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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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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
098ca878c22181e967649c49a8a71045cdf1a85b | [
"self._block_specs = block_specs\nself._batch_norm_activation = batch_norm_activation\nself._data_format = data_format",
"x = images\nwith tf.variable_scope('efficientnet'):\n x = nn_ops.conv2d_fixed_padding(inputs=x, filters=32, kernel_size=3, strides=2, data_format=self._data_format)\n x = tf.identity(x, ... | <|body_start_0|>
self._block_specs = block_specs
self._batch_norm_activation = batch_norm_activation
self._data_format = data_format
<|end_body_0|>
<|body_start_1|>
x = images
with tf.variable_scope('efficientnet'):
x = nn_ops.conv2d_fixed_padding(inputs=x, filters=3... | Class to build EfficientNet and X family models. | EfficientNetX | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EfficientNetX:
"""Class to build EfficientNet and X family models."""
def __init__(self, block_specs=build_block_specs(), batch_norm_activation=nn_ops.BatchNormActivation(), data_format='channels_last'):
"""EfficientNet initialization function. Args: block_specs: a list of BlockSpec ... | stack_v2_sparse_classes_36k_train_031000 | 7,394 | permissive | [
{
"docstring": "EfficientNet initialization function. Args: block_specs: a list of BlockSpec objects that specifies the EfficientNet network. By default, the previously discovered EfficientNet-A1 is used. batch_norm_activation: an operation that includes a batch normalization layer followed by an optional activ... | 2 | null | Implement the Python class `EfficientNetX` described below.
Class description:
Class to build EfficientNet and X family models.
Method signatures and docstrings:
- def __init__(self, block_specs=build_block_specs(), batch_norm_activation=nn_ops.BatchNormActivation(), data_format='channels_last'): EfficientNet initial... | Implement the Python class `EfficientNetX` described below.
Class description:
Class to build EfficientNet and X family models.
Method signatures and docstrings:
- def __init__(self, block_specs=build_block_specs(), batch_norm_activation=nn_ops.BatchNormActivation(), data_format='channels_last'): EfficientNet initial... | 0f7adb97a93ec3e3485c261d030c507eb16b33e4 | <|skeleton|>
class EfficientNetX:
"""Class to build EfficientNet and X family models."""
def __init__(self, block_specs=build_block_specs(), batch_norm_activation=nn_ops.BatchNormActivation(), data_format='channels_last'):
"""EfficientNet initialization function. Args: block_specs: a list of BlockSpec ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EfficientNetX:
"""Class to build EfficientNet and X family models."""
def __init__(self, block_specs=build_block_specs(), batch_norm_activation=nn_ops.BatchNormActivation(), data_format='channels_last'):
"""EfficientNet initialization function. Args: block_specs: a list of BlockSpec objects that ... | the_stack_v2_python_sparse | models/official/detection/modeling/architecture/efficientnet.py | tensorflow/tpu | train | 5,627 |
de5cc6767c3f9066a3bc76aa323be54addad780c | [
"try:\n firewallController = FirewallController()\n json_data = json.dumps(firewallController.get_interface_ipv4Configuration_netmask(id))\n resp = Response(json_data, status=200, mimetype='application/json')\n return resp\nexcept ValueError as ve:\n return Response(json.dumps(str(ve)), status=404, m... | <|body_start_0|>
try:
firewallController = FirewallController()
json_data = json.dumps(firewallController.get_interface_ipv4Configuration_netmask(id))
resp = Response(json_data, status=200, mimetype='application/json')
return resp
except ValueError as ve:
... | Interface_ifEntry_Ipv4Configuration_Netmask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Interface_ifEntry_Ipv4Configuration_Netmask:
def get(self, id):
"""Get the netmask of an interface"""
<|body_0|>
def put(self, id):
"""Update the netmask of an interface"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
firewallContro... | stack_v2_sparse_classes_36k_train_031001 | 12,460 | no_license | [
{
"docstring": "Get the netmask of an interface",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Update the netmask of an interface",
"name": "put",
"signature": "def put(self, id)"
}
] | 2 | null | Implement the Python class `Interface_ifEntry_Ipv4Configuration_Netmask` described below.
Class description:
Implement the Interface_ifEntry_Ipv4Configuration_Netmask class.
Method signatures and docstrings:
- def get(self, id): Get the netmask of an interface
- def put(self, id): Update the netmask of an interface | Implement the Python class `Interface_ifEntry_Ipv4Configuration_Netmask` described below.
Class description:
Implement the Interface_ifEntry_Ipv4Configuration_Netmask class.
Method signatures and docstrings:
- def get(self, id): Get the netmask of an interface
- def put(self, id): Update the netmask of an interface
... | 6070e3cb6bf957e04f5d8267db11f3296410e18e | <|skeleton|>
class Interface_ifEntry_Ipv4Configuration_Netmask:
def get(self, id):
"""Get the netmask of an interface"""
<|body_0|>
def put(self, id):
"""Update the netmask of an interface"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Interface_ifEntry_Ipv4Configuration_Netmask:
def get(self, id):
"""Get the netmask of an interface"""
try:
firewallController = FirewallController()
json_data = json.dumps(firewallController.get_interface_ipv4Configuration_netmask(id))
resp = Response(json_d... | the_stack_v2_python_sparse | configuration-agent/firewall/rest_api/resources/interface.py | ReliableLion/frog4-configurable-vnf | train | 0 | |
d31699dfa2483d5123ba0ee8986c3de272dc8e94 | [
"query = kwargs.get('query', '')\nsite_domains = cherrypy.engine.publish('registry:search:valuelist', 'logindex:site_domain').pop()\nsaved_queries = cherrypy.engine.publish('registry:search:dict', 'visitors*', key_slice=1).pop()\nregistry_url = cherrypy.engine.publish('app_url', '/registry').pop()\nif 'default' in ... | <|body_start_0|>
query = kwargs.get('query', '')
site_domains = cherrypy.engine.publish('registry:search:valuelist', 'logindex:site_domain').pop()
saved_queries = cherrypy.engine.publish('registry:search:dict', 'visitors*', key_slice=1).pop()
registry_url = cherrypy.engine.publish('app_u... | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
def GET(self, **kwargs: str) -> bytes:
"""Display a search interface, and the results of the default query"""
<|body_0|>
def get_active_date(log_records: List[sqlite3.Row], query: str) -> Union[date, datetime]:
"""Figure out which date the query pertains ... | stack_v2_sparse_classes_36k_train_031002 | 4,492 | no_license | [
{
"docstring": "Display a search interface, and the results of the default query",
"name": "GET",
"signature": "def GET(self, **kwargs: str) -> bytes"
},
{
"docstring": "Figure out which date the query pertains to.",
"name": "get_active_date",
"signature": "def get_active_date(log_record... | 3 | null | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def GET(self, **kwargs: str) -> bytes: Display a search interface, and the results of the default query
- def get_active_date(log_records: List[sqlite3.Row], query: str) -> U... | Implement the Python class `Controller` described below.
Class description:
Implement the Controller class.
Method signatures and docstrings:
- def GET(self, **kwargs: str) -> bytes: Display a search interface, and the results of the default query
- def get_active_date(log_records: List[sqlite3.Row], query: str) -> U... | 7129415303b94d5d10b2c29ec432f0c7d41cc651 | <|skeleton|>
class Controller:
def GET(self, **kwargs: str) -> bytes:
"""Display a search interface, and the results of the default query"""
<|body_0|>
def get_active_date(log_records: List[sqlite3.Row], query: str) -> Union[date, datetime]:
"""Figure out which date the query pertains ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
def GET(self, **kwargs: str) -> bytes:
"""Display a search interface, and the results of the default query"""
query = kwargs.get('query', '')
site_domains = cherrypy.engine.publish('registry:search:valuelist', 'logindex:site_domain').pop()
saved_queries = cherrypy.e... | the_stack_v2_python_sparse | apps/visitors/main.py | lovett/medley | train | 6 | |
be9b3144f5dce329f9ae784186b5c33bc8d408d7 | [
"sensor = Sensor('127.0.0.1', 8000)\npump = Pump('127.0.0.1', 8000)\ndecider = Decider(10, 0.1)\ncontroller = Controller(sensor, pump, decider)\nsensor.measure = MagicMock(return_value=10)\npump.get_state = MagicMock(return_value=pump.PUMP_OFF)\npump.set_state = MagicMock(return_value=True)\nself.assertTrue(control... | <|body_start_0|>
sensor = Sensor('127.0.0.1', 8000)
pump = Pump('127.0.0.1', 8000)
decider = Decider(10, 0.1)
controller = Controller(sensor, pump, decider)
sensor.measure = MagicMock(return_value=10)
pump.get_state = MagicMock(return_value=pump.PUMP_OFF)
pump.set... | Unit tests for the Controller class | ControllerTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ControllerTests:
"""Unit tests for the Controller class"""
def test_tick_true(self):
"""Test that tick return True if pump.set_state returns True"""
<|body_0|>
def test_tick_false(self):
"""Test that tick return False if pump.set_state returns False"""
<|... | stack_v2_sparse_classes_36k_train_031003 | 4,700 | no_license | [
{
"docstring": "Test that tick return True if pump.set_state returns True",
"name": "test_tick_true",
"signature": "def test_tick_true(self)"
},
{
"docstring": "Test that tick return False if pump.set_state returns False",
"name": "test_tick_false",
"signature": "def test_tick_false(self... | 2 | null | Implement the Python class `ControllerTests` described below.
Class description:
Unit tests for the Controller class
Method signatures and docstrings:
- def test_tick_true(self): Test that tick return True if pump.set_state returns True
- def test_tick_false(self): Test that tick return False if pump.set_state return... | Implement the Python class `ControllerTests` described below.
Class description:
Unit tests for the Controller class
Method signatures and docstrings:
- def test_tick_true(self): Test that tick return True if pump.set_state returns True
- def test_tick_false(self): Test that tick return False if pump.set_state return... | b1fea0309b3495b3e1dc167d7029bc9e4b6f00f1 | <|skeleton|>
class ControllerTests:
"""Unit tests for the Controller class"""
def test_tick_true(self):
"""Test that tick return True if pump.set_state returns True"""
<|body_0|>
def test_tick_false(self):
"""Test that tick return False if pump.set_state returns False"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ControllerTests:
"""Unit tests for the Controller class"""
def test_tick_true(self):
"""Test that tick return True if pump.set_state returns True"""
sensor = Sensor('127.0.0.1', 8000)
pump = Pump('127.0.0.1', 8000)
decider = Decider(10, 0.1)
controller = Controller... | the_stack_v2_python_sparse | students/CocoKaku/lesson6/water-regulation/waterregulation/test.py | UWPCE-PythonCert-ClassRepos/SP_Online_Course2_2018 | train | 4 |
c6c2d01db5c4093f6b325c8dd9fd8c5501ba34dc | [
"mock_client = Taxii2FeedClient(url='', collection_to_fetch='default', proxies=[], verify=False, objects_to_fetch='')\ndefault_id = 1\nnondefault_id = 2\nmock_client.collections = [MockCollection(default_id, 'default'), MockCollection(nondefault_id, 'not_default')]\nmock_client.collection_to_fetch = mock_client.col... | <|body_start_0|>
mock_client = Taxii2FeedClient(url='', collection_to_fetch='default', proxies=[], verify=False, objects_to_fetch='')
default_id = 1
nondefault_id = 2
mock_client.collections = [MockCollection(default_id, 'default'), MockCollection(nondefault_id, 'not_default')]
m... | Scenario: Test fetch_indicators_command | TestFetchIndicators | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestFetchIndicators:
"""Scenario: Test fetch_indicators_command"""
def test_single_no_context(self, mocker):
"""Scenario: Test single collection fetch with no last run Given: - collection to fetch is available and set to 'default' - there is no integration context - limit is -1 - ini... | stack_v2_sparse_classes_36k_train_031004 | 9,956 | permissive | [
{
"docstring": "Scenario: Test single collection fetch with no last run Given: - collection to fetch is available and set to 'default' - there is no integration context - limit is -1 - initial interval is `1 day` When: - fetch_indicators_command is called Then: - update last run with latest collection fetch tim... | 4 | stack_v2_sparse_classes_30k_train_019030 | Implement the Python class `TestFetchIndicators` described below.
Class description:
Scenario: Test fetch_indicators_command
Method signatures and docstrings:
- def test_single_no_context(self, mocker): Scenario: Test single collection fetch with no last run Given: - collection to fetch is available and set to 'defau... | Implement the Python class `TestFetchIndicators` described below.
Class description:
Scenario: Test fetch_indicators_command
Method signatures and docstrings:
- def test_single_no_context(self, mocker): Scenario: Test single collection fetch with no last run Given: - collection to fetch is available and set to 'defau... | 01b57f8c658c2faed047313d3034e8052ffa83ce | <|skeleton|>
class TestFetchIndicators:
"""Scenario: Test fetch_indicators_command"""
def test_single_no_context(self, mocker):
"""Scenario: Test single collection fetch with no last run Given: - collection to fetch is available and set to 'default' - there is no integration context - limit is -1 - ini... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestFetchIndicators:
"""Scenario: Test fetch_indicators_command"""
def test_single_no_context(self, mocker):
"""Scenario: Test single collection fetch with no last run Given: - collection to fetch is available and set to 'default' - there is no integration context - limit is -1 - initial interval... | the_stack_v2_python_sparse | Packs/FeedTAXII/Integrations/FeedTAXII2/FeedTAXII2_test.py | adambaumeister/content | train | 2 |
776fb4718fbe54b8cd0b5d71d83a3f59ffba5a18 | [
"self.entity_id = _slug(name)\nself._attr_name = name\nself._attr_unique_id = topic\nself._state_key = state_key\nself._attr_native_unit_of_measurement = units\nself._attr_icon = icon\nself._attr_device_class = device_class",
"ev = {}\nev.update(event)\nself._attr_extra_state_attributes = ev\nself._attr_native_va... | <|body_start_0|>
self.entity_id = _slug(name)
self._attr_name = name
self._attr_unique_id = topic
self._state_key = state_key
self._attr_native_unit_of_measurement = units
self._attr_icon = icon
self._attr_device_class = device_class
<|end_body_0|>
<|body_start_1... | Representation of an ARWN sensor. | ArwnSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArwnSensor:
"""Representation of an ARWN sensor."""
def __init__(self, topic, name, state_key, units, icon=None, device_class=None):
"""Initialize the sensor."""
<|body_0|>
def set_event(self, event):
"""Update the sensor with the most recent event."""
<|... | stack_v2_sparse_classes_36k_train_031005 | 5,948 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, topic, name, state_key, units, icon=None, device_class=None)"
},
{
"docstring": "Update the sensor with the most recent event.",
"name": "set_event",
"signature": "def set_event(self, event)"
... | 2 | null | Implement the Python class `ArwnSensor` described below.
Class description:
Representation of an ARWN sensor.
Method signatures and docstrings:
- def __init__(self, topic, name, state_key, units, icon=None, device_class=None): Initialize the sensor.
- def set_event(self, event): Update the sensor with the most recent... | Implement the Python class `ArwnSensor` described below.
Class description:
Representation of an ARWN sensor.
Method signatures and docstrings:
- def __init__(self, topic, name, state_key, units, icon=None, device_class=None): Initialize the sensor.
- def set_event(self, event): Update the sensor with the most recent... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ArwnSensor:
"""Representation of an ARWN sensor."""
def __init__(self, topic, name, state_key, units, icon=None, device_class=None):
"""Initialize the sensor."""
<|body_0|>
def set_event(self, event):
"""Update the sensor with the most recent event."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArwnSensor:
"""Representation of an ARWN sensor."""
def __init__(self, topic, name, state_key, units, icon=None, device_class=None):
"""Initialize the sensor."""
self.entity_id = _slug(name)
self._attr_name = name
self._attr_unique_id = topic
self._state_key = stat... | the_stack_v2_python_sparse | homeassistant/components/arwn/sensor.py | home-assistant/core | train | 35,501 |
f6797c753535093d995b1fea07443c77cb3058f7 | [
"if input_type == 'f':\n file = open(path, 'r')\nelif input_type == 's':\n file = path\nelse:\n raise exceptions.BadInputError(f'invalid input type {input_type}')\npdl = yaml.safe_load(file)\nself.type_checks = {'typedef': self.validate_typedef, 'component': self.validate_component, 'graph': self.validate_... | <|body_start_0|>
if input_type == 'f':
file = open(path, 'r')
elif input_type == 's':
file = path
else:
raise exceptions.BadInputError(f'invalid input type {input_type}')
pdl = yaml.safe_load(file)
self.type_checks = {'typedef': self.validate_t... | Represents a single PDL file. | File | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class File:
"""Represents a single PDL file."""
def __init__(self, path, input_type='f'):
"""Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's contents belong in, - imports: a list of imports that th... | stack_v2_sparse_classes_36k_train_031006 | 5,874 | permissive | [
{
"docstring": "Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's contents belong in, - imports: a list of imports that the file's contents use, - body: the body of PDL. Parameters ---------- path: string path should cont... | 6 | stack_v2_sparse_classes_30k_train_004552 | Implement the Python class `File` described below.
Class description:
Represents a single PDL file.
Method signatures and docstrings:
- def __init__(self, path, input_type='f'): Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's... | Implement the Python class `File` described below.
Class description:
Represents a single PDL file.
Method signatures and docstrings:
- def __init__(self, path, input_type='f'): Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's... | 345e7d47efdac04c2c5f70d55f83bd77acdbb511 | <|skeleton|>
class File:
"""Represents a single PDL file."""
def __init__(self, path, input_type='f'):
"""Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's contents belong in, - imports: a list of imports that th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class File:
"""Represents a single PDL file."""
def __init__(self, path, input_type='f'):
"""Initialize a File object from a file's worth of PDL. The PDL file should contain exactly three fields: - name: the namespace that the file's contents belong in, - imports: a list of imports that the file's cont... | the_stack_v2_python_sparse | topside/pdl/file.py | roguextech/Waterloo-Rocketry-topside | train | 0 |
cf0bf8ecf962cec11a35a563aa67f1b038a1709d | [
"ExecutionElement.__init__(self, uid)\nself.action = action\nself._args_api, self._data_in_api = get_filter_api(self.action)\nif isinstance(args, list):\n args = {arg['name']: arg['value'] for arg in args}\nelif isinstance(args, dict):\n args = args\nelse:\n args = {}\nself.args = validate_filter_parameter... | <|body_start_0|>
ExecutionElement.__init__(self, uid)
self.action = action
self._args_api, self._data_in_api = get_filter_api(self.action)
if isinstance(args, list):
args = {arg['name']: arg['value'] for arg in args}
elif isinstance(args, dict):
args = arg... | Filter | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Filter:
def __init__(self, action, args=None, uid=None):
"""Initializes a new Filter object. A Filter is used to filter input into a workflow. Args: action (str, optional): The action name for the filter. Defaults to an empty string. args (dict[str:str], optional): Dictionary of Argument... | stack_v2_sparse_classes_36k_train_031007 | 2,894 | permissive | [
{
"docstring": "Initializes a new Filter object. A Filter is used to filter input into a workflow. Args: action (str, optional): The action name for the filter. Defaults to an empty string. args (dict[str:str], optional): Dictionary of Argument keys to Argument values. This dictionary will be converted to a dic... | 2 | null | Implement the Python class `Filter` described below.
Class description:
Implement the Filter class.
Method signatures and docstrings:
- def __init__(self, action, args=None, uid=None): Initializes a new Filter object. A Filter is used to filter input into a workflow. Args: action (str, optional): The action name for ... | Implement the Python class `Filter` described below.
Class description:
Implement the Filter class.
Method signatures and docstrings:
- def __init__(self, action, args=None, uid=None): Initializes a new Filter object. A Filter is used to filter input into a workflow. Args: action (str, optional): The action name for ... | 18cd8b6d10241955bea5422947af9cf67f73aead | <|skeleton|>
class Filter:
def __init__(self, action, args=None, uid=None):
"""Initializes a new Filter object. A Filter is used to filter input into a workflow. Args: action (str, optional): The action name for the filter. Defaults to an empty string. args (dict[str:str], optional): Dictionary of Argument... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Filter:
def __init__(self, action, args=None, uid=None):
"""Initializes a new Filter object. A Filter is used to filter input into a workflow. Args: action (str, optional): The action name for the filter. Defaults to an empty string. args (dict[str:str], optional): Dictionary of Argument keys to Argum... | the_stack_v2_python_sparse | core/executionelements/filter.py | JustinTervala/WALKOFF | train | 0 | |
cc15e2111cd96a422debe0d6bf491ae7cdd6723a | [
"self.actor_id = kwargs.get('actor_id')\nself.name = kwargs.get('name')\nself.level = kwargs.get('level')\nself.gold = kwargs.get('gold')\nself.experience = kwargs.get('experience')\nself.max_hp = kwargs.get('max_hp')\nself.hp = kwargs.get('hp')\nself.max_ammo = kwargs.get('max_ammo')\nself.ammo = kwargs.get('ammo'... | <|body_start_0|>
self.actor_id = kwargs.get('actor_id')
self.name = kwargs.get('name')
self.level = kwargs.get('level')
self.gold = kwargs.get('gold')
self.experience = kwargs.get('experience')
self.max_hp = kwargs.get('max_hp')
self.hp = kwargs.get('hp')
... | Actor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Actor:
def __init__(self, **kwargs):
"""Params: actor_id: int name: str level: int gold: int experience: int max_hp: int hp: int max_ammo: int ammo: int"""
<|body_0|>
def load(self, **kwargs):
"""load from dict Exception: KeyError"""
<|body_1|>
def dump(... | stack_v2_sparse_classes_36k_train_031008 | 26,590 | no_license | [
{
"docstring": "Params: actor_id: int name: str level: int gold: int experience: int max_hp: int hp: int max_ammo: int ammo: int",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "load from dict Exception: KeyError",
"name": "load",
"signature": "def loa... | 3 | stack_v2_sparse_classes_30k_train_007130 | Implement the Python class `Actor` described below.
Class description:
Implement the Actor class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Params: actor_id: int name: str level: int gold: int experience: int max_hp: int hp: int max_ammo: int ammo: int
- def load(self, **kwargs): load from dic... | Implement the Python class `Actor` described below.
Class description:
Implement the Actor class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Params: actor_id: int name: str level: int gold: int experience: int max_hp: int hp: int max_ammo: int ammo: int
- def load(self, **kwargs): load from dic... | aa0b2697e295889e8c23a7104889ea95f2a4b6b1 | <|skeleton|>
class Actor:
def __init__(self, **kwargs):
"""Params: actor_id: int name: str level: int gold: int experience: int max_hp: int hp: int max_ammo: int ammo: int"""
<|body_0|>
def load(self, **kwargs):
"""load from dict Exception: KeyError"""
<|body_1|>
def dump(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Actor:
def __init__(self, **kwargs):
"""Params: actor_id: int name: str level: int gold: int experience: int max_hp: int hp: int max_ammo: int ammo: int"""
self.actor_id = kwargs.get('actor_id')
self.name = kwargs.get('name')
self.level = kwargs.get('level')
self.gold =... | the_stack_v2_python_sparse | message.py | songhui17/Server | train | 0 | |
c4144cf04301498932689276bc72f74e97b9f3ff | [
"self._schema = customer_schema\nself._provider = provider\nself._months_to_keep = num_of_months_to_keep\nif self._months_to_keep is None:\n self._months_to_keep = Config.MASU_RETAIN_NUM_MONTHS\nself._line_items_months = line_items_month_to_keep\nif self._line_items_months is None:\n self._line_items_months =... | <|body_start_0|>
self._schema = customer_schema
self._provider = provider
self._months_to_keep = num_of_months_to_keep
if self._months_to_keep is None:
self._months_to_keep = Config.MASU_RETAIN_NUM_MONTHS
self._line_items_months = line_items_month_to_keep
if s... | Removes expired report data based on masu's retention policy. Retention policy can be configured via environment variable. | ExpiredDataRemover | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExpiredDataRemover:
"""Removes expired report data based on masu's retention policy. Retention policy can be configured via environment variable."""
def __init__(self, customer_schema, provider, num_of_months_to_keep=None, line_items_month_to_keep=None):
"""Initializer. Args: custome... | stack_v2_sparse_classes_36k_train_031009 | 5,846 | permissive | [
{
"docstring": "Initializer. Args: customer_schema (String): Schema name for given customer. num_of_months_to_keep (Int): Number of months to retain in database.",
"name": "__init__",
"signature": "def __init__(self, customer_schema, provider, num_of_months_to_keep=None, line_items_month_to_keep=None)"
... | 4 | stack_v2_sparse_classes_30k_train_002966 | Implement the Python class `ExpiredDataRemover` described below.
Class description:
Removes expired report data based on masu's retention policy. Retention policy can be configured via environment variable.
Method signatures and docstrings:
- def __init__(self, customer_schema, provider, num_of_months_to_keep=None, l... | Implement the Python class `ExpiredDataRemover` described below.
Class description:
Removes expired report data based on masu's retention policy. Retention policy can be configured via environment variable.
Method signatures and docstrings:
- def __init__(self, customer_schema, provider, num_of_months_to_keep=None, l... | 0416e5216eb1ec4b41c8dd4999adde218b1ab2e1 | <|skeleton|>
class ExpiredDataRemover:
"""Removes expired report data based on masu's retention policy. Retention policy can be configured via environment variable."""
def __init__(self, customer_schema, provider, num_of_months_to_keep=None, line_items_month_to_keep=None):
"""Initializer. Args: custome... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExpiredDataRemover:
"""Removes expired report data based on masu's retention policy. Retention policy can be configured via environment variable."""
def __init__(self, customer_schema, provider, num_of_months_to_keep=None, line_items_month_to_keep=None):
"""Initializer. Args: customer_schema (Str... | the_stack_v2_python_sparse | koku/masu/processor/expired_data_remover.py | project-koku/koku | train | 225 |
6a85e86260d833c5bdacebb6338f77072fdcca23 | [
"try:\n self._authenticate_user_dn(password)\n self._check_requirements()\nexcept self.AuthenticationFailed as e:\n logger.debug(u'Authentication failed for %s: %s' % (self._username, e))\n return False\nexcept ldap.LDAPError as e:\n logger.warning(u'Caught LDAPError while authenticating %s: %s', sel... | <|body_start_0|>
try:
self._authenticate_user_dn(password)
self._check_requirements()
except self.AuthenticationFailed as e:
logger.debug(u'Authentication failed for %s: %s' % (self._username, e))
return False
except ldap.LDAPError as e:
... | _PolyauthenticationLDAPUser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _PolyauthenticationLDAPUser:
def ldap_authenticate(self, password):
"""Searches LDAP user and populates his attributes"""
<|body_0|>
def add_user_to_db(self):
"""Creating user id DB"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
se... | stack_v2_sparse_classes_36k_train_031010 | 3,949 | no_license | [
{
"docstring": "Searches LDAP user and populates his attributes",
"name": "ldap_authenticate",
"signature": "def ldap_authenticate(self, password)"
},
{
"docstring": "Creating user id DB",
"name": "add_user_to_db",
"signature": "def add_user_to_db(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002014 | Implement the Python class `_PolyauthenticationLDAPUser` described below.
Class description:
Implement the _PolyauthenticationLDAPUser class.
Method signatures and docstrings:
- def ldap_authenticate(self, password): Searches LDAP user and populates his attributes
- def add_user_to_db(self): Creating user id DB | Implement the Python class `_PolyauthenticationLDAPUser` described below.
Class description:
Implement the _PolyauthenticationLDAPUser class.
Method signatures and docstrings:
- def ldap_authenticate(self, password): Searches LDAP user and populates his attributes
- def add_user_to_db(self): Creating user id DB
<|sk... | 3bbf6d6347f8615f2d6a3052017f8f69a4244476 | <|skeleton|>
class _PolyauthenticationLDAPUser:
def ldap_authenticate(self, password):
"""Searches LDAP user and populates his attributes"""
<|body_0|>
def add_user_to_db(self):
"""Creating user id DB"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _PolyauthenticationLDAPUser:
def ldap_authenticate(self, password):
"""Searches LDAP user and populates his attributes"""
try:
self._authenticate_user_dn(password)
self._check_requirements()
except self.AuthenticationFailed as e:
logger.debug(u'Authe... | the_stack_v2_python_sparse | src/polyana-web-authentication/polyauthentication/backends.py | KirpichenkovPavel/merger | train | 0 | |
76c4de2c83b3e3ebbf01af528bdaae6c4d9795a0 | [
"est = clone(self.clf)\nest.fit(X.to_numpy(), y)\nif hasattr(est, 'coef_'):\n importance = est.coef_\nelif hasattr(est, 'feature_importances_'):\n importance = est.feature_importances_\nelse:\n raise AttributeError('{} do not has coef_ or feature_importance_'.format(self.clf.__class__.__name__))\nreturn (i... | <|body_start_0|>
est = clone(self.clf)
est.fit(X.to_numpy(), y)
if hasattr(est, 'coef_'):
importance = est.coef_
elif hasattr(est, 'feature_importances_'):
importance = est.feature_importances_
else:
raise AttributeError('{} do not has coef_ or... | FeatureImportanceSelect | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureImportanceSelect:
def get_thres(self, X, y):
"""得到不同特征的重要程度和最小值。"""
<|body_0|>
def choose(self, X, y, to_select=None):
"""不断出去最不重要的特征，最终选取结果最好的作为最终选择的特征进行后续建模。"""
<|body_1|>
def plot_process(self):
"""可视化在不断去除掉最不重要特征的情况下，结果的变化过程。"""
... | stack_v2_sparse_classes_36k_train_031011 | 15,365 | no_license | [
{
"docstring": "得到不同特征的重要程度和最小值。",
"name": "get_thres",
"signature": "def get_thres(self, X, y)"
},
{
"docstring": "不断出去最不重要的特征，最终选取结果最好的作为最终选择的特征进行后续建模。",
"name": "choose",
"signature": "def choose(self, X, y, to_select=None)"
},
{
"docstring": "可视化在不断去除掉最不重要特征的情况下，结果的变化过程。",
... | 3 | stack_v2_sparse_classes_30k_train_021632 | Implement the Python class `FeatureImportanceSelect` described below.
Class description:
Implement the FeatureImportanceSelect class.
Method signatures and docstrings:
- def get_thres(self, X, y): 得到不同特征的重要程度和最小值。
- def choose(self, X, y, to_select=None): 不断出去最不重要的特征，最终选取结果最好的作为最终选择的特征进行后续建模。
- def plot_process(self)... | Implement the Python class `FeatureImportanceSelect` described below.
Class description:
Implement the FeatureImportanceSelect class.
Method signatures and docstrings:
- def get_thres(self, X, y): 得到不同特征的重要程度和最小值。
- def choose(self, X, y, to_select=None): 不断出去最不重要的特征，最终选取结果最好的作为最终选择的特征进行后续建模。
- def plot_process(self)... | 823184005a3a2ed70a32b37c0afc2066e6e8907a | <|skeleton|>
class FeatureImportanceSelect:
def get_thres(self, X, y):
"""得到不同特征的重要程度和最小值。"""
<|body_0|>
def choose(self, X, y, to_select=None):
"""不断出去最不重要的特征，最终选取结果最好的作为最终选择的特征进行后续建模。"""
<|body_1|>
def plot_process(self):
"""可视化在不断去除掉最不重要特征的情况下，结果的变化过程。"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeatureImportanceSelect:
def get_thres(self, X, y):
"""得到不同特征的重要程度和最小值。"""
est = clone(self.clf)
est.fit(X.to_numpy(), y)
if hasattr(est, 'coef_'):
importance = est.coef_
elif hasattr(est, 'feature_importances_'):
importance = est.feature_importa... | the_stack_v2_python_sparse | WorkCode/Models/UserFunc/FeatureEngineering.py | johngolt/gitln | train | 1 | |
58f65d75ad373949cf0198f5c14d8a296cf06d03 | [
"super().__init__(coordinator=coordinator, kind=kind, name=name, item_id=item_id, icon=icon)\nself._state_key = state_key\nself._state = None\nself._last_action = 0\nself._state_delay = 30",
"state_int = 0\nif self._last_action < time.time() - self._state_delay:\n state_int = int(self.coordinator.data[self._it... | <|body_start_0|>
super().__init__(coordinator=coordinator, kind=kind, name=name, item_id=item_id, icon=icon)
self._state_key = state_key
self._state = None
self._last_action = 0
self._state_delay = 30
<|end_body_0|>
<|body_start_1|>
state_int = 0
if self._last_ac... | Define an Omnilogic Base Switch entity to be extended. | OmniLogicSwitch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OmniLogicSwitch:
"""Define an Omnilogic Base Switch entity to be extended."""
def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None:
"""Initialize Entities."""
<|body_0|>
def is_on(self):
... | stack_v2_sparse_classes_36k_train_031012 | 8,137 | permissive | [
{
"docstring": "Initialize Entities.",
"name": "__init__",
"signature": "def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None"
},
{
"docstring": "Return the on/off state of the switch.",
"name": "is_on",
"sig... | 2 | stack_v2_sparse_classes_30k_train_021135 | Implement the Python class `OmniLogicSwitch` described below.
Class description:
Define an Omnilogic Base Switch entity to be extended.
Method signatures and docstrings:
- def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None: Initialize E... | Implement the Python class `OmniLogicSwitch` described below.
Class description:
Define an Omnilogic Base Switch entity to be extended.
Method signatures and docstrings:
- def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None: Initialize E... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class OmniLogicSwitch:
"""Define an Omnilogic Base Switch entity to be extended."""
def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None:
"""Initialize Entities."""
<|body_0|>
def is_on(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OmniLogicSwitch:
"""Define an Omnilogic Base Switch entity to be extended."""
def __init__(self, coordinator: OmniLogicUpdateCoordinator, kind: str, name: str, icon: str, item_id: tuple, state_key: str) -> None:
"""Initialize Entities."""
super().__init__(coordinator=coordinator, kind=kin... | the_stack_v2_python_sparse | homeassistant/components/omnilogic/switch.py | home-assistant/core | train | 35,501 |
d9f78fa6ebc41ee8e75a732c1f55f9f6ce179d65 | [
"if not self.create_time:\n self.create_time = datetime.datetime.now()\nreturn super(Message, self).save(*args, **kwargs)",
"user = User.objects.get(id=self.user_id)\nres = {'id': str(self.id), 'msgType': self.msg_type, 'content': self.content, 'createTime': self.create_time.strftime('%s'), 'company': user.com... | <|body_start_0|>
if not self.create_time:
self.create_time = datetime.datetime.now()
return super(Message, self).save(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
user = User.objects.get(id=self.user_id)
res = {'id': str(self.id), 'msgType': self.msg_type, 'content': sel... | 消息类 | Message | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message:
"""消息类"""
def save(self, *args, **kwargs):
"""改写save函数，自动保存create_time"""
<|body_0|>
def get_json(self):
"""获取动态"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not self.create_time:
self.create_time = datetime.datetime.n... | stack_v2_sparse_classes_36k_train_031013 | 19,588 | no_license | [
{
"docstring": "改写save函数，自动保存create_time",
"name": "save",
"signature": "def save(self, *args, **kwargs)"
},
{
"docstring": "获取动态",
"name": "get_json",
"signature": "def get_json(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016197 | Implement the Python class `Message` described below.
Class description:
消息类
Method signatures and docstrings:
- def save(self, *args, **kwargs): 改写save函数，自动保存create_time
- def get_json(self): 获取动态 | Implement the Python class `Message` described below.
Class description:
消息类
Method signatures and docstrings:
- def save(self, *args, **kwargs): 改写save函数，自动保存create_time
- def get_json(self): 获取动态
<|skeleton|>
class Message:
"""消息类"""
def save(self, *args, **kwargs):
"""改写save函数，自动保存create_time"""
... | e31b674d38ce62c0ee30bf3dda4462060631974e | <|skeleton|>
class Message:
"""消息类"""
def save(self, *args, **kwargs):
"""改写save函数，自动保存create_time"""
<|body_0|>
def get_json(self):
"""获取动态"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Message:
"""消息类"""
def save(self, *args, **kwargs):
"""改写save函数，自动保存create_time"""
if not self.create_time:
self.create_time = datetime.datetime.now()
return super(Message, self).save(*args, **kwargs)
def get_json(self):
"""获取动态"""
user = User.obje... | the_stack_v2_python_sparse | taotao/api/models.py | leolinf/tornado-demo | train | 3 |
1be1ad830133b06647b37ac28e34bafe2fb59976 | [
"entity.name = domain.name\nentity.time = domain.time\nentity.width = domain.width\nentity.height = domain.height\nentity.spawnX = domain.spawn[0]\nentity.spawnY = domain.spawn[1]\nentity.worldSurface = domain.worldSurface\nentity.rockLayer = domain.rockLayer\nentity.isDay = domain.isDay\nentity.isBloodMoon = domai... | <|body_start_0|>
entity.name = domain.name
entity.time = domain.time
entity.width = domain.width
entity.height = domain.height
entity.spawnX = domain.spawn[0]
entity.spawnY = domain.spawn[1]
entity.worldSurface = domain.worldSurface
entity.rockLayer = doma... | Maps L{World} and L{WorldEntity} objects | WorldMapper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorldMapper:
"""Maps L{World} and L{WorldEntity} objects"""
def domainToEntity(self, domain, entity):
"""Maps a L{World} domain object to a L{WorldEntity} object"""
<|body_0|>
def entityToDomain(self, entity, domain):
"""Maps a L{WorldEntity} to a L{World} object... | stack_v2_sparse_classes_36k_train_031014 | 2,701 | no_license | [
{
"docstring": "Maps a L{World} domain object to a L{WorldEntity} object",
"name": "domainToEntity",
"signature": "def domainToEntity(self, domain, entity)"
},
{
"docstring": "Maps a L{WorldEntity} to a L{World} object",
"name": "entityToDomain",
"signature": "def entityToDomain(self, en... | 2 | stack_v2_sparse_classes_30k_train_010728 | Implement the Python class `WorldMapper` described below.
Class description:
Maps L{World} and L{WorldEntity} objects
Method signatures and docstrings:
- def domainToEntity(self, domain, entity): Maps a L{World} domain object to a L{WorldEntity} object
- def entityToDomain(self, entity, domain): Maps a L{WorldEntity}... | Implement the Python class `WorldMapper` described below.
Class description:
Maps L{World} and L{WorldEntity} objects
Method signatures and docstrings:
- def domainToEntity(self, domain, entity): Maps a L{World} domain object to a L{WorldEntity} object
- def entityToDomain(self, entity, domain): Maps a L{WorldEntity}... | 020ee14a28d61af9660d5d84d575c2e6302ce748 | <|skeleton|>
class WorldMapper:
"""Maps L{World} and L{WorldEntity} objects"""
def domainToEntity(self, domain, entity):
"""Maps a L{World} domain object to a L{WorldEntity} object"""
<|body_0|>
def entityToDomain(self, entity, domain):
"""Maps a L{WorldEntity} to a L{World} object... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorldMapper:
"""Maps L{World} and L{WorldEntity} objects"""
def domainToEntity(self, domain, entity):
"""Maps a L{World} domain object to a L{WorldEntity} object"""
entity.name = domain.name
entity.time = domain.time
entity.width = domain.width
entity.height = doma... | the_stack_v2_python_sparse | db/mappers.py | smoak/TPS | train | 9 |
2ac2bcfc80ea029601d99032b74cfea42f683920 | [
"self.assertEqual(list_copy([7, 8, 9, 10]), [7, 8, 9, 10])\nself.assertEqual(list_copy(['Rohan', '6,7,8', 7]), ['Rohan', '6,7,8', 7])\nself.assertEqual(list_copy([]), [])\nself.assertNotEqual(list_copy([10, 11, 12, 13]), [])\nself.assertNotEqual(list_copy([10, 11, 12, 13]), [10, 12])",
"self.assertEqual(list_inte... | <|body_start_0|>
self.assertEqual(list_copy([7, 8, 9, 10]), [7, 8, 9, 10])
self.assertEqual(list_copy(['Rohan', '6,7,8', 7]), ['Rohan', '6,7,8', 7])
self.assertEqual(list_copy([]), [])
self.assertNotEqual(list_copy([10, 11, 12, 13]), [])
self.assertNotEqual(list_copy([10, 11, 12,... | MyTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyTestCase:
def test_list_copy(self):
"""Function is used to test copy of list"""
<|body_0|>
def test_list_intersect(self):
"""Function is used to test intersection between two lists"""
<|body_1|>
def test_list_difference(self):
"""Function is us... | stack_v2_sparse_classes_36k_train_031015 | 2,888 | no_license | [
{
"docstring": "Function is used to test copy of list",
"name": "test_list_copy",
"signature": "def test_list_copy(self)"
},
{
"docstring": "Function is used to test intersection between two lists",
"name": "test_list_intersect",
"signature": "def test_list_intersect(self)"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_012416 | Implement the Python class `MyTestCase` described below.
Class description:
Implement the MyTestCase class.
Method signatures and docstrings:
- def test_list_copy(self): Function is used to test copy of list
- def test_list_intersect(self): Function is used to test intersection between two lists
- def test_list_diffe... | Implement the Python class `MyTestCase` described below.
Class description:
Implement the MyTestCase class.
Method signatures and docstrings:
- def test_list_copy(self): Function is used to test copy of list
- def test_list_intersect(self): Function is used to test intersection between two lists
- def test_list_diffe... | 7fe7bb8518584cc98f00f16d6b1cd0a288254ee3 | <|skeleton|>
class MyTestCase:
def test_list_copy(self):
"""Function is used to test copy of list"""
<|body_0|>
def test_list_intersect(self):
"""Function is used to test intersection between two lists"""
<|body_1|>
def test_list_difference(self):
"""Function is us... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyTestCase:
def test_list_copy(self):
"""Function is used to test copy of list"""
self.assertEqual(list_copy([7, 8, 9, 10]), [7, 8, 9, 10])
self.assertEqual(list_copy(['Rohan', '6,7,8', 7]), ['Rohan', '6,7,8', 7])
self.assertEqual(list_copy([]), [])
self.assertNotEqual(... | the_stack_v2_python_sparse | HW_06_Rohan_Ratwani/HW06_Test_Rohan_Ratwani.py | RohanRatwani/SSW-810 | train | 0 | |
8d801c45749ab7d46487f78945e58aa10e87c108 | [
"if not isinstance(model_grid, RasterModelGrid):\n raise TypeError('model_grid must be a Landlab RasterModelGrid')\nself.number_of_orientations = 2\nsuper().__init__(model_grid, node_state_dict, transition_list, initial_node_states, prop_data, prop_reset_value, seed)",
"self.link_orientation = np.zeros(self.gr... | <|body_start_0|>
if not isinstance(model_grid, RasterModelGrid):
raise TypeError('model_grid must be a Landlab RasterModelGrid')
self.number_of_orientations = 2
super().__init__(model_grid, node_state_dict, transition_list, initial_node_states, prop_data, prop_reset_value, seed)
<|en... | Oriented raster CellLab-CTS model. RasterCTS constructor: sets number of orientations to 2 and calls base-class constructor. Parameters ---------- model_grid : Landlab ModelGrid object Reference to the model's grid node_state_dict : dict Keys are node-state codes, values are the names associated with these codes transi... | OrientedRasterCTS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrientedRasterCTS:
"""Oriented raster CellLab-CTS model. RasterCTS constructor: sets number of orientations to 2 and calls base-class constructor. Parameters ---------- model_grid : Landlab ModelGrid object Reference to the model's grid node_state_dict : dict Keys are node-state codes, values are... | stack_v2_sparse_classes_36k_train_031016 | 4,813 | permissive | [
{
"docstring": "RasterCTS constructor: sets number of orientations to 2 and calls base-class constructor. Parameters ---------- model_grid : Landlab ModelGrid object Reference to the model's grid node_state_dict : dict Keys are node-state codes, values are the names associated with these codes transition_list :... | 2 | null | Implement the Python class `OrientedRasterCTS` described below.
Class description:
Oriented raster CellLab-CTS model. RasterCTS constructor: sets number of orientations to 2 and calls base-class constructor. Parameters ---------- model_grid : Landlab ModelGrid object Reference to the model's grid node_state_dict : dic... | Implement the Python class `OrientedRasterCTS` described below.
Class description:
Oriented raster CellLab-CTS model. RasterCTS constructor: sets number of orientations to 2 and calls base-class constructor. Parameters ---------- model_grid : Landlab ModelGrid object Reference to the model's grid node_state_dict : dic... | 1cd72e5832ece1aa922cd1b239e2e94ed0f11f8b | <|skeleton|>
class OrientedRasterCTS:
"""Oriented raster CellLab-CTS model. RasterCTS constructor: sets number of orientations to 2 and calls base-class constructor. Parameters ---------- model_grid : Landlab ModelGrid object Reference to the model's grid node_state_dict : dict Keys are node-state codes, values are... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrientedRasterCTS:
"""Oriented raster CellLab-CTS model. RasterCTS constructor: sets number of orientations to 2 and calls base-class constructor. Parameters ---------- model_grid : Landlab ModelGrid object Reference to the model's grid node_state_dict : dict Keys are node-state codes, values are the names as... | the_stack_v2_python_sparse | landlab/ca/oriented_raster_cts.py | landlab/landlab | train | 326 |
b4001cba7380517627fdb854f4ea2af66ce9e553 | [
"left = right = max_sum = float('-inf')\nfor a in arr:\n left, right = (max(a, left + a), max(left, right + a))\n max_sum = max(max_sum, right, left)\nreturn max_sum",
"n = len(arr)\ndp = [[float('-inf')] * 2 for _ in range(n)]\nres = float('-inf')\nfor i, a in enumerate(arr):\n dp[i][0] = max(a, dp[i - ... | <|body_start_0|>
left = right = max_sum = float('-inf')
for a in arr:
left, right = (max(a, left + a), max(left, right + a))
max_sum = max(max_sum, right, left)
return max_sum
<|end_body_0|>
<|body_start_1|>
n = len(arr)
dp = [[float('-inf')] * 2 for _ in... | Array | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Array:
def maximum_sum(self, arr: List[int]) -> int:
"""Approach: DP (contant space) Time Complexity: O(N) Space Complexity: O(1) :param arr: :return:"""
<|body_0|>
def maximum_sum_(self, arr: List[int]) -> int:
"""Approach: DP Formulae: --------- dp(i,0) = max(arr(i... | stack_v2_sparse_classes_36k_train_031017 | 2,196 | no_license | [
{
"docstring": "Approach: DP (contant space) Time Complexity: O(N) Space Complexity: O(1) :param arr: :return:",
"name": "maximum_sum",
"signature": "def maximum_sum(self, arr: List[int]) -> int"
},
{
"docstring": "Approach: DP Formulae: --------- dp(i,0) = max(arr(i), dp(i - 1, 0) + arr(i)) dp(... | 3 | null | Implement the Python class `Array` described below.
Class description:
Implement the Array class.
Method signatures and docstrings:
- def maximum_sum(self, arr: List[int]) -> int: Approach: DP (contant space) Time Complexity: O(N) Space Complexity: O(1) :param arr: :return:
- def maximum_sum_(self, arr: List[int]) ->... | Implement the Python class `Array` described below.
Class description:
Implement the Array class.
Method signatures and docstrings:
- def maximum_sum(self, arr: List[int]) -> int: Approach: DP (contant space) Time Complexity: O(N) Space Complexity: O(1) :param arr: :return:
- def maximum_sum_(self, arr: List[int]) ->... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Array:
def maximum_sum(self, arr: List[int]) -> int:
"""Approach: DP (contant space) Time Complexity: O(N) Space Complexity: O(1) :param arr: :return:"""
<|body_0|>
def maximum_sum_(self, arr: List[int]) -> int:
"""Approach: DP Formulae: --------- dp(i,0) = max(arr(i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Array:
def maximum_sum(self, arr: List[int]) -> int:
"""Approach: DP (contant space) Time Complexity: O(N) Space Complexity: O(1) :param arr: :return:"""
left = right = max_sum = float('-inf')
for a in arr:
left, right = (max(a, left + a), max(left, right + a))
... | the_stack_v2_python_sparse | revisited_2021/arrays/max_sub_sum_with_one_deletion.py | Shiv2157k/leet_code | train | 1 | |
fe1b68be12c5b5606e3c516dd1543be259d091e3 | [
"data_list = []\nresults = self.query.all()\nformatter = self.request.locale.dates.getFormatter('date', 'short')\nfor result in results:\n data = {}\n data['qid'] = 'i-' + str(result.parliamentary_item_id)\n if type(result) == domain.AgendaItem:\n g = u' ' + result.group.type + u' ' + result.group.s... | <|body_start_0|>
data_list = []
results = self.query.all()
formatter = self.request.locale.dates.getFormatter('date', 'short')
for result in results:
data = {}
data['qid'] = 'i-' + str(result.parliamentary_item_id)
if type(result) == domain.AgendaItem:... | Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible) | ItemInStageViewlet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemInStageViewlet:
"""Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)"""
def getData(self):
"""return the data of the query"""
<|body_0|>
def update(self):
"""refresh the query""... | stack_v2_sparse_classes_36k_train_031018 | 35,739 | no_license | [
{
"docstring": "return the data of the query",
"name": "getData",
"signature": "def getData(self)"
},
{
"docstring": "refresh the query",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019543 | Implement the Python class `ItemInStageViewlet` described below.
Class description:
Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)
Method signatures and docstrings:
- def getData(self): return the data of the query
- def update(self)... | Implement the Python class `ItemInStageViewlet` described below.
Class description:
Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)
Method signatures and docstrings:
- def getData(self): return the data of the query
- def update(self)... | 5cf0ba31dfbff8d2c1b4aa8ab6f69c7a0ae9870d | <|skeleton|>
class ItemInStageViewlet:
"""Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)"""
def getData(self):
"""return the data of the query"""
<|body_0|>
def update(self):
"""refresh the query""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ItemInStageViewlet:
"""Group parliamentary items per stage: e.g. action required, in progress, answered/debated, 'dead' (withdrawn, elapsed, inadmissible)"""
def getData(self):
"""return the data of the query"""
data_list = []
results = self.query.all()
formatter = self.re... | the_stack_v2_python_sparse | bungeni.buildout/branches/bungeni.buildout-refactor-2010-06-02/src/bungeni.main/bungeni/ui/viewlets/workspace.py | malangalanga/bungeni-portal | train | 0 |
06c1a0d84c8db317d092edc8460a589020d15641 | [
"context = super().get_context_data(**kwargs)\ncontext['key'], _ = list(self.workflow.attributes.items())[kwargs['pk']]\nreturn context",
"wf_attributes = self.workflow.attributes\nkey = sorted(wf_attributes.keys())[kwargs['pk']]\nwf_attributes.pop(key, None)\nself.workflow.attributes = wf_attributes\nself.workfl... | <|body_start_0|>
context = super().get_context_data(**kwargs)
context['key'], _ = list(self.workflow.attributes.items())[kwargs['pk']]
return context
<|end_body_0|>
<|body_start_1|>
wf_attributes = self.workflow.attributes
key = sorted(wf_attributes.keys())[kwargs['pk']]
... | View to delete an existing attribute in a workflow. | WorkflowAttributeDeleteView | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkflowAttributeDeleteView:
"""View to delete an existing attribute in a workflow."""
def get_context_data(self, **kwargs):
"""Add pk and the key name to the context."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Perform the attribute delete operati... | stack_v2_sparse_classes_36k_train_031019 | 2,934 | permissive | [
{
"docstring": "Add pk and the key name to the context.",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
{
"docstring": "Perform the attribute delete operation.",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | null | Implement the Python class `WorkflowAttributeDeleteView` described below.
Class description:
View to delete an existing attribute in a workflow.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Add pk and the key name to the context.
- def post(self, request, *args, **kwargs): Perform the att... | Implement the Python class `WorkflowAttributeDeleteView` described below.
Class description:
View to delete an existing attribute in a workflow.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Add pk and the key name to the context.
- def post(self, request, *args, **kwargs): Perform the att... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class WorkflowAttributeDeleteView:
"""View to delete an existing attribute in a workflow."""
def get_context_data(self, **kwargs):
"""Add pk and the key name to the context."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Perform the attribute delete operati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkflowAttributeDeleteView:
"""View to delete an existing attribute in a workflow."""
def get_context_data(self, **kwargs):
"""Add pk and the key name to the context."""
context = super().get_context_data(**kwargs)
context['key'], _ = list(self.workflow.attributes.items())[kwargs... | the_stack_v2_python_sparse | ontask/workflow/views/attribute.py | abelardopardo/ontask_b | train | 43 |
671849ab2adf46447ae6df8a0ff3220cc0aaa574 | [
"self.window = window\nworkspace = window.application.get_service(IWorkspace)\nself.pages = [ProjectWizardPage(id='project_page', location=workspace.absolute_path)]\nsuper(ProjectWizard, self).__init__(**traits)",
"workspace = self.window.application.get_service(IWorkspace)\npwp = self.pages[0]\nproject = workspa... | <|body_start_0|>
self.window = window
workspace = window.application.get_service(IWorkspace)
self.pages = [ProjectWizardPage(id='project_page', location=workspace.absolute_path)]
super(ProjectWizard, self).__init__(**traits)
<|end_body_0|>
<|body_start_1|>
workspace = self.windo... | A wizard for project creation. | ProjectWizard | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectWizard:
"""A wizard for project creation."""
def __init__(self, window, **traits):
"""Returns a ProjectWizard."""
<|body_0|>
def _finished_fired(self):
"""Performs the project resource creation if the wizard is finished successfully."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_031020 | 7,796 | permissive | [
{
"docstring": "Returns a ProjectWizard.",
"name": "__init__",
"signature": "def __init__(self, window, **traits)"
},
{
"docstring": "Performs the project resource creation if the wizard is finished successfully.",
"name": "_finished_fired",
"signature": "def _finished_fired(self)"
}
] | 2 | null | Implement the Python class `ProjectWizard` described below.
Class description:
A wizard for project creation.
Method signatures and docstrings:
- def __init__(self, window, **traits): Returns a ProjectWizard.
- def _finished_fired(self): Performs the project resource creation if the wizard is finished successfully. | Implement the Python class `ProjectWizard` described below.
Class description:
A wizard for project creation.
Method signatures and docstrings:
- def __init__(self, window, **traits): Returns a ProjectWizard.
- def _finished_fired(self): Performs the project resource creation if the wizard is finished successfully.
... | e8fc0b2d6b9b08e60389fc4714a5cf51f628b57f | <|skeleton|>
class ProjectWizard:
"""A wizard for project creation."""
def __init__(self, window, **traits):
"""Returns a ProjectWizard."""
<|body_0|>
def _finished_fired(self):
"""Performs the project resource creation if the wizard is finished successfully."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectWizard:
"""A wizard for project creation."""
def __init__(self, window, **traits):
"""Returns a ProjectWizard."""
self.window = window
workspace = window.application.get_service(IWorkspace)
self.pages = [ProjectWizardPage(id='project_page', location=workspace.absolu... | the_stack_v2_python_sparse | puddle/resource/wizard/project_wizard.py | rwl/puddle | train | 2 |
38c276fda97a8f5b43ee444929d3c7103c8e2d6e | [
"if categories_filter is None:\n categories_filter = {'Default': IMultiprocessChildPlugin}\nPluginManager.__init__(self, categories_filter=categories_filter, directories_list=directories_list, plugin_info_ext=plugin_info_ext, plugin_locator=plugin_locator)",
"instanciated_element = MultiprocessPluginProxy()\np... | <|body_start_0|>
if categories_filter is None:
categories_filter = {'Default': IMultiprocessChildPlugin}
PluginManager.__init__(self, categories_filter=categories_filter, directories_list=directories_list, plugin_info_ext=plugin_info_ext, plugin_locator=plugin_locator)
<|end_body_0|>
<|body... | Subclass of the PluginManager that runs each plugin in a different process | MultiprocessPluginManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiprocessPluginManager:
"""Subclass of the PluginManager that runs each plugin in a different process"""
def __init__(self, categories_filter=None, directories_list=None, plugin_info_ext=None, plugin_locator=None):
"""init"""
<|body_0|>
def instanciateElement(self, el... | stack_v2_sparse_classes_36k_train_031021 | 1,628 | permissive | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self, categories_filter=None, directories_list=None, plugin_info_ext=None, plugin_locator=None)"
},
{
"docstring": "This method instanciate each plugin in a new process and link it to the parent with a pipe. In the parent proc... | 2 | stack_v2_sparse_classes_30k_train_003563 | Implement the Python class `MultiprocessPluginManager` described below.
Class description:
Subclass of the PluginManager that runs each plugin in a different process
Method signatures and docstrings:
- def __init__(self, categories_filter=None, directories_list=None, plugin_info_ext=None, plugin_locator=None): init
-... | Implement the Python class `MultiprocessPluginManager` described below.
Class description:
Subclass of the PluginManager that runs each plugin in a different process
Method signatures and docstrings:
- def __init__(self, categories_filter=None, directories_list=None, plugin_info_ext=None, plugin_locator=None): init
-... | 7c3d9e975dae3835e2ccf42c425d65b26466e82a | <|skeleton|>
class MultiprocessPluginManager:
"""Subclass of the PluginManager that runs each plugin in a different process"""
def __init__(self, categories_filter=None, directories_list=None, plugin_info_ext=None, plugin_locator=None):
"""init"""
<|body_0|>
def instanciateElement(self, el... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiprocessPluginManager:
"""Subclass of the PluginManager that runs each plugin in a different process"""
def __init__(self, categories_filter=None, directories_list=None, plugin_info_ext=None, plugin_locator=None):
"""init"""
if categories_filter is None:
categories_filter ... | the_stack_v2_python_sparse | venv/lib/python2.7/site-packages/yapsy/MultiprocessPluginManager.py | WhySoGeeky/DroidPot | train | 6 |
8202b65efd2e9414410d73fc04decc39c5fd5749 | [
"self.graph = graph\nself.distance = dict()\nfor source in self.graph.iternodes():\n self.distance[source] = dict()\n for target in self.graph.iternodes():\n self.distance[source][target] = float('inf')\n self.distance[source][source] = 0\nif self.graph.is_directed():\n for edge in self.graph.ite... | <|body_start_0|>
self.graph = graph
self.distance = dict()
for source in self.graph.iternodes():
self.distance[source] = dict()
for target in self.graph.iternodes():
self.distance[source][target] = float('inf')
self.distance[source][source] = 0... | The Floyd-Warshall algorithm, nonnegative edge weights. Negative cycles are forbidden. Attributes ---------- graph : input weighted graph (directed or undirected) distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from graphtheory.structures.graphs import Graph >>> from grap... | FloydWarshallAllGraphs | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FloydWarshallAllGraphs:
"""The Floyd-Warshall algorithm, nonnegative edge weights. Negative cycles are forbidden. Attributes ---------- graph : input weighted graph (directed or undirected) distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from grapht... | stack_v2_sparse_classes_36k_train_031022 | 7,754 | permissive | [
{
"docstring": "The algorithm initialization. Parameters ---------- graph : directed or undirected weighted graph",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Finding all shortest paths.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019603 | Implement the Python class `FloydWarshallAllGraphs` described below.
Class description:
The Floyd-Warshall algorithm, nonnegative edge weights. Negative cycles are forbidden. Attributes ---------- graph : input weighted graph (directed or undirected) distance : dict-of-dict Examples -------- >>> from graphtheory.struc... | Implement the Python class `FloydWarshallAllGraphs` described below.
Class description:
The Floyd-Warshall algorithm, nonnegative edge weights. Negative cycles are forbidden. Attributes ---------- graph : input weighted graph (directed or undirected) distance : dict-of-dict Examples -------- >>> from graphtheory.struc... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class FloydWarshallAllGraphs:
"""The Floyd-Warshall algorithm, nonnegative edge weights. Negative cycles are forbidden. Attributes ---------- graph : input weighted graph (directed or undirected) distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from grapht... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FloydWarshallAllGraphs:
"""The Floyd-Warshall algorithm, nonnegative edge weights. Negative cycles are forbidden. Attributes ---------- graph : input weighted graph (directed or undirected) distance : dict-of-dict Examples -------- >>> from graphtheory.structures.edges import Edge >>> from graphtheory.structu... | the_stack_v2_python_sparse | graphtheory/shortestpaths/floydwarshall.py | kgashok/graphs-dict | train | 0 |
903e295630fefb53f60a3ce3ada21975eb918d51 | [
"tree = deepcopy(obj.__dict__)\npath = tree.pop('path', None)\nbuffer = tree.pop('buffer', None)\nsave_content = tree.pop('asdf_save_content')\nalgorithm = tree.pop('hashing_algorithm')\nhash_value = tree.pop('hash')\nif save_content:\n if buffer is None:\n buffer = obj.get_file_content()\n tree['conte... | <|body_start_0|>
tree = deepcopy(obj.__dict__)
path = tree.pop('path', None)
buffer = tree.pop('buffer', None)
save_content = tree.pop('asdf_save_content')
algorithm = tree.pop('hashing_algorithm')
hash_value = tree.pop('hash')
if save_content:
if buff... | Serialization class for `weldx.core.ExternalFile`. | ExternalFileConverter | [
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternalFileConverter:
"""Serialization class for `weldx.core.ExternalFile`."""
def to_yaml_tree(self, obj: ExternalFile, tag: str, ctx) -> dict:
"""Convert to python dict."""
<|body_0|>
def from_yaml_tree(self, node: dict, tag: str, ctx):
"""Construct from tree.... | stack_v2_sparse_classes_36k_train_031023 | 2,357 | permissive | [
{
"docstring": "Convert to python dict.",
"name": "to_yaml_tree",
"signature": "def to_yaml_tree(self, obj: ExternalFile, tag: str, ctx) -> dict"
},
{
"docstring": "Construct from tree.",
"name": "from_yaml_tree",
"signature": "def from_yaml_tree(self, node: dict, tag: str, ctx)"
}
] | 2 | null | Implement the Python class `ExternalFileConverter` described below.
Class description:
Serialization class for `weldx.core.ExternalFile`.
Method signatures and docstrings:
- def to_yaml_tree(self, obj: ExternalFile, tag: str, ctx) -> dict: Convert to python dict.
- def from_yaml_tree(self, node: dict, tag: str, ctx):... | Implement the Python class `ExternalFileConverter` described below.
Class description:
Serialization class for `weldx.core.ExternalFile`.
Method signatures and docstrings:
- def to_yaml_tree(self, obj: ExternalFile, tag: str, ctx) -> dict: Convert to python dict.
- def from_yaml_tree(self, node: dict, tag: str, ctx):... | 7bc16a196ee669822f3663f3c7a08f6bbd0c76d5 | <|skeleton|>
class ExternalFileConverter:
"""Serialization class for `weldx.core.ExternalFile`."""
def to_yaml_tree(self, obj: ExternalFile, tag: str, ctx) -> dict:
"""Convert to python dict."""
<|body_0|>
def from_yaml_tree(self, node: dict, tag: str, ctx):
"""Construct from tree.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExternalFileConverter:
"""Serialization class for `weldx.core.ExternalFile`."""
def to_yaml_tree(self, obj: ExternalFile, tag: str, ctx) -> dict:
"""Convert to python dict."""
tree = deepcopy(obj.__dict__)
path = tree.pop('path', None)
buffer = tree.pop('buffer', None)
... | the_stack_v2_python_sparse | weldx/tags/core/file.py | BAMWelDX/weldx | train | 20 |
a8177b63ea2691590ff458a622d3e25a401bfa99 | [
"if not root or root == p or root == q:\n return root\nleft = self.lowestCommonAncestor(root.left, p, q)\nright = self.lowestCommonAncestor(root.right, p, q)\nif not left:\n return right\nif not right:\n return left\nif left and right:\n return root\nreturn None",
"if not root or root == p or root == ... | <|body_start_0|>
if not root or root == p or root == q:
return root
left = self.lowestCommonAncestor(root.left, p, q)
right = self.lowestCommonAncestor(root.right, p, q)
if not left:
return right
if not right:
return left
if left and ri... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""1、读题：节点值唯一，p、q不同节点均存在二叉树，求二者的最近公共祖先，可能为自己。 2、思路： 递归、分治： 1）从根节点出发，记录每个节点找到p或者q的状态然后往父节点传。 2）找p或者q都可以返回的逻辑是： 2.1 找到一个节点p（或者q），就确定了该节点一定与最终结果有关： 2.1.1 p是最终结果，比如找到p，包含了后裔节点q，此时返回了p。 2.1... | stack_v2_sparse_classes_36k_train_031024 | 2,380 | no_license | [
{
"docstring": "1、读题：节点值唯一，p、q不同节点均存在二叉树，求二者的最近公共祖先，可能为自己。 2、思路： 递归、分治： 1）从根节点出发，记录每个节点找到p或者q的状态然后往父节点传。 2）找p或者q都可以返回的逻辑是： 2.1 找到一个节点p（或者q），就确定了该节点一定与最终结果有关： 2.1.1 p是最终结果，比如找到p，包含了后裔节点q，此时返回了p。 2.1.2 p不是最终结果，返回该节点的结果后，通过q节点的返回结果合并即可找到最终结果。",
"name": "lowestCommonAncestor",
"signature": "def lowestCommon... | 2 | stack_v2_sparse_classes_30k_train_013297 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode': 1、读题：节点值唯一，p、q不同节点均存在二叉树，求二者的最近公共祖先，可能为自己。 2、思路： 递归、分治： 1）从根节点出发，记录每个节点找到p或者q的状态然后往父... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode': 1、读题：节点值唯一，p、q不同节点均存在二叉树，求二者的最近公共祖先，可能为自己。 2、思路： 递归、分治： 1）从根节点出发，记录每个节点找到p或者q的状态然后往父... | 7fde3c1dddf8ca6b89924ca13d0aa5ffc03a1545 | <|skeleton|>
class Solution:
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""1、读题：节点值唯一，p、q不同节点均存在二叉树，求二者的最近公共祖先，可能为自己。 2、思路： 递归、分治： 1）从根节点出发，记录每个节点找到p或者q的状态然后往父节点传。 2）找p或者q都可以返回的逻辑是： 2.1 找到一个节点p（或者q），就确定了该节点一定与最终结果有关： 2.1.1 p是最终结果，比如找到p，包含了后裔节点q，此时返回了p。 2.1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode':
"""1、读题：节点值唯一，p、q不同节点均存在二叉树，求二者的最近公共祖先，可能为自己。 2、思路： 递归、分治： 1）从根节点出发，记录每个节点找到p或者q的状态然后往父节点传。 2）找p或者q都可以返回的逻辑是： 2.1 找到一个节点p（或者q），就确定了该节点一定与最终结果有关： 2.1.1 p是最终结果，比如找到p，包含了后裔节点q，此时返回了p。 2.1.2 p不是最终结果，返回该... | the_stack_v2_python_sparse | Week_03/236.lowest-common-ancestor-of-a-binary-tree.py | liubio0/algorithm022 | train | 0 | |
9f2bccb03081cbc1a28beaa34f1547455e602dd9 | [
"threading.Thread.__init__(self)\nself.daemon = True\nself.queue = queue\nself.processedUrls = processedUrls\nself.selectedDomains = selectedDomains\nself.selectedUrls = selectedUrls\nself.baseFileName = baseFileName\nself.parseTimeout = parseTimeout",
"global parseCancelled\nstartTime = time.time()\nlastActionTi... | <|body_start_0|>
threading.Thread.__init__(self)
self.daemon = True
self.queue = queue
self.processedUrls = processedUrls
self.selectedDomains = selectedDomains
self.selectedUrls = selectedUrls
self.baseFileName = baseFileName
self.parseTimeout = parseTime... | SpiderMonitor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpiderMonitor:
def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout):
"""Инициализация"""
<|body_0|>
def run(self):
"""Каждые 5 секунд сохраняем базу в файл и выводим текущую информацию. По истечении тайматута завершаем в... | stack_v2_sparse_classes_36k_train_031025 | 5,227 | no_license | [
{
"docstring": "Инициализация",
"name": "__init__",
"signature": "def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout)"
},
{
"docstring": "Каждые 5 секунд сохраняем базу в файл и выводим текущую информацию. По истечении тайматута завершаем выполнени... | 2 | stack_v2_sparse_classes_30k_train_010093 | Implement the Python class `SpiderMonitor` described below.
Class description:
Implement the SpiderMonitor class.
Method signatures and docstrings:
- def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout): Инициализация
- def run(self): Каждые 5 секунд сохраняем базу в фай... | Implement the Python class `SpiderMonitor` described below.
Class description:
Implement the SpiderMonitor class.
Method signatures and docstrings:
- def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout): Инициализация
- def run(self): Каждые 5 секунд сохраняем базу в фай... | d2771bf04aa187dda6d468883a5a167237589369 | <|skeleton|>
class SpiderMonitor:
def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout):
"""Инициализация"""
<|body_0|>
def run(self):
"""Каждые 5 секунд сохраняем базу в файл и выводим текущую информацию. По истечении тайматута завершаем в... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpiderMonitor:
def __init__(self, queue, processedUrls, selectedDomains, selectedUrls, baseFileName, parseTimeout):
"""Инициализация"""
threading.Thread.__init__(self)
self.daemon = True
self.queue = queue
self.processedUrls = processedUrls
self.selectedDomains ... | the_stack_v2_python_sparse | doorsagents/baseparser.py | cash2one/doorscenter | train | 0 | |
8fd103c2892d529f5fd66ed603ad285900c9f5c9 | [
"nbm = self.notebook_manager\ncheckpoints = nbm.list_checkpoints(notebook_id)\ndata = jsonapi.dumps(checkpoints, default=date_default)\nself.finish(data)",
"nbm = self.notebook_manager\ncheckpoint = nbm.create_checkpoint(notebook_id)\ndata = jsonapi.dumps(checkpoint, default=date_default)\nself.set_header('Locati... | <|body_start_0|>
nbm = self.notebook_manager
checkpoints = nbm.list_checkpoints(notebook_id)
data = jsonapi.dumps(checkpoints, default=date_default)
self.finish(data)
<|end_body_0|>
<|body_start_1|>
nbm = self.notebook_manager
checkpoint = nbm.create_checkpoint(notebook_... | NotebookCheckpointsHandler | [
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotebookCheckpointsHandler:
def get(self, notebook_id):
"""get lists checkpoints for a notebook"""
<|body_0|>
def post(self, notebook_id):
"""post creates a new checkpoint"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nbm = self.notebook_manager
... | stack_v2_sparse_classes_36k_train_031026 | 5,267 | permissive | [
{
"docstring": "get lists checkpoints for a notebook",
"name": "get",
"signature": "def get(self, notebook_id)"
},
{
"docstring": "post creates a new checkpoint",
"name": "post",
"signature": "def post(self, notebook_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005772 | Implement the Python class `NotebookCheckpointsHandler` described below.
Class description:
Implement the NotebookCheckpointsHandler class.
Method signatures and docstrings:
- def get(self, notebook_id): get lists checkpoints for a notebook
- def post(self, notebook_id): post creates a new checkpoint | Implement the Python class `NotebookCheckpointsHandler` described below.
Class description:
Implement the NotebookCheckpointsHandler class.
Method signatures and docstrings:
- def get(self, notebook_id): get lists checkpoints for a notebook
- def post(self, notebook_id): post creates a new checkpoint
<|skeleton|>
cl... | 2c9002f16bb5c265e0d14f4a2314c86eeaa35cb6 | <|skeleton|>
class NotebookCheckpointsHandler:
def get(self, notebook_id):
"""get lists checkpoints for a notebook"""
<|body_0|>
def post(self, notebook_id):
"""post creates a new checkpoint"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotebookCheckpointsHandler:
def get(self, notebook_id):
"""get lists checkpoints for a notebook"""
nbm = self.notebook_manager
checkpoints = nbm.list_checkpoints(notebook_id)
data = jsonapi.dumps(checkpoints, default=date_default)
self.finish(data)
def post(self, n... | the_stack_v2_python_sparse | pkgs/ipython-1.2.1-py27_0/lib/python2.7/site-packages/IPython/html/services/notebooks/handlers.py | wangyum/Anaconda | train | 11 | |
72b4cb5b5edc245b3a7cd791a5beba5b5c960e7b | [
"stock = StockModel.query.filter_by(id=stock_id).first()\nif not stock:\n stock_api.abort(404, 'Stock {} not found'.format(stock_id))\nelse:\n return stock",
"stock = StockModel.query.filter_by(id=stock_id).first()\nif not stock:\n stock_api.abort(404, 'Stock {} not found'.format(stock_id))\nstock.delete... | <|body_start_0|>
stock = StockModel.query.filter_by(id=stock_id).first()
if not stock:
stock_api.abort(404, 'Stock {} not found'.format(stock_id))
else:
return stock
<|end_body_0|>
<|body_start_1|>
stock = StockModel.query.filter_by(id=stock_id).first()
i... | Stock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Stock:
def get(self, stock_id):
"""Get a stock given its identifier"""
<|body_0|>
def delete(self, stock_id):
"""Delete a stock given its identifier"""
<|body_1|>
def put(self, stock_id):
"""Update a stock given its identifier"""
<|body_2... | stack_v2_sparse_classes_36k_train_031027 | 3,211 | no_license | [
{
"docstring": "Get a stock given its identifier",
"name": "get",
"signature": "def get(self, stock_id)"
},
{
"docstring": "Delete a stock given its identifier",
"name": "delete",
"signature": "def delete(self, stock_id)"
},
{
"docstring": "Update a stock given its identifier",
... | 3 | stack_v2_sparse_classes_30k_train_014588 | Implement the Python class `Stock` described below.
Class description:
Implement the Stock class.
Method signatures and docstrings:
- def get(self, stock_id): Get a stock given its identifier
- def delete(self, stock_id): Delete a stock given its identifier
- def put(self, stock_id): Update a stock given its identifi... | Implement the Python class `Stock` described below.
Class description:
Implement the Stock class.
Method signatures and docstrings:
- def get(self, stock_id): Get a stock given its identifier
- def delete(self, stock_id): Delete a stock given its identifier
- def put(self, stock_id): Update a stock given its identifi... | f380164e92b70874042364ad4b5b20c5793d6921 | <|skeleton|>
class Stock:
def get(self, stock_id):
"""Get a stock given its identifier"""
<|body_0|>
def delete(self, stock_id):
"""Delete a stock given its identifier"""
<|body_1|>
def put(self, stock_id):
"""Update a stock given its identifier"""
<|body_2... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Stock:
def get(self, stock_id):
"""Get a stock given its identifier"""
stock = StockModel.query.filter_by(id=stock_id).first()
if not stock:
stock_api.abort(404, 'Stock {} not found'.format(stock_id))
else:
return stock
def delete(self, stock_id):
... | the_stack_v2_python_sparse | project/app/main/controllers/stock.py | ArielVilleda/docker-flask-postgres | train | 0 | |
cbf1708b5a64a01c4426122e5f958f52d22f31c3 | [
"record = set()\nj = i = 0\nmaxlth = 0\nwhile i < len(s) and j < len(s):\n if s[j] not in record:\n record.add(s[j])\n j += 1\n maxlth = max(maxlth, j - i)\n else:\n record.remove(s[i])\n i += 1\nreturn maxlth",
"record = collections.Counter()\ni = 0\nmaxlth = 0\nfor j in ... | <|body_start_0|>
record = set()
j = i = 0
maxlth = 0
while i < len(s) and j < len(s):
if s[j] not in record:
record.add(s[j])
j += 1
maxlth = max(maxlth, j - i)
else:
record.remove(s[i])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring_1(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def lengthOfLongestSubstring_2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
def lengthOfLongestSubstring_3(self, s):
""":type s: str :rtype: int""... | stack_v2_sparse_classes_36k_train_031028 | 2,038 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "lengthOfLongestSubstring_1",
"signature": "def lengthOfLongestSubstring_1(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "lengthOfLongestSubstring_2",
"signature": "def lengthOfLongestSubstring_2(self, s)"
},
{
... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring_1(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring_2(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring_3(self, s): :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLongestSubstring_1(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring_2(self, s): :type s: str :rtype: int
- def lengthOfLongestSubstring_3(self, s): :... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Solution:
def lengthOfLongestSubstring_1(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def lengthOfLongestSubstring_2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
def lengthOfLongestSubstring_3(self, s):
""":type s: str :rtype: int""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLongestSubstring_1(self, s):
""":type s: str :rtype: int"""
record = set()
j = i = 0
maxlth = 0
while i < len(s) and j < len(s):
if s[j] not in record:
record.add(s[j])
j += 1
maxlth = max... | the_stack_v2_python_sparse | medium/twopointer/test_3_Longest_Substring_Without_Repeating_Characters.py | wuxu1019/leetcode_sophia | train | 1 | |
518f3d02e49c396960bcde24a98ffc6ff8d6b94e | [
"super(PlainParamsFile, self).__init__(path)\nlines = self.read().split('\\n')\nlines = (l.strip() for l in lines)\nself._lines = [l for l in lines if l and (not l.startswith('#'))]\nself._names = get_names(self._lines)",
"info = {}\nfor line in self._lines:\n key, value = get_key_value(line)\n info[key] = ... | <|body_start_0|>
super(PlainParamsFile, self).__init__(path)
lines = self.read().split('\n')
lines = (l.strip() for l in lines)
self._lines = [l for l in lines if l and (not l.startswith('#'))]
self._names = get_names(self._lines)
<|end_body_0|>
<|body_start_1|>
info = {... | . | PlainParamsFile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlainParamsFile:
"""."""
def __init__(self, path):
"""."""
<|body_0|>
def get_info(self):
"""."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(PlainParamsFile, self).__init__(path)
lines = self.read().split('\n')
lines = (l... | stack_v2_sparse_classes_36k_train_031029 | 7,197 | permissive | [
{
"docstring": ".",
"name": "__init__",
"signature": "def __init__(self, path)"
},
{
"docstring": ".",
"name": "get_info",
"signature": "def get_info(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003199 | Implement the Python class `PlainParamsFile` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, path): .
- def get_info(self): . | Implement the Python class `PlainParamsFile` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, path): .
- def get_info(self): .
<|skeleton|>
class PlainParamsFile:
"""."""
def __init__(self, path):
"""."""
<|body_0|>
def get_info(self):
... | a94831cd1bf40a59587a7b6cc2e9b5c4306b1bf2 | <|skeleton|>
class PlainParamsFile:
"""."""
def __init__(self, path):
"""."""
<|body_0|>
def get_info(self):
"""."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlainParamsFile:
"""."""
def __init__(self, path):
"""."""
super(PlainParamsFile, self).__init__(path)
lines = self.read().split('\n')
lines = (l.strip() for l in lines)
self._lines = [l for l in lines if l and (not l.startswith('#'))]
self._names = get_nam... | the_stack_v2_python_sparse | libs/base_utils/plain_params_file.py | RichardWeng/Stino | train | 0 |
c704ba7e09d5b635926f3f81fe2620e89f8f5c84 | [
"self.src = src\nself.dst = dst\nself.smtp = None\nself.default_message = 'Your post processsing job has completed successfully'\nself.default_status = 'SUCCEESS'",
"if not msg:\n msg = self.default_message\nif not status:\n status = self.default_status\nself.smtp = smtplib.SMTP('localhost')\nmessage = MIME... | <|body_start_0|>
self.src = src
self.dst = dst
self.smtp = None
self.default_message = 'Your post processsing job has completed successfully'
self.default_status = 'SUCCEESS'
<|end_body_0|>
<|body_start_1|>
if not msg:
msg = self.default_message
if no... | A simple class for sending email | Mailer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mailer:
"""A simple class for sending email"""
def __init__(self, src, dst):
"""Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email address"""
<|body_0|>
def send(self, status=None... | stack_v2_sparse_classes_36k_train_031030 | 1,584 | permissive | [
{
"docstring": "Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email address",
"name": "__init__",
"signature": "def __init__(self, src, dst)"
},
{
"docstring": "Send the email with contents = msg and subje... | 2 | stack_v2_sparse_classes_30k_train_018189 | Implement the Python class `Mailer` described below.
Class description:
A simple class for sending email
Method signatures and docstrings:
- def __init__(self, src, dst): Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email addr... | Implement the Python class `Mailer` described below.
Class description:
A simple class for sending email
Method signatures and docstrings:
- def __init__(self, src, dst): Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email addr... | 84110cab08f7897d1489a6dc925258580a5d2bff | <|skeleton|>
class Mailer:
"""A simple class for sending email"""
def __init__(self, src, dst):
"""Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email address"""
<|body_0|>
def send(self, status=None... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Mailer:
"""A simple class for sending email"""
def __init__(self, src, dst):
"""Initialize the mailer with source = src and destination = dst Parameters: src (str): the source email address dst (str): the destination email address"""
self.src = src
self.dst = dst
self.smtp... | the_stack_v2_python_sparse | processflow/lib/mailer.py | E3SM-Project/processflow | train | 4 |
2619c35a0c04efc0995553f410c5c4bc14682c75 | [
"dp_max = [nums[0]] * len(nums)\ndp_min = [nums[0]] * len(nums)\nfor i in range(1, len(nums)):\n dp_max[i] = max(dp_max[i - 1] * nums[i], dp_min[i - 1] * nums[i], nums[i])\n dp_min[i] = min(dp_max[i - 1] * nums[i], dp_min[i - 1] * nums[i], nums[i])\nreturn max(dp_max)",
"max_now = min_now = max_prodcut = nu... | <|body_start_0|>
dp_max = [nums[0]] * len(nums)
dp_min = [nums[0]] * len(nums)
for i in range(1, len(nums)):
dp_max[i] = max(dp_max[i - 1] * nums[i], dp_min[i - 1] * nums[i], nums[i])
dp_min[i] = min(dp_max[i - 1] * nums[i], dp_min[i - 1] * nums[i], nums[i])
retur... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProduct1(self, nums: List[int]) -> int:
"""dp[i]记录num[i]的最优解。 由于存在负数，会导致最大的变最小的，最小的变最大的。 所以维护两个数组，分别记录最大值和最小值。"""
<|body_0|>
def maxProduct2(self, nums: List[int]) -> int:
"""Kadane算法，类似053题解。 无需记录所有的dp，只需记录前一个最优解即可。"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_36k_train_031031 | 2,021 | no_license | [
{
"docstring": "dp[i]记录num[i]的最优解。 由于存在负数，会导致最大的变最小的，最小的变最大的。 所以维护两个数组，分别记录最大值和最小值。",
"name": "maxProduct1",
"signature": "def maxProduct1(self, nums: List[int]) -> int"
},
{
"docstring": "Kadane算法，类似053题解。 无需记录所有的dp，只需记录前一个最优解即可。",
"name": "maxProduct2",
"signature": "def maxProduct2(se... | 2 | stack_v2_sparse_classes_30k_train_010661 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct1(self, nums: List[int]) -> int: dp[i]记录num[i]的最优解。 由于存在负数，会导致最大的变最小的，最小的变最大的。 所以维护两个数组，分别记录最大值和最小值。
- def maxProduct2(self, nums: List[int]) -> int: Kadane算法，类似053... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct1(self, nums: List[int]) -> int: dp[i]记录num[i]的最优解。 由于存在负数，会导致最大的变最小的，最小的变最大的。 所以维护两个数组，分别记录最大值和最小值。
- def maxProduct2(self, nums: List[int]) -> int: Kadane算法，类似053... | 2bbb1640589aab34f2bc42489283033cc11fb885 | <|skeleton|>
class Solution:
def maxProduct1(self, nums: List[int]) -> int:
"""dp[i]记录num[i]的最优解。 由于存在负数，会导致最大的变最小的，最小的变最大的。 所以维护两个数组，分别记录最大值和最小值。"""
<|body_0|>
def maxProduct2(self, nums: List[int]) -> int:
"""Kadane算法，类似053题解。 无需记录所有的dp，只需记录前一个最优解即可。"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProduct1(self, nums: List[int]) -> int:
"""dp[i]记录num[i]的最优解。 由于存在负数，会导致最大的变最小的，最小的变最大的。 所以维护两个数组，分别记录最大值和最小值。"""
dp_max = [nums[0]] * len(nums)
dp_min = [nums[0]] * len(nums)
for i in range(1, len(nums)):
dp_max[i] = max(dp_max[i - 1] * nums[i], dp... | the_stack_v2_python_sparse | 152_maximum-product-subarray.py | helloocc/algorithm | train | 1 | |
f1f2ab8a2dd361b8dd32ad5e25f9c3c0393a02d9 | [
"if controller is not None:\n if not is_string(controller):\n raise ValueError('Controller name must be a string')\n controller = controller.strip()\n if not controller:\n _logger.warning('Empty controller name given')\n controller = None\n elif ' ' in controller:\n raise Val... | <|body_start_0|>
if controller is not None:
if not is_string(controller):
raise ValueError('Controller name must be a string')
controller = controller.strip()
if not controller:
_logger.warning('Empty controller name given')
con... | @Provides decorator Defines an interface exported by a component. | Provides | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Provides:
"""@Provides decorator Defines an interface exported by a component."""
def __init__(self, specifications, controller=None):
"""Sets up a provided service. A service controller can be defined to enable or disable the service. :param specifications: A list of provided interf... | stack_v2_sparse_classes_36k_train_031032 | 41,418 | permissive | [
{
"docstring": "Sets up a provided service. A service controller can be defined to enable or disable the service. :param specifications: A list of provided interface(s) name(s) (can't be empty) :param controller: Name of the service controller class field (optional) :raise ValueError: If the specifications are ... | 2 | stack_v2_sparse_classes_30k_train_015168 | Implement the Python class `Provides` described below.
Class description:
@Provides decorator Defines an interface exported by a component.
Method signatures and docstrings:
- def __init__(self, specifications, controller=None): Sets up a provided service. A service controller can be defined to enable or disable the ... | Implement the Python class `Provides` described below.
Class description:
@Provides decorator Defines an interface exported by a component.
Method signatures and docstrings:
- def __init__(self, specifications, controller=None): Sets up a provided service. A service controller can be defined to enable or disable the ... | 686556cdde20beba77ae202de9969be46feed5e2 | <|skeleton|>
class Provides:
"""@Provides decorator Defines an interface exported by a component."""
def __init__(self, specifications, controller=None):
"""Sets up a provided service. A service controller can be defined to enable or disable the service. :param specifications: A list of provided interf... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Provides:
"""@Provides decorator Defines an interface exported by a component."""
def __init__(self, specifications, controller=None):
"""Sets up a provided service. A service controller can be defined to enable or disable the service. :param specifications: A list of provided interface(s) name(s... | the_stack_v2_python_sparse | python/src/lib/python/pelix/ipopo/decorators.py | cohorte/cohorte-runtime | train | 3 |
1eed389327923e79e16725c9ccc56787dfe0d9c4 | [
"self.se = set()\nself.di = {}\nfor i in dictionary:\n if i not in self.se:\n self.se.update([i])\n else:\n continue\n if len(i) <= 2:\n key = i\n elif len(i) == 3:\n key = i[0] + '1' + i[-1]\n else:\n key = i[0] + str(len(i) - 2) + i[-1]\n self.di[key] = self.di... | <|body_start_0|>
self.se = set()
self.di = {}
for i in dictionary:
if i not in self.se:
self.se.update([i])
else:
continue
if len(i) <= 2:
key = i
elif len(i) == 3:
key = i[0] + '1' + ... | https://leetcode.com/problems/unique-word-abbreviation/description/ | ValidWordAbbr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
"""https://leetcode.com/problems/unique-word-abbreviation/description/"""
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, i):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_031033 | 1,576 | no_license | [
{
"docstring": ":type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": ":type word: str :rtype: bool",
"name": "isUnique",
"signature": "def isUnique(self, i)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019532 | Implement the Python class `ValidWordAbbr` described below.
Class description:
https://leetcode.com/problems/unique-word-abbreviation/description/
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, i): :type word: str :rtype: bool | Implement the Python class `ValidWordAbbr` described below.
Class description:
https://leetcode.com/problems/unique-word-abbreviation/description/
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, i): :type word: str :rtype: bool
<|skeleton|>
class V... | 30bfafb6a7727c9305b22933b63d9d645182c633 | <|skeleton|>
class ValidWordAbbr:
"""https://leetcode.com/problems/unique-word-abbreviation/description/"""
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, i):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
"""https://leetcode.com/problems/unique-word-abbreviation/description/"""
def __init__(self, dictionary):
""":type dictionary: List[str]"""
self.se = set()
self.di = {}
for i in dictionary:
if i not in self.se:
self.se.update([i])... | the_stack_v2_python_sparse | leetcode/Hash-Table/unique-word-abbreviation.py | iCodeIN/competitive-programming-5 | train | 0 |
4860c833e40934d1965efedb528f15911f820ba4 | [
"self.noise = noise\nif seed != -1:\n numpy.random.seed(seed)",
"if self.noise == 0:\n return\ninputSize = data.size\nflipBits = numpy.random.randint(0, inputSize, self.noise * inputSize)\ndata[flipBits] = numpy.logical_not(data[flipBits])"
] | <|body_start_0|>
self.noise = noise
if seed != -1:
numpy.random.seed(seed)
<|end_body_0|>
<|body_start_1|>
if self.noise == 0:
return
inputSize = data.size
flipBits = numpy.random.randint(0, inputSize, self.noise * inputSize)
data[flipBits] = nump... | This RecordSensor filter adds noise to the input | AddNoise | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddNoise:
"""This RecordSensor filter adds noise to the input"""
def __init__(self, noise=0.0, seed=-1):
"""Construct the filter Parameters: ------------------------------------------------- noise: Amount of noise to add, from 0 to 1.0"""
<|body_0|>
def process(self, enc... | stack_v2_sparse_classes_36k_train_031034 | 1,686 | no_license | [
{
"docstring": "Construct the filter Parameters: ------------------------------------------------- noise: Amount of noise to add, from 0 to 1.0",
"name": "__init__",
"signature": "def __init__(self, noise=0.0, seed=-1)"
},
{
"docstring": "Modify the data in place, adding noise",
"name": "pro... | 2 | stack_v2_sparse_classes_30k_train_019404 | Implement the Python class `AddNoise` described below.
Class description:
This RecordSensor filter adds noise to the input
Method signatures and docstrings:
- def __init__(self, noise=0.0, seed=-1): Construct the filter Parameters: ------------------------------------------------- noise: Amount of noise to add, from ... | Implement the Python class `AddNoise` described below.
Class description:
This RecordSensor filter adds noise to the input
Method signatures and docstrings:
- def __init__(self, noise=0.0, seed=-1): Construct the filter Parameters: ------------------------------------------------- noise: Amount of noise to add, from ... | d494b3041069d377d6a7a9c296a14334f2fa5acc | <|skeleton|>
class AddNoise:
"""This RecordSensor filter adds noise to the input"""
def __init__(self, noise=0.0, seed=-1):
"""Construct the filter Parameters: ------------------------------------------------- noise: Amount of noise to add, from 0 to 1.0"""
<|body_0|>
def process(self, enc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddNoise:
"""This RecordSensor filter adds noise to the input"""
def __init__(self, noise=0.0, seed=-1):
"""Construct the filter Parameters: ------------------------------------------------- noise: Amount of noise to add, from 0 to 1.0"""
self.noise = noise
if seed != -1:
... | the_stack_v2_python_sparse | python/numenta_nupic/nupic-master/src/nupic/regions/RecordSensorFilters/AddNoise.py | LiuFang816/SALSTM_py_data | train | 10 |
a373bbff6e100d62b0a6e31ced7ebe390ecdeb8b | [
"list_dict = []\nlist_date = []\nfor niv1 in data:\n for niv2 in niv1:\n list_dict.append(niv2)\nstring_dict = list_dict[0]\ndictionary = ast.literal_eval(string_dict)\nvalues = dictionary.get('media_likes')\nfor i in range(len(values)):\n list_date.append(values[i][0])\nreturn list_date",
"list_dict... | <|body_start_0|>
list_dict = []
list_date = []
for niv1 in data:
for niv2 in niv1:
list_dict.append(niv2)
string_dict = list_dict[0]
dictionary = ast.literal_eval(string_dict)
values = dictionary.get('media_likes')
for i in range(len(va... | InstagramLikeReader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstagramLikeReader:
def list_date(self, data):
"""From the "raw" data sent this function return a list containing all the date related to a "like": --> data at the right level are put in a list (list of dictionaries) --> from this str(dictionries) ast.literal_eval recognise a dictionary... | stack_v2_sparse_classes_36k_train_031035 | 3,835 | permissive | [
{
"docstring": "From the \"raw\" data sent this function return a list containing all the date related to a \"like\": --> data at the right level are put in a list (list of dictionaries) --> from this str(dictionries) ast.literal_eval recognise a dictionary --> values related to 'media_likes' (ie the one of the... | 3 | null | Implement the Python class `InstagramLikeReader` described below.
Class description:
Implement the InstagramLikeReader class.
Method signatures and docstrings:
- def list_date(self, data): From the "raw" data sent this function return a list containing all the date related to a "like": --> data at the right level are... | Implement the Python class `InstagramLikeReader` described below.
Class description:
Implement the InstagramLikeReader class.
Method signatures and docstrings:
- def list_date(self, data): From the "raw" data sent this function return a list containing all the date related to a "like": --> data at the right level are... | 179dd4f04713026656c0849916166fd1ed0d6f31 | <|skeleton|>
class InstagramLikeReader:
def list_date(self, data):
"""From the "raw" data sent this function return a list containing all the date related to a "like": --> data at the right level are put in a list (list of dictionaries) --> from this str(dictionries) ast.literal_eval recognise a dictionary... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstagramLikeReader:
def list_date(self, data):
"""From the "raw" data sent this function return a list containing all the date related to a "like": --> data at the right level are put in a list (list of dictionaries) --> from this str(dictionries) ast.literal_eval recognise a dictionary --> values re... | the_stack_v2_python_sparse | Package/instagram_sub_readers/like.py | AdrienCarthoblaz/Master-Thesis | train | 2 | |
643419eba6bcc4560189b253d6b9f5ba348cefc0 | [
"Weight.__init__(self, *args, **kwargs)\nself._ranges = ranges if ranges is not None else []\nself._initial = initial",
"self.log.info('Creating weights for spectrum from given ranges...')\nweights = np.zeros(len(spectrum)) + self._initial\nfor start, end, weight in self._ranges:\n w = (spectrum.wave >= start)... | <|body_start_0|>
Weight.__init__(self, *args, **kwargs)
self._ranges = ranges if ranges is not None else []
self._initial = initial
<|end_body_0|>
<|body_start_1|>
self.log.info('Creating weights for spectrum from given ranges...')
weights = np.zeros(len(spectrum)) + self._initi... | Creates a weights array from given ranges. This class, when called, creates a weights array from the given wavelength ranges. | WeightRanges | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeightRanges:
"""Creates a weights array from given ranges. This class, when called, creates a weights array from the given wavelength ranges."""
def __init__(self, ranges: List[Tuple[float, float, float]]=None, initial: float=1.0, *args, **kwargs):
"""Initializes a new weight. Args:... | stack_v2_sparse_classes_36k_train_031036 | 1,626 | permissive | [
{
"docstring": "Initializes a new weight. Args: ranges: List of tuples of (wave start, wave end, weight). initial: Initial value for whole array.",
"name": "__init__",
"signature": "def __init__(self, ranges: List[Tuple[float, float, float]]=None, initial: float=1.0, *args, **kwargs)"
},
{
"docs... | 2 | null | Implement the Python class `WeightRanges` described below.
Class description:
Creates a weights array from given ranges. This class, when called, creates a weights array from the given wavelength ranges.
Method signatures and docstrings:
- def __init__(self, ranges: List[Tuple[float, float, float]]=None, initial: flo... | Implement the Python class `WeightRanges` described below.
Class description:
Creates a weights array from given ranges. This class, when called, creates a weights array from the given wavelength ranges.
Method signatures and docstrings:
- def __init__(self, ranges: List[Tuple[float, float, float]]=None, initial: flo... | 648eb1758e3744d9e3d6669edc4a0c4753559f17 | <|skeleton|>
class WeightRanges:
"""Creates a weights array from given ranges. This class, when called, creates a weights array from the given wavelength ranges."""
def __init__(self, ranges: List[Tuple[float, float, float]]=None, initial: float=1.0, *args, **kwargs):
"""Initializes a new weight. Args:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WeightRanges:
"""Creates a weights array from given ranges. This class, when called, creates a weights array from the given wavelength ranges."""
def __init__(self, ranges: List[Tuple[float, float, float]]=None, initial: float=1.0, *args, **kwargs):
"""Initializes a new weight. Args: ranges: List... | the_stack_v2_python_sparse | spexxy/weight/ranges.py | thusser/spexxy | train | 4 |
49b57c1a8342f9fdd5c1f14e35b13225dbde0b55 | [
"if not isinstance(record_id, int):\n raise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: record_id EXPECTED TYPE: int', None, None)\nif not isinstance(module_api_name, str):\n raise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: module_api_name EXPECTED TYPE: str', None, None)\nself.__record_id = record_id\ns... | <|body_start_0|>
if not isinstance(record_id, int):
raise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: record_id EXPECTED TYPE: int', None, None)
if not isinstance(module_api_name, str):
raise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: module_api_name EXPECTED TYPE: str', Non... | BluePrintOperations | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BluePrintOperations:
def __init__(self, record_id, module_api_name):
"""Creates an instance of BluePrintOperations with the given parameters Parameters: record_id (int) : An int representing the record_id module_api_name (string) : A string representing the module_api_name"""
<|b... | stack_v2_sparse_classes_36k_train_031037 | 3,177 | no_license | [
{
"docstring": "Creates an instance of BluePrintOperations with the given parameters Parameters: record_id (int) : An int representing the record_id module_api_name (string) : A string representing the module_api_name",
"name": "__init__",
"signature": "def __init__(self, record_id, module_api_name)"
... | 3 | null | Implement the Python class `BluePrintOperations` described below.
Class description:
Implement the BluePrintOperations class.
Method signatures and docstrings:
- def __init__(self, record_id, module_api_name): Creates an instance of BluePrintOperations with the given parameters Parameters: record_id (int) : An int re... | Implement the Python class `BluePrintOperations` described below.
Class description:
Implement the BluePrintOperations class.
Method signatures and docstrings:
- def __init__(self, record_id, module_api_name): Creates an instance of BluePrintOperations with the given parameters Parameters: record_id (int) : An int re... | bba7328de07b137d2cb6e2aac31b8f57e0803026 | <|skeleton|>
class BluePrintOperations:
def __init__(self, record_id, module_api_name):
"""Creates an instance of BluePrintOperations with the given parameters Parameters: record_id (int) : An int representing the record_id module_api_name (string) : A string representing the module_api_name"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BluePrintOperations:
def __init__(self, record_id, module_api_name):
"""Creates an instance of BluePrintOperations with the given parameters Parameters: record_id (int) : An int representing the record_id module_api_name (string) : A string representing the module_api_name"""
if not isinstance... | the_stack_v2_python_sparse | zcrmsdk/src/com/zoho/crm/api/blue_print/blue_print_operations.py | L1nuxFNC/zohocrm-python-sdk | train | 0 | |
399e33108e8183e8a5a282f9388dd0dc383ea088 | [
"super(PeriodicUpsample1D, self).__init__()\nself.in_channel = in_channel\nself.out_channel = out_channel\nself.conv1d = nn.Conv1d(in_channel, out_channel, 3, 1, 0)",
"x = torch.stack((torch.zeros_like(x), x), dim=-1).view(x.shape[0], x.shape[1], -1)\nx = torch.cat((x[..., -1:], x, x[..., :1]), dim=-1)\nx = self.... | <|body_start_0|>
super(PeriodicUpsample1D, self).__init__()
self.in_channel = in_channel
self.out_channel = out_channel
self.conv1d = nn.Conv1d(in_channel, out_channel, 3, 1, 0)
<|end_body_0|>
<|body_start_1|>
x = torch.stack((torch.zeros_like(x), x), dim=-1).view(x.shape[0], x.... | PeriodicUpsample1D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PeriodicUpsample1D:
def __init__(self, in_channel, out_channel):
""":param in_channel: input planes :param out_channel: output planes"""
<|body_0|>
def forward(self, x):
""":param x: tensor of shape (N, C, L) :return tensor of shape (N, C, 2L)"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_031038 | 7,677 | no_license | [
{
"docstring": ":param in_channel: input planes :param out_channel: output planes",
"name": "__init__",
"signature": "def __init__(self, in_channel, out_channel)"
},
{
"docstring": ":param x: tensor of shape (N, C, L) :return tensor of shape (N, C, 2L)",
"name": "forward",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_018815 | Implement the Python class `PeriodicUpsample1D` described below.
Class description:
Implement the PeriodicUpsample1D class.
Method signatures and docstrings:
- def __init__(self, in_channel, out_channel): :param in_channel: input planes :param out_channel: output planes
- def forward(self, x): :param x: tensor of sha... | Implement the Python class `PeriodicUpsample1D` described below.
Class description:
Implement the PeriodicUpsample1D class.
Method signatures and docstrings:
- def __init__(self, in_channel, out_channel): :param in_channel: input planes :param out_channel: output planes
- def forward(self, x): :param x: tensor of sha... | 666bbecd9f9b2c9bebaf82deab3ccb8586d60dca | <|skeleton|>
class PeriodicUpsample1D:
def __init__(self, in_channel, out_channel):
""":param in_channel: input planes :param out_channel: output planes"""
<|body_0|>
def forward(self, x):
""":param x: tensor of shape (N, C, L) :return tensor of shape (N, C, 2L)"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PeriodicUpsample1D:
def __init__(self, in_channel, out_channel):
""":param in_channel: input planes :param out_channel: output planes"""
super(PeriodicUpsample1D, self).__init__()
self.in_channel = in_channel
self.out_channel = out_channel
self.conv1d = nn.Conv1d(in_cha... | the_stack_v2_python_sparse | experiments/exp3_segmentation/model.py | maxjiang93/DDSL | train | 55 | |
a9beb82e56f0b8ee7a2bf550c126d906789ddf08 | [
"self.X_train = None\nself.y_train = None\nself.trees = []\nself.N = N\nself.M = M\nself.F = F",
"header = ['att' + str(i) for i in range(len(X_train[0]))]\nattribute_domains = {}\nfor i, val in enumerate(header):\n attribute_domains[val] = myutils.unique_index(X_train, i)\nself.X_train = X_train\nself.y_train... | <|body_start_0|>
self.X_train = None
self.y_train = None
self.trees = []
self.N = N
self.M = M
self.F = F
<|end_body_0|>
<|body_start_1|>
header = ['att' + str(i) for i in range(len(X_train[0]))]
attribute_domains = {}
for i, val in enumerate(head... | Represents a decision tree classifier. Attributes: X_train(list of list of obj): The list of training instances (samples). The shape of X_train is (n_train_samples, n_features) y_train(list of obj): The target y values (parallel to X_train). The shape of y_train is n_samples tree(nested list): The extracted tree model.... | MyRandomForestClassifier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyRandomForestClassifier:
"""Represents a decision tree classifier. Attributes: X_train(list of list of obj): The list of training instances (samples). The shape of X_train is (n_train_samples, n_features) y_train(list of obj): The target y values (parallel to X_train). The shape of y_train is n_... | stack_v2_sparse_classes_36k_train_031039 | 10,235 | no_license | [
{
"docstring": "Initializer for MyDecisionTreeClassifier.",
"name": "__init__",
"signature": "def __init__(self, F=2, N=4, M=3)"
},
{
"docstring": "Fits a decision tree classifier to X_train and y_train using the TDIDT (top down induction of decision tree) algorithm. Args: X_train(list of list o... | 3 | stack_v2_sparse_classes_30k_test_000433 | Implement the Python class `MyRandomForestClassifier` described below.
Class description:
Represents a decision tree classifier. Attributes: X_train(list of list of obj): The list of training instances (samples). The shape of X_train is (n_train_samples, n_features) y_train(list of obj): The target y values (parallel ... | Implement the Python class `MyRandomForestClassifier` described below.
Class description:
Represents a decision tree classifier. Attributes: X_train(list of list of obj): The list of training instances (samples). The shape of X_train is (n_train_samples, n_features) y_train(list of obj): The target y values (parallel ... | e1c9bd77026dadb993361e79514a295edd5775f3 | <|skeleton|>
class MyRandomForestClassifier:
"""Represents a decision tree classifier. Attributes: X_train(list of list of obj): The list of training instances (samples). The shape of X_train is (n_train_samples, n_features) y_train(list of obj): The target y values (parallel to X_train). The shape of y_train is n_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyRandomForestClassifier:
"""Represents a decision tree classifier. Attributes: X_train(list of list of obj): The list of training instances (samples). The shape of X_train is (n_train_samples, n_features) y_train(list of obj): The target y values (parallel to X_train). The shape of y_train is n_samples tree(... | the_stack_v2_python_sparse | mysklearn/myclassifiers.py | CarterKekoa/SpotifyRecommendationApp | train | 1 |
d382542dc331a95aa328f5919b4186324ec647a0 | [
"Package.__init__(self, model, extension, 'MPBAS', unitnumber)\nnrow, ncol, nlay, nper = self.parent.mf.nrow_ncol_nlay_nper\nself.parent.mf.get_name_file_entries()\nself.heading1 = '# MPBAS for Modpath, generated by hataripy.'\nself.heading2 = '#'\nself.hnoflo = hnoflo\nself.hdry = hdry\nself.def_face_ct = def_face... | <|body_start_0|>
Package.__init__(self, model, extension, 'MPBAS', unitnumber)
nrow, ncol, nlay, nper = self.parent.mf.nrow_ncol_nlay_nper
self.parent.mf.get_name_file_entries()
self.heading1 = '# MPBAS for Modpath, generated by hataripy.'
self.heading2 = '#'
self.hnoflo ... | MODPATH Basic Package Class. Parameters ---------- model : model object The model object (of type :class:`hataripy.modpath.mp.Modpath`) to which this package will be added. hnoflo : float Head value assigned to inactive cells (default is -9999.). hdry : float Head value assigned to dry cells (default is -8888.). def_fa... | ModpathBas | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModpathBas:
"""MODPATH Basic Package Class. Parameters ---------- model : model object The model object (of type :class:`hataripy.modpath.mp.Modpath`) to which this package will be added. hnoflo : float Head value assigned to inactive cells (default is -9999.). hdry : float Head value assigned to... | stack_v2_sparse_classes_36k_train_031040 | 5,451 | permissive | [
{
"docstring": "Package constructor.",
"name": "__init__",
"signature": "def __init__(self, model, hnoflo=-9999.0, hdry=-8888.0, def_face_ct=0, bud_label=None, def_iface=None, laytyp=0, ibound=1, prsity=0.3, prsityCB=0.3, extension='mpbas', unitnumber=86)"
},
{
"docstring": "Write the package fi... | 2 | null | Implement the Python class `ModpathBas` described below.
Class description:
MODPATH Basic Package Class. Parameters ---------- model : model object The model object (of type :class:`hataripy.modpath.mp.Modpath`) to which this package will be added. hnoflo : float Head value assigned to inactive cells (default is -9999... | Implement the Python class `ModpathBas` described below.
Class description:
MODPATH Basic Package Class. Parameters ---------- model : model object The model object (of type :class:`hataripy.modpath.mp.Modpath`) to which this package will be added. hnoflo : float Head value assigned to inactive cells (default is -9999... | 7db7869f34b875c9f76d42b7a4801b0c23738448 | <|skeleton|>
class ModpathBas:
"""MODPATH Basic Package Class. Parameters ---------- model : model object The model object (of type :class:`hataripy.modpath.mp.Modpath`) to which this package will be added. hnoflo : float Head value assigned to inactive cells (default is -9999.). hdry : float Head value assigned to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModpathBas:
"""MODPATH Basic Package Class. Parameters ---------- model : model object The model object (of type :class:`hataripy.modpath.mp.Modpath`) to which this package will be added. hnoflo : float Head value assigned to inactive cells (default is -9999.). hdry : float Head value assigned to dry cells (d... | the_stack_v2_python_sparse | hataripy/modpath/mpbas.py | hatarilabs/hataripy | train | 4 |
3ffad6484813466dce3cc5e9f1615a99324427c4 | [
"super().__init__(hass, _LOGGER, name=DOMAIN, update_interval=TIME_BETWEEN_UPDATES)\nself._train_api = TrafikverketTrain(async_get_clientsession(hass), entry.data[CONF_API_KEY])\nself.from_station: StationInfo = from_station\nself.to_station: StationInfo = to_station\nself._time: time | None = dt_util.parse_time(en... | <|body_start_0|>
super().__init__(hass, _LOGGER, name=DOMAIN, update_interval=TIME_BETWEEN_UPDATES)
self._train_api = TrafikverketTrain(async_get_clientsession(hass), entry.data[CONF_API_KEY])
self.from_station: StationInfo = from_station
self.to_station: StationInfo = to_station
... | A Trafikverket Data Update Coordinator. | TVDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TVDataUpdateCoordinator:
"""A Trafikverket Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry, to_station: StationInfo, from_station: StationInfo, filter_product: str | None) -> None:
"""Initialize the Trafikverket coordinator."""
<|body_0|... | stack_v2_sparse_classes_36k_train_031041 | 4,898 | permissive | [
{
"docstring": "Initialize the Trafikverket coordinator.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, entry: ConfigEntry, to_station: StationInfo, from_station: StationInfo, filter_product: str | None) -> None"
},
{
"docstring": "Fetch data from Trafikverket.",
... | 2 | null | Implement the Python class `TVDataUpdateCoordinator` described below.
Class description:
A Trafikverket Data Update Coordinator.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, entry: ConfigEntry, to_station: StationInfo, from_station: StationInfo, filter_product: str | None) -> None: Init... | Implement the Python class `TVDataUpdateCoordinator` described below.
Class description:
A Trafikverket Data Update Coordinator.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, entry: ConfigEntry, to_station: StationInfo, from_station: StationInfo, filter_product: str | None) -> None: Init... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class TVDataUpdateCoordinator:
"""A Trafikverket Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry, to_station: StationInfo, from_station: StationInfo, filter_product: str | None) -> None:
"""Initialize the Trafikverket coordinator."""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TVDataUpdateCoordinator:
"""A Trafikverket Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, entry: ConfigEntry, to_station: StationInfo, from_station: StationInfo, filter_product: str | None) -> None:
"""Initialize the Trafikverket coordinator."""
super().__init__(hass,... | the_stack_v2_python_sparse | homeassistant/components/trafikverket_train/coordinator.py | home-assistant/core | train | 35,501 |
67dd26601b07be3466c1b76aeb13a9ace7633425 | [
"super(Export, self).__init__(config=config, args=args)\nself.host = None\nself.port = None\nself.user = None\nself.password = None\nself.db = None\nself.prefix = None\nself.tags = None\nself.export_enable = self.load_conf()\nif not self.export_enable:\n sys.exit(2)\nself.client = self.init()",
"if self.config... | <|body_start_0|>
super(Export, self).__init__(config=config, args=args)
self.host = None
self.port = None
self.user = None
self.password = None
self.db = None
self.prefix = None
self.tags = None
self.export_enable = self.load_conf()
if not ... | This class manages the InfluxDB export module. | Export | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Export:
"""This class manages the InfluxDB export module."""
def __init__(self, config=None, args=None):
"""Init the InfluxDB export IF."""
<|body_0|>
def load_conf(self, section='influxdb'):
"""Load the InfluxDb configuration in the Glances configuration file.""... | stack_v2_sparse_classes_36k_train_031042 | 5,114 | no_license | [
{
"docstring": "Init the InfluxDB export IF.",
"name": "__init__",
"signature": "def __init__(self, config=None, args=None)"
},
{
"docstring": "Load the InfluxDb configuration in the Glances configuration file.",
"name": "load_conf",
"signature": "def load_conf(self, section='influxdb')"... | 4 | stack_v2_sparse_classes_30k_train_002552 | Implement the Python class `Export` described below.
Class description:
This class manages the InfluxDB export module.
Method signatures and docstrings:
- def __init__(self, config=None, args=None): Init the InfluxDB export IF.
- def load_conf(self, section='influxdb'): Load the InfluxDb configuration in the Glances ... | Implement the Python class `Export` described below.
Class description:
This class manages the InfluxDB export module.
Method signatures and docstrings:
- def __init__(self, config=None, args=None): Init the InfluxDB export IF.
- def load_conf(self, section='influxdb'): Load the InfluxDb configuration in the Glances ... | babafa44bbf8234b9d579282de18e382e5499a9b | <|skeleton|>
class Export:
"""This class manages the InfluxDB export module."""
def __init__(self, config=None, args=None):
"""Init the InfluxDB export IF."""
<|body_0|>
def load_conf(self, section='influxdb'):
"""Load the InfluxDb configuration in the Glances configuration file.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Export:
"""This class manages the InfluxDB export module."""
def __init__(self, config=None, args=None):
"""Init the InfluxDB export IF."""
super(Export, self).__init__(config=config, args=args)
self.host = None
self.port = None
self.user = None
self.passwo... | the_stack_v2_python_sparse | gl/exports/glances_influxdb.py | mondo0/testgl | train | 0 |
ad5481e9b26a8ea9f9d56a19ed369ce6fad3ce59 | [
"user = request.user\ncheck_user_status(user)\nuser_id = user.id\nrestaurant = PendingRestaurant.get_by_owner(user_id)\nrest_id = restaurant._id\ndishes = PendingFood.get_by_restaurant(rest_id)\nresponse = {'Dishes': models_to_json(dishes)}\nreturn JsonResponse(response)",
"user = request.user\ncheck_user_status(... | <|body_start_0|>
user = request.user
check_user_status(user)
user_id = user.id
restaurant = PendingRestaurant.get_by_owner(user_id)
rest_id = restaurant._id
dishes = PendingFood.get_by_restaurant(rest_id)
response = {'Dishes': models_to_json(dishes)}
retur... | pending dish view | PendingDishView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PendingDishView:
"""pending dish view"""
def get(self, request):
"""Retrieve all dishes from restaurant owned by user"""
<|body_0|>
def post(self, request):
"""Insert dish into database"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = requ... | stack_v2_sparse_classes_36k_train_031043 | 19,356 | no_license | [
{
"docstring": "Retrieve all dishes from restaurant owned by user",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Insert dish into database",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000252 | Implement the Python class `PendingDishView` described below.
Class description:
pending dish view
Method signatures and docstrings:
- def get(self, request): Retrieve all dishes from restaurant owned by user
- def post(self, request): Insert dish into database | Implement the Python class `PendingDishView` described below.
Class description:
pending dish view
Method signatures and docstrings:
- def get(self, request): Retrieve all dishes from restaurant owned by user
- def post(self, request): Insert dish into database
<|skeleton|>
class PendingDishView:
"""pending dish... | 2707062c9a9a8bb4baca955e8a60ba08cc9f8953 | <|skeleton|>
class PendingDishView:
"""pending dish view"""
def get(self, request):
"""Retrieve all dishes from restaurant owned by user"""
<|body_0|>
def post(self, request):
"""Insert dish into database"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PendingDishView:
"""pending dish view"""
def get(self, request):
"""Retrieve all dishes from restaurant owned by user"""
user = request.user
check_user_status(user)
user_id = user.id
restaurant = PendingRestaurant.get_by_owner(user_id)
rest_id = restaurant.... | the_stack_v2_python_sparse | backend/restaurant/views.py | MochiTarts/Find-Dining-The-Bridge | train | 1 |
237301f707617ec931ab8dc4acd3b066752d3196 | [
"digits = digits[::-1]\nprint(digits)\nl = len(digits)\np = l - 1\nf = False\nwhile p >= 0:\n if digits[p] != 9:\n digits[p] += 1\n if f == True or p == l - 1:\n return digits\n else:\n f = True\n digits[p] = 0\n p -= 1\n if p == -1:\n digits.ins... | <|body_start_0|>
digits = digits[::-1]
print(digits)
l = len(digits)
p = l - 1
f = False
while p >= 0:
if digits[p] != 9:
digits[p] += 1
if f == True or p == l - 1:
return digits
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def plusOne(self, digits):
""":type digits: List[int] :rtype: List[int] 正序计算"""
<|body_0|>
def plusOne2(self, digits):
""":type digits: List[int] :rtype: List[int] 反转数组，从左往右计算 反转后第一位+1小于10，则+1即可退出循环 反转后第一位+1=10，则当前位=0，继续循环；最后一位时直接=0且最后增加一位1"""
<|bod... | stack_v2_sparse_classes_36k_train_031044 | 2,450 | no_license | [
{
"docstring": ":type digits: List[int] :rtype: List[int] 正序计算",
"name": "plusOne",
"signature": "def plusOne(self, digits)"
},
{
"docstring": ":type digits: List[int] :rtype: List[int] 反转数组，从左往右计算 反转后第一位+1小于10，则+1即可退出循环 反转后第一位+1=10，则当前位=0，继续循环；最后一位时直接=0且最后增加一位1",
"name": "plusOne2",
"si... | 3 | stack_v2_sparse_classes_30k_val_000023 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne(self, digits): :type digits: List[int] :rtype: List[int] 正序计算
- def plusOne2(self, digits): :type digits: List[int] :rtype: List[int] 反转数组，从左往右计算 反转后第一位+1小于10，则+1即可退出... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def plusOne(self, digits): :type digits: List[int] :rtype: List[int] 正序计算
- def plusOne2(self, digits): :type digits: List[int] :rtype: List[int] 反转数组，从左往右计算 反转后第一位+1小于10，则+1即可退出... | b0f498ebe84e46b7e17e94759dd462891dcc8f85 | <|skeleton|>
class Solution:
def plusOne(self, digits):
""":type digits: List[int] :rtype: List[int] 正序计算"""
<|body_0|>
def plusOne2(self, digits):
""":type digits: List[int] :rtype: List[int] 反转数组，从左往右计算 反转后第一位+1小于10，则+1即可退出循环 反转后第一位+1=10，则当前位=0，继续循环；最后一位时直接=0且最后增加一位1"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def plusOne(self, digits):
""":type digits: List[int] :rtype: List[int] 正序计算"""
digits = digits[::-1]
print(digits)
l = len(digits)
p = l - 1
f = False
while p >= 0:
if digits[p] != 9:
digits[p] += 1
... | the_stack_v2_python_sparse | 初级算法/array_7.py | wulinlw/leetcode_cn | train | 0 | |
4f53eebf489d79c775025a3b2a251a5d34039a3a | [
"basic_url = 'https://math.ly/api/v1/'\nbasic_url += area + '/' + topic + '.json'\nif difficulty:\n basic_url += '?difficulty=' + difficulty\nres = requests.get(basic_url).json()\nchoices = [re.sub('</math>, <math>', ', ', choice) for choice in res['choices']]\nchoices = [i.replace('<math>', '<math xmlns=\"http:... | <|body_start_0|>
basic_url = 'https://math.ly/api/v1/'
basic_url += area + '/' + topic + '.json'
if difficulty:
basic_url += '?difficulty=' + difficulty
res = requests.get(basic_url).json()
choices = [re.sub('</math>, <math>', ', ', choice) for choice in res['choices'... | A class that represents a Math.ly problem receiver. | Receiver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Receiver:
"""A class that represents a Math.ly problem receiver."""
def get_random_problem(self, area, topic, difficulty=None):
"""(str, str, str) -> Problem :param area: area of the problem(e.g. 'algebra') :param topic: topic of the problem (e.g. 'linear-equations') :param difficult... | stack_v2_sparse_classes_36k_train_031045 | 9,855 | no_license | [
{
"docstring": "(str, str, str) -> Problem :param area: area of the problem(e.g. 'algebra') :param topic: topic of the problem (e.g. 'linear-equations') :param difficulty: difficulty(beginner, intermediate, advanced) (Default value = None) :returns: a Problem object of current problem",
"name": "get_random_... | 3 | stack_v2_sparse_classes_30k_train_005671 | Implement the Python class `Receiver` described below.
Class description:
A class that represents a Math.ly problem receiver.
Method signatures and docstrings:
- def get_random_problem(self, area, topic, difficulty=None): (str, str, str) -> Problem :param area: area of the problem(e.g. 'algebra') :param topic: topic ... | Implement the Python class `Receiver` described below.
Class description:
A class that represents a Math.ly problem receiver.
Method signatures and docstrings:
- def get_random_problem(self, area, topic, difficulty=None): (str, str, str) -> Problem :param area: area of the problem(e.g. 'algebra') :param topic: topic ... | 43ea67af67bd9ceb9a2dd0ce7cf4ee342c3e13a2 | <|skeleton|>
class Receiver:
"""A class that represents a Math.ly problem receiver."""
def get_random_problem(self, area, topic, difficulty=None):
"""(str, str, str) -> Problem :param area: area of the problem(e.g. 'algebra') :param topic: topic of the problem (e.g. 'linear-equations') :param difficult... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Receiver:
"""A class that represents a Math.ly problem receiver."""
def get_random_problem(self, area, topic, difficulty=None):
"""(str, str, str) -> Problem :param area: area of the problem(e.g. 'algebra') :param topic: topic of the problem (e.g. 'linear-equations') :param difficulty: difficulty... | the_stack_v2_python_sparse | flask-app/my_modules/classes.py | Centurion256/ProjectLogos | train | 1 |
d43b7ebba3c8d859469b2168efecb696a855bdf9 | [
"if not prices:\n return 0\nn = len(prices)\ndp, min_buy_stock_value = ([0] * n, prices[0])\nfor i in range(1, n):\n min_buy_stock_value = min(prices[i], min_buy_stock_value)\n dp[i] = max(prices[i] - min_buy_stock_value, dp[i - 1])\nreturn dp[n - 1]",
"if not prices:\n return 0\nn, min_buy_stock_valu... | <|body_start_0|>
if not prices:
return 0
n = len(prices)
dp, min_buy_stock_value = ([0] * n, prices[0])
for i in range(1, n):
min_buy_stock_value = min(prices[i], min_buy_stock_value)
dp[i] = max(prices[i] - min_buy_stock_value, dp[i - 1])
retu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices: list) -> int:
"""动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])"""
<|body_0|>
def maxProfit_1(self, prices: list) -> int:
"""迭代"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_031046 | 3,964 | no_license | [
{
"docstring": "动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])",
"name": "maxProfit",
"signature": "def maxProfit(self, prices: list) -> int"
},
{
"docstring": "迭代",
"name": "maxProfit_1",
"signature": "def maxProfit_1... | 4 | stack_v2_sparse_classes_30k_train_007738 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: list) -> int: 动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])
- def maxProfit_1(s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices: list) -> int: 动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])
- def maxProfit_1(s... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def maxProfit(self, prices: list) -> int:
"""动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])"""
<|body_0|>
def maxProfit_1(self, prices: list) -> int:
"""迭代"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices: list) -> int:
"""动态规划 先找到最小的买入价格，然后和当前价格相减，得出利润，再和之前的利润比较，得出最大利润 dp[i]就表示第i天的利润 dp[i] = max(prices[i] - min_buy_stock_value, dp[i-1])"""
if not prices:
return 0
n = len(prices)
dp, min_buy_stock_value = ([0] * n, prices[0])
... | the_stack_v2_python_sparse | algorithm/leetcode/dp/08-买卖股票的最佳时机.py | lxconfig/UbuntuCode_bak | train | 0 | |
d7c7e62165a52178590ade734048b8f292472f7f | [
"assert model_name in ['Resnet50_FPN', 'MobileNetV3_largeFPN', 'MobileNetV3_largeFPN_320', 'MaskRCNN', 'YOLOv5x'], 'Error: model not found'\nweights_path += 'best_' + model_name + '.pt'\nself.model = get_object_detection_model(num_classes=2, mtype=model_name, weights_path=weights_path, device=torch.device('cpu'))\n... | <|body_start_0|>
assert model_name in ['Resnet50_FPN', 'MobileNetV3_largeFPN', 'MobileNetV3_largeFPN_320', 'MaskRCNN', 'YOLOv5x'], 'Error: model not found'
weights_path += 'best_' + model_name + '.pt'
self.model = get_object_detection_model(num_classes=2, mtype=model_name, weights_path=weights_p... | ObjectPredictor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObjectPredictor:
def __init__(self, model_name='MobileNetV3_largeFPN', weights_path='/home/phil/Documents/Projects/CV_SLAM_project/cv_lib/models/'):
"""Constructor :param model_name: name of the pre trained model to load :param weights_path: from where to load the trained weights"""
... | stack_v2_sparse_classes_36k_train_031047 | 11,558 | no_license | [
{
"docstring": "Constructor :param model_name: name of the pre trained model to load :param weights_path: from where to load the trained weights",
"name": "__init__",
"signature": "def __init__(self, model_name='MobileNetV3_largeFPN', weights_path='/home/phil/Documents/Projects/CV_SLAM_project/cv_lib/mo... | 2 | stack_v2_sparse_classes_30k_val_001056 | Implement the Python class `ObjectPredictor` described below.
Class description:
Implement the ObjectPredictor class.
Method signatures and docstrings:
- def __init__(self, model_name='MobileNetV3_largeFPN', weights_path='/home/phil/Documents/Projects/CV_SLAM_project/cv_lib/models/'): Constructor :param model_name: n... | Implement the Python class `ObjectPredictor` described below.
Class description:
Implement the ObjectPredictor class.
Method signatures and docstrings:
- def __init__(self, model_name='MobileNetV3_largeFPN', weights_path='/home/phil/Documents/Projects/CV_SLAM_project/cv_lib/models/'): Constructor :param model_name: n... | 7101da99d0744405b9faa0ef6c9c98f4e3adf148 | <|skeleton|>
class ObjectPredictor:
def __init__(self, model_name='MobileNetV3_largeFPN', weights_path='/home/phil/Documents/Projects/CV_SLAM_project/cv_lib/models/'):
"""Constructor :param model_name: name of the pre trained model to load :param weights_path: from where to load the trained weights"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObjectPredictor:
def __init__(self, model_name='MobileNetV3_largeFPN', weights_path='/home/phil/Documents/Projects/CV_SLAM_project/cv_lib/models/'):
"""Constructor :param model_name: name of the pre trained model to load :param weights_path: from where to load the trained weights"""
assert mod... | the_stack_v2_python_sparse | cv_lib/src/object_prediction.py | PhiCtl/Object-pose-estimation | train | 0 | |
2b895cf4392273b689ddafc6f26c5ab11f737a5a | [
"super(CustomSmoothL1Loss, self).__init__()\nself.beta = beta\nself.reduction = reduction\nself.loss_weight = loss_weight",
"reduction = reduction_override if reduction_override else self.reduction\nif target.numel() > 0:\n loss_bbox = self.loss_weight * smooth_l1_loss(pred, target, weight, beta=self.beta, red... | <|body_start_0|>
super(CustomSmoothL1Loss, self).__init__()
self.beta = beta
self.reduction = reduction
self.loss_weight = loss_weight
<|end_body_0|>
<|body_start_1|>
reduction = reduction_override if reduction_override else self.reduction
if target.numel() > 0:
... | Smooth L1 Loss. | CustomSmoothL1Loss | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomSmoothL1Loss:
"""Smooth L1 Loss."""
def __init__(self, beta=1.0, reduction='mean', loss_weight=1.0):
"""Init smooth l1 loss."""
<|body_0|>
def forward(self, pred, target, weight=None, avg_factor=None, reduction_override=None, **kwargs):
"""Forward compute. ... | stack_v2_sparse_classes_36k_train_031048 | 13,829 | permissive | [
{
"docstring": "Init smooth l1 loss.",
"name": "__init__",
"signature": "def __init__(self, beta=1.0, reduction='mean', loss_weight=1.0)"
},
{
"docstring": "Forward compute. :param pred: predict :param target: target :param weight: weight :param avg_factor: avg factor :param reduction_override: ... | 2 | stack_v2_sparse_classes_30k_train_017843 | Implement the Python class `CustomSmoothL1Loss` described below.
Class description:
Smooth L1 Loss.
Method signatures and docstrings:
- def __init__(self, beta=1.0, reduction='mean', loss_weight=1.0): Init smooth l1 loss.
- def forward(self, pred, target, weight=None, avg_factor=None, reduction_override=None, **kwarg... | Implement the Python class `CustomSmoothL1Loss` described below.
Class description:
Smooth L1 Loss.
Method signatures and docstrings:
- def __init__(self, beta=1.0, reduction='mean', loss_weight=1.0): Init smooth l1 loss.
- def forward(self, pred, target, weight=None, avg_factor=None, reduction_override=None, **kwarg... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class CustomSmoothL1Loss:
"""Smooth L1 Loss."""
def __init__(self, beta=1.0, reduction='mean', loss_weight=1.0):
"""Init smooth l1 loss."""
<|body_0|>
def forward(self, pred, target, weight=None, avg_factor=None, reduction_override=None, **kwargs):
"""Forward compute. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomSmoothL1Loss:
"""Smooth L1 Loss."""
def __init__(self, beta=1.0, reduction='mean', loss_weight=1.0):
"""Init smooth l1 loss."""
super(CustomSmoothL1Loss, self).__init__()
self.beta = beta
self.reduction = reduction
self.loss_weight = loss_weight
def forw... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/operator/rpn.py | Huawei-Ascend/modelzoo | train | 1 |
9abace3e504e8347a1a27059c908a1c3d4ee3e4f | [
"ReporterFactory.__init__(self, reporter_type=reporter_type)\nPersistenceExecutor.__init__(self)\nself.interval = interval\nself.reporter_args = reporter_args\nself.log = ''\nself.send_report = self.create_reporter()\nself.persistent = persistent",
"self.send_report(host='smtp.gmail.com', port=587, email=self.rep... | <|body_start_0|>
ReporterFactory.__init__(self, reporter_type=reporter_type)
PersistenceExecutor.__init__(self)
self.interval = interval
self.reporter_args = reporter_args
self.log = ''
self.send_report = self.create_reporter()
self.persistent = persistent
<|end_b... | Implements a keylogger that sends reports to the given Reporter `reporter_type` Inherits: ReporterFactory PersistenceExecutor | Keylogger | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Keylogger:
"""Implements a keylogger that sends reports to the given Reporter `reporter_type` Inherits: ReporterFactory PersistenceExecutor"""
def __init__(self, interval: int, persistent: bool=True, reporter_type: ReportMethod=ReportMethod.EMAIL, **reporter_args: list):
"""Args: int... | stack_v2_sparse_classes_36k_train_031049 | 2,682 | permissive | [
{
"docstring": "Args: interval (int): Report interval persistent (bool): Setting this flag will cause the keylogger to be persistent reporter_type (ReportMethod): The Reporter type. Defaults to email via Gmail reporter_args (list): Keyword arguments to be passed to the Reporter; these will vary",
"name": "_... | 4 | stack_v2_sparse_classes_30k_train_011213 | Implement the Python class `Keylogger` described below.
Class description:
Implements a keylogger that sends reports to the given Reporter `reporter_type` Inherits: ReporterFactory PersistenceExecutor
Method signatures and docstrings:
- def __init__(self, interval: int, persistent: bool=True, reporter_type: ReportMet... | Implement the Python class `Keylogger` described below.
Class description:
Implements a keylogger that sends reports to the given Reporter `reporter_type` Inherits: ReporterFactory PersistenceExecutor
Method signatures and docstrings:
- def __init__(self, interval: int, persistent: bool=True, reporter_type: ReportMet... | 89cba5bf07ec579aa6987e4866db446c8457927f | <|skeleton|>
class Keylogger:
"""Implements a keylogger that sends reports to the given Reporter `reporter_type` Inherits: ReporterFactory PersistenceExecutor"""
def __init__(self, interval: int, persistent: bool=True, reporter_type: ReportMethod=ReportMethod.EMAIL, **reporter_args: list):
"""Args: int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Keylogger:
"""Implements a keylogger that sends reports to the given Reporter `reporter_type` Inherits: ReporterFactory PersistenceExecutor"""
def __init__(self, interval: int, persistent: bool=True, reporter_type: ReportMethod=ReportMethod.EMAIL, **reporter_args: list):
"""Args: interval (int): ... | the_stack_v2_python_sparse | brutus/payloads/keylogger/Keylogger.py | RakhithJK/brutus | train | 0 |
82b347d25fc817ec12056895c869a0641b61e92d | [
"if cached_dependencies is not None:\n value = cached_dependencies.get(name)\nelse:\n value = super(NumpyState, self)._lookup_dependency(name)\nif value is None:\n value = _NumpyWrapper(np.array([]))\n new_reference = base.TrackableReference(name=name, ref=value)\n self._unconditional_checkpoint_depe... | <|body_start_0|>
if cached_dependencies is not None:
value = cached_dependencies.get(name)
else:
value = super(NumpyState, self)._lookup_dependency(name)
if value is None:
value = _NumpyWrapper(np.array([]))
new_reference = base.TrackableReference(... | A checkpointable object whose NumPy array attributes are saved/restored. Example usage: ```python arrays = numpy_storage.NumpyState() checkpoint = tf.train.Checkpoint(numpy_arrays=arrays) arrays.x = np.ones([3, 4]) directory = self.get_temp_dir() prefix = os.path.join(directory, 'ckpt') save_path = checkpoint.save(pref... | NumpyState | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumpyState:
"""A checkpointable object whose NumPy array attributes are saved/restored. Example usage: ```python arrays = numpy_storage.NumpyState() checkpoint = tf.train.Checkpoint(numpy_arrays=arrays) arrays.x = np.ones([3, 4]) directory = self.get_temp_dir() prefix = os.path.join(directory, 'c... | stack_v2_sparse_classes_36k_train_031050 | 9,502 | permissive | [
{
"docstring": "Create placeholder NumPy arrays for to-be-restored attributes. Typically `_lookup_dependency` is used to check by name whether a dependency exists. We cheat slightly by creating a checkpointable object for `name` if we don't already have one, giving us attribute re-creation behavior when loading... | 3 | null | Implement the Python class `NumpyState` described below.
Class description:
A checkpointable object whose NumPy array attributes are saved/restored. Example usage: ```python arrays = numpy_storage.NumpyState() checkpoint = tf.train.Checkpoint(numpy_arrays=arrays) arrays.x = np.ones([3, 4]) directory = self.get_temp_di... | Implement the Python class `NumpyState` described below.
Class description:
A checkpointable object whose NumPy array attributes are saved/restored. Example usage: ```python arrays = numpy_storage.NumpyState() checkpoint = tf.train.Checkpoint(numpy_arrays=arrays) arrays.x = np.ones([3, 4]) directory = self.get_temp_di... | eca1093d3a047e538f17f6ab92ab4d8144284f23 | <|skeleton|>
class NumpyState:
"""A checkpointable object whose NumPy array attributes are saved/restored. Example usage: ```python arrays = numpy_storage.NumpyState() checkpoint = tf.train.Checkpoint(numpy_arrays=arrays) arrays.x = np.ones([3, 4]) directory = self.get_temp_dir() prefix = os.path.join(directory, 'c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumpyState:
"""A checkpointable object whose NumPy array attributes are saved/restored. Example usage: ```python arrays = numpy_storage.NumpyState() checkpoint = tf.train.Checkpoint(numpy_arrays=arrays) arrays.x = np.ones([3, 4]) directory = self.get_temp_dir() prefix = os.path.join(directory, 'ckpt') save_pa... | the_stack_v2_python_sparse | tf_agents/utils/numpy_storage.py | tensorflow/agents | train | 2,755 |
c97067a23527757ba5364863fe6c33b4bffd55d4 | [
"super().__init__(**kwargs)\nif align_file_name != '':\n try:\n self.align_file = open(align_file_name, 'r')\n except FileNotFoundError:\n print('ERROR: Alignment file ' + align_file_name + ' not found.')\n exit()\nself.a_frame_extractor = Frame_extractor()\nself.b_frame_extractor = Frame... | <|body_start_0|>
super().__init__(**kwargs)
if align_file_name != '':
try:
self.align_file = open(align_file_name, 'r')
except FileNotFoundError:
print('ERROR: Alignment file ' + align_file_name + ' not found.')
exit()
self.... | Main_link_control | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Main_link_control:
def __init__(self, align_file_name='', a_lang_mark='', b_lang_mark='', **kwargs):
"""overriden block method"""
<|body_0|>
def process_bundle(self, bundle):
"""overriden block method"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_031051 | 1,839 | no_license | [
{
"docstring": "overriden block method",
"name": "__init__",
"signature": "def __init__(self, align_file_name='', a_lang_mark='', b_lang_mark='', **kwargs)"
},
{
"docstring": "overriden block method",
"name": "process_bundle",
"signature": "def process_bundle(self, bundle)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018586 | Implement the Python class `Main_link_control` described below.
Class description:
Implement the Main_link_control class.
Method signatures and docstrings:
- def __init__(self, align_file_name='', a_lang_mark='', b_lang_mark='', **kwargs): overriden block method
- def process_bundle(self, bundle): overriden block met... | Implement the Python class `Main_link_control` described below.
Class description:
Implement the Main_link_control class.
Method signatures and docstrings:
- def __init__(self, align_file_name='', a_lang_mark='', b_lang_mark='', **kwargs): overriden block method
- def process_bundle(self, bundle): overriden block met... | 194446ec1adeec5ef85db3f96b6d8d2876cc8811 | <|skeleton|>
class Main_link_control:
def __init__(self, align_file_name='', a_lang_mark='', b_lang_mark='', **kwargs):
"""overriden block method"""
<|body_0|>
def process_bundle(self, bundle):
"""overriden block method"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Main_link_control:
def __init__(self, align_file_name='', a_lang_mark='', b_lang_mark='', **kwargs):
"""overriden block method"""
super().__init__(**kwargs)
if align_file_name != '':
try:
self.align_file = open(align_file_name, 'r')
except FileNo... | the_stack_v2_python_sparse | udapi-python/udapi/block/valency/control/main_link_control.py | Jankus1994/ud-valency | train | 0 | |
217e353e2c7c3f7dbcea52ef8addc8cd4310b080 | [
"test = '2\\n-1 5\\n1 5'\nself.assertEqual(calculate(test), '10')\nself.assertEqual(get_inputs(test)[0], 2)\nself.assertEqual(list(get_inputs(test)[1]), [-1, 5, 1, 5])\ntest = '3\\n-2 2\\n1 4\\n-1 3'\nself.assertEqual(calculate(test), '9')\ntest = '3\\n1 9\\n3 5\\n7 10'\nself.assertEqual(calculate(test), '9')\ntest... | <|body_start_0|>
test = '2\n-1 5\n1 5'
self.assertEqual(calculate(test), '10')
self.assertEqual(get_inputs(test)[0], 2)
self.assertEqual(list(get_inputs(test)[1]), [-1, 5, 1, 5])
test = '3\n-2 2\n1 4\n-1 3'
self.assertEqual(calculate(test), '9')
test = '3\n1 9\n3 ... | unitTests | [
"Unlicense",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class unitTests:
def test_sample_tests(self):
"""Quiz sample tests. Add to separate lines"""
<|body_0|>
def test_Apple_class__basic_functions(self):
"""Apple class basic functions testing"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
test = '2\n-1 5\n1 ... | stack_v2_sparse_classes_36k_train_031052 | 4,316 | permissive | [
{
"docstring": "Quiz sample tests. Add to separate lines",
"name": "test_sample_tests",
"signature": "def test_sample_tests(self)"
},
{
"docstring": "Apple class basic functions testing",
"name": "test_Apple_class__basic_functions",
"signature": "def test_Apple_class__basic_functions(sel... | 2 | stack_v2_sparse_classes_30k_train_014265 | Implement the Python class `unitTests` described below.
Class description:
Implement the unitTests class.
Method signatures and docstrings:
- def test_sample_tests(self): Quiz sample tests. Add to separate lines
- def test_Apple_class__basic_functions(self): Apple class basic functions testing | Implement the Python class `unitTests` described below.
Class description:
Implement the unitTests class.
Method signatures and docstrings:
- def test_sample_tests(self): Quiz sample tests. Add to separate lines
- def test_Apple_class__basic_functions(self): Apple class basic functions testing
<|skeleton|>
class uni... | ae02ea872ca91ef98630cc172a844b82cc56f621 | <|skeleton|>
class unitTests:
def test_sample_tests(self):
"""Quiz sample tests. Add to separate lines"""
<|body_0|>
def test_Apple_class__basic_functions(self):
"""Apple class basic functions testing"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class unitTests:
def test_sample_tests(self):
"""Quiz sample tests. Add to separate lines"""
test = '2\n-1 5\n1 5'
self.assertEqual(calculate(test), '10')
self.assertEqual(get_inputs(test)[0], 2)
self.assertEqual(list(get_inputs(test)[1]), [-1, 5, 1, 5])
test = '3\n-2... | the_stack_v2_python_sparse | codeforces/558A_apple.py | snsokolov/contests | train | 1 | |
e3d7d5ffe762e18f302fb7898241c2c8a22e5ade | [
"super(GitDiff, self).__init__(path)\nself.path = path\nself.branch = branch\nself.diff_branch = diff_branch\nself.debug = []\nos.chdir(path)",
"current_branch_results = self._get_current_branch()\nif current_branch_results['results'] == self.branch:\n return True\ncurrent_branch_results = self._checkout(self.... | <|body_start_0|>
super(GitDiff, self).__init__(path)
self.path = path
self.branch = branch
self.diff_branch = diff_branch
self.debug = []
os.chdir(path)
<|end_body_0|>
<|body_start_1|>
current_branch_results = self._get_current_branch()
if current_branch_... | Class to wrap the git merge line tools | GitDiff | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GitDiff:
"""Class to wrap the git merge line tools"""
def __init__(self, path, branch, diff_branch):
"""Constructor for GitDiff"""
<|body_0|>
def checkout_branch(self):
"""check out the desired branch"""
<|body_1|>
def diff(self):
"""perform ... | stack_v2_sparse_classes_36k_train_031053 | 1,101 | permissive | [
{
"docstring": "Constructor for GitDiff",
"name": "__init__",
"signature": "def __init__(self, path, branch, diff_branch)"
},
{
"docstring": "check out the desired branch",
"name": "checkout_branch",
"signature": "def checkout_branch(self)"
},
{
"docstring": "perform a git diff",... | 3 | null | Implement the Python class `GitDiff` described below.
Class description:
Class to wrap the git merge line tools
Method signatures and docstrings:
- def __init__(self, path, branch, diff_branch): Constructor for GitDiff
- def checkout_branch(self): check out the desired branch
- def diff(self): perform a git diff | Implement the Python class `GitDiff` described below.
Class description:
Class to wrap the git merge line tools
Method signatures and docstrings:
- def __init__(self, path, branch, diff_branch): Constructor for GitDiff
- def checkout_branch(self): check out the desired branch
- def diff(self): perform a git diff
<|s... | e342f6659a4ef1a188ff403e2fc6b06ac6d119c7 | <|skeleton|>
class GitDiff:
"""Class to wrap the git merge line tools"""
def __init__(self, path, branch, diff_branch):
"""Constructor for GitDiff"""
<|body_0|>
def checkout_branch(self):
"""check out the desired branch"""
<|body_1|>
def diff(self):
"""perform ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GitDiff:
"""Class to wrap the git merge line tools"""
def __init__(self, path, branch, diff_branch):
"""Constructor for GitDiff"""
super(GitDiff, self).__init__(path)
self.path = path
self.branch = branch
self.diff_branch = diff_branch
self.debug = []
... | the_stack_v2_python_sparse | ansible/roles/lib_git/build/src/git_diff.py | openshift/openshift-tools | train | 170 |
64fcdc388482f2f40acca078d6d6aa8f8149c8f2 | [
"stack = []\nans = []\nwhile stack or root:\n if root:\n ans.append(str(root.val))\n stack.append(root)\n root = root.left\n else:\n node = stack.pop()\n root = node.right\nreturn ' '.join(ans)",
"if not data:\n return None\ndata = map(int, data.split(' '))\ndummy = roo... | <|body_start_0|>
stack = []
ans = []
while stack or root:
if root:
ans.append(str(root.val))
stack.append(root)
root = root.left
else:
node = stack.pop()
root = node.right
return ' '.j... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_031054 | 2,343 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | e5d8ce9c8a9d43ce791655183f6c7cc713da004e | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
stack = []
ans = []
while stack or root:
if root:
ans.append(str(root.val))
stack.append(root)
root = root.lef... | the_stack_v2_python_sparse | Q449-Serialize and Deserialize BST-Medium.py | ChenxiiCheng/Python-LC-Solution | train | 1 | |
a468aa8b0a6d86d3a8df14de7dafffb8d82f1bc3 | [
"self.bot = bot\nself.cmd = CommandCooldown()\nself.db = self.bot.db\nself.cds = self.db[self.bot.cfg.db.database].CooldownSystem",
"if isinstance(user, str):\n cd_name = f'cd_{cmd}_{user}'\nelse:\n cd_name = f'cd_{cmd}_{user.id}'\nentry = self.cds.find_one({'name': cd_name})\nif entry:\n end_stamp = ent... | <|body_start_0|>
self.bot = bot
self.cmd = CommandCooldown()
self.db = self.bot.db
self.cds = self.db[self.bot.cfg.db.database].CooldownSystem
<|end_body_0|>
<|body_start_1|>
if isinstance(user, str):
cd_name = f'cd_{cmd}_{user}'
else:
cd_name = f... | CooldownControl | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CooldownControl:
def __init__(self, bot):
"""The cooldown control core. A collection of functions to read cooldown data from mongo. Cooldowns are stored as MongoDB files so they persist. :param bot:"""
<|body_0|>
def on_cooldown(self, cmd, user):
"""A quick check to ... | stack_v2_sparse_classes_36k_train_031055 | 4,155 | no_license | [
{
"docstring": "The cooldown control core. A collection of functions to read cooldown data from mongo. Cooldowns are stored as MongoDB files so they persist. :param bot:",
"name": "__init__",
"signature": "def __init__(self, bot)"
},
{
"docstring": "A quick check to see if a user is on cool-down... | 4 | stack_v2_sparse_classes_30k_train_019364 | Implement the Python class `CooldownControl` described below.
Class description:
Implement the CooldownControl class.
Method signatures and docstrings:
- def __init__(self, bot): The cooldown control core. A collection of functions to read cooldown data from mongo. Cooldowns are stored as MongoDB files so they persis... | Implement the Python class `CooldownControl` described below.
Class description:
Implement the CooldownControl class.
Method signatures and docstrings:
- def __init__(self, bot): The cooldown control core. A collection of functions to read cooldown data from mongo. Cooldowns are stored as MongoDB files so they persis... | 72175c0f58e36c7b6325a6cb2224731434781aca | <|skeleton|>
class CooldownControl:
def __init__(self, bot):
"""The cooldown control core. A collection of functions to read cooldown data from mongo. Cooldowns are stored as MongoDB files so they persist. :param bot:"""
<|body_0|>
def on_cooldown(self, cmd, user):
"""A quick check to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CooldownControl:
def __init__(self, bot):
"""The cooldown control core. A collection of functions to read cooldown data from mongo. Cooldowns are stored as MongoDB files so they persist. :param bot:"""
self.bot = bot
self.cmd = CommandCooldown()
self.db = self.bot.db
se... | the_stack_v2_python_sparse | marshmallow/core/mechanics/cooldown.py | bretzle/Marshmallow-Bot | train | 0 | |
72f802d8f52419c39180f2005c7d5d769a5baf24 | [
"initial = super().get_initial()\ninitial['product_id'] = self.kwargs['product_pk']\ninitial['purchaser'] = self.request.user.staff_member.id\nreturn initial",
"context = super().get_context_data(*args, **kwargs)\ncontext['product'] = get_object_or_404(BaseProduct, pk=self.kwargs['product_pk'])\npurchase_charge =... | <|body_start_0|>
initial = super().get_initial()
initial['product_id'] = self.kwargs['product_pk']
initial['purchaser'] = self.request.user.staff_member.id
return initial
<|end_body_0|>
<|body_start_1|>
context = super().get_context_data(*args, **kwargs)
context['product... | View for creating new purchases. | CreatePurchase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreatePurchase:
"""View for creating new purchases."""
def get_initial(self):
"""Return initial values for the form."""
<|body_0|>
def get_context_data(self, *args, **kwargs):
"""Return context for the template."""
<|body_1|>
def form_valid(self, for... | stack_v2_sparse_classes_36k_train_031056 | 5,763 | no_license | [
{
"docstring": "Return initial values for the form.",
"name": "get_initial",
"signature": "def get_initial(self)"
},
{
"docstring": "Return context for the template.",
"name": "get_context_data",
"signature": "def get_context_data(self, *args, **kwargs)"
},
{
"docstring": "Create... | 3 | stack_v2_sparse_classes_30k_val_001053 | Implement the Python class `CreatePurchase` described below.
Class description:
View for creating new purchases.
Method signatures and docstrings:
- def get_initial(self): Return initial values for the form.
- def get_context_data(self, *args, **kwargs): Return context for the template.
- def form_valid(self, form): ... | Implement the Python class `CreatePurchase` described below.
Class description:
View for creating new purchases.
Method signatures and docstrings:
- def get_initial(self): Return initial values for the form.
- def get_context_data(self, *args, **kwargs): Return context for the template.
- def form_valid(self, form): ... | ba51d4e304b1aeb296fa2fe16611c892fcdbd471 | <|skeleton|>
class CreatePurchase:
"""View for creating new purchases."""
def get_initial(self):
"""Return initial values for the form."""
<|body_0|>
def get_context_data(self, *args, **kwargs):
"""Return context for the template."""
<|body_1|>
def form_valid(self, for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreatePurchase:
"""View for creating new purchases."""
def get_initial(self):
"""Return initial values for the form."""
initial = super().get_initial()
initial['product_id'] = self.kwargs['product_pk']
initial['purchaser'] = self.request.user.staff_member.id
return... | the_stack_v2_python_sparse | purchases/views.py | stcstores/stcadmin | train | 0 |
05828022f8847c36214b54c9fda2dab4a3e07b67 | [
"parser.add_argument('-u', '--username', default='User Name', help='User name')\nparser.add_argument('-e', '--email', default='user@bogus.com', help='User email')\nparser.add_argument('-i', '--instructor', action='store_true', help='Include in instructor group')\nparser.add_argument('-p', default='boguspwd', help='... | <|body_start_0|>
parser.add_argument('-u', '--username', default='User Name', help='User name')
parser.add_argument('-e', '--email', default='user@bogus.com', help='User email')
parser.add_argument('-i', '--instructor', action='store_true', help='Include in instructor group')
parser.add_... | Class implementing a command to create a single user. | Command | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
"""Class implementing a command to create a single user."""
def add_arguments(self, parser):
"""Parse command arguments."""
<|body_0|>
def handle(self, *args, **options):
"""Execute command to create a single user. :param args: Arguments given to the com... | stack_v2_sparse_classes_36k_train_031057 | 2,328 | permissive | [
{
"docstring": "Parse command arguments.",
"name": "add_arguments",
"signature": "def add_arguments(self, parser)"
},
{
"docstring": "Execute command to create a single user. :param args: Arguments given to the command :param options: Options parsed :return: Nothing",
"name": "handle",
"... | 2 | null | Implement the Python class `Command` described below.
Class description:
Class implementing a command to create a single user.
Method signatures and docstrings:
- def add_arguments(self, parser): Parse command arguments.
- def handle(self, *args, **options): Execute command to create a single user. :param args: Argum... | Implement the Python class `Command` described below.
Class description:
Class implementing a command to create a single user.
Method signatures and docstrings:
- def add_arguments(self, parser): Parse command arguments.
- def handle(self, *args, **options): Execute command to create a single user. :param args: Argum... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class Command:
"""Class implementing a command to create a single user."""
def add_arguments(self, parser):
"""Parse command arguments."""
<|body_0|>
def handle(self, *args, **options):
"""Execute command to create a single user. :param args: Arguments given to the com... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Command:
"""Class implementing a command to create a single user."""
def add_arguments(self, parser):
"""Parse command arguments."""
parser.add_argument('-u', '--username', default='User Name', help='User name')
parser.add_argument('-e', '--email', default='user@bogus.com', help='... | the_stack_v2_python_sparse | ontask/management/commands/create_user.py | abelardopardo/ontask_b | train | 43 |
2b551172bf54fd9244d467e6079151b001a79ddf | [
"super(PositionalEncoding, self).__init__()\nself.dropout: nn.Dropout = nn.Dropout(p=dropout)\npe = torch.zeros(seq_len, d_model)\nposition = torch.arange(0, seq_len, dtype=torch.float).unsqueeze(1)\ndiv_term = torch.exp(torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model))\npe[:, 0::2] = torch.sin(... | <|body_start_0|>
super(PositionalEncoding, self).__init__()
self.dropout: nn.Dropout = nn.Dropout(p=dropout)
pe = torch.zeros(seq_len, d_model)
position = torch.arange(0, seq_len, dtype=torch.float).unsqueeze(1)
div_term = torch.exp(torch.arange(0, d_model, 2).float() * (-math.lo... | ``Positional Encoding`` used in the ``Transformer`` model proposed in `Attention is all you need`. References: `Sequence-to-Sequence Modeling with nn.Transformer and TorchText <https://pytorch.org/tutorials/beginner/transformer_tutorial.html#define-the-model>`_ | PositionalEncoding | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PositionalEncoding:
"""``Positional Encoding`` used in the ``Transformer`` model proposed in `Attention is all you need`. References: `Sequence-to-Sequence Modeling with nn.Transformer and TorchText <https://pytorch.org/tutorials/beginner/transformer_tutorial.html#define-the-model>`_"""
def ... | stack_v2_sparse_classes_36k_train_031058 | 1,939 | permissive | [
{
"docstring": "Args: d_model: the number of expected features in the encoder/decoder inputs. seq_len: length of input sequence. dropout: dropout rate.",
"name": "__init__",
"signature": "def __init__(self, d_model: int, seq_len: int, dropout: float=0.1) -> None"
},
{
"docstring": "Forward propa... | 2 | stack_v2_sparse_classes_30k_train_006823 | Implement the Python class `PositionalEncoding` described below.
Class description:
``Positional Encoding`` used in the ``Transformer`` model proposed in `Attention is all you need`. References: `Sequence-to-Sequence Modeling with nn.Transformer and TorchText <https://pytorch.org/tutorials/beginner/transformer_tutoria... | Implement the Python class `PositionalEncoding` described below.
Class description:
``Positional Encoding`` used in the ``Transformer`` model proposed in `Attention is all you need`. References: `Sequence-to-Sequence Modeling with nn.Transformer and TorchText <https://pytorch.org/tutorials/beginner/transformer_tutoria... | 454d72a51daf8fab6419ceaa62c72d932fef2a61 | <|skeleton|>
class PositionalEncoding:
"""``Positional Encoding`` used in the ``Transformer`` model proposed in `Attention is all you need`. References: `Sequence-to-Sequence Modeling with nn.Transformer and TorchText <https://pytorch.org/tutorials/beginner/transformer_tutorial.html#define-the-model>`_"""
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PositionalEncoding:
"""``Positional Encoding`` used in the ``Transformer`` model proposed in `Attention is all you need`. References: `Sequence-to-Sequence Modeling with nn.Transformer and TorchText <https://pytorch.org/tutorials/beginner/transformer_tutorial.html#define-the-model>`_"""
def __init__(self... | the_stack_v2_python_sparse | enchanter/addons/layers/positional_encoding.py | khirotaka/enchanter | train | 8 |
5716b5f02e9f550df441f371313598e695e5933e | [
"serializer = Serializer(REGISTER_ENCRYPT_KEY, 3600)\ntry:\n user_id = serializer.loads(token)\n user = User.objects.get(id=user_id)\n if user.is_active == 1:\n return render(request, 'active.html', {'user': user, 'error_msg': 'your email has been verified, Please login in directly!'})\n return r... | <|body_start_0|>
serializer = Serializer(REGISTER_ENCRYPT_KEY, 3600)
try:
user_id = serializer.loads(token)
user = User.objects.get(id=user_id)
if user.is_active == 1:
return render(request, 'active.html', {'user': user, 'error_msg': 'your email has be... | user activation | ActiveView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActiveView:
"""user activation"""
def get(self, request, token):
"""get user activation page"""
<|body_0|>
def post(self, request, token):
"""get the user information to activate it"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
serializer = Se... | stack_v2_sparse_classes_36k_train_031059 | 28,206 | no_license | [
{
"docstring": "get user activation page",
"name": "get",
"signature": "def get(self, request, token)"
},
{
"docstring": "get the user information to activate it",
"name": "post",
"signature": "def post(self, request, token)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011164 | Implement the Python class `ActiveView` described below.
Class description:
user activation
Method signatures and docstrings:
- def get(self, request, token): get user activation page
- def post(self, request, token): get the user information to activate it | Implement the Python class `ActiveView` described below.
Class description:
user activation
Method signatures and docstrings:
- def get(self, request, token): get user activation page
- def post(self, request, token): get the user information to activate it
<|skeleton|>
class ActiveView:
"""user activation"""
... | 5efeebedd4695ef9d904beb707a1538ba049b187 | <|skeleton|>
class ActiveView:
"""user activation"""
def get(self, request, token):
"""get user activation page"""
<|body_0|>
def post(self, request, token):
"""get the user information to activate it"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActiveView:
"""user activation"""
def get(self, request, token):
"""get user activation page"""
serializer = Serializer(REGISTER_ENCRYPT_KEY, 3600)
try:
user_id = serializer.loads(token)
user = User.objects.get(id=user_id)
if user.is_active == 1... | the_stack_v2_python_sparse | dbbus/apps/user/views.py | mofiebiger/DublinBus | train | 1 |
8c9a5abaf56e2c958ad44fd406c96d65f3833360 | [
"if not hasattr(self, '_image'):\n img_dts = {}\n pname = self.product.name\n sname = self.sector.name\n img_dts['start_fullext' + sname + pname] = datetime.utcnow()\n log.info('Entering external data-based algorithm.')\n \"\\n Products are mapped one to one from productfiles/<platform_... | <|body_start_0|>
if not hasattr(self, '_image'):
img_dts = {}
pname = self.product.name
sname = self.sector.name
img_dts['start_fullext' + sname + pname] = datetime.utcnow()
log.info('Entering external data-based algorithm.')
"\n ... | ExternalAlg | [
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternalAlg:
def image(self):
"""ExternalAlg is different than ExternalImg in that it takes in the entire datafile for processing (rather than pre-registered data), and returns an arbitrary array or dictionary of arrays instead of an RGB image array). If a dictionary is returned, one ima... | stack_v2_sparse_classes_36k_train_031060 | 7,441 | permissive | [
{
"docstring": "ExternalAlg is different than ExternalImg in that it takes in the entire datafile for processing (rather than pre-registered data), and returns an arbitrary array or dictionary of arrays instead of an RGB image array). If a dictionary is returned, one image will be created per dictionary entry (... | 3 | stack_v2_sparse_classes_30k_train_002164 | Implement the Python class `ExternalAlg` described below.
Class description:
Implement the ExternalAlg class.
Method signatures and docstrings:
- def image(self): ExternalAlg is different than ExternalImg in that it takes in the entire datafile for processing (rather than pre-registered data), and returns an arbitrar... | Implement the Python class `ExternalAlg` described below.
Class description:
Implement the ExternalAlg class.
Method signatures and docstrings:
- def image(self): ExternalAlg is different than ExternalImg in that it takes in the entire datafile for processing (rather than pre-registered data), and returns an arbitrar... | a07e128467b71a5bff25ba0215e020bfe57706dd | <|skeleton|>
class ExternalAlg:
def image(self):
"""ExternalAlg is different than ExternalImg in that it takes in the entire datafile for processing (rather than pre-registered data), and returns an arbitrary array or dictionary of arrays instead of an RGB image array). If a dictionary is returned, one ima... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExternalAlg:
def image(self):
"""ExternalAlg is different than ExternalImg in that it takes in the entire datafile for processing (rather than pre-registered data), and returns an arbitrary array or dictionary of arrays instead of an RGB image array). If a dictionary is returned, one image will be cre... | the_stack_v2_python_sparse | geoips/geoimg/plot/externalalg.py | WIEQLI/GeoIPS | train | 0 | |
6247bec60a0bc31fb748744866b29c2632956aa9 | [
"legalMoves = gameState.getLegalActions()\nscores = [self.evaluationFunction(gameState, action) for action in legalMoves]\nbestScore = max(scores)\nbestIndices = [index for index in range(len(scores)) if scores[index] == bestScore]\nchosenIndex = random.choice(bestIndices)\n'Add more of your code here if you want t... | <|body_start_0|>
legalMoves = gameState.getLegalActions()
scores = [self.evaluationFunction(gameState, action) for action in legalMoves]
bestScore = max(scores)
bestIndices = [index for index in range(len(scores)) if scores[index] == bestScore]
chosenIndex = random.choice(bestInd... | A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our method headers. | ReflexAgent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReflexAgent:
"""A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our method headers."""
def getAction(sel... | stack_v2_sparse_classes_36k_train_031061 | 12,585 | permissive | [
{
"docstring": "You do not need to change this method, but you're welcome to. getAction chooses among the best options according to the evaluation function. Just like in the previous project, getAction takes a GameState and returns some Directions.X for some X in the set {NORTH, SOUTH, WEST, EAST, STOP}",
"... | 2 | stack_v2_sparse_classes_30k_train_012576 | Implement the Python class `ReflexAgent` described below.
Class description:
A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our me... | Implement the Python class `ReflexAgent` described below.
Class description:
A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our me... | f0fa32a4af9354177af0af9e5792c5136173f0b8 | <|skeleton|>
class ReflexAgent:
"""A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our method headers."""
def getAction(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReflexAgent:
"""A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our method headers."""
def getAction(self, gameState)... | the_stack_v2_python_sparse | ArtificialIntelligence/Project2/multiagent/multiAgents.py | iuuuuuaena/CUG-Practice | train | 7 |
df525bd38c608465b9fbf4899b120d90ed4cbcc5 | [
"data = requests.get(url).text\nhtml = BeautifulSoup(data)\ntr = html.find_all('tr')\nhy = tr[0].find_all('td')[0].text.split('\\t')[0]\ntitle = [i.text for i in tr[1].find_all('td')]\ntitle = title[:2] + title[3:10]\ntitle.append('行业')\nres = []\nBM = {'B': 1000000000, 'M': 1000000}\nfor td in tr[2:-2]:\n td = ... | <|body_start_0|>
data = requests.get(url).text
html = BeautifulSoup(data)
tr = html.find_all('tr')
hy = tr[0].find_all('td')[0].text.split('\t')[0]
title = [i.text for i in tr[1].find_all('td')]
title = title[:2] + title[3:10]
title.append('行业')
res = []
... | 市值、货币、行业 | BanKuai | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BanKuai:
"""市值、货币、行业"""
def get_hyl(self, url):
"""以指定行业的URL获取其下所属的股票数据"""
<|body_0|>
def get_hys(self, url='http://www.etnet.com.hk/www/sc/stocks/industry_adu.php'):
"""获取所有的行业URL"""
<|body_1|>
def get_all(self):
"""获得所有数据"""
<|body_... | stack_v2_sparse_classes_36k_train_031062 | 11,353 | no_license | [
{
"docstring": "以指定行业的URL获取其下所属的股票数据",
"name": "get_hyl",
"signature": "def get_hyl(self, url)"
},
{
"docstring": "获取所有的行业URL",
"name": "get_hys",
"signature": "def get_hys(self, url='http://www.etnet.com.hk/www/sc/stocks/industry_adu.php')"
},
{
"docstring": "获得所有数据",
"name"... | 3 | stack_v2_sparse_classes_30k_train_015806 | Implement the Python class `BanKuai` described below.
Class description:
市值、货币、行业
Method signatures and docstrings:
- def get_hyl(self, url): 以指定行业的URL获取其下所属的股票数据
- def get_hys(self, url='http://www.etnet.com.hk/www/sc/stocks/industry_adu.php'): 获取所有的行业URL
- def get_all(self): 获得所有数据 | Implement the Python class `BanKuai` described below.
Class description:
市值、货币、行业
Method signatures and docstrings:
- def get_hyl(self, url): 以指定行业的URL获取其下所属的股票数据
- def get_hys(self, url='http://www.etnet.com.hk/www/sc/stocks/industry_adu.php'): 获取所有的行业URL
- def get_all(self): 获得所有数据
<|skeleton|>
class BanKuai:
... | 818ae04b6f2ca00495c73fd9b3810f083aa3339e | <|skeleton|>
class BanKuai:
"""市值、货币、行业"""
def get_hyl(self, url):
"""以指定行业的URL获取其下所属的股票数据"""
<|body_0|>
def get_hys(self, url='http://www.etnet.com.hk/www/sc/stocks/industry_adu.php'):
"""获取所有的行业URL"""
<|body_1|>
def get_all(self):
"""获得所有数据"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BanKuai:
"""市值、货币、行业"""
def get_hyl(self, url):
"""以指定行业的URL获取其下所属的股票数据"""
data = requests.get(url).text
html = BeautifulSoup(data)
tr = html.find_all('tr')
hy = tr[0].find_all('td')[0].text.split('\t')[0]
title = [i.text for i in tr[1].find_all('td')]
... | the_stack_v2_python_sparse | 2019/港股回购数据获取/huigou_guben.py | hunaghaikong/CodeAll | train | 0 |
cb56898ebeae70e1c76faeaf5afa14abf8fccc75 | [
"self.full_backup_script = full_backup_script\nself.incremental_backup_script = incremental_backup_script\nself.log_backup_script = log_backup_script\nself.remote_host = remote_host\nself.username = username",
"if dictionary is None:\n return None\nfull_backup_script = cohesity_management_sdk.models.remote_scr... | <|body_start_0|>
self.full_backup_script = full_backup_script
self.incremental_backup_script = incremental_backup_script
self.log_backup_script = log_backup_script
self.remote_host = remote_host
self.username = username
<|end_body_0|>
<|body_start_1|>
if dictionary is No... | Implementation of the 'RemoteJobScript' model. Provides details about the Remote Adapter associated with a 'kPuppeteer' Protection Job. Attributes: full_backup_script (RemoteScriptPathAndParams): Specifies the script that should run for the Full (no CBT) backup schedule of a Remote Adapter 'kPuppeteer' Job. This field ... | RemoteJobScript | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteJobScript:
"""Implementation of the 'RemoteJobScript' model. Provides details about the Remote Adapter associated with a 'kPuppeteer' Protection Job. Attributes: full_backup_script (RemoteScriptPathAndParams): Specifies the script that should run for the Full (no CBT) backup schedule of a R... | stack_v2_sparse_classes_36k_train_031063 | 4,552 | permissive | [
{
"docstring": "Constructor for the RemoteJobScript class",
"name": "__init__",
"signature": "def __init__(self, full_backup_script=None, incremental_backup_script=None, log_backup_script=None, remote_host=None, username=None)"
},
{
"docstring": "Creates an instance of this model from a dictiona... | 2 | stack_v2_sparse_classes_30k_train_005210 | Implement the Python class `RemoteJobScript` described below.
Class description:
Implementation of the 'RemoteJobScript' model. Provides details about the Remote Adapter associated with a 'kPuppeteer' Protection Job. Attributes: full_backup_script (RemoteScriptPathAndParams): Specifies the script that should run for t... | Implement the Python class `RemoteJobScript` described below.
Class description:
Implementation of the 'RemoteJobScript' model. Provides details about the Remote Adapter associated with a 'kPuppeteer' Protection Job. Attributes: full_backup_script (RemoteScriptPathAndParams): Specifies the script that should run for t... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RemoteJobScript:
"""Implementation of the 'RemoteJobScript' model. Provides details about the Remote Adapter associated with a 'kPuppeteer' Protection Job. Attributes: full_backup_script (RemoteScriptPathAndParams): Specifies the script that should run for the Full (no CBT) backup schedule of a R... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RemoteJobScript:
"""Implementation of the 'RemoteJobScript' model. Provides details about the Remote Adapter associated with a 'kPuppeteer' Protection Job. Attributes: full_backup_script (RemoteScriptPathAndParams): Specifies the script that should run for the Full (no CBT) backup schedule of a Remote Adapter... | the_stack_v2_python_sparse | cohesity_management_sdk/models/remote_job_script.py | cohesity/management-sdk-python | train | 24 |
8e857d658f73fabc750a023ba5b9bc74ddb70530 | [
"if type(description) is not dict or args or kwargs:\n raise RuntimeError('You appear to want the old DMA driver which has been deprecated and moved to pynq.lib.deprecated')\nsuper().__init__(description=description)\nself.description = description\nif 'parameters' not in description:\n raise RuntimeError('Un... | <|body_start_0|>
if type(description) is not dict or args or kwargs:
raise RuntimeError('You appear to want the old DMA driver which has been deprecated and moved to pynq.lib.deprecated')
super().__init__(description=description)
self.description = description
if 'parameters'... | Class for Interacting with the AXI Simple DMA Engine This class provides two attributes for the read and write channels. The read channel copies data from the stream into memory and the write channel copies data from memory to the output stream. Both channels have an identical API consisting of `transfer` and `wait` fu... | DMA | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DMA:
"""Class for Interacting with the AXI Simple DMA Engine This class provides two attributes for the read and write channels. The read channel copies data from the stream into memory and the write channel copies data from memory to the output stream. Both channels have an identical API consist... | stack_v2_sparse_classes_36k_train_031064 | 25,817 | permissive | [
{
"docstring": "Create an instance of the DMA Driver For DMA, max transfer length is (2^sg_length_width -1). See PG021 tables 2-15, 2-25, 2-31 and 2-38. Parameters ---------- description : dict The entry in the IP dict describing the DMA engine",
"name": "__init__",
"signature": "def __init__(self, desc... | 3 | null | Implement the Python class `DMA` described below.
Class description:
Class for Interacting with the AXI Simple DMA Engine This class provides two attributes for the read and write channels. The read channel copies data from the stream into memory and the write channel copies data from memory to the output stream. Both... | Implement the Python class `DMA` described below.
Class description:
Class for Interacting with the AXI Simple DMA Engine This class provides two attributes for the read and write channels. The read channel copies data from the stream into memory and the write channel copies data from memory to the output stream. Both... | 38e9fcee46f0839e83e123cf22af76b13671a574 | <|skeleton|>
class DMA:
"""Class for Interacting with the AXI Simple DMA Engine This class provides two attributes for the read and write channels. The read channel copies data from the stream into memory and the write channel copies data from memory to the output stream. Both channels have an identical API consist... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DMA:
"""Class for Interacting with the AXI Simple DMA Engine This class provides two attributes for the read and write channels. The read channel copies data from the stream into memory and the write channel copies data from memory to the output stream. Both channels have an identical API consisting of `trans... | the_stack_v2_python_sparse | pynq/lib/dma.py | yunqu/PYNQ | train | 8 |
1e756284afa662f793a74c7800a347180f7d95a9 | [
"if not root:\n return []\nq = deque([root])\nres = []\nwhile q:\n size = len(q)\n while size > 0:\n size -= 1\n node = q.popleft()\n res.append(node.val)\n if node.left:\n q.append(node.left)\n if node.right:\n q.append(node.right)\nreturn res",
"... | <|body_start_0|>
if not root:
return []
q = deque([root])
res = []
while q:
size = len(q)
while size > 0:
size -= 1
node = q.popleft()
res.append(node.val)
if node.left:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[int]:
"""Level order using a queue. BFS"""
<|body_0|>
def levelOrder2(self, root: TreeNode) -> List[List[int]]:
"""Level order using a queue. BFS"""
<|body_1|>
def levelOrder3(self, root: TreeNode) -... | stack_v2_sparse_classes_36k_train_031065 | 2,359 | no_license | [
{
"docstring": "Level order using a queue. BFS",
"name": "levelOrder",
"signature": "def levelOrder(self, root: TreeNode) -> List[int]"
},
{
"docstring": "Level order using a queue. BFS",
"name": "levelOrder2",
"signature": "def levelOrder2(self, root: TreeNode) -> List[List[int]]"
},
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[int]: Level order using a queue. BFS
- def levelOrder2(self, root: TreeNode) -> List[List[int]]: Level order using a queue. BFS
- def... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[int]: Level order using a queue. BFS
- def levelOrder2(self, root: TreeNode) -> List[List[int]]: Level order using a queue. BFS
- def... | 0f16635de49dc63a207d34f7e612546977a5753e | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[int]:
"""Level order using a queue. BFS"""
<|body_0|>
def levelOrder2(self, root: TreeNode) -> List[List[int]]:
"""Level order using a queue. BFS"""
<|body_1|>
def levelOrder3(self, root: TreeNode) -... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root: TreeNode) -> List[int]:
"""Level order using a queue. BFS"""
if not root:
return []
q = deque([root])
res = []
while q:
size = len(q)
while size > 0:
size -= 1
node ... | the_stack_v2_python_sparse | jianzhioffer/32-1levelOrderTraverse.py | bycxw/coder | train | 0 | |
a24fd9e3332d60a70c72263725aa8fc42f9bb77c | [
"a = []\n\ndef helper(root):\n if not root:\n a.append('#')\n return\n a.append(str(root.val))\n helper(root.left)\n helper(root.right)\nhelper(root)\nreturn ' '.join(a)",
"a = data.split()\nself.i = 0\n\ndef helper():\n if a[self.i] == '#':\n self.i += 1\n return None\n... | <|body_start_0|>
a = []
def helper(root):
if not root:
a.append('#')
return
a.append(str(root.val))
helper(root.left)
helper(root.right)
helper(root)
return ' '.join(a)
<|end_body_0|>
<|body_start_1|>
... | Codec_DFS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec_DFS:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_031066 | 5,078 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_020344 | Implement the Python class `Codec_DFS` described below.
Class description:
Implement the Codec_DFS class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str... | Implement the Python class `Codec_DFS` described below.
Class description:
Implement the Codec_DFS class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Codec_DFS:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec_DFS:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
a = []
def helper(root):
if not root:
a.append('#')
return
a.append(str(root.val))
helper(root.left)
... | the_stack_v2_python_sparse | code297SerializeAndDeserializeBinaryTree.py | cybelewang/leetcode-python | train | 0 | |
5bf508a5d1476c83e97a645f47e391f00f0ca9da | [
"res = []\nif not root:\n return res\nres.append(root.val)\nfrontier = deque([root])\nwhile frontier:\n expand = frontier.popleft()\n for kid in (expand.left, expand.right):\n if kid is None:\n res.append(None)\n else:\n res.append(kid.val)\n frontier.append(k... | <|body_start_0|>
res = []
if not root:
return res
res.append(root.val)
frontier = deque([root])
while frontier:
expand = frontier.popleft()
for kid in (expand.left, expand.right):
if kid is None:
res.append(N... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_031067 | 2,351 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_007817 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 11d6bf2ba7b50c07e048df37c4e05c8f46b92241 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = []
if not root:
return res
res.append(root.val)
frontier = deque([root])
while frontier:
expand = frontier.popleft()
... | the_stack_v2_python_sparse | LeetCodes/facebook/Serialize and Deserialize Binary Tree.py | chutianwen/LeetCodes | train | 0 | |
3dfb196226adeb20568b0a7048d1859a22168fcb | [
"self.config = config\nself.classifier = classifier\nself.orig_image = orig_image\nwith tf.variable_scope('taint'):\n self.taint = tf.Variable(tf.random_uniform([self.config['img_height'], self.config['img_width']], dtype=tf.float64))\nself.loss = self.add_loss_op(self.taint)\nself.train_op = self.add_train_op(s... | <|body_start_0|>
self.config = config
self.classifier = classifier
self.orig_image = orig_image
with tf.variable_scope('taint'):
self.taint = tf.Variable(tf.random_uniform([self.config['img_height'], self.config['img_width']], dtype=tf.float64))
self.loss = self.add_l... | Represents an adversarial system that uses gradient descent to minimize the loss (-1 * <classifier loss>) + lambda * <norm of taint>^2. This loss maximizes the classifier's probability of the tainted image being the target letter while keeping the "amount of taint" small. | GradAdv | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GradAdv:
"""Represents an adversarial system that uses gradient descent to minimize the loss (-1 * <classifier loss>) + lambda * <norm of taint>^2. This loss maximizes the classifier's probability of the tainted image being the target letter while keeping the "amount of taint" small."""
def ... | stack_v2_sparse_classes_36k_train_031068 | 6,004 | permissive | [
{
"docstring": "Initializes the GradAdv object with a configuration, classifier, and original image Args: config: a dictionary containing hyperparameters and settings such as img_height, img_width, num_classes (26 for just identifying letters), epochs, learning_rate, norm_constant (lambda in the GradAdv descrip... | 5 | stack_v2_sparse_classes_30k_train_013547 | Implement the Python class `GradAdv` described below.
Class description:
Represents an adversarial system that uses gradient descent to minimize the loss (-1 * <classifier loss>) + lambda * <norm of taint>^2. This loss maximizes the classifier's probability of the tainted image being the target letter while keeping th... | Implement the Python class `GradAdv` described below.
Class description:
Represents an adversarial system that uses gradient descent to minimize the loss (-1 * <classifier loss>) + lambda * <norm of taint>^2. This loss maximizes the classifier's probability of the tainted image being the target letter while keeping th... | 2159e8891c7b60b0d947ea6310e8a52ef8b4392f | <|skeleton|>
class GradAdv:
"""Represents an adversarial system that uses gradient descent to minimize the loss (-1 * <classifier loss>) + lambda * <norm of taint>^2. This loss maximizes the classifier's probability of the tainted image being the target letter while keeping the "amount of taint" small."""
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GradAdv:
"""Represents an adversarial system that uses gradient descent to minimize the loss (-1 * <classifier loss>) + lambda * <norm of taint>^2. This loss maximizes the classifier's probability of the tainted image being the target letter while keeping the "amount of taint" small."""
def __init__(self... | the_stack_v2_python_sparse | src/grad_adv.py | asjchen/taint | train | 1 |
0a1ee42ef5d5173186bf631d9190e131b4c34ea3 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | BufferServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BufferServicer:
"""Missing associated documentation comment in .proto file."""
def SendTrajectories(self, request_iterator, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def SendExperiences(self, request_iterator, context):
"... | stack_v2_sparse_classes_36k_train_031069 | 3,945 | permissive | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "SendTrajectories",
"signature": "def SendTrajectories(self, request_iterator, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "SendExperiences",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_019350 | Implement the Python class `BufferServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def SendTrajectories(self, request_iterator, context): Missing associated documentation comment in .proto file.
- def SendExperiences(self, reque... | Implement the Python class `BufferServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def SendTrajectories(self, request_iterator, context): Missing associated documentation comment in .proto file.
- def SendExperiences(self, reque... | 28723664cd408e3e33c40658284ed24b0068027f | <|skeleton|>
class BufferServicer:
"""Missing associated documentation comment in .proto file."""
def SendTrajectories(self, request_iterator, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def SendExperiences(self, request_iterator, context):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BufferServicer:
"""Missing associated documentation comment in .proto file."""
def SendTrajectories(self, request_iterator, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not impl... | the_stack_v2_python_sparse | rls/distribute/pb2/apex_buffer_pb2_grpc.py | nisheethjaiswal/RLs | train | 0 |
0f9d262f05dfe04e665c7bf42067f34b368712d6 | [
"super(SelfAttention, self).__init__()\nself.W = tf.keras.layers.Dense(units)\nself.U = tf.keras.layers.Dense(units)\nself.V = tf.keras.layers.Dense(1)",
"new_s_prev = tf.expand_dims(s_prev, axis=1)\nscore = self.V(tf.nn.tanh(self.W(new_s_prev) + self.U(hidden_states)))\nweights = tf.nn.softmax(score, axis=1)\nco... | <|body_start_0|>
super(SelfAttention, self).__init__()
self.W = tf.keras.layers.Dense(units)
self.U = tf.keras.layers.Dense(units)
self.V = tf.keras.layers.Dense(1)
<|end_body_0|>
<|body_start_1|>
new_s_prev = tf.expand_dims(s_prev, axis=1)
score = self.V(tf.nn.tanh(self... | Class Self attention | SelfAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
"""Class Self attention"""
def __init__(self, units):
"""method initializer Args: units: Integer representing the number of hidden units in the alignment model W - Dense layer with units units, to be applied to the previous decoder hidden state U - Dense layer with uni... | stack_v2_sparse_classes_36k_train_031070 | 1,833 | no_license | [
{
"docstring": "method initializer Args: units: Integer representing the number of hidden units in the alignment model W - Dense layer with units units, to be applied to the previous decoder hidden state U - Dense layer with units units, to be applied to the encoder hidden states V - Dense layer with 1 units, t... | 2 | stack_v2_sparse_classes_30k_train_013133 | Implement the Python class `SelfAttention` described below.
Class description:
Class Self attention
Method signatures and docstrings:
- def __init__(self, units): method initializer Args: units: Integer representing the number of hidden units in the alignment model W - Dense layer with units units, to be applied to t... | Implement the Python class `SelfAttention` described below.
Class description:
Class Self attention
Method signatures and docstrings:
- def __init__(self, units): method initializer Args: units: Integer representing the number of hidden units in the alignment model W - Dense layer with units units, to be applied to t... | 7f9a040f23eda32c5aa154c991c930a01b490f0f | <|skeleton|>
class SelfAttention:
"""Class Self attention"""
def __init__(self, units):
"""method initializer Args: units: Integer representing the number of hidden units in the alignment model W - Dense layer with units units, to be applied to the previous decoder hidden state U - Dense layer with uni... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelfAttention:
"""Class Self attention"""
def __init__(self, units):
"""method initializer Args: units: Integer representing the number of hidden units in the alignment model W - Dense layer with units units, to be applied to the previous decoder hidden state U - Dense layer with units units, to ... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/1-self_attention.py | dbaroli/holbertonschool-machine_learning | train | 0 |
ecfd7d5871bde42a25414b22df1aecb02b5ffc5d | [
"codec = cls()\ncodec_info = {'encode': codec.encode, 'decode': codec.decode, '_is_text_encoding': False}\nreturn CodecInfo(**codec_info)",
"if isinstance(input, memoryview):\n input = input.tobytes()\nif not isinstance(input, (bytes, bytearray)):\n raise with_context(exc=TypeError(\"Can't encode {type}; by... | <|body_start_0|>
codec = cls()
codec_info = {'encode': codec.encode, 'decode': codec.decode, '_is_text_encoding': False}
return CodecInfo(**codec_info)
<|end_body_0|>
<|body_start_1|>
if isinstance(input, memoryview):
input = input.tobytes()
if not isinstance(input, ... | Legacy codec for converting byte strings into trytes, and vice versa. This method encodes each pair of trytes as an ASCII code point (and vice versa when decoding). The end result requires more space than if the trytes were converted mathematically, but because the result is ASCII, it's easier to work with. Think of th... | AsciiTrytesCodec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsciiTrytesCodec:
"""Legacy codec for converting byte strings into trytes, and vice versa. This method encodes each pair of trytes as an ASCII code point (and vice versa when decoding). The end result requires more space than if the trytes were converted mathematically, but because the result is ... | stack_v2_sparse_classes_36k_train_031071 | 6,409 | permissive | [
{
"docstring": "Returns information used by the codecs library to configure the codec for use.",
"name": "get_codec_info",
"signature": "def get_codec_info(cls) -> CodecInfo"
},
{
"docstring": "Encodes a byte string into trytes.",
"name": "encode",
"signature": "def encode(self, input: U... | 3 | stack_v2_sparse_classes_30k_train_015105 | Implement the Python class `AsciiTrytesCodec` described below.
Class description:
Legacy codec for converting byte strings into trytes, and vice versa. This method encodes each pair of trytes as an ASCII code point (and vice versa when decoding). The end result requires more space than if the trytes were converted mat... | Implement the Python class `AsciiTrytesCodec` described below.
Class description:
Legacy codec for converting byte strings into trytes, and vice versa. This method encodes each pair of trytes as an ASCII code point (and vice versa when decoding). The end result requires more space than if the trytes were converted mat... | d7b4c923fd3aec045b94719ad9a747ac8253541c | <|skeleton|>
class AsciiTrytesCodec:
"""Legacy codec for converting byte strings into trytes, and vice versa. This method encodes each pair of trytes as an ASCII code point (and vice versa when decoding). The end result requires more space than if the trytes were converted mathematically, but because the result is ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AsciiTrytesCodec:
"""Legacy codec for converting byte strings into trytes, and vice versa. This method encodes each pair of trytes as an ASCII code point (and vice versa when decoding). The end result requires more space than if the trytes were converted mathematically, but because the result is ASCII, it's e... | the_stack_v2_python_sparse | iota/codecs.py | fprotopapa/iota.py | train | 0 |
90446aafea8231211b56868c9247836ee15be91b | [
"my_wifi = self.driver.find_element_by_xpath('/html/body/div[1]/div/div/div/header/div[2]/ul/li[1]/div/div')\nActionChains(self.driver).move_to_element(my_wifi).perform()\ntime.sleep(1)\ndecices = self.driver.find_element_by_xpath('/html/body/div[1]/div/div/div/header/div[2]/ul/li[1]/ul/li[2]')\nActionChains(self.d... | <|body_start_0|>
my_wifi = self.driver.find_element_by_xpath('/html/body/div[1]/div/div/div/header/div[2]/ul/li[1]/div/div')
ActionChains(self.driver).move_to_element(my_wifi).perform()
time.sleep(1)
decices = self.driver.find_element_by_xpath('/html/body/div[1]/div/div/div/header/div[2]... | MyWifi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyWifi:
def test_access_devices_limit_time(self):
"""接入设备-限时"""
<|body_0|>
def test_access_devices_limit_speed(self):
"""接入设备-限速"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
my_wifi = self.driver.find_element_by_xpath('/html/body/div[1]/div/div/d... | stack_v2_sparse_classes_36k_train_031072 | 3,434 | no_license | [
{
"docstring": "接入设备-限时",
"name": "test_access_devices_limit_time",
"signature": "def test_access_devices_limit_time(self)"
},
{
"docstring": "接入设备-限速",
"name": "test_access_devices_limit_speed",
"signature": "def test_access_devices_limit_speed(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017457 | Implement the Python class `MyWifi` described below.
Class description:
Implement the MyWifi class.
Method signatures and docstrings:
- def test_access_devices_limit_time(self): 接入设备-限时
- def test_access_devices_limit_speed(self): 接入设备-限速 | Implement the Python class `MyWifi` described below.
Class description:
Implement the MyWifi class.
Method signatures and docstrings:
- def test_access_devices_limit_time(self): 接入设备-限时
- def test_access_devices_limit_speed(self): 接入设备-限速
<|skeleton|>
class MyWifi:
def test_access_devices_limit_time(self):
... | 794cae756d4316c2ad75399e57b24bbce5776210 | <|skeleton|>
class MyWifi:
def test_access_devices_limit_time(self):
"""接入设备-限时"""
<|body_0|>
def test_access_devices_limit_speed(self):
"""接入设备-限速"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyWifi:
def test_access_devices_limit_time(self):
"""接入设备-限时"""
my_wifi = self.driver.find_element_by_xpath('/html/body/div[1]/div/div/div/header/div[2]/ul/li[1]/div/div')
ActionChains(self.driver).move_to_element(my_wifi).perform()
time.sleep(1)
decices = self.driver.f... | the_stack_v2_python_sparse | WebAuto/test_my_wifi.py | jungaohzz/Practice_1 | train | 0 | |
09664f8a4cce173651142202ebfab6d36a157a55 | [
"data = super().read()\nprint(f'Read and decompressed {data}')\nreturn data",
"print(f'Compressing {data}')\nsuper().write(data)\nprint(f'Compressed {data} written')"
] | <|body_start_0|>
data = super().read()
print(f'Read and decompressed {data}')
return data
<|end_body_0|>
<|body_start_1|>
print(f'Compressing {data}')
super().write(data)
print(f'Compressed {data} written')
<|end_body_1|>
| This is a decorator (read: wrapper) adds compression/decompression behaviour to a datasource (just place holder print statements for this example). This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decorator (like the EncryptionDataSourceDecorator). | CompressedDataSourceDecorator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompressedDataSourceDecorator:
"""This is a decorator (read: wrapper) adds compression/decompression behaviour to a datasource (just place holder print statements for this example). This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decor... | stack_v2_sparse_classes_36k_train_031073 | 6,195 | no_license | [
{
"docstring": "\"Decompress\" the data read from the object that this decorator is wrapped around. :return: the data read as a string",
"name": "read",
"signature": "def read(self)"
},
{
"docstring": "\"Compress\" data before writing it to a data source that this decorator is wrapped around. :p... | 2 | stack_v2_sparse_classes_30k_train_009899 | Implement the Python class `CompressedDataSourceDecorator` described below.
Class description:
This is a decorator (read: wrapper) adds compression/decompression behaviour to a datasource (just place holder print statements for this example). This decorator can wrap around a concrete DataSource (like FileDataSource) o... | Implement the Python class `CompressedDataSourceDecorator` described below.
Class description:
This is a decorator (read: wrapper) adds compression/decompression behaviour to a datasource (just place holder print statements for this example). This decorator can wrap around a concrete DataSource (like FileDataSource) o... | 68ad3a22646c5433e395fbee2c1fbb972b805c09 | <|skeleton|>
class CompressedDataSourceDecorator:
"""This is a decorator (read: wrapper) adds compression/decompression behaviour to a datasource (just place holder print statements for this example). This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompressedDataSourceDecorator:
"""This is a decorator (read: wrapper) adds compression/decompression behaviour to a datasource (just place holder print statements for this example). This decorator can wrap around a concrete DataSource (like FileDataSource) or it can also wrap around another Decorator (like th... | the_stack_v2_python_sparse | Lectures/1028/decorator_example.py | usop7/Python_OOP_Projects | train | 0 |
f4cbea656d5fb9c9e504d6f88f971acebd218660 | [
"q = kwd.get('q', '')\nif not q:\n raise NotImplemented('Listing of all the tools is not implemented. Provide parameter \"q\" to search instead.')\nelse:\n page = kwd.get('page', 1)\n page_size = kwd.get('page_size', 10)\n try:\n page = int(page)\n page_size = int(page_size)\n except Va... | <|body_start_0|>
q = kwd.get('q', '')
if not q:
raise NotImplemented('Listing of all the tools is not implemented. Provide parameter "q" to search instead.')
else:
page = kwd.get('page', 1)
page_size = kwd.get('page_size', 10)
try:
... | RESTful controller for interactions with tools in the Tool Shed. | ToolsController | [
"CC-BY-2.5",
"AFL-2.1",
"AFL-3.0",
"CC-BY-3.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ToolsController:
"""RESTful controller for interactions with tools in the Tool Shed."""
def index(self, trans, **kwd):
"""GET /api/tools Displays a collection of tools with optional criteria. :param q: (optional)if present search on the given query will be performed :type q: str :par... | stack_v2_sparse_classes_36k_train_031074 | 4,493 | permissive | [
{
"docstring": "GET /api/tools Displays a collection of tools with optional criteria. :param q: (optional)if present search on the given query will be performed :type q: str :param page: (optional)requested page of the search :type page: int :param page_size: (optional)requested page_size of the search :type pa... | 2 | null | Implement the Python class `ToolsController` described below.
Class description:
RESTful controller for interactions with tools in the Tool Shed.
Method signatures and docstrings:
- def index(self, trans, **kwd): GET /api/tools Displays a collection of tools with optional criteria. :param q: (optional)if present sear... | Implement the Python class `ToolsController` described below.
Class description:
RESTful controller for interactions with tools in the Tool Shed.
Method signatures and docstrings:
- def index(self, trans, **kwd): GET /api/tools Displays a collection of tools with optional criteria. :param q: (optional)if present sear... | 1ad89511540e6800cd2d0da5d878c1c77d8ccfe9 | <|skeleton|>
class ToolsController:
"""RESTful controller for interactions with tools in the Tool Shed."""
def index(self, trans, **kwd):
"""GET /api/tools Displays a collection of tools with optional criteria. :param q: (optional)if present search on the given query will be performed :type q: str :par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ToolsController:
"""RESTful controller for interactions with tools in the Tool Shed."""
def index(self, trans, **kwd):
"""GET /api/tools Displays a collection of tools with optional criteria. :param q: (optional)if present search on the given query will be performed :type q: str :param page: (opt... | the_stack_v2_python_sparse | lib/galaxy/webapps/tool_shed/api/tools.py | abretaud/galaxy | train | 0 |
568da508e4482fe744c0a69277722f462e92e847 | [
"list_dict = []\ndata = pd.read_json(self.path, encoding='utf-8')\nfor t in data.iterrows():\n d = dict(t[1])\n list_dict.append(d)\ndf = pd.DataFrame.from_dict(self.dropnested(list_dict))\ndf['date'] = df['acquisitionTime'].apply(lambda t: parser.isoparse(t))\ndf['date'] = df.date.dt.tz_localize(None)\ndf['d... | <|body_start_0|>
list_dict = []
data = pd.read_json(self.path, encoding='utf-8')
for t in data.iterrows():
d = dict(t[1])
list_dict.append(d)
df = pd.DataFrame.from_dict(self.dropnested(list_dict))
df['date'] = df['acquisitionTime'].apply(lambda t: parser.... | GoogleAppsReader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GoogleAppsReader:
def read(self):
"""Read json file and give a panda dataframe cleaned ---> encoding utf-8 to avoid special character not readable (é, ü etc...) ---> all nested dictionnaries (ie. each app) is put in a list ---> the dataframe is constructed from the returned dictionnary f... | stack_v2_sparse_classes_36k_train_031075 | 3,240 | permissive | [
{
"docstring": "Read json file and give a panda dataframe cleaned ---> encoding utf-8 to avoid special character not readable (é, ü etc...) ---> all nested dictionnaries (ie. each app) is put in a list ---> the dataframe is constructed from the returned dictionnary from dropnested ---> parser.isoparse transform... | 2 | stack_v2_sparse_classes_30k_train_002324 | Implement the Python class `GoogleAppsReader` described below.
Class description:
Implement the GoogleAppsReader class.
Method signatures and docstrings:
- def read(self): Read json file and give a panda dataframe cleaned ---> encoding utf-8 to avoid special character not readable (é, ü etc...) ---> all nested dictio... | Implement the Python class `GoogleAppsReader` described below.
Class description:
Implement the GoogleAppsReader class.
Method signatures and docstrings:
- def read(self): Read json file and give a panda dataframe cleaned ---> encoding utf-8 to avoid special character not readable (é, ü etc...) ---> all nested dictio... | 179dd4f04713026656c0849916166fd1ed0d6f31 | <|skeleton|>
class GoogleAppsReader:
def read(self):
"""Read json file and give a panda dataframe cleaned ---> encoding utf-8 to avoid special character not readable (é, ü etc...) ---> all nested dictionnaries (ie. each app) is put in a list ---> the dataframe is constructed from the returned dictionnary f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GoogleAppsReader:
def read(self):
"""Read json file and give a panda dataframe cleaned ---> encoding utf-8 to avoid special character not readable (é, ü etc...) ---> all nested dictionnaries (ie. each app) is put in a list ---> the dataframe is constructed from the returned dictionnary from dropnested... | the_stack_v2_python_sparse | Package/google_sub_readers/apps.py | AdrienCarthoblaz/Master-Thesis | train | 2 | |
51c625dbc71a1250e342d1b2144940129cf285e6 | [
"base.DataLayer.__init__(self, **kwargs)\nself._filenames = self.spec['puff']\nself._use_mpi = self.spec.get('use_mpi', True)\nself._minibatch = self.spec['minibatch']\nself._puffs = [base.Puff(filename) for filename in self._filenames]\nnum_data = [puff.num_data() for puff in self._puffs]\nif len(set(num_data)) ==... | <|body_start_0|>
base.DataLayer.__init__(self, **kwargs)
self._filenames = self.spec['puff']
self._use_mpi = self.spec.get('use_mpi', True)
self._minibatch = self.spec['minibatch']
self._puffs = [base.Puff(filename) for filename in self._filenames]
num_data = [puff.num_da... | A layer that loads data from a set of puff files. | PuffSamplerLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PuffSamplerLayer:
"""A layer that loads data from a set of puff files."""
def __init__(self, **kwargs):
"""Initializes the Puff sampling layer. kwargs: minibatch: the minibatch size. puff: a list of puff files to be read. These files should have the same number of data points, and th... | stack_v2_sparse_classes_36k_train_031076 | 2,104 | no_license | [
{
"docstring": "Initializes the Puff sampling layer. kwargs: minibatch: the minibatch size. puff: a list of puff files to be read. These files should have the same number of data points, and the sampler will return data points from different points with the same index. use_mpi: if set True, when the code is run... | 2 | stack_v2_sparse_classes_30k_train_021281 | Implement the Python class `PuffSamplerLayer` described below.
Class description:
A layer that loads data from a set of puff files.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initializes the Puff sampling layer. kwargs: minibatch: the minibatch size. puff: a list of puff files to be read. These... | Implement the Python class `PuffSamplerLayer` described below.
Class description:
A layer that loads data from a set of puff files.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initializes the Puff sampling layer. kwargs: minibatch: the minibatch size. puff: a list of puff files to be read. These... | 6fa4cdfbd0d0b8d486d7146bf1e32edd3662fec4 | <|skeleton|>
class PuffSamplerLayer:
"""A layer that loads data from a set of puff files."""
def __init__(self, **kwargs):
"""Initializes the Puff sampling layer. kwargs: minibatch: the minibatch size. puff: a list of puff files to be read. These files should have the same number of data points, and th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PuffSamplerLayer:
"""A layer that loads data from a set of puff files."""
def __init__(self, **kwargs):
"""Initializes the Puff sampling layer. kwargs: minibatch: the minibatch size. puff: a list of puff files to be read. These files should have the same number of data points, and the sampler wil... | the_stack_v2_python_sparse | decaf/layers/puffsampler.py | UCBAIR/decaf-release | train | 62 |
86f281e80929c33a34ec8dc63e07c5478c3947c3 | [
"super().__init__(reduce, transfer_attributes)\nself._time_window = time_window\nself._cluster_method = DBSCAN(self._time_window, min_samples=1)\nself._keys = keys\nself._time_key = time_key",
"dom_index = group_by(data, self._keys)\nif data.batch is not None:\n features = data.features[0]\nelse:\n features... | <|body_start_0|>
super().__init__(reduce, transfer_attributes)
self._time_window = time_window
self._cluster_method = DBSCAN(self._time_window, min_samples=1)
self._keys = keys
self._time_key = time_key
<|end_body_0|>
<|body_start_1|>
dom_index = group_by(data, self._key... | Coarsen pulses to DOM-level, with additional time-window clustering. | DOMAndTimeWindowCoarsening | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DOMAndTimeWindowCoarsening:
"""Coarsen pulses to DOM-level, with additional time-window clustering."""
def __init__(self, time_window: float, reduce: str='avg', transfer_attributes: bool=True, keys: List[str]=['dom_x', 'dom_y', 'dom_z', 'rde', 'pmt_area'], time_key: str='dom_time'):
... | stack_v2_sparse_classes_36k_train_031077 | 11,190 | permissive | [
{
"docstring": "Cluster pulses on the same DOM within `time_window`.",
"name": "__init__",
"signature": "def __init__(self, time_window: float, reduce: str='avg', transfer_attributes: bool=True, keys: List[str]=['dom_x', 'dom_y', 'dom_z', 'rde', 'pmt_area'], time_key: str='dom_time')"
},
{
"docs... | 2 | stack_v2_sparse_classes_30k_train_018223 | Implement the Python class `DOMAndTimeWindowCoarsening` described below.
Class description:
Coarsen pulses to DOM-level, with additional time-window clustering.
Method signatures and docstrings:
- def __init__(self, time_window: float, reduce: str='avg', transfer_attributes: bool=True, keys: List[str]=['dom_x', 'dom_... | Implement the Python class `DOMAndTimeWindowCoarsening` described below.
Class description:
Coarsen pulses to DOM-level, with additional time-window clustering.
Method signatures and docstrings:
- def __init__(self, time_window: float, reduce: str='avg', transfer_attributes: bool=True, keys: List[str]=['dom_x', 'dom_... | f6e03282dd665c81d06eaa1ab55a07d138064e9a | <|skeleton|>
class DOMAndTimeWindowCoarsening:
"""Coarsen pulses to DOM-level, with additional time-window clustering."""
def __init__(self, time_window: float, reduce: str='avg', transfer_attributes: bool=True, keys: List[str]=['dom_x', 'dom_y', 'dom_z', 'rde', 'pmt_area'], time_key: str='dom_time'):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DOMAndTimeWindowCoarsening:
"""Coarsen pulses to DOM-level, with additional time-window clustering."""
def __init__(self, time_window: float, reduce: str='avg', transfer_attributes: bool=True, keys: List[str]=['dom_x', 'dom_y', 'dom_z', 'rde', 'pmt_area'], time_key: str='dom_time'):
"""Cluster pu... | the_stack_v2_python_sparse | src/graphnet/models/coarsening.py | graphnet-team/graphnet | train | 55 |
ae0c89122b0b25bb91f45d8b43586a5d87704185 | [
"res = []\nself.dfs(root, res)\nreturn res",
"if root:\n self.dfs(root.left, res)\n self.dfs(root.right, res)\n res.append(root.val)",
"if not root:\n return []\nstack, res = ([root], [])\nwhile stack:\n node = stack.pop()\n if node.left:\n stack.append(node.left)\n if node.right:\n ... | <|body_start_0|>
res = []
self.dfs(root, res)
return res
<|end_body_0|>
<|body_start_1|>
if root:
self.dfs(root.left, res)
self.dfs(root.right, res)
res.append(root.val)
<|end_body_1|>
<|body_start_2|>
if not root:
return []
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def dfs(self, root, res):
""":type root: TreeNode :type res: List[int] :rtype: None"""
<|body_1|>
def postorderTraversal_1(self, root):
""":type... | stack_v2_sparse_classes_36k_train_031078 | 2,233 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "postorderTraversal",
"signature": "def postorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :type res: List[int] :rtype: None",
"name": "dfs",
"signature": "def dfs(self, root, res)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_010678 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def postorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def dfs(self, root, res): :type root: TreeNode :type res: List[int] :rtype: None
- def postorderTrave... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def postorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def dfs(self, root, res): :type root: TreeNode :type res: List[int] :rtype: None
- def postorderTrave... | 3d9e0ad2f6ed92ec969556f75d97c51ea4854719 | <|skeleton|>
class Solution:
def postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def dfs(self, root, res):
""":type root: TreeNode :type res: List[int] :rtype: None"""
<|body_1|>
def postorderTraversal_1(self, root):
""":type... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def postorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
res = []
self.dfs(root, res)
return res
def dfs(self, root, res):
""":type root: TreeNode :type res: List[int] :rtype: None"""
if root:
self.dfs(root.left... | the_stack_v2_python_sparse | Solutions/0145_postorderTraversal.py | YoupengLi/leetcode-sorting | train | 3 | |
669ba5d3ddcb833f1e01465ccec198b7daee4b80 | [
"super(BertLayerNorm, self).__init__()\nself.reducemean = P.ReduceMean(keep_dims=True)\nself.sub = P.Sub()\nself.pow = P.Pow()\nself.add = P.Add()\nself.sqrt = P.Sqrt()\nself.div = P.Div()\nself.mul = P.Mul()\nself.variance_epsilon = eps\nself.bert_layer_norm_weight = Parameter(Tensor(np.random.uniform(0, 1, bert_l... | <|body_start_0|>
super(BertLayerNorm, self).__init__()
self.reducemean = P.ReduceMean(keep_dims=True)
self.sub = P.Sub()
self.pow = P.Pow()
self.add = P.Add()
self.sqrt = P.Sqrt()
self.div = P.Div()
self.mul = P.Mul()
self.variance_epsilon = eps
... | Normalization module of reader downstream | BertLayerNorm | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BertLayerNorm:
"""Normalization module of reader downstream"""
def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12):
"""init function"""
<|body_0|>
def construct(self, x):
"""construct function"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k_train_031079 | 9,011 | permissive | [
{
"docstring": "init function",
"name": "__init__",
"signature": "def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12)"
},
{
"docstring": "construct function",
"name": "construct",
"signature": "def construct(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003505 | Implement the Python class `BertLayerNorm` described below.
Class description:
Normalization module of reader downstream
Method signatures and docstrings:
- def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12): init function
- def construct(self, x): construct function | Implement the Python class `BertLayerNorm` described below.
Class description:
Normalization module of reader downstream
Method signatures and docstrings:
- def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12): init function
- def construct(self, x): construct function
<|skeleton|>... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class BertLayerNorm:
"""Normalization module of reader downstream"""
def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12):
"""init function"""
<|body_0|>
def construct(self, x):
"""construct function"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BertLayerNorm:
"""Normalization module of reader downstream"""
def __init__(self, bert_layer_norm_weight_shape, bert_layer_norm_bias_shape, eps=1e-12):
"""init function"""
super(BertLayerNorm, self).__init__()
self.reducemean = P.ReduceMean(keep_dims=True)
self.sub = P.Sub... | the_stack_v2_python_sparse | research/nlp/tprr/src/reader_downstream.py | mindspore-ai/models | train | 301 |
96647a534284a3a0c57ba511cb75f8bb8cd45ddb | [
"session = db_apis.get_session()\nwith session.begin():\n db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])\nif db_lb.listeners:\n if amphora is not None:\n with session.begin():\n db_amp = self.amphora_repo.get(session, id=amphora[constants.ID])\n el... | <|body_start_0|>
session = db_apis.get_session()
with session.begin():
db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])
if db_lb.listeners:
if amphora is not None:
with session.begin():
db_amp = se... | Task to start all listeners on the vip. | ListenersStart | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListenersStart:
"""Task to start all listeners on the vip."""
def execute(self, loadbalancer, amphora=None):
"""Execute listener start routines for listeners on an amphora."""
<|body_0|>
def revert(self, loadbalancer, *args, **kwargs):
"""Handle failed listeners ... | stack_v2_sparse_classes_36k_train_031080 | 28,773 | permissive | [
{
"docstring": "Execute listener start routines for listeners on an amphora.",
"name": "execute",
"signature": "def execute(self, loadbalancer, amphora=None)"
},
{
"docstring": "Handle failed listeners starts.",
"name": "revert",
"signature": "def revert(self, loadbalancer, *args, **kwar... | 2 | null | Implement the Python class `ListenersStart` described below.
Class description:
Task to start all listeners on the vip.
Method signatures and docstrings:
- def execute(self, loadbalancer, amphora=None): Execute listener start routines for listeners on an amphora.
- def revert(self, loadbalancer, *args, **kwargs): Han... | Implement the Python class `ListenersStart` described below.
Class description:
Task to start all listeners on the vip.
Method signatures and docstrings:
- def execute(self, loadbalancer, amphora=None): Execute listener start routines for listeners on an amphora.
- def revert(self, loadbalancer, *args, **kwargs): Han... | 0426285a41464a5015494584f109eed35a0d44db | <|skeleton|>
class ListenersStart:
"""Task to start all listeners on the vip."""
def execute(self, loadbalancer, amphora=None):
"""Execute listener start routines for listeners on an amphora."""
<|body_0|>
def revert(self, loadbalancer, *args, **kwargs):
"""Handle failed listeners ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListenersStart:
"""Task to start all listeners on the vip."""
def execute(self, loadbalancer, amphora=None):
"""Execute listener start routines for listeners on an amphora."""
session = db_apis.get_session()
with session.begin():
db_lb = self.loadbalancer_repo.get(sess... | the_stack_v2_python_sparse | octavia/controller/worker/v2/tasks/amphora_driver_tasks.py | openstack/octavia | train | 147 |
507e922530dd635f124b537ffb3bb4025c52a744 | [
"bucket = self._table[j]\nif bucket is None:\n raise KeyError('Key Error: Map has no key-value entry for ' + repr(key))\nreturn bucket[key]",
"if self._table[j] is None:\n self._table[j] = UnsortedTableMap()\noldsize = len(self._table[j])\nself._table[j][key] = value\nif len(self._table[j]) > oldsize:\n ... | <|body_start_0|>
bucket = self._table[j]
if bucket is None:
raise KeyError('Key Error: Map has no key-value entry for ' + repr(key))
return bucket[key]
<|end_body_0|>
<|body_start_1|>
if self._table[j] is None:
self._table[j] = UnsortedTableMap()
oldsize ... | Hash map with separate chaining for collision resolution | ChainHashMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChainHashMap:
"""Hash map with separate chaining for collision resolution"""
def _bucket_getitem(self, j, key):
"""Get an item associated with key from a bucket at index j of bucket array"""
<|body_0|>
def _bucket_setitem(self, j, key, value):
"""Set a key-value ... | stack_v2_sparse_classes_36k_train_031081 | 2,213 | no_license | [
{
"docstring": "Get an item associated with key from a bucket at index j of bucket array",
"name": "_bucket_getitem",
"signature": "def _bucket_getitem(self, j, key)"
},
{
"docstring": "Set a key-value into bucket at index j of bucket array",
"name": "_bucket_setitem",
"signature": "def ... | 4 | null | Implement the Python class `ChainHashMap` described below.
Class description:
Hash map with separate chaining for collision resolution
Method signatures and docstrings:
- def _bucket_getitem(self, j, key): Get an item associated with key from a bucket at index j of bucket array
- def _bucket_setitem(self, j, key, val... | Implement the Python class `ChainHashMap` described below.
Class description:
Hash map with separate chaining for collision resolution
Method signatures and docstrings:
- def _bucket_getitem(self, j, key): Get an item associated with key from a bucket at index j of bucket array
- def _bucket_setitem(self, j, key, val... | 96e2cf2bdfe615042fbf64576167d5cae24d622e | <|skeleton|>
class ChainHashMap:
"""Hash map with separate chaining for collision resolution"""
def _bucket_getitem(self, j, key):
"""Get an item associated with key from a bucket at index j of bucket array"""
<|body_0|>
def _bucket_setitem(self, j, key, value):
"""Set a key-value ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChainHashMap:
"""Hash map with separate chaining for collision resolution"""
def _bucket_getitem(self, j, key):
"""Get an item associated with key from a bucket at index j of bucket array"""
bucket = self._table[j]
if bucket is None:
raise KeyError('Key Error: Map has ... | the_stack_v2_python_sparse | hashmaps/chainhashmap.py | Pato91/msft | train | 0 |
f5420dd5ed9ac7615ed7cb322de376eadbb4352f | [
"logger.info(f'SvgAndImageFormField.to_py :: {data} :: {type(data)}')\ntry:\n test_file = super().to_python(data)\nexcept ValidationError:\n if not self.is_svg(data):\n raise\n else:\n test_file = data\nif test_file is None:\n return None\nif hasattr(data, 'temporary_file_path'):\n ifil... | <|body_start_0|>
logger.info(f'SvgAndImageFormField.to_py :: {data} :: {type(data)}')
try:
test_file = super().to_python(data)
except ValidationError:
if not self.is_svg(data):
raise
else:
test_file = data
if test_file i... | SvgAndImageFormField | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SvgAndImageFormField:
def to_python(self, data):
"""Checks that the file-upload field data contains a valid image (GIF, JPG, PNG, possibly others -- whatever the Python Imaging Library supports)."""
<|body_0|>
def is_svg(self, f):
"""Check if provided file is svg"""
... | stack_v2_sparse_classes_36k_train_031082 | 3,303 | permissive | [
{
"docstring": "Checks that the file-upload field data contains a valid image (GIF, JPG, PNG, possibly others -- whatever the Python Imaging Library supports).",
"name": "to_python",
"signature": "def to_python(self, data)"
},
{
"docstring": "Check if provided file is svg",
"name": "is_svg",... | 2 | null | Implement the Python class `SvgAndImageFormField` described below.
Class description:
Implement the SvgAndImageFormField class.
Method signatures and docstrings:
- def to_python(self, data): Checks that the file-upload field data contains a valid image (GIF, JPG, PNG, possibly others -- whatever the Python Imaging Li... | Implement the Python class `SvgAndImageFormField` described below.
Class description:
Implement the SvgAndImageFormField class.
Method signatures and docstrings:
- def to_python(self, data): Checks that the file-upload field data contains a valid image (GIF, JPG, PNG, possibly others -- whatever the Python Imaging Li... | 1055300216619c30cb06d58e51d78f739beb6483 | <|skeleton|>
class SvgAndImageFormField:
def to_python(self, data):
"""Checks that the file-upload field data contains a valid image (GIF, JPG, PNG, possibly others -- whatever the Python Imaging Library supports)."""
<|body_0|>
def is_svg(self, f):
"""Check if provided file is svg"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SvgAndImageFormField:
def to_python(self, data):
"""Checks that the file-upload field data contains a valid image (GIF, JPG, PNG, possibly others -- whatever the Python Imaging Library supports)."""
logger.info(f'SvgAndImageFormField.to_py :: {data} :: {type(data)}')
try:
t... | the_stack_v2_python_sparse | foundation/core/svg.py | okfn/website | train | 83 | |
9ea20f6c82956b473b8bd9fb7619a1b50bd8de74 | [
"params = [10000, 5, 10, 15]\nheight = 100\nwidth = 200\nworld_map = gen.generate_map(height=height, width=width, params=params)\nimage = img.get_map_overview(world_map)\npixels = image.load()\nfor x in range(width):\n for y in range(height):\n color = tuple(img.get_color(world_map[x][y]))\n self.a... | <|body_start_0|>
params = [10000, 5, 10, 15]
height = 100
width = 200
world_map = gen.generate_map(height=height, width=width, params=params)
image = img.get_map_overview(world_map)
pixels = image.load()
for x in range(width):
for y in range(height):
... | MapCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MapCase:
def test_map_overview_accuracy(self):
"""Test if image of map overview properly represents generated map matrix."""
<|body_0|>
def test_spreading_players(self):
"""Test if players are properly spread across."""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_031083 | 1,357 | permissive | [
{
"docstring": "Test if image of map overview properly represents generated map matrix.",
"name": "test_map_overview_accuracy",
"signature": "def test_map_overview_accuracy(self)"
},
{
"docstring": "Test if players are properly spread across.",
"name": "test_spreading_players",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_013293 | Implement the Python class `MapCase` described below.
Class description:
Implement the MapCase class.
Method signatures and docstrings:
- def test_map_overview_accuracy(self): Test if image of map overview properly represents generated map matrix.
- def test_spreading_players(self): Test if players are properly sprea... | Implement the Python class `MapCase` described below.
Class description:
Implement the MapCase class.
Method signatures and docstrings:
- def test_map_overview_accuracy(self): Test if image of map overview properly represents generated map matrix.
- def test_spreading_players(self): Test if players are properly sprea... | 1edad57d47ad975950639fc391b645e47509cf58 | <|skeleton|>
class MapCase:
def test_map_overview_accuracy(self):
"""Test if image of map overview properly represents generated map matrix."""
<|body_0|>
def test_spreading_players(self):
"""Test if players are properly spread across."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MapCase:
def test_map_overview_accuracy(self):
"""Test if image of map overview properly represents generated map matrix."""
params = [10000, 5, 10, 15]
height = 100
width = 200
world_map = gen.generate_map(height=height, width=width, params=params)
image = img.... | the_stack_v2_python_sparse | map_generation/test_map_generation.py | GabrielWechta/age-of-divisiveness | train | 0 | |
538d445e457171953756acf0f1e21677ba0b26a1 | [
"self.width, self.height = dim\nself.width = self.width // 2\nself.height = self.height // 2\nself.ruleset = ruleset\nself.surface = pygame.Surface(dim)\nself.generation = [0] + [random.randint(0, 1) for i in range(self.width - 1)] + [0]",
"number = left * 4 + center * 2 + right\nif number == 7:\n if self.rule... | <|body_start_0|>
self.width, self.height = dim
self.width = self.width // 2
self.height = self.height // 2
self.ruleset = ruleset
self.surface = pygame.Surface(dim)
self.generation = [0] + [random.randint(0, 1) for i in range(self.width - 1)] + [0]
<|end_body_0|>
<|body_... | simple Cellular Automata - Wolfram Elementary | WolframElementary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WolframElementary:
"""simple Cellular Automata - Wolfram Elementary"""
def __init__(self, dim: tuple, ruleset: int):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
<|body_0|>
def rule(self, left: int, center: int, right: int) -> int:
... | stack_v2_sparse_classes_36k_train_031084 | 3,015 | no_license | [
{
"docstring": ":param dim: dimension of surface to draw on :param ruleset: ruleset to use",
"name": "__init__",
"signature": "def __init__(self, dim: tuple, ruleset: int)"
},
{
"docstring": "apply ruleset",
"name": "rule",
"signature": "def rule(self, left: int, center: int, right: int)... | 3 | stack_v2_sparse_classes_30k_train_003372 | Implement the Python class `WolframElementary` described below.
Class description:
simple Cellular Automata - Wolfram Elementary
Method signatures and docstrings:
- def __init__(self, dim: tuple, ruleset: int): :param dim: dimension of surface to draw on :param ruleset: ruleset to use
- def rule(self, left: int, cent... | Implement the Python class `WolframElementary` described below.
Class description:
simple Cellular Automata - Wolfram Elementary
Method signatures and docstrings:
- def __init__(self, dim: tuple, ruleset: int): :param dim: dimension of surface to draw on :param ruleset: ruleset to use
- def rule(self, left: int, cent... | 1fd421195a2888c0588a49f5a043a1110eedcdbf | <|skeleton|>
class WolframElementary:
"""simple Cellular Automata - Wolfram Elementary"""
def __init__(self, dim: tuple, ruleset: int):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
<|body_0|>
def rule(self, left: int, center: int, right: int) -> int:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WolframElementary:
"""simple Cellular Automata - Wolfram Elementary"""
def __init__(self, dim: tuple, ruleset: int):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
self.width, self.height = dim
self.width = self.width // 2
self.height = se... | the_stack_v2_python_sparse | effects/WolframElementary.py | gunny26/pygame | train | 5 |
c6a550a378f2cda7e85b6bd609568186edf62a06 | [
"filters, keywords = rest_utils.parse_filters_kwargs(request, ['session'])\nsession = keywords.get('session')\nif not session:\n session = env_api.Session.get_or_create_or_delete(request, environment)\ncomponent = api.muranoclient(request).services.get(environment, '/' + component, session)\nif component:\n r... | <|body_start_0|>
filters, keywords = rest_utils.parse_filters_kwargs(request, ['session'])
session = keywords.get('session')
if not session:
session = env_api.Session.get_or_create_or_delete(request, environment)
component = api.muranoclient(request).services.get(environment,... | API for Murano components Metadata | ComponentsMetadata | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComponentsMetadata:
"""API for Murano components Metadata"""
def get(self, request, environment, component):
"""Get a metadata object for a component in a given environment Example GET: http://localhost/api/app-catalog/environments/123/components/456/metadata The following get parame... | stack_v2_sparse_classes_36k_train_031085 | 6,096 | permissive | [
{
"docstring": "Get a metadata object for a component in a given environment Example GET: http://localhost/api/app-catalog/environments/123/components/456/metadata The following get parameters may be passed in the GET request: :param environment: identifier of the environment :param component: identifier of the... | 2 | null | Implement the Python class `ComponentsMetadata` described below.
Class description:
API for Murano components Metadata
Method signatures and docstrings:
- def get(self, request, environment, component): Get a metadata object for a component in a given environment Example GET: http://localhost/api/app-catalog/environm... | Implement the Python class `ComponentsMetadata` described below.
Class description:
API for Murano components Metadata
Method signatures and docstrings:
- def get(self, request, environment, component): Get a metadata object for a component in a given environment Example GET: http://localhost/api/app-catalog/environm... | 54e2ea8a71385b1c7624b3d2c8056bd8a2c2e2f7 | <|skeleton|>
class ComponentsMetadata:
"""API for Murano components Metadata"""
def get(self, request, environment, component):
"""Get a metadata object for a component in a given environment Example GET: http://localhost/api/app-catalog/environments/123/components/456/metadata The following get parame... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComponentsMetadata:
"""API for Murano components Metadata"""
def get(self, request, environment, component):
"""Get a metadata object for a component in a given environment Example GET: http://localhost/api/app-catalog/environments/123/components/456/metadata The following get parameters may be p... | the_stack_v2_python_sparse | muranodashboard/api/rest/environments.py | openstack/murano-dashboard | train | 38 |
22eab1ad986beb1fd7a5fdea21e6ee70e044ea06 | [
"for row in range(0, len(board)):\n for col in range(0, len(board[0])):\n board_copy = deepcopy(board)\n if self.existRecu(board_copy, word, row, col):\n return True\nreturn False",
"if len(word) == 0:\n return True\nelif row < 0 or row == len(board):\n return False\nelif col < 0... | <|body_start_0|>
for row in range(0, len(board)):
for col in range(0, len(board[0])):
board_copy = deepcopy(board)
if self.existRecu(board_copy, word, row, col):
return True
return False
<|end_body_0|>
<|body_start_1|>
if len(word)... | Solution_A | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_A:
def exist(self, board: List[List[str]], word: str) -> bool:
"""Use a recursive finder to recursively find the word in the matrix This is still an brutal force method to check every route until find the correct one. Exceeded max time limit when case is long."""
<|body_... | stack_v2_sparse_classes_36k_train_031086 | 10,401 | permissive | [
{
"docstring": "Use a recursive finder to recursively find the word in the matrix This is still an brutal force method to check every route until find the correct one. Exceeded max time limit when case is long.",
"name": "exist",
"signature": "def exist(self, board: List[List[str]], word: str) -> bool"
... | 2 | stack_v2_sparse_classes_30k_train_004174 | Implement the Python class `Solution_A` described below.
Class description:
Implement the Solution_A class.
Method signatures and docstrings:
- def exist(self, board: List[List[str]], word: str) -> bool: Use a recursive finder to recursively find the word in the matrix This is still an brutal force method to check ev... | Implement the Python class `Solution_A` described below.
Class description:
Implement the Solution_A class.
Method signatures and docstrings:
- def exist(self, board: List[List[str]], word: str) -> bool: Use a recursive finder to recursively find the word in the matrix This is still an brutal force method to check ev... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution_A:
def exist(self, board: List[List[str]], word: str) -> bool:
"""Use a recursive finder to recursively find the word in the matrix This is still an brutal force method to check every route until find the correct one. Exceeded max time limit when case is long."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution_A:
def exist(self, board: List[List[str]], word: str) -> bool:
"""Use a recursive finder to recursively find the word in the matrix This is still an brutal force method to check every route until find the correct one. Exceeded max time limit when case is long."""
for row in range(0, l... | the_stack_v2_python_sparse | LeetCode/LC079_word_search.py | jxie0755/Learning_Python | train | 0 | |
75340e4ccb2c340859344f55936952cbe6794341 | [
"providers = pq.get_providers()\nif not providers:\n return self.bad_response('Internal error')\nres = [{'id': p.id, 'title': p.title, 'link': p.link} for p in providers]\nreturn self.success_response({'providers': res})",
"data = request.get_json()\ntitle = data.get('title')\nlink = data.get('link')\nif not t... | <|body_start_0|>
providers = pq.get_providers()
if not providers:
return self.bad_response('Internal error')
res = [{'id': p.id, 'title': p.title, 'link': p.link} for p in providers]
return self.success_response({'providers': res})
<|end_body_0|>
<|body_start_1|>
dat... | ProviderHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProviderHandler:
def get(self):
"""Get providers list."""
<|body_0|>
def post(self):
"""{ 'title': str, 'link': str }"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
providers = pq.get_providers()
if not providers:
return self.ba... | stack_v2_sparse_classes_36k_train_031087 | 1,028 | no_license | [
{
"docstring": "Get providers list.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "{ 'title': str, 'link': str }",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018831 | Implement the Python class `ProviderHandler` described below.
Class description:
Implement the ProviderHandler class.
Method signatures and docstrings:
- def get(self): Get providers list.
- def post(self): { 'title': str, 'link': str } | Implement the Python class `ProviderHandler` described below.
Class description:
Implement the ProviderHandler class.
Method signatures and docstrings:
- def get(self): Get providers list.
- def post(self): { 'title': str, 'link': str }
<|skeleton|>
class ProviderHandler:
def get(self):
"""Get providers... | 8d3dfc06e0738e3e9547604d421788b4145fd971 | <|skeleton|>
class ProviderHandler:
def get(self):
"""Get providers list."""
<|body_0|>
def post(self):
"""{ 'title': str, 'link': str }"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProviderHandler:
def get(self):
"""Get providers list."""
providers = pq.get_providers()
if not providers:
return self.bad_response('Internal error')
res = [{'id': p.id, 'title': p.title, 'link': p.link} for p in providers]
return self.success_response({'pro... | the_stack_v2_python_sparse | app/handlers/provider.py | AleksandrFrolov/BackofficeSS | train | 0 | |
de1a59e11cf5e04112c8a67b84e527ba273b8d34 | [
"if not nums:\n return 0\nmydict = {}\nres = 1\nfor num in nums:\n if num in mydict.keys():\n continue\n mydict[num] = 1\n ll = num\n rr = num\n val = 1\n if num - 1 in mydict.keys():\n ll = num - mydict[num - 1]\n val += mydict[num - 1]\n if num + 1 in mydict.keys():\n ... | <|body_start_0|>
if not nums:
return 0
mydict = {}
res = 1
for num in nums:
if num in mydict.keys():
continue
mydict[num] = 1
ll = num
rr = num
val = 1
if num - 1 in mydict.keys():
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def longestConsecutive2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def longestConsecutive3(self, nums):
""":type nums: List[int]... | stack_v2_sparse_classes_36k_train_031088 | 2,537 | 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)"
},
{
"docst... | 3 | stack_v2_sparse_classes_30k_train_019806 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestConsecutive(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive2(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive3(self, num... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestConsecutive(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive2(self, nums): :type nums: List[int] :rtype: int
- def longestConsecutive3(self, num... | 690b685048c8e89d26047b6bc48b5f9af7d59cbb | <|skeleton|>
class Solution:
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def longestConsecutive2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def longestConsecutive3(self, nums):
""":type nums: List[int]... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestConsecutive(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 0
mydict = {}
res = 1
for num in nums:
if num in mydict.keys():
continue
mydict[num] = 1
ll = num
... | the_stack_v2_python_sparse | 数组/128. 最长连续序列.py | SimmonsChen/LeetCode | train | 0 | |
13cba416c87f67fb9e755b41b823511d7a8db3fa | [
"self.host = host\nself.port = port\nself.data = None",
"try:\n connection = Telnet(host=self.host, port=self.port, timeout=DEFAULT_TIMEOUT)\n data = connection.read_all().decode('ascii').lstrip('|').rstrip('|').split('||')\n self.data = {data[i].split('|')[0]: data[i] for i in range(0, len(data), 1)}\ne... | <|body_start_0|>
self.host = host
self.port = port
self.data = None
<|end_body_0|>
<|body_start_1|>
try:
connection = Telnet(host=self.host, port=self.port, timeout=DEFAULT_TIMEOUT)
data = connection.read_all().decode('ascii').lstrip('|').rstrip('|').split('||')
... | Get the latest data from HDDTemp and update the states. | HddTempData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HddTempData:
"""Get the latest data from HDDTemp and update the states."""
def __init__(self, host, port):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Get the latest data from HDDTemp running as daemon."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_031089 | 4,109 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, host, port)"
},
{
"docstring": "Get the latest data from HDDTemp running as daemon.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011423 | Implement the Python class `HddTempData` described below.
Class description:
Get the latest data from HDDTemp and update the states.
Method signatures and docstrings:
- def __init__(self, host, port): Initialize the data object.
- def update(self): Get the latest data from HDDTemp running as daemon. | Implement the Python class `HddTempData` described below.
Class description:
Get the latest data from HDDTemp and update the states.
Method signatures and docstrings:
- def __init__(self, host, port): Initialize the data object.
- def update(self): Get the latest data from HDDTemp running as daemon.
<|skeleton|>
cla... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class HddTempData:
"""Get the latest data from HDDTemp and update the states."""
def __init__(self, host, port):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Get the latest data from HDDTemp running as daemon."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HddTempData:
"""Get the latest data from HDDTemp and update the states."""
def __init__(self, host, port):
"""Initialize the data object."""
self.host = host
self.port = port
self.data = None
def update(self):
"""Get the latest data from HDDTemp running as dae... | the_stack_v2_python_sparse | homeassistant/components/hddtemp/sensor.py | home-assistant/core | train | 35,501 |
1c5fa355bff71df7a5c204eebc2ef78d4c101d54 | [
"arg_is_iter = False\nif len(args) == 1:\n arg_is_iter = True\n args = args[0]\nsymb_args = []\nres = initial_val\nnum_non_symbolic_args = 0\nfor x in args:\n if isinstance(x, Expression):\n symb_args.append(x)\n else:\n num_non_symbolic_args += 1\n res = builtin_f(res, x)\nif len(s... | <|body_start_0|>
arg_is_iter = False
if len(args) == 1:
arg_is_iter = True
args = args[0]
symb_args = []
res = initial_val
num_non_symbolic_args = 0
for x in args:
if isinstance(x, Expression):
symb_args.append(x)
... | MinMax_base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MinMax_base:
def eval_helper(self, this_f, builtin_f, initial_val, args):
"""EXAMPLES:: sage: max_symbolic(3,5,x) # indirect doctest max(x, 5) sage: min_symbolic(3,5,x) min(x, 3)"""
<|body_0|>
def __call__(self, *args, **kwds):
"""EXAMPLES:: sage: max_symbolic(3,5,x)... | stack_v2_sparse_classes_36k_train_031090 | 10,190 | no_license | [
{
"docstring": "EXAMPLES:: sage: max_symbolic(3,5,x) # indirect doctest max(x, 5) sage: min_symbolic(3,5,x) min(x, 3)",
"name": "eval_helper",
"signature": "def eval_helper(self, this_f, builtin_f, initial_val, args)"
},
{
"docstring": "EXAMPLES:: sage: max_symbolic(3,5,x) max(x, 5) sage: max_sy... | 2 | null | Implement the Python class `MinMax_base` described below.
Class description:
Implement the MinMax_base class.
Method signatures and docstrings:
- def eval_helper(self, this_f, builtin_f, initial_val, args): EXAMPLES:: sage: max_symbolic(3,5,x) # indirect doctest max(x, 5) sage: min_symbolic(3,5,x) min(x, 3)
- def __c... | Implement the Python class `MinMax_base` described below.
Class description:
Implement the MinMax_base class.
Method signatures and docstrings:
- def eval_helper(self, this_f, builtin_f, initial_val, args): EXAMPLES:: sage: max_symbolic(3,5,x) # indirect doctest max(x, 5) sage: min_symbolic(3,5,x) min(x, 3)
- def __c... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class MinMax_base:
def eval_helper(self, this_f, builtin_f, initial_val, args):
"""EXAMPLES:: sage: max_symbolic(3,5,x) # indirect doctest max(x, 5) sage: min_symbolic(3,5,x) min(x, 3)"""
<|body_0|>
def __call__(self, *args, **kwds):
"""EXAMPLES:: sage: max_symbolic(3,5,x)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MinMax_base:
def eval_helper(self, this_f, builtin_f, initial_val, args):
"""EXAMPLES:: sage: max_symbolic(3,5,x) # indirect doctest max(x, 5) sage: min_symbolic(3,5,x) min(x, 3)"""
arg_is_iter = False
if len(args) == 1:
arg_is_iter = True
args = args[0]
... | the_stack_v2_python_sparse | sage/src/sage/functions/min_max.py | bopopescu/geosci | train | 0 | |
df6de79959ed641a6accf7e227db5a3351d3a684 | [
"Turtle.__init__(self, shape='square', visible=False)\nself.speed(0)\nself.color(outlineColor, fillColor)\nself.up()\nself.goto(xPos, yPos)\nself.resizemode(rmode='user')\nself.shapesize(stretch_wid=length / 20, stretch_len=length / 20)\nself._text = text\nself._index = index\nself._grid = grid\nself.onclick(lambda... | <|body_start_0|>
Turtle.__init__(self, shape='square', visible=False)
self.speed(0)
self.color(outlineColor, fillColor)
self.up()
self.goto(xPos, yPos)
self.resizemode(rmode='user')
self.shapesize(stretch_wid=length / 20, stretch_len=length / 20)
self._tex... | Represents a Tic-Tac-Toe square. | Square | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Square:
"""Represents a Tic-Tac-Toe square."""
def __init__(self, index, grid, length, xPos, yPos, outlineColor='black', fillColor='white', text=EMPTY):
"""Sets the initial state of the Tic-Tac-Toe square."""
<|body_0|>
def text(self, text=None):
"""Getter, sette... | stack_v2_sparse_classes_36k_train_031091 | 1,091 | no_license | [
{
"docstring": "Sets the initial state of the Tic-Tac-Toe square.",
"name": "__init__",
"signature": "def __init__(self, index, grid, length, xPos, yPos, outlineColor='black', fillColor='white', text=EMPTY)"
},
{
"docstring": "Getter, setter for _text",
"name": "text",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_009249 | Implement the Python class `Square` described below.
Class description:
Represents a Tic-Tac-Toe square.
Method signatures and docstrings:
- def __init__(self, index, grid, length, xPos, yPos, outlineColor='black', fillColor='white', text=EMPTY): Sets the initial state of the Tic-Tac-Toe square.
- def text(self, text... | Implement the Python class `Square` described below.
Class description:
Represents a Tic-Tac-Toe square.
Method signatures and docstrings:
- def __init__(self, index, grid, length, xPos, yPos, outlineColor='black', fillColor='white', text=EMPTY): Sets the initial state of the Tic-Tac-Toe square.
- def text(self, text... | eb4c49115d100ff8cf0f77523db126b503a6611a | <|skeleton|>
class Square:
"""Represents a Tic-Tac-Toe square."""
def __init__(self, index, grid, length, xPos, yPos, outlineColor='black', fillColor='white', text=EMPTY):
"""Sets the initial state of the Tic-Tac-Toe square."""
<|body_0|>
def text(self, text=None):
"""Getter, sette... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Square:
"""Represents a Tic-Tac-Toe square."""
def __init__(self, index, grid, length, xPos, yPos, outlineColor='black', fillColor='white', text=EMPTY):
"""Sets the initial state of the Tic-Tac-Toe square."""
Turtle.__init__(self, shape='square', visible=False)
self.speed(0)
... | the_stack_v2_python_sparse | ticktactoe/square.py | chivitc1/python-turtle-learning | train | 0 |
d97991577af3fa405d7995ae49df4886b0476482 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file | AuthenticationServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticationServicer:
"""Missing associated documentation comment in .proto file"""
def authenticate(self, request, context):
"""Missing associated documentation comment in .proto file"""
<|body_0|>
def validateToken(self, request, context):
"""Missing associat... | stack_v2_sparse_classes_36k_train_031092 | 7,766 | no_license | [
{
"docstring": "Missing associated documentation comment in .proto file",
"name": "authenticate",
"signature": "def authenticate(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file",
"name": "validateToken",
"signature": "def validateToken(... | 2 | stack_v2_sparse_classes_30k_train_005596 | Implement the Python class `AuthenticationServicer` described below.
Class description:
Missing associated documentation comment in .proto file
Method signatures and docstrings:
- def authenticate(self, request, context): Missing associated documentation comment in .proto file
- def validateToken(self, request, conte... | Implement the Python class `AuthenticationServicer` described below.
Class description:
Missing associated documentation comment in .proto file
Method signatures and docstrings:
- def authenticate(self, request, context): Missing associated documentation comment in .proto file
- def validateToken(self, request, conte... | 626dae0efa20a66d1f69f49be15ab90c623ec33b | <|skeleton|>
class AuthenticationServicer:
"""Missing associated documentation comment in .proto file"""
def authenticate(self, request, context):
"""Missing associated documentation comment in .proto file"""
<|body_0|>
def validateToken(self, request, context):
"""Missing associat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthenticationServicer:
"""Missing associated documentation comment in .proto file"""
def authenticate(self, request, context):
"""Missing associated documentation comment in .proto file"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented... | the_stack_v2_python_sparse | svms-job-module-service/backup/connectors/vms_profile_manager/protoc/profile_manager_pb2_grpc.py | shankarmahato/Job_module | train | 0 |
039c842ad5c69d4b5fc35be04ef62a1ab981ae2c | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Proto file describing the keyword plan campaign keyword service. Service to manage Keyword Plan campaign keywords. KeywordPlanCampaign is required to add the campaign keywords. Only negative keywords are supported. A maximum of 1000 negative keywords are allowed per plan. This includes both campaign negative keywords a... | KeywordPlanCampaignKeywordServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeywordPlanCampaignKeywordServiceServicer:
"""Proto file describing the keyword plan campaign keyword service. Service to manage Keyword Plan campaign keywords. KeywordPlanCampaign is required to add the campaign keywords. Only negative keywords are supported. A maximum of 1000 negative keywords ... | stack_v2_sparse_classes_36k_train_031093 | 4,515 | permissive | [
{
"docstring": "Returns the requested plan in full detail.",
"name": "GetKeywordPlanCampaignKeyword",
"signature": "def GetKeywordPlanCampaignKeyword(self, request, context)"
},
{
"docstring": "Creates, updates, or removes Keyword Plan campaign keywords. Operation statuses are returned.",
"n... | 2 | null | Implement the Python class `KeywordPlanCampaignKeywordServiceServicer` described below.
Class description:
Proto file describing the keyword plan campaign keyword service. Service to manage Keyword Plan campaign keywords. KeywordPlanCampaign is required to add the campaign keywords. Only negative keywords are supporte... | Implement the Python class `KeywordPlanCampaignKeywordServiceServicer` described below.
Class description:
Proto file describing the keyword plan campaign keyword service. Service to manage Keyword Plan campaign keywords. KeywordPlanCampaign is required to add the campaign keywords. Only negative keywords are supporte... | a5b6cede64f4d9912ae6ad26927a54e40448c9fe | <|skeleton|>
class KeywordPlanCampaignKeywordServiceServicer:
"""Proto file describing the keyword plan campaign keyword service. Service to manage Keyword Plan campaign keywords. KeywordPlanCampaign is required to add the campaign keywords. Only negative keywords are supported. A maximum of 1000 negative keywords ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KeywordPlanCampaignKeywordServiceServicer:
"""Proto file describing the keyword plan campaign keyword service. Service to manage Keyword Plan campaign keywords. KeywordPlanCampaign is required to add the campaign keywords. Only negative keywords are supported. A maximum of 1000 negative keywords are allowed p... | the_stack_v2_python_sparse | google/ads/google_ads/v4/proto/services/keyword_plan_campaign_keyword_service_pb2_grpc.py | fiboknacky/google-ads-python | train | 0 |
310410e29abccbba00f653f0a1a27c482c9f8aab | [
"def rec(res, index, nums, path, k):\n if len(path) == k:\n path.sort()\n res.append(path)\n for i in range(index, len(nums)):\n if len(path + [nums[i]]) > k:\n continue\n rec(res, i + 1, nums, path + [nums[i]], k)\nnums = [i + 1 for i in range(n)]\nans = []\nrec(ans, 0,... | <|body_start_0|>
def rec(res, index, nums, path, k):
if len(path) == k:
path.sort()
res.append(path)
for i in range(index, len(nums)):
if len(path + [nums[i]]) > k:
continue
rec(res, i + 1, nums, path + [... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combine(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
<|body_0|>
def combine2(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def rec(res, index, ... | stack_v2_sparse_classes_36k_train_031094 | 1,299 | no_license | [
{
"docstring": ":type n: int :type k: int :rtype: List[List[int]]",
"name": "combine",
"signature": "def combine(self, n, k)"
},
{
"docstring": ":type n: int :type k: int :rtype: List[List[int]]",
"name": "combine2",
"signature": "def combine2(self, n, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015113 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combine(self, n, k): :type n: int :type k: int :rtype: List[List[int]]
- def combine2(self, n, k): :type n: int :type k: int :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combine(self, n, k): :type n: int :type k: int :rtype: List[List[int]]
- def combine2(self, n, k): :type n: int :type k: int :rtype: List[List[int]]
<|skeleton|>
class Solut... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def combine(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
<|body_0|>
def combine2(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def combine(self, n, k):
""":type n: int :type k: int :rtype: List[List[int]]"""
def rec(res, index, nums, path, k):
if len(path) == k:
path.sort()
res.append(path)
for i in range(index, len(nums)):
if len(path +... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00077.Combinations.py | roger6blog/LeetCode | train | 0 | |
100da2ddcf49bdf1bdacb19482975c831c77fc6d | [
"try:\n result = data.HbaseManager().create_table(baseid, tb)\n return_data = {'status': '200', 'result': result}\n return Response(json.dumps(return_data))\nexcept Exception as e:\n return_data = {'status': '400', 'result': str(e)}\n return Response(json.dumps(return_data))",
"try:\n result = d... | <|body_start_0|>
try:
result = data.HbaseManager().create_table(baseid, tb)
return_data = {'status': '200', 'result': result}
return Response(json.dumps(return_data))
except Exception as e:
return_data = {'status': '400', 'result': str(e)}
retu... | 1. Name : DataFrameTable (step 4) 2. Steps - WDNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/job/{nnid}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/data/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/data/{args}... | DataFrameTable | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataFrameTable:
"""1. Name : DataFrameTable (step 4) 2. Steps - WDNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/job/{nnid}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/data/ - post /api/v1/type/data... | stack_v2_sparse_classes_36k_train_031095 | 3,100 | no_license | [
{
"docstring": "- desc :create table with given name",
"name": "post",
"signature": "def post(self, request, baseid, tb)"
},
{
"docstring": "- desc : return all table",
"name": "get",
"signature": "def get(self, request, baseid)"
},
{
"docstring": "- desc : rename table - Request... | 4 | null | Implement the Python class `DataFrameTable` described below.
Class description:
1. Name : DataFrameTable (step 4) 2. Steps - WDNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/job/{nnid}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/ - post /api/v1/type/dataframe/base/{baseid}/ta... | Implement the Python class `DataFrameTable` described below.
Class description:
1. Name : DataFrameTable (step 4) 2. Steps - WDNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/job/{nnid}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/ - post /api/v1/type/dataframe/base/{baseid}/ta... | ef058737f391de817c74398ef9a5d3a28f973c98 | <|skeleton|>
class DataFrameTable:
"""1. Name : DataFrameTable (step 4) 2. Steps - WDNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/job/{nnid}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/data/ - post /api/v1/type/data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataFrameTable:
"""1. Name : DataFrameTable (step 4) 2. Steps - WDNN essential steps - post /api/v1/type/common/env/ - post /api/v1/type/common/job/{nnid}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/ - post /api/v1/type/dataframe/base/{baseid}/table/{tb}/data/ - post /api/v1/type/dataframe/base/{b... | the_stack_v2_python_sparse | tfmsarest/views/dataframe_table.py | TensorMSA/tensormsa_old | train | 6 |
ac5c682e4e85ebd08c4afb0951cb85232014b83b | [
"self.smtp_server = settings.SMTP_HOST\nself.port = settings.SMTP_PORT\nself.sender_email = settings.SMTP_USER\nself.password = settings.SMTP_PASS\nself.receiver_email = to\nself.message = MIMEMultipart('alternative')\nself.message['Subject'] = subject\nself.message['From'] = self.sender_email\nself.message['To'] =... | <|body_start_0|>
self.smtp_server = settings.SMTP_HOST
self.port = settings.SMTP_PORT
self.sender_email = settings.SMTP_USER
self.password = settings.SMTP_PASS
self.receiver_email = to
self.message = MIMEMultipart('alternative')
self.message['Subject'] = subject
... | Class to support the mailing settings and actions | MailSender | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailSender:
"""Class to support the mailing settings and actions"""
def __init__(self, html, subject, text, to):
"""This method will facilitate the setup of the mail service, as well as the message building process :param html: message in html format :param subject: message subject :... | stack_v2_sparse_classes_36k_train_031096 | 2,143 | no_license | [
{
"docstring": "This method will facilitate the setup of the mail service, as well as the message building process :param html: message in html format :param subject: message subject :param text: message in plain text :param to: destination mail info",
"name": "__init__",
"signature": "def __init__(self... | 2 | stack_v2_sparse_classes_30k_train_011516 | Implement the Python class `MailSender` described below.
Class description:
Class to support the mailing settings and actions
Method signatures and docstrings:
- def __init__(self, html, subject, text, to): This method will facilitate the setup of the mail service, as well as the message building process :param html:... | Implement the Python class `MailSender` described below.
Class description:
Class to support the mailing settings and actions
Method signatures and docstrings:
- def __init__(self, html, subject, text, to): This method will facilitate the setup of the mail service, as well as the message building process :param html:... | e4c228b90add962640b04b66e2952ce2502215c5 | <|skeleton|>
class MailSender:
"""Class to support the mailing settings and actions"""
def __init__(self, html, subject, text, to):
"""This method will facilitate the setup of the mail service, as well as the message building process :param html: message in html format :param subject: message subject :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MailSender:
"""Class to support the mailing settings and actions"""
def __init__(self, html, subject, text, to):
"""This method will facilitate the setup of the mail service, as well as the message building process :param html: message in html format :param subject: message subject :param text: m... | the_stack_v2_python_sparse | status/mail_sender.py | Ampath-Summer-2020/Ampath-Summer-2020 | train | 1 |
f477fc0823af961884e87f5a90b3f8a698e20024 | [
"super(RtuQuery, self).__init__()\nself._request_address = 0\nself._response_address = 0",
"self._request_address = slave\nif self._request_address < 0 or self._request_address > 255:\n raise InvalidArgumentError('Invalid address {0}'.format(self._request_address))\ndata = struct.pack('>B', self._request_addre... | <|body_start_0|>
super(RtuQuery, self).__init__()
self._request_address = 0
self._response_address = 0
<|end_body_0|>
<|body_start_1|>
self._request_address = slave
if self._request_address < 0 or self._request_address > 255:
raise InvalidArgumentError('Invalid addre... | Subclass of a Query. Adds the Modbus RTU specific part of the protocol | RtuQuery | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RtuQuery:
"""Subclass of a Query. Adds the Modbus RTU specific part of the protocol"""
def __init__(self):
"""Constructor"""
<|body_0|>
def build_request(self, pdu, slave):
"""Add the Modbus RTU part to the request"""
<|body_1|>
def parse_response(se... | stack_v2_sparse_classes_36k_train_031097 | 9,056 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Add the Modbus RTU part to the request",
"name": "build_request",
"signature": "def build_request(self, pdu, slave)"
},
{
"docstring": "Extract the pdu from the Modbus RTU respo... | 5 | null | Implement the Python class `RtuQuery` described below.
Class description:
Subclass of a Query. Adds the Modbus RTU specific part of the protocol
Method signatures and docstrings:
- def __init__(self): Constructor
- def build_request(self, pdu, slave): Add the Modbus RTU part to the request
- def parse_response(self, ... | Implement the Python class `RtuQuery` described below.
Class description:
Subclass of a Query. Adds the Modbus RTU specific part of the protocol
Method signatures and docstrings:
- def __init__(self): Constructor
- def build_request(self, pdu, slave): Add the Modbus RTU part to the request
- def parse_response(self, ... | a5aeb1238b26c1af55cf3a82787ed347dff1fb86 | <|skeleton|>
class RtuQuery:
"""Subclass of a Query. Adds the Modbus RTU specific part of the protocol"""
def __init__(self):
"""Constructor"""
<|body_0|>
def build_request(self, pdu, slave):
"""Add the Modbus RTU part to the request"""
<|body_1|>
def parse_response(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RtuQuery:
"""Subclass of a Query. Adds the Modbus RTU specific part of the protocol"""
def __init__(self):
"""Constructor"""
super(RtuQuery, self).__init__()
self._request_address = 0
self._response_address = 0
def build_request(self, pdu, slave):
"""Add the M... | the_stack_v2_python_sparse | external/modbus_tk/modbus_tk/modbus_rtu.py | intel/intel-device-resource-mgt-lib | train | 2 |
1b78c7d9d8a926db4786577ea8ebd650eecd1d3c | [
"super(LandmarkGeneratorHeatmap, self).__init__(dim, output_size, landmark_indizes, landmark_flip_pairs, data_format, pre_transformation, post_transformation)\nself.output_size_np = list(reversed(self.output_size))\nself.sigma = sigma\nself.scale_factor = scale_factor\nself.normalize_center = normalize_center",
"... | <|body_start_0|>
super(LandmarkGeneratorHeatmap, self).__init__(dim, output_size, landmark_indizes, landmark_flip_pairs, data_format, pre_transformation, post_transformation)
self.output_size_np = list(reversed(self.output_size))
self.sigma = sigma
self.scale_factor = scale_factor
... | Generates images of Gaussian heatmaps | LandmarkGeneratorHeatmap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LandmarkGeneratorHeatmap:
"""Generates images of Gaussian heatmaps"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformation=None):
"""Init... | stack_v2_sparse_classes_36k_train_031098 | 16,690 | no_license | [
{
"docstring": "Initializer :param output_size: output image size :param sigma: Gaussian sigma :param scale_factor: heatmap scale factor, each value of the Gaussian will be multiplied with this value :param normalize_center: if True, the value on the center is set to scale_factor otherwise, the default gaussian... | 2 | stack_v2_sparse_classes_30k_train_015575 | Implement the Python class `LandmarkGeneratorHeatmap` described below.
Class description:
Generates images of Gaussian heatmaps
Method signatures and docstrings:
- def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first',... | Implement the Python class `LandmarkGeneratorHeatmap` described below.
Class description:
Generates images of Gaussian heatmaps
Method signatures and docstrings:
- def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first',... | ef6cee91264ba1fe6b40d9823a07647b95bcc2c4 | <|skeleton|>
class LandmarkGeneratorHeatmap:
"""Generates images of Gaussian heatmaps"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformation=None):
"""Init... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LandmarkGeneratorHeatmap:
"""Generates images of Gaussian heatmaps"""
def __init__(self, dim, output_size, sigma, scale_factor, normalize_center, landmark_indizes=None, landmark_flip_pairs=None, data_format='channels_first', pre_transformation=None, post_transformation=None):
"""Initializer :para... | the_stack_v2_python_sparse | generators/landmark_generator.py | XiaoweiXu/MedicalDataAugmentationTool | train | 1 |
594de2f782273a947aab6a1e2a3b48b02493c2af | [
"self.mesh_name = mesh_name\nself.repo_mesh_name = mesh_name + 'Repo'\nprint('[MeshInfo] Repository name: {0:s}'.format(self.repo_mesh_name))\nif int(sv.Repository.Exists(self.repo_mesh_name)):\n print('[MeshInfo] {0:s} is already in the repository.'.format(self.repo_mesh_name))\nelse:\n sv.GUI.ExportMeshToRe... | <|body_start_0|>
self.mesh_name = mesh_name
self.repo_mesh_name = mesh_name + 'Repo'
print('[MeshInfo] Repository name: {0:s}'.format(self.repo_mesh_name))
if int(sv.Repository.Exists(self.repo_mesh_name)):
print('[MeshInfo] {0:s} is already in the repository.'.format(self.re... | This class is used to print mesh information. | MeshInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MeshInfo:
"""This class is used to print mesh information."""
def __init__(self, mesh_name):
"""Initialize the MeshInfo object Args: mesh_name (string): The name of a SimVascular Meshes data node."""
<|body_0|>
def print_nodes(self, ofile=sys.stdout):
"""Print th... | stack_v2_sparse_classes_36k_train_031099 | 6,127 | no_license | [
{
"docstring": "Initialize the MeshInfo object Args: mesh_name (string): The name of a SimVascular Meshes data node.",
"name": "__init__",
"signature": "def __init__(self, mesh_name)"
},
{
"docstring": "Print the mesh nodal coordinates.",
"name": "print_nodes",
"signature": "def print_no... | 5 | stack_v2_sparse_classes_30k_train_002141 | Implement the Python class `MeshInfo` described below.
Class description:
This class is used to print mesh information.
Method signatures and docstrings:
- def __init__(self, mesh_name): Initialize the MeshInfo object Args: mesh_name (string): The name of a SimVascular Meshes data node.
- def print_nodes(self, ofile=... | Implement the Python class `MeshInfo` described below.
Class description:
This class is used to print mesh information.
Method signatures and docstrings:
- def __init__(self, mesh_name): Initialize the MeshInfo object Args: mesh_name (string): The name of a SimVascular Meshes data node.
- def print_nodes(self, ofile=... | d2db6cdec30225fd89a37e9ef7dc99dfdb25d4a3 | <|skeleton|>
class MeshInfo:
"""This class is used to print mesh information."""
def __init__(self, mesh_name):
"""Initialize the MeshInfo object Args: mesh_name (string): The name of a SimVascular Meshes data node."""
<|body_0|>
def print_nodes(self, ofile=sys.stdout):
"""Print th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MeshInfo:
"""This class is used to print mesh information."""
def __init__(self, mesh_name):
"""Initialize the MeshInfo object Args: mesh_name (string): The name of a SimVascular Meshes data node."""
self.mesh_name = mesh_name
self.repo_mesh_name = mesh_name + 'Repo'
print... | the_stack_v2_python_sparse | simvascular-python-scripts/mesh_info.py | Arash67/cardiovascular | train | 0 |
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