deleting an item - adding an item - altering the key - altering the value"""
<|body_0|>
def is_valid(self):
"""App engine doesn't support the empty_permitted flag to mod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseFormSet:
def __init__(self, data=None, instances=None, extra_forms=2):
"""Testing Concerns: - deleting an item - adding an item - altering the key - altering the value"""
self.forms = []
instances = instances or []
for i, obj in enumerate(instances):
if isinstan... | the_stack_v2_python_sparse | permachart/charter/form_utils.py | justinabrahms/permachart | train | 1 | |
86c9d57842f9431b86c70b00d1e9355d793f805c | [
"super(GetSchedulerScalingPolicy, self).setUp()\nself.at_value = self.autoscale_behaviors.get_time_in_utc(600)\nself.cron_value = '0 */10 * * *'\nself.at_style_policy = self.autoscale_behaviors.create_schedule_policy_given(group_id=self.group.id, sp_name='hahaha', sp_change=self.sp_change, schedule_at=self.at_value... | <|body_start_0|>
super(GetSchedulerScalingPolicy, self).setUp()
self.at_value = self.autoscale_behaviors.get_time_in_utc(600)
self.cron_value = '0 */10 * * *'
self.at_style_policy = self.autoscale_behaviors.create_schedule_policy_given(group_id=self.group.id, sp_name='hahaha', sp_change=... | Verify get scheduler policies. | GetSchedulerScalingPolicy | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetSchedulerScalingPolicy:
"""Verify get scheduler policies."""
def setUp(self):
"""Create 2 scheduler policies, one at-style and another cron-style on the scaling group with 0 minentities"""
<|body_0|>
def test_get_at_style_scaling_policy(self):
"""Verify get at... | stack_v2_sparse_classes_36k_train_018512 | 5,980 | permissive | [
{
"docstring": "Create 2 scheduler policies, one at-style and another cron-style on the scaling group with 0 minentities",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Verify get at style schedule policy's response code 200, headers and data.",
"name": "test_get_at_styl... | 5 | null | Implement the Python class `GetSchedulerScalingPolicy` described below.
Class description:
Verify get scheduler policies.
Method signatures and docstrings:
- def setUp(self): Create 2 scheduler policies, one at-style and another cron-style on the scaling group with 0 minentities
- def test_get_at_style_scaling_policy... | Implement the Python class `GetSchedulerScalingPolicy` described below.
Class description:
Verify get scheduler policies.
Method signatures and docstrings:
- def setUp(self): Create 2 scheduler policies, one at-style and another cron-style on the scaling group with 0 minentities
- def test_get_at_style_scaling_policy... | 7199cdd67255fe116dbcbedea660c13453671134 | <|skeleton|>
class GetSchedulerScalingPolicy:
"""Verify get scheduler policies."""
def setUp(self):
"""Create 2 scheduler policies, one at-style and another cron-style on the scaling group with 0 minentities"""
<|body_0|>
def test_get_at_style_scaling_policy(self):
"""Verify get at... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetSchedulerScalingPolicy:
"""Verify get scheduler policies."""
def setUp(self):
"""Create 2 scheduler policies, one at-style and another cron-style on the scaling group with 0 minentities"""
super(GetSchedulerScalingPolicy, self).setUp()
self.at_value = self.autoscale_behaviors.g... | the_stack_v2_python_sparse | autoscale_cloudroast/test_repo/autoscale/functional/scheduler/test_get_scheduler_policies.py | rackerlabs/otter | train | 20 |
8a35cc0467f05bc6c013748ef70aa4c80b707008 | [
"if head.next is None or head.next is None:\n return head\nnew_head = self.reverseList(head.next)\nhead.next.next = head\nhead.next = None\nreturn new_head",
"if head is None:\n return head\npre = None\ncur = head\nwhile cur is not None:\n next_node = cur.next\n cur.next = pre\n pre = cur\n cur ... | <|body_start_0|>
if head.next is None or head.next is None:
return head
new_head = self.reverseList(head.next)
head.next.next = head
head.next = None
return new_head
<|end_body_0|>
<|body_start_1|>
if head is None:
return head
pre = None
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head: ListNode) -> ListNode:
"""递归"""
<|body_0|>
def reverseList1(self, head: ListNode) -> ListNode:
"""迭代"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if head.next is None or head.next is None:
return ... | stack_v2_sparse_classes_36k_train_018513 | 941 | no_license | [
{
"docstring": "递归",
"name": "reverseList",
"signature": "def reverseList(self, head: ListNode) -> ListNode"
},
{
"docstring": "迭代",
"name": "reverseList1",
"signature": "def reverseList1(self, head: ListNode) -> ListNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_002207 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head: ListNode) -> ListNode: 递归
- def reverseList1(self, head: ListNode) -> ListNode: 迭代 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head: ListNode) -> ListNode: 递归
- def reverseList1(self, head: ListNode) -> ListNode: 迭代
<|skeleton|>
class Solution:
def reverseList(self, head: List... | 3fa96c81f92595cf076ad675ba332e2b0eb0e071 | <|skeleton|>
class Solution:
def reverseList(self, head: ListNode) -> ListNode:
"""递归"""
<|body_0|>
def reverseList1(self, head: ListNode) -> ListNode:
"""迭代"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList(self, head: ListNode) -> ListNode:
"""递归"""
if head.next is None or head.next is None:
return head
new_head = self.reverseList(head.next)
head.next.next = head
head.next = None
return new_head
def reverseList1(self, hea... | the_stack_v2_python_sparse | 2020-03/3月每日一题复习/206反转链表.py | Annihilation7/Leetcode-Love | train | 0 | |
b03090fd9840a23d7d9588afba135c37ffe75293 | [
"r = urllib.request.urlopen(self.url)\njdata = json.loads(r.read().decode(r.info().get_param('charset') or 'utf-8'))\nself.alldata = jdata['items']\nself.target_list = [list(item.keys())[0] for item in self.alldata]\nprint(f'Loaded {len(self.target_list)} targets')",
"try:\n ti = self.target_list.index(target)... | <|body_start_0|>
r = urllib.request.urlopen(self.url)
jdata = json.loads(r.read().decode(r.info().get_param('charset') or 'utf-8'))
self.alldata = jdata['items']
self.target_list = [list(item.keys())[0] for item in self.alldata]
print(f'Loaded {len(self.target_list)} targets')
<|... | ExoplanetWatch | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExoplanetWatch:
def __init__(self) -> None:
"""An interface to the Exoplanet Watch Results Database Parameters ---------- Returns ------- None"""
<|body_0|>
def get(self, target):
"""Returns a dictionary of the result for the given target Parameters ---------- target... | stack_v2_sparse_classes_36k_train_018514 | 5,589 | permissive | [
{
"docstring": "An interface to the Exoplanet Watch Results Database Parameters ---------- Returns ------- None",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Returns a dictionary of the result for the given target Parameters ---------- target : str The target... | 2 | stack_v2_sparse_classes_30k_train_020333 | Implement the Python class `ExoplanetWatch` described below.
Class description:
Implement the ExoplanetWatch class.
Method signatures and docstrings:
- def __init__(self) -> None: An interface to the Exoplanet Watch Results Database Parameters ---------- Returns ------- None
- def get(self, target): Returns a diction... | Implement the Python class `ExoplanetWatch` described below.
Class description:
Implement the ExoplanetWatch class.
Method signatures and docstrings:
- def __init__(self) -> None: An interface to the Exoplanet Watch Results Database Parameters ---------- Returns ------- None
- def get(self, target): Returns a diction... | 2a5b09c01a5f19289d1947b09a0789f11e5ed7b2 | <|skeleton|>
class ExoplanetWatch:
def __init__(self) -> None:
"""An interface to the Exoplanet Watch Results Database Parameters ---------- Returns ------- None"""
<|body_0|>
def get(self, target):
"""Returns a dictionary of the result for the given target Parameters ---------- target... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExoplanetWatch:
def __init__(self) -> None:
"""An interface to the Exoplanet Watch Results Database Parameters ---------- Returns ------- None"""
r = urllib.request.urlopen(self.url)
jdata = json.loads(r.read().decode(r.info().get_param('charset') or 'utf-8'))
self.alldata = jd... | the_stack_v2_python_sparse | exotic/api/ew.py | rzellem/EXOTIC | train | 65 | |
c83d84d1e8e31802f6efa6f2076fc844984adcc6 | [
"if spec.deprecated == fullname:\n warnings.warn(f'Module {fullname} is deprecated since rally-openstack {spec.release}. Use {spec.get_new_name(fullname)} instead.', stacklevel=3)\nreturn importlib.machinery.ModuleSpec(fullname, ModuleLoader(spec))",
"for spec in _MOVES:\n if spec.deprecated in fullname:\n ... | <|body_start_0|>
if spec.deprecated == fullname:
warnings.warn(f'Module {fullname} is deprecated since rally-openstack {spec.release}. Use {spec.get_new_name(fullname)} instead.', stacklevel=3)
return importlib.machinery.ModuleSpec(fullname, ModuleLoader(spec))
<|end_body_0|>
<|body_start_1... | ModulesMovementsHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModulesMovementsHandler:
def _process_spec(cls, fullname, spec):
"""Make module spec and print warning message if needed."""
<|body_0|>
def find_spec(cls, fullname, path=None, target=None):
"""This functions is what gets executed by the loader."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_018515 | 6,151 | permissive | [
{
"docstring": "Make module spec and print warning message if needed.",
"name": "_process_spec",
"signature": "def _process_spec(cls, fullname, spec)"
},
{
"docstring": "This functions is what gets executed by the loader.",
"name": "find_spec",
"signature": "def find_spec(cls, fullname, ... | 2 | stack_v2_sparse_classes_30k_train_006402 | Implement the Python class `ModulesMovementsHandler` described below.
Class description:
Implement the ModulesMovementsHandler class.
Method signatures and docstrings:
- def _process_spec(cls, fullname, spec): Make module spec and print warning message if needed.
- def find_spec(cls, fullname, path=None, target=None)... | Implement the Python class `ModulesMovementsHandler` described below.
Class description:
Implement the ModulesMovementsHandler class.
Method signatures and docstrings:
- def _process_spec(cls, fullname, spec): Make module spec and print warning message if needed.
- def find_spec(cls, fullname, path=None, target=None)... | 9ff67887bf848c5966bb4a2f37018500d30dbe45 | <|skeleton|>
class ModulesMovementsHandler:
def _process_spec(cls, fullname, spec):
"""Make module spec and print warning message if needed."""
<|body_0|>
def find_spec(cls, fullname, path=None, target=None):
"""This functions is what gets executed by the loader."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModulesMovementsHandler:
def _process_spec(cls, fullname, spec):
"""Make module spec and print warning message if needed."""
if spec.deprecated == fullname:
warnings.warn(f'Module {fullname} is deprecated since rally-openstack {spec.release}. Use {spec.get_new_name(fullname)} inste... | the_stack_v2_python_sparse | rally_openstack/_compat.py | openstack/rally-openstack | train | 41 | |
17fc7b66b537c554121d16ef3a73c3f43f49a50d | [
"mocker = Mocker()\nnumber = mocker.mock()\ncorpus_file = mocker.mock()\ncorpus_dir = mocker.mock()\ntext = mocker.mock()\ncorpus_file = 'script.rst'\nmocker.replay()\nscript = update_corpus_xml_info.Update_Corpus_XML_Info(number, corpus_file, corpus_dir, text)\nmocker.restore()\nmocker.verify()\nself.assertEqual(s... | <|body_start_0|>
mocker = Mocker()
number = mocker.mock()
corpus_file = mocker.mock()
corpus_dir = mocker.mock()
text = mocker.mock()
corpus_file = 'script.rst'
mocker.replay()
script = update_corpus_xml_info.Update_Corpus_XML_Info(number, corpus_file, cor... | test_UCXI_snippet_pair_count | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_UCXI_snippet_pair_count:
def test_snippet_pair_count_without_xml(self):
"""Probando el método snippet_pair_count cuando no está el fichero. Para ello se utiliza un nombre de fichero no existente en esta ruta 'script.rst'. .. Nota:: se acerca bastante al nombre del fichero que aparec... | stack_v2_sparse_classes_36k_train_018516 | 2,468 | no_license | [
{
"docstring": "Probando el método snippet_pair_count cuando no está el fichero. Para ello se utiliza un nombre de fichero no existente en esta ruta 'script.rst'. .. Nota:: se acerca bastante al nombre del fichero que aparece allí que es scripts.rst, es intencional la selección de este nombre para que parezca q... | 2 | stack_v2_sparse_classes_30k_train_000563 | Implement the Python class `test_UCXI_snippet_pair_count` described below.
Class description:
Implement the test_UCXI_snippet_pair_count class.
Method signatures and docstrings:
- def test_snippet_pair_count_without_xml(self): Probando el método snippet_pair_count cuando no está el fichero. Para ello se utiliza un no... | Implement the Python class `test_UCXI_snippet_pair_count` described below.
Class description:
Implement the test_UCXI_snippet_pair_count class.
Method signatures and docstrings:
- def test_snippet_pair_count_without_xml(self): Probando el método snippet_pair_count cuando no está el fichero. Para ello se utiliza un no... | 91bb65e6ce014257dec9c3e071a6c43796916005 | <|skeleton|>
class test_UCXI_snippet_pair_count:
def test_snippet_pair_count_without_xml(self):
"""Probando el método snippet_pair_count cuando no está el fichero. Para ello se utiliza un nombre de fichero no existente en esta ruta 'script.rst'. .. Nota:: se acerca bastante al nombre del fichero que aparec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test_UCXI_snippet_pair_count:
def test_snippet_pair_count_without_xml(self):
"""Probando el método snippet_pair_count cuando no está el fichero. Para ello se utiliza un nombre de fichero no existente en esta ruta 'script.rst'. .. Nota:: se acerca bastante al nombre del fichero que aparece allí que es ... | the_stack_v2_python_sparse | scripts/test_update_xml_info.py | sorice/QtNLP-Linguist | train | 0 | |
d9f63b1a4634f19267f5e865b78daf1d9ceefc15 | [
"self.protected_count = protected_count\nself.protected_size = protected_size\nself.unprotected_count = unprotected_count\nself.unprotected_size = unprotected_size",
"if dictionary is None:\n return None\nprotected_count = dictionary.get('protectedCount')\nprotected_size = dictionary.get('protectedSize')\nunpr... | <|body_start_0|>
self.protected_count = protected_count
self.protected_size = protected_size
self.unprotected_count = unprotected_count
self.unprotected_size = unprotected_size
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
protected_count... | Implementation of the 'ProtectionSummary' model. Specifies the number of protected and unprotected objects, and their sizes information of the given entity. Attributes: protected_count (long|int): Specifies the number of objects that are protected under the given entity. protected_size (long|int): Specifies the total s... | ProtectionSummary | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectionSummary:
"""Implementation of the 'ProtectionSummary' model. Specifies the number of protected and unprotected objects, and their sizes information of the given entity. Attributes: protected_count (long|int): Specifies the number of objects that are protected under the given entity. pro... | stack_v2_sparse_classes_36k_train_018517 | 2,551 | permissive | [
{
"docstring": "Constructor for the ProtectionSummary class",
"name": "__init__",
"signature": "def __init__(self, protected_count=None, protected_size=None, unprotected_count=None, unprotected_size=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (d... | 2 | stack_v2_sparse_classes_30k_train_007741 | Implement the Python class `ProtectionSummary` described below.
Class description:
Implementation of the 'ProtectionSummary' model. Specifies the number of protected and unprotected objects, and their sizes information of the given entity. Attributes: protected_count (long|int): Specifies the number of objects that ar... | Implement the Python class `ProtectionSummary` described below.
Class description:
Implementation of the 'ProtectionSummary' model. Specifies the number of protected and unprotected objects, and their sizes information of the given entity. Attributes: protected_count (long|int): Specifies the number of objects that ar... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ProtectionSummary:
"""Implementation of the 'ProtectionSummary' model. Specifies the number of protected and unprotected objects, and their sizes information of the given entity. Attributes: protected_count (long|int): Specifies the number of objects that are protected under the given entity. pro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtectionSummary:
"""Implementation of the 'ProtectionSummary' model. Specifies the number of protected and unprotected objects, and their sizes information of the given entity. Attributes: protected_count (long|int): Specifies the number of objects that are protected under the given entity. protected_size (... | the_stack_v2_python_sparse | cohesity_management_sdk/models/protection_summary.py | cohesity/management-sdk-python | train | 24 |
76fa1c3a03857c79ece5b4b5c73d9c7d3584fa16 | [
"if isinstance(class_names, str):\n class_names = [class_names]\nself.class_names = list() if class_names is None else class_names\nself.exact_match = exact_match\nself.return_types = return_types",
"if not self.class_names:\n return True\nclass_name = edict.get_class_name()\nfor check_name in self.class_na... | <|body_start_0|>
if isinstance(class_names, str):
class_names = [class_names]
self.class_names = list() if class_names is None else class_names
self.exact_match = exact_match
self.return_types = return_types
<|end_body_0|>
<|body_start_1|>
if not self.class_names:
... | Entity iterate class. | EntityIter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntityIter:
"""Entity iterate class."""
def __init__(self, class_names=None, exact_match=True, return_types='index'):
"""Store the base attributes for the generator."""
<|body_0|>
def _is_valid(self, edict):
"""Verify that the edict needs yielded."""
<|bo... | stack_v2_sparse_classes_36k_train_018518 | 4,153 | no_license | [
{
"docstring": "Store the base attributes for the generator.",
"name": "__init__",
"signature": "def __init__(self, class_names=None, exact_match=True, return_types='index')"
},
{
"docstring": "Verify that the edict needs yielded.",
"name": "_is_valid",
"signature": "def _is_valid(self, ... | 2 | stack_v2_sparse_classes_30k_train_005502 | Implement the Python class `EntityIter` described below.
Class description:
Entity iterate class.
Method signatures and docstrings:
- def __init__(self, class_names=None, exact_match=True, return_types='index'): Store the base attributes for the generator.
- def _is_valid(self, edict): Verify that the edict needs yie... | Implement the Python class `EntityIter` described below.
Class description:
Entity iterate class.
Method signatures and docstrings:
- def __init__(self, class_names=None, exact_match=True, return_types='index'): Store the base attributes for the generator.
- def _is_valid(self, edict): Verify that the edict needs yie... | 2d6fc3d0e0534e6eb2046fb11e40706ca42a2a59 | <|skeleton|>
class EntityIter:
"""Entity iterate class."""
def __init__(self, class_names=None, exact_match=True, return_types='index'):
"""Store the base attributes for the generator."""
<|body_0|>
def _is_valid(self, edict):
"""Verify that the edict needs yielded."""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EntityIter:
"""Entity iterate class."""
def __init__(self, class_names=None, exact_match=True, return_types='index'):
"""Store the base attributes for the generator."""
if isinstance(class_names, str):
class_names = [class_names]
self.class_names = list() if class_name... | the_stack_v2_python_sparse | addons/source-python/packages/source-python/filters/entities.py | Doldol/Source.Python | train | 0 |
68dfc0f950ba4cc07bbbcb9aec5ed9e8631ede51 | [
"CtrlDev.__init__(self, parent)\nself._name = u'Memória'\nself._category = 'Sistema'\nself._diag = DiagMemory(self)\nself._compat = CompatMemory(self)\nself._guiClass = GUIMemory",
"self._callInfo()\nself._callCompat()\nself._callDiag()"
] | <|body_start_0|>
CtrlDev.__init__(self, parent)
self._name = u'Memória'
self._category = 'Sistema'
self._diag = DiagMemory(self)
self._compat = CompatMemory(self)
self._guiClass = GUIMemory
<|end_body_0|>
<|body_start_1|>
self._callInfo()
self._callCompat... | Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição. | CtrlMemory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CtrlMemory:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe ba... | stack_v2_sparse_classes_36k_train_018519 | 1,202 | no_license | [
{
"docstring": "Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe base 'CtrlDev'.",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": "Executa o info, compat, diag e cria as telas de exibição.",
"name": "execute_lib",
... | 2 | stack_v2_sparse_classes_30k_train_018675 | Implement the Python class `CtrlMemory` described below.
Class description:
Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição.
Method signatures and docstrings:
- def __init__(self, parent): Construtor que inicializa os atributo... | Implement the Python class `CtrlMemory` described below.
Class description:
Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição.
Method signatures and docstrings:
- def __init__(self, parent): Construtor que inicializa os atributo... | bda0c2c8977dd1246339f1f0f4718d29e8795f21 | <|skeleton|>
class CtrlMemory:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe ba... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CtrlMemory:
"""Estende a classe 'CtrlDev'. Classe de controle que chama os testes de identificação, compatibilidade, diagnóstico e cria a tela de exibição."""
def __init__(self, parent):
"""Construtor que inicializa os atributos '_diag', '_compat' e '_guiClass' definidos na classe base 'CtrlDev'.... | the_stack_v2_python_sparse | src/libs/memory/ctrl_memory.py | adrianomelo/ldc-desktop | train | 1 |
5bc2379fcc2e2765582d5ab63ca3fdf8e4b541b5 | [
"if not root:\n return ''\nstack, all_nodes = ([], [])\nstack.append(root)\nall_nodes.append(str(root.val))\nwhile stack:\n temp = []\n for node in stack:\n if node.left:\n all_nodes.append(str(node.left.val))\n temp.append(node.left)\n else:\n all_nodes.appen... | <|body_start_0|>
if not root:
return ''
stack, all_nodes = ([], [])
stack.append(root)
all_nodes.append(str(root.val))
while stack:
temp = []
for node in stack:
if node.left:
all_nodes.append(str(node.left.va... | 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. Space: O(2^h); h == height of the tree :type data: str :rtype: TreeNode"""
... | stack_v2_sparse_classes_36k_train_018520 | 2,372 | 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. Space: O(2^h); h == height of the tree :type data: str :rtype: TreeNode",
"name": "deseria... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. Space: O(2^h); h == hei... | 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. Space: O(2^h); h == hei... | 1a3c1f4d6e9d3444039f087763b93241f4ba7892 | <|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. Space: O(2^h); h == height of the tree :type data: str :rtype: TreeNode"""
... | 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 ''
stack, all_nodes = ([], [])
stack.append(root)
all_nodes.append(str(root.val))
while stack:
temp = []
... | the_stack_v2_python_sparse | Algorithm/297_Tree_Serialize_Deserialize.py | Gi1ia/TechNoteBook | train | 7 | |
e27ed907252aa88bebc472207016219620ba87bb | [
"self.json_data = json_data\nself.status_code = status_code\nself.exception = exception",
"if self.exception:\n raise self.exception\nreturn self.json_data"
] | <|body_start_0|>
self.json_data = json_data
self.status_code = status_code
self.exception = exception
<|end_body_0|>
<|body_start_1|>
if self.exception:
raise self.exception
return self.json_data
<|end_body_1|>
| Mock response object for testing. | MockResponse | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MockResponse:
"""Mock response object for testing."""
def __init__(self, json_data, status_code, exception=None):
"""Create object."""
<|body_0|>
def json(self):
"""Return json data."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.json_data... | stack_v2_sparse_classes_36k_train_018521 | 17,261 | permissive | [
{
"docstring": "Create object.",
"name": "__init__",
"signature": "def __init__(self, json_data, status_code, exception=None)"
},
{
"docstring": "Return json data.",
"name": "json",
"signature": "def json(self)"
}
] | 2 | null | Implement the Python class `MockResponse` described below.
Class description:
Mock response object for testing.
Method signatures and docstrings:
- def __init__(self, json_data, status_code, exception=None): Create object.
- def json(self): Return json data. | Implement the Python class `MockResponse` described below.
Class description:
Mock response object for testing.
Method signatures and docstrings:
- def __init__(self, json_data, status_code, exception=None): Create object.
- def json(self): Return json data.
<|skeleton|>
class MockResponse:
"""Mock response obje... | 0416e5216eb1ec4b41c8dd4999adde218b1ab2e1 | <|skeleton|>
class MockResponse:
"""Mock response object for testing."""
def __init__(self, json_data, status_code, exception=None):
"""Create object."""
<|body_0|>
def json(self):
"""Return json data."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MockResponse:
"""Mock response object for testing."""
def __init__(self, json_data, status_code, exception=None):
"""Create object."""
self.json_data = json_data
self.status_code = status_code
self.exception = exception
def json(self):
"""Return json data."""
... | the_stack_v2_python_sparse | koku/koku/test_rbac.py | project-koku/koku | train | 225 |
2e9b9afdbb8a65dfe58a6193fd22cd699bef7116 | [
"if self.letter is not None:\n valid = message.startswith(self.letter)\n remaining = message[1:]\n return (valid, remaining)\nremaining = message\nfor rule_num in self.ruleset1:\n rule = rulebook[rule_num]\n valid, remaining = rule.is_valid(remaining, rulebook)\n if not valid:\n break\nif v... | <|body_start_0|>
if self.letter is not None:
valid = message.startswith(self.letter)
remaining = message[1:]
return (valid, remaining)
remaining = message
for rule_num in self.ruleset1:
rule = rulebook[rule_num]
valid, remaining = rule.... | Holds a rule. | Rule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rule:
"""Holds a rule."""
def is_valid(self, message: str, rulebook: Dict[int, object]) -> Tuple[bool, str]:
"""Check whether rule applies. If so return remaining message."""
<|body_0|>
def get_valid_messages(self, prefix: str, rulebook: Dict[int, object], ruleset: List[... | stack_v2_sparse_classes_36k_train_018522 | 5,517 | no_license | [
{
"docstring": "Check whether rule applies. If so return remaining message.",
"name": "is_valid",
"signature": "def is_valid(self, message: str, rulebook: Dict[int, object]) -> Tuple[bool, str]"
},
{
"docstring": "Return all valid messages following on from prefix.",
"name": "get_valid_messa... | 2 | null | Implement the Python class `Rule` described below.
Class description:
Holds a rule.
Method signatures and docstrings:
- def is_valid(self, message: str, rulebook: Dict[int, object]) -> Tuple[bool, str]: Check whether rule applies. If so return remaining message.
- def get_valid_messages(self, prefix: str, rulebook: D... | Implement the Python class `Rule` described below.
Class description:
Holds a rule.
Method signatures and docstrings:
- def is_valid(self, message: str, rulebook: Dict[int, object]) -> Tuple[bool, str]: Check whether rule applies. If so return remaining message.
- def get_valid_messages(self, prefix: str, rulebook: D... | 568effb090668f6eefc483ae9573612e1cef215c | <|skeleton|>
class Rule:
"""Holds a rule."""
def is_valid(self, message: str, rulebook: Dict[int, object]) -> Tuple[bool, str]:
"""Check whether rule applies. If so return remaining message."""
<|body_0|>
def get_valid_messages(self, prefix: str, rulebook: Dict[int, object], ruleset: List[... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Rule:
"""Holds a rule."""
def is_valid(self, message: str, rulebook: Dict[int, object]) -> Tuple[bool, str]:
"""Check whether rule applies. If so return remaining message."""
if self.letter is not None:
valid = message.startswith(self.letter)
remaining = message[1:... | the_stack_v2_python_sparse | 2020/day-19.py | valeonte/advent-of-code-python | train | 0 |
e4791412da0cc3439476c78f0b8df7db19e05957 | [
"data['program'] = get_object_or_404(Program, pk=data['program_id'])\nif not data['program'].financial_aid_availability:\n raise ValidationError('Financial aid not available for this program.')\nif not ProgramEnrollment.objects.filter(program=data['program'], user=self.context['request'].user).exists():\n rai... | <|body_start_0|>
data['program'] = get_object_or_404(Program, pk=data['program_id'])
if not data['program'].financial_aid_availability:
raise ValidationError('Financial aid not available for this program.')
if not ProgramEnrollment.objects.filter(program=data['program'], user=self.co... | Serializer for financial aid requests | FinancialAidRequestSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FinancialAidRequestSerializer:
"""Serializer for financial aid requests"""
def validate(self, data):
"""Validators for this serializer"""
<|body_0|>
def save(self):
"""Override save method"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data['pr... | stack_v2_sparse_classes_36k_train_018523 | 6,670 | no_license | [
{
"docstring": "Validators for this serializer",
"name": "validate",
"signature": "def validate(self, data)"
},
{
"docstring": "Override save method",
"name": "save",
"signature": "def save(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005765 | Implement the Python class `FinancialAidRequestSerializer` described below.
Class description:
Serializer for financial aid requests
Method signatures and docstrings:
- def validate(self, data): Validators for this serializer
- def save(self): Override save method | Implement the Python class `FinancialAidRequestSerializer` described below.
Class description:
Serializer for financial aid requests
Method signatures and docstrings:
- def validate(self, data): Validators for this serializer
- def save(self): Override save method
<|skeleton|>
class FinancialAidRequestSerializer:
... | 3c166bc52dfe8d7aa04f922134f4f6deeff49eb6 | <|skeleton|>
class FinancialAidRequestSerializer:
"""Serializer for financial aid requests"""
def validate(self, data):
"""Validators for this serializer"""
<|body_0|>
def save(self):
"""Override save method"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FinancialAidRequestSerializer:
"""Serializer for financial aid requests"""
def validate(self, data):
"""Validators for this serializer"""
data['program'] = get_object_or_404(Program, pk=data['program_id'])
if not data['program'].financial_aid_availability:
raise Valida... | the_stack_v2_python_sparse | financialaid/serializers.py | avontd2868/micromasters | train | 0 |
1f00e10485a6e620e2f5e880a4c18027fac5162d | [
"def helper(node, level, result):\n if not node:\n return\n if len(result) == level:\n result.append([])\n result[level].append(node.val)\n if node.left:\n helper(node.left, level + 1, result)\n if node.right:\n helper(node.right, level + 1, result)\nif not root:\n retu... | <|body_start_0|>
def helper(node, level, result):
if not node:
return
if len(result) == level:
result.append([])
result[level].append(node.val)
if node.left:
helper(node.left, level + 1, result)
if node.r... | BFS. | Solution | [
"WTFPL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""BFS."""
def levelOrder_1(self, root: TreeNode) -> List[List[int]]:
"""Solve recursively."""
<|body_0|>
def levelOrder_2(self, root: TreeNode) -> List[List[int]]:
"""Solve iteratively by using queue."""
<|body_1|>
def levelOrder_3(self, r... | stack_v2_sparse_classes_36k_train_018524 | 2,036 | permissive | [
{
"docstring": "Solve recursively.",
"name": "levelOrder_1",
"signature": "def levelOrder_1(self, root: TreeNode) -> List[List[int]]"
},
{
"docstring": "Solve iteratively by using queue.",
"name": "levelOrder_2",
"signature": "def levelOrder_2(self, root: TreeNode) -> List[List[int]]"
... | 3 | stack_v2_sparse_classes_30k_test_000205 | Implement the Python class `Solution` described below.
Class description:
BFS.
Method signatures and docstrings:
- def levelOrder_1(self, root: TreeNode) -> List[List[int]]: Solve recursively.
- def levelOrder_2(self, root: TreeNode) -> List[List[int]]: Solve iteratively by using queue.
- def levelOrder_3(self, root:... | Implement the Python class `Solution` described below.
Class description:
BFS.
Method signatures and docstrings:
- def levelOrder_1(self, root: TreeNode) -> List[List[int]]: Solve recursively.
- def levelOrder_2(self, root: TreeNode) -> List[List[int]]: Solve iteratively by using queue.
- def levelOrder_3(self, root:... | 5e5e7098d2310c972314c9c9895aafd048047fe6 | <|skeleton|>
class Solution:
"""BFS."""
def levelOrder_1(self, root: TreeNode) -> List[List[int]]:
"""Solve recursively."""
<|body_0|>
def levelOrder_2(self, root: TreeNode) -> List[List[int]]:
"""Solve iteratively by using queue."""
<|body_1|>
def levelOrder_3(self, r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""BFS."""
def levelOrder_1(self, root: TreeNode) -> List[List[int]]:
"""Solve recursively."""
def helper(node, level, result):
if not node:
return
if len(result) == level:
result.append([])
result[level].append... | the_stack_v2_python_sparse | 0102_Binary_Tree_Level_Order_Traversal.py | imguozr/LC-Solutions | train | 0 |
334839b5ccb98cd07b5b6540cb19f92b130228f6 | [
"def insert(target):\n left, right = (0, len(res) - 1)\n while left <= right:\n mid = left + (right - left) / 2\n if res[mid] < target:\n left = mid + 1\n else:\n right = mid - 1\n if left == len(res):\n res.append(target)\n else:\n res[left] = ta... | <|body_start_0|>
def insert(target):
left, right = (0, len(res) - 1)
while left <= right:
mid = left + (right - left) / 2
if res[mid] < target:
left = mid + 1
else:
right = mid - 1
if left... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxEnvelopes(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
<|body_0|>
def maxEnvelopes2(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def insert... | stack_v2_sparse_classes_36k_train_018525 | 3,342 | no_license | [
{
"docstring": ":type envelopes: List[List[int]] :rtype: int",
"name": "maxEnvelopes",
"signature": "def maxEnvelopes(self, envelopes)"
},
{
"docstring": ":type envelopes: List[List[int]] :rtype: int",
"name": "maxEnvelopes2",
"signature": "def maxEnvelopes2(self, envelopes)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003023 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxEnvelopes(self, envelopes): :type envelopes: List[List[int]] :rtype: int
- def maxEnvelopes2(self, envelopes): :type envelopes: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxEnvelopes(self, envelopes): :type envelopes: List[List[int]] :rtype: int
- def maxEnvelopes2(self, envelopes): :type envelopes: List[List[int]] :rtype: int
<|skeleton|>
c... | 340ae58fb65b97aa6c6ab2daa8cbd82d1093deae | <|skeleton|>
class Solution:
def maxEnvelopes(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
<|body_0|>
def maxEnvelopes2(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxEnvelopes(self, envelopes):
""":type envelopes: List[List[int]] :rtype: int"""
def insert(target):
left, right = (0, len(res) - 1)
while left <= right:
mid = left + (right - left) / 2
if res[mid] < target:
... | the_stack_v2_python_sparse | learnpythonthehardway/russian-doll-envelopes-354.py | dgpllc/leetcode-python | train | 0 | |
e4ee08938bd9106e6c0f1d1ca0d18a06a202bbbd | [
"idxs = []\nfor ii in range(len(unsorted_loglikelihoods)):\n idx = np.where(np.all(sorted_samples[ii] == unsorted_samples, axis=1))[0]\n if len(idx) > 1:\n logger.warning('Multiple likelihood matches found between sorted and unsorted samples. Taking the first match.')\n idxs.append(idx[0])\nreturn u... | <|body_start_0|>
idxs = []
for ii in range(len(unsorted_loglikelihoods)):
idx = np.where(np.all(sorted_samples[ii] == unsorted_samples, axis=1))[0]
if len(idx) > 1:
logger.warning('Multiple likelihood matches found between sorted and unsorted samples. Taking the f... | NestedSampler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NestedSampler:
def reorder_loglikelihoods(unsorted_loglikelihoods, unsorted_samples, sorted_samples):
"""Reorders the stored log-likelihood after they have been reweighted This creates a sorting index by matching the reweights `result.samples` against the raw samples, then uses this inde... | stack_v2_sparse_classes_36k_train_018526 | 36,082 | permissive | [
{
"docstring": "Reorders the stored log-likelihood after they have been reweighted This creates a sorting index by matching the reweights `result.samples` against the raw samples, then uses this index to sort the loglikelihoods Parameters ========== sorted_samples, unsorted_samples: array-like Sorted and unsort... | 2 | stack_v2_sparse_classes_30k_val_000456 | Implement the Python class `NestedSampler` described below.
Class description:
Implement the NestedSampler class.
Method signatures and docstrings:
- def reorder_loglikelihoods(unsorted_loglikelihoods, unsorted_samples, sorted_samples): Reorders the stored log-likelihood after they have been reweighted This creates a... | Implement the Python class `NestedSampler` described below.
Class description:
Implement the NestedSampler class.
Method signatures and docstrings:
- def reorder_loglikelihoods(unsorted_loglikelihoods, unsorted_samples, sorted_samples): Reorders the stored log-likelihood after they have been reweighted This creates a... | 9c1dda6cc1510692ce4ac75c608de5fae53e971c | <|skeleton|>
class NestedSampler:
def reorder_loglikelihoods(unsorted_loglikelihoods, unsorted_samples, sorted_samples):
"""Reorders the stored log-likelihood after they have been reweighted This creates a sorting index by matching the reweights `result.samples` against the raw samples, then uses this inde... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NestedSampler:
def reorder_loglikelihoods(unsorted_loglikelihoods, unsorted_samples, sorted_samples):
"""Reorders the stored log-likelihood after they have been reweighted This creates a sorting index by matching the reweights `result.samples` against the raw samples, then uses this index to sort the ... | the_stack_v2_python_sparse | bilby/core/sampler/base_sampler.py | khunsang/bilby | train | 0 | |
1280ed338b62c620ba48ae107498ae1cf4f1b7f4 | [
"workflow_collection_subscription = get_object_or_404(WorkflowCollectionSubscription, id=id, user=request.user.id)\nserializer = WorkflowCollectionSubscriptionSummarySerializer(workflow_collection_subscription, context={'request': request})\nreturn Response(data=serializer.data)",
"workflow_collection_subscriptio... | <|body_start_0|>
workflow_collection_subscription = get_object_or_404(WorkflowCollectionSubscription, id=id, user=request.user.id)
serializer = WorkflowCollectionSubscriptionSummarySerializer(workflow_collection_subscription, context={'request': request})
return Response(data=serializer.data)
<|... | **Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription resource belonging to the requesting user. | WorkflowCollectionSubscriptionView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkflowCollectionSubscriptionView:
"""**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription resource belonging to the requesting user.... | stack_v2_sparse_classes_36k_train_018527 | 12,221 | permissive | [
{
"docstring": "Retrieve a WorkflowCollectionSubscription representation. Path Parameters: id (str): The UUID of the workflow collection subscription to retrieve. Returns: A HTTP response containing a dict-like JSON representation of the workflow collection subscription with a 200 status code. { \"detail\": \"h... | 2 | stack_v2_sparse_classes_30k_train_002188 | Implement the Python class `WorkflowCollectionSubscriptionView` described below.
Class description:
**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription res... | Implement the Python class `WorkflowCollectionSubscriptionView` described below.
Class description:
**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription res... | dc0e8807263266713d3d7fa46e240e8d72db28d1 | <|skeleton|>
class WorkflowCollectionSubscriptionView:
"""**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription resource belonging to the requesting user.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkflowCollectionSubscriptionView:
"""**Supported HTTP Methods** * Get: Retrieve a summary representation of a particular WorkflowCollectionSubscription resource belonging to the requesting user. * Put: Update a particular WorkflowCollectionSubscription resource belonging to the requesting user."""
def ... | the_stack_v2_python_sparse | django_workflow_system/api/views/user/workflows/subscription.py | kwang1971/django-workflow-system | train | 0 |
13eb71c8cffc308faeb91bdbfb76aae8d47301b7 | [
"if not valid(j1, j2, j3, m1, m2, m3):\n raise ValueError(\"j1, j2, j3 must be integers or half integers the mi's must be so that mi is one of -ji, -ji+1, ..., 0, ..., ji-1, ji where i is 1, 2 or 3.\")\nif trivial_zero(j1, j2, j3, m1, m2, m3):\n return 0.0\nrrfcalc = os.path.abspath(os... | <|body_start_0|>
if not valid(j1, j2, j3, m1, m2, m3):
raise ValueError("j1, j2, j3 must be integers or half integers the mi's must be so that mi is one of -ji, -ji+1, ..., 0, ..., ji-1, ji where i is 1, 2 or 3.")
if trivial_zero(j1, j2, j3, m1, m2, m3):
r... | Provides python access to Anthony Stone's RRF code (v 3.2), via the program rrfcalc, allowing computation of w3j symbols. The program rrfcalc must be installed for this class to work. For some reason wrapping his fortran code directly with f2py ends with errors that are difficult to diagnose. | W3jStone | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class W3jStone:
"""Provides python access to Anthony Stone's RRF code (v 3.2), via the program rrfcalc, allowing computation of w3j symbols. The program rrfcalc must be installed for this class to work. For some reason wrapping his fortran code directly with f2py ends with errors that are difficult to ... | stack_v2_sparse_classes_36k_train_018528 | 25,178 | no_license | [
{
"docstring": "Returns the double precision value of the exact calculation of the 3j symbol: (j1 j2 j3) (m1 m2 m3) Parameters ---------- j1 : float A float representation of an integer or half-integer. j2 : float A float representation of an integer or half-integer. j3 : float A float representation of an inte... | 2 | stack_v2_sparse_classes_30k_train_017056 | Implement the Python class `W3jStone` described below.
Class description:
Provides python access to Anthony Stone's RRF code (v 3.2), via the program rrfcalc, allowing computation of w3j symbols. The program rrfcalc must be installed for this class to work. For some reason wrapping his fortran code directly with f2py ... | Implement the Python class `W3jStone` described below.
Class description:
Provides python access to Anthony Stone's RRF code (v 3.2), via the program rrfcalc, allowing computation of w3j symbols. The program rrfcalc must be installed for this class to work. For some reason wrapping his fortran code directly with f2py ... | 2ce16d776448553e2ae5c45f3cf973c8271aefbf | <|skeleton|>
class W3jStone:
"""Provides python access to Anthony Stone's RRF code (v 3.2), via the program rrfcalc, allowing computation of w3j symbols. The program rrfcalc must be installed for this class to work. For some reason wrapping his fortran code directly with f2py ends with errors that are difficult to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class W3jStone:
"""Provides python access to Anthony Stone's RRF code (v 3.2), via the program rrfcalc, allowing computation of w3j symbols. The program rrfcalc must be installed for this class to work. For some reason wrapping his fortran code directly with f2py ends with errors that are difficult to diagnose."""
... | the_stack_v2_python_sparse | Code/packages/coffee/swsh/w3j/w3j.py | mfuphi/SOFTX_2019_93 | train | 0 |
c8cdaa16bef0dcbdf1f733ca5682b7d0d6649120 | [
"self.modules = []\nfor fname in mod_list:\n self.modules.append([fname, os.path.splitext(fname)[0], None])",
"tileset_data = self.modules[mod_index]\nfilename, modulename, tile_obj = tileset_data\nif not tile_obj:\n obj = __import__('pyslip', globals(), locals(), [modulename])\n tileset = getattr(obj, m... | <|body_start_0|>
self.modules = []
for fname in mod_list:
self.modules.append([fname, os.path.splitext(fname)[0], None])
<|end_body_0|>
<|body_start_1|>
tileset_data = self.modules[mod_index]
filename, modulename, tile_obj = tileset_data
if not tile_obj:
... | A class to manage multiple tileset objects. ts = TilesetManager(source_list) # 'source_list' is list of tileset source modules ts.get_tile_source(index) # 'index' into 'source_list' of source to use Features 'lazy' importing, only imports when the tileset is used the first time. | TilesetManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TilesetManager:
"""A class to manage multiple tileset objects. ts = TilesetManager(source_list) # 'source_list' is list of tileset source modules ts.get_tile_source(index) # 'index' into 'source_list' of source to use Features 'lazy' importing, only imports when the tileset is used the first time... | stack_v2_sparse_classes_36k_train_018529 | 4,444 | no_license | [
{
"docstring": "Create a set of tile sources. mod_list list of module filenames to manage The list is something like: ['open_street_map.py', 'gmt_local.py'] We can access tilesets using the index of the module in the 'mod_list'.",
"name": "__init__",
"signature": "def __init__(self, mod_list)"
},
{
... | 2 | stack_v2_sparse_classes_30k_test_000810 | Implement the Python class `TilesetManager` described below.
Class description:
A class to manage multiple tileset objects. ts = TilesetManager(source_list) # 'source_list' is list of tileset source modules ts.get_tile_source(index) # 'index' into 'source_list' of source to use Features 'lazy' importing, only imports ... | Implement the Python class `TilesetManager` described below.
Class description:
A class to manage multiple tileset objects. ts = TilesetManager(source_list) # 'source_list' is list of tileset source modules ts.get_tile_source(index) # 'index' into 'source_list' of source to use Features 'lazy' importing, only imports ... | 9c641e35f82e304b83576ad9bb5788eee6cb6d2b | <|skeleton|>
class TilesetManager:
"""A class to manage multiple tileset objects. ts = TilesetManager(source_list) # 'source_list' is list of tileset source modules ts.get_tile_source(index) # 'index' into 'source_list' of source to use Features 'lazy' importing, only imports when the tileset is used the first time... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TilesetManager:
"""A class to manage multiple tileset objects. ts = TilesetManager(source_list) # 'source_list' is list of tileset source modules ts.get_tile_source(index) # 'index' into 'source_list' of source to use Features 'lazy' importing, only imports when the tileset is used the first time."""
def... | the_stack_v2_python_sparse | ui/map.py | ahenshaw/rusty_venture | train | 0 |
4064ed106fadaa742a34723a1c84a69e82620870 | [
"global task_tree\n\ndef simulation():\n return None\nself.suspended_tree = task_tree\nself.world_state, self.objects2attached = BulletWorld.current_bullet_world.save_state()\nself.simulated_root = TaskTreeNode(code=Code(simulation))\ntask_tree = self.simulated_root\npybullet.addUserDebugText('Simulating...', [0... | <|body_start_0|>
global task_tree
def simulation():
return None
self.suspended_tree = task_tree
self.world_state, self.objects2attached = BulletWorld.current_bullet_world.save_state()
self.simulated_root = TaskTreeNode(code=Code(simulation))
task_tree = self.... | TaskTree for execution in a 'new' simulation. | SimulatedTaskTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimulatedTaskTree:
"""TaskTree for execution in a 'new' simulation."""
def __enter__(self):
"""At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are then available inside the with statement."""
<|bod... | stack_v2_sparse_classes_36k_train_018530 | 11,387 | no_license | [
{
"docstring": "At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are then available inside the with statement.",
"name": "__enter__",
"signature": "def __enter__(self)"
},
{
"docstring": "Restore the old state at the e... | 2 | stack_v2_sparse_classes_30k_train_020594 | Implement the Python class `SimulatedTaskTree` described below.
Class description:
TaskTree for execution in a 'new' simulation.
Method signatures and docstrings:
- def __enter__(self): At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are t... | Implement the Python class `SimulatedTaskTree` described below.
Class description:
TaskTree for execution in a 'new' simulation.
Method signatures and docstrings:
- def __enter__(self): At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are t... | f9ef666d6d4685660c9517652f2c568ed2c9367c | <|skeleton|>
class SimulatedTaskTree:
"""TaskTree for execution in a 'new' simulation."""
def __enter__(self):
"""At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are then available inside the with statement."""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimulatedTaskTree:
"""TaskTree for execution in a 'new' simulation."""
def __enter__(self):
"""At the beginning of a with statement the current task tree and bullet world will be suspended and remembered. Fresh structures are then available inside the with statement."""
global task_tree
... | the_stack_v2_python_sparse | src/pycram/task.py | cram2/pycram | train | 12 |
3e45d8b67b719e6eac7a123f4b769a6ff260a959 | [
"n = len(matrix[0])\nfor i in range(math.ceil(n / 2)):\n for j in range(i, n - i - 1):\n matrix[i][j], matrix[j][n - 1 - i], matrix[n - 1 - i][n - 1 - j], matrix[n - 1 - j][i] = (matrix[n - 1 - j][i], matrix[i][j], matrix[j][n - 1 - i], matrix[n - 1 - i][n - 1 - j])",
"length = len(matrix)\nfor i in ran... | <|body_start_0|>
n = len(matrix[0])
for i in range(math.ceil(n / 2)):
for j in range(i, n - i - 1):
matrix[i][j], matrix[j][n - 1 - i], matrix[n - 1 - i][n - 1 - j], matrix[n - 1 - j][i] = (matrix[n - 1 - j][i], matrix[i][j], matrix[j][n - 1 - i], matrix[n - 1 - i][n - 1 - j]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate_(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate(self, matrix) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_1|>... | stack_v2_sparse_classes_36k_train_018531 | 1,236 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",
"name": "rotate_",
"signature": "def rotate_(self, matrix)"
},
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"name": "rotate",
"signature": "de... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate_(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate(self, matrix) -> None: Do not return an... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate_(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate(self, matrix) -> None: Do not return an... | 238995bd23c8a6c40c6035890e94baa2473d4bbc | <|skeleton|>
class Solution:
def rotate_(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate(self, matrix) -> None:
"""Do not return anything, modify matrix in-place instead."""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate_(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
n = len(matrix[0])
for i in range(math.ceil(n / 2)):
for j in range(i, n - i - 1):
matrix[i][j], matrix[j][n - 1 - i... | the_stack_v2_python_sparse | problems/RotateImage.py | wan-catherine/Leetcode | train | 5 | |
e29b1886a005525a5b7cb606b498f9dd03946b3e | [
"BaseJaffleCommand.parse_command_line(self, argv)\nif not self.extra_args:\n print('No kernel specified.', file=sys.stderr)\n self.exit(1)\nself.session_id = self.extra_args[0]\ntry:\n status = JaffleStatus.load(self.status_file_path)\n print('status', status)\nexcept FileNotFoundError:\n print('Jaff... | <|body_start_0|>
BaseJaffleCommand.parse_command_line(self, argv)
if not self.extra_args:
print('No kernel specified.', file=sys.stderr)
self.exit(1)
self.session_id = self.extra_args[0]
try:
status = JaffleStatus.load(self.status_file_path)
... | Console for a jaffle kernel. | JaffleConsoleCommand | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JaffleConsoleCommand:
"""Console for a jaffle kernel."""
def parse_command_line(self, argv):
"""Parses comnand line. Parameters ---------- argv : list[str] Command line strings."""
<|body_0|>
def init_shell(self):
"""Initializes the interactive shell and set sign... | stack_v2_sparse_classes_36k_train_018532 | 2,398 | permissive | [
{
"docstring": "Parses comnand line. Parameters ---------- argv : list[str] Command line strings.",
"name": "parse_command_line",
"signature": "def parse_command_line(self, argv)"
},
{
"docstring": "Initializes the interactive shell and set signal handlers.",
"name": "init_shell",
"signa... | 2 | null | Implement the Python class `JaffleConsoleCommand` described below.
Class description:
Console for a jaffle kernel.
Method signatures and docstrings:
- def parse_command_line(self, argv): Parses comnand line. Parameters ---------- argv : list[str] Command line strings.
- def init_shell(self): Initializes the interacti... | Implement the Python class `JaffleConsoleCommand` described below.
Class description:
Console for a jaffle kernel.
Method signatures and docstrings:
- def parse_command_line(self, argv): Parses comnand line. Parameters ---------- argv : list[str] Command line strings.
- def init_shell(self): Initializes the interacti... | ab8352716c973eef9c224ff80d0dd66b95c606a3 | <|skeleton|>
class JaffleConsoleCommand:
"""Console for a jaffle kernel."""
def parse_command_line(self, argv):
"""Parses comnand line. Parameters ---------- argv : list[str] Command line strings."""
<|body_0|>
def init_shell(self):
"""Initializes the interactive shell and set sign... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JaffleConsoleCommand:
"""Console for a jaffle kernel."""
def parse_command_line(self, argv):
"""Parses comnand line. Parameters ---------- argv : list[str] Command line strings."""
BaseJaffleCommand.parse_command_line(self, argv)
if not self.extra_args:
print('No kerne... | the_stack_v2_python_sparse | jaffle/command/console/command.py | daniel-covelli/jaffle | train | 0 |
4eb6d2bb4cb8366e248851b40f809caa48b10f4e | [
"operation_settings_objs = OperationSettings.objects.filter(owner=request.manager)\nif operation_settings_objs.count() == 0:\n operation_settings = OperationSettings.objects.create(owner=request.manager)\nelse:\n operation_settings = operation_settings_objs[0]\nc = RequestContext(request, {'first_nav_name': F... | <|body_start_0|>
operation_settings_objs = OperationSettings.objects.filter(owner=request.manager)
if operation_settings_objs.count() == 0:
operation_settings = OperationSettings.objects.create(owner=request.manager)
else:
operation_settings = operation_settings_objs[0]
... | DirectFollow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectFollow:
def get(request):
"""快速关注页面"""
<|body_0|>
def api_post(request):
"""更新快速关注信息"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
operation_settings_objs = OperationSettings.objects.filter(owner=request.manager)
if operation_setting... | stack_v2_sparse_classes_36k_train_018533 | 1,715 | no_license | [
{
"docstring": "快速关注页面",
"name": "get",
"signature": "def get(request)"
},
{
"docstring": "更新快速关注信息",
"name": "api_post",
"signature": "def api_post(request)"
}
] | 2 | null | Implement the Python class `DirectFollow` described below.
Class description:
Implement the DirectFollow class.
Method signatures and docstrings:
- def get(request): 快速关注页面
- def api_post(request): 更新快速关注信息 | Implement the Python class `DirectFollow` described below.
Class description:
Implement the DirectFollow class.
Method signatures and docstrings:
- def get(request): 快速关注页面
- def api_post(request): 更新快速关注信息
<|skeleton|>
class DirectFollow:
def get(request):
"""快速关注页面"""
<|body_0|>
def api_p... | 8b2f7befe92841bcc35e0e60cac5958ef3f3af54 | <|skeleton|>
class DirectFollow:
def get(request):
"""快速关注页面"""
<|body_0|>
def api_post(request):
"""更新快速关注信息"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DirectFollow:
def get(request):
"""快速关注页面"""
operation_settings_objs = OperationSettings.objects.filter(owner=request.manager)
if operation_settings_objs.count() == 0:
operation_settings = OperationSettings.objects.create(owner=request.manager)
else:
ope... | the_stack_v2_python_sparse | weapp/weixin2/mp_user/direct_follow.py | chengdg/weizoom | train | 1 | |
0582fe1d0c3100afd8d4baa29f0fbca1dbf47097 | [
"super(LikelihoodEstimator, self).__init__()\nself.mean_block = tf.keras.Sequential([layers.Dense(output_dim), layers.BatchNormalization(), layers.ELU(), layers.Dense(output_dim)])\nself.logvar_block = tf.keras.Sequential([layers.Dense(output_dim), layers.BatchNormalization(), layers.ELU(), layers.Dense(output_dim,... | <|body_start_0|>
super(LikelihoodEstimator, self).__init__()
self.mean_block = tf.keras.Sequential([layers.Dense(output_dim), layers.BatchNormalization(), layers.ELU(), layers.Dense(output_dim)])
self.logvar_block = tf.keras.Sequential([layers.Dense(output_dim), layers.BatchNormalization(), laye... | Network to estimate the log-likelihood. | LikelihoodEstimator | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LikelihoodEstimator:
"""Network to estimate the log-likelihood."""
def __init__(self, output_dim):
"""Initializer. Args: output_dim: An integer for the dimension of the output."""
<|body_0|>
def call(self, inputs, training=False):
"""Computes a forward pass. Args... | stack_v2_sparse_classes_36k_train_018534 | 30,548 | permissive | [
{
"docstring": "Initializer. Args: output_dim: An integer for the dimension of the output.",
"name": "__init__",
"signature": "def __init__(self, output_dim)"
},
{
"docstring": "Computes a forward pass. Args: inputs: An input tensor. training: A boolean indicating whether the call is for trainin... | 2 | null | Implement the Python class `LikelihoodEstimator` described below.
Class description:
Network to estimate the log-likelihood.
Method signatures and docstrings:
- def __init__(self, output_dim): Initializer. Args: output_dim: An integer for the dimension of the output.
- def call(self, inputs, training=False): Computes... | Implement the Python class `LikelihoodEstimator` described below.
Class description:
Network to estimate the log-likelihood.
Method signatures and docstrings:
- def __init__(self, output_dim): Initializer. Args: output_dim: An integer for the dimension of the output.
- def call(self, inputs, training=False): Computes... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class LikelihoodEstimator:
"""Network to estimate the log-likelihood."""
def __init__(self, output_dim):
"""Initializer. Args: output_dim: An integer for the dimension of the output."""
<|body_0|>
def call(self, inputs, training=False):
"""Computes a forward pass. Args... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LikelihoodEstimator:
"""Network to estimate the log-likelihood."""
def __init__(self, output_dim):
"""Initializer. Args: output_dim: An integer for the dimension of the output."""
super(LikelihoodEstimator, self).__init__()
self.mean_block = tf.keras.Sequential([layers.Dense(outpu... | the_stack_v2_python_sparse | poem/cv_mim/models.py | Jimmy-INL/google-research | train | 1 |
78972ff408306570ac5e4a6af7fa578c5d420361 | [
"x = _generate_products(100000)\nwith self.session() as sess:\n x_ph = tf.placeholder(x.dtype, len(x))\n angle_ph = losses.safe_acosd(x_ph)\n angle, d_angle = sess.run((angle_ph, tf.gradients(tf.reduce_sum(angle_ph), x_ph)), feed_dict={x_ph: x})\n for v in [angle, d_angle]:\n self.assertTrue(np.a... | <|body_start_0|>
x = _generate_products(100000)
with self.session() as sess:
x_ph = tf.placeholder(x.dtype, len(x))
angle_ph = losses.safe_acosd(x_ph)
angle, d_angle = sess.run((angle_ph, tf.gradients(tf.reduce_sum(angle_ph), x_ph)), feed_dict={x_ph: x})
f... | Tests losses.safe_acosd(). | SafeArcCosDTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SafeArcCosDTest:
"""Tests losses.safe_acosd()."""
def testFiniteAngleAndGradient(self):
"""Test that the angle and the gradient are finite for all x in [-1, 1]."""
<|body_0|>
def testAccurateAngle(self):
"""Test that the angle is very accurate."""
<|body_... | stack_v2_sparse_classes_36k_train_018535 | 17,094 | permissive | [
{
"docstring": "Test that the angle and the gradient are finite for all x in [-1, 1].",
"name": "testFiniteAngleAndGradient",
"signature": "def testFiniteAngleAndGradient(self)"
},
{
"docstring": "Test that the angle is very accurate.",
"name": "testAccurateAngle",
"signature": "def test... | 3 | stack_v2_sparse_classes_30k_train_014283 | Implement the Python class `SafeArcCosDTest` described below.
Class description:
Tests losses.safe_acosd().
Method signatures and docstrings:
- def testFiniteAngleAndGradient(self): Test that the angle and the gradient are finite for all x in [-1, 1].
- def testAccurateAngle(self): Test that the angle is very accurat... | Implement the Python class `SafeArcCosDTest` described below.
Class description:
Tests losses.safe_acosd().
Method signatures and docstrings:
- def testFiniteAngleAndGradient(self): Test that the angle and the gradient are finite for all x in [-1, 1].
- def testAccurateAngle(self): Test that the angle is very accurat... | c52b225082327ea34bed80357dbff004fc9926ba | <|skeleton|>
class SafeArcCosDTest:
"""Tests losses.safe_acosd()."""
def testFiniteAngleAndGradient(self):
"""Test that the angle and the gradient are finite for all x in [-1, 1]."""
<|body_0|>
def testAccurateAngle(self):
"""Test that the angle is very accurate."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SafeArcCosDTest:
"""Tests losses.safe_acosd()."""
def testFiniteAngleAndGradient(self):
"""Test that the angle and the gradient are finite for all x in [-1, 1]."""
x = _generate_products(100000)
with self.session() as sess:
x_ph = tf.placeholder(x.dtype, len(x))
... | the_stack_v2_python_sparse | python/losses_test.py | mahmoudnafifi/ffcc | train | 1 |
bde5734a5b56400bfe2e61540ec4c1636e1c23c6 | [
"self._subsystems = subsystems\nself._x_dims = [sys._x_dim for sys in subsystems]\nx_dim = sum(self._x_dims)\nu_dims = [sys._u_dim for sys in subsystems]\nsuper(ProductMultiPlayerDynamicalSystem, self).__init__(x_dim, u_dims, T)",
"subsystem_xs = np.split(x, np.cumsum(self._x_dims[:-1]), axis=0)\nx_dot_list = [sy... | <|body_start_0|>
self._subsystems = subsystems
self._x_dims = [sys._x_dim for sys in subsystems]
x_dim = sum(self._x_dims)
u_dims = [sys._u_dim for sys in subsystems]
super(ProductMultiPlayerDynamicalSystem, self).__init__(x_dim, u_dims, T)
<|end_body_0|>
<|body_start_1|>
... | ProductMultiPlayerDynamicalSystem | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductMultiPlayerDynamicalSystem:
def __init__(self, subsystems, T=0.1):
"""Initialize with a list of dynamical systems. :param subsystems: list of component (single-player) dynamical systems :type subsystems: [DynamicalSystem] :param T: time interval :type T: float"""
<|body_0|... | stack_v2_sparse_classes_36k_train_018536 | 5,130 | permissive | [
{
"docstring": "Initialize with a list of dynamical systems. :param subsystems: list of component (single-player) dynamical systems :type subsystems: [DynamicalSystem] :param T: time interval :type T: float",
"name": "__init__",
"signature": "def __init__(self, subsystems, T=0.1)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_test_000741 | Implement the Python class `ProductMultiPlayerDynamicalSystem` described below.
Class description:
Implement the ProductMultiPlayerDynamicalSystem class.
Method signatures and docstrings:
- def __init__(self, subsystems, T=0.1): Initialize with a list of dynamical systems. :param subsystems: list of component (single... | Implement the Python class `ProductMultiPlayerDynamicalSystem` described below.
Class description:
Implement the ProductMultiPlayerDynamicalSystem class.
Method signatures and docstrings:
- def __init__(self, subsystems, T=0.1): Initialize with a list of dynamical systems. :param subsystems: list of component (single... | fbe9501a51e33498e0b916e2a870dada7c61df57 | <|skeleton|>
class ProductMultiPlayerDynamicalSystem:
def __init__(self, subsystems, T=0.1):
"""Initialize with a list of dynamical systems. :param subsystems: list of component (single-player) dynamical systems :type subsystems: [DynamicalSystem] :param T: time interval :type T: float"""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductMultiPlayerDynamicalSystem:
def __init__(self, subsystems, T=0.1):
"""Initialize with a list of dynamical systems. :param subsystems: list of component (single-player) dynamical systems :type subsystems: [DynamicalSystem] :param T: time interval :type T: float"""
self._subsystems = subs... | the_stack_v2_python_sparse | python/product_multiplayer_dynamical_system.py | HJReachability/ilqgames | train | 89 | |
6de6495f5d64be3fd6c6c388574d69e1ab0249da | [
"super(LMEvaluator, self).__init__(val_iter, reporter, device=-1)\nself.model = eval_model\nself.device = device",
"val_iter = self.get_iterator('main')\nloss = 0\nnll = 0\ncount = 0\nself.model.eval()\nwith torch.no_grad():\n for batch in copy.copy(val_iter):\n x, t = concat_examples(batch, device=self... | <|body_start_0|>
super(LMEvaluator, self).__init__(val_iter, reporter, device=-1)
self.model = eval_model
self.device = device
<|end_body_0|>
<|body_start_1|>
val_iter = self.get_iterator('main')
loss = 0
nll = 0
count = 0
self.model.eval()
with t... | A custom evaluator for a pytorch LM. | LMEvaluator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LMEvaluator:
"""A custom evaluator for a pytorch LM."""
def __init__(self, val_iter, eval_model, reporter, device):
"""Initialize class. :param chainer.dataset.Iterator val_iter : The validation iterator :param LMInterface eval_model : The model to evaluate :param chainer.Reporter re... | stack_v2_sparse_classes_36k_train_018537 | 14,856 | permissive | [
{
"docstring": "Initialize class. :param chainer.dataset.Iterator val_iter : The validation iterator :param LMInterface eval_model : The model to evaluate :param chainer.Reporter reporter : The observations reporter :param int device : The device id to use",
"name": "__init__",
"signature": "def __init_... | 2 | null | Implement the Python class `LMEvaluator` described below.
Class description:
A custom evaluator for a pytorch LM.
Method signatures and docstrings:
- def __init__(self, val_iter, eval_model, reporter, device): Initialize class. :param chainer.dataset.Iterator val_iter : The validation iterator :param LMInterface eval... | Implement the Python class `LMEvaluator` described below.
Class description:
A custom evaluator for a pytorch LM.
Method signatures and docstrings:
- def __init__(self, val_iter, eval_model, reporter, device): Initialize class. :param chainer.dataset.Iterator val_iter : The validation iterator :param LMInterface eval... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class LMEvaluator:
"""A custom evaluator for a pytorch LM."""
def __init__(self, val_iter, eval_model, reporter, device):
"""Initialize class. :param chainer.dataset.Iterator val_iter : The validation iterator :param LMInterface eval_model : The model to evaluate :param chainer.Reporter re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LMEvaluator:
"""A custom evaluator for a pytorch LM."""
def __init__(self, val_iter, eval_model, reporter, device):
"""Initialize class. :param chainer.dataset.Iterator val_iter : The validation iterator :param LMInterface eval_model : The model to evaluate :param chainer.Reporter reporter : The ... | the_stack_v2_python_sparse | espnet/lm/pytorch_backend/lm.py | espnet/espnet | train | 7,242 |
5dc93c67927189ac1133e832d97a6a5813073590 | [
"self._setup(field_mapping={'properties': FieldMapping(SimulationProperties.parse, SimulationProperties.toJSONObject), 'sources': ListFieldMapping(SimulationSource.parse, SimulationSource.toJSONObject, [])})\nif properties is not None:\n self.properties = properties\nelif simulation_name is not None:\n self.p... | <|body_start_0|>
self._setup(field_mapping={'properties': FieldMapping(SimulationProperties.parse, SimulationProperties.toJSONObject), 'sources': ListFieldMapping(SimulationSource.parse, SimulationSource.toJSONObject, [])})
if properties is not None:
self.properties = properties
elif... | FeedSimulationConfiguration API Object which could be passed to WSO2 SP Event Simulator via EventSimulatorClient. | FeedSimulationConfiguration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeedSimulationConfiguration:
"""FeedSimulationConfiguration API Object which could be passed to WSO2 SP Event Simulator via EventSimulatorClient."""
def __init__(self, simulation_name=None, properties=None):
"""Instantiates FeedSimulationConfiguration. :param simulation_name: name of... | stack_v2_sparse_classes_36k_train_018538 | 2,279 | permissive | [
{
"docstring": "Instantiates FeedSimulationConfiguration. :param simulation_name: name of simulation :param properties: SimulationProperties",
"name": "__init__",
"signature": "def __init__(self, simulation_name=None, properties=None)"
},
{
"docstring": "Converts a Python Class Object (from JSON... | 2 | stack_v2_sparse_classes_30k_train_004883 | Implement the Python class `FeedSimulationConfiguration` described below.
Class description:
FeedSimulationConfiguration API Object which could be passed to WSO2 SP Event Simulator via EventSimulatorClient.
Method signatures and docstrings:
- def __init__(self, simulation_name=None, properties=None): Instantiates Fee... | Implement the Python class `FeedSimulationConfiguration` described below.
Class description:
FeedSimulationConfiguration API Object which could be passed to WSO2 SP Event Simulator via EventSimulatorClient.
Method signatures and docstrings:
- def __init__(self, simulation_name=None, properties=None): Instantiates Fee... | 343db17ca1331d0a53335478d01bba69338cf24b | <|skeleton|>
class FeedSimulationConfiguration:
"""FeedSimulationConfiguration API Object which could be passed to WSO2 SP Event Simulator via EventSimulatorClient."""
def __init__(self, simulation_name=None, properties=None):
"""Instantiates FeedSimulationConfiguration. :param simulation_name: name of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeedSimulationConfiguration:
"""FeedSimulationConfiguration API Object which could be passed to WSO2 SP Event Simulator via EventSimulatorClient."""
def __init__(self, simulation_name=None, properties=None):
"""Instantiates FeedSimulationConfiguration. :param simulation_name: name of simulation :... | the_stack_v2_python_sparse | PySiddhi/sp/EventSimulator/FeedSimulationConfiguration.py | whummer/PySiddhi | train | 0 |
5412e603a0a085ed5f007afab4a32fdc4bbaae54 | [
"super(ResConfigSettings, self).set_values()\nParam = self.env['ir.config_parameter'].sudo()\nParam.set_param('stock.group_stock_production_lot', self.group_stock_production_lot)",
"res = super(ResConfigSettings, self).get_values()\nparams = self.env['ir.config_parameter'].sudo()\nres.update(group_stock_productio... | <|body_start_0|>
super(ResConfigSettings, self).set_values()
Param = self.env['ir.config_parameter'].sudo()
Param.set_param('stock.group_stock_production_lot', self.group_stock_production_lot)
<|end_body_0|>
<|body_start_1|>
res = super(ResConfigSettings, self).get_values()
para... | ResConfigSettings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResConfigSettings:
def set_values(self):
"""Set values for configuration"""
<|body_0|>
def get_values(self):
"""Get values for configuration"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(ResConfigSettings, self).set_values()
Param = ... | stack_v2_sparse_classes_36k_train_018539 | 826 | no_license | [
{
"docstring": "Set values for configuration",
"name": "set_values",
"signature": "def set_values(self)"
},
{
"docstring": "Get values for configuration",
"name": "get_values",
"signature": "def get_values(self)"
}
] | 2 | null | Implement the Python class `ResConfigSettings` described below.
Class description:
Implement the ResConfigSettings class.
Method signatures and docstrings:
- def set_values(self): Set values for configuration
- def get_values(self): Get values for configuration | Implement the Python class `ResConfigSettings` described below.
Class description:
Implement the ResConfigSettings class.
Method signatures and docstrings:
- def set_values(self): Set values for configuration
- def get_values(self): Get values for configuration
<|skeleton|>
class ResConfigSettings:
def set_valu... | 6e3117aa3bf0d1bed101b2cedd89f5d26911277e | <|skeleton|>
class ResConfigSettings:
def set_values(self):
"""Set values for configuration"""
<|body_0|>
def get_values(self):
"""Get values for configuration"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResConfigSettings:
def set_values(self):
"""Set values for configuration"""
super(ResConfigSettings, self).set_values()
Param = self.env['ir.config_parameter'].sudo()
Param.set_param('stock.group_stock_production_lot', self.group_stock_production_lot)
def get_values(self):... | the_stack_v2_python_sparse | silent_inventory_adjustment/models/res_config_settings.py | AkshayKvenu/advanced_parallel | train | 1 | |
331f7416945d6b97a1324bb0ba1a0fd076c18677 | [
"lookup_url_kwarg = self.lookup_url_kwarg or self.lookup_field\nlookup = self.kwargs.get(lookup_url_kwarg, None)\nif lookup is not None:\n return VideoUsers.objects.filter(video__hash_key=lookup).select_related('user', 'video').order_by('created_at')\nreturn VideoUsers.objects.none()",
"if self.request.method ... | <|body_start_0|>
lookup_url_kwarg = self.lookup_url_kwarg or self.lookup_field
lookup = self.kwargs.get(lookup_url_kwarg, None)
if lookup is not None:
return VideoUsers.objects.filter(video__hash_key=lookup).select_related('user', 'video').order_by('created_at')
return VideoU... | List all users of a video and add/invite new users. ## Reading ### Permissions * Only authenticated users can read this endpoint. * Only associated users can read this endpoint for a given video. ### Fields Reading this endpoint returns a list of VideoUser objects Name | Description | Type ----------------- | ---------... | VideoUserList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoUserList:
"""List all users of a video and add/invite new users. ## Reading ### Permissions * Only authenticated users can read this endpoint. * Only associated users can read this endpoint for a given video. ### Fields Reading this endpoint returns a list of VideoUser objects Name | Descrip... | stack_v2_sparse_classes_36k_train_018540 | 40,640 | no_license | [
{
"docstring": "This view should return a list of all associated users of a video as determined by the lookup parameters of the view.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "a POST request implies video user creation so return the serializer for video u... | 2 | stack_v2_sparse_classes_30k_train_008360 | Implement the Python class `VideoUserList` described below.
Class description:
List all users of a video and add/invite new users. ## Reading ### Permissions * Only authenticated users can read this endpoint. * Only associated users can read this endpoint for a given video. ### Fields Reading this endpoint returns a l... | Implement the Python class `VideoUserList` described below.
Class description:
List all users of a video and add/invite new users. ## Reading ### Permissions * Only authenticated users can read this endpoint. * Only associated users can read this endpoint for a given video. ### Fields Reading this endpoint returns a l... | 1f4b4cd74c9b4280437f73bdfef4491536194eeb | <|skeleton|>
class VideoUserList:
"""List all users of a video and add/invite new users. ## Reading ### Permissions * Only authenticated users can read this endpoint. * Only associated users can read this endpoint for a given video. ### Fields Reading this endpoint returns a list of VideoUser objects Name | Descrip... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VideoUserList:
"""List all users of a video and add/invite new users. ## Reading ### Permissions * Only authenticated users can read this endpoint. * Only associated users can read this endpoint for a given video. ### Fields Reading this endpoint returns a list of VideoUser objects Name | Description | Type -... | the_stack_v2_python_sparse | gravvy/apps/video/views.py | nceruchalu/gravvy-server | train | 1 |
5ca3da2a310e40bc7513d5b487fd72ee0ea7e586 | [
"if not root:\n return True\nreturn self.subroutine(root.left, root.right)",
"if not left and (not right):\n return True\nif not left and right or (left and (not right)):\n return False\nif left.val != right.val:\n return False\nelse:\n out_pair = self.subroutine(left.left, right.right)\n in_pai... | <|body_start_0|>
if not root:
return True
return self.subroutine(root.left, root.right)
<|end_body_0|>
<|body_start_1|>
if not left and (not right):
return True
if not left and right or (left and (not right)):
return False
if left.val != right... | Leet101 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Leet101:
def is_symmetric(self, root):
"""Find if tree is symmetric. Args: root -- TreeNode Returns: True if tree is symmetric. False otherwise."""
<|body_0|>
def subroutine(self, left, right):
"""Subroutine to check if left and right subtrees are symmetric. Args: le... | stack_v2_sparse_classes_36k_train_018541 | 1,323 | no_license | [
{
"docstring": "Find if tree is symmetric. Args: root -- TreeNode Returns: True if tree is symmetric. False otherwise.",
"name": "is_symmetric",
"signature": "def is_symmetric(self, root)"
},
{
"docstring": "Subroutine to check if left and right subtrees are symmetric. Args: left -- TreeNode rig... | 2 | null | Implement the Python class `Leet101` described below.
Class description:
Implement the Leet101 class.
Method signatures and docstrings:
- def is_symmetric(self, root): Find if tree is symmetric. Args: root -- TreeNode Returns: True if tree is symmetric. False otherwise.
- def subroutine(self, left, right): Subroutine... | Implement the Python class `Leet101` described below.
Class description:
Implement the Leet101 class.
Method signatures and docstrings:
- def is_symmetric(self, root): Find if tree is symmetric. Args: root -- TreeNode Returns: True if tree is symmetric. False otherwise.
- def subroutine(self, left, right): Subroutine... | b0cfcfa1eff0101cf8e0e3fb9db55fb83f566f6f | <|skeleton|>
class Leet101:
def is_symmetric(self, root):
"""Find if tree is symmetric. Args: root -- TreeNode Returns: True if tree is symmetric. False otherwise."""
<|body_0|>
def subroutine(self, left, right):
"""Subroutine to check if left and right subtrees are symmetric. Args: le... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Leet101:
def is_symmetric(self, root):
"""Find if tree is symmetric. Args: root -- TreeNode Returns: True if tree is symmetric. False otherwise."""
if not root:
return True
return self.subroutine(root.left, root.right)
def subroutine(self, left, right):
"""Subr... | the_stack_v2_python_sparse | archive/algorithms-leetcode/leet101.py | riehseun/software-engineering | train | 0 | |
375710431123c81b4a5cb981bcca1f4ecbc9bf97 | [
"address = quote_plus(address, safe=',')\nmaps_address = 'http://maps.apple.com/?address=' + address\nprocess = Popen(['open', '-a', 'Maps', maps_address], stdout=PIPE, stderr=PIPE)\nstdout, stderr = process.communicate()",
"name = kwargs.get('name', 'Selected Location')\nmaps_address = 'http://maps.apple.com/?ll... | <|body_start_0|>
address = quote_plus(address, safe=',')
maps_address = 'http://maps.apple.com/?address=' + address
process = Popen(['open', '-a', 'Maps', maps_address], stdout=PIPE, stderr=PIPE)
stdout, stderr = process.communicate()
<|end_body_0|>
<|body_start_1|>
name = kwarg... | Implementation of MacOS Maps API. | MacOSMaps | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MacOSMaps:
"""Implementation of MacOS Maps API."""
def _open_by_address(self, address, **kwargs):
""":param address: An address string that geolocation can understand."""
<|body_0|>
def _open_by_lat_long(self, latitude, longitude, **kwargs):
"""Open a coordinate ... | stack_v2_sparse_classes_36k_train_018542 | 2,777 | permissive | [
{
"docstring": ":param address: An address string that geolocation can understand.",
"name": "_open_by_address",
"signature": "def _open_by_address(self, address, **kwargs)"
},
{
"docstring": "Open a coordinate span denoting a latitudinal delta and a longitudinal delta (similar to MKCoordinateSp... | 4 | stack_v2_sparse_classes_30k_train_021608 | Implement the Python class `MacOSMaps` described below.
Class description:
Implementation of MacOS Maps API.
Method signatures and docstrings:
- def _open_by_address(self, address, **kwargs): :param address: An address string that geolocation can understand.
- def _open_by_lat_long(self, latitude, longitude, **kwargs... | Implement the Python class `MacOSMaps` described below.
Class description:
Implementation of MacOS Maps API.
Method signatures and docstrings:
- def _open_by_address(self, address, **kwargs): :param address: An address string that geolocation can understand.
- def _open_by_lat_long(self, latitude, longitude, **kwargs... | d8a2b3d16b12fc54667744a092a453ad007c9448 | <|skeleton|>
class MacOSMaps:
"""Implementation of MacOS Maps API."""
def _open_by_address(self, address, **kwargs):
""":param address: An address string that geolocation can understand."""
<|body_0|>
def _open_by_lat_long(self, latitude, longitude, **kwargs):
"""Open a coordinate ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MacOSMaps:
"""Implementation of MacOS Maps API."""
def _open_by_address(self, address, **kwargs):
""":param address: An address string that geolocation can understand."""
address = quote_plus(address, safe=',')
maps_address = 'http://maps.apple.com/?address=' + address
pro... | the_stack_v2_python_sparse | plyer/platforms/macosx/maps.py | kivy/plyer | train | 1,516 |
9faf7adc6a822906ed35f15e43078d10d771428c | [
"env.switch[1].ui.create_mirror_session(1, 2, 'IngressAndEgress')\nsessions = env.switch[1].ui.get_mirroring_sessions()\nsession = {'sourcePortId': 1, 'destinationPortId': 2, 'mirroringMode': 'IngressAndEgress'}\nassert session in sessions, 'Mirroring session has not been created'\nenv.switch[1].ui.delete_mirroring... | <|body_start_0|>
env.switch[1].ui.create_mirror_session(1, 2, 'IngressAndEgress')
sessions = env.switch[1].ui.get_mirroring_sessions()
session = {'sourcePortId': 1, 'destinationPortId': 2, 'mirroringMode': 'IngressAndEgress'}
assert session in sessions, 'Mirroring session has not been cr... | @description Suite for Mirroring testing | TestMirroringSamples | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestMirroringSamples:
"""@description Suite for Mirroring testing"""
def test_configure_mirroring_session(self, env):
"""@brief Verify that simple Mirroring session can be created and deleted @steps -# Create simple mirroring session. -# Verify session has been created. -# Delete mir... | stack_v2_sparse_classes_36k_train_018543 | 5,725 | permissive | [
{
"docstring": "@brief Verify that simple Mirroring session can be created and deleted @steps -# Create simple mirroring session. -# Verify session has been created. -# Delete mirroring session. -# Verify session has been deleted. @endsteps",
"name": "test_configure_mirroring_session",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_008204 | Implement the Python class `TestMirroringSamples` described below.
Class description:
@description Suite for Mirroring testing
Method signatures and docstrings:
- def test_configure_mirroring_session(self, env): @brief Verify that simple Mirroring session can be created and deleted @steps -# Create simple mirroring s... | Implement the Python class `TestMirroringSamples` described below.
Class description:
@description Suite for Mirroring testing
Method signatures and docstrings:
- def test_configure_mirroring_session(self, env): @brief Verify that simple Mirroring session can be created and deleted @steps -# Create simple mirroring s... | 18c532fcea7b98cbeadd68e82bdad78ebaaecf4e | <|skeleton|>
class TestMirroringSamples:
"""@description Suite for Mirroring testing"""
def test_configure_mirroring_session(self, env):
"""@brief Verify that simple Mirroring session can be created and deleted @steps -# Create simple mirroring session. -# Verify session has been created. -# Delete mir... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestMirroringSamples:
"""@description Suite for Mirroring testing"""
def test_configure_mirroring_session(self, env):
"""@brief Verify that simple Mirroring session can be created and deleted @steps -# Create simple mirroring session. -# Verify session has been created. -# Delete mirroring sessio... | the_stack_v2_python_sparse | l2/mirroring/test_mirroring_samples.py | ravigupta1989/testcases | train | 0 |
b6d99b70a6402a13a61176e2c8b02b49c4202b00 | [
"resource = f'/inspection/api/v1/formInstances/{formInstanceId}/document'\nresponse = item_fixture.request('GET', resource)\nreturn response",
"resource = f'/inspection/api/v1/formInstances/{formInstanceId}/attachments'\nresponse = item_fixture.request('GET', resource)\nreturn response"
] | <|body_start_0|>
resource = f'/inspection/api/v1/formInstances/{formInstanceId}/document'
response = item_fixture.request('GET', resource)
return response
<|end_body_0|>
<|body_start_1|>
resource = f'/inspection/api/v1/formInstances/{formInstanceId}/attachments'
response = item_... | FormAttachments | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FormAttachments:
def formInstancesGET(self, item_fixture, formInstanceId=None):
"""查询表单文件 :param item_fixture: item fixture,"""
<|body_0|>
def formInstancesGET(self, item_fixture, formInstanceId=None):
"""查询表单附件 :param item_fixture: item fixture,"""
<|body_1|... | stack_v2_sparse_classes_36k_train_018544 | 898 | no_license | [
{
"docstring": "查询表单文件 :param item_fixture: item fixture,",
"name": "formInstancesGET",
"signature": "def formInstancesGET(self, item_fixture, formInstanceId=None)"
},
{
"docstring": "查询表单附件 :param item_fixture: item fixture,",
"name": "formInstancesGET",
"signature": "def formInstancesG... | 2 | stack_v2_sparse_classes_30k_train_021673 | Implement the Python class `FormAttachments` described below.
Class description:
Implement the FormAttachments class.
Method signatures and docstrings:
- def formInstancesGET(self, item_fixture, formInstanceId=None): 查询表单文件 :param item_fixture: item fixture,
- def formInstancesGET(self, item_fixture, formInstanceId=N... | Implement the Python class `FormAttachments` described below.
Class description:
Implement the FormAttachments class.
Method signatures and docstrings:
- def formInstancesGET(self, item_fixture, formInstanceId=None): 查询表单文件 :param item_fixture: item fixture,
- def formInstancesGET(self, item_fixture, formInstanceId=N... | f875de62f7f505c596ea5567e1fc2c8a64010f87 | <|skeleton|>
class FormAttachments:
def formInstancesGET(self, item_fixture, formInstanceId=None):
"""查询表单文件 :param item_fixture: item fixture,"""
<|body_0|>
def formInstancesGET(self, item_fixture, formInstanceId=None):
"""查询表单附件 :param item_fixture: item fixture,"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FormAttachments:
def formInstancesGET(self, item_fixture, formInstanceId=None):
"""查询表单文件 :param item_fixture: item fixture,"""
resource = f'/inspection/api/v1/formInstances/{formInstanceId}/document'
response = item_fixture.request('GET', resource)
return response
def for... | the_stack_v2_python_sparse | swagger/api/inspection/form_attachments.py | zhangjingwen198817/pytest-api-allure | train | 1 | |
4be8f87febad39fee52b02451e812a66999f2cf9 | [
"maxSoFar = 0\nu = set(nums)\nwhile len(u) > 0:\n item = u.pop()\n cur = item\n count = 1\n cur += 1\n while cur in u:\n u.remove(cur)\n cur += 1\n count += 1\n cur = item - 1\n while cur in u:\n u.remove(cur)\n cur -= 1\n count += 1\n maxSoFar = max... | <|body_start_0|>
maxSoFar = 0
u = set(nums)
while len(u) > 0:
item = u.pop()
cur = item
count = 1
cur += 1
while cur in u:
u.remove(cur)
cur += 1
count += 1
cur = item - 1
... | https://leetcode.com/problems/longest-consecutive-sequence/description/ | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""https://leetcode.com/problems/longest-consecutive-sequence/description/"""
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def longestConsecutive2(self, nums):
""":type nums: List[int] :rtype: int"""
<|b... | stack_v2_sparse_classes_36k_train_018545 | 1,284 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "longestConsecutive",
"signature": "def longestConsecutive(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "longestConsecutive2",
"signature": "def longestConsecutive2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
https://leetcode.com/problems/longest-consecutive-sequence/description/
Method signatures and docstrings:
- def longestConsecutive(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive2(self, nums): :type nums: List[int] :rtyp... | Implement the Python class `Solution` described below.
Class description:
https://leetcode.com/problems/longest-consecutive-sequence/description/
Method signatures and docstrings:
- def longestConsecutive(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive2(self, nums): :type nums: List[int] :rtyp... | 54d3d9530b25272d4a2e5dc33e7035c44f506dc5 | <|skeleton|>
class Solution:
"""https://leetcode.com/problems/longest-consecutive-sequence/description/"""
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def longestConsecutive2(self, nums):
""":type nums: List[int] :rtype: int"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""https://leetcode.com/problems/longest-consecutive-sequence/description/"""
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
maxSoFar = 0
u = set(nums)
while len(u) > 0:
item = u.pop()
cur = item
co... | the_stack_v2_python_sparse | old/Session002/TopInterviewQuestions/LongestConsecutiveSequence.py | MaxIakovliev/algorithms | train | 0 |
751de327e538fea7fa1cfccc26afea28c0c0180e | [
"self._symbols = list()\nself._ngram = 1\nself.set_symbols(symbols)\nself.set_ngram(n)",
"if len(symbols) == 0:\n raise EmptyError\nself._symbols = symbols",
"n = int(n)\nif 0 < n <= MAX_NGRAM:\n self._ngram = n\nelse:\n raise InsideIntervalError(n, 1, MAX_NGRAM)",
"if len(self._symbols) == 0:\n r... | <|body_start_0|>
self._symbols = list()
self._ngram = 1
self.set_symbols(symbols)
self.set_ngram(n)
<|end_body_0|>
<|body_start_1|>
if len(symbols) == 0:
raise EmptyError
self._symbols = symbols
<|end_body_1|>
<|body_start_2|>
n = int(n)
if 0... | Entropy estimation. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Entropy is a measure of unpredictability of information content. Entropy is one of several ways to measure dive... | sppasEntropy | [
"GFDL-1.1-or-later",
"GPL-3.0-only",
"GPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sppasEntropy:
"""Entropy estimation. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Entropy is a measure of unpredictability of information content. Entrop... | stack_v2_sparse_classes_36k_train_018546 | 4,263 | permissive | [
{
"docstring": "Create a sppasEntropy instance with a list of symbols. :param symbols: (list) a vector of symbols of any type. :param n: (int) n value for n-gram estimation. n ranges 1..MAX_NGRAM",
"name": "__init__",
"signature": "def __init__(self, symbols, n=1)"
},
{
"docstring": "Set the lis... | 4 | stack_v2_sparse_classes_30k_train_003027 | Implement the Python class `sppasEntropy` described below.
Class description:
Entropy estimation. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Entropy is a measure of unpredic... | Implement the Python class `sppasEntropy` described below.
Class description:
Entropy estimation. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Entropy is a measure of unpredic... | 3167b65f576abcc27a8767d24c274a04712bd948 | <|skeleton|>
class sppasEntropy:
"""Entropy estimation. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Entropy is a measure of unpredictability of information content. Entrop... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class sppasEntropy:
"""Entropy estimation. :author: Brigitte Bigi :organization: Laboratoire Parole et Langage, Aix-en-Provence, France :contact: develop@sppas.org :license: GPL, v3 :copyright: Copyright (C) 2011-2018 Brigitte Bigi Entropy is a measure of unpredictability of information content. Entropy is one of s... | the_stack_v2_python_sparse | sppas/sppas/src/calculus/infotheory/entropy.py | mirfan899/MTTS | train | 0 |
f4d885a7a4a80f073c3be731125a5cfbba927285 | [
"if digits[-1] < 9:\n digits[-1] += 1\n return digits\ndigits[-1] = 0\nfor j in range(1, len(digits)):\n i = len(digits) - 1 - j\n if digits[i] < 9:\n digits[i] += 1\n return digits\n else:\n digits[i] = 0\nif digits[0] == 0:\n digits.insert(0, 1)\nreturn digits",
"for i in ... | <|body_start_0|>
if digits[-1] < 9:
digits[-1] += 1
return digits
digits[-1] = 0
for j in range(1, len(digits)):
i = len(digits) - 1 - j
if digits[i] < 9:
digits[i] += 1
return digits
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def plusOne(self, digits):
"""从数组末尾判断是否需要进位 执行用时 : 52 ms, 在Plus One的Python3提交中击败了86.46% 的用户 内存消耗 : 13.1 MB, 在Plus One的Python3提交中击败了82.41% 的用户"""
<|body_0|>
def plusOne1(self, digits):
"""从数组末尾判断是否需要进位 改进版 执行用时 : 36 ms, 在Plus One的Python3提交中击败了99.97% 的用户 内存消耗... | stack_v2_sparse_classes_36k_train_018547 | 2,447 | no_license | [
{
"docstring": "从数组末尾判断是否需要进位 执行用时 : 52 ms, 在Plus One的Python3提交中击败了86.46% 的用户 内存消耗 : 13.1 MB, 在Plus One的Python3提交中击败了82.41% 的用户",
"name": "plusOne",
"signature": "def plusOne(self, digits)"
},
{
"docstring": "从数组末尾判断是否需要进位 改进版 执行用时 : 36 ms, 在Plus One的Python3提交中击败了99.97% 的用户 内存消耗 : 13.1 MB, 在Plus... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne(self, digits): 从数组末尾判断是否需要进位 执行用时 : 52 ms, 在Plus One的Python3提交中击败了86.46% 的用户 内存消耗 : 13.1 MB, 在Plus One的Python3提交中击败了82.41% 的用户
- def plusOne1(self, digits): 从数组末尾判断是否... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne(self, digits): 从数组末尾判断是否需要进位 执行用时 : 52 ms, 在Plus One的Python3提交中击败了86.46% 的用户 内存消耗 : 13.1 MB, 在Plus One的Python3提交中击败了82.41% 的用户
- def plusOne1(self, digits): 从数组末尾判断是否... | 7bca9dc8ec211be15c12f89bffbb680d639f87bf | <|skeleton|>
class Solution:
def plusOne(self, digits):
"""从数组末尾判断是否需要进位 执行用时 : 52 ms, 在Plus One的Python3提交中击败了86.46% 的用户 内存消耗 : 13.1 MB, 在Plus One的Python3提交中击败了82.41% 的用户"""
<|body_0|>
def plusOne1(self, digits):
"""从数组末尾判断是否需要进位 改进版 执行用时 : 36 ms, 在Plus One的Python3提交中击败了99.97% 的用户 内存消耗... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def plusOne(self, digits):
"""从数组末尾判断是否需要进位 执行用时 : 52 ms, 在Plus One的Python3提交中击败了86.46% 的用户 内存消耗 : 13.1 MB, 在Plus One的Python3提交中击败了82.41% 的用户"""
if digits[-1] < 9:
digits[-1] += 1
return digits
digits[-1] = 0
for j in range(1, len(digits)):
... | the_stack_v2_python_sparse | python/leetcode/66-plus-one.py | wxnacy/study | train | 18 | |
b289e1fb8cb63905a33774a47eabdd4b8ad2a4f5 | [
"goals = super().published()\ngoals = goals.filter(categories__state='published', categories__packaged_content=False)\nreturn goals.distinct()",
"published = kwargs.pop('published', True)\nqs = super().get_queryset()\nif published:\n qs = qs.filter(categories__packaged_content=True, state='published')\nelse:\n... | <|body_start_0|>
goals = super().published()
goals = goals.filter(categories__state='published', categories__packaged_content=False)
return goals.distinct()
<|end_body_0|>
<|body_start_1|>
published = kwargs.pop('published', True)
qs = super().get_queryset()
if published... | GoalManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GoalManager:
def published(self, *args, **kwargs):
"""Returns Goals that are published and are contained within non-packaged categories (that are also published)."""
<|body_0|>
def packages(self, *args, **kwargs):
"""Return only Categories that have been marked as pa... | stack_v2_sparse_classes_36k_train_018548 | 21,796 | permissive | [
{
"docstring": "Returns Goals that are published and are contained within non-packaged categories (that are also published).",
"name": "published",
"signature": "def published(self, *args, **kwargs)"
},
{
"docstring": "Return only Categories that have been marked as packages. By default this ret... | 2 | null | Implement the Python class `GoalManager` described below.
Class description:
Implement the GoalManager class.
Method signatures and docstrings:
- def published(self, *args, **kwargs): Returns Goals that are published and are contained within non-packaged categories (that are also published).
- def packages(self, *arg... | Implement the Python class `GoalManager` described below.
Class description:
Implement the GoalManager class.
Method signatures and docstrings:
- def published(self, *args, **kwargs): Returns Goals that are published and are contained within non-packaged categories (that are also published).
- def packages(self, *arg... | 3d22179c581ab3da18900483930d5ecc0a5fca73 | <|skeleton|>
class GoalManager:
def published(self, *args, **kwargs):
"""Returns Goals that are published and are contained within non-packaged categories (that are also published)."""
<|body_0|>
def packages(self, *args, **kwargs):
"""Return only Categories that have been marked as pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GoalManager:
def published(self, *args, **kwargs):
"""Returns Goals that are published and are contained within non-packaged categories (that are also published)."""
goals = super().published()
goals = goals.filter(categories__state='published', categories__packaged_content=False)
... | the_stack_v2_python_sparse | tndata_backend/goals/managers.py | tndatacommons/tndata_backend | train | 1 | |
8a2c625dc5abf745fd4f36636544e1834c8c2ff8 | [
"create_listener_flow = linear_flow.Flow(constants.CREATE_LISTENER_FLOW)\ncreate_listener_flow.add(lifecycle_tasks.ListenersToErrorOnRevertTask(requires=constants.LISTENERS))\ncreate_listener_flow.add(amphora_driver_tasks.ListenersUpdate(requires=constants.LOADBALANCER_ID))\ncreate_listener_flow.add(network_tasks.U... | <|body_start_0|>
create_listener_flow = linear_flow.Flow(constants.CREATE_LISTENER_FLOW)
create_listener_flow.add(lifecycle_tasks.ListenersToErrorOnRevertTask(requires=constants.LISTENERS))
create_listener_flow.add(amphora_driver_tasks.ListenersUpdate(requires=constants.LOADBALANCER_ID))
... | ListenerFlows | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListenerFlows:
def get_create_listener_flow(self):
"""Create a flow to create a listener :returns: The flow for creating a listener"""
<|body_0|>
def get_create_all_listeners_flow(self):
"""Create a flow to create all listeners :returns: The flow for creating all lis... | stack_v2_sparse_classes_36k_train_018549 | 5,910 | permissive | [
{
"docstring": "Create a flow to create a listener :returns: The flow for creating a listener",
"name": "get_create_listener_flow",
"signature": "def get_create_listener_flow(self)"
},
{
"docstring": "Create a flow to create all listeners :returns: The flow for creating all listeners",
"name... | 5 | stack_v2_sparse_classes_30k_train_007490 | Implement the Python class `ListenerFlows` described below.
Class description:
Implement the ListenerFlows class.
Method signatures and docstrings:
- def get_create_listener_flow(self): Create a flow to create a listener :returns: The flow for creating a listener
- def get_create_all_listeners_flow(self): Create a fl... | Implement the Python class `ListenerFlows` described below.
Class description:
Implement the ListenerFlows class.
Method signatures and docstrings:
- def get_create_listener_flow(self): Create a flow to create a listener :returns: The flow for creating a listener
- def get_create_all_listeners_flow(self): Create a fl... | 0426285a41464a5015494584f109eed35a0d44db | <|skeleton|>
class ListenerFlows:
def get_create_listener_flow(self):
"""Create a flow to create a listener :returns: The flow for creating a listener"""
<|body_0|>
def get_create_all_listeners_flow(self):
"""Create a flow to create all listeners :returns: The flow for creating all lis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListenerFlows:
def get_create_listener_flow(self):
"""Create a flow to create a listener :returns: The flow for creating a listener"""
create_listener_flow = linear_flow.Flow(constants.CREATE_LISTENER_FLOW)
create_listener_flow.add(lifecycle_tasks.ListenersToErrorOnRevertTask(requires=... | the_stack_v2_python_sparse | octavia/controller/worker/v2/flows/listener_flows.py | openstack/octavia | train | 147 | |
45c43060945b3d39b479f22e89c3d6f57f3f51e4 | [
"self.L = L\nself.N = 2 * L + 1\nself.alpha = alpha\nself.kappa = kappa\nself.beta = beta",
"L = self.L\nN = self.N\nassert mu.shape == (L,)\nassert var.shape == (L, L)\nalpha = self.alpha\nkappa = self.kappa\nbeta = self.beta\nsigmaMat = np.zeros((N, L))\nLambda = alpha ** 2 * (L + kappa) - L\nsigmaMat[0, :] = m... | <|body_start_0|>
self.L = L
self.N = 2 * L + 1
self.alpha = alpha
self.kappa = kappa
self.beta = beta
<|end_body_0|>
<|body_start_1|>
L = self.L
N = self.N
assert mu.shape == (L,)
assert var.shape == (L, L)
alpha = self.alpha
kappa... | UGP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UGP:
def __init__(self, L, alpha=0.001, kappa=0.0, beta=2.0):
"""Initialize the unscented transform parameters :param L: dim of the input a practical value set for the remaining params: :param alpha: 1. :param kappa: 2. :param beta: 0."""
<|body_0|>
def get_sigma_points(self... | stack_v2_sparse_classes_36k_train_018550 | 36,021 | no_license | [
{
"docstring": "Initialize the unscented transform parameters :param L: dim of the input a practical value set for the remaining params: :param alpha: 1. :param kappa: 2. :param beta: 0.",
"name": "__init__",
"signature": "def __init__(self, L, alpha=0.001, kappa=0.0, beta=2.0)"
},
{
"docstring"... | 4 | null | Implement the Python class `UGP` described below.
Class description:
Implement the UGP class.
Method signatures and docstrings:
- def __init__(self, L, alpha=0.001, kappa=0.0, beta=2.0): Initialize the unscented transform parameters :param L: dim of the input a practical value set for the remaining params: :param alp... | Implement the Python class `UGP` described below.
Class description:
Implement the UGP class.
Method signatures and docstrings:
- def __init__(self, L, alpha=0.001, kappa=0.0, beta=2.0): Initialize the unscented transform parameters :param L: dim of the input a practical value set for the remaining params: :param alp... | 5e3823e534714c008e146eecda82a5b21c43db39 | <|skeleton|>
class UGP:
def __init__(self, L, alpha=0.001, kappa=0.0, beta=2.0):
"""Initialize the unscented transform parameters :param L: dim of the input a practical value set for the remaining params: :param alpha: 1. :param kappa: 2. :param beta: 0."""
<|body_0|>
def get_sigma_points(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UGP:
def __init__(self, L, alpha=0.001, kappa=0.0, beta=2.0):
"""Initialize the unscented transform parameters :param L: dim of the input a practical value set for the remaining params: :param alpha: 1. :param kappa: 2. :param beta: 0."""
self.L = L
self.N = 2 * L + 1
self.alph... | the_stack_v2_python_sparse | model_leraning_utils.py | shbz80/model_learning | train | 1 | |
331f7416945d6b97a1324bb0ba1a0fd076c18677 | [
"lookup_url_kwarg = self.lookup_url_kwarg or self.lookup_field\nlookup = self.kwargs.get(lookup_url_kwarg, None)\nif lookup is not None:\n return Clip.objects.filter(video__hash_key=lookup).select_related('owner', 'video')\nreturn Clip.objects.none()",
"lookup_url_kwarg = self.lookup_url_kwarg or self.lookup_f... | <|body_start_0|>
lookup_url_kwarg = self.lookup_url_kwarg or self.lookup_field
lookup = self.kwargs.get(lookup_url_kwarg, None)
if lookup is not None:
return Clip.objects.filter(video__hash_key=lookup).select_related('owner', 'video')
return Clip.objects.none()
<|end_body_0|>... | List all clips of a video and create new clips. ## Reading ### Permissions * Anyone can read this endpoint. ### Fields Reading this endpoint returns a list of [Clip objects](0/) ## Publishing ### Permissions * Only authenticated users can create using this endpoint. * Only associated users of a video can write to this ... | VideoClipList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoClipList:
"""List all clips of a video and create new clips. ## Reading ### Permissions * Anyone can read this endpoint. ### Fields Reading this endpoint returns a list of [Clip objects](0/) ## Publishing ### Permissions * Only authenticated users can create using this endpoint. * Only assoc... | stack_v2_sparse_classes_36k_train_018551 | 40,640 | no_license | [
{
"docstring": "This view should return a list of all clips for the video as determined by the lookup parameters of the view.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Create a new clip",
"name": "perform_create",
"signature": "def perform_create(... | 2 | stack_v2_sparse_classes_30k_train_011946 | Implement the Python class `VideoClipList` described below.
Class description:
List all clips of a video and create new clips. ## Reading ### Permissions * Anyone can read this endpoint. ### Fields Reading this endpoint returns a list of [Clip objects](0/) ## Publishing ### Permissions * Only authenticated users can c... | Implement the Python class `VideoClipList` described below.
Class description:
List all clips of a video and create new clips. ## Reading ### Permissions * Anyone can read this endpoint. ### Fields Reading this endpoint returns a list of [Clip objects](0/) ## Publishing ### Permissions * Only authenticated users can c... | 1f4b4cd74c9b4280437f73bdfef4491536194eeb | <|skeleton|>
class VideoClipList:
"""List all clips of a video and create new clips. ## Reading ### Permissions * Anyone can read this endpoint. ### Fields Reading this endpoint returns a list of [Clip objects](0/) ## Publishing ### Permissions * Only authenticated users can create using this endpoint. * Only assoc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VideoClipList:
"""List all clips of a video and create new clips. ## Reading ### Permissions * Anyone can read this endpoint. ### Fields Reading this endpoint returns a list of [Clip objects](0/) ## Publishing ### Permissions * Only authenticated users can create using this endpoint. * Only associated users o... | the_stack_v2_python_sparse | gravvy/apps/video/views.py | nceruchalu/gravvy-server | train | 1 |
e16ec123bc45a9ae8519ce2ccfc8316ac2b32b0a | [
"self._hasnext = None\ni, _num = (0, '')\nself.stack_alpha, self.stack_digit = ([], [])\nif compressedString:\n while i < len(compressedString):\n if compressedString[i].isalpha():\n if self.stack_alpha:\n self.stack_alpha.append(compressedString[i])\n self.stack_d... | <|body_start_0|>
self._hasnext = None
i, _num = (0, '')
self.stack_alpha, self.stack_digit = ([], [])
if compressedString:
while i < len(compressedString):
if compressedString[i].isalpha():
if self.stack_alpha:
self.... | StringIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
<|body_0|>
def next(self):
""":rtype: str"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_36k_train_018552 | 3,161 | no_license | [
{
"docstring": ":type compressedString: str",
"name": "__init__",
"signature": "def __init__(self, compressedString)"
},
{
"docstring": ":rtype: str",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",
"signature": "def hasN... | 3 | null | Implement the Python class `StringIterator` described below.
Class description:
Implement the StringIterator class.
Method signatures and docstrings:
- def __init__(self, compressedString): :type compressedString: str
- def next(self): :rtype: str
- def hasNext(self): :rtype: bool | Implement the Python class `StringIterator` described below.
Class description:
Implement the StringIterator class.
Method signatures and docstrings:
- def __init__(self, compressedString): :type compressedString: str
- def next(self): :rtype: str
- def hasNext(self): :rtype: bool
<|skeleton|>
class StringIterator:
... | 546cbce06fcd4bc34e16d42b5d5eb68fb25e16a9 | <|skeleton|>
class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
<|body_0|>
def next(self):
""":rtype: str"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StringIterator:
def __init__(self, compressedString):
""":type compressedString: str"""
self._hasnext = None
i, _num = (0, '')
self.stack_alpha, self.stack_digit = ([], [])
if compressedString:
while i < len(compressedString):
if compressedSt... | the_stack_v2_python_sparse | leetcode/solution_604.py | eselyavka/python | train | 0 | |
09afa85effbf5260991f534ab2711b812b5069c7 | [
"timestamp = str(time.time())\npvt_key, pub_key = Signature.get_key_pair()\nsignature = bytes.hex(Signature.sign(pvt_key, transaction.__dict__.__str__()))\nmsg_id = Signature.gen_id_by_sig(signature)\nreturn Message(msg_id=msg_id, msg_type=msg_type, transaction=transaction.__dict__, timestamp=timestamp, pub_key=byt... | <|body_start_0|>
timestamp = str(time.time())
pvt_key, pub_key = Signature.get_key_pair()
signature = bytes.hex(Signature.sign(pvt_key, transaction.__dict__.__str__()))
msg_id = Signature.gen_id_by_sig(signature)
return Message(msg_id=msg_id, msg_type=msg_type, transaction=transa... | MessageService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessageService:
def gen_msg(msg_type, transaction):
"""根据 msg type 和 transaction 生成一个 Message 类对象 :param msg_type: :param transaction: Transaction对象 :return:"""
<|body_0|>
def verify_msg(msg):
"""判断 msg 的签名是否正确 :param msg: Message 对象 :return:"""
<|body_1|>
<... | stack_v2_sparse_classes_36k_train_018553 | 1,605 | permissive | [
{
"docstring": "根据 msg type 和 transaction 生成一个 Message 类对象 :param msg_type: :param transaction: Transaction对象 :return:",
"name": "gen_msg",
"signature": "def gen_msg(msg_type, transaction)"
},
{
"docstring": "判断 msg 的签名是否正确 :param msg: Message 对象 :return:",
"name": "verify_msg",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_001189 | Implement the Python class `MessageService` described below.
Class description:
Implement the MessageService class.
Method signatures and docstrings:
- def gen_msg(msg_type, transaction): 根据 msg type 和 transaction 生成一个 Message 类对象 :param msg_type: :param transaction: Transaction对象 :return:
- def verify_msg(msg): 判断 m... | Implement the Python class `MessageService` described below.
Class description:
Implement the MessageService class.
Method signatures and docstrings:
- def gen_msg(msg_type, transaction): 根据 msg type 和 transaction 生成一个 Message 类对象 :param msg_type: :param transaction: Transaction对象 :return:
- def verify_msg(msg): 判断 m... | 84dfa1461e6d3de40bf78f8ad9079badef095f9e | <|skeleton|>
class MessageService:
def gen_msg(msg_type, transaction):
"""根据 msg type 和 transaction 生成一个 Message 类对象 :param msg_type: :param transaction: Transaction对象 :return:"""
<|body_0|>
def verify_msg(msg):
"""判断 msg 的签名是否正确 :param msg: Message 对象 :return:"""
<|body_1|>
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MessageService:
def gen_msg(msg_type, transaction):
"""根据 msg type 和 transaction 生成一个 Message 类对象 :param msg_type: :param transaction: Transaction对象 :return:"""
timestamp = str(time.time())
pvt_key, pub_key = Signature.get_key_pair()
signature = bytes.hex(Signature.sign(pvt_key... | the_stack_v2_python_sparse | BlockchainDjango/service/message_service.py | just2husky/BlockchainDjango | train | 0 | |
bfbdc3f68fc97b7f9ae7b3cbb105447b5624b213 | [
"super(IndexBatchIterator, self).__init__(*args, **kwargs)\nself.source = source\nif source is not None:\n x = source.data\n input_shape = [len(x) + (SAMPLE_SIZE - 1), N_ELECTRODES]\n self.augmented = np.zeros(input_shape, dtype=np.float32)\n self.augmented[SAMPLE_SIZE - 1:] = x\n self.augmented[:SAM... | <|body_start_0|>
super(IndexBatchIterator, self).__init__(*args, **kwargs)
self.source = source
if source is not None:
x = source.data
input_shape = [len(x) + (SAMPLE_SIZE - 1), N_ELECTRODES]
self.augmented = np.zeros(input_shape, dtype=np.float32)
... | Generate BatchData from indices. Rather than passing the data into the fit function, instead we just pass in indices to the data. The actual data is then grabbed from a Source object that is passed in at the creation of the IndexBatchIterator. Passing in a '-1' grabs a random value from the Source. As a result, an "epo... | IndexBatchIterator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexBatchIterator:
"""Generate BatchData from indices. Rather than passing the data into the fit function, instead we just pass in indices to the data. The actual data is then grabbed from a Source object that is passed in at the creation of the IndexBatchIterator. Passing in a '-1' grabs a rand... | stack_v2_sparse_classes_36k_train_018554 | 12,952 | permissive | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, source, *args, **kwargs)"
},
{
"docstring": "Transform.",
"name": "transform",
"signature": "def transform(self, X_indices, y_indices)"
}
] | 2 | null | Implement the Python class `IndexBatchIterator` described below.
Class description:
Generate BatchData from indices. Rather than passing the data into the fit function, instead we just pass in indices to the data. The actual data is then grabbed from a Source object that is passed in at the creation of the IndexBatchI... | Implement the Python class `IndexBatchIterator` described below.
Class description:
Generate BatchData from indices. Rather than passing the data into the fit function, instead we just pass in indices to the data. The actual data is then grabbed from a Source object that is passed in at the creation of the IndexBatchI... | 87de739aba2399fd31072ee81b391f9b7a63f540 | <|skeleton|>
class IndexBatchIterator:
"""Generate BatchData from indices. Rather than passing the data into the fit function, instead we just pass in indices to the data. The actual data is then grabbed from a Source object that is passed in at the creation of the IndexBatchIterator. Passing in a '-1' grabs a rand... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IndexBatchIterator:
"""Generate BatchData from indices. Rather than passing the data into the fit function, instead we just pass in indices to the data. The actual data is then grabbed from a Source object that is passed in at the creation of the IndexBatchIterator. Passing in a '-1' grabs a random value from... | the_stack_v2_python_sparse | data/external/repositories_2to3/197978/Grasp-and-lift-EEG-challenge-master/lvl1/genPreds_CNN_Tim.py | Keesiu/meta-kaggle | train | 0 |
3d0d5f807470962327068d15dd5ab318f3676ba3 | [
"self.r = radius\nself.x = x_center\nself.y = y_center",
"f = True\nwhile f:\n a = random.uniform(self.x - self.r, self.x + self.r)\n b = random.uniform(self.y - self.r, self.y + self.r)\n if (a - self.x) ** 2 + (b - self.y) ** 2 <= self.r ** 2:\n f = False\n r0 = a\n r1 = b\nreturn ... | <|body_start_0|>
self.r = radius
self.x = x_center
self.y = y_center
<|end_body_0|>
<|body_start_1|>
f = True
while f:
a = random.uniform(self.x - self.r, self.x + self.r)
b = random.uniform(self.y - self.r, self.y + self.r)
if (a - self.x) **... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.r = radius
... | stack_v2_sparse_classes_36k_train_018555 | 846 | no_license | [
{
"docstring": ":type radius: float :type x_center: float :type y_center: float",
"name": "__init__",
"signature": "def __init__(self, radius, x_center, y_center)"
},
{
"docstring": ":rtype: List[float]",
"name": "randPoint",
"signature": "def randPoint(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float
- def randPoint(self): :rtype: List[float] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float
- def randPoint(self): :rtype: List[float]
<|skeleton|>
class Sol... | 20623defecf65cbc35b194d8b60d8b211816ee4f | <|skeleton|>
class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
self.r = radius
self.x = x_center
self.y = y_center
def randPoint(self):
""":rtype: List[float]"""
f = True
while f:
... | the_stack_v2_python_sparse | in_Python/0478 Generate Random Point in a Circle.py | YangLiyli131/Leetcode2020 | train | 0 | |
11c3af7dc218e166c9efe6faca2a1760519b80b4 | [
"if not s.isdigit():\n return False\nif int(s) <= 255 and str(int(s)) == s:\n return True\nreturn False",
"s_len = len(s)\nif s_len < i + 1:\n return\nif k == 1:\n s1 = s[:i + 1]\n if self.isValidNum(s1):\n dict_kinds[i, k] = [s1]\nelse:\n l2 = []\n for j in range(1, 4):\n l1 = ... | <|body_start_0|>
if not s.isdigit():
return False
if int(s) <= 255 and str(int(s)) == s:
return True
return False
<|end_body_0|>
<|body_start_1|>
s_len = len(s)
if s_len < i + 1:
return
if k == 1:
s1 = s[:i + 1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidNum(self, s):
"""用来计算ip地址中间的某一个字符串是否合法"""
<|body_0|>
def getIndexValues(self, s, i, k, dict_kinds):
"""计算第i索引为结尾的字符串分成k个满足条件的数字的个数，并且加入到dict_kinds中"""
<|body_1|>
def restoreIpAddresses(self, s):
""":type s: str :rtype: List[s... | stack_v2_sparse_classes_36k_train_018556 | 2,305 | no_license | [
{
"docstring": "用来计算ip地址中间的某一个字符串是否合法",
"name": "isValidNum",
"signature": "def isValidNum(self, s)"
},
{
"docstring": "计算第i索引为结尾的字符串分成k个满足条件的数字的个数，并且加入到dict_kinds中",
"name": "getIndexValues",
"signature": "def getIndexValues(self, s, i, k, dict_kinds)"
},
{
"docstring": ":type s... | 3 | stack_v2_sparse_classes_30k_train_016946 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidNum(self, s): 用来计算ip地址中间的某一个字符串是否合法
- def getIndexValues(self, s, i, k, dict_kinds): 计算第i索引为结尾的字符串分成k个满足条件的数字的个数，并且加入到dict_kinds中
- def restoreIpAddresses(self, s): :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidNum(self, s): 用来计算ip地址中间的某一个字符串是否合法
- def getIndexValues(self, s, i, k, dict_kinds): 计算第i索引为结尾的字符串分成k个满足条件的数字的个数，并且加入到dict_kinds中
- def restoreIpAddresses(self, s): :t... | 313ea5583d423ec89d66d5f0c5f2dcc87cc3e68a | <|skeleton|>
class Solution:
def isValidNum(self, s):
"""用来计算ip地址中间的某一个字符串是否合法"""
<|body_0|>
def getIndexValues(self, s, i, k, dict_kinds):
"""计算第i索引为结尾的字符串分成k个满足条件的数字的个数，并且加入到dict_kinds中"""
<|body_1|>
def restoreIpAddresses(self, s):
""":type s: str :rtype: List[s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValidNum(self, s):
"""用来计算ip地址中间的某一个字符串是否合法"""
if not s.isdigit():
return False
if int(s) <= 255 and str(int(s)) == s:
return True
return False
def getIndexValues(self, s, i, k, dict_kinds):
"""计算第i索引为结尾的字符串分成k个满足条件的数字的个数，并且加... | the_stack_v2_python_sparse | 0093_RestoreIPAddresses.py | cheungrui/leetcode | train | 0 | |
68947c9ca630bdad67c88ccd610cce695ed0ce28 | [
"self.channel_owner_vec = channel_owner_vec\nself.channel_type = channel_type\nself.create_new_channel = create_new_channel\nself.id = id\nself.name = name",
"if dictionary is None:\n return None\nchannel_owner_vec = None\nif dictionary.get('channelOwnerVec') != None:\n channel_owner_vec = list()\n for s... | <|body_start_0|>
self.channel_owner_vec = channel_owner_vec
self.channel_type = channel_type
self.create_new_channel = create_new_channel
self.id = id
self.name = name
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
channel_owner_ve... | Implementation of the 'RestoreO365TeamsParams_TargetChannel' model. Target channel for teams granular restore to alternate loc. At least one of id or name must be specified. name must be specified if create_new_channel is true. Attributes: channel_owner_vec (list of EntityProto): Owners for the private channel. This is... | RestoreO365TeamsParams_TargetChannel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreO365TeamsParams_TargetChannel:
"""Implementation of the 'RestoreO365TeamsParams_TargetChannel' model. Target channel for teams granular restore to alternate loc. At least one of id or name must be specified. name must be specified if create_new_channel is true. Attributes: channel_owner_ve... | stack_v2_sparse_classes_36k_train_018557 | 2,919 | permissive | [
{
"docstring": "Constructor for the RestoreO365TeamsParams_TargetChannel class",
"name": "__init__",
"signature": "def __init__(self, channel_owner_vec=None, channel_type=None, create_new_channel=None, id=None, name=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Ar... | 2 | stack_v2_sparse_classes_30k_train_007180 | Implement the Python class `RestoreO365TeamsParams_TargetChannel` described below.
Class description:
Implementation of the 'RestoreO365TeamsParams_TargetChannel' model. Target channel for teams granular restore to alternate loc. At least one of id or name must be specified. name must be specified if create_new_channe... | Implement the Python class `RestoreO365TeamsParams_TargetChannel` described below.
Class description:
Implementation of the 'RestoreO365TeamsParams_TargetChannel' model. Target channel for teams granular restore to alternate loc. At least one of id or name must be specified. name must be specified if create_new_channe... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreO365TeamsParams_TargetChannel:
"""Implementation of the 'RestoreO365TeamsParams_TargetChannel' model. Target channel for teams granular restore to alternate loc. At least one of id or name must be specified. name must be specified if create_new_channel is true. Attributes: channel_owner_ve... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestoreO365TeamsParams_TargetChannel:
"""Implementation of the 'RestoreO365TeamsParams_TargetChannel' model. Target channel for teams granular restore to alternate loc. At least one of id or name must be specified. name must be specified if create_new_channel is true. Attributes: channel_owner_vec (list of En... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_o_365_teams_params_target_channel.py | cohesity/management-sdk-python | train | 24 |
51d2390497f97399be477bdffcf83eacae9c3257 | [
"res = []\nfor s in [S, T]:\n tmp = []\n for i in s:\n if i is not '#':\n tmp.append(i)\n elif i is '#' and tmp != []:\n tmp.pop()\n res.append(tmp)\nreturn res[0] == res[1]",
"def F(S):\n skip = 0\n for x in reversed(S):\n if x == '#':\n skip +... | <|body_start_0|>
res = []
for s in [S, T]:
tmp = []
for i in s:
if i is not '#':
tmp.append(i)
elif i is '#' and tmp != []:
tmp.pop()
res.append(tmp)
return res[0] == res[1]
<|end_body_0|>... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_0|>
def backspaceCompare2(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
for s i... | stack_v2_sparse_classes_36k_train_018558 | 2,087 | no_license | [
{
"docstring": ":type S: str :type T: str :rtype: bool",
"name": "backspaceCompare",
"signature": "def backspaceCompare(self, S, T)"
},
{
"docstring": ":type S: str :type T: str :rtype: bool",
"name": "backspaceCompare2",
"signature": "def backspaceCompare2(self, S, T)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020413 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
- def backspaceCompare2(self, S, T): :type S: str :type T: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
- def backspaceCompare2(self, S, T): :type S: str :type T: str :rtype: bool
<|skeleton|>
class Solution:... | 416fed6e441612e1ad82467d07ee1b5570386a94 | <|skeleton|>
class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_0|>
def backspaceCompare2(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
res = []
for s in [S, T]:
tmp = []
for i in s:
if i is not '#':
tmp.append(i)
elif i is '#' and tmp != []:
... | the_stack_v2_python_sparse | src/python/backspace_string_compare.py | liadbiz/Leetcode-Solutions | train | 1 | |
8e415d927798cd6f6b11d587872033f02df75d74 | [
"super(GlobalBestPSO, self).__init__(n_particles, dimensions, options, bounds, velocity_clamp)\nself.logger = logging.getLogger(__name__)\nself.assertions()\nself.reset()",
"for i in xrange(iters):\n current_cost = objective_func(self.pos)\n pbest_cost = objective_func(self.personal_best_pos)\n m = curre... | <|body_start_0|>
super(GlobalBestPSO, self).__init__(n_particles, dimensions, options, bounds, velocity_clamp)
self.logger = logging.getLogger(__name__)
self.assertions()
self.reset()
<|end_body_0|>
<|body_start_1|>
for i in xrange(iters):
current_cost = objective_fu... | GlobalBestPSO | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GlobalBestPSO:
def __init__(self, n_particles, dimensions, options, bounds=None, velocity_clamp=None):
"""Initializes the swarm. Attributes ---------- n_particles : int number of particles in the swarm. dimensions : int number of dimensions in the space. options : dict with keys :code:`{... | stack_v2_sparse_classes_36k_train_018559 | 8,709 | permissive | [
{
"docstring": "Initializes the swarm. Attributes ---------- n_particles : int number of particles in the swarm. dimensions : int number of dimensions in the space. options : dict with keys :code:`{'c1', 'c2', 'w'}` a dictionary containing the parameters for the specific optimization technique * c1 : float cogn... | 4 | stack_v2_sparse_classes_30k_train_005180 | Implement the Python class `GlobalBestPSO` described below.
Class description:
Implement the GlobalBestPSO class.
Method signatures and docstrings:
- def __init__(self, n_particles, dimensions, options, bounds=None, velocity_clamp=None): Initializes the swarm. Attributes ---------- n_particles : int number of particl... | Implement the Python class `GlobalBestPSO` described below.
Class description:
Implement the GlobalBestPSO class.
Method signatures and docstrings:
- def __init__(self, n_particles, dimensions, options, bounds=None, velocity_clamp=None): Initializes the swarm. Attributes ---------- n_particles : int number of particl... | 353f92f7657a6f676a271d8d7f00d7c20e39d234 | <|skeleton|>
class GlobalBestPSO:
def __init__(self, n_particles, dimensions, options, bounds=None, velocity_clamp=None):
"""Initializes the swarm. Attributes ---------- n_particles : int number of particles in the swarm. dimensions : int number of dimensions in the space. options : dict with keys :code:`{... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GlobalBestPSO:
def __init__(self, n_particles, dimensions, options, bounds=None, velocity_clamp=None):
"""Initializes the swarm. Attributes ---------- n_particles : int number of particles in the swarm. dimensions : int number of dimensions in the space. options : dict with keys :code:`{'c1', 'c2', 'w... | the_stack_v2_python_sparse | pso_doc/pyswarms-master/pyswarms/single/global_best.py | smart1004/learn_src | train | 3 | |
71e1e1077b3efbd4d4171f92b6f98250f65a2cf9 | [
"pygame.init()\nself.surface = pygame.display.set_mode((800, 600))\nnr_molecules = 50\nself.molecules = Molecules(nr_molecules, self.surface.get_size())",
"clock = pygame.time.Clock()\nrunning = True\nwhile running:\n self.surface.fill((0, 0, 0))\n for event in pygame.event.get():\n if event.type == ... | <|body_start_0|>
pygame.init()
self.surface = pygame.display.set_mode((800, 600))
nr_molecules = 50
self.molecules = Molecules(nr_molecules, self.surface.get_size())
<|end_body_0|>
<|body_start_1|>
clock = pygame.time.Clock()
running = True
while running:
... | Gas_Simulation that simulates molecules moving and colliding | Gas_Simulation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Gas_Simulation:
"""Gas_Simulation that simulates molecules moving and colliding"""
def __init__(self):
"""Initalizes the Simulation"""
<|body_0|>
def run(self):
"""Runs the simulation until the program ends"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_018560 | 5,895 | no_license | [
{
"docstring": "Initalizes the Simulation",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Runs the simulation until the program ends",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015680 | Implement the Python class `Gas_Simulation` described below.
Class description:
Gas_Simulation that simulates molecules moving and colliding
Method signatures and docstrings:
- def __init__(self): Initalizes the Simulation
- def run(self): Runs the simulation until the program ends | Implement the Python class `Gas_Simulation` described below.
Class description:
Gas_Simulation that simulates molecules moving and colliding
Method signatures and docstrings:
- def __init__(self): Initalizes the Simulation
- def run(self): Runs the simulation until the program ends
<|skeleton|>
class Gas_Simulation:... | dd8fec6f71b18aaa4a78e26a4afefc8c70327093 | <|skeleton|>
class Gas_Simulation:
"""Gas_Simulation that simulates molecules moving and colliding"""
def __init__(self):
"""Initalizes the Simulation"""
<|body_0|>
def run(self):
"""Runs the simulation until the program ends"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Gas_Simulation:
"""Gas_Simulation that simulates molecules moving and colliding"""
def __init__(self):
"""Initalizes the Simulation"""
pygame.init()
self.surface = pygame.display.set_mode((800, 600))
nr_molecules = 50
self.molecules = Molecules(nr_molecules, self.s... | the_stack_v2_python_sparse | Gas_Simulation.py | bterwijn/python | train | 0 |
4532e4e194201d10952dd091737e026abf57c20a | [
"super().__init__(**kwargs)\nself.has_monthly_pass = monthly_pass\nself.contact_details = ContactDetails(name=name, email=email)",
"if self.card_id[:1] == 'T' and self.card_id[1:].isdigit() and (int(self._balance) >= 0):\n return True\nreturn False",
"fields = super().get_fields()\nfields['name'] = 'Contact ... | <|body_start_0|>
super().__init__(**kwargs)
self.has_monthly_pass = monthly_pass
self.contact_details = ContactDetails(name=name, email=email)
<|end_body_0|>
<|body_start_1|>
if self.card_id[:1] == 'T' and self.card_id[1:].isdigit() and (int(self._balance) >= 0):
return True... | Represent a card used for transit system. TransitCard holds a balance, a boolean variable to tell whether it is a monthly pass or not, and some contact information. TransitCard must have a balance of 0 or more and the card ID must start with a "T" followed by digits in order to be validated. This class implements and i... | TransitCard | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransitCard:
"""Represent a card used for transit system. TransitCard holds a balance, a boolean variable to tell whether it is a monthly pass or not, and some contact information. TransitCard must have a balance of 0 or more and the card ID must start with a "T" followed by digits in order to be... | stack_v2_sparse_classes_36k_train_018561 | 13,320 | no_license | [
{
"docstring": "Initialize the transit card object :param name: name of the contact as a String :param email: email of the contact as a String :param monthly_pass: Bool that checks if it is a monthly pass :param kwargs: a dictionary of named arguments and values. This is to provide support in the event of multi... | 4 | stack_v2_sparse_classes_30k_train_008515 | Implement the Python class `TransitCard` described below.
Class description:
Represent a card used for transit system. TransitCard holds a balance, a boolean variable to tell whether it is a monthly pass or not, and some contact information. TransitCard must have a balance of 0 or more and the card ID must start with ... | Implement the Python class `TransitCard` described below.
Class description:
Represent a card used for transit system. TransitCard holds a balance, a boolean variable to tell whether it is a monthly pass or not, and some contact information. TransitCard must have a balance of 0 or more and the card ID must start with ... | e4953c9a4f574a6d92cbd0815e5150dd1523c31d | <|skeleton|>
class TransitCard:
"""Represent a card used for transit system. TransitCard holds a balance, a boolean variable to tell whether it is a monthly pass or not, and some contact information. TransitCard must have a balance of 0 or more and the card ID must start with a "T" followed by digits in order to be... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransitCard:
"""Represent a card used for transit system. TransitCard holds a balance, a boolean variable to tell whether it is a monthly pass or not, and some contact information. TransitCard must have a balance of 0 or more and the card ID must start with a "T" followed by digits in order to be validated. T... | the_stack_v2_python_sparse | Labs/Lab6/cards.py | kchung90/Python-Labs-Assignments | train | 0 |
01a0f10255d2035845b96106d604f5734edf98d7 | [
"settings.addListsToRepository('skeinforge_tools.analyze_plugins.vectorwrite.html', '', self)\nself.activateVectorwrite = settings.BooleanSetting().getFromValue('Activate Vectorwrite', self, False)\nself.fileNameInput = settings.FileNameInput().getFromFileName([('Gcode text files', '*.gcode')], 'Open File to Write ... | <|body_start_0|>
settings.addListsToRepository('skeinforge_tools.analyze_plugins.vectorwrite.html', '', self)
self.activateVectorwrite = settings.BooleanSetting().getFromValue('Activate Vectorwrite', self, False)
self.fileNameInput = settings.FileNameInput().getFromFileName([('Gcode text files',... | A class to handle the vectorwrite settings. | VectorwriteRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VectorwriteRepository:
"""A class to handle the vectorwrite settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Write button has been clicked."""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_36k_train_018562 | 12,022 | no_license | [
{
"docstring": "Set the default settings, execute title & settings fileName.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Write button has been clicked.",
"name": "execute",
"signature": "def execute(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012012 | Implement the Python class `VectorwriteRepository` described below.
Class description:
A class to handle the vectorwrite settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Write button has been clicked. | Implement the Python class `VectorwriteRepository` described below.
Class description:
A class to handle the vectorwrite settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Write button has been clicked.
<|skeleton|>
clas... | fd69d8e856780c826386dc973ceabcc03623f3e8 | <|skeleton|>
class VectorwriteRepository:
"""A class to handle the vectorwrite settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Write button has been clicked."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VectorwriteRepository:
"""A class to handle the vectorwrite settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
settings.addListsToRepository('skeinforge_tools.analyze_plugins.vectorwrite.html', '', self)
self.activateVectorwrite = s... | the_stack_v2_python_sparse | skeinforge_tools/analyze_plugins/vectorwrite.py | bmander/skeinforge | train | 34 |
105572cacce8cd3c9884e1c37d137915ff8d0be2 | [
"self.p0 = p0\nself.p1 = p1\nself.p2 = p2\nself.rowid = rowid",
"volume = self.p0.x * (self.p1.z * self.p2.y - self.p1.y * self.p2.z)\nvolume += self.p0.y * (self.p1.x * self.p2.z - self.p1.z * self.p2.x)\nvolume += self.p0.z * (self.p1.y * self.p2.x - self.p1.x * self.p2.y)\nreturn volume / 6",
"D0 = [[centroi... | <|body_start_0|>
self.p0 = p0
self.p1 = p1
self.p2 = p2
self.rowid = rowid
<|end_body_0|>
<|body_start_1|>
volume = self.p0.x * (self.p1.z * self.p2.y - self.p1.y * self.p2.z)
volume += self.p0.y * (self.p1.x * self.p2.z - self.p1.z * self.p2.x)
volume += self.p0... | Tetrahedron3d | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tetrahedron3d:
def __init__(self, p0, p1, p2, rowid=-1):
"""@param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d"""
<|body_0|>
def tetrahedronVolume(self):
"""Funcion que obtiene el volumen del tetraedro formado entre el tri... | stack_v2_sparse_classes_36k_train_018563 | 2,652 | no_license | [
{
"docstring": "@param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d",
"name": "__init__",
"signature": "def __init__(self, p0, p1, p2, rowid=-1)"
},
{
"docstring": "Funcion que obtiene el volumen del tetraedro formado entre el triangulo exterior y el c... | 3 | stack_v2_sparse_classes_30k_train_020314 | Implement the Python class `Tetrahedron3d` described below.
Class description:
Implement the Tetrahedron3d class.
Method signatures and docstrings:
- def __init__(self, p0, p1, p2, rowid=-1): @param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d
- def tetrahedronVolume(self):... | Implement the Python class `Tetrahedron3d` described below.
Class description:
Implement the Tetrahedron3d class.
Method signatures and docstrings:
- def __init__(self, p0, p1, p2, rowid=-1): @param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d
- def tetrahedronVolume(self):... | a93de278ea92ad8d57d66fcb76744d394400bd11 | <|skeleton|>
class Tetrahedron3d:
def __init__(self, p0, p1, p2, rowid=-1):
"""@param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d"""
<|body_0|>
def tetrahedronVolume(self):
"""Funcion que obtiene el volumen del tetraedro formado entre el tri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tetrahedron3d:
def __init__(self, p0, p1, p2, rowid=-1):
"""@param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d"""
self.p0 = p0
self.p1 = p1
self.p2 = p2
self.rowid = rowid
def tetrahedronVolume(self):
"""Funcion ... | the_stack_v2_python_sparse | geometry/controller/geometry_3d/tetrahedron_3d.py | nvergarayi/Cubicador | train | 0 | |
18cd624a6d1ab97fff2a8d7966a3e7e2efa0590a | [
"super(CharCNN, self).__init__()\nself.device = device\nself.char_len = char_len\nself.word_emb_dim = word_emb_dim\nself.kernel_sizes = kernel_sizes\nself.embedding = nn.Embedding(vocab_size, char_emb_dim)\nself.kernels = nn.ModuleList([nn.Conv1d(in_channels=char_emb_dim, out_channels=num_features, kernel_size=kern... | <|body_start_0|>
super(CharCNN, self).__init__()
self.device = device
self.char_len = char_len
self.word_emb_dim = word_emb_dim
self.kernel_sizes = kernel_sizes
self.embedding = nn.Embedding(vocab_size, char_emb_dim)
self.kernels = nn.ModuleList([nn.Conv1d(in_chan... | An implementation of 'Character-Aware Neural Language Models' of Kim et al. (2015). | CharCNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CharCNN:
"""An implementation of 'Character-Aware Neural Language Models' of Kim et al. (2015)."""
def __init__(self, vocab_size: int, char_emb_dim: int, word_emb_dim: int, kernel_sizes: List[List[int]], char_len: int, device: str):
"""Parameters: vocab_size: `int`. Vocabulary size o... | stack_v2_sparse_classes_36k_train_018564 | 4,912 | no_license | [
{
"docstring": "Parameters: vocab_size: `int`. Vocabulary size of chracters used in the model emb_dim: `int`. Embedding size kernel_sizes: A `list` of `list`s of `int`s. The nested list indicates feature maps for the convolutions in the paper (i.e. [(kernel_size, # kernels), ...]) char_len: 'int'. Character len... | 2 | stack_v2_sparse_classes_30k_train_007489 | Implement the Python class `CharCNN` described below.
Class description:
An implementation of 'Character-Aware Neural Language Models' of Kim et al. (2015).
Method signatures and docstrings:
- def __init__(self, vocab_size: int, char_emb_dim: int, word_emb_dim: int, kernel_sizes: List[List[int]], char_len: int, devic... | Implement the Python class `CharCNN` described below.
Class description:
An implementation of 'Character-Aware Neural Language Models' of Kim et al. (2015).
Method signatures and docstrings:
- def __init__(self, vocab_size: int, char_emb_dim: int, word_emb_dim: int, kernel_sizes: List[List[int]], char_len: int, devic... | ca033284850147b334d3771df8235a1135eba76c | <|skeleton|>
class CharCNN:
"""An implementation of 'Character-Aware Neural Language Models' of Kim et al. (2015)."""
def __init__(self, vocab_size: int, char_emb_dim: int, word_emb_dim: int, kernel_sizes: List[List[int]], char_len: int, device: str):
"""Parameters: vocab_size: `int`. Vocabulary size o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CharCNN:
"""An implementation of 'Character-Aware Neural Language Models' of Kim et al. (2015)."""
def __init__(self, vocab_size: int, char_emb_dim: int, word_emb_dim: int, kernel_sizes: List[List[int]], char_len: int, device: str):
"""Parameters: vocab_size: `int`. Vocabulary size of chracters u... | the_stack_v2_python_sparse | papers/4.ELMo/char_cnn.py | euhkim/NLP | train | 0 |
34aa7b91b0f5d2cbaf2df9c3986ace0ec5603b41 | [
"self.fs_type = fs_type\nself.read_only = read_only\nself.secret_ref = secret_ref\nself.volume_name = volume_name\nself.volume_namespace = volume_namespace",
"if dictionary is None:\n return None\nfs_type = dictionary.get('fsType')\nread_only = dictionary.get('readOnly')\nsecret_ref = cohesity_management_sdk.m... | <|body_start_0|>
self.fs_type = fs_type
self.read_only = read_only
self.secret_ref = secret_ref
self.volume_name = volume_name
self.volume_namespace = volume_namespace
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
fs_type = dictio... | Implementation of the 'PodInfo_PodSpec_VolumeInfo_StorageOS' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. read_only (bool): TODO: Type description here. secret_ref (ObjectReference): TODO: Type description here. volume_name (string): TODO: Type description here. volume_... | PodInfo_PodSpec_VolumeInfo_StorageOS | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PodInfo_PodSpec_VolumeInfo_StorageOS:
"""Implementation of the 'PodInfo_PodSpec_VolumeInfo_StorageOS' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. read_only (bool): TODO: Type description here. secret_ref (ObjectReference): TODO: Type description ... | stack_v2_sparse_classes_36k_train_018565 | 2,532 | permissive | [
{
"docstring": "Constructor for the PodInfo_PodSpec_VolumeInfo_StorageOS class",
"name": "__init__",
"signature": "def __init__(self, fs_type=None, read_only=None, secret_ref=None, volume_name=None, volume_namespace=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Ar... | 2 | null | Implement the Python class `PodInfo_PodSpec_VolumeInfo_StorageOS` described below.
Class description:
Implementation of the 'PodInfo_PodSpec_VolumeInfo_StorageOS' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. read_only (bool): TODO: Type description here. secret_ref (Ob... | Implement the Python class `PodInfo_PodSpec_VolumeInfo_StorageOS` described below.
Class description:
Implementation of the 'PodInfo_PodSpec_VolumeInfo_StorageOS' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. read_only (bool): TODO: Type description here. secret_ref (Ob... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class PodInfo_PodSpec_VolumeInfo_StorageOS:
"""Implementation of the 'PodInfo_PodSpec_VolumeInfo_StorageOS' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. read_only (bool): TODO: Type description here. secret_ref (ObjectReference): TODO: Type description ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PodInfo_PodSpec_VolumeInfo_StorageOS:
"""Implementation of the 'PodInfo_PodSpec_VolumeInfo_StorageOS' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. read_only (bool): TODO: Type description here. secret_ref (ObjectReference): TODO: Type description here. volume_... | the_stack_v2_python_sparse | cohesity_management_sdk/models/pod_info_pod_spec_volume_info_storage_os.py | cohesity/management-sdk-python | train | 24 |
d0c44c99119ac2e02260ff2f0b0d23a3c6d45be4 | [
"super().__init__()\nself.weights = torch.nn.Parameter(torch.zeros(feature_number, feature_number))\ntorch.nn.init.xavier_uniform_(self.weights)",
"attention = torch.nn.functional.normalize(self.weights, dim=-1)\nleft_representations = torch.nn.functional.normalize(left_representations, dim=-1)\nright_representat... | <|body_start_0|>
super().__init__()
self.weights = torch.nn.Parameter(torch.zeros(feature_number, feature_number))
torch.nn.init.xavier_uniform_(self.weights)
<|end_body_0|>
<|body_start_1|>
attention = torch.nn.functional.normalize(self.weights, dim=-1)
left_representations = t... | Attention layer. | EmbeddingLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmbeddingLayer:
"""Attention layer."""
def __init__(self, feature_number: int):
"""Initialize the relational embedding layer. :param feature_number: Number of features."""
<|body_0|>
def forward(self, left_representations: torch.FloatTensor, right_representations: torch.... | stack_v2_sparse_classes_36k_train_018566 | 25,672 | no_license | [
{
"docstring": "Initialize the relational embedding layer. :param feature_number: Number of features.",
"name": "__init__",
"signature": "def __init__(self, feature_number: int)"
},
{
"docstring": "Make a forward pass with the drug representations. :param left_representations: Left side drug rep... | 2 | stack_v2_sparse_classes_30k_train_008353 | Implement the Python class `EmbeddingLayer` described below.
Class description:
Attention layer.
Method signatures and docstrings:
- def __init__(self, feature_number: int): Initialize the relational embedding layer. :param feature_number: Number of features.
- def forward(self, left_representations: torch.FloatTenso... | Implement the Python class `EmbeddingLayer` described below.
Class description:
Attention layer.
Method signatures and docstrings:
- def __init__(self, feature_number: int): Initialize the relational embedding layer. :param feature_number: Number of features.
- def forward(self, left_representations: torch.FloatTenso... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class EmbeddingLayer:
"""Attention layer."""
def __init__(self, feature_number: int):
"""Initialize the relational embedding layer. :param feature_number: Number of features."""
<|body_0|>
def forward(self, left_representations: torch.FloatTensor, right_representations: torch.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmbeddingLayer:
"""Attention layer."""
def __init__(self, feature_number: int):
"""Initialize the relational embedding layer. :param feature_number: Number of features."""
super().__init__()
self.weights = torch.nn.Parameter(torch.zeros(feature_number, feature_number))
tor... | the_stack_v2_python_sparse | generated/test_AstraZeneca_chemicalx.py | jansel/pytorch-jit-paritybench | train | 35 |
1d060ca1719316864ea9d464e9612fef4139dda4 | [
"self._cpu = CPU()\nself._memory = Memory()\nself._hard_drive = HardDrive()",
"self._cpu.freeze()\nself._memory.load_data(self._hard_drive.read_data(self._BOOT_SECTOR, self._SECTOR_SIZE), self._BOOT_ADDRESS)\nself._cpu.jump(self._BOOT_ADDRESS)\nself._cpu.execute()"
] | <|body_start_0|>
self._cpu = CPU()
self._memory = Memory()
self._hard_drive = HardDrive()
<|end_body_0|>
<|body_start_1|>
self._cpu.freeze()
self._memory.load_data(self._hard_drive.read_data(self._BOOT_SECTOR, self._SECTOR_SIZE), self._BOOT_ADDRESS)
self._cpu.jump(self._... | Facade class for computer that serves as a front-facing interface masking more complex sub-components to simplify the usage for client and minimize the dependencies between the client and the sub-components. | ComputerFacade | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComputerFacade:
"""Facade class for computer that serves as a front-facing interface masking more complex sub-components to simplify the usage for client and minimize the dependencies between the client and the sub-components."""
def __init__(self):
"""Default constructor."""
... | stack_v2_sparse_classes_36k_train_018567 | 2,600 | permissive | [
{
"docstring": "Default constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Starts this computer. :return: None",
"name": "start",
"signature": "def start(self) -> None"
}
] | 2 | null | Implement the Python class `ComputerFacade` described below.
Class description:
Facade class for computer that serves as a front-facing interface masking more complex sub-components to simplify the usage for client and minimize the dependencies between the client and the sub-components.
Method signatures and docstrin... | Implement the Python class `ComputerFacade` described below.
Class description:
Facade class for computer that serves as a front-facing interface masking more complex sub-components to simplify the usage for client and minimize the dependencies between the client and the sub-components.
Method signatures and docstrin... | 7a8167a85456b481aba15d5eee5a64b116b00adc | <|skeleton|>
class ComputerFacade:
"""Facade class for computer that serves as a front-facing interface masking more complex sub-components to simplify the usage for client and minimize the dependencies between the client and the sub-components."""
def __init__(self):
"""Default constructor."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComputerFacade:
"""Facade class for computer that serves as a front-facing interface masking more complex sub-components to simplify the usage for client and minimize the dependencies between the client and the sub-components."""
def __init__(self):
"""Default constructor."""
self._cpu = ... | the_stack_v2_python_sparse | 3-Structural Patterns/7-Facade Pattern/Computer Example/Python/computer.py | Ziang-Lu/Design-Patterns | train | 2 |
9b26d6fbd196081dc66411ec59b0eba1117f9344 | [
"item = RequestBids.query.filter_by(id=request_bid_id).first()\nif not item:\n return abort(404, 'request_bid_id not found')\nreturn jsonify(item.to_json())",
"item = RequestBids.query.filter_by(id=request_bid_id).first()\nif item and item.user_id == g.user.id:\n item.delete()\n return jsonify(dict(succe... | <|body_start_0|>
item = RequestBids.query.filter_by(id=request_bid_id).first()
if not item:
return abort(404, 'request_bid_id not found')
return jsonify(item.to_json())
<|end_body_0|>
<|body_start_1|>
item = RequestBids.query.filter_by(id=request_bid_id).first()
if i... | RequestBidAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequestBidAPI:
def get(self, request_bid_id):
"""get details request_bid_id"""
<|body_0|>
def delete(self, request_bid_id):
"""delete request_bid_id"""
<|body_1|>
def put(self, request_bid_id):
"""update request_bid_id"""
<|body_2|>
<|en... | stack_v2_sparse_classes_36k_train_018568 | 4,039 | no_license | [
{
"docstring": "get details request_bid_id",
"name": "get",
"signature": "def get(self, request_bid_id)"
},
{
"docstring": "delete request_bid_id",
"name": "delete",
"signature": "def delete(self, request_bid_id)"
},
{
"docstring": "update request_bid_id",
"name": "put",
... | 3 | stack_v2_sparse_classes_30k_train_019319 | Implement the Python class `RequestBidAPI` described below.
Class description:
Implement the RequestBidAPI class.
Method signatures and docstrings:
- def get(self, request_bid_id): get details request_bid_id
- def delete(self, request_bid_id): delete request_bid_id
- def put(self, request_bid_id): update request_bid_... | Implement the Python class `RequestBidAPI` described below.
Class description:
Implement the RequestBidAPI class.
Method signatures and docstrings:
- def get(self, request_bid_id): get details request_bid_id
- def delete(self, request_bid_id): delete request_bid_id
- def put(self, request_bid_id): update request_bid_... | 1c7d812e214590e0f4759e6c5be411bd64f8e3c4 | <|skeleton|>
class RequestBidAPI:
def get(self, request_bid_id):
"""get details request_bid_id"""
<|body_0|>
def delete(self, request_bid_id):
"""delete request_bid_id"""
<|body_1|>
def put(self, request_bid_id):
"""update request_bid_id"""
<|body_2|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequestBidAPI:
def get(self, request_bid_id):
"""get details request_bid_id"""
item = RequestBids.query.filter_by(id=request_bid_id).first()
if not item:
return abort(404, 'request_bid_id not found')
return jsonify(item.to_json())
def delete(self, request_bid_i... | the_stack_v2_python_sparse | apis/bids.py | ajutor-app/backend | train | 0 | |
d3dfc731a62bcb7b8d1a35807286cdde242f7057 | [
"Frame.__init__(self, master)\nself.grid()\nself.create_widgets()",
"Label(self, text='Choose your favorite movie type').grid(row=0, column=0, sticky=W)\nLabel(self, text='Select all that apply:').grid(row=1, column=0, sticky=W)\nself.comedy = BooleanVar()\nCheckbutton(self, text='Comedy', variable=self.comedy, c... | <|body_start_0|>
Frame.__init__(self, master)
self.grid()
self.create_widgets()
<|end_body_0|>
<|body_start_1|>
Label(self, text='Choose your favorite movie type').grid(row=0, column=0, sticky=W)
Label(self, text='Select all that apply:').grid(row=1, column=0, sticky=W)
... | Application | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
def __init__(self, master):
"""initialize the Frame"""
<|body_0|>
def create_widgets(self):
"""create widgets for movie type choice"""
<|body_1|>
def update_text(self):
"""update text widget and display favorite movie types"""
... | stack_v2_sparse_classes_36k_train_018569 | 1,854 | no_license | [
{
"docstring": "initialize the Frame",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "create widgets for movie type choice",
"name": "create_widgets",
"signature": "def create_widgets(self)"
},
{
"docstring": "update text widget and display favor... | 3 | stack_v2_sparse_classes_30k_train_013898 | Implement the Python class `Application` described below.
Class description:
Implement the Application class.
Method signatures and docstrings:
- def __init__(self, master): initialize the Frame
- def create_widgets(self): create widgets for movie type choice
- def update_text(self): update text widget and display fa... | Implement the Python class `Application` described below.
Class description:
Implement the Application class.
Method signatures and docstrings:
- def __init__(self, master): initialize the Frame
- def create_widgets(self): create widgets for movie type choice
- def update_text(self): update text widget and display fa... | 728a8614fa50e3de0541efa87f71ec047326d66a | <|skeleton|>
class Application:
def __init__(self, master):
"""initialize the Frame"""
<|body_0|>
def create_widgets(self):
"""create widgets for movie type choice"""
<|body_1|>
def update_text(self):
"""update text widget and display favorite movie types"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Application:
def __init__(self, master):
"""initialize the Frame"""
Frame.__init__(self, master)
self.grid()
self.create_widgets()
def create_widgets(self):
"""create widgets for movie type choice"""
Label(self, text='Choose your favorite movie type').grid(... | the_stack_v2_python_sparse | src/Ex14/check_box.py | lil-val/she-codes | train | 0 | |
be61de41076fae63ad04c0beee3b101c50e2ae5e | [
"def dfs(node):\n if node is None:\n return\n l = node.left\n r = node.right\n while l:\n l.next = r\n l = l.right\n r = r.left\n if node.left:\n dfs(node.left)\n dfs(node.right)\ndfs(root)\nreturn root",
"from collections import deque\nif root is None:\n ... | <|body_start_0|>
def dfs(node):
if node is None:
return
l = node.left
r = node.right
while l:
l.next = r
l = l.right
r = r.left
if node.left:
dfs(node.left)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def connect(self, root: 'Node') -> 'Node':
"""Recursive1, Time: O(n), Space: O(logn) for recursive stack"""
<|body_0|>
def connect(self, root: 'Node') -> 'Node':
"""BFS, Time: O(n), Space: O(logn)"""
<|body_1|>
def connect(self, root: 'Node') -... | stack_v2_sparse_classes_36k_train_018570 | 2,251 | no_license | [
{
"docstring": "Recursive1, Time: O(n), Space: O(logn) for recursive stack",
"name": "connect",
"signature": "def connect(self, root: 'Node') -> 'Node'"
},
{
"docstring": "BFS, Time: O(n), Space: O(logn)",
"name": "connect",
"signature": "def connect(self, root: 'Node') -> 'Node'"
},
... | 4 | stack_v2_sparse_classes_30k_train_014592 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def connect(self, root: 'Node') -> 'Node': Recursive1, Time: O(n), Space: O(logn) for recursive stack
- def connect(self, root: 'Node') -> 'Node': BFS, Time: O(n), Space: O(logn)... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def connect(self, root: 'Node') -> 'Node': Recursive1, Time: O(n), Space: O(logn) for recursive stack
- def connect(self, root: 'Node') -> 'Node': BFS, Time: O(n), Space: O(logn)... | 72136e3487d239f5b37e2d6393e034262a6bf599 | <|skeleton|>
class Solution:
def connect(self, root: 'Node') -> 'Node':
"""Recursive1, Time: O(n), Space: O(logn) for recursive stack"""
<|body_0|>
def connect(self, root: 'Node') -> 'Node':
"""BFS, Time: O(n), Space: O(logn)"""
<|body_1|>
def connect(self, root: 'Node') -... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def connect(self, root: 'Node') -> 'Node':
"""Recursive1, Time: O(n), Space: O(logn) for recursive stack"""
def dfs(node):
if node is None:
return
l = node.left
r = node.right
while l:
l.next = r
... | the_stack_v2_python_sparse | python/116-Populating Next Right Pointers in Each Node.py | cwza/leetcode | train | 0 | |
b2c6b168c014ce163b75ae9192dc9c59ecd46238 | [
"cur, prev = (root, None)\nres = []\nwhile cur:\n if not cur.left:\n res.append(cur.val)\n cur = cur.right\n else:\n prev = cur.left\n while prev.right and prev.right != cur:\n prev = prev.right\n if not prev.right:\n res.append(cur.val)\n pr... | <|body_start_0|>
cur, prev = (root, None)
res = []
while cur:
if not cur.left:
res.append(cur.val)
cur = cur.right
else:
prev = cur.left
while prev.right and prev.right != cur:
prev = prev... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def preorderTraversal_on(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cur, prev = (root, N... | stack_v2_sparse_classes_36k_train_018571 | 1,475 | permissive | [
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "preorderTraversal_on",
"signature": "def preorderTraversal_on(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def preorderTraversal_on(self, root): :type root: TreeNode :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def preorderTraversal_on(self, root): :type root: TreeNode :rtype: List[int]
<|skeleton|>
class Solut... | 86f1cb98de801f58c39d9a48ce9de12df7303d20 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def preorderTraversal_on(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
cur, prev = (root, None)
res = []
while cur:
if not cur.left:
res.append(cur.val)
cur = cur.right
else:
prev = cur.l... | the_stack_v2_python_sparse | 144-Binary-Tree-Preorder-Traversal/solution.py | Tanych/CodeTracking | train | 0 | |
d9e557ec3e189281715e55d81fa18c5f3dcfe623 | [
"super().__init__()\nif dim == 1:\n conv = nn.Conv1d\n bn = nn.BatchNorm1d\nelif dim == 2:\n conv = nn.Conv2d\n bn = nn.BatchNorm2d\nelse:\n raise ValueError\nif not isinstance(out_channels, (list, tuple)):\n out_channels = [out_channels]\nlayers = []\nfor oc in out_channels:\n layers.extend([c... | <|body_start_0|>
super().__init__()
if dim == 1:
conv = nn.Conv1d
bn = nn.BatchNorm1d
elif dim == 2:
conv = nn.Conv2d
bn = nn.BatchNorm2d
else:
raise ValueError
if not isinstance(out_channels, (list, tuple)):
... | SharedMLP Module, comprising Conv2d, BatchNorm and ReLU blocks. | SharedMLP | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SharedMLP:
"""SharedMLP Module, comprising Conv2d, BatchNorm and ReLU blocks."""
def __init__(self, in_channels, out_channels, dim=1):
"""Constructor for SharedMLP Block. Args: in_channels: Number of input channels. out_channels: Number of output channels. dim: Input dimension"""
... | stack_v2_sparse_classes_36k_train_018572 | 22,879 | permissive | [
{
"docstring": "Constructor for SharedMLP Block. Args: in_channels: Number of input channels. out_channels: Number of output channels. dim: Input dimension",
"name": "__init__",
"signature": "def __init__(self, in_channels, out_channels, dim=1)"
},
{
"docstring": "Forward pass for SharedMLP Args... | 2 | stack_v2_sparse_classes_30k_train_019438 | Implement the Python class `SharedMLP` described below.
Class description:
SharedMLP Module, comprising Conv2d, BatchNorm and ReLU blocks.
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, dim=1): Constructor for SharedMLP Block. Args: in_channels: Number of input channels. out_channel... | Implement the Python class `SharedMLP` described below.
Class description:
SharedMLP Module, comprising Conv2d, BatchNorm and ReLU blocks.
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, dim=1): Constructor for SharedMLP Block. Args: in_channels: Number of input channels. out_channel... | 51482281dc180786e7563c73c12ac5df89289748 | <|skeleton|>
class SharedMLP:
"""SharedMLP Module, comprising Conv2d, BatchNorm and ReLU blocks."""
def __init__(self, in_channels, out_channels, dim=1):
"""Constructor for SharedMLP Block. Args: in_channels: Number of input channels. out_channels: Number of output channels. dim: Input dimension"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SharedMLP:
"""SharedMLP Module, comprising Conv2d, BatchNorm and ReLU blocks."""
def __init__(self, in_channels, out_channels, dim=1):
"""Constructor for SharedMLP Block. Args: in_channels: Number of input channels. out_channels: Number of output channels. dim: Input dimension"""
super().... | the_stack_v2_python_sparse | ml3d/torch/models/pvcnn.py | CosmosHua/Open3D-ML | train | 0 |
db5291bd94f5b45b7d05fbed6fdaac1a159b6e23 | [
"w, h = (len(board), len(board[0]))\nboard_p = np.zeros((w + 2, h + 2))\nboard_p[1:w + 1, 1:h + 1] = board\nfor i in range(1, w + 1):\n for j in range(1, h + 1):\n value = self.conv2d(board_p, i, j)\n if value > 3 or value < 2:\n board[i - 1][j - 1] = 0\n elif value == 3:\n ... | <|body_start_0|>
w, h = (len(board), len(board[0]))
board_p = np.zeros((w + 2, h + 2))
board_p[1:w + 1, 1:h + 1] = board
for i in range(1, w + 1):
for j in range(1, h + 1):
value = self.conv2d(board_p, i, j)
if value > 3 or value < 2:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def gameOfLife(self, board) -> None:
"""Do not return anything, modify board in-place instead."""
<|body_0|>
def conv2d(self, board_p, i, j):
"""convolution implemention :para board_p: board after 0 padding(np.array) i,j : loction :output value_convolution"... | stack_v2_sparse_classes_36k_train_018573 | 3,141 | permissive | [
{
"docstring": "Do not return anything, modify board in-place instead.",
"name": "gameOfLife",
"signature": "def gameOfLife(self, board) -> None"
},
{
"docstring": "convolution implemention :para board_p: board after 0 padding(np.array) i,j : loction :output value_convolution",
"name": "conv... | 2 | stack_v2_sparse_classes_30k_train_000671 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def gameOfLife(self, board) -> None: Do not return anything, modify board in-place instead.
- def conv2d(self, board_p, i, j): convolution implemention :para board_p: board after... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def gameOfLife(self, board) -> None: Do not return anything, modify board in-place instead.
- def conv2d(self, board_p, i, j): convolution implemention :para board_p: board after... | 91c8b09c278f5abb67e90f0096fc83bef975647b | <|skeleton|>
class Solution:
def gameOfLife(self, board) -> None:
"""Do not return anything, modify board in-place instead."""
<|body_0|>
def conv2d(self, board_p, i, j):
"""convolution implemention :para board_p: board after 0 padding(np.array) i,j : loction :output value_convolution"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def gameOfLife(self, board) -> None:
"""Do not return anything, modify board in-place instead."""
w, h = (len(board), len(board[0]))
board_p = np.zeros((w + 2, h + 2))
board_p[1:w + 1, 1:h + 1] = board
for i in range(1, w + 1):
for j in range(1, h ... | the_stack_v2_python_sparse | 289LifeGame/GameOfLife.py | Easonyesheng/CodePractice | train | 0 | |
ea8121a54b5b2caa22f5d479eb911057149648e5 | [
"self.possible_steps = step_list\nself.all_combinations = []\nself.slice_with_multiple_scales(range(n), self.possible_steps)\nreturn len(self.all_combinations)",
"target_length = len(target)\nfor step in step_list:\n clone_pieces = current_pieces[:]\n slice_index = current_index + step\n piece = target[c... | <|body_start_0|>
self.possible_steps = step_list
self.all_combinations = []
self.slice_with_multiple_scales(range(n), self.possible_steps)
return len(self.all_combinations)
<|end_body_0|>
<|body_start_1|>
target_length = len(target)
for step in step_list:
clo... | 目前此种方法failed了，超时, 在输入值为35的时候。此方法可以获得解，但算法复杂度太高。但是此种方法可以显示出所有的组合。 | SolutionFailed1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SolutionFailed1:
"""目前此种方法failed了，超时, 在输入值为35的时候。此方法可以获得解，但算法复杂度太高。但是此种方法可以显示出所有的组合。"""
def climbStairs(self, n, step_list=[1, 2]):
""":type n: int :rtype: int"""
<|body_0|>
def slice_with_multiple_scales(self, target, step_list, current_index=0, current_pieces=[]):
... | stack_v2_sparse_classes_36k_train_018574 | 4,780 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs",
"signature": "def climbStairs(self, n, step_list=[1, 2])"
},
{
"docstring": "一个任意长度的有序列表，可以按照参数列表里提供的n种尺度进行连续切分，返回最后可能的切分结果总数",
"name": "slice_with_multiple_scales",
"signature": "def slice_with_multiple_scales(self, targe... | 2 | null | Implement the Python class `SolutionFailed1` described below.
Class description:
目前此种方法failed了，超时, 在输入值为35的时候。此方法可以获得解，但算法复杂度太高。但是此种方法可以显示出所有的组合。
Method signatures and docstrings:
- def climbStairs(self, n, step_list=[1, 2]): :type n: int :rtype: int
- def slice_with_multiple_scales(self, target, step_list, current_i... | Implement the Python class `SolutionFailed1` described below.
Class description:
目前此种方法failed了，超时, 在输入值为35的时候。此方法可以获得解，但算法复杂度太高。但是此种方法可以显示出所有的组合。
Method signatures and docstrings:
- def climbStairs(self, n, step_list=[1, 2]): :type n: int :rtype: int
- def slice_with_multiple_scales(self, target, step_list, current_i... | 2a7401c6e407db533877de6e20a2b523f7964fdb | <|skeleton|>
class SolutionFailed1:
"""目前此种方法failed了，超时, 在输入值为35的时候。此方法可以获得解，但算法复杂度太高。但是此种方法可以显示出所有的组合。"""
def climbStairs(self, n, step_list=[1, 2]):
""":type n: int :rtype: int"""
<|body_0|>
def slice_with_multiple_scales(self, target, step_list, current_index=0, current_pieces=[]):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SolutionFailed1:
"""目前此种方法failed了，超时, 在输入值为35的时候。此方法可以获得解，但算法复杂度太高。但是此种方法可以显示出所有的组合。"""
def climbStairs(self, n, step_list=[1, 2]):
""":type n: int :rtype: int"""
self.possible_steps = step_list
self.all_combinations = []
self.slice_with_multiple_scales(range(n), self.poss... | the_stack_v2_python_sparse | THEORIES/algorithm/leetcode/Y70_Climbing_Stairs.py | bb2qqq/tech_notes | train | 0 |
d0c44c99119ac2e02260ff2f0b0d23a3c6d45be4 | [
"super().__init__()\nself.weight_query = torch.nn.Parameter(torch.zeros(feature_number, feature_number // 2))\nself.weight_key = torch.nn.Parameter(torch.zeros(feature_number, feature_number // 2))\nself.bias = torch.nn.Parameter(torch.zeros(feature_number // 2))\nself.attention = torch.nn.Parameter(torch.zeros(fea... | <|body_start_0|>
super().__init__()
self.weight_query = torch.nn.Parameter(torch.zeros(feature_number, feature_number // 2))
self.weight_key = torch.nn.Parameter(torch.zeros(feature_number, feature_number // 2))
self.bias = torch.nn.Parameter(torch.zeros(feature_number // 2))
sel... | Co-attention layer for drug pairs. | DrugDrugAttentionLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DrugDrugAttentionLayer:
"""Co-attention layer for drug pairs."""
def __init__(self, feature_number: int):
"""Initialize the co-attention layer. :param feature_number: Number of input features."""
<|body_0|>
def forward(self, left_representations: torch.Tensor, right_repr... | stack_v2_sparse_classes_36k_train_018575 | 25,672 | no_license | [
{
"docstring": "Initialize the co-attention layer. :param feature_number: Number of input features.",
"name": "__init__",
"signature": "def __init__(self, feature_number: int)"
},
{
"docstring": "Make a forward pass with the co-attention calculation. :param left_representations: Matrix of left h... | 2 | stack_v2_sparse_classes_30k_train_011780 | Implement the Python class `DrugDrugAttentionLayer` described below.
Class description:
Co-attention layer for drug pairs.
Method signatures and docstrings:
- def __init__(self, feature_number: int): Initialize the co-attention layer. :param feature_number: Number of input features.
- def forward(self, left_represent... | Implement the Python class `DrugDrugAttentionLayer` described below.
Class description:
Co-attention layer for drug pairs.
Method signatures and docstrings:
- def __init__(self, feature_number: int): Initialize the co-attention layer. :param feature_number: Number of input features.
- def forward(self, left_represent... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class DrugDrugAttentionLayer:
"""Co-attention layer for drug pairs."""
def __init__(self, feature_number: int):
"""Initialize the co-attention layer. :param feature_number: Number of input features."""
<|body_0|>
def forward(self, left_representations: torch.Tensor, right_repr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DrugDrugAttentionLayer:
"""Co-attention layer for drug pairs."""
def __init__(self, feature_number: int):
"""Initialize the co-attention layer. :param feature_number: Number of input features."""
super().__init__()
self.weight_query = torch.nn.Parameter(torch.zeros(feature_number,... | the_stack_v2_python_sparse | generated/test_AstraZeneca_chemicalx.py | jansel/pytorch-jit-paritybench | train | 35 |
2724fd1e7bc09a955f1e5d13e87b1a834e4566ac | [
"super().__init__()\nself.norm = nn.InstanceNorm1D(in_channels, momentum=0.1, data_format='NCL', weight_attr=False, bias_attr=False)\nself.aux_conv = nn.Sequential(nn.Conv1D(aux_channels, in_channels, kernel_size, 1, bias_attr=bias, padding=(kernel_size - 1) // 2))\nself.gated_conv = nn.Sequential(nn.Conv1D(in_chan... | <|body_start_0|>
super().__init__()
self.norm = nn.InstanceNorm1D(in_channels, momentum=0.1, data_format='NCL', weight_attr=False, bias_attr=False)
self.aux_conv = nn.Sequential(nn.Conv1D(aux_channels, in_channels, kernel_size, 1, bias_attr=bias, padding=(kernel_size - 1) // 2))
self.gat... | TADE Layer module. | TADELayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TADELayer:
"""TADE Layer module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'):
"""Initilize TADE layer."""
<|body_0|>
def forward(self, x, c):
"""Calcul... | stack_v2_sparse_classes_36k_train_018576 | 5,634 | permissive | [
{
"docstring": "Initilize TADE layer.",
"name": "__init__",
"signature": "def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest')"
},
{
"docstring": "Calculate forward propagation. Args: x (Tensor): ... | 2 | null | Implement the Python class `TADELayer` described below.
Class description:
TADE Layer module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'): Initilize TADE layer.
- def forwar... | Implement the Python class `TADELayer` described below.
Class description:
TADE Layer module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'): Initilize TADE layer.
- def forwar... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class TADELayer:
"""TADE Layer module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'):
"""Initilize TADE layer."""
<|body_0|>
def forward(self, x, c):
"""Calcul... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TADELayer:
"""TADE Layer module."""
def __init__(self, in_channels: int=64, aux_channels: int=80, kernel_size: int=9, bias: bool=True, upsample_factor: int=2, upsample_mode: str='nearest'):
"""Initilize TADE layer."""
super().__init__()
self.norm = nn.InstanceNorm1D(in_channels, m... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/tade_res_block.py | anniyanvr/DeepSpeech-1 | train | 0 |
fdb0155429b27491aa1b76045027aab6c2ecd05e | [
"optimizer.Optimizer.__init__(self, **kwargs)\nself.stepKind = kwargs['step']\nself.optimalPoint = kwargs['x0']\nself.lineSearch = kwargs['line_search']\nself.state['new_parameters'] = self.optimalPoint\nself.state['new_value'] = self.function(self.optimalPoint)\nself.recordHistory(**self.state)",
"self.state['ol... | <|body_start_0|>
optimizer.Optimizer.__init__(self, **kwargs)
self.stepKind = kwargs['step']
self.optimalPoint = kwargs['x0']
self.lineSearch = kwargs['line_search']
self.state['new_parameters'] = self.optimalPoint
self.state['new_value'] = self.function(self.optimalPoint... | A standard optimizer, takes a step and finds the best candidate Must give in self.optimalPoint the optimal point after optimization | StandardOptimizer | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardOptimizer:
"""A standard optimizer, takes a step and finds the best candidate Must give in self.optimalPoint the optimal point after optimization"""
def __init__(self, **kwargs):
"""Needs to have : - an object function to optimize (function), alternatively a function ('fun'),... | stack_v2_sparse_classes_36k_train_018577 | 2,378 | permissive | [
{
"docstring": "Needs to have : - an object function to optimize (function), alternatively a function ('fun'), gradient ('gradient'), ... - a way to get a new point, that is a step (step) - a criterion to stop the optimization (criterion) - a starting point (x0) - a way to find the best point on a line (lineSea... | 2 | null | Implement the Python class `StandardOptimizer` described below.
Class description:
A standard optimizer, takes a step and finds the best candidate Must give in self.optimalPoint the optimal point after optimization
Method signatures and docstrings:
- def __init__(self, **kwargs): Needs to have : - an object function ... | Implement the Python class `StandardOptimizer` described below.
Class description:
A standard optimizer, takes a step and finds the best candidate Must give in self.optimalPoint the optimal point after optimization
Method signatures and docstrings:
- def __init__(self, **kwargs): Needs to have : - an object function ... | 3d298e908ff55340cd3612078508be0c791f63a8 | <|skeleton|>
class StandardOptimizer:
"""A standard optimizer, takes a step and finds the best candidate Must give in self.optimalPoint the optimal point after optimization"""
def __init__(self, **kwargs):
"""Needs to have : - an object function to optimize (function), alternatively a function ('fun'),... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StandardOptimizer:
"""A standard optimizer, takes a step and finds the best candidate Must give in self.optimalPoint the optimal point after optimization"""
def __init__(self, **kwargs):
"""Needs to have : - an object function to optimize (function), alternatively a function ('fun'), gradient ('g... | the_stack_v2_python_sparse | PyDSTool/Toolbox/optimizers/optimizer/standard_optimizer.py | mdlama/pydstool | train | 2 |
159437dc3d490b4982953cd6dbeccee803bf2e60 | [
"self.auth_before_sign = auth_before_sign\nself.social_security_number = social_security_number\nself.signature_method_unique_id = signature_method_unique_id\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nauth_before_sign = dictionary.get('authBeforeSign')\nsocial_... | <|body_start_0|>
self.auth_before_sign = auth_before_sign
self.social_security_number = social_security_number
self.signature_method_unique_id = signature_method_unique_id
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
... | Implementation of the 'Authentication' model. TODO: type model description here. Attributes: auth_before_sign (bool): If this is set to true, you have to include the social security number or SignatureMethod unique id for the signer social_security_number (string): The signers social security number signature_method_un... | Authentication | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Authentication:
"""Implementation of the 'Authentication' model. TODO: type model description here. Attributes: auth_before_sign (bool): If this is set to true, you have to include the social security number or SignatureMethod unique id for the signer social_security_number (string): The signers ... | stack_v2_sparse_classes_36k_train_018578 | 2,927 | permissive | [
{
"docstring": "Constructor for the Authentication class",
"name": "__init__",
"signature": "def __init__(self, auth_before_sign=None, social_security_number=None, signature_method_unique_id=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary A... | 2 | null | Implement the Python class `Authentication` described below.
Class description:
Implementation of the 'Authentication' model. TODO: type model description here. Attributes: auth_before_sign (bool): If this is set to true, you have to include the social security number or SignatureMethod unique id for the signer social... | Implement the Python class `Authentication` described below.
Class description:
Implementation of the 'Authentication' model. TODO: type model description here. Attributes: auth_before_sign (bool): If this is set to true, you have to include the social security number or SignatureMethod unique id for the signer social... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class Authentication:
"""Implementation of the 'Authentication' model. TODO: type model description here. Attributes: auth_before_sign (bool): If this is set to true, you have to include the social security number or SignatureMethod unique id for the signer social_security_number (string): The signers ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Authentication:
"""Implementation of the 'Authentication' model. TODO: type model description here. Attributes: auth_before_sign (bool): If this is set to true, you have to include the social security number or SignatureMethod unique id for the signer social_security_number (string): The signers social securi... | the_stack_v2_python_sparse | idfy_rest_client/models/authentication.py | dealflowteam/Idfy | train | 0 |
e15b9ea79199ae4e6e607eb7695a6c594e39e43e | [
"self.num_archival_runs = num_archival_runs\nself.num_backup_runs = num_backup_runs\nself.num_replication_runs = num_replication_runs",
"if dictionary is None:\n return None\nnum_archival_runs = dictionary.get('numArchivalRuns')\nnum_backup_runs = dictionary.get('numBackupRuns')\nnum_replication_runs = diction... | <|body_start_0|>
self.num_archival_runs = num_archival_runs
self.num_backup_runs = num_backup_runs
self.num_replication_runs = num_replication_runs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
num_archival_runs = dictionary.get('numArchivalRuns'... | Implementation of the 'ProtectionRunsStats' model. Specifies the Protection Runs statistics response. Attributes: num_archival_runs (long|int): Specifies the count of archival Runs. num_backup_runs (long|int): Specifies the count of backup Runs. num_replication_runs (long|int): Specifies the count of replication Runs. | ProtectionRunsStats | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectionRunsStats:
"""Implementation of the 'ProtectionRunsStats' model. Specifies the Protection Runs statistics response. Attributes: num_archival_runs (long|int): Specifies the count of archival Runs. num_backup_runs (long|int): Specifies the count of backup Runs. num_replication_runs (long|... | stack_v2_sparse_classes_36k_train_018579 | 2,056 | permissive | [
{
"docstring": "Constructor for the ProtectionRunsStats class",
"name": "__init__",
"signature": "def __init__(self, num_archival_runs=None, num_backup_runs=None, num_replication_runs=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A d... | 2 | null | Implement the Python class `ProtectionRunsStats` described below.
Class description:
Implementation of the 'ProtectionRunsStats' model. Specifies the Protection Runs statistics response. Attributes: num_archival_runs (long|int): Specifies the count of archival Runs. num_backup_runs (long|int): Specifies the count of b... | Implement the Python class `ProtectionRunsStats` described below.
Class description:
Implementation of the 'ProtectionRunsStats' model. Specifies the Protection Runs statistics response. Attributes: num_archival_runs (long|int): Specifies the count of archival Runs. num_backup_runs (long|int): Specifies the count of b... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ProtectionRunsStats:
"""Implementation of the 'ProtectionRunsStats' model. Specifies the Protection Runs statistics response. Attributes: num_archival_runs (long|int): Specifies the count of archival Runs. num_backup_runs (long|int): Specifies the count of backup Runs. num_replication_runs (long|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtectionRunsStats:
"""Implementation of the 'ProtectionRunsStats' model. Specifies the Protection Runs statistics response. Attributes: num_archival_runs (long|int): Specifies the count of archival Runs. num_backup_runs (long|int): Specifies the count of backup Runs. num_replication_runs (long|int): Specifi... | the_stack_v2_python_sparse | cohesity_management_sdk/models/protection_runs_stats.py | cohesity/management-sdk-python | train | 24 |
05d7b1ba0c012909c0d8a4077fbe12f389d82909 | [
"self.size = 300\nself.counter = [0] * self.size\nself.next, self.cur_time = (1, 1)",
"diff = timestamp - self.cur_time\nif diff >= self.size:\n self.counter = [0] * self.size\nelse:\n diff2 = self.size - self.next - diff\n if diff2 > 0:\n self.counter[self.next:self.next + diff] = [0] * diff\n ... | <|body_start_0|>
self.size = 300
self.counter = [0] * self.size
self.next, self.cur_time = (1, 1)
<|end_body_0|>
<|body_start_1|>
diff = timestamp - self.cur_time
if diff >= self.size:
self.counter = [0] * self.size
else:
diff2 = self.size - self.... | HitCounter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity)."""
<|body_1|>
def getHits(self, timestamp: in... | stack_v2_sparse_classes_36k_train_018580 | 6,469 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Record a hit. @param timestamp - The current timestamp (in seconds granularity).",
"name": "hit",
"signature": "def hit(self, timestamp: int) -> None"
},
{
... | 3 | null | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp: int) -> None: Record a hit. @param timestamp - The current timestamp (in seconds granulari... | Implement the Python class `HitCounter` described below.
Class description:
Implement the HitCounter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def hit(self, timestamp: int) -> None: Record a hit. @param timestamp - The current timestamp (in seconds granulari... | 4a1747b6497305f3821612d9c358a6795b1690da | <|skeleton|>
class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds granularity)."""
<|body_1|>
def getHits(self, timestamp: in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HitCounter:
def __init__(self):
"""Initialize your data structure here."""
self.size = 300
self.counter = [0] * self.size
self.next, self.cur_time = (1, 1)
def hit(self, timestamp: int) -> None:
"""Record a hit. @param timestamp - The current timestamp (in seconds ... | the_stack_v2_python_sparse | HashTable/q362_design_hit_counter.py | sevenhe716/LeetCode | train | 0 | |
03dd5e4d617d1587d96287217541a2f14fb6f3f1 | [
"account_data = validated_data.pop('account')\naccount = User(**account_data)\naccount.set_password(account.password)\naccount.save()\nuser_profile = UserProfileModel.objects.create(account=account, **validated_data)\nreturn user_profile",
"instance.profile_photo = validated_data.get('profile_photo', instance.pro... | <|body_start_0|>
account_data = validated_data.pop('account')
account = User(**account_data)
account.set_password(account.password)
account.save()
user_profile = UserProfileModel.objects.create(account=account, **validated_data)
return user_profile
<|end_body_0|>
<|body_... | The serializer for the user profile model | UserProfileSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfileSerializer:
"""The serializer for the user profile model"""
def create(self, validated_data):
"""Creates a new user profile from the request's data"""
<|body_0|>
def update(self, instance, validated_data):
"""Updates a certain user profile from the req... | stack_v2_sparse_classes_36k_train_018581 | 3,283 | permissive | [
{
"docstring": "Creates a new user profile from the request's data",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "Updates a certain user profile from the request's data",
"name": "update",
"signature": "def update(self, instance, validated_data)"
... | 2 | stack_v2_sparse_classes_30k_train_007997 | Implement the Python class `UserProfileSerializer` described below.
Class description:
The serializer for the user profile model
Method signatures and docstrings:
- def create(self, validated_data): Creates a new user profile from the request's data
- def update(self, instance, validated_data): Updates a certain user... | Implement the Python class `UserProfileSerializer` described below.
Class description:
The serializer for the user profile model
Method signatures and docstrings:
- def create(self, validated_data): Creates a new user profile from the request's data
- def update(self, instance, validated_data): Updates a certain user... | 7c361a31c5225c6ad649fcf92e323bdb10cc4c16 | <|skeleton|>
class UserProfileSerializer:
"""The serializer for the user profile model"""
def create(self, validated_data):
"""Creates a new user profile from the request's data"""
<|body_0|>
def update(self, instance, validated_data):
"""Updates a certain user profile from the req... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserProfileSerializer:
"""The serializer for the user profile model"""
def create(self, validated_data):
"""Creates a new user profile from the request's data"""
account_data = validated_data.pop('account')
account = User(**account_data)
account.set_password(account.passwo... | the_stack_v2_python_sparse | users/serializers.py | ahmed-alllam/Koshkie-Server | train | 0 |
e7b0ac669d8868f13a4af5696315ba0bee32b59a | [
"date = data.strftime('%A')\nservice_start = self.context['service'].service_start\nif service_start:\n if service_start < data:\n return data\n else:\n raise serializers.ValidationError('The time of service end must be great than service start')\nelse:\n raise serializers.ValidationError('Th... | <|body_start_0|>
date = data.strftime('%A')
service_start = self.context['service'].service_start
if service_start:
if service_start < data:
return data
else:
raise serializers.ValidationError('The time of service end must be great than ser... | Start the service with the time of server. | EndServiceSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EndServiceSerializer:
"""Start the service with the time of server."""
def validate_service_end(self, data):
"""Validate if the service start in the date."""
<|body_0|>
def validate_is_active(self, data):
"""Validate if the service is in this moment active."""
... | stack_v2_sparse_classes_36k_train_018582 | 6,205 | permissive | [
{
"docstring": "Validate if the service start in the date.",
"name": "validate_service_end",
"signature": "def validate_service_end(self, data)"
},
{
"docstring": "Validate if the service is in this moment active.",
"name": "validate_is_active",
"signature": "def validate_is_active(self,... | 2 | stack_v2_sparse_classes_30k_val_000983 | Implement the Python class `EndServiceSerializer` described below.
Class description:
Start the service with the time of server.
Method signatures and docstrings:
- def validate_service_end(self, data): Validate if the service start in the date.
- def validate_is_active(self, data): Validate if the service is in this... | Implement the Python class `EndServiceSerializer` described below.
Class description:
Start the service with the time of server.
Method signatures and docstrings:
- def validate_service_end(self, data): Validate if the service start in the date.
- def validate_is_active(self, data): Validate if the service is in this... | 5c37c6876ca13b5794ac44e0342b810426acbc76 | <|skeleton|>
class EndServiceSerializer:
"""Start the service with the time of server."""
def validate_service_end(self, data):
"""Validate if the service start in the date."""
<|body_0|>
def validate_is_active(self, data):
"""Validate if the service is in this moment active."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EndServiceSerializer:
"""Start the service with the time of server."""
def validate_service_end(self, data):
"""Validate if the service start in the date."""
date = data.strftime('%A')
service_start = self.context['service'].service_start
if service_start:
if s... | the_stack_v2_python_sparse | hisitter/services/serializers/services.py | babysitter-finder/backend | train | 1 |
126841737e9e2420e363ae8fa32669bbe08c6de6 | [
"pg.sprite.Sprite.__init__(self)\nself.filename = filename\nself.hp = 100\nself.image = pg.image.load(os.path.join('Images', self.filename))\nself.coords = [int(self.image.get_rect()[0] + scr_size[0] / 2), int(self.image.get_rect()[1] + 4 * scr_size[1] / 7)]\nself.rect = self.coords\nself.mask = pg.mask.from_surfac... | <|body_start_0|>
pg.sprite.Sprite.__init__(self)
self.filename = filename
self.hp = 100
self.image = pg.image.load(os.path.join('Images', self.filename))
self.coords = [int(self.image.get_rect()[0] + scr_size[0] / 2), int(self.image.get_rect()[1] + 4 * scr_size[1] / 7)]
s... | Dantes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dantes:
def __init__(self, scr, scr_size, filename):
"""Dantes object class Parametrs: **scr** - game screen. **scr_size** - game screen size. **filename** - Dantes image file name."""
<|body_0|>
def check_dantes_hp(self, scr, screensize):
"""Function that checks Dan... | stack_v2_sparse_classes_36k_train_018583 | 2,771 | no_license | [
{
"docstring": "Dantes object class Parametrs: **scr** - game screen. **scr_size** - game screen size. **filename** - Dantes image file name.",
"name": "__init__",
"signature": "def __init__(self, scr, scr_size, filename)"
},
{
"docstring": "Function that checks Dantes health points and redraw h... | 3 | stack_v2_sparse_classes_30k_train_000795 | Implement the Python class `Dantes` described below.
Class description:
Implement the Dantes class.
Method signatures and docstrings:
- def __init__(self, scr, scr_size, filename): Dantes object class Parametrs: **scr** - game screen. **scr_size** - game screen size. **filename** - Dantes image file name.
- def check... | Implement the Python class `Dantes` described below.
Class description:
Implement the Dantes class.
Method signatures and docstrings:
- def __init__(self, scr, scr_size, filename): Dantes object class Parametrs: **scr** - game screen. **scr_size** - game screen size. **filename** - Dantes image file name.
- def check... | 9d813cfb7995f47953d653f9c450f7921dc26fe5 | <|skeleton|>
class Dantes:
def __init__(self, scr, scr_size, filename):
"""Dantes object class Parametrs: **scr** - game screen. **scr_size** - game screen size. **filename** - Dantes image file name."""
<|body_0|>
def check_dantes_hp(self, scr, screensize):
"""Function that checks Dan... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dantes:
def __init__(self, scr, scr_size, filename):
"""Dantes object class Parametrs: **scr** - game screen. **scr_size** - game screen size. **filename** - Dantes image file name."""
pg.sprite.Sprite.__init__(self)
self.filename = filename
self.hp = 100
self.image = p... | the_stack_v2_python_sparse | duel_ily_zassal/modules/fighters.py | python-practice-b02-006/Power.Rangers | train | 0 | |
b82bdafd7a5ad6ee1cf69b3eb8d2c08d04369e79 | [
"self.in_column = in_column\nself.strategy = ImputerMode(strategy)\nself.window = window\nself.fill_value: Optional[int] = None\nself.nan_timestamps = None",
"self.nan_timestamps = df[df[self.in_column].isna()].index\nif self.strategy == ImputerMode.zero:\n self.fill_value = 0\nelif self.strategy == ImputerMod... | <|body_start_0|>
self.in_column = in_column
self.strategy = ImputerMode(strategy)
self.window = window
self.fill_value: Optional[int] = None
self.nan_timestamps = None
<|end_body_0|>
<|body_start_1|>
self.nan_timestamps = df[df[self.in_column].isna()].index
if se... | Fills Nans in series of DataFrame with zeros, previous value, average or moving average. | _OneSegmentTimeSeriesImputerTransform | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _OneSegmentTimeSeriesImputerTransform:
"""Fills Nans in series of DataFrame with zeros, previous value, average or moving average."""
def __init__(self, in_column: str='target', strategy: str=ImputerMode.zero, window: int=-1):
"""Create instance of _OneSegmentTimeSeriesImputerTransfo... | stack_v2_sparse_classes_36k_train_018584 | 5,793 | permissive | [
{
"docstring": "Create instance of _OneSegmentTimeSeriesImputerTransform. Parameters ---------- in_column: name of processed column strategy: filling value in missed dates: - If \"zero\", then replace missing dates with zeros - If \"mean\", then replace missing dates using the mean in fit stage. - If \"running_... | 5 | null | Implement the Python class `_OneSegmentTimeSeriesImputerTransform` described below.
Class description:
Fills Nans in series of DataFrame with zeros, previous value, average or moving average.
Method signatures and docstrings:
- def __init__(self, in_column: str='target', strategy: str=ImputerMode.zero, window: int=-1... | Implement the Python class `_OneSegmentTimeSeriesImputerTransform` described below.
Class description:
Fills Nans in series of DataFrame with zeros, previous value, average or moving average.
Method signatures and docstrings:
- def __init__(self, in_column: str='target', strategy: str=ImputerMode.zero, window: int=-1... | b2453671b00affe2af23c4b10f556f6fb5d7d602 | <|skeleton|>
class _OneSegmentTimeSeriesImputerTransform:
"""Fills Nans in series of DataFrame with zeros, previous value, average or moving average."""
def __init__(self, in_column: str='target', strategy: str=ImputerMode.zero, window: int=-1):
"""Create instance of _OneSegmentTimeSeriesImputerTransfo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _OneSegmentTimeSeriesImputerTransform:
"""Fills Nans in series of DataFrame with zeros, previous value, average or moving average."""
def __init__(self, in_column: str='target', strategy: str=ImputerMode.zero, window: int=-1):
"""Create instance of _OneSegmentTimeSeriesImputerTransform. Parameter... | the_stack_v2_python_sparse | etna/transforms/imputation.py | jingmouren/etna-ts | train | 0 |
a754919e854bb13f1e283e8e8fada59e9c1298c1 | [
"self.r = 0\nself.c = 0\nself.l = vec2d",
"re = self.l[self.r][self.c]\nself.c += 1\nreturn re",
"while self.r < len(self.l):\n if self.c < len(self.l[self.r]):\n return True\n self.r += 1\n self.c = 0\nreturn False"
] | <|body_start_0|>
self.r = 0
self.c = 0
self.l = vec2d
<|end_body_0|>
<|body_start_1|>
re = self.l[self.r][self.c]
self.c += 1
return re
<|end_body_1|>
<|body_start_2|>
while self.r < len(self.l):
if self.c < len(self.l[self.r]):
retur... | Vector2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_018585 | 1,584 | no_license | [
{
"docstring": "Initialize your data structure here. :type vec2d: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, vec2d)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",... | 3 | stack_v2_sparse_classes_30k_train_012433 | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class V... | fe79161211cc08c269cde9e1fdcfed27de11f2cb | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
self.r = 0
self.c = 0
self.l = vec2d
def next(self):
""":rtype: int"""
re = self.l[self.r][self.c]
self.c += 1
return re
def ha... | the_stack_v2_python_sparse | MyLeetCode/python/Flatten 2D Vector.py | ihuei801/leetcode | train | 0 | |
4bd2466bd0b7dd2a9cda0f53e216372bf9503a0a | [
"try:\n team = TeamService.get_team_by_id(team_id)\n team_dto = UpdateTeamDTO(request.get_json())\n team_dto.team_id = team_id\n team_dto.validate()\n authenticated_user_id = token_auth.current_user()\n if not TeamService.is_user_team_manager(team_id, authenticated_user_id) and (not OrganisationSe... | <|body_start_0|>
try:
team = TeamService.get_team_by_id(team_id)
team_dto = UpdateTeamDTO(request.get_json())
team_dto.team_id = team_id
team_dto.validate()
authenticated_user_id = token_auth.current_user()
if not TeamService.is_user_team_m... | TeamsRestAPI | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeamsRestAPI:
def patch(self, team_id):
"""Updates a team --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - name: team_id in: path descripti... | stack_v2_sparse_classes_36k_train_018586 | 12,780 | permissive | [
{
"docstring": "Updates a team --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - name: team_id in: path description: The unique team ID required: true type: integer... | 3 | stack_v2_sparse_classes_30k_val_001081 | Implement the Python class `TeamsRestAPI` described below.
Class description:
Implement the TeamsRestAPI class.
Method signatures and docstrings:
- def patch(self, team_id): Updates a team --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session t... | Implement the Python class `TeamsRestAPI` described below.
Class description:
Implement the TeamsRestAPI class.
Method signatures and docstrings:
- def patch(self, team_id): Updates a team --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session t... | 45bf3937c74902226096aee5b49e7abea62df524 | <|skeleton|>
class TeamsRestAPI:
def patch(self, team_id):
"""Updates a team --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - name: team_id in: path descripti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TeamsRestAPI:
def patch(self, team_id):
"""Updates a team --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - name: team_id in: path description: The unique... | the_stack_v2_python_sparse | backend/api/teams/resources.py | hotosm/tasking-manager | train | 526 | |
e79cdc1c4c07313e38b00117ed064a043b55c73b | [
"self._algorithm = algorithm\nif algorithm == 'kd_tree':\n self.tree = cKDTree(data, leafsize=leafsize)\nelse:\n raise ValueError('invalid algorithm')",
"if self._algorithm == 'kd_tree':\n ind = self.tree.query_ball_point(q, r)\n if len(ind) == 0:\n return (ind, 0)\n dist = scipy.spatial.min... | <|body_start_0|>
self._algorithm = algorithm
if algorithm == 'kd_tree':
self.tree = cKDTree(data, leafsize=leafsize)
else:
raise ValueError('invalid algorithm')
<|end_body_0|>
<|body_start_1|>
if self._algorithm == 'kd_tree':
ind = self.tree.query_bal... | Nearest neighbor locator. Class for finding the neighbors of a points within a given distance. Parameters ---------- data : array_like, (n_sample, n_dimensions) Locations of points to be indexed. Note that if data is a C-contiguous array of dtype float64 the data will not be copied. Othersize and internal copy will be ... | NNLocator | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NNLocator:
"""Nearest neighbor locator. Class for finding the neighbors of a points within a given distance. Parameters ---------- data : array_like, (n_sample, n_dimensions) Locations of points to be indexed. Note that if data is a C-contiguous array of dtype float64 the data will not be copied.... | stack_v2_sparse_classes_36k_train_018587 | 31,793 | permissive | [
{
"docstring": "initalize.",
"name": "__init__",
"signature": "def __init__(self, data, leafsize=10, algorithm='kd_tree')"
},
{
"docstring": "Find all neighbors and distances within a given distance. Parameters ---------- q : n_dimensional tuple Point to query r : float Distance within which nei... | 2 | null | Implement the Python class `NNLocator` described below.
Class description:
Nearest neighbor locator. Class for finding the neighbors of a points within a given distance. Parameters ---------- data : array_like, (n_sample, n_dimensions) Locations of points to be indexed. Note that if data is a C-contiguous array of dty... | Implement the Python class `NNLocator` described below.
Class description:
Nearest neighbor locator. Class for finding the neighbors of a points within a given distance. Parameters ---------- data : array_like, (n_sample, n_dimensions) Locations of points to be indexed. Note that if data is a C-contiguous array of dty... | 172bbcf1cf3bcdb953c76ebae72c27c95dc2e606 | <|skeleton|>
class NNLocator:
"""Nearest neighbor locator. Class for finding the neighbors of a points within a given distance. Parameters ---------- data : array_like, (n_sample, n_dimensions) Locations of points to be indexed. Note that if data is a C-contiguous array of dtype float64 the data will not be copied.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NNLocator:
"""Nearest neighbor locator. Class for finding the neighbors of a points within a given distance. Parameters ---------- data : array_like, (n_sample, n_dimensions) Locations of points to be indexed. Note that if data is a C-contiguous array of dtype float64 the data will not be copied. Othersize an... | the_stack_v2_python_sparse | pyart/map/grid_mapper.py | ARM-DOE/pyart | train | 455 |
1b7f7a781a846c0a13ccfe7431fbc1f0d264326f | [
"self._init_fn = jax.jit(init_fn, device=self._device)\nself._apply_fn = apply_fn\nself._sample_fn = jax.jit(self._sample, device=self._device)",
"batch_size, sample_len = x.shape\n\ndef one_step(params, state, rng, i, x):\n step_sample = jax.lax.dynamic_slice(x, [0, i], [batch_size, 1])\n rng, rng_ = jax.r... | <|body_start_0|>
self._init_fn = jax.jit(init_fn, device=self._device)
self._apply_fn = apply_fn
self._sample_fn = jax.jit(self._sample, device=self._device)
<|end_body_0|>
<|body_start_1|>
batch_size, sample_len = x.shape
def one_step(params, state, rng, i, x):
ste... | Sampling from the TransformerXL model. | Bow2TextTransformerSampler | [
"CC-BY-SA-4.0",
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bow2TextTransformerSampler:
"""Sampling from the TransformerXL model."""
def _jit_model(self, init_fn, apply_fn):
"""Jit `init_fn` and `apply_fn`, the latter is used in `self._sample`."""
<|body_0|>
def _sample(self, params: Mapping[str, Any], state: Mapping[str, Any], r... | stack_v2_sparse_classes_36k_train_018588 | 12,853 | permissive | [
{
"docstring": "Jit `init_fn` and `apply_fn`, the latter is used in `self._sample`.",
"name": "_jit_model",
"signature": "def _jit_model(self, init_fn, apply_fn)"
},
{
"docstring": "Generate samples conditioned on the bag-of-words of the graph. Args: params: parameters of the transformer. state:... | 3 | null | Implement the Python class `Bow2TextTransformerSampler` described below.
Class description:
Sampling from the TransformerXL model.
Method signatures and docstrings:
- def _jit_model(self, init_fn, apply_fn): Jit `init_fn` and `apply_fn`, the latter is used in `self._sample`.
- def _sample(self, params: Mapping[str, A... | Implement the Python class `Bow2TextTransformerSampler` described below.
Class description:
Sampling from the TransformerXL model.
Method signatures and docstrings:
- def _jit_model(self, init_fn, apply_fn): Jit `init_fn` and `apply_fn`, the latter is used in `self._sample`.
- def _sample(self, params: Mapping[str, A... | a6ef8053380d6aa19aaae14b93f013ae9762d057 | <|skeleton|>
class Bow2TextTransformerSampler:
"""Sampling from the TransformerXL model."""
def _jit_model(self, init_fn, apply_fn):
"""Jit `init_fn` and `apply_fn`, the latter is used in `self._sample`."""
<|body_0|>
def _sample(self, params: Mapping[str, Any], state: Mapping[str, Any], r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bow2TextTransformerSampler:
"""Sampling from the TransformerXL model."""
def _jit_model(self, init_fn, apply_fn):
"""Jit `init_fn` and `apply_fn`, the latter is used in `self._sample`."""
self._init_fn = jax.jit(init_fn, device=self._device)
self._apply_fn = apply_fn
self.... | the_stack_v2_python_sparse | wikigraphs/wikigraphs/model/sampler.py | sethuramanio/deepmind-research | train | 1 |
a7a99f8b33a8c8b8e47e6bd2b48e38a94b444e18 | [
"super(Location_Box_Loss, self).__init__()\nself.prior_w = prior_w\nself.prior_cx = prior_cx\nself.prior_cy = prior_cy\nself.size_variance = size_variance\nself.center_variance = center_variance",
"ww_gt = gt_box[:, 2] - gt_box[:, 0]\nhh_gt = gt_box[:, 3] - gt_box[:, 1]\nxx_gt_tr = (gt_box[:, 2] + gt_box[:, 0]) /... | <|body_start_0|>
super(Location_Box_Loss, self).__init__()
self.prior_w = prior_w
self.prior_cx = prior_cx
self.prior_cy = prior_cy
self.size_variance = size_variance
self.center_variance = center_variance
<|end_body_0|>
<|body_start_1|>
ww_gt = gt_box[:, 2] - gt... | Location_Box_Loss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Location_Box_Loss:
def __init__(self, prior_w=0.5, prior_cx=0.5, prior_cy=0.5, size_variance=0.1, center_variance=0.1):
"""Implement Loss of box locolization smooth L1 regression loss."""
<|body_0|>
def forward(self, gt_box, predicted_vec):
"""# predicted_vec x_cente... | stack_v2_sparse_classes_36k_train_018589 | 7,988 | permissive | [
{
"docstring": "Implement Loss of box locolization smooth L1 regression loss.",
"name": "__init__",
"signature": "def __init__(self, prior_w=0.5, prior_cx=0.5, prior_cy=0.5, size_variance=0.1, center_variance=0.1)"
},
{
"docstring": "# predicted_vec x_center(-1,1) /center_variance y_center(-1,1)... | 2 | null | Implement the Python class `Location_Box_Loss` described below.
Class description:
Implement the Location_Box_Loss class.
Method signatures and docstrings:
- def __init__(self, prior_w=0.5, prior_cx=0.5, prior_cy=0.5, size_variance=0.1, center_variance=0.1): Implement Loss of box locolization smooth L1 regression los... | Implement the Python class `Location_Box_Loss` described below.
Class description:
Implement the Location_Box_Loss class.
Method signatures and docstrings:
- def __init__(self, prior_w=0.5, prior_cx=0.5, prior_cy=0.5, size_variance=0.1, center_variance=0.1): Implement Loss of box locolization smooth L1 regression los... | e6c09414c49e695b0f4221a3c6245ae3929a1788 | <|skeleton|>
class Location_Box_Loss:
def __init__(self, prior_w=0.5, prior_cx=0.5, prior_cy=0.5, size_variance=0.1, center_variance=0.1):
"""Implement Loss of box locolization smooth L1 regression loss."""
<|body_0|>
def forward(self, gt_box, predicted_vec):
"""# predicted_vec x_cente... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Location_Box_Loss:
def __init__(self, prior_w=0.5, prior_cx=0.5, prior_cy=0.5, size_variance=0.1, center_variance=0.1):
"""Implement Loss of box locolization smooth L1 regression loss."""
super(Location_Box_Loss, self).__init__()
self.prior_w = prior_w
self.prior_cx = prior_cx
... | the_stack_v2_python_sparse | modeling/location_box_loss.py | zyxwvu321/Classifer_SSL_Longtail | train | 0 | |
76f4445f69177a8bcd6e24c64d6af791aa61a891 | [
"device_id = None\nif self.device():\n device_id = self.device().idx_uid()\nreturn device_id",
"description = None\nif self.description:\n description = self.description\nreturn description"
] | <|body_start_0|>
device_id = None
if self.device():
device_id = self.device().idx_uid()
return device_id
<|end_body_0|>
<|body_start_1|>
description = None
if self.description:
description = self.description
return description
<|end_body_1|>
| ComponentIndexable | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComponentIndexable:
def idx_deviceId(self):
"""device the component belongs to"""
<|body_0|>
def idx_description(self):
"""description of the component"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
device_id = None
if self.device():
... | stack_v2_sparse_classes_36k_train_018590 | 26,766 | no_license | [
{
"docstring": "device the component belongs to",
"name": "idx_deviceId",
"signature": "def idx_deviceId(self)"
},
{
"docstring": "description of the component",
"name": "idx_description",
"signature": "def idx_description(self)"
}
] | 2 | null | Implement the Python class `ComponentIndexable` described below.
Class description:
Implement the ComponentIndexable class.
Method signatures and docstrings:
- def idx_deviceId(self): device the component belongs to
- def idx_description(self): description of the component | Implement the Python class `ComponentIndexable` described below.
Class description:
Implement the ComponentIndexable class.
Method signatures and docstrings:
- def idx_deviceId(self): device the component belongs to
- def idx_description(self): description of the component
<|skeleton|>
class ComponentIndexable:
... | 1ea508c3d2b51742bc3b448c445cd0a3dba9e798 | <|skeleton|>
class ComponentIndexable:
def idx_deviceId(self):
"""device the component belongs to"""
<|body_0|>
def idx_description(self):
"""description of the component"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComponentIndexable:
def idx_deviceId(self):
"""device the component belongs to"""
device_id = None
if self.device():
device_id = self.device().idx_uid()
return device_id
def idx_description(self):
"""description of the component"""
description =... | the_stack_v2_python_sparse | Products/Zuul/catalog/indexable.py | zenoss/zenoss-prodbin | train | 27 | |
1cc5847563b3606fc337946683b75fb15e332235 | [
"self.id = id\nself.created_date = created_date\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nid = dictionary.get('id')\ncreated_date = dictionary.get('createdDate')\nfor key in cls._names.values():\n if key in dictionary:\n del dictionary[key]\nreturn c... | <|body_start_0|>
self.id = id
self.created_date = created_date
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
id = dictionary.get('id')
created_date = dictionary.get('createdDate')
... | Implementation of the 'Create TxPush Test Transaction Response' model. Response for TxPush test transaction Attributes: id (long|int): The ID of the new transaction record created_date (long|int): A timestamp of when the transaction was added (see Handling Dates and Times) | CreateTxpushTestTransactionResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateTxpushTestTransactionResponse:
"""Implementation of the 'Create TxPush Test Transaction Response' model. Response for TxPush test transaction Attributes: id (long|int): The ID of the new transaction record created_date (long|int): A timestamp of when the transaction was added (see Handling ... | stack_v2_sparse_classes_36k_train_018591 | 2,019 | permissive | [
{
"docstring": "Constructor for the CreateTxpushTestTransactionResponse class",
"name": "__init__",
"signature": "def __init__(self, id=None, created_date=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dict... | 2 | stack_v2_sparse_classes_30k_train_011575 | Implement the Python class `CreateTxpushTestTransactionResponse` described below.
Class description:
Implementation of the 'Create TxPush Test Transaction Response' model. Response for TxPush test transaction Attributes: id (long|int): The ID of the new transaction record created_date (long|int): A timestamp of when t... | Implement the Python class `CreateTxpushTestTransactionResponse` described below.
Class description:
Implementation of the 'Create TxPush Test Transaction Response' model. Response for TxPush test transaction Attributes: id (long|int): The ID of the new transaction record created_date (long|int): A timestamp of when t... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class CreateTxpushTestTransactionResponse:
"""Implementation of the 'Create TxPush Test Transaction Response' model. Response for TxPush test transaction Attributes: id (long|int): The ID of the new transaction record created_date (long|int): A timestamp of when the transaction was added (see Handling ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateTxpushTestTransactionResponse:
"""Implementation of the 'Create TxPush Test Transaction Response' model. Response for TxPush test transaction Attributes: id (long|int): The ID of the new transaction record created_date (long|int): A timestamp of when the transaction was added (see Handling Dates and Tim... | the_stack_v2_python_sparse | finicityapi/models/create_txpush_test_transaction_response.py | monarchmoney/finicity-python | train | 0 |
9e7a32ae9f6da41d06b0a066bc8fd2ff2d931ced | [
"for testvalue, expected in self.knownvalues:\n p = project.Project()\n for d in self.directions:\n for s in self.seasons:\n for f in self.frames:\n for l in self.layers:\n result = p.image_path(d, s, f, l, testvalue, validate=True)\n self... | <|body_start_0|>
for testvalue, expected in self.knownvalues:
p = project.Project()
for d in self.directions:
for s in self.seasons:
for f in self.frames:
for l in self.layers:
result = p.image_path(d... | Test image path validator and image path settings | image_path | [
"BSD-2-Clause",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class image_path:
"""Test image path validator and image path settings"""
def test_knownvalues_validate(self):
"""Test that known values are validated correctly"""
<|body_0|>
def test_knownvalues_set(self):
"""Test that known values are set correctly"""
<|body_... | stack_v2_sparse_classes_36k_train_018592 | 3,994 | permissive | [
{
"docstring": "Test that known values are validated correctly",
"name": "test_knownvalues_validate",
"signature": "def test_knownvalues_validate(self)"
},
{
"docstring": "Test that known values are set correctly",
"name": "test_knownvalues_set",
"signature": "def test_knownvalues_set(se... | 3 | stack_v2_sparse_classes_30k_val_000338 | Implement the Python class `image_path` described below.
Class description:
Test image path validator and image path settings
Method signatures and docstrings:
- def test_knownvalues_validate(self): Test that known values are validated correctly
- def test_knownvalues_set(self): Test that known values are set correct... | Implement the Python class `image_path` described below.
Class description:
Test image path validator and image path settings
Method signatures and docstrings:
- def test_knownvalues_validate(self): Test that known values are validated correctly
- def test_knownvalues_set(self): Test that known values are set correct... | 307a9de864566fece1a999888e19048aeef9734c | <|skeleton|>
class image_path:
"""Test image path validator and image path settings"""
def test_knownvalues_validate(self):
"""Test that known values are validated correctly"""
<|body_0|>
def test_knownvalues_set(self):
"""Test that known values are set correctly"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class image_path:
"""Test image path validator and image path settings"""
def test_knownvalues_validate(self):
"""Test that known values are validated correctly"""
for testvalue, expected in self.knownvalues:
p = project.Project()
for d in self.directions:
... | the_stack_v2_python_sparse | project_test.py | An-dz/tilecutter | train | 4 |
a323697bcb1dd0fc10d482b2558083b79d61be76 | [
"self.Ch2P2_19a = '010'\nself.Ch2P2_19b = '017'\nself.Ch2P2_19c = '006'\nself.Ch2P_20a = '014'\nself.Ch2P_20b = '008'\nself.Ch2P_20c = '013'\nself.Ch2P_20d = '004'\nself.Ch2P_22a = '00010001 11101010 00100010 00001110'\nself.Ch2P_22b = '00001110 00111000 11101010 00111000'\nself.Ch2P_22c = '01101110 00001110 001110... | <|body_start_0|>
self.Ch2P2_19a = '010'
self.Ch2P2_19b = '017'
self.Ch2P2_19c = '006'
self.Ch2P_20a = '014'
self.Ch2P_20b = '008'
self.Ch2P_20c = '013'
self.Ch2P_20d = '004'
self.Ch2P_22a = '00010001 11101010 00100010 00001110'
self.Ch2P_22b = '000... | HW02 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HW02:
def ch2(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。 #作業 2. 課本 Ch2. P2.19"""
<|body_0|>
def ch3(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch3P3_28a = "xxx" 意思是 ... | stack_v2_sparse_classes_36k_train_018593 | 2,288 | no_license | [
{
"docstring": "請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = \"xxx\" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 \"xxx\" ： 你要填入你的答地方。 #作業 2. 課本 Ch2. P2.19",
"name": "ch2",
"signature": "def ch2(self)"
},
{
"docstring": "請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch3P3_28a = \"xxx\" 意思... | 2 | null | Implement the Python class `HW02` described below.
Class description:
Implement the HW02 class.
Method signatures and docstrings:
- def ch2(self): 請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。 #作業 2. 課本 Ch2. P2.19
- def ch3(s... | Implement the Python class `HW02` described below.
Class description:
Implement the HW02 class.
Method signatures and docstrings:
- def ch2(self): 請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。 #作業 2. 課本 Ch2. P2.19
- def ch3(s... | 008575d161d48672f906bdaec130f0c5060cd36d | <|skeleton|>
class HW02:
def ch2(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。 #作業 2. 課本 Ch2. P2.19"""
<|body_0|>
def ch3(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch3P3_28a = "xxx" 意思是 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HW02:
def ch2(self):
"""請將你計算出來的答案填入以下變數，助教會寫程式自動批改。 Ch2P2_19a = "xxx" 意思是 Ch2 : 第二章 P2_19a: 第二章結尾處的 PRACTICE SET 段落處的 Problems 第 P2-19 題的 a 小題 "xxx" ： 你要填入你的答地方。 #作業 2. 課本 Ch2. P2.19"""
self.Ch2P2_19a = '010'
self.Ch2P2_19b = '017'
self.Ch2P2_19c = '006'
self.Ch2P_20a ... | the_stack_v2_python_sparse | homework02_B05505045.py | PeterWolf-tw/ESOE-CS101-2016 | train | 21 | |
1e7618ebe6ba93d2b846688dd14547a1244c3281 | [
"INT_MAX = 3001\n\ndef helper(arr, cur):\n if len(arr) == 1:\n return cur\n elif len(arr) < k:\n return -1\n n = len(arr)\n moves = INT_MAX\n cnt = 0\n for j in range(k - 1):\n cnt += arr[j]\n for i in range(n - k + 1):\n cnt += arr[i + k - 1]\n moves = min(mo... | <|body_start_0|>
INT_MAX = 3001
def helper(arr, cur):
if len(arr) == 1:
return cur
elif len(arr) < k:
return -1
n = len(arr)
moves = INT_MAX
cnt = 0
for j in range(k - 1):
cnt += arr[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeStones(self, stones, k):
""":type stones: List[int] :type k: int :rtype: int"""
<|body_0|>
def mergeStones2(self, stones, k):
""":type stones: List[int] :type k: int :rtype: int"""
<|body_1|>
def mergeStones3(self, stones, k):
... | stack_v2_sparse_classes_36k_train_018594 | 5,379 | no_license | [
{
"docstring": ":type stones: List[int] :type k: int :rtype: int",
"name": "mergeStones",
"signature": "def mergeStones(self, stones, k)"
},
{
"docstring": ":type stones: List[int] :type k: int :rtype: int",
"name": "mergeStones2",
"signature": "def mergeStones2(self, stones, k)"
},
... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeStones(self, stones, k): :type stones: List[int] :type k: int :rtype: int
- def mergeStones2(self, stones, k): :type stones: List[int] :type k: int :rtype: int
- def mer... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeStones(self, stones, k): :type stones: List[int] :type k: int :rtype: int
- def mergeStones2(self, stones, k): :type stones: List[int] :type k: int :rtype: int
- def mer... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def mergeStones(self, stones, k):
""":type stones: List[int] :type k: int :rtype: int"""
<|body_0|>
def mergeStones2(self, stones, k):
""":type stones: List[int] :type k: int :rtype: int"""
<|body_1|>
def mergeStones3(self, stones, k):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeStones(self, stones, k):
""":type stones: List[int] :type k: int :rtype: int"""
INT_MAX = 3001
def helper(arr, cur):
if len(arr) == 1:
return cur
elif len(arr) < k:
return -1
n = len(arr)
... | the_stack_v2_python_sparse | M/MinimumCosttoMergeStones.py | bssrdf/pyleet | train | 2 | |
1e875bddc2fc85562802f313571262e3b969a862 | [
"if n == 0:\n return 1\ncount = 0\nfor i in xrange(10 ** n):\n if len(set(str(i))) == len(str(i)):\n count += 1\nreturn count",
"if n == 0:\n return 1\nnums = 1\ntotal = 1\ndp = [9, 9, 8, 7, 6, 5, 4, 3, 2, 1]\nfor i in dp[:n]:\n nums *= i\n total += nums\nreturn total",
"if n == 0:\n re... | <|body_start_0|>
if n == 0:
return 1
count = 0
for i in xrange(10 ** n):
if len(set(str(i))) == len(str(i)):
count += 1
return count
<|end_body_0|>
<|body_start_1|>
if n == 0:
return 1
nums = 1
total = 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countNumbersWithUniqueDigits_TLE(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def countNumbersWithUniqueDigits(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def countNumbersWithUniqueDigits2(self, n):
""":type n: int :r... | stack_v2_sparse_classes_36k_train_018595 | 2,619 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "countNumbersWithUniqueDigits_TLE",
"signature": "def countNumbersWithUniqueDigits_TLE(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "countNumbersWithUniqueDigits",
"signature": "def countNumbersWithUniqueDigits(self, n... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countNumbersWithUniqueDigits_TLE(self, n): :type n: int :rtype: int
- def countNumbersWithUniqueDigits(self, n): :type n: int :rtype: int
- def countNumbersWithUniqueDigits2(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countNumbersWithUniqueDigits_TLE(self, n): :type n: int :rtype: int
- def countNumbersWithUniqueDigits(self, n): :type n: int :rtype: int
- def countNumbersWithUniqueDigits2(... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def countNumbersWithUniqueDigits_TLE(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def countNumbersWithUniqueDigits(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def countNumbersWithUniqueDigits2(self, n):
""":type n: int :r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countNumbersWithUniqueDigits_TLE(self, n):
""":type n: int :rtype: int"""
if n == 0:
return 1
count = 0
for i in xrange(10 ** n):
if len(set(str(i))) == len(str(i)):
count += 1
return count
def countNumbersWithU... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00357.Count Numbers with Unique Digits.py | roger6blog/LeetCode | train | 0 | |
128ef5d80c9748b0e88f2b4bdd1bfcbfefcefd1f | [
"self.db = SqliteDB()\nself.code_list = []\nself.data = self.get_data()\nself.data_for_table = {}",
"with self.db as cur:\n cur.execute('SELECT * FROM salaries')\nreturn cur.fetchall()",
"for string in self.data:\n if string[1] not in self.code_list:\n self.code_list.append(string[1])\nfor i in sel... | <|body_start_0|>
self.db = SqliteDB()
self.code_list = []
self.data = self.get_data()
self.data_for_table = {}
<|end_body_0|>
<|body_start_1|>
with self.db as cur:
cur.execute('SELECT * FROM salaries')
return cur.fetchall()
<|end_body_1|>
<|body_start_2|>
... | Класс, рассчитывающий общую численность персонала по категориям | PersonelSummary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersonelSummary:
"""Класс, рассчитывающий общую численность персонала по категориям"""
def __init__(self) -> None:
"""Метод инициализации класса"""
<|body_0|>
def get_data(self) -> tuple:
"""Метод, получающий из БД данные о всех записях :return: self.cur.fetchall... | stack_v2_sparse_classes_36k_train_018596 | 3,002 | no_license | [
{
"docstring": "Метод инициализации класса",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Метод, получающий из БД данные о всех записях :return: self.cur.fetchall() - список с результами запроса",
"name": "get_data",
"signature": "def get_data(self) ->... | 4 | stack_v2_sparse_classes_30k_train_005517 | Implement the Python class `PersonelSummary` described below.
Class description:
Класс, рассчитывающий общую численность персонала по категориям
Method signatures and docstrings:
- def __init__(self) -> None: Метод инициализации класса
- def get_data(self) -> tuple: Метод, получающий из БД данные о всех записях :retu... | Implement the Python class `PersonelSummary` described below.
Class description:
Класс, рассчитывающий общую численность персонала по категориям
Method signatures and docstrings:
- def __init__(self) -> None: Метод инициализации класса
- def get_data(self) -> tuple: Метод, получающий из БД данные о всех записях :retu... | f63d5db6780cc02cb064e70d2076eba94cb45785 | <|skeleton|>
class PersonelSummary:
"""Класс, рассчитывающий общую численность персонала по категориям"""
def __init__(self) -> None:
"""Метод инициализации класса"""
<|body_0|>
def get_data(self) -> tuple:
"""Метод, получающий из БД данные о всех записях :return: self.cur.fetchall... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PersonelSummary:
"""Класс, рассчитывающий общую численность персонала по категориям"""
def __init__(self) -> None:
"""Метод инициализации класса"""
self.db = SqliteDB()
self.code_list = []
self.data = self.get_data()
self.data_for_table = {}
def get_data(self)... | the_stack_v2_python_sparse | counting/personel_summary.py | Pheeneek/Salary | train | 0 |
77838437d58b03a23534a0acff77a335ef016086 | [
"if sent_tokenizer:\n self.sent_tokenizer = sent_tokenizer()\nelse:\n punkt_param = PunktParameters()\n self.sent_tokenizer = PunktSentenceTokenizer(punkt_param)",
"sents = self.sent_tokenizer.tokenize(text)\ntokenizer = TreebankWordTokenizer()\nreturn [item for sublist in tokenizer.tokenize_sents(sents)... | <|body_start_0|>
if sent_tokenizer:
self.sent_tokenizer = sent_tokenizer()
else:
punkt_param = PunktParameters()
self.sent_tokenizer = PunktSentenceTokenizer(punkt_param)
<|end_body_0|>
<|body_start_1|>
sents = self.sent_tokenizer.tokenize(text)
token... | Class for punkt word tokenization | PunktWordTokenizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PunktWordTokenizer:
"""Class for punkt word tokenization"""
def __init__(self, sent_tokenizer: object=None):
""":param language : language for sentences tokenization :type language: str"""
<|body_0|>
def tokenize(self, text: str):
""":rtype: list :param text: tex... | stack_v2_sparse_classes_36k_train_018597 | 3,603 | permissive | [
{
"docstring": ":param language : language for sentences tokenization :type language: str",
"name": "__init__",
"signature": "def __init__(self, sent_tokenizer: object=None)"
},
{
"docstring": ":rtype: list :param text: text to be tokenized into sentences :type text: str",
"name": "tokenize"... | 2 | null | Implement the Python class `PunktWordTokenizer` described below.
Class description:
Class for punkt word tokenization
Method signatures and docstrings:
- def __init__(self, sent_tokenizer: object=None): :param language : language for sentences tokenization :type language: str
- def tokenize(self, text: str): :rtype: ... | Implement the Python class `PunktWordTokenizer` described below.
Class description:
Class for punkt word tokenization
Method signatures and docstrings:
- def __init__(self, sent_tokenizer: object=None): :param language : language for sentences tokenization :type language: str
- def tokenize(self, text: str): :rtype: ... | 8a122113d2509aef85bebba8e2c303471c107ff4 | <|skeleton|>
class PunktWordTokenizer:
"""Class for punkt word tokenization"""
def __init__(self, sent_tokenizer: object=None):
""":param language : language for sentences tokenization :type language: str"""
<|body_0|>
def tokenize(self, text: str):
""":rtype: list :param text: tex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PunktWordTokenizer:
"""Class for punkt word tokenization"""
def __init__(self, sent_tokenizer: object=None):
""":param language : language for sentences tokenization :type language: str"""
if sent_tokenizer:
self.sent_tokenizer = sent_tokenizer()
else:
punk... | the_stack_v2_python_sparse | src/cltk/tokenizers/word.py | cltk/cltk | train | 847 |
a6dfa7eef2478d97fb1b4afa371bc0faf333833d | [
"self.original_patch_size = patch_size * 2\nkwargs['transforms'] = _Transform(K.CenterCrop(patch_size))\nsuper().__init__(ChesapeakeCVPR, batch_size, patch_size, length, num_workers, **kwargs)\nassert class_set in [5, 7]\nif use_prior_labels and class_set == 7:\n raise ValueError('The pre-generated prior labels ... | <|body_start_0|>
self.original_patch_size = patch_size * 2
kwargs['transforms'] = _Transform(K.CenterCrop(patch_size))
super().__init__(ChesapeakeCVPR, batch_size, patch_size, length, num_workers, **kwargs)
assert class_set in [5, 7]
if use_prior_labels and class_set == 7:
... | LightningDataModule implementation for the Chesapeake CVPR Land Cover dataset. Uses the random splits defined per state to partition tiles into train, val, and test sets. | ChesapeakeCVPRDataModule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChesapeakeCVPRDataModule:
"""LightningDataModule implementation for the Chesapeake CVPR Land Cover dataset. Uses the random splits defined per state to partition tiles into train, val, and test sets."""
def __init__(self, train_splits: list[str], val_splits: list[str], test_splits: list[str]... | stack_v2_sparse_classes_36k_train_018598 | 6,692 | permissive | [
{
"docstring": "Initialize a new ChesapeakeCVPRDataModule instance. Args: train_splits: Splits used to train the model, e.g., [\"ny-train\"]. val_splits: Splits used to validate the model, e.g., [\"ny-val\"]. test_splits: Splits used to test the model, e.g., [\"ny-test\"]. batch_size: Size of each mini-batch. p... | 3 | stack_v2_sparse_classes_30k_train_002534 | Implement the Python class `ChesapeakeCVPRDataModule` described below.
Class description:
LightningDataModule implementation for the Chesapeake CVPR Land Cover dataset. Uses the random splits defined per state to partition tiles into train, val, and test sets.
Method signatures and docstrings:
- def __init__(self, tr... | Implement the Python class `ChesapeakeCVPRDataModule` described below.
Class description:
LightningDataModule implementation for the Chesapeake CVPR Land Cover dataset. Uses the random splits defined per state to partition tiles into train, val, and test sets.
Method signatures and docstrings:
- def __init__(self, tr... | 29985861614b3b93f9ef5389469ebb98570de7dd | <|skeleton|>
class ChesapeakeCVPRDataModule:
"""LightningDataModule implementation for the Chesapeake CVPR Land Cover dataset. Uses the random splits defined per state to partition tiles into train, val, and test sets."""
def __init__(self, train_splits: list[str], val_splits: list[str], test_splits: list[str]... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChesapeakeCVPRDataModule:
"""LightningDataModule implementation for the Chesapeake CVPR Land Cover dataset. Uses the random splits defined per state to partition tiles into train, val, and test sets."""
def __init__(self, train_splits: list[str], val_splits: list[str], test_splits: list[str], batch_size:... | the_stack_v2_python_sparse | torchgeo/datamodules/chesapeake.py | microsoft/torchgeo | train | 1,724 |
67191c9d2aa72935e6e6504f77821b3c72c70711 | [
"if not len(viewports) > 0:\n raise Exception('Must provide at least one viewport for MegaViewport!')\nself.viewports = viewports\nself.arc_width = arc_width\nx_min = 16384\ny_min = 16384\nx_max = 0\ny_max = 0\nfor viewport in viewports:\n geometry = ManagedWindow.lookup_viewport_geometry(viewport)\n x_min... | <|body_start_0|>
if not len(viewports) > 0:
raise Exception('Must provide at least one viewport for MegaViewport!')
self.viewports = viewports
self.arc_width = arc_width
x_min = 16384
y_min = 16384
x_max = 0
y_max = 0
for viewport in viewports:... | Helper for converting angular offsets to viewport coordinates across the span of all viewports. It is assumed that: * All given viewports have the same dimensions. * The pointing device is located roughly at the center of the cylinder. | MegaViewport | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MegaViewport:
"""Helper for converting angular offsets to viewport coordinates across the span of all viewports. It is assumed that: * All given viewports have the same dimensions. * The pointing device is located roughly at the center of the cylinder."""
def __init__(self, viewports, arc_wi... | stack_v2_sparse_classes_36k_train_018599 | 3,416 | permissive | [
{
"docstring": "Args: viewports (list[str]): List of viewports from left to right. arc_width (float): Physical arc width of all viewports in radians. Raises: Exception: No viewports provided.",
"name": "__init__",
"signature": "def __init__(self, viewports, arc_width)"
},
{
"docstring": "Convert... | 3 | stack_v2_sparse_classes_30k_train_004735 | Implement the Python class `MegaViewport` described below.
Class description:
Helper for converting angular offsets to viewport coordinates across the span of all viewports. It is assumed that: * All given viewports have the same dimensions. * The pointing device is located roughly at the center of the cylinder.
Meth... | Implement the Python class `MegaViewport` described below.
Class description:
Helper for converting angular offsets to viewport coordinates across the span of all viewports. It is assumed that: * All given viewports have the same dimensions. * The pointing device is located roughly at the center of the cylinder.
Meth... | 90233b939bb4873c00a72e84ab3f8d1a776edee8 | <|skeleton|>
class MegaViewport:
"""Helper for converting angular offsets to viewport coordinates across the span of all viewports. It is assumed that: * All given viewports have the same dimensions. * The pointing device is located roughly at the center of the cylinder."""
def __init__(self, viewports, arc_wi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MegaViewport:
"""Helper for converting angular offsets to viewport coordinates across the span of all viewports. It is assumed that: * All given viewports have the same dimensions. * The pointing device is located roughly at the center of the cylinder."""
def __init__(self, viewports, arc_width):
... | the_stack_v2_python_sparse | lg_pointer/src/lg_pointer/megaviewport.py | EndPointCorp/lg_ros_nodes | train | 18 |
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