blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d6ca8dd435162d3a0bf9409e984136bf54671cd9 | [
"currency_code = currency_for_request(request)\ncurrency = Currency.objects.all_accepted().get(iso_4217_code=currency_code)\nserializer = CurrencySerializer(currency)\nreturn Response(serializer.data)",
"serializer = CurrencySessionSerializer(data=request.data)\nif serializer.is_valid():\n currency_code = seri... | <|body_start_0|>
currency_code = currency_for_request(request)
currency = Currency.objects.all_accepted().get(iso_4217_code=currency_code)
serializer = CurrencySerializer(currency)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
serializer = CurrencySessionSeria... | CurrencySessionAPIView | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CurrencySessionAPIView:
def get(self, request, *args, **kwargs):
"""Return the currency for the request."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Set the currency in the session."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
curr... | stack_v2_sparse_classes_36k_train_022500 | 2,594 | permissive | [
{
"docstring": "Return the currency for the request.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Set the currency in the session.",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | null | Implement the Python class `CurrencySessionAPIView` described below.
Class description:
Implement the CurrencySessionAPIView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Return the currency for the request.
- def post(self, request, *args, **kwargs): Set the currency in the sess... | Implement the Python class `CurrencySessionAPIView` described below.
Class description:
Implement the CurrencySessionAPIView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Return the currency for the request.
- def post(self, request, *args, **kwargs): Set the currency in the sess... | c2814749c547349ff63415bdc81f53eb1215c7c0 | <|skeleton|>
class CurrencySessionAPIView:
def get(self, request, *args, **kwargs):
"""Return the currency for the request."""
<|body_0|>
def post(self, request, *args, **kwargs):
"""Set the currency in the session."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CurrencySessionAPIView:
def get(self, request, *args, **kwargs):
"""Return the currency for the request."""
currency_code = currency_for_request(request)
currency = Currency.objects.all_accepted().get(iso_4217_code=currency_code)
serializer = CurrencySerializer(currency)
... | the_stack_v2_python_sparse | satchmo/currency/api/views.py | ToeKnee/jelly-roll | train | 0 | |
330c511f0f6f06d060ecc82374f7ed169e72094e | [
"self.data = None\nself._hass = hass\nself._app_id = app_id\nself._device_id = device_id\nself._values = values\nself._url = TTN_DATA_STORAGE_URL.format(app_id=app_id, endpoint='api/v2/query', device_id=device_id)\nself._headers = {ACCEPT: CONTENT_TYPE_JSON, AUTHORIZATION: f'key {access_key}'}",
"try:\n sessio... | <|body_start_0|>
self.data = None
self._hass = hass
self._app_id = app_id
self._device_id = device_id
self._values = values
self._url = TTN_DATA_STORAGE_URL.format(app_id=app_id, endpoint='api/v2/query', device_id=device_id)
self._headers = {ACCEPT: CONTENT_TYPE_J... | Get the latest data from The Things Network Data Storage. | TtnDataStorage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TtnDataStorage:
"""Get the latest data from The Things Network Data Storage."""
def __init__(self, hass, app_id, device_id, access_key, values):
"""Initialize the data object."""
<|body_0|>
async def async_update(self):
"""Get the current state from The Things Ne... | stack_v2_sparse_classes_36k_train_022501 | 5,254 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, hass, app_id, device_id, access_key, values)"
},
{
"docstring": "Get the current state from The Things Network Data Storage.",
"name": "async_update",
"signature": "async def async_update(s... | 2 | stack_v2_sparse_classes_30k_train_012851 | Implement the Python class `TtnDataStorage` described below.
Class description:
Get the latest data from The Things Network Data Storage.
Method signatures and docstrings:
- def __init__(self, hass, app_id, device_id, access_key, values): Initialize the data object.
- async def async_update(self): Get the current sta... | Implement the Python class `TtnDataStorage` described below.
Class description:
Get the latest data from The Things Network Data Storage.
Method signatures and docstrings:
- def __init__(self, hass, app_id, device_id, access_key, values): Initialize the data object.
- async def async_update(self): Get the current sta... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class TtnDataStorage:
"""Get the latest data from The Things Network Data Storage."""
def __init__(self, hass, app_id, device_id, access_key, values):
"""Initialize the data object."""
<|body_0|>
async def async_update(self):
"""Get the current state from The Things Ne... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TtnDataStorage:
"""Get the latest data from The Things Network Data Storage."""
def __init__(self, hass, app_id, device_id, access_key, values):
"""Initialize the data object."""
self.data = None
self._hass = hass
self._app_id = app_id
self._device_id = device_id
... | the_stack_v2_python_sparse | homeassistant/components/thethingsnetwork/sensor.py | home-assistant/core | train | 35,501 |
90748831127ee2c6594153a8350142c2c7888bbe | [
"res = Instrument.objects.all()\nif scenario_id:\n rs = RoadSegment.objects.filter(scenario__id=scenario_id).all()\n rc = RoadCondition.objects.filter(road_segment_road_condition__in=rs).all()\n rca = RoadConditionAction.objects.filter(road_condition_road_condition_actions__in=rc).all()\n ia = Instrumen... | <|body_start_0|>
res = Instrument.objects.all()
if scenario_id:
rs = RoadSegment.objects.filter(scenario__id=scenario_id).all()
rc = RoadCondition.objects.filter(road_segment_road_condition__in=rs).all()
rca = RoadConditionAction.objects.filter(road_condition_road_con... | Query | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Query:
def resolve_instruments(self, info, instrument_id=None, name=None, instrument_type_id=None, instrument_system_id=None, desc=None, folder_id=None, scenario_id=None, label_name=None, **kwargs):
"""Queries instruments from the database :param label_name: :param info: :param instrumen... | stack_v2_sparse_classes_36k_train_022502 | 9,470 | no_license | [
{
"docstring": "Queries instruments from the database :param label_name: :param info: :param instrument_id: The instrument ID to filter on :param name: The (part of the) name to filter on :param instrument_type_id: The instrument_type ID to filter on :param instrument_system_id: The instrument_system ID to filt... | 3 | null | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def resolve_instruments(self, info, instrument_id=None, name=None, instrument_type_id=None, instrument_system_id=None, desc=None, folder_id=None, scenario_id=None, label_name=None, **k... | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def resolve_instruments(self, info, instrument_id=None, name=None, instrument_type_id=None, instrument_system_id=None, desc=None, folder_id=None, scenario_id=None, label_name=None, **k... | 618440303dcbf819cd61aa5e593b4b50483f0070 | <|skeleton|>
class Query:
def resolve_instruments(self, info, instrument_id=None, name=None, instrument_type_id=None, instrument_system_id=None, desc=None, folder_id=None, scenario_id=None, label_name=None, **kwargs):
"""Queries instruments from the database :param label_name: :param info: :param instrumen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Query:
def resolve_instruments(self, info, instrument_id=None, name=None, instrument_type_id=None, instrument_system_id=None, desc=None, folder_id=None, scenario_id=None, label_name=None, **kwargs):
"""Queries instruments from the database :param label_name: :param info: :param instrument_id: The inst... | the_stack_v2_python_sparse | backend/api/instruments/schema.py | Rohan-Deshamudre/Smart-traffic-management-system | train | 0 | |
7db6f15b378c878d272b9d49ed79750117d32712 | [
"node_data = dict(id='node' + node['id'], type=node['labels'][0])\nif node.get('properties'):\n node_data.update(node['properties'])\nreturn {'data': node_data}",
"edge_data = dict(id='edge' + edge['id'], type=edge['type'], source='node' + edge['startNode'], target='node' + edge['endNode'])\nif edge.get('prope... | <|body_start_0|>
node_data = dict(id='node' + node['id'], type=node['labels'][0])
if node.get('properties'):
node_data.update(node['properties'])
return {'data': node_data}
<|end_body_0|>
<|body_start_1|>
edge_data = dict(id='edge' + edge['id'], type=edge['type'], source='no... | Cytoscape formatter. This formatter will return the graph compatible with the open source graph Javascript library Cytoscape (http://js.cytoscape.org/). | CytoscapeOutputFormatter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CytoscapeOutputFormatter:
"""Cytoscape formatter. This formatter will return the graph compatible with the open source graph Javascript library Cytoscape (http://js.cytoscape.org/)."""
def format_node(self, node):
"""Format a Cytoscape graph node. Args: node: A dictionary with one no... | stack_v2_sparse_classes_36k_train_022503 | 8,202 | permissive | [
{
"docstring": "Format a Cytoscape graph node. Args: node: A dictionary with one node Returns: Dictionary with a Cytoscape formatted node",
"name": "format_node",
"signature": "def format_node(self, node)"
},
{
"docstring": "Format a Cytoscape graph egde. Args: edge: A dictionary with one edge R... | 2 | stack_v2_sparse_classes_30k_train_016063 | Implement the Python class `CytoscapeOutputFormatter` described below.
Class description:
Cytoscape formatter. This formatter will return the graph compatible with the open source graph Javascript library Cytoscape (http://js.cytoscape.org/).
Method signatures and docstrings:
- def format_node(self, node): Format a C... | Implement the Python class `CytoscapeOutputFormatter` described below.
Class description:
Cytoscape formatter. This formatter will return the graph compatible with the open source graph Javascript library Cytoscape (http://js.cytoscape.org/).
Method signatures and docstrings:
- def format_node(self, node): Format a C... | e0c833151c28e940103c3034f4cb26b1eb81750e | <|skeleton|>
class CytoscapeOutputFormatter:
"""Cytoscape formatter. This formatter will return the graph compatible with the open source graph Javascript library Cytoscape (http://js.cytoscape.org/)."""
def format_node(self, node):
"""Format a Cytoscape graph node. Args: node: A dictionary with one no... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CytoscapeOutputFormatter:
"""Cytoscape formatter. This formatter will return the graph compatible with the open source graph Javascript library Cytoscape (http://js.cytoscape.org/)."""
def format_node(self, node):
"""Format a Cytoscape graph node. Args: node: A dictionary with one node Returns: D... | the_stack_v2_python_sparse | timesketch/lib/datastores/neo4j.py | LDO-CERT/timesketch | train | 1 |
32823a1bc17d31398adf4dd83dd0f50127a45e62 | [
"del kwargs\nsleep(1)\nreturn read_pd_df(self._DATA_DEFS.get(ioc_type), ioc_type)",
"if isinstance(results, pd.DataFrame):\n return results\nreturn pd.DataFrame()"
] | <|body_start_0|>
del kwargs
sleep(1)
return read_pd_df(self._DATA_DEFS.get(ioc_type), ioc_type)
<|end_body_0|>
<|body_start_1|>
if isinstance(results, pd.DataFrame):
return results
return pd.DataFrame()
<|end_body_1|>
| TILookup demo class. | TILookupDemo | [
"LicenseRef-scancode-generic-cla",
"LGPL-3.0-only",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown",
"ISC",
"LGPL-2.0-or-later",
"PSF-2.0",
"Apache-2.0",
"BSD-2-Clause",
"LGPL-2.1-only",
"Unlicense",
"Python-2.0",
"LicenseRef-scancode-python-cwi",
"MIT",
"LGPL-2.1-or-later",
"GPL-2.... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TILookupDemo:
"""TILookup demo class."""
def lookup_ioc(self, ioc_type, **kwargs):
"""Lookup single IoC."""
<|body_0|>
def result_to_df(results):
"""Convert IoC results to DataFrame."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
del kwargs
... | stack_v2_sparse_classes_36k_train_022504 | 7,922 | permissive | [
{
"docstring": "Lookup single IoC.",
"name": "lookup_ioc",
"signature": "def lookup_ioc(self, ioc_type, **kwargs)"
},
{
"docstring": "Convert IoC results to DataFrame.",
"name": "result_to_df",
"signature": "def result_to_df(results)"
}
] | 2 | null | Implement the Python class `TILookupDemo` described below.
Class description:
TILookup demo class.
Method signatures and docstrings:
- def lookup_ioc(self, ioc_type, **kwargs): Lookup single IoC.
- def result_to_df(results): Convert IoC results to DataFrame. | Implement the Python class `TILookupDemo` described below.
Class description:
TILookup demo class.
Method signatures and docstrings:
- def lookup_ioc(self, ioc_type, **kwargs): Lookup single IoC.
- def result_to_df(results): Convert IoC results to DataFrame.
<|skeleton|>
class TILookupDemo:
"""TILookup demo clas... | 44b1a390510f9be2772ec62cb95d0fc67dfc234b | <|skeleton|>
class TILookupDemo:
"""TILookup demo class."""
def lookup_ioc(self, ioc_type, **kwargs):
"""Lookup single IoC."""
<|body_0|>
def result_to_df(results):
"""Convert IoC results to DataFrame."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TILookupDemo:
"""TILookup demo class."""
def lookup_ioc(self, ioc_type, **kwargs):
"""Lookup single IoC."""
del kwargs
sleep(1)
return read_pd_df(self._DATA_DEFS.get(ioc_type), ioc_type)
def result_to_df(results):
"""Convert IoC results to DataFrame."""
... | the_stack_v2_python_sparse | tools/mp_demo_data.py | RiskIQ/msticpy | train | 1 |
dc312aa954ab604b6fa2b6584a6586ca2253a8b2 | [
"OptimizerBase.__init__(self, disp)\nself.n_epoch = n_epoch\nself.iter_per_epoch = iter_per_epoch\nself.maxiter = int(self.n_epoch * self.iter_per_epoch)\nself.print_freq = int(self.print_freq * self.iter_per_epoch)\nself.step_rate = step_rate\nself.decay = decay\nself.momentum = momentum\nself.offset = offset",
... | <|body_start_0|>
OptimizerBase.__init__(self, disp)
self.n_epoch = n_epoch
self.iter_per_epoch = iter_per_epoch
self.maxiter = int(self.n_epoch * self.iter_per_epoch)
self.print_freq = int(self.print_freq * self.iter_per_epoch)
self.step_rate = step_rate
self.deca... | A wrapper-class for AdaDelta method from climin library. Requires gradient estimation. | AdaDelta | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdaDelta:
"""A wrapper-class for AdaDelta method from climin library. Requires gradient estimation."""
def __init__(self, disp=False, iter_per_epoch=1, n_epoch=1000, step_rate=1.0, decay=0.9, momentum=0.0, offset=0.0001):
""":param iter_per_epoch: number of iteration per epoch :param... | stack_v2_sparse_classes_36k_train_022505 | 4,677 | no_license | [
{
"docstring": ":param iter_per_epoch: number of iteration per epoch :param n_epoch: maximum number of epochs (or iterations if no sample_size is provided) The names of the other parameters are the same as in the corresponding climin method :param step_rate: step size of the method :param decay: decay of the mo... | 2 | stack_v2_sparse_classes_30k_val_000199 | Implement the Python class `AdaDelta` described below.
Class description:
A wrapper-class for AdaDelta method from climin library. Requires gradient estimation.
Method signatures and docstrings:
- def __init__(self, disp=False, iter_per_epoch=1, n_epoch=1000, step_rate=1.0, decay=0.9, momentum=0.0, offset=0.0001): :p... | Implement the Python class `AdaDelta` described below.
Class description:
A wrapper-class for AdaDelta method from climin library. Requires gradient estimation.
Method signatures and docstrings:
- def __init__(self, disp=False, iter_per_epoch=1, n_epoch=1000, step_rate=1.0, decay=0.9, momentum=0.0, offset=0.0001): :p... | fbc0be813096f21e02e9f8d306df1c21f7e006a7 | <|skeleton|>
class AdaDelta:
"""A wrapper-class for AdaDelta method from climin library. Requires gradient estimation."""
def __init__(self, disp=False, iter_per_epoch=1, n_epoch=1000, step_rate=1.0, decay=0.9, momentum=0.0, offset=0.0001):
""":param iter_per_epoch: number of iteration per epoch :param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdaDelta:
"""A wrapper-class for AdaDelta method from climin library. Requires gradient estimation."""
def __init__(self, disp=False, iter_per_epoch=1, n_epoch=1000, step_rate=1.0, decay=0.9, momentum=0.0, offset=0.0001):
""":param iter_per_epoch: number of iteration per epoch :param n_epoch: max... | the_stack_v2_python_sparse | gplib/optim/methods/wrappers.py | izmailovpavel/gplib | train | 2 |
bfa0457e263c20e92bf7be278d54247cc18aa0db | [
"m, n = (len(nums1), len(nums2))\nif m > n:\n return self.findMediaSortedArrays(nums2, nums1)\nif m == 0:\n return 0.5 * (nums2[(n - 1) // 2] + nums[n // 2])\ncut = (m + n) // 2\nlo, hi = (0, m)\nMIN, MAX = (float('-inf'), float('inf'))\nwhile True:\n cut1 = lo + (hi - lo) // 2\n cut2 = cut - cut1\n ... | <|body_start_0|>
m, n = (len(nums1), len(nums2))
if m > n:
return self.findMediaSortedArrays(nums2, nums1)
if m == 0:
return 0.5 * (nums2[(n - 1) // 2] + nums[n // 2])
cut = (m + n) // 2
lo, hi = (0, m)
MIN, MAX = (float('-inf'), float('inf'))
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMediaSortedArrays1(self, nums1: List[int], nums2: List[int]) -> float:
"""binary search: search cutting points cut1 & cut2 in nums1 and nums2 so that cut1 + cut2 == (len(nums1) + len(nums2)) // 2 and nums1[cut1-1] <= nums2[cut2] and nums1[cut1] >= nums2[cut2-1] time: O(... | stack_v2_sparse_classes_36k_train_022506 | 2,528 | no_license | [
{
"docstring": "binary search: search cutting points cut1 & cut2 in nums1 and nums2 so that cut1 + cut2 == (len(nums1) + len(nums2)) // 2 and nums1[cut1-1] <= nums2[cut2] and nums1[cut1] >= nums2[cut2-1] time: O(log(min(m, n))) space: O(1)",
"name": "findMediaSortedArrays1",
"signature": "def findMediaS... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMediaSortedArrays1(self, nums1: List[int], nums2: List[int]) -> float: binary search: search cutting points cut1 & cut2 in nums1 and nums2 so that cut1 + cut2 == (len(num... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMediaSortedArrays1(self, nums1: List[int], nums2: List[int]) -> float: binary search: search cutting points cut1 & cut2 in nums1 and nums2 so that cut1 + cut2 == (len(num... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def findMediaSortedArrays1(self, nums1: List[int], nums2: List[int]) -> float:
"""binary search: search cutting points cut1 & cut2 in nums1 and nums2 so that cut1 + cut2 == (len(nums1) + len(nums2)) // 2 and nums1[cut1-1] <= nums2[cut2] and nums1[cut1] >= nums2[cut2-1] time: O(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMediaSortedArrays1(self, nums1: List[int], nums2: List[int]) -> float:
"""binary search: search cutting points cut1 & cut2 in nums1 and nums2 so that cut1 + cut2 == (len(nums1) + len(nums2)) // 2 and nums1[cut1-1] <= nums2[cut2] and nums1[cut1] >= nums2[cut2-1] time: O(log(min(m, n))... | the_stack_v2_python_sparse | Leetcode 0004. Median of Two Sorted Arrays.py | Chaoran-sjsu/leetcode | train | 0 | |
06caf0cb733db96dfbba5c34355065cb61dd2747 | [
"self.db_url = _mask_uri(db_url)\nself.client = MDBClient(db_url)\nself.db = self.client.get()\nself._query_collection = self.db[CatalogConstants.catalog_collections['query']]\nself._feature_collection = self.db[CatalogConstants.catalog_collections['feature']]\nself._model_collection = self.db[CatalogConstants.cata... | <|body_start_0|>
self.db_url = _mask_uri(db_url)
self.client = MDBClient(db_url)
self.db = self.client.get()
self._query_collection = self.db[CatalogConstants.catalog_collections['query']]
self._feature_collection = self.db[CatalogConstants.catalog_collections['feature']]
... | Catalog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Catalog:
def __init__(self, db_url: str):
"""initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url"""
<|body_0|>
def save(self, dev_id: str, data_type: str, data: dict):
"""Args: def_id(str): dev identifier data_type(str): f... | stack_v2_sparse_classes_36k_train_022507 | 2,944 | no_license | [
{
"docstring": "initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url",
"name": "__init__",
"signature": "def __init__(self, db_url: str)"
},
{
"docstring": "Args: def_id(str): dev identifier data_type(str): feature, query or model object data(dict): ca... | 3 | stack_v2_sparse_classes_30k_train_007598 | Implement the Python class `Catalog` described below.
Class description:
Implement the Catalog class.
Method signatures and docstrings:
- def __init__(self, db_url: str): initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url
- def save(self, dev_id: str, data_type: str, data... | Implement the Python class `Catalog` described below.
Class description:
Implement the Catalog class.
Method signatures and docstrings:
- def __init__(self, db_url: str): initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url
- def save(self, dev_id: str, data_type: str, data... | d9b72831510b8a9e7004d3ccfac073e3ef3c1f52 | <|skeleton|>
class Catalog:
def __init__(self, db_url: str):
"""initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url"""
<|body_0|>
def save(self, dev_id: str, data_type: str, data: dict):
"""Args: def_id(str): dev identifier data_type(str): f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Catalog:
def __init__(self, db_url: str):
"""initiates catalog and collection for storing features and queries Args: db_url(str): mongodb url"""
self.db_url = _mask_uri(db_url)
self.client = MDBClient(db_url)
self.db = self.client.get()
self._query_collection = self.db[... | the_stack_v2_python_sparse | feature_store/catalog.py | miararoy/feature_store | train | 0 | |
044a3470f76db302683901cc6dae4b460ee42c52 | [
"if host_ids and self.context['user'] not in host_ids:\n raise serializers.ValidationError('Must include self as host')\nelse:\n return host_ids",
"hosts = validated_data.pop('hosts')\ninstance = Queue.objects.create(**validated_data)\nif hosts:\n instance.hosts.set(hosts)\nelse:\n instance.hosts.set(... | <|body_start_0|>
if host_ids and self.context['user'] not in host_ids:
raise serializers.ValidationError('Must include self as host')
else:
return host_ids
<|end_body_0|>
<|body_start_1|>
hosts = validated_data.pop('hosts')
instance = Queue.objects.create(**valid... | Serializer used when viewing queue as a host. | QueueHostSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueueHostSerializer:
"""Serializer used when viewing queue as a host."""
def validate_host_ids(self, host_ids):
"""Require empty hosts_ids (default to current user) or require current user in host_ids"""
<|body_0|>
def create(self, validated_data):
"""Set current... | stack_v2_sparse_classes_36k_train_022508 | 10,335 | permissive | [
{
"docstring": "Require empty hosts_ids (default to current user) or require current user in host_ids",
"name": "validate_host_ids",
"signature": "def validate_host_ids(self, host_ids)"
},
{
"docstring": "Set current user as host if not provided many-to-many fields cannot be set until the model ... | 2 | stack_v2_sparse_classes_30k_train_009833 | Implement the Python class `QueueHostSerializer` described below.
Class description:
Serializer used when viewing queue as a host.
Method signatures and docstrings:
- def validate_host_ids(self, host_ids): Require empty hosts_ids (default to current user) or require current user in host_ids
- def create(self, validat... | Implement the Python class `QueueHostSerializer` described below.
Class description:
Serializer used when viewing queue as a host.
Method signatures and docstrings:
- def validate_host_ids(self, host_ids): Require empty hosts_ids (default to current user) or require current user in host_ids
- def create(self, validat... | 12e2185faf35307564bea910ff1baad7bef1ff76 | <|skeleton|>
class QueueHostSerializer:
"""Serializer used when viewing queue as a host."""
def validate_host_ids(self, host_ids):
"""Require empty hosts_ids (default to current user) or require current user in host_ids"""
<|body_0|>
def create(self, validated_data):
"""Set current... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueueHostSerializer:
"""Serializer used when viewing queue as a host."""
def validate_host_ids(self, host_ids):
"""Require empty hosts_ids (default to current user) or require current user in host_ids"""
if host_ids and self.context['user'] not in host_ids:
raise serializers.V... | the_stack_v2_python_sparse | src/officehours_api/serializers.py | tl-its-umich-edu/remote-office-hours-queue | train | 12 |
441a13a3359174644eab0deca73e2743880ee24e | [
"self._caffe = kwargs.pop('caffe')\nself._creator = kwargs.pop('creator')\nkwargs.setdefault('label_suffix', '')\nsuper(CashReportForm, self).__init__(*args, **kwargs)\nself.fields['cash_before_shift'].label = 'Pieniądze na początku zmiany'\nself.fields['cash_after_shift'].label = 'Pieniądze na końcu zmiany'\nself.... | <|body_start_0|>
self._caffe = kwargs.pop('caffe')
self._creator = kwargs.pop('creator')
kwargs.setdefault('label_suffix', '')
super(CashReportForm, self).__init__(*args, **kwargs)
self.fields['cash_before_shift'].label = 'Pieniądze na początku zmiany'
self.fields['cash_a... | Responsible for creating a cash report. | CashReportForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CashReportForm:
"""Responsible for creating a cash report."""
def __init__(self, *args, **kwargs):
"""Initialize all CashReport's fields."""
<|body_0|>
def save(self, commit=True):
"""Override of save method, to add Caffe relation."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_022509 | 4,623 | permissive | [
{
"docstring": "Initialize all CashReport's fields.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Override of save method, to add Caffe relation.",
"name": "save",
"signature": "def save(self, commit=True)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005900 | Implement the Python class `CashReportForm` described below.
Class description:
Responsible for creating a cash report.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize all CashReport's fields.
- def save(self, commit=True): Override of save method, to add Caffe relation. | Implement the Python class `CashReportForm` described below.
Class description:
Responsible for creating a cash report.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize all CashReport's fields.
- def save(self, commit=True): Override of save method, to add Caffe relation.
<|skeleto... | cdb7f5edb29255c7e874eaa6231621063210a8b0 | <|skeleton|>
class CashReportForm:
"""Responsible for creating a cash report."""
def __init__(self, *args, **kwargs):
"""Initialize all CashReport's fields."""
<|body_0|>
def save(self, commit=True):
"""Override of save method, to add Caffe relation."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CashReportForm:
"""Responsible for creating a cash report."""
def __init__(self, *args, **kwargs):
"""Initialize all CashReport's fields."""
self._caffe = kwargs.pop('caffe')
self._creator = kwargs.pop('creator')
kwargs.setdefault('label_suffix', '')
super(CashRepo... | the_stack_v2_python_sparse | caffe/cash/forms.py | VirrageS/io-kawiarnie | train | 3 |
0f6108aeac83bd52ab6edbcbf2758b089d8d8a02 | [
"name = self['name']\nif transactions_to_include and (not match_string_or_regular_expression(name, transactions_to_include)):\n return False\nreturn not match_string_or_regular_expression(name, transactions_to_ignore)",
"name, response_time = (self['name'], self[response_time_to_evaluate])\nfor transaction_spe... | <|body_start_0|>
name = self['name']
if transactions_to_include and (not match_string_or_regular_expression(name, transactions_to_include)):
return False
return not match_string_or_regular_expression(name, transactions_to_ignore)
<|end_body_0|>
<|body_start_1|>
name, respons... | Entity representing a performance transaction. | TransactionEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransactionEntity:
"""Entity representing a performance transaction."""
def is_to_be_included(self, transactions_to_include: list[str], transactions_to_ignore: list[str]) -> bool:
"""Return whether the transaction should be included."""
<|body_0|>
def is_slow(self, respo... | stack_v2_sparse_classes_36k_train_022510 | 16,901 | permissive | [
{
"docstring": "Return whether the transaction should be included.",
"name": "is_to_be_included",
"signature": "def is_to_be_included(self, transactions_to_include: list[str], transactions_to_ignore: list[str]) -> bool"
},
{
"docstring": "Return whether the transaction is slow.",
"name": "is... | 2 | null | Implement the Python class `TransactionEntity` described below.
Class description:
Entity representing a performance transaction.
Method signatures and docstrings:
- def is_to_be_included(self, transactions_to_include: list[str], transactions_to_ignore: list[str]) -> bool: Return whether the transaction should be inc... | Implement the Python class `TransactionEntity` described below.
Class description:
Entity representing a performance transaction.
Method signatures and docstrings:
- def is_to_be_included(self, transactions_to_include: list[str], transactions_to_ignore: list[str]) -> bool: Return whether the transaction should be inc... | 5d9952bf0bd47895824fa78428d3e4f4d6b5d9b3 | <|skeleton|>
class TransactionEntity:
"""Entity representing a performance transaction."""
def is_to_be_included(self, transactions_to_include: list[str], transactions_to_ignore: list[str]) -> bool:
"""Return whether the transaction should be included."""
<|body_0|>
def is_slow(self, respo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransactionEntity:
"""Entity representing a performance transaction."""
def is_to_be_included(self, transactions_to_include: list[str], transactions_to_ignore: list[str]) -> bool:
"""Return whether the transaction should be included."""
name = self['name']
if transactions_to_inclu... | the_stack_v2_python_sparse | components/collector/src/base_collectors/source_collector.py | ICTU/quality-time | train | 43 |
4b9bd497ae353583a4947fec6237f4e0d1ed224d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UnifiedApprovalStage()",
"from .subject_set import SubjectSet\nfrom .subject_set import SubjectSet\nfields: Dict[str, Callable[[Any], None]] = {'approvalStageTimeOutInDays': lambda n: setattr(self, 'approval_stage_time_out_in_days', n.... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UnifiedApprovalStage()
<|end_body_0|>
<|body_start_1|>
from .subject_set import SubjectSet
from .subject_set import SubjectSet
fields: Dict[str, Callable[[Any], None]] = {'approv... | UnifiedApprovalStage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnifiedApprovalStage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedApprovalStage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | stack_v2_sparse_classes_36k_train_022511 | 4,542 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: UnifiedApprovalStage",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminato... | 3 | null | Implement the Python class `UnifiedApprovalStage` described below.
Class description:
Implement the UnifiedApprovalStage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedApprovalStage: Creates a new instance of the appropriate class based o... | Implement the Python class `UnifiedApprovalStage` described below.
Class description:
Implement the UnifiedApprovalStage class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedApprovalStage: Creates a new instance of the appropriate class based o... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UnifiedApprovalStage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedApprovalStage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnifiedApprovalStage:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UnifiedApprovalStage:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | the_stack_v2_python_sparse | msgraph/generated/models/unified_approval_stage.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
303fe8e106534239cd648882cdecb891e0d386b2 | [
"dict, rolling_hash, res = ({}, 0, [])\nfor i in range(len(s)):\n rolling_hash = rolling_hash << 3 & 1073741823 | ord(s[i]) & 7\n if rolling_hash not in dict:\n dict[rolling_hash] = True\n elif dict[rolling_hash]:\n res.append(s[i - 9:i + 1])\n dict[rolling_hash] = False\nreturn res",
... | <|body_start_0|>
dict, rolling_hash, res = ({}, 0, [])
for i in range(len(s)):
rolling_hash = rolling_hash << 3 & 1073741823 | ord(s[i]) & 7
if rolling_hash not in dict:
dict[rolling_hash] = True
elif dict[rolling_hash]:
res.append(s[i ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findRepeatedDnaSequences(self, s):
""":type s: str :rtype: List[str]"""
<|body_0|>
def findRepeatedDnaSequences2(self, s):
""":type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dict, rolling_hash, res = ({},... | stack_v2_sparse_classes_36k_train_022512 | 1,855 | no_license | [
{
"docstring": ":type s: str :rtype: List[str]",
"name": "findRepeatedDnaSequences",
"signature": "def findRepeatedDnaSequences(self, s)"
},
{
"docstring": ":type s: str :rtype: List[str]",
"name": "findRepeatedDnaSequences2",
"signature": "def findRepeatedDnaSequences2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findRepeatedDnaSequences(self, s): :type s: str :rtype: List[str]
- def findRepeatedDnaSequences2(self, s): :type s: str :rtype: List[str] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findRepeatedDnaSequences(self, s): :type s: str :rtype: List[str]
- def findRepeatedDnaSequences2(self, s): :type s: str :rtype: List[str]
<|skeleton|>
class Solution:
... | 035ef08434fa1ca781a6fb2f9eed3538b7d20c02 | <|skeleton|>
class Solution:
def findRepeatedDnaSequences(self, s):
""":type s: str :rtype: List[str]"""
<|body_0|>
def findRepeatedDnaSequences2(self, s):
""":type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findRepeatedDnaSequences(self, s):
""":type s: str :rtype: List[str]"""
dict, rolling_hash, res = ({}, 0, [])
for i in range(len(s)):
rolling_hash = rolling_hash << 3 & 1073741823 | ord(s[i]) & 7
if rolling_hash not in dict:
dict[ro... | the_stack_v2_python_sparse | leetcode_python/Hash_table/repeated-dna-sequences.py | yennanliu/CS_basics | train | 64 | |
1630d7cfbe932aa37fa28265d63ba3b1c224ea36 | [
"values = {'a': bf.Tru(), 'b': bf.Fls(), 'c': bf.Fls()}\nformula = bf.And([bf.Or([bf.Var('b'), bf.Var('a'), bf.Var('c')]), bf.Or([bf.Not(bf.Var('a')), bf.Not(bf.Var('c'))]), bf.Not(bf.Var('b'))])\nresult = formula.evaluate(values)\nself.assertTrue(result, 'Invalid evaluation, expected True.')",
"values = {'a': bf... | <|body_start_0|>
values = {'a': bf.Tru(), 'b': bf.Fls(), 'c': bf.Fls()}
formula = bf.And([bf.Or([bf.Var('b'), bf.Var('a'), bf.Var('c')]), bf.Or([bf.Not(bf.Var('a')), bf.Not(bf.Var('c'))]), bf.Not(bf.Var('b'))])
result = formula.evaluate(values)
self.assertTrue(result, 'Invalid evaluation... | Unit test for the evaluation method of the algorithm utilities. | evaluation_unit_test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class evaluation_unit_test:
"""Unit test for the evaluation method of the algorithm utilities."""
def test_simple_evaluation_to_true(self):
"""Tests the evaluation of a simple formula with the specified values. Must evaluate to True."""
<|body_0|>
def test_simple_evaluation_to... | stack_v2_sparse_classes_36k_train_022513 | 2,078 | no_license | [
{
"docstring": "Tests the evaluation of a simple formula with the specified values. Must evaluate to True.",
"name": "test_simple_evaluation_to_true",
"signature": "def test_simple_evaluation_to_true(self)"
},
{
"docstring": "Tests the evaluation of a simple formula with the specified values. Mu... | 4 | stack_v2_sparse_classes_30k_train_011426 | Implement the Python class `evaluation_unit_test` described below.
Class description:
Unit test for the evaluation method of the algorithm utilities.
Method signatures and docstrings:
- def test_simple_evaluation_to_true(self): Tests the evaluation of a simple formula with the specified values. Must evaluate to True.... | Implement the Python class `evaluation_unit_test` described below.
Class description:
Unit test for the evaluation method of the algorithm utilities.
Method signatures and docstrings:
- def test_simple_evaluation_to_true(self): Tests the evaluation of a simple formula with the specified values. Must evaluate to True.... | bb4e876919bb956b75c442d528f3892553f1ee6f | <|skeleton|>
class evaluation_unit_test:
"""Unit test for the evaluation method of the algorithm utilities."""
def test_simple_evaluation_to_true(self):
"""Tests the evaluation of a simple formula with the specified values. Must evaluate to True."""
<|body_0|>
def test_simple_evaluation_to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class evaluation_unit_test:
"""Unit test for the evaluation method of the algorithm utilities."""
def test_simple_evaluation_to_true(self):
"""Tests the evaluation of a simple formula with the specified values. Must evaluate to True."""
values = {'a': bf.Tru(), 'b': bf.Fls(), 'c': bf.Fls()}
... | the_stack_v2_python_sparse | unit_tests/evaluation_unit_test.py | KePcA/LVR-sat | train | 0 |
7c3c5e87f9ada0fb82af9dd988e90bf85eb56c95 | [
"super(SaveToDiskWrapper, self).__init__(env=env)\nself._output_dir = output_dir\nself._episode = None",
"self._episode = Episode(self._output_dir, next(tokens))\nobservation = self.env.reset(*args, **kwargs)\nself._episode.append(**observation)\nreturn observation",
"observation, reward, done, info = self.env.... | <|body_start_0|>
super(SaveToDiskWrapper, self).__init__(env=env)
self._output_dir = output_dir
self._episode = None
<|end_body_0|>
<|body_start_1|>
self._episode = Episode(self._output_dir, next(tokens))
observation = self.env.reset(*args, **kwargs)
self._episode.append... | Stores observations to the disk. | SaveToDiskWrapper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaveToDiskWrapper:
"""Stores observations to the disk."""
def __init__(self, env: gym.Env, *, output_dir: str) -> None:
"""Constructs a gym wrapper to store observations to the disk."""
<|body_0|>
def reset(self, *args: Any, **kwargs: Any) -> Observations:
"""Res... | stack_v2_sparse_classes_36k_train_022514 | 8,971 | permissive | [
{
"docstring": "Constructs a gym wrapper to store observations to the disk.",
"name": "__init__",
"signature": "def __init__(self, env: gym.Env, *, output_dir: str) -> None"
},
{
"docstring": "Resets the wrapped environment and initializes a new episode.",
"name": "reset",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_020896 | Implement the Python class `SaveToDiskWrapper` described below.
Class description:
Stores observations to the disk.
Method signatures and docstrings:
- def __init__(self, env: gym.Env, *, output_dir: str) -> None: Constructs a gym wrapper to store observations to the disk.
- def reset(self, *args: Any, **kwargs: Any)... | Implement the Python class `SaveToDiskWrapper` described below.
Class description:
Stores observations to the disk.
Method signatures and docstrings:
- def __init__(self, env: gym.Env, *, output_dir: str) -> None: Constructs a gym wrapper to store observations to the disk.
- def reset(self, *args: Any, **kwargs: Any)... | 1680aee77a53228412f9bab34068f0a9576c58e3 | <|skeleton|>
class SaveToDiskWrapper:
"""Stores observations to the disk."""
def __init__(self, env: gym.Env, *, output_dir: str) -> None:
"""Constructs a gym wrapper to store observations to the disk."""
<|body_0|>
def reset(self, *args: Any, **kwargs: Any) -> Observations:
"""Res... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SaveToDiskWrapper:
"""Stores observations to the disk."""
def __init__(self, env: gym.Env, *, output_dir: str) -> None:
"""Constructs a gym wrapper to store observations to the disk."""
super(SaveToDiskWrapper, self).__init__(env=env)
self._output_dir = output_dir
self._ep... | the_stack_v2_python_sparse | oatomobile/core/rl.py | OATML/oatomobile | train | 177 |
dfb5e078391c943fe470f208aa39d20d044e8527 | [
"try:\n extensions_config = getattr(current_app.extensions['invenio-app-ils'], 'series_metadata_extensions')\nexcept AttributeError:\n return {}\nExtensionSchema = extensions_config.to_schema()\nreturn ExtensionSchema().dump(obj)",
"try:\n extensions_config = getattr(current_app.extensions['invenio-app-i... | <|body_start_0|>
try:
extensions_config = getattr(current_app.extensions['invenio-app-ils'], 'series_metadata_extensions')
except AttributeError:
return {}
ExtensionSchema = extensions_config.to_schema()
return ExtensionSchema().dump(obj)
<|end_body_0|>
<|body_st... | Series schema. | SeriesSchemaV1 | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SeriesSchemaV1:
"""Series schema."""
def dump_extensions(self, obj):
"""Dumps the extensions value. :params obj: content of the object's 'extensions' field"""
<|body_0|>
def load_extensions(self, value):
"""Loads the 'extensions' field. :params value: content of ... | stack_v2_sparse_classes_36k_train_022515 | 4,051 | permissive | [
{
"docstring": "Dumps the extensions value. :params obj: content of the object's 'extensions' field",
"name": "dump_extensions",
"signature": "def dump_extensions(self, obj)"
},
{
"docstring": "Loads the 'extensions' field. :params value: content of the input's 'extensions' field",
"name": "... | 3 | null | Implement the Python class `SeriesSchemaV1` described below.
Class description:
Series schema.
Method signatures and docstrings:
- def dump_extensions(self, obj): Dumps the extensions value. :params obj: content of the object's 'extensions' field
- def load_extensions(self, value): Loads the 'extensions' field. :para... | Implement the Python class `SeriesSchemaV1` described below.
Class description:
Series schema.
Method signatures and docstrings:
- def dump_extensions(self, obj): Dumps the extensions value. :params obj: content of the object's 'extensions' field
- def load_extensions(self, value): Loads the 'extensions' field. :para... | 1c36526e85510100c5f64059518d1b716d87ac10 | <|skeleton|>
class SeriesSchemaV1:
"""Series schema."""
def dump_extensions(self, obj):
"""Dumps the extensions value. :params obj: content of the object's 'extensions' field"""
<|body_0|>
def load_extensions(self, value):
"""Loads the 'extensions' field. :params value: content of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SeriesSchemaV1:
"""Series schema."""
def dump_extensions(self, obj):
"""Dumps the extensions value. :params obj: content of the object's 'extensions' field"""
try:
extensions_config = getattr(current_app.extensions['invenio-app-ils'], 'series_metadata_extensions')
exce... | the_stack_v2_python_sparse | invenio_app_ils/series/loaders/jsonschemas/series.py | inveniosoftware/invenio-app-ils | train | 64 |
cd709243eb68e48b2a763e4a73f99e6c0026f17b | [
"conf['angel.worker.matrix.transfer.request.timeout.ms'] = 60000\njconf = conf.dict_to_jconf()\nsuper(LinearRegRunner, self).train(conf, conf._jvm.com.tencent.angel.ml.regression.linear.LinearRegModel(jconf, None), 'com.tencent.angel.ml.regression.linear.LinearRegTrainTask')",
"conf['angel.worker.matrix.transfer.... | <|body_start_0|>
conf['angel.worker.matrix.transfer.request.timeout.ms'] = 60000
jconf = conf.dict_to_jconf()
super(LinearRegRunner, self).train(conf, conf._jvm.com.tencent.angel.ml.regression.linear.LinearRegModel(jconf, None), 'com.tencent.angel.ml.regression.linear.LinearRegTrainTask')
<|end_... | Run linear regression task on angel | LinearRegRunner | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearRegRunner:
"""Run linear regression task on angel"""
def train(self, conf):
"""Run linear regression train task :param conf: configuration of a algorithm and resource :return:"""
<|body_0|>
def predict(self, conf):
"""Run linear regression predict task :par... | stack_v2_sparse_classes_36k_train_022516 | 2,910 | permissive | [
{
"docstring": "Run linear regression train task :param conf: configuration of a algorithm and resource :return:",
"name": "train",
"signature": "def train(self, conf)"
},
{
"docstring": "Run linear regression predict task :param conf: configuration of algorithm and resource :return:",
"name... | 3 | stack_v2_sparse_classes_30k_train_019133 | Implement the Python class `LinearRegRunner` described below.
Class description:
Run linear regression task on angel
Method signatures and docstrings:
- def train(self, conf): Run linear regression train task :param conf: configuration of a algorithm and resource :return:
- def predict(self, conf): Run linear regress... | Implement the Python class `LinearRegRunner` described below.
Class description:
Run linear regression task on angel
Method signatures and docstrings:
- def train(self, conf): Run linear regression train task :param conf: configuration of a algorithm and resource :return:
- def predict(self, conf): Run linear regress... | cb015db12356ffbfbdde096e4ec112a2cd324ac3 | <|skeleton|>
class LinearRegRunner:
"""Run linear regression task on angel"""
def train(self, conf):
"""Run linear regression train task :param conf: configuration of a algorithm and resource :return:"""
<|body_0|>
def predict(self, conf):
"""Run linear regression predict task :par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearRegRunner:
"""Run linear regression task on angel"""
def train(self, conf):
"""Run linear regression train task :param conf: configuration of a algorithm and resource :return:"""
conf['angel.worker.matrix.transfer.request.timeout.ms'] = 60000
jconf = conf.dict_to_jconf()
... | the_stack_v2_python_sparse | angel-ps/python/pyangel/ml/regression/runner.py | haitwang-cloud/angel | train | 0 |
be32339233a4716666f09b2ab0e5801aba4e918d | [
"if TurboJPEGSingleton.__instance is None:\n TurboJPEGSingleton()\nreturn TurboJPEGSingleton.__instance",
"try:\n from turbojpeg import TurboJPEG\n TurboJPEGSingleton.__instance = TurboJPEG()\nexcept Exception:\n _LOGGER.exception('Error loading libturbojpeg; Cameras may impact HomeKit performance')\n... | <|body_start_0|>
if TurboJPEGSingleton.__instance is None:
TurboJPEGSingleton()
return TurboJPEGSingleton.__instance
<|end_body_0|>
<|body_start_1|>
try:
from turbojpeg import TurboJPEG
TurboJPEGSingleton.__instance = TurboJPEG()
except Exception:
... | Load TurboJPEG only once. Ensures we do not log load failures each snapshot since camera image fetches happen every few seconds. | TurboJPEGSingleton | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TurboJPEGSingleton:
"""Load TurboJPEG only once. Ensures we do not log load failures each snapshot since camera image fetches happen every few seconds."""
def instance() -> TurboJPEG | Literal[False] | None:
"""Singleton for TurboJPEG."""
<|body_0|>
def __init__(self) ->... | stack_v2_sparse_classes_36k_train_022517 | 3,257 | permissive | [
{
"docstring": "Singleton for TurboJPEG.",
"name": "instance",
"signature": "def instance() -> TurboJPEG | Literal[False] | None"
},
{
"docstring": "Try to create TurboJPEG only once.",
"name": "__init__",
"signature": "def __init__(self) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_020677 | Implement the Python class `TurboJPEGSingleton` described below.
Class description:
Load TurboJPEG only once. Ensures we do not log load failures each snapshot since camera image fetches happen every few seconds.
Method signatures and docstrings:
- def instance() -> TurboJPEG | Literal[False] | None: Singleton for Tu... | Implement the Python class `TurboJPEGSingleton` described below.
Class description:
Load TurboJPEG only once. Ensures we do not log load failures each snapshot since camera image fetches happen every few seconds.
Method signatures and docstrings:
- def instance() -> TurboJPEG | Literal[False] | None: Singleton for Tu... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class TurboJPEGSingleton:
"""Load TurboJPEG only once. Ensures we do not log load failures each snapshot since camera image fetches happen every few seconds."""
def instance() -> TurboJPEG | Literal[False] | None:
"""Singleton for TurboJPEG."""
<|body_0|>
def __init__(self) ->... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TurboJPEGSingleton:
"""Load TurboJPEG only once. Ensures we do not log load failures each snapshot since camera image fetches happen every few seconds."""
def instance() -> TurboJPEG | Literal[False] | None:
"""Singleton for TurboJPEG."""
if TurboJPEGSingleton.__instance is None:
... | the_stack_v2_python_sparse | homeassistant/components/camera/img_util.py | home-assistant/core | train | 35,501 |
aa6cea4db7feb61a837d7c248371e0283b3aa299 | [
"self.__width = width\nself.__height = height\nself.__score = 0\nself.__f = 0\nself.__food = food\nself.__snake = deque([(0, 0)])\nself.__direction = {'U': (-1, 0), 'L': (0, -1), 'R': (0, 1), 'D': (1, 0)}\nself.__lookup = {(0, 0)}",
"def valid(x, y):\n return 0 <= x < self.__height and 0 <= y < self.__width an... | <|body_start_0|>
self.__width = width
self.__height = height
self.__score = 0
self.__f = 0
self.__food = food
self.__snake = deque([(0, 0)])
self.__direction = {'U': (-1, 0), 'L': (0, -1), 'R': (0, 1), 'D': (1, 0)}
self.__lookup = {(0, 0)}
<|end_body_0|>
... | SnakeGame | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k_train_022518 | 1,950 | permissive | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :type height: int :type food: List[List[int]]",
... | 2 | null | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | 4dc4e6642dc92f1983c13564cc0fd99917cab358 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :... | the_stack_v2_python_sparse | Python/design-snake-game.py | kamyu104/LeetCode-Solutions | train | 4,549 | |
0e07df5de969277dc69536d0fe57a72958bcfed2 | [
"if not email:\n raise ValueError('User must have an email address')\nprint('-----------------Antes de guardar usuarios')\nemail = self.normalize_email(email)\nuser = self.model(email=email)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email, password)\nuser.i... | <|body_start_0|>
if not email:
raise ValueError('User must have an email address')
print('-----------------Antes de guardar usuarios')
email = self.normalize_email(email)
user = self.model(email=email)
user.set_password(password)
user.save(using=self._db)
... | Administrador para perfiles de Usuario | UserProfileManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfileManager:
"""Administrador para perfiles de Usuario"""
def create_user(self, email: str, password: str) -> User:
"""Crea un nuevo usuario"""
<|body_0|>
def create_superuser(self, email: str, password: str) -> User:
"""Crea un nuevo superusuario"""
... | stack_v2_sparse_classes_36k_train_022519 | 2,388 | no_license | [
{
"docstring": "Crea un nuevo usuario",
"name": "create_user",
"signature": "def create_user(self, email: str, password: str) -> User"
},
{
"docstring": "Crea un nuevo superusuario",
"name": "create_superuser",
"signature": "def create_superuser(self, email: str, password: str) -> User"
... | 2 | stack_v2_sparse_classes_30k_train_020099 | Implement the Python class `UserProfileManager` described below.
Class description:
Administrador para perfiles de Usuario
Method signatures and docstrings:
- def create_user(self, email: str, password: str) -> User: Crea un nuevo usuario
- def create_superuser(self, email: str, password: str) -> User: Crea un nuevo ... | Implement the Python class `UserProfileManager` described below.
Class description:
Administrador para perfiles de Usuario
Method signatures and docstrings:
- def create_user(self, email: str, password: str) -> User: Crea un nuevo usuario
- def create_superuser(self, email: str, password: str) -> User: Crea un nuevo ... | 6f7ee866d21cd87de1b03a57adc3276204031a9e | <|skeleton|>
class UserProfileManager:
"""Administrador para perfiles de Usuario"""
def create_user(self, email: str, password: str) -> User:
"""Crea un nuevo usuario"""
<|body_0|>
def create_superuser(self, email: str, password: str) -> User:
"""Crea un nuevo superusuario"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserProfileManager:
"""Administrador para perfiles de Usuario"""
def create_user(self, email: str, password: str) -> User:
"""Crea un nuevo usuario"""
if not email:
raise ValueError('User must have an email address')
print('-----------------Antes de guardar usuarios')
... | the_stack_v2_python_sparse | profiles/models.py | JCamilo5/backProyecto1 | train | 0 |
7d7e589b11a4ef6a52dcfcb0423815e2f290ec39 | [
"super().__init__(**kwargs)\ndim = len(voxel_size)\nassert len(spatial_size) == 2 * dim, f'{spatial_size}'\nself._voxel_size = voxel_size\nself._spatial_size = spatial_size\nself._voxel_spatial_size = voxel_utils.compute_voxel_spatial_size(spatial_size, self._voxel_size)",
"point_voxel_xyz_float = ops.floor(point... | <|body_start_0|>
super().__init__(**kwargs)
dim = len(voxel_size)
assert len(spatial_size) == 2 * dim, f'{spatial_size}'
self._voxel_size = voxel_size
self._spatial_size = spatial_size
self._voxel_spatial_size = voxel_utils.compute_voxel_spatial_size(spatial_size, self._v... | Voxelization layer. | PointToVoxel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointToVoxel:
"""Voxelization layer."""
def __init__(self, voxel_size, spatial_size, **kwargs):
"""Voxelization layer constructor. Args: voxel_size: voxel size in each xyz dimension. spatial_size: max/min range in each dim in global coordinate frame. name: layer name **kwargs: additi... | stack_v2_sparse_classes_36k_train_022520 | 9,351 | permissive | [
{
"docstring": "Voxelization layer constructor. Args: voxel_size: voxel size in each xyz dimension. spatial_size: max/min range in each dim in global coordinate frame. name: layer name **kwargs: additional key value args (e.g. dtype) passed to the parent class.",
"name": "__init__",
"signature": "def __... | 2 | stack_v2_sparse_classes_30k_train_008620 | Implement the Python class `PointToVoxel` described below.
Class description:
Voxelization layer.
Method signatures and docstrings:
- def __init__(self, voxel_size, spatial_size, **kwargs): Voxelization layer constructor. Args: voxel_size: voxel size in each xyz dimension. spatial_size: max/min range in each dim in g... | Implement the Python class `PointToVoxel` described below.
Class description:
Voxelization layer.
Method signatures and docstrings:
- def __init__(self, voxel_size, spatial_size, **kwargs): Voxelization layer constructor. Args: voxel_size: voxel size in each xyz dimension. spatial_size: max/min range in each dim in g... | e83f229f1b7b847cd712d5cd4810097d3e06d14e | <|skeleton|>
class PointToVoxel:
"""Voxelization layer."""
def __init__(self, voxel_size, spatial_size, **kwargs):
"""Voxelization layer constructor. Args: voxel_size: voxel size in each xyz dimension. spatial_size: max/min range in each dim in global coordinate frame. name: layer name **kwargs: additi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointToVoxel:
"""Voxelization layer."""
def __init__(self, voxel_size, spatial_size, **kwargs):
"""Voxelization layer constructor. Args: voxel_size: voxel size in each xyz dimension. spatial_size: max/min range in each dim in global coordinate frame. name: layer name **kwargs: additional key valu... | the_stack_v2_python_sparse | keras_cv/layers/object_detection_3d/voxelization.py | keras-team/keras-cv | train | 818 |
6aa499b865a746a5429bf954af963efb1e6ad538 | [
"if self.params.opt_mode == 'min':\n opt_idx = np.argmin(self.exe_path.y)\nelif self.params.opt_mode == 'max':\n opt_idx = np.argmax(self.exe_path.y)\nopt_pair = [self.exe_path.x[opt_idx], self.exe_path.y[opt_idx]]\nreturn opt_pair",
"def dist_fn(a, b):\n a = np.array(a[0] + [a[1]])\n b = np.array(b[0... | <|body_start_0|>
if self.params.opt_mode == 'min':
opt_idx = np.argmin(self.exe_path.y)
elif self.params.opt_mode == 'max':
opt_idx = np.argmax(self.exe_path.y)
opt_pair = [self.exe_path.x[opt_idx], self.exe_path.y[opt_idx]]
return opt_pair
<|end_body_0|>
<|body_... | Algorithm that scans over a grid of points, and as output returns the minimum function input over the grid. | GlobalOptGrid | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GlobalOptGrid:
"""Algorithm that scans over a grid of points, and as output returns the minimum function input over the grid."""
def get_output(self):
"""Return output based on self.exe_path."""
<|body_0|>
def get_output_dist_fn(self):
"""Return distance function... | stack_v2_sparse_classes_36k_train_022521 | 19,618 | no_license | [
{
"docstring": "Return output based on self.exe_path.",
"name": "get_output",
"signature": "def get_output(self)"
},
{
"docstring": "Return distance function for pairs of outputs.",
"name": "get_output_dist_fn",
"signature": "def get_output_dist_fn(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013702 | Implement the Python class `GlobalOptGrid` described below.
Class description:
Algorithm that scans over a grid of points, and as output returns the minimum function input over the grid.
Method signatures and docstrings:
- def get_output(self): Return output based on self.exe_path.
- def get_output_dist_fn(self): Ret... | Implement the Python class `GlobalOptGrid` described below.
Class description:
Algorithm that scans over a grid of points, and as output returns the minimum function input over the grid.
Method signatures and docstrings:
- def get_output(self): Return output based on self.exe_path.
- def get_output_dist_fn(self): Ret... | d75d1a89bb566e62662e4d010d91893bfe1ee9f4 | <|skeleton|>
class GlobalOptGrid:
"""Algorithm that scans over a grid of points, and as output returns the minimum function input over the grid."""
def get_output(self):
"""Return output based on self.exe_path."""
<|body_0|>
def get_output_dist_fn(self):
"""Return distance function... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GlobalOptGrid:
"""Algorithm that scans over a grid of points, and as output returns the minimum function input over the grid."""
def get_output(self):
"""Return output based on self.exe_path."""
if self.params.opt_mode == 'min':
opt_idx = np.argmin(self.exe_path.y)
eli... | the_stack_v2_python_sparse | bax/alg/algorithms.py | willieneis/bayesian-algorithm-execution | train | 45 |
0a93421684c42fe385e9b477fa47cd680587e965 | [
"assert isinstance(public_key, str), type(public_key)\nsuper(MultiChainPaymentProvider, self).__init__()\nself.multi_chain_community = multi_chain_community\nself.public_key = public_key",
"assert isinstance(candidate, Candidate), type(candidate)\nassert isinstance(quantity, Quantity), type(quantity)\nif self.bal... | <|body_start_0|>
assert isinstance(public_key, str), type(public_key)
super(MultiChainPaymentProvider, self).__init__()
self.multi_chain_community = multi_chain_community
self.public_key = public_key
<|end_body_0|>
<|body_start_1|>
assert isinstance(candidate, Candidate), type(c... | "Multi chain payment provider which enables checking the multi chain balance of this peer and transferring multi chain to other peers | MultiChainPaymentProvider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiChainPaymentProvider:
""""Multi chain payment provider which enables checking the multi chain balance of this peer and transferring multi chain to other peers"""
def __init__(self, multi_chain_community, public_key):
""":param multi_chain_community: The multi chain community whi... | stack_v2_sparse_classes_36k_train_022522 | 3,445 | no_license | [
{
"docstring": ":param multi_chain_community: The multi chain community which manages multi chain transfers :param public_key: The public key of this peer",
"name": "__init__",
"signature": "def __init__(self, multi_chain_community, public_key)"
},
{
"docstring": "Transfers the selected quantity... | 3 | stack_v2_sparse_classes_30k_train_001271 | Implement the Python class `MultiChainPaymentProvider` described below.
Class description:
"Multi chain payment provider which enables checking the multi chain balance of this peer and transferring multi chain to other peers
Method signatures and docstrings:
- def __init__(self, multi_chain_community, public_key): :p... | Implement the Python class `MultiChainPaymentProvider` described below.
Class description:
"Multi chain payment provider which enables checking the multi chain balance of this peer and transferring multi chain to other peers
Method signatures and docstrings:
- def __init__(self, multi_chain_community, public_key): :p... | cc4d1c27166d68c39e5c38e77bb70093f34e19e5 | <|skeleton|>
class MultiChainPaymentProvider:
""""Multi chain payment provider which enables checking the multi chain balance of this peer and transferring multi chain to other peers"""
def __init__(self, multi_chain_community, public_key):
""":param multi_chain_community: The multi chain community whi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiChainPaymentProvider:
""""Multi chain payment provider which enables checking the multi chain balance of this peer and transferring multi chain to other peers"""
def __init__(self, multi_chain_community, public_key):
""":param multi_chain_community: The multi chain community which manages mu... | the_stack_v2_python_sparse | market/core/payment_provider.py | devos50/decentralized-market | train | 0 |
f05ec5e7e676982c02605a2473749c19645750b1 | [
"super(InstrumentDialog, self).__init__(parent, wx.ID_ANY, title='Edit instrument', minWidth=300)\nself.inst = inst\nself.spec = inst.getSpecification()\nsetpanel = wx.Panel(self)\nsetsizer = wx.FlexGridSizer(len(self.spec) + 1, 2, 3, 3)\nsetpanel.SetSizer(setsizer)\nname = self.inst.getName()\nself.tbs = []\nsetsi... | <|body_start_0|>
super(InstrumentDialog, self).__init__(parent, wx.ID_ANY, title='Edit instrument', minWidth=300)
self.inst = inst
self.spec = inst.getSpecification()
setpanel = wx.Panel(self)
setsizer = wx.FlexGridSizer(len(self.spec) + 1, 2, 3, 3)
setpanel.SetSizer(sets... | A simple dialog for creating new instruments. | InstrumentDialog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstrumentDialog:
"""A simple dialog for creating new instruments."""
def __init__(self, parent, inst):
"""Create a new instrument dialog."""
<|body_0|>
def update(self):
"""Update the instrument to reflect changes."""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_022523 | 31,205 | no_license | [
{
"docstring": "Create a new instrument dialog.",
"name": "__init__",
"signature": "def __init__(self, parent, inst)"
},
{
"docstring": "Update the instrument to reflect changes.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005836 | Implement the Python class `InstrumentDialog` described below.
Class description:
A simple dialog for creating new instruments.
Method signatures and docstrings:
- def __init__(self, parent, inst): Create a new instrument dialog.
- def update(self): Update the instrument to reflect changes. | Implement the Python class `InstrumentDialog` described below.
Class description:
A simple dialog for creating new instruments.
Method signatures and docstrings:
- def __init__(self, parent, inst): Create a new instrument dialog.
- def update(self): Update the instrument to reflect changes.
<|skeleton|>
class Instru... | 6001bd91ab998a3271b1a160fed7de0d0b342cc6 | <|skeleton|>
class InstrumentDialog:
"""A simple dialog for creating new instruments."""
def __init__(self, parent, inst):
"""Create a new instrument dialog."""
<|body_0|>
def update(self):
"""Update the instrument to reflect changes."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstrumentDialog:
"""A simple dialog for creating new instruments."""
def __init__(self, parent, inst):
"""Create a new instrument dialog."""
super(InstrumentDialog, self).__init__(parent, wx.ID_ANY, title='Edit instrument', minWidth=300)
self.inst = inst
self.spec = inst.... | the_stack_v2_python_sparse | src/gui/object_config.py | tcflanagan/transport | train | 0 |
cd13334606d2ab202838a1e176a051c52af96cd4 | [
"if data_loc == 'disk':\n root = server_setup.BACKUP_DATA_ROOT_DIR\nelse:\n root = server_setup.DATA_ROOT_DIR\nif server_setup.DEPLOYMENT_MODE == DeploymentMode.Server:\n return SSHDataAccess(root)\nreturn LocalDataAccess(root)",
"mode = server_setup.DEPLOYMENT_MODE\nif mode == DeploymentMode.Server:\n ... | <|body_start_0|>
if data_loc == 'disk':
root = server_setup.BACKUP_DATA_ROOT_DIR
else:
root = server_setup.DATA_ROOT_DIR
if server_setup.DEPLOYMENT_MODE == DeploymentMode.Server:
return SSHDataAccess(root)
return LocalDataAccess(root)
<|end_body_0|>
<... | Factory for data access instances | Context | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Context:
"""Factory for data access instances"""
def get_data_access(data_loc=None):
"""Return a data access instance appropriate for the current environment. :param str data_loc: pass "disk" if using data from backup disk, otherwise leave the default. :return: (:class:`powersimdata.... | stack_v2_sparse_classes_36k_train_022524 | 1,570 | permissive | [
{
"docstring": "Return a data access instance appropriate for the current environment. :param str data_loc: pass \"disk\" if using data from backup disk, otherwise leave the default. :return: (:class:`powersimdata.data_access.data_access.DataAccess`) -- a data access instance",
"name": "get_data_access",
... | 2 | stack_v2_sparse_classes_30k_train_006833 | Implement the Python class `Context` described below.
Class description:
Factory for data access instances
Method signatures and docstrings:
- def get_data_access(data_loc=None): Return a data access instance appropriate for the current environment. :param str data_loc: pass "disk" if using data from backup disk, oth... | Implement the Python class `Context` described below.
Class description:
Factory for data access instances
Method signatures and docstrings:
- def get_data_access(data_loc=None): Return a data access instance appropriate for the current environment. :param str data_loc: pass "disk" if using data from backup disk, oth... | 2fa9fb907fd55a96ffd3d584614b47af79a0bda8 | <|skeleton|>
class Context:
"""Factory for data access instances"""
def get_data_access(data_loc=None):
"""Return a data access instance appropriate for the current environment. :param str data_loc: pass "disk" if using data from backup disk, otherwise leave the default. :return: (:class:`powersimdata.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Context:
"""Factory for data access instances"""
def get_data_access(data_loc=None):
"""Return a data access instance appropriate for the current environment. :param str data_loc: pass "disk" if using data from backup disk, otherwise leave the default. :return: (:class:`powersimdata.data_access.d... | the_stack_v2_python_sparse | powersimdata/data_access/context.py | abhinavgairola/PowerSimData | train | 0 |
72a5e1c06e1a851491947d3c873d0ba117671d7b | [
"super().__init__('opendr_object_detection_2d_detr_node')\nif output_rgb_image_topic is not None:\n self.image_publisher = self.create_publisher(ROS_Image, output_rgb_image_topic, 1)\nelse:\n self.image_publisher = None\nif detections_topic is not None:\n self.detection_publisher = self.create_publisher(De... | <|body_start_0|>
super().__init__('opendr_object_detection_2d_detr_node')
if output_rgb_image_topic is not None:
self.image_publisher = self.create_publisher(ROS_Image, output_rgb_image_topic, 1)
else:
self.image_publisher = None
if detections_topic is not None:
... | ObjectDetectionDetrNode | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObjectDetectionDetrNode:
def __init__(self, input_rgb_image_topic='image_raw', output_rgb_image_topic='/opendr/image_objects_annotated', detections_topic='/opendr/objects', device='cuda'):
"""Creates a ROS2 Node for object detection with DETR. :param input_rgb_image_topic: Topic from whi... | stack_v2_sparse_classes_36k_train_022525 | 7,921 | permissive | [
{
"docstring": "Creates a ROS2 Node for object detection with DETR. :param input_rgb_image_topic: Topic from which we are reading the input image :type input_rgb_image_topic: str :param output_rgb_image_topic: Topic to which we are publishing the annotated image (if None, no annotated image is published) :type ... | 2 | null | Implement the Python class `ObjectDetectionDetrNode` described below.
Class description:
Implement the ObjectDetectionDetrNode class.
Method signatures and docstrings:
- def __init__(self, input_rgb_image_topic='image_raw', output_rgb_image_topic='/opendr/image_objects_annotated', detections_topic='/opendr/objects', ... | Implement the Python class `ObjectDetectionDetrNode` described below.
Class description:
Implement the ObjectDetectionDetrNode class.
Method signatures and docstrings:
- def __init__(self, input_rgb_image_topic='image_raw', output_rgb_image_topic='/opendr/image_objects_annotated', detections_topic='/opendr/objects', ... | b3d6ce670cdf63469fc5766630eb295d67b3d788 | <|skeleton|>
class ObjectDetectionDetrNode:
def __init__(self, input_rgb_image_topic='image_raw', output_rgb_image_topic='/opendr/image_objects_annotated', detections_topic='/opendr/objects', device='cuda'):
"""Creates a ROS2 Node for object detection with DETR. :param input_rgb_image_topic: Topic from whi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObjectDetectionDetrNode:
def __init__(self, input_rgb_image_topic='image_raw', output_rgb_image_topic='/opendr/image_objects_annotated', detections_topic='/opendr/objects', device='cuda'):
"""Creates a ROS2 Node for object detection with DETR. :param input_rgb_image_topic: Topic from which we are read... | the_stack_v2_python_sparse | projects/opendr_ws_2/src/opendr_perception/opendr_perception/object_detection_2d_detr_node.py | opendr-eu/opendr | train | 535 | |
d3bea7e63cc6cb5ab792c258b8c1ca7382e47c76 | [
"if not isinstance(uid, str) or not bool(uid.strip()):\n message: str = 'uid cannot be Null'\n raise InputError(status=error_codes.input_error_code, description=message)\nif not isinstance(organization_id, str) or not bool(organization_id.strip()):\n message: str = 'organization_id cannot be Null'\n rai... | <|body_start_0|>
if not isinstance(uid, str) or not bool(uid.strip()):
message: str = 'uid cannot be Null'
raise InputError(status=error_codes.input_error_code, description=message)
if not isinstance(organization_id, str) or not bool(organization_id.strip()):
message:... | UserValidators | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserValidators:
def is_user_valid(organization_id: str, uid: str) -> Optional[bool]:
"""**is_user_valid** returns true if user_instance is found and user_instance.is_active :param organization_id: :param uid: :return:"""
<|body_0|>
async def is_user_valid_async(organization_... | stack_v2_sparse_classes_36k_train_022526 | 14,108 | permissive | [
{
"docstring": "**is_user_valid** returns true if user_instance is found and user_instance.is_active :param organization_id: :param uid: :return:",
"name": "is_user_valid",
"signature": "def is_user_valid(organization_id: str, uid: str) -> Optional[bool]"
},
{
"docstring": "**is_user_valid_async... | 4 | null | Implement the Python class `UserValidators` described below.
Class description:
Implement the UserValidators class.
Method signatures and docstrings:
- def is_user_valid(organization_id: str, uid: str) -> Optional[bool]: **is_user_valid** returns true if user_instance is found and user_instance.is_active :param organ... | Implement the Python class `UserValidators` described below.
Class description:
Implement the UserValidators class.
Method signatures and docstrings:
- def is_user_valid(organization_id: str, uid: str) -> Optional[bool]: **is_user_valid** returns true if user_instance is found and user_instance.is_active :param organ... | e8cf1df3f061c9745977e207568ffed2abdc70fc | <|skeleton|>
class UserValidators:
def is_user_valid(organization_id: str, uid: str) -> Optional[bool]:
"""**is_user_valid** returns true if user_instance is found and user_instance.is_active :param organization_id: :param uid: :return:"""
<|body_0|>
async def is_user_valid_async(organization_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserValidators:
def is_user_valid(organization_id: str, uid: str) -> Optional[bool]:
"""**is_user_valid** returns true if user_instance is found and user_instance.is_active :param organization_id: :param uid: :return:"""
if not isinstance(uid, str) or not bool(uid.strip()):
message... | the_stack_v2_python_sparse | database/users.py | saaiiravi/membership_and_affiliate_api | train | 0 | |
66700b042f02ed0edec9cae8a9dc13a8237e6ad1 | [
"self.object_attributes_param = object_attributes_param\nself.object_param = object_param\nself.mtype = mtype",
"if dictionary is None:\n return None\nobject_attributes_param = cohesity_management_sdk.models.ad_attribute_restore_param.ADAttributeRestoreParam.from_dictionary(dictionary.get('objectAttributesPara... | <|body_start_0|>
self.object_attributes_param = object_attributes_param
self.object_param = object_param
self.mtype = mtype
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
object_attributes_param = cohesity_management_sdk.models.ad_attribute_restor... | Implementation of the 'ADUpdateRestoreTaskOptions' model. TODO: type description here. Attributes: object_attributes_param (ADAttributeRestoreParam): Object attributes restore params with the list of attributes to be restored. This is set only when type is kObjectAttributes. object_param (ADObjectRestoreParam): Object ... | ADUpdateRestoreTaskOptions | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ADUpdateRestoreTaskOptions:
"""Implementation of the 'ADUpdateRestoreTaskOptions' model. TODO: type description here. Attributes: object_attributes_param (ADAttributeRestoreParam): Object attributes restore params with the list of attributes to be restored. This is set only when type is kObjectAt... | stack_v2_sparse_classes_36k_train_022527 | 2,578 | permissive | [
{
"docstring": "Constructor for the ADUpdateRestoreTaskOptions class",
"name": "__init__",
"signature": "def __init__(self, object_attributes_param=None, object_param=None, mtype=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictio... | 2 | stack_v2_sparse_classes_30k_test_000769 | Implement the Python class `ADUpdateRestoreTaskOptions` described below.
Class description:
Implementation of the 'ADUpdateRestoreTaskOptions' model. TODO: type description here. Attributes: object_attributes_param (ADAttributeRestoreParam): Object attributes restore params with the list of attributes to be restored. ... | Implement the Python class `ADUpdateRestoreTaskOptions` described below.
Class description:
Implementation of the 'ADUpdateRestoreTaskOptions' model. TODO: type description here. Attributes: object_attributes_param (ADAttributeRestoreParam): Object attributes restore params with the list of attributes to be restored. ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ADUpdateRestoreTaskOptions:
"""Implementation of the 'ADUpdateRestoreTaskOptions' model. TODO: type description here. Attributes: object_attributes_param (ADAttributeRestoreParam): Object attributes restore params with the list of attributes to be restored. This is set only when type is kObjectAt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ADUpdateRestoreTaskOptions:
"""Implementation of the 'ADUpdateRestoreTaskOptions' model. TODO: type description here. Attributes: object_attributes_param (ADAttributeRestoreParam): Object attributes restore params with the list of attributes to be restored. This is set only when type is kObjectAttributes. obj... | the_stack_v2_python_sparse | cohesity_management_sdk/models/ad_update_restore_task_options.py | cohesity/management-sdk-python | train | 24 |
0e11ce0548ad8099182b985528d48df94a26aca8 | [
"Node.__init__(self, name)\nself.acceptChild = [Node.LIMIT]\nself.nodeType = Node.THRESHOLD",
"if self.getSubNode(name, Node.LIMIT):\n raise HanCannotCreateConf('The limit: ' + name + ' already exists for threshold: ' + self.name)\nlimit = HanLimit(name, warning, error)\nself.appendChild(limit)"
] | <|body_start_0|>
Node.__init__(self, name)
self.acceptChild = [Node.LIMIT]
self.nodeType = Node.THRESHOLD
<|end_body_0|>
<|body_start_1|>
if self.getSubNode(name, Node.LIMIT):
raise HanCannotCreateConf('The limit: ' + name + ' already exists for threshold: ' + self.name)
... | The han representation of a DQThreshold | HanThreshold | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HanThreshold:
"""The han representation of a DQThreshold"""
def __init__(self, name):
"""Creates a han threshold configuration element"""
<|body_0|>
def addLimit(self, name, warning, error):
"""Adds a limit to the threshold @param name: the limits name @param war... | stack_v2_sparse_classes_36k_train_022528 | 30,609 | permissive | [
{
"docstring": "Creates a han threshold configuration element",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": "Adds a limit to the threshold @param name: the limits name @param warning: the limit value for the warning level @param error: the limit value for the er... | 2 | null | Implement the Python class `HanThreshold` described below.
Class description:
The han representation of a DQThreshold
Method signatures and docstrings:
- def __init__(self, name): Creates a han threshold configuration element
- def addLimit(self, name, warning, error): Adds a limit to the threshold @param name: the l... | Implement the Python class `HanThreshold` described below.
Class description:
The han representation of a DQThreshold
Method signatures and docstrings:
- def __init__(self, name): Creates a han threshold configuration element
- def addLimit(self, name, warning, error): Adds a limit to the threshold @param name: the l... | 354f92551294f7be678aebcd7b9d67d2c4448176 | <|skeleton|>
class HanThreshold:
"""The han representation of a DQThreshold"""
def __init__(self, name):
"""Creates a han threshold configuration element"""
<|body_0|>
def addLimit(self, name, warning, error):
"""Adds a limit to the threshold @param name: the limits name @param war... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HanThreshold:
"""The han representation of a DQThreshold"""
def __init__(self, name):
"""Creates a han threshold configuration element"""
Node.__init__(self, name)
self.acceptChild = [Node.LIMIT]
self.nodeType = Node.THRESHOLD
def addLimit(self, name, warning, error):... | the_stack_v2_python_sparse | DataQuality/DataQualityUtils/python/hanwriter.py | strigazi/athena | train | 0 |
7afb0fb6f0da4ba058bd2b265400e8977bd727ce | [
"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... | Service for retrieving and updating individual error groups. | ErrorGroupServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ErrorGroupServiceServicer:
"""Service for retrieving and updating individual error groups."""
def GetGroup(self, request, context):
"""Get the specified group."""
<|body_0|>
def UpdateGroup(self, request, context):
"""Replace the data for the specified group. Fai... | stack_v2_sparse_classes_36k_train_022529 | 3,345 | permissive | [
{
"docstring": "Get the specified group.",
"name": "GetGroup",
"signature": "def GetGroup(self, request, context)"
},
{
"docstring": "Replace the data for the specified group. Fails if the group does not exist.",
"name": "UpdateGroup",
"signature": "def UpdateGroup(self, request, context... | 2 | null | Implement the Python class `ErrorGroupServiceServicer` described below.
Class description:
Service for retrieving and updating individual error groups.
Method signatures and docstrings:
- def GetGroup(self, request, context): Get the specified group.
- def UpdateGroup(self, request, context): Replace the data for the... | Implement the Python class `ErrorGroupServiceServicer` described below.
Class description:
Service for retrieving and updating individual error groups.
Method signatures and docstrings:
- def GetGroup(self, request, context): Get the specified group.
- def UpdateGroup(self, request, context): Replace the data for the... | d897d56bce03d1fda98b79afb08264e51d46c421 | <|skeleton|>
class ErrorGroupServiceServicer:
"""Service for retrieving and updating individual error groups."""
def GetGroup(self, request, context):
"""Get the specified group."""
<|body_0|>
def UpdateGroup(self, request, context):
"""Replace the data for the specified group. Fai... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ErrorGroupServiceServicer:
"""Service for retrieving and updating individual error groups."""
def GetGroup(self, request, context):
"""Get the specified group."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplem... | the_stack_v2_python_sparse | error_reporting/google/cloud/errorreporting_v1beta1/proto/error_group_service_pb2_grpc.py | tswast/google-cloud-python | train | 1 |
bb0b96011d907fd36814a4be9b4aeb737cdd1a12 | [
"if code == None:\n return json.dumps([c.__dict__ for c in Category().selectAllCategories()])\nelse:\n return json.dumps(Category().selectCategory(code).__dict__)",
"if strJson != None:\n category = Category()\n category.__dict__ = json.loads(strJson)\n if category.isNew():\n category.insert... | <|body_start_0|>
if code == None:
return json.dumps([c.__dict__ for c in Category().selectAllCategories()])
else:
return json.dumps(Category().selectCategory(code).__dict__)
<|end_body_0|>
<|body_start_1|>
if strJson != None:
category = Category()
... | Classe que controla os acessos ao cadastro de categorias. | CategoryController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CategoryController:
"""Classe que controla os acessos ao cadastro de categorias."""
def GET(self, code=None):
"""Lista as categorias cadastradas no sistema."""
<|body_0|>
def PUT(self, strJson):
"""Inclui ou atualiza"""
<|body_1|>
def DELETE(self, co... | stack_v2_sparse_classes_36k_train_022530 | 1,689 | permissive | [
{
"docstring": "Lista as categorias cadastradas no sistema.",
"name": "GET",
"signature": "def GET(self, code=None)"
},
{
"docstring": "Inclui ou atualiza",
"name": "PUT",
"signature": "def PUT(self, strJson)"
},
{
"docstring": "Apaga uma categoria do sistema.",
"name": "DELE... | 3 | stack_v2_sparse_classes_30k_train_000104 | Implement the Python class `CategoryController` described below.
Class description:
Classe que controla os acessos ao cadastro de categorias.
Method signatures and docstrings:
- def GET(self, code=None): Lista as categorias cadastradas no sistema.
- def PUT(self, strJson): Inclui ou atualiza
- def DELETE(self, code=N... | Implement the Python class `CategoryController` described below.
Class description:
Classe que controla os acessos ao cadastro de categorias.
Method signatures and docstrings:
- def GET(self, code=None): Lista as categorias cadastradas no sistema.
- def PUT(self, strJson): Inclui ou atualiza
- def DELETE(self, code=N... | bee8c9ecf4ef44ba579e4a3b58acf0c2f1467147 | <|skeleton|>
class CategoryController:
"""Classe que controla os acessos ao cadastro de categorias."""
def GET(self, code=None):
"""Lista as categorias cadastradas no sistema."""
<|body_0|>
def PUT(self, strJson):
"""Inclui ou atualiza"""
<|body_1|>
def DELETE(self, co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CategoryController:
"""Classe que controla os acessos ao cadastro de categorias."""
def GET(self, code=None):
"""Lista as categorias cadastradas no sistema."""
if code == None:
return json.dumps([c.__dict__ for c in Category().selectAllCategories()])
else:
... | the_stack_v2_python_sparse | Back End/Controller/CategoriaController.py | jhelioreis/petnew | train | 0 |
a99b567277147063307a96e3e32d303f9139c279 | [
"form = ArtistForm({'name': '', 'artist_statement': 'test', 'image': 'test'})\nself.assertFalse(form.is_valid())\nself.assertIn('name', form.errors.keys())\nself.assertEqual(form.errors['name'][0], 'This field is required.')",
"form = ArtistForm({'name': 'test', 'artist_statement': '', 'image': 'test'})\nself.ass... | <|body_start_0|>
form = ArtistForm({'name': '', 'artist_statement': 'test', 'image': 'test'})
self.assertFalse(form.is_valid())
self.assertIn('name', form.errors.keys())
self.assertEqual(form.errors['name'][0], 'This field is required.')
<|end_body_0|>
<|body_start_1|>
form = Ar... | Test that the artist form works | TestArtistForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestArtistForm:
"""Test that the artist form works"""
def test_name_is_required(self):
"""Test if form submits without name field"""
<|body_0|>
def test_artist_statement_is_required(self):
"""Test if form submits without artist_statement field"""
<|body_1... | stack_v2_sparse_classes_36k_train_022531 | 1,801 | no_license | [
{
"docstring": "Test if form submits without name field",
"name": "test_name_is_required",
"signature": "def test_name_is_required(self)"
},
{
"docstring": "Test if form submits without artist_statement field",
"name": "test_artist_statement_is_required",
"signature": "def test_artist_st... | 3 | stack_v2_sparse_classes_30k_train_007018 | Implement the Python class `TestArtistForm` described below.
Class description:
Test that the artist form works
Method signatures and docstrings:
- def test_name_is_required(self): Test if form submits without name field
- def test_artist_statement_is_required(self): Test if form submits without artist_statement fiel... | Implement the Python class `TestArtistForm` described below.
Class description:
Test that the artist form works
Method signatures and docstrings:
- def test_name_is_required(self): Test if form submits without name field
- def test_artist_statement_is_required(self): Test if form submits without artist_statement fiel... | b4ef7a46708711bda460667b1f602d0bd67c0bae | <|skeleton|>
class TestArtistForm:
"""Test that the artist form works"""
def test_name_is_required(self):
"""Test if form submits without name field"""
<|body_0|>
def test_artist_statement_is_required(self):
"""Test if form submits without artist_statement field"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestArtistForm:
"""Test that the artist form works"""
def test_name_is_required(self):
"""Test if form submits without name field"""
form = ArtistForm({'name': '', 'artist_statement': 'test', 'image': 'test'})
self.assertFalse(form.is_valid())
self.assertIn('name', form.er... | the_stack_v2_python_sparse | artists/test_forms.py | AmyOShea/MS4-ARTstop | train | 1 |
bc65436d9a2bc4edf2fc88d854bc39f53fa65ad2 | [
"self.fs_type = fs_type\nself.gateway = gateway\nself.protection_domain = protection_domain\nself.read_only = read_only\nself.secret_ref = secret_ref\nself.ssl_enabled = ssl_enabled\nself.storage_mode = storage_mode\nself.storage_pool = storage_pool\nself.system = system\nself.volume_name = volume_name",
"if dict... | <|body_start_0|>
self.fs_type = fs_type
self.gateway = gateway
self.protection_domain = protection_domain
self.read_only = read_only
self.secret_ref = secret_ref
self.ssl_enabled = ssl_enabled
self.storage_mode = storage_mode
self.storage_pool = storage_po... | Implementation of the 'PodInfo_PodSpec_VolumeInfo_ScaleIO' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. gateway (string): TODO: Type description here. protection_domain (string): TODO: Type description here. read_only (bool): TODO: Type description here. secret_ref (Obj... | PodInfo_PodSpec_VolumeInfo_ScaleIO | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PodInfo_PodSpec_VolumeInfo_ScaleIO:
"""Implementation of the 'PodInfo_PodSpec_VolumeInfo_ScaleIO' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. gateway (string): TODO: Type description here. protection_domain (string): TODO: Type description here. ... | stack_v2_sparse_classes_36k_train_022532 | 3,699 | permissive | [
{
"docstring": "Constructor for the PodInfo_PodSpec_VolumeInfo_ScaleIO class",
"name": "__init__",
"signature": "def __init__(self, fs_type=None, gateway=None, protection_domain=None, read_only=None, secret_ref=None, ssl_enabled=None, storage_mode=None, storage_pool=None, system=None, volume_name=None)"... | 2 | null | Implement the Python class `PodInfo_PodSpec_VolumeInfo_ScaleIO` described below.
Class description:
Implementation of the 'PodInfo_PodSpec_VolumeInfo_ScaleIO' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. gateway (string): TODO: Type description here. protection_domain ... | Implement the Python class `PodInfo_PodSpec_VolumeInfo_ScaleIO` described below.
Class description:
Implementation of the 'PodInfo_PodSpec_VolumeInfo_ScaleIO' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. gateway (string): TODO: Type description here. protection_domain ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class PodInfo_PodSpec_VolumeInfo_ScaleIO:
"""Implementation of the 'PodInfo_PodSpec_VolumeInfo_ScaleIO' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. gateway (string): TODO: Type description here. protection_domain (string): TODO: Type description here. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PodInfo_PodSpec_VolumeInfo_ScaleIO:
"""Implementation of the 'PodInfo_PodSpec_VolumeInfo_ScaleIO' model. TODO: type description here. Attributes: fs_type (string): TODO: Type description here. gateway (string): TODO: Type description here. protection_domain (string): TODO: Type description here. read_only (bo... | the_stack_v2_python_sparse | cohesity_management_sdk/models/pod_info_pod_spec_volume_info_scale_io.py | cohesity/management-sdk-python | train | 24 |
f79227895895befb9d6477caac884e53171e7c28 | [
"super().__init__(parent, Qt.FramelessWindowHint | Qt.WindowSystemMenuHint)\nself.question = str(question)\nself.style = style\nself.initUi()",
"self.questionLabel = QLabel(self.question)\nself.questionLabel.setWordWrap(True)\nstyleBtn = '\\n QPushButton {\\n font-family: Asap;\\n fon... | <|body_start_0|>
super().__init__(parent, Qt.FramelessWindowHint | Qt.WindowSystemMenuHint)
self.question = str(question)
self.style = style
self.initUi()
<|end_body_0|>
<|body_start_1|>
self.questionLabel = QLabel(self.question)
self.questionLabel.setWordWrap(True)
... | Dialog to ask a question. | QuestionDialog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuestionDialog:
"""Dialog to ask a question."""
def __init__(self, parent, question, style=None):
"""Init."""
<|body_0|>
def initUi(self):
"""Ui Setup."""
<|body_1|>
def paintEvent(self, event):
"""Set window background color."""
<|bo... | stack_v2_sparse_classes_36k_train_022533 | 27,111 | no_license | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, parent, question, style=None)"
},
{
"docstring": "Ui Setup.",
"name": "initUi",
"signature": "def initUi(self)"
},
{
"docstring": "Set window background color.",
"name": "paintEvent",
"signature"... | 3 | stack_v2_sparse_classes_30k_train_002906 | Implement the Python class `QuestionDialog` described below.
Class description:
Dialog to ask a question.
Method signatures and docstrings:
- def __init__(self, parent, question, style=None): Init.
- def initUi(self): Ui Setup.
- def paintEvent(self, event): Set window background color. | Implement the Python class `QuestionDialog` described below.
Class description:
Dialog to ask a question.
Method signatures and docstrings:
- def __init__(self, parent, question, style=None): Init.
- def initUi(self): Ui Setup.
- def paintEvent(self, event): Set window background color.
<|skeleton|>
class QuestionDi... | a5d18593e689123cac34af552628ed2818ca5d59 | <|skeleton|>
class QuestionDialog:
"""Dialog to ask a question."""
def __init__(self, parent, question, style=None):
"""Init."""
<|body_0|>
def initUi(self):
"""Ui Setup."""
<|body_1|>
def paintEvent(self, event):
"""Set window background color."""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuestionDialog:
"""Dialog to ask a question."""
def __init__(self, parent, question, style=None):
"""Init."""
super().__init__(parent, Qt.FramelessWindowHint | Qt.WindowSystemMenuHint)
self.question = str(question)
self.style = style
self.initUi()
def initUi(s... | the_stack_v2_python_sparse | Dialogs.py | edgary777/lonchepos | train | 0 |
98510541d5a94800927ccd29eacdf2e8a9eda1dc | [
"self._name = name or 'cms_swap'\nif holiday_calendar is None:\n holiday_calendar = dates.create_holiday_calendar(weekend_mask=dates.WeekendMask.SATURDAY_SUNDAY)\nwith tf.name_scope(self._name):\n self._dtype = dtype\n self._start_date = dates.convert_to_date_tensor(start_date)\n self._maturity_date = d... | <|body_start_0|>
self._name = name or 'cms_swap'
if holiday_calendar is None:
holiday_calendar = dates.create_holiday_calendar(weekend_mask=dates.WeekendMask.SATURDAY_SUNDAY)
with tf.name_scope(self._name):
self._dtype = dtype
self._start_date = dates.convert_... | Represents a batch of CMS Swaps. A CMS swap is a swap contract where the floating leg payments are based on the constant maturity swap (CMS) rate. The CMS rate refers to a future fixing of swap rate of a fixed maturity, i.e. the breakeven swap rate on a standard fixed-to-float swap of the specified maturity [1]. Let S_... | CMSSwap | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CMSSwap:
"""Represents a batch of CMS Swaps. A CMS swap is a swap contract where the floating leg payments are based on the constant maturity swap (CMS) rate. The CMS rate refers to a future fixing of swap rate of a fixed maturity, i.e. the breakeven swap rate on a standard fixed-to-float swap of... | stack_v2_sparse_classes_36k_train_022534 | 26,955 | permissive | [
{
"docstring": "Initialize a batch of CMS swap contracts. Args: start_date: A rank 1 `DateTensor` specifying the dates for the inception (start of the accrual) of the swap cpntracts. The shape of the input correspond to the numbercof instruments being created. maturity_date: A rank 1 `DateTensor` specifying the... | 3 | null | Implement the Python class `CMSSwap` described below.
Class description:
Represents a batch of CMS Swaps. A CMS swap is a swap contract where the floating leg payments are based on the constant maturity swap (CMS) rate. The CMS rate refers to a future fixing of swap rate of a fixed maturity, i.e. the breakeven swap ra... | Implement the Python class `CMSSwap` described below.
Class description:
Represents a batch of CMS Swaps. A CMS swap is a swap contract where the floating leg payments are based on the constant maturity swap (CMS) rate. The CMS rate refers to a future fixing of swap rate of a fixed maturity, i.e. the breakeven swap ra... | 0d3a2193c0f2d320b65e602cf01d7a617da484df | <|skeleton|>
class CMSSwap:
"""Represents a batch of CMS Swaps. A CMS swap is a swap contract where the floating leg payments are based on the constant maturity swap (CMS) rate. The CMS rate refers to a future fixing of swap rate of a fixed maturity, i.e. the breakeven swap rate on a standard fixed-to-float swap of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CMSSwap:
"""Represents a batch of CMS Swaps. A CMS swap is a swap contract where the floating leg payments are based on the constant maturity swap (CMS) rate. The CMS rate refers to a future fixing of swap rate of a fixed maturity, i.e. the breakeven swap rate on a standard fixed-to-float swap of the specifie... | the_stack_v2_python_sparse | tf_quant_finance/experimental/instruments/cms_swap.py | google/tf-quant-finance | train | 4,165 |
9cdedc343a3509e9a3ac40b2a79d33704c980b12 | [
"need = defaultdict(int)\nwindow = defaultdict(int)\nfor c in p:\n need[c] += 1\nleft, right = (0, 0)\nvalid = 0\nres = []\nwhile right < len(s):\n c = s[right]\n right += 1\n if c in need:\n window[c] += 1\n if window[c] == need[c]:\n valid += 1\n while right - left >= len(p... | <|body_start_0|>
need = defaultdict(int)
window = defaultdict(int)
for c in p:
need[c] += 1
left, right = (0, 0)
valid = 0
res = []
while right < len(s):
c = s[right]
right += 1
if c in need:
window[c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findAnagramsFramework(self, s, p):
""":type s: str :type p: str :rtype: List[int] use the sliding window framework"""
<|body_0|>
def findAnagrams(self, s, p):
""":type s: str :type p: str :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_022535 | 3,914 | no_license | [
{
"docstring": ":type s: str :type p: str :rtype: List[int] use the sliding window framework",
"name": "findAnagramsFramework",
"signature": "def findAnagramsFramework(self, s, p)"
},
{
"docstring": ":type s: str :type p: str :rtype: List[int]",
"name": "findAnagrams",
"signature": "def ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAnagramsFramework(self, s, p): :type s: str :type p: str :rtype: List[int] use the sliding window framework
- def findAnagrams(self, s, p): :type s: str :type p: str :rty... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAnagramsFramework(self, s, p): :type s: str :type p: str :rtype: List[int] use the sliding window framework
- def findAnagrams(self, s, p): :type s: str :type p: str :rty... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def findAnagramsFramework(self, s, p):
""":type s: str :type p: str :rtype: List[int] use the sliding window framework"""
<|body_0|>
def findAnagrams(self, s, p):
""":type s: str :type p: str :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findAnagramsFramework(self, s, p):
""":type s: str :type p: str :rtype: List[int] use the sliding window framework"""
need = defaultdict(int)
window = defaultdict(int)
for c in p:
need[c] += 1
left, right = (0, 0)
valid = 0
res ... | the_stack_v2_python_sparse | F/FindAllAnagramsInAString.py | bssrdf/pyleet | train | 2 | |
3e61c8ae57ecfedb1b5cfbd62c4b2d1894894c8c | [
"self.symbol_list = context.symbol_list\nself.context = context\nself.heartbeat = context.heartbeat\nself.data_handler_cls = data_handler\nself.execution_handler_cls = execution_handler\nself.portfolio_cls = portfolio\nself.strategy_cls = strategy\nself.risk_handler_cls = risk_handler\nself.broker_handler_cls = bro... | <|body_start_0|>
self.symbol_list = context.symbol_list
self.context = context
self.heartbeat = context.heartbeat
self.data_handler_cls = data_handler
self.execution_handler_cls = execution_handler
self.portfolio_cls = portfolio
self.strategy_cls = strategy
... | Event-driven backtest. | LiveTrader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LiveTrader:
"""Event-driven backtest."""
def __init__(self, data_handler, execution_handler, portfolio, strategy, risk_handler, broker_handler, context):
""". Parameters:"""
<|body_0|>
def _set_up(self):
"""Generates the trading instance objects from their classe... | stack_v2_sparse_classes_36k_train_022536 | 3,842 | no_license | [
{
"docstring": ". Parameters:",
"name": "__init__",
"signature": "def __init__(self, data_handler, execution_handler, portfolio, strategy, risk_handler, broker_handler, context)"
},
{
"docstring": "Generates the trading instance objects from their classes and sets up the trading environment.",
... | 4 | null | Implement the Python class `LiveTrader` described below.
Class description:
Event-driven backtest.
Method signatures and docstrings:
- def __init__(self, data_handler, execution_handler, portfolio, strategy, risk_handler, broker_handler, context): . Parameters:
- def _set_up(self): Generates the trading instance obje... | Implement the Python class `LiveTrader` described below.
Class description:
Event-driven backtest.
Method signatures and docstrings:
- def __init__(self, data_handler, execution_handler, portfolio, strategy, risk_handler, broker_handler, context): . Parameters:
- def _set_up(self): Generates the trading instance obje... | 1b88117961a3912aa9b2c0326aa5081a884d0a8d | <|skeleton|>
class LiveTrader:
"""Event-driven backtest."""
def __init__(self, data_handler, execution_handler, portfolio, strategy, risk_handler, broker_handler, context):
""". Parameters:"""
<|body_0|>
def _set_up(self):
"""Generates the trading instance objects from their classe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LiveTrader:
"""Event-driven backtest."""
def __init__(self, data_handler, execution_handler, portfolio, strategy, risk_handler, broker_handler, context):
""". Parameters:"""
self.symbol_list = context.symbol_list
self.context = context
self.heartbeat = context.heartbeat
... | the_stack_v2_python_sparse | htr/core/engines/live_trader.py | mglcampos/trader | train | 0 |
5e0bb01d74bbd6f718e89f791108781631760596 | [
"yes_to_all = force_import_from_game\nfor data_type in self.DATA_TYPES:\n yes_to_all = self.import_data_type(data_type, force_import_from_game, yes_to_all, with_window=with_window)\n if data_type == 'maps' and first_time and (self.maps is not None):\n archives_msb = self.maps.DukesArchives\n rep... | <|body_start_0|>
yes_to_all = force_import_from_game
for data_type in self.DATA_TYPES:
yes_to_all = self.import_data_type(data_type, force_import_from_game, yes_to_all, with_window=with_window)
if data_type == 'maps' and first_time and (self.maps is not None):
arc... | GameDirectoryProject | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameDirectoryProject:
def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False):
"""Also offer to translate events/regions with entity IDs and export entities modules."""
<|body_0|>
def offer_fix_broken_regions(self, with_w... | stack_v2_sparse_classes_36k_train_022537 | 6,562 | no_license | [
{
"docstring": "Also offer to translate events/regions with entity IDs and export entities modules.",
"name": "initialize_project",
"signature": "def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False)"
},
{
"docstring": "Offer to fix broken ... | 4 | stack_v2_sparse_classes_30k_test_000167 | Implement the Python class `GameDirectoryProject` described below.
Class description:
Implement the GameDirectoryProject class.
Method signatures and docstrings:
- def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False): Also offer to translate events/regions with... | Implement the Python class `GameDirectoryProject` described below.
Class description:
Implement the GameDirectoryProject class.
Method signatures and docstrings:
- def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False): Also offer to translate events/regions with... | 88693c0015056ee8e3d1dbcb795c05fca4349e38 | <|skeleton|>
class GameDirectoryProject:
def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False):
"""Also offer to translate events/regions with entity IDs and export entities modules."""
<|body_0|>
def offer_fix_broken_regions(self, with_w... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameDirectoryProject:
def initialize_project(self, force_import_from_game=False, with_window: ProjectWindow=None, first_time=False):
"""Also offer to translate events/regions with entity IDs and export entities modules."""
yes_to_all = force_import_from_game
for data_type in self.DATA_... | the_stack_v2_python_sparse | soulstruct/darksouls1r/project/core.py | Nahnahchi/soulstruct | train | 0 | |
afc9fd6acedf961760e56df85b34507f4857611f | [
"if name not in Replacements._rep:\n return None\nreturn Replacements._rep[name]",
"if otherclass is None:\n otherclass = classname\nif (classname, otherclass, optype) not in Replacements._oprep:\n return None\nreturn Replacements._oprep[classname, otherclass, optype]"
] | <|body_start_0|>
if name not in Replacements._rep:
return None
return Replacements._rep[name]
<|end_body_0|>
<|body_start_1|>
if otherclass is None:
otherclass = classname
if (classname, otherclass, optype) not in Replacements._oprep:
return None
... | A management singleton for functions that replace existing function calls with either an SDFG or a node. Used in the Python frontend to replace functions such as `numpy.ndarray` and operators such as `Array.__add__`. | Replacements | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Replacements:
"""A management singleton for functions that replace existing function calls with either an SDFG or a node. Used in the Python frontend to replace functions such as `numpy.ndarray` and operators such as `Array.__add__`."""
def get(name):
"""Returns an implementation of ... | stack_v2_sparse_classes_36k_train_022538 | 2,356 | permissive | [
{
"docstring": "Returns an implementation of a function.",
"name": "get",
"signature": "def get(name)"
},
{
"docstring": "Returns an implementation of an operator.",
"name": "getop",
"signature": "def getop(classname: str, optype: str, otherclass: str=None)"
}
] | 2 | null | Implement the Python class `Replacements` described below.
Class description:
A management singleton for functions that replace existing function calls with either an SDFG or a node. Used in the Python frontend to replace functions such as `numpy.ndarray` and operators such as `Array.__add__`.
Method signatures and d... | Implement the Python class `Replacements` described below.
Class description:
A management singleton for functions that replace existing function calls with either an SDFG or a node. Used in the Python frontend to replace functions such as `numpy.ndarray` and operators such as `Array.__add__`.
Method signatures and d... | 4d65e0951c112160fe783766404a806b6043b521 | <|skeleton|>
class Replacements:
"""A management singleton for functions that replace existing function calls with either an SDFG or a node. Used in the Python frontend to replace functions such as `numpy.ndarray` and operators such as `Array.__add__`."""
def get(name):
"""Returns an implementation of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Replacements:
"""A management singleton for functions that replace existing function calls with either an SDFG or a node. Used in the Python frontend to replace functions such as `numpy.ndarray` and operators such as `Array.__add__`."""
def get(name):
"""Returns an implementation of a function.""... | the_stack_v2_python_sparse | dace/frontend/common/op_repository.py | 1C4nfaN/dace | train | 1 |
138a97d2124d1e38e875f47a964e795cc7f712fb | [
"results = []\ndbUtil = MsqlTools()\npageNo = (page - 1) * limit\nif logName == '':\n sql = string.Template('select * from t_log order by operation_time $sortOrder limit $pageNo,$limit;')\n sql = sql.substitute(pageNo=pageNo, limit=limit, sortOrder=sortOrder)\n items = MsqlTools.get_all(dbUtil, sql)\n s... | <|body_start_0|>
results = []
dbUtil = MsqlTools()
pageNo = (page - 1) * limit
if logName == '':
sql = string.Template('select * from t_log order by operation_time $sortOrder limit $pageNo,$limit;')
sql = sql.substitute(pageNo=pageNo, limit=limit, sortOrder=sortOr... | db_log_list | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class db_log_list:
def show_log_list(self, page, limit, sortOrder, logName):
"""查询t_user表所有数据"""
<|body_0|>
def add_log(self, log_name, operation_type, operation_status, log_describes):
"""添加日志 :return:"""
<|body_1|>
def sector_user(self, login_name):
... | stack_v2_sparse_classes_36k_train_022539 | 3,370 | no_license | [
{
"docstring": "查询t_user表所有数据",
"name": "show_log_list",
"signature": "def show_log_list(self, page, limit, sortOrder, logName)"
},
{
"docstring": "添加日志 :return:",
"name": "add_log",
"signature": "def add_log(self, log_name, operation_type, operation_status, log_describes)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_006131 | Implement the Python class `db_log_list` described below.
Class description:
Implement the db_log_list class.
Method signatures and docstrings:
- def show_log_list(self, page, limit, sortOrder, logName): 查询t_user表所有数据
- def add_log(self, log_name, operation_type, operation_status, log_describes): 添加日志 :return:
- def ... | Implement the Python class `db_log_list` described below.
Class description:
Implement the db_log_list class.
Method signatures and docstrings:
- def show_log_list(self, page, limit, sortOrder, logName): 查询t_user表所有数据
- def add_log(self, log_name, operation_type, operation_status, log_describes): 添加日志 :return:
- def ... | 64ced2b9bd1fe9503521024ea2ddc05efc21f969 | <|skeleton|>
class db_log_list:
def show_log_list(self, page, limit, sortOrder, logName):
"""查询t_user表所有数据"""
<|body_0|>
def add_log(self, log_name, operation_type, operation_status, log_describes):
"""添加日志 :return:"""
<|body_1|>
def sector_user(self, login_name):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class db_log_list:
def show_log_list(self, page, limit, sortOrder, logName):
"""查询t_user表所有数据"""
results = []
dbUtil = MsqlTools()
pageNo = (page - 1) * limit
if logName == '':
sql = string.Template('select * from t_log order by operation_time $sortOrder limit $pa... | the_stack_v2_python_sparse | app/db/db_log_list.py | fzj123/auto_test_platform-master | train | 0 | |
5ffb6c30f4adf86f2d0c3d37d0ec642935186672 | [
"data = get_enum_row_by_id(pk)\nif not data:\n raise NotFound\nresult = marshal(data, fields_item_enum_cn, envelope=structure_key_item_cn)\nreturn jsonify(result)",
"result = delete_enum(pk)\nif result:\n success_msg = SUCCESS_MSG.copy()\n return make_response(jsonify(success_msg), 204)\nelse:\n failu... | <|body_start_0|>
data = get_enum_row_by_id(pk)
if not data:
raise NotFound
result = marshal(data, fields_item_enum_cn, envelope=structure_key_item_cn)
return jsonify(result)
<|end_body_0|>
<|body_start_1|>
result = delete_enum(pk)
if result:
succe... | EnumResource | EnumResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnumResource:
"""EnumResource"""
def get(self, pk):
"""Example: curl http://0.0.0.0:5000/yonyou/enum/1 :param pk: :return:"""
<|body_0|>
def delete(self, pk):
"""Example: curl http://0.0.0.0:5000/yonyou/enum/1 -X DELETE :param pk: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_022540 | 3,553 | permissive | [
{
"docstring": "Example: curl http://0.0.0.0:5000/yonyou/enum/1 :param pk: :return:",
"name": "get",
"signature": "def get(self, pk)"
},
{
"docstring": "Example: curl http://0.0.0.0:5000/yonyou/enum/1 -X DELETE :param pk: :return:",
"name": "delete",
"signature": "def delete(self, pk)"
... | 2 | stack_v2_sparse_classes_30k_train_015876 | Implement the Python class `EnumResource` described below.
Class description:
EnumResource
Method signatures and docstrings:
- def get(self, pk): Example: curl http://0.0.0.0:5000/yonyou/enum/1 :param pk: :return:
- def delete(self, pk): Example: curl http://0.0.0.0:5000/yonyou/enum/1 -X DELETE :param pk: :return: | Implement the Python class `EnumResource` described below.
Class description:
EnumResource
Method signatures and docstrings:
- def get(self, pk): Example: curl http://0.0.0.0:5000/yonyou/enum/1 :param pk: :return:
- def delete(self, pk): Example: curl http://0.0.0.0:5000/yonyou/enum/1 -X DELETE :param pk: :return:
<... | 6ef54f3f7efbbaff6169e963dcf45ab25e11e593 | <|skeleton|>
class EnumResource:
"""EnumResource"""
def get(self, pk):
"""Example: curl http://0.0.0.0:5000/yonyou/enum/1 :param pk: :return:"""
<|body_0|>
def delete(self, pk):
"""Example: curl http://0.0.0.0:5000/yonyou/enum/1 -X DELETE :param pk: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnumResource:
"""EnumResource"""
def get(self, pk):
"""Example: curl http://0.0.0.0:5000/yonyou/enum/1 :param pk: :return:"""
data = get_enum_row_by_id(pk)
if not data:
raise NotFound
result = marshal(data, fields_item_enum_cn, envelope=structure_key_item_cn)
... | the_stack_v2_python_sparse | web_api/yonyou/resources/enum.py | zhanghe06/flask_restful | train | 2 |
d9fbd616b087fbbc8ac4e7ebfa1e627b08f9d304 | [
"if isinstance(data, Log):\n data = data.log\nmodel = LogModel(**data)\ndb.session.add(model)\ndb.session.commit()\nreturn model.id",
"id = data.get('id')\nresult = LogModel.query.get(id)\nsoft_delete(result)",
"report_id = data.get('id')\nlogid = data.get('logid')\ntry:\n offset = int(data.get('offset', ... | <|body_start_0|>
if isinstance(data, Log):
data = data.log
model = LogModel(**data)
db.session.add(model)
db.session.commit()
return model.id
<|end_body_0|>
<|body_start_1|>
id = data.get('id')
result = LogModel.query.get(id)
soft_delete(resul... | LogService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogService:
def create(self, data):
""":param data: :return:"""
<|body_0|>
def delete(self, data):
""":param data: :return:"""
<|body_1|>
def search(self, data):
""":param data: :return:"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_022541 | 1,434 | permissive | [
{
"docstring": ":param data: :return:",
"name": "create",
"signature": "def create(self, data)"
},
{
"docstring": ":param data: :return:",
"name": "delete",
"signature": "def delete(self, data)"
},
{
"docstring": ":param data: :return:",
"name": "search",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_004962 | Implement the Python class `LogService` described below.
Class description:
Implement the LogService class.
Method signatures and docstrings:
- def create(self, data): :param data: :return:
- def delete(self, data): :param data: :return:
- def search(self, data): :param data: :return: | Implement the Python class `LogService` described below.
Class description:
Implement the LogService class.
Method signatures and docstrings:
- def create(self, data): :param data: :return:
- def delete(self, data): :param data: :return:
- def search(self, data): :param data: :return:
<|skeleton|>
class LogService:
... | 54dc4000263ab9e8873f0d429a7fe48b11fb727a | <|skeleton|>
class LogService:
def create(self, data):
""":param data: :return:"""
<|body_0|>
def delete(self, data):
""":param data: :return:"""
<|body_1|>
def search(self, data):
""":param data: :return:"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogService:
def create(self, data):
""":param data: :return:"""
if isinstance(data, Log):
data = data.log
model = LogModel(**data)
db.session.add(model)
db.session.commit()
return model.id
def delete(self, data):
""":param data: :return:... | the_stack_v2_python_sparse | clover/log/service.py | taoyanli0808/clover | train | 18 | |
9dd91f29b7ba52fd1bfd24c1d4b5b34cd28d60c7 | [
"compiler = cls(filename)\ncompiler.visit(node)\nreturn compiler.stack.pop()",
"self.filename = filename\nself.block = '<undefined>'\nself.stack = []",
"self.block = node.name\nobj = {'enamldef': True, 'type': node.name, 'base': node.base, 'doc': node.doc, 'lineno': node.lineno, 'identifier': node.identifier, '... | <|body_start_0|>
compiler = cls(filename)
compiler.visit(node)
return compiler.stack.pop()
<|end_body_0|>
<|body_start_1|>
self.filename = filename
self.block = '<undefined>'
self.stack = []
<|end_body_1|>
<|body_start_2|>
self.block = node.name
obj = {'... | A visitor which compiles a Declaration node into a code object. | DeclarationCompiler | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeclarationCompiler:
"""A visitor which compiles a Declaration node into a code object."""
def compile(cls, node, filename):
"""The main entry point of the DeclarationCompiler. This compiler compiles the given Declaration node into a description dictionary which can be used to build ... | stack_v2_sparse_classes_36k_train_022542 | 24,020 | permissive | [
{
"docstring": "The main entry point of the DeclarationCompiler. This compiler compiles the given Declaration node into a description dictionary which can be used to build out the component tree at run time. Top assist with debugging, every production generated by the compiler has the filename, lineno, and bloc... | 6 | stack_v2_sparse_classes_30k_train_015404 | Implement the Python class `DeclarationCompiler` described below.
Class description:
A visitor which compiles a Declaration node into a code object.
Method signatures and docstrings:
- def compile(cls, node, filename): The main entry point of the DeclarationCompiler. This compiler compiles the given Declaration node ... | Implement the Python class `DeclarationCompiler` described below.
Class description:
A visitor which compiles a Declaration node into a code object.
Method signatures and docstrings:
- def compile(cls, node, filename): The main entry point of the DeclarationCompiler. This compiler compiles the given Declaration node ... | 424bba29219de58fe9e47196de6763de8b2009f2 | <|skeleton|>
class DeclarationCompiler:
"""A visitor which compiles a Declaration node into a code object."""
def compile(cls, node, filename):
"""The main entry point of the DeclarationCompiler. This compiler compiles the given Declaration node into a description dictionary which can be used to build ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeclarationCompiler:
"""A visitor which compiles a Declaration node into a code object."""
def compile(cls, node, filename):
"""The main entry point of the DeclarationCompiler. This compiler compiles the given Declaration node into a description dictionary which can be used to build out the compo... | the_stack_v2_python_sparse | enaml/core/enaml_compiler.py | enthought/enaml | train | 17 |
df14c2c069f5f8b9cde8c3ffdc05492e8294cb72 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Schema()",
"from ..entity import Entity\nfrom .property_ import Property_\nfrom ..entity import Entity\nfrom .property_ import Property_\nfields: Dict[str, Callable[[Any], None]] = {'baseType': lambda n: setattr(self, 'base_type', n.ge... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Schema()
<|end_body_0|>
<|body_start_1|>
from ..entity import Entity
from .property_ import Property_
from ..entity import Entity
from .property_ import Property_
... | Schema | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Schema:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Schema:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Schema"""
... | stack_v2_sparse_classes_36k_train_022543 | 2,452 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Schema",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse_... | 3 | stack_v2_sparse_classes_30k_train_008692 | Implement the Python class `Schema` described below.
Class description:
Implement the Schema class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Schema: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: Th... | Implement the Python class `Schema` described below.
Class description:
Implement the Schema class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Schema: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: Th... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Schema:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Schema:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Schema"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Schema:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Schema:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Schema"""
if not p... | the_stack_v2_python_sparse | msgraph/generated/models/external_connectors/schema.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
affaba8fe4d4818a8879fc88b03017d526f7a3e8 | [
"if flask.current_app:\n return flask.g\nelse:\n logger.warning('No current_app, falling back to non-threadsafe database connection')\n return cls",
"holder = cls._holder()\nif not getattr(holder, '_db', None):\n holder._db = db_connection()\nreturn holder._db",
"holder = cls._holder()\nif hasattr(h... | <|body_start_0|>
if flask.current_app:
return flask.g
else:
logger.warning('No current_app, falling back to non-threadsafe database connection')
return cls
<|end_body_0|>
<|body_start_1|>
holder = cls._holder()
if not getattr(holder, '_db', None):
... | GlobalDB | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GlobalDB:
def _holder(cls):
"""We generally want to work in the `g` context (i.e. per request), but there are paths through the app which won't have access. In those situations, fall back to the non-threadsafe static member approach"""
<|body_0|>
def db(cls):
"""Buil... | stack_v2_sparse_classes_36k_train_022544 | 2,596 | permissive | [
{
"docstring": "We generally want to work in the `g` context (i.e. per request), but there are paths through the app which won't have access. In those situations, fall back to the non-threadsafe static member approach",
"name": "_holder",
"signature": "def _holder(cls)"
},
{
"docstring": "Build ... | 3 | null | Implement the Python class `GlobalDB` described below.
Class description:
Implement the GlobalDB class.
Method signatures and docstrings:
- def _holder(cls): We generally want to work in the `g` context (i.e. per request), but there are paths through the app which won't have access. In those situations, fall back to ... | Implement the Python class `GlobalDB` described below.
Class description:
Implement the GlobalDB class.
Method signatures and docstrings:
- def _holder(cls): We generally want to work in the `g` context (i.e. per request), but there are paths through the app which won't have access. In those situations, fall back to ... | b12c73976fd7eb5728eda90e56e053759c733c35 | <|skeleton|>
class GlobalDB:
def _holder(cls):
"""We generally want to work in the `g` context (i.e. per request), but there are paths through the app which won't have access. In those situations, fall back to the non-threadsafe static member approach"""
<|body_0|>
def db(cls):
"""Buil... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GlobalDB:
def _holder(cls):
"""We generally want to work in the `g` context (i.e. per request), but there are paths through the app which won't have access. In those situations, fall back to the non-threadsafe static member approach"""
if flask.current_app:
return flask.g
e... | the_stack_v2_python_sparse | dataactcore/interfaces/db.py | fedspendingtransparency/data-act-broker-backend | train | 55 | |
cefbd0464db5762ad670394baf0502c961302603 | [
"self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')\nself.filtry = Caffe.objects.create(name='filtry', city='Warszawa', street='Filry', house_number='14', postal_code='44-100')\nfirst_cat = Category.objects.create(name='first', caffe=self.caff... | <|body_start_0|>
self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')
self.filtry = Caffe.objects.create(name='filtry', city='Warszawa', street='Filry', house_number='14', postal_code='44-100')
first_cat = Category.objects.cr... | FullProduct tests. | FullProductModelTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FullProductModelTest:
"""FullProduct tests."""
def setUp(self):
"""Test data setup."""
<|body_0|>
def test_full_product(self):
"""Test creating FullProducts."""
<|body_1|>
def test_fullproduct_validation(self):
"""Check if FullProduct has pro... | stack_v2_sparse_classes_36k_train_022545 | 14,711 | permissive | [
{
"docstring": "Test data setup.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test creating FullProducts.",
"name": "test_full_product",
"signature": "def test_full_product(self)"
},
{
"docstring": "Check if FullProduct has proper validation.",
"name":... | 3 | stack_v2_sparse_classes_30k_val_000375 | Implement the Python class `FullProductModelTest` described below.
Class description:
FullProduct tests.
Method signatures and docstrings:
- def setUp(self): Test data setup.
- def test_full_product(self): Test creating FullProducts.
- def test_fullproduct_validation(self): Check if FullProduct has proper validation. | Implement the Python class `FullProductModelTest` described below.
Class description:
FullProduct tests.
Method signatures and docstrings:
- def setUp(self): Test data setup.
- def test_full_product(self): Test creating FullProducts.
- def test_fullproduct_validation(self): Check if FullProduct has proper validation.... | cdb7f5edb29255c7e874eaa6231621063210a8b0 | <|skeleton|>
class FullProductModelTest:
"""FullProduct tests."""
def setUp(self):
"""Test data setup."""
<|body_0|>
def test_full_product(self):
"""Test creating FullProducts."""
<|body_1|>
def test_fullproduct_validation(self):
"""Check if FullProduct has pro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FullProductModelTest:
"""FullProduct tests."""
def setUp(self):
"""Test data setup."""
self.caffe = Caffe.objects.create(name='kafo', city='Gliwice', street='Wieczorka', house_number='14', postal_code='44-100')
self.filtry = Caffe.objects.create(name='filtry', city='Warszawa', str... | the_stack_v2_python_sparse | caffe/reports/test_models.py | VirrageS/io-kawiarnie | train | 3 |
337dc67ed4620a488f66b001d77dd9753dde6486 | [
"try:\n exception = request.json\n (services.log_service().upsert_exception(exception), 201)\nexcept Exception as e:\n nsp.abort(500, 'An internal error has occurred: {}'.format(e))",
"try:\n exception = request.json\n (services.log_service().upsert_exception(exception), 204)\nexcept Exception as e... | <|body_start_0|>
try:
exception = request.json
(services.log_service().upsert_exception(exception), 201)
except Exception as e:
nsp.abort(500, 'An internal error has occurred: {}'.format(e))
<|end_body_0|>
<|body_start_1|>
try:
exception = request... | Exception | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exception:
def post(self):
"""Insert a new exception log"""
<|body_0|>
def put(self):
"""Update an exception object by it's id."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
exception = request.json
(services.log_servi... | stack_v2_sparse_classes_36k_train_022546 | 4,427 | no_license | [
{
"docstring": "Insert a new exception log",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Update an exception object by it's id.",
"name": "put",
"signature": "def put(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007215 | Implement the Python class `Exception` described below.
Class description:
Implement the Exception class.
Method signatures and docstrings:
- def post(self): Insert a new exception log
- def put(self): Update an exception object by it's id. | Implement the Python class `Exception` described below.
Class description:
Implement the Exception class.
Method signatures and docstrings:
- def post(self): Insert a new exception log
- def put(self): Update an exception object by it's id.
<|skeleton|>
class Exception:
def post(self):
"""Insert a new e... | df826cf7098aee59e0a1ced6f465c2e8bb3df9a5 | <|skeleton|>
class Exception:
def post(self):
"""Insert a new exception log"""
<|body_0|>
def put(self):
"""Update an exception object by it's id."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Exception:
def post(self):
"""Insert a new exception log"""
try:
exception = request.json
(services.log_service().upsert_exception(exception), 201)
except Exception as e:
nsp.abort(500, 'An internal error has occurred: {}'.format(e))
def put(sel... | the_stack_v2_python_sparse | patient_portal/patient_portal/api/logs.py | bkh148/patient-cloud | train | 0 | |
39d06fdee411c634ee53e07a1ceda24cefca13b4 | [
"super().__init__()\nself.downsampler = nn.AvgPool1d(4, stride=2, padding=1, count_include_pad=False)\nself.discriminators = nn.ModuleDict()\nfor idx in range(discriminator_number):\n self.discriminators[f'disc_{idx}'] = DiscriminatorBlock(downsampling_factor=downsampling_factor)",
"output = []\nfor name, desc... | <|body_start_0|>
super().__init__()
self.downsampler = nn.AvgPool1d(4, stride=2, padding=1, count_include_pad=False)
self.discriminators = nn.ModuleDict()
for idx in range(discriminator_number):
self.discriminators[f'disc_{idx}'] = DiscriminatorBlock(downsampling_factor=downs... | Discriminator model for MelGAN | Discriminator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Discriminator:
"""Discriminator model for MelGAN"""
def __init__(self, discriminator_number: int=3, downsampling_factor: int=4):
"""Discriminator model for MelGAN Consists of several discriminators with various downsampling factors. Base discriminator consists only of convolutional l... | stack_v2_sparse_classes_36k_train_022547 | 4,148 | no_license | [
{
"docstring": "Discriminator model for MelGAN Consists of several discriminators with various downsampling factors. Base discriminator consists only of convolutional layers. Args: discriminator_number: number of discriminator blocks downsampling_factor: downsampling factor for every discriminator block.",
... | 2 | stack_v2_sparse_classes_30k_train_012327 | Implement the Python class `Discriminator` described below.
Class description:
Discriminator model for MelGAN
Method signatures and docstrings:
- def __init__(self, discriminator_number: int=3, downsampling_factor: int=4): Discriminator model for MelGAN Consists of several discriminators with various downsampling fac... | Implement the Python class `Discriminator` described below.
Class description:
Discriminator model for MelGAN
Method signatures and docstrings:
- def __init__(self, discriminator_number: int=3, downsampling_factor: int=4): Discriminator model for MelGAN Consists of several discriminators with various downsampling fac... | d5eac1cfb7d382c26d9e1961e443941410e1c1ba | <|skeleton|>
class Discriminator:
"""Discriminator model for MelGAN"""
def __init__(self, discriminator_number: int=3, downsampling_factor: int=4):
"""Discriminator model for MelGAN Consists of several discriminators with various downsampling factors. Base discriminator consists only of convolutional l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Discriminator:
"""Discriminator model for MelGAN"""
def __init__(self, discriminator_number: int=3, downsampling_factor: int=4):
"""Discriminator model for MelGAN Consists of several discriminators with various downsampling factors. Base discriminator consists only of convolutional layers. Args: ... | the_stack_v2_python_sparse | src/models/discriminator.py | elephantmipt/MelGAN | train | 6 |
27e37ed6be765abaa07ff4a912dfa1972a82dc2e | [
"self.end_time_usecs = end_time_usecs\nself.environment = environment\nself.job_uids = job_uids\nself.protection_source_id = protection_source_id\nself.start_time_usecs = start_time_usecs",
"if dictionary is None:\n return None\nend_time_usecs = dictionary.get('endTimeUsecs')\nenvironment = dictionary.get('env... | <|body_start_0|>
self.end_time_usecs = end_time_usecs
self.environment = environment
self.job_uids = job_uids
self.protection_source_id = protection_source_id
self.start_time_usecs = start_time_usecs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
retu... | Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Timestamp (in microseconds). environment (EnvironmentRestorePointsForTimeRangeParamEnum): Specifies... | RestorePointsForTimeRangeParam | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestorePointsForTimeRangeParam:
"""Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Timestamp (in microseconds). environment ... | stack_v2_sparse_classes_36k_train_022548 | 6,957 | permissive | [
{
"docstring": "Constructor for the RestorePointsForTimeRangeParam class",
"name": "__init__",
"signature": "def __init__(self, end_time_usecs=None, environment=None, job_uids=None, protection_source_id=None, start_time_usecs=None)"
},
{
"docstring": "Creates an instance of this model from a dic... | 2 | null | Implement the Python class `RestorePointsForTimeRangeParam` described below.
Class description:
Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Ti... | Implement the Python class `RestorePointsForTimeRangeParam` described below.
Class description:
Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Ti... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestorePointsForTimeRangeParam:
"""Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Timestamp (in microseconds). environment ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestorePointsForTimeRangeParam:
"""Implementation of the 'RestorePointsForTimeRangeParam' model. Specifies the request parameters to restore points for time range API. Attributes: end_time_usecs (long|int): Specifies the end time specified as a Unix epoch Timestamp (in microseconds). environment (EnvironmentR... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_points_for_time_range_param.py | cohesity/management-sdk-python | train | 24 |
a9597c3c329e90b11761a1dc46619a08794f40fe | [
"self.FLAGS = FLAGS\nself.input = input_\nself.labels = labels\nself.loss = None\nself.predict = None\nself.train_step = None\nself.evaluation = None",
"with tf.name_scope('architecture'):\n self.predict = self.architecture()\nwith tf.name_scope('loss'):\n self.loss = self.calc_loss()\nwith tf.name_scope('t... | <|body_start_0|>
self.FLAGS = FLAGS
self.input = input_
self.labels = labels
self.loss = None
self.predict = None
self.train_step = None
self.evaluation = None
<|end_body_0|>
<|body_start_1|>
with tf.name_scope('architecture'):
self.predict = ... | This class represents convolutional network for mnist | DeepMnist | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepMnist:
"""This class represents convolutional network for mnist"""
def __init__(self, input_, labels, FLAGS):
"""Constructor"""
<|body_0|>
def build(self):
"""build model"""
<|body_1|>
def architecture(self):
"""From tensorflow website de... | stack_v2_sparse_classes_36k_train_022549 | 5,072 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, input_, labels, FLAGS)"
},
{
"docstring": "build model",
"name": "build",
"signature": "def build(self)"
},
{
"docstring": "From tensorflow website deepnn builds the graph for a deep net for classi... | 6 | stack_v2_sparse_classes_30k_train_004485 | Implement the Python class `DeepMnist` described below.
Class description:
This class represents convolutional network for mnist
Method signatures and docstrings:
- def __init__(self, input_, labels, FLAGS): Constructor
- def build(self): build model
- def architecture(self): From tensorflow website deepnn builds the... | Implement the Python class `DeepMnist` described below.
Class description:
This class represents convolutional network for mnist
Method signatures and docstrings:
- def __init__(self, input_, labels, FLAGS): Constructor
- def build(self): build model
- def architecture(self): From tensorflow website deepnn builds the... | 284774a13bb155770ac0576e3624ff528e73cb18 | <|skeleton|>
class DeepMnist:
"""This class represents convolutional network for mnist"""
def __init__(self, input_, labels, FLAGS):
"""Constructor"""
<|body_0|>
def build(self):
"""build model"""
<|body_1|>
def architecture(self):
"""From tensorflow website de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeepMnist:
"""This class represents convolutional network for mnist"""
def __init__(self, input_, labels, FLAGS):
"""Constructor"""
self.FLAGS = FLAGS
self.input = input_
self.labels = labels
self.loss = None
self.predict = None
self.train_step = No... | the_stack_v2_python_sparse | tutorial/mnist_conv.py | shohad25/thesis | train | 0 |
6c064f3a5b767547fc49ee2eef89b62a6f47a332 | [
"params = base.get_params(None, locals())\nrequest = http.Request('GET', self.get_url(), params)\nreturn (request, parsers.parse_json)",
"params = base.get_params(None, locals())\nrequest = http.Request('DELETE', self.get_url(), params)\nreturn (request, parsers.parse_json)"
] | <|body_start_0|>
params = base.get_params(None, locals())
request = http.Request('GET', self.get_url(), params)
return (request, parsers.parse_json)
<|end_body_0|>
<|body_start_1|>
params = base.get_params(None, locals())
request = http.Request('DELETE', self.get_url(), params)
... | Filters | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Filters:
def get(self, type=None):
"""Returns all filters. Upstream documentation: https://developers.pipedrive.com/v1#methods-Filters"""
<|body_0|>
def delete(self, ids):
"""Marks multiple filters as deleted. Upstream documentation: https://developers.pipedrive.com/... | stack_v2_sparse_classes_36k_train_022550 | 1,086 | permissive | [
{
"docstring": "Returns all filters. Upstream documentation: https://developers.pipedrive.com/v1#methods-Filters",
"name": "get",
"signature": "def get(self, type=None)"
},
{
"docstring": "Marks multiple filters as deleted. Upstream documentation: https://developers.pipedrive.com/v1#methods-Filt... | 2 | null | Implement the Python class `Filters` described below.
Class description:
Implement the Filters class.
Method signatures and docstrings:
- def get(self, type=None): Returns all filters. Upstream documentation: https://developers.pipedrive.com/v1#methods-Filters
- def delete(self, ids): Marks multiple filters as delete... | Implement the Python class `Filters` described below.
Class description:
Implement the Filters class.
Method signatures and docstrings:
- def get(self, type=None): Returns all filters. Upstream documentation: https://developers.pipedrive.com/v1#methods-Filters
- def delete(self, ids): Marks multiple filters as delete... | 25caa745a104c8dc209584fa359294c65dbf88bb | <|skeleton|>
class Filters:
def get(self, type=None):
"""Returns all filters. Upstream documentation: https://developers.pipedrive.com/v1#methods-Filters"""
<|body_0|>
def delete(self, ids):
"""Marks multiple filters as deleted. Upstream documentation: https://developers.pipedrive.com/... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Filters:
def get(self, type=None):
"""Returns all filters. Upstream documentation: https://developers.pipedrive.com/v1#methods-Filters"""
params = base.get_params(None, locals())
request = http.Request('GET', self.get_url(), params)
return (request, parsers.parse_json)
def... | the_stack_v2_python_sparse | libsaas/services/pipedrive/filters.py | piplcom/libsaas | train | 1 | |
5ba168808aada276dad4aad1a07b340dfb890745 | [
"self.deque = collections.deque([])\nself.dic = {}\nself.capacity = capacity",
"if key not in self.dic:\n return -1\nself.deque.remove(key)\nself.deque.append(key)\nreturn self.dic[key]",
"if key in self.dic:\n self.deque.remove(key)\nelif len(self.dic) == self.capacity:\n v = self.deque.popleft()\n ... | <|body_start_0|>
self.deque = collections.deque([])
self.dic = {}
self.capacity = capacity
<|end_body_0|>
<|body_start_1|>
if key not in self.dic:
return -1
self.deque.remove(key)
self.deque.append(key)
return self.dic[key]
<|end_body_1|>
<|body_star... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_022551 | 2,684 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: nothing",
"name": "set",
"sig... | 3 | stack_v2_sparse_classes_30k_train_000261 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :rtype: int
- def set(self, key, value): :type key: int :type value: int :rtype: nothing
<|skeleton|>
cla... | 9b82e3bd1b404e3cff31469986577ceec3924f73 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":rtype: int"""
<|body_1|>
def set(self, key, value):
""":type key: int :type value: int :rtype: nothing"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.deque = collections.deque([])
self.dic = {}
self.capacity = capacity
def get(self, key):
""":rtype: int"""
if key not in self.dic:
return -1
self.deque.remove(key)
... | the_stack_v2_python_sparse | Python/146. LRU Cache.py | Qiumy/leetcode | train | 0 | |
0f3241d2f903e0e00fa0abcd291bec7d9d73ae7c | [
"super(EncoderLayer, self).__init__()\nwith self.init_scope():\n self.self_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_bias=initial_bias)\n self.feed_forward = PositionwiseFeedForward(n_units, d_units=d_units, dropout=dropout, initialW=initialW, initial_bias=initial_bias)... | <|body_start_0|>
super(EncoderLayer, self).__init__()
with self.init_scope():
self.self_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_bias=initial_bias)
self.feed_forward = PositionwiseFeedForward(n_units, d_units=d_units, dropout=dropout, init... | Single encoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate | EncoderLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderLayer:
"""Single encoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, ... | stack_v2_sparse_classes_36k_train_022552 | 1,903 | permissive | [
{
"docstring": "Initialize EncoderLayer.",
"name": "__init__",
"signature": "def __init__(self, n_units, d_units=0, h=8, dropout=0.1, initialW=None, initial_bias=None)"
},
{
"docstring": "Forward Positional Encoding.",
"name": "forward",
"signature": "def forward(self, e, xx_mask, batch)... | 2 | null | Implement the Python class `EncoderLayer` described below.
Class description:
Single encoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout ra... | Implement the Python class `EncoderLayer` described below.
Class description:
Single encoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout ra... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class EncoderLayer:
"""Single encoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderLayer:
"""Single encoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, d_units=0, h=... | the_stack_v2_python_sparse | espnet/nets/chainer_backend/transformer/encoder_layer.py | espnet/espnet | train | 7,242 |
737e211d3b7624f7cadd1f7699e16d496a82375f | [
"user = users.get_current_user()\nif not user:\n self.response.out.write(json.dumps(error_obj('User not logged in.')))\n return\nfriend = self.request.get('email')\nif not friend:\n self.response.out.write(json.dumps(error_obj('Must provide email of friend to add.')))\n return\naccount = user_info.get_u... | <|body_start_0|>
user = users.get_current_user()
if not user:
self.response.out.write(json.dumps(error_obj('User not logged in.')))
return
friend = self.request.get('email')
if not friend:
self.response.out.write(json.dumps(error_obj('Must provide emai... | Friend | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Friend:
def get(self):
"""Get a global friend's availability and blurb."""
<|body_0|>
def post(self):
"""Add a friend"""
<|body_1|>
def delete(self):
"""Remove a friend."""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
user = use... | stack_v2_sparse_classes_36k_train_022553 | 3,414 | no_license | [
{
"docstring": "Get a global friend's availability and blurb.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Add a friend",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Remove a friend.",
"name": "delete",
"signature": "def delete(sel... | 3 | stack_v2_sparse_classes_30k_train_020791 | Implement the Python class `Friend` described below.
Class description:
Implement the Friend class.
Method signatures and docstrings:
- def get(self): Get a global friend's availability and blurb.
- def post(self): Add a friend
- def delete(self): Remove a friend. | Implement the Python class `Friend` described below.
Class description:
Implement the Friend class.
Method signatures and docstrings:
- def get(self): Get a global friend's availability and blurb.
- def post(self): Add a friend
- def delete(self): Remove a friend.
<|skeleton|>
class Friend:
def get(self):
... | 0f121a58617131c01ff76ccca0e46a41aae76db6 | <|skeleton|>
class Friend:
def get(self):
"""Get a global friend's availability and blurb."""
<|body_0|>
def post(self):
"""Add a friend"""
<|body_1|>
def delete(self):
"""Remove a friend."""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Friend:
def get(self):
"""Get a global friend's availability and blurb."""
user = users.get_current_user()
if not user:
self.response.out.write(json.dumps(error_obj('User not logged in.')))
return
friend = self.request.get('email')
if not friend:... | the_stack_v2_python_sparse | controllers/friend.py | ShelleyGoldberg/golight | train | 0 | |
664d0cd8a14df0c733193adf7cf4a6c6e7748a5c | [
"filtered = [x for x in self if ue_id in x.ue_measurements]\ncells = sorted(filtered, key=lambda x: x.ue_measurements[ue_id]['rsrp'], reverse=True)\nreturn CellPool(cells)",
"filtered = [x for x in self if ue_id in x.ue_measurements]\ncells = sorted(filtered, key=lambda x: x.ue_measurements[ue_id]['rsrq'], revers... | <|body_start_0|>
filtered = [x for x in self if ue_id in x.ue_measurements]
cells = sorted(filtered, key=lambda x: x.ue_measurements[ue_id]['rsrp'], reverse=True)
return CellPool(cells)
<|end_body_0|>
<|body_start_1|>
filtered = [x for x in self if ue_id in x.ue_measurements]
ce... | EmPOWER cell pool. This extends the list in order to add a few filtering and sorting methods | CellPool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CellPool:
"""EmPOWER cell pool. This extends the list in order to add a few filtering and sorting methods"""
def sort_by_rsrp(self, ue_id):
"""Return list sorted by rsrp for the specified address."""
<|body_0|>
def sort_by_rsrq(self, ue_id):
"""Return list sorted... | stack_v2_sparse_classes_36k_train_022554 | 5,209 | permissive | [
{
"docstring": "Return list sorted by rsrp for the specified address.",
"name": "sort_by_rsrp",
"signature": "def sort_by_rsrp(self, ue_id)"
},
{
"docstring": "Return list sorted by rsrq for the specified address.",
"name": "sort_by_rsrq",
"signature": "def sort_by_rsrq(self, ue_id)"
}... | 4 | stack_v2_sparse_classes_30k_train_001167 | Implement the Python class `CellPool` described below.
Class description:
EmPOWER cell pool. This extends the list in order to add a few filtering and sorting methods
Method signatures and docstrings:
- def sort_by_rsrp(self, ue_id): Return list sorted by rsrp for the specified address.
- def sort_by_rsrq(self, ue_id... | Implement the Python class `CellPool` described below.
Class description:
EmPOWER cell pool. This extends the list in order to add a few filtering and sorting methods
Method signatures and docstrings:
- def sort_by_rsrp(self, ue_id): Return list sorted by rsrp for the specified address.
- def sort_by_rsrq(self, ue_id... | eda52649f855722fdec1d02e25a28c61a8fbda06 | <|skeleton|>
class CellPool:
"""EmPOWER cell pool. This extends the list in order to add a few filtering and sorting methods"""
def sort_by_rsrp(self, ue_id):
"""Return list sorted by rsrp for the specified address."""
<|body_0|>
def sort_by_rsrq(self, ue_id):
"""Return list sorted... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CellPool:
"""EmPOWER cell pool. This extends the list in order to add a few filtering and sorting methods"""
def sort_by_rsrp(self, ue_id):
"""Return list sorted by rsrp for the specified address."""
filtered = [x for x in self if ue_id in x.ue_measurements]
cells = sorted(filtere... | the_stack_v2_python_sparse | empower/core/cellpool.py | imec-idlab/sdn_wifi_manager | train | 0 |
ff0079322c9c2cf6171813bc663a3b31c2aaa26c | [
"for entity in obj.entity_set.all():\n if user.has_perm('share_entity', entity):\n update_permission(entity, payload)\nfor data in obj.data.all():\n if user.has_perm('share_data', data):\n update_permission(data, payload)",
"if not request.user.is_authenticated:\n raise exceptions.NotFound\... | <|body_start_0|>
for entity in obj.entity_set.all():
if user.has_perm('share_entity', entity):
update_permission(entity, payload)
for data in obj.data.all():
if user.has_perm('share_data', data):
update_permission(data, payload)
<|end_body_0|>
<|b... | Base API view for :class:`Collection` objects. | BaseCollectionViewSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseCollectionViewSet:
"""Base API view for :class:`Collection` objects."""
def set_content_permissions(self, user, obj, payload):
"""Apply permissions to data objects and entities in ``Collection``."""
<|body_0|>
def create(self, request, *args, **kwargs):
"""On... | stack_v2_sparse_classes_36k_train_022555 | 3,589 | permissive | [
{
"docstring": "Apply permissions to data objects and entities in ``Collection``.",
"name": "set_content_permissions",
"signature": "def set_content_permissions(self, user, obj, payload)"
},
{
"docstring": "Only authenticated users can create new collections.",
"name": "create",
"signatu... | 3 | stack_v2_sparse_classes_30k_train_020515 | Implement the Python class `BaseCollectionViewSet` described below.
Class description:
Base API view for :class:`Collection` objects.
Method signatures and docstrings:
- def set_content_permissions(self, user, obj, payload): Apply permissions to data objects and entities in ``Collection``.
- def create(self, request,... | Implement the Python class `BaseCollectionViewSet` described below.
Class description:
Base API view for :class:`Collection` objects.
Method signatures and docstrings:
- def set_content_permissions(self, user, obj, payload): Apply permissions to data objects and entities in ``Collection``.
- def create(self, request,... | 11a06a9d741dcc999253246919a0abc12127fd2a | <|skeleton|>
class BaseCollectionViewSet:
"""Base API view for :class:`Collection` objects."""
def set_content_permissions(self, user, obj, payload):
"""Apply permissions to data objects and entities in ``Collection``."""
<|body_0|>
def create(self, request, *args, **kwargs):
"""On... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseCollectionViewSet:
"""Base API view for :class:`Collection` objects."""
def set_content_permissions(self, user, obj, payload):
"""Apply permissions to data objects and entities in ``Collection``."""
for entity in obj.entity_set.all():
if user.has_perm('share_entity', entit... | the_stack_v2_python_sparse | resolwe/flow/views/collection.py | romunov/resolwe | train | 0 |
44e6c8601ed236699e42dfb54d278190afe77e2f | [
"super(TrafficStreamsBaseClass, self).__init__()\nself.p1_dst_start_mac = u'02:02:00:00:12:00'\nself.p2_dst_start_mac = u'02:02:00:00:02:00'\nself.p1_src_start_ip = u'10.0.0.1'\nself.p1_dst_start_ip = u'20.0.0.0'\nself.p1_dst_end_ip = u'20.0.0.3'\nself.p2_src_start_ip = u'20.0.0.1'\nself.p2_dst_start_ip = u'10.0.0.... | <|body_start_0|>
super(TrafficStreamsBaseClass, self).__init__()
self.p1_dst_start_mac = u'02:02:00:00:12:00'
self.p2_dst_start_mac = u'02:02:00:00:02:00'
self.p1_src_start_ip = u'10.0.0.1'
self.p1_dst_start_ip = u'20.0.0.0'
self.p1_dst_end_ip = u'20.0.0.3'
self.p... | Stream profile. | TrafficStreams | [
"GPL-2.0-only",
"GPL-1.0-or-later",
"CC-BY-4.0",
"Apache-2.0",
"LicenseRef-scancode-dco-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrafficStreams:
"""Stream profile."""
def __init__(self):
"""Initialization and setting of streams' parameters."""
<|body_0|>
def define_packets(self):
"""Defines the packets to be sent from the traffic generator. Packet definition: | ETH | IP | :returns: Packets... | stack_v2_sparse_classes_36k_train_022556 | 4,907 | permissive | [
{
"docstring": "Initialization and setting of streams' parameters.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Defines the packets to be sent from the traffic generator. Packet definition: | ETH | IP | :returns: Packets to be sent from the traffic generator. :rtype... | 2 | null | Implement the Python class `TrafficStreams` described below.
Class description:
Stream profile.
Method signatures and docstrings:
- def __init__(self): Initialization and setting of streams' parameters.
- def define_packets(self): Defines the packets to be sent from the traffic generator. Packet definition: | ETH | I... | Implement the Python class `TrafficStreams` described below.
Class description:
Stream profile.
Method signatures and docstrings:
- def __init__(self): Initialization and setting of streams' parameters.
- def define_packets(self): Defines the packets to be sent from the traffic generator. Packet definition: | ETH | I... | 947057d7310cd1602119258c6b82fbb25fe1b79d | <|skeleton|>
class TrafficStreams:
"""Stream profile."""
def __init__(self):
"""Initialization and setting of streams' parameters."""
<|body_0|>
def define_packets(self):
"""Defines the packets to be sent from the traffic generator. Packet definition: | ETH | IP | :returns: Packets... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrafficStreams:
"""Stream profile."""
def __init__(self):
"""Initialization and setting of streams' parameters."""
super(TrafficStreamsBaseClass, self).__init__()
self.p1_dst_start_mac = u'02:02:00:00:12:00'
self.p2_dst_start_mac = u'02:02:00:00:02:00'
self.p1_src_... | the_stack_v2_python_sparse | GPL/traffic_profiles/trex/trex-stl-3n-ethip4-ip4dst4-2cnf.py | FDio/csit | train | 28 |
dbb04c94750c152755d66a5a56a1f3fb7dc714bb | [
"super()._define_vars()\nself._transformer: Transformer = Transformer()\n'\\n Our lark->veredi tree transformer.\\n '\nself._variables: MutableMapping[lark.Token, tree.Node] = {}\n'\\n A collection to hold the name & value of any variables declared in the\\n tree.\\n '\nself._mili... | <|body_start_0|>
super()._define_vars()
self._transformer: Transformer = Transformer()
'\n Our lark->veredi tree transformer.\n '
self._variables: MutableMapping[lark.Token, tree.Node] = {}
'\n A collection to hold the name & value of any variables declared i... | MathParser interface implementation. Wraps up the lark parsing and tranformation operations for getting from a string to some valid d20 math tree. | D20Parser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class D20Parser:
"""MathParser interface implementation. Wraps up the lark parsing and tranformation operations for getting from a string to some valid d20 math tree."""
def _define_vars(self) -> None:
"""Instance variable definitions, type hinting, doc strings, etc."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_022557 | 11,922 | no_license | [
{
"docstring": "Instance variable definitions, type hinting, doc strings, etc.",
"name": "_define_vars",
"signature": "def _define_vars(self) -> None"
},
{
"docstring": "Initialize/reset/clear/whatever our instance variables in prep for next parse & transform.",
"name": "_set_up",
"signa... | 3 | stack_v2_sparse_classes_30k_train_018290 | Implement the Python class `D20Parser` described below.
Class description:
MathParser interface implementation. Wraps up the lark parsing and tranformation operations for getting from a string to some valid d20 math tree.
Method signatures and docstrings:
- def _define_vars(self) -> None: Instance variable definition... | Implement the Python class `D20Parser` described below.
Class description:
MathParser interface implementation. Wraps up the lark parsing and tranformation operations for getting from a string to some valid d20 math tree.
Method signatures and docstrings:
- def _define_vars(self) -> None: Instance variable definition... | 8c9fc1170ceac335985686571568eebf08b0db7a | <|skeleton|>
class D20Parser:
"""MathParser interface implementation. Wraps up the lark parsing and tranformation operations for getting from a string to some valid d20 math tree."""
def _define_vars(self) -> None:
"""Instance variable definitions, type hinting, doc strings, etc."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class D20Parser:
"""MathParser interface implementation. Wraps up the lark parsing and tranformation operations for getting from a string to some valid d20 math tree."""
def _define_vars(self) -> None:
"""Instance variable definitions, type hinting, doc strings, etc."""
super()._define_vars()
... | the_stack_v2_python_sparse | math/d20/parser.py | cole-brown/veredi-code | train | 1 |
d2b337f57706b002e9b6442f6342d3996e2637c9 | [
"super().__init__()\nif config and isinstance(config, dict):\n self.update(config)",
"for key in dir(obj):\n if not key.isupper():\n continue\n self[key] = getattr(obj, key)",
"for key, value in kw.items():\n if not key.isupper():\n continue\n self[key] = value",
"fmt_js = json.lo... | <|body_start_0|>
super().__init__()
if config and isinstance(config, dict):
self.update(config)
<|end_body_0|>
<|body_start_1|>
for key in dir(obj):
if not key.isupper():
continue
self[key] = getattr(obj, key)
<|end_body_1|>
<|body_start_2|>
... | Extend origin dict class | Config | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
"""Extend origin dict class"""
def __init__(self, config: t.Optional[t.Dict]=None) -> None:
"""Initialize config instance"""
<|body_0|>
def from_object(self, obj: object) -> None:
"""Read config items from python object"""
<|body_1|>
def from... | stack_v2_sparse_classes_36k_train_022558 | 2,393 | permissive | [
{
"docstring": "Initialize config instance",
"name": "__init__",
"signature": "def __init__(self, config: t.Optional[t.Dict]=None) -> None"
},
{
"docstring": "Read config items from python object",
"name": "from_object",
"signature": "def from_object(self, obj: object) -> None"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_006238 | Implement the Python class `Config` described below.
Class description:
Extend origin dict class
Method signatures and docstrings:
- def __init__(self, config: t.Optional[t.Dict]=None) -> None: Initialize config instance
- def from_object(self, obj: object) -> None: Read config items from python object
- def from_dic... | Implement the Python class `Config` described below.
Class description:
Extend origin dict class
Method signatures and docstrings:
- def __init__(self, config: t.Optional[t.Dict]=None) -> None: Initialize config instance
- def from_object(self, obj: object) -> None: Read config items from python object
- def from_dic... | 6df8d6c26ec095e6c6c78101087c452e7bc713df | <|skeleton|>
class Config:
"""Extend origin dict class"""
def __init__(self, config: t.Optional[t.Dict]=None) -> None:
"""Initialize config instance"""
<|body_0|>
def from_object(self, obj: object) -> None:
"""Read config items from python object"""
<|body_1|>
def from... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Config:
"""Extend origin dict class"""
def __init__(self, config: t.Optional[t.Dict]=None) -> None:
"""Initialize config instance"""
super().__init__()
if config and isinstance(config, dict):
self.update(config)
def from_object(self, obj: object) -> None:
... | the_stack_v2_python_sparse | mask/config.py | Eastwu5788/Mask | train | 40 |
944d8ac6e854cc311959fd3e513e9bc8932e7ce9 | [
"response = self.client.get(reverse('blog_post_list'))\nself.assertEqual(response.status_code, 200)\nresponse = self.client.get(reverse('blog_post_feed', args=('rss',)))\nself.assertEqual(response.status_code, 200)\nresponse = self.client.get(reverse('blog_post_feed', args=('atom',)))\nself.assertEqual(response.sta... | <|body_start_0|>
response = self.client.get(reverse('blog_post_list'))
self.assertEqual(response.status_code, 200)
response = self.client.get(reverse('blog_post_feed', args=('rss',)))
self.assertEqual(response.status_code, 200)
response = self.client.get(reverse('blog_post_feed',... | BlogTests | [
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlogTests:
def test_blog_views(self):
"""Basic status code test for blog views."""
<|body_0|>
def test_login_protected_blog(self):
"""Test the blog is login protected if its page has login_required set to True."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_022559 | 2,048 | permissive | [
{
"docstring": "Basic status code test for blog views.",
"name": "test_blog_views",
"signature": "def test_blog_views(self)"
},
{
"docstring": "Test the blog is login protected if its page has login_required set to True.",
"name": "test_login_protected_blog",
"signature": "def test_login... | 2 | stack_v2_sparse_classes_30k_train_010404 | Implement the Python class `BlogTests` described below.
Class description:
Implement the BlogTests class.
Method signatures and docstrings:
- def test_blog_views(self): Basic status code test for blog views.
- def test_login_protected_blog(self): Test the blog is login protected if its page has login_required set to ... | Implement the Python class `BlogTests` described below.
Class description:
Implement the BlogTests class.
Method signatures and docstrings:
- def test_blog_views(self): Basic status code test for blog views.
- def test_login_protected_blog(self): Test the blog is login protected if its page has login_required set to ... | 66b5a1089ed0ce2e615f889f35b5e39db91950ae | <|skeleton|>
class BlogTests:
def test_blog_views(self):
"""Basic status code test for blog views."""
<|body_0|>
def test_login_protected_blog(self):
"""Test the blog is login protected if its page has login_required set to True."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BlogTests:
def test_blog_views(self):
"""Basic status code test for blog views."""
response = self.client.get(reverse('blog_post_list'))
self.assertEqual(response.status_code, 200)
response = self.client.get(reverse('blog_post_feed', args=('rss',)))
self.assertEqual(res... | the_stack_v2_python_sparse | mezzanine/blog/tests.py | yasakawa/mezzanine | train | 4 | |
b56e2e75fedbd56d73f2eba058a750e3349ad41f | [
"for k in dir(self.Default):\n if k[0] == '_':\n continue\n v = getattr(self.Default, k)\n if callable(v):\n continue\n self[k] = copy.copy(v)\nDict.__init__(self, *args, **kwargs)",
"if cls.__components is None:\n cls.__components = {}\nreturn cls.__components",
"def wrapper(target... | <|body_start_0|>
for k in dir(self.Default):
if k[0] == '_':
continue
v = getattr(self.Default, k)
if callable(v):
continue
self[k] = copy.copy(v)
Dict.__init__(self, *args, **kwargs)
<|end_body_0|>
<|body_start_1|>
... | デフォルトの辞書エントリを持つ `Dict` クラス; デフォルトの辞書エントリの値は :func:`copy.copy` によって浅いコピーが行われる。 TODO: components, register についての説明 | AutoDict | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoDict:
"""デフォルトの辞書エントリを持つ `Dict` クラス; デフォルトの辞書エントリの値は :func:`copy.copy` によって浅いコピーが行われる。 TODO: components, register についての説明"""
def __init__(self, *args, **kwargs):
"""デフォルトの辞書エントリで初期化した後に、与えられた引数で dictとして初期化する。"""
<|body_0|>
def components(cls):
"""この辞書の要素となりえる... | stack_v2_sparse_classes_36k_train_022560 | 22,736 | permissive | [
{
"docstring": "デフォルトの辞書エントリで初期化した後に、与えられた引数で dictとして初期化する。",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "この辞書の要素となりえる `AutoDict` のサブクラスの一覧を得る",
"name": "components",
"signature": "def components(cls)"
},
{
"docstring": "この辞書の要素となりえる ... | 4 | stack_v2_sparse_classes_30k_train_017081 | Implement the Python class `AutoDict` described below.
Class description:
デフォルトの辞書エントリを持つ `Dict` クラス; デフォルトの辞書エントリの値は :func:`copy.copy` によって浅いコピーが行われる。 TODO: components, register についての説明
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): デフォルトの辞書エントリで初期化した後に、与えられた引数で dictとして初期化する。
- def componen... | Implement the Python class `AutoDict` described below.
Class description:
デフォルトの辞書エントリを持つ `Dict` クラス; デフォルトの辞書エントリの値は :func:`copy.copy` によって浅いコピーが行われる。 TODO: components, register についての説明
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): デフォルトの辞書エントリで初期化した後に、与えられた引数で dictとして初期化する。
- def componen... | ba9190524d7543347208e7ebf0618e2605dd4649 | <|skeleton|>
class AutoDict:
"""デフォルトの辞書エントリを持つ `Dict` クラス; デフォルトの辞書エントリの値は :func:`copy.copy` によって浅いコピーが行われる。 TODO: components, register についての説明"""
def __init__(self, *args, **kwargs):
"""デフォルトの辞書エントリで初期化した後に、与えられた引数で dictとして初期化する。"""
<|body_0|>
def components(cls):
"""この辞書の要素となりえる... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutoDict:
"""デフォルトの辞書エントリを持つ `Dict` クラス; デフォルトの辞書エントリの値は :func:`copy.copy` によって浅いコピーが行われる。 TODO: components, register についての説明"""
def __init__(self, *args, **kwargs):
"""デフォルトの辞書エントリで初期化した後に、与えられた引数で dictとして初期化する。"""
for k in dir(self.Default):
if k[0] == '_':
c... | the_stack_v2_python_sparse | amp/core/utils.py | nohomepand/amp | train | 0 |
215f778e1a813fb3df4c494c0a9e8e05d639cd63 | [
"left, right = divmod(n, 26)\nres = string.uppercase[right - 1]\nif right == 0:\n left -= 1\nwhile left:\n left, right = divmod(left, 26)\n res = string.uppercase[right - 1] + res\n if right == 0:\n left -= 1\nreturn res",
"res = ''\nwhile n:\n n -= 1\n n, right = divmod(n, 26)\n res =... | <|body_start_0|>
left, right = divmod(n, 26)
res = string.uppercase[right - 1]
if right == 0:
left -= 1
while left:
left, right = divmod(left, 26)
res = string.uppercase[right - 1] + res
if right == 0:
left -= 1
retu... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _convertToTitle(self, n):
""":type n: int :rtype: str"""
<|body_0|>
def convertToTitle(self, n):
""":type n: int :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
left, right = divmod(n, 26)
res = string.uppercase[rig... | stack_v2_sparse_classes_36k_train_022561 | 1,643 | permissive | [
{
"docstring": ":type n: int :rtype: str",
"name": "_convertToTitle",
"signature": "def _convertToTitle(self, n)"
},
{
"docstring": ":type n: int :rtype: str",
"name": "convertToTitle",
"signature": "def convertToTitle(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _convertToTitle(self, n): :type n: int :rtype: str
- def convertToTitle(self, n): :type n: int :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _convertToTitle(self, n): :type n: int :rtype: str
- def convertToTitle(self, n): :type n: int :rtype: str
<|skeleton|>
class Solution:
def _convertToTitle(self, n):
... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _convertToTitle(self, n):
""":type n: int :rtype: str"""
<|body_0|>
def convertToTitle(self, n):
""":type n: int :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _convertToTitle(self, n):
""":type n: int :rtype: str"""
left, right = divmod(n, 26)
res = string.uppercase[right - 1]
if right == 0:
left -= 1
while left:
left, right = divmod(left, 26)
res = string.uppercase[right - 1]... | the_stack_v2_python_sparse | 168.excel-sheet-column-title.py | windard/leeeeee | train | 0 | |
88e9c16bb8871fb99e9b0fae3b8b4e3f02d4f5e1 | [
"super(CheckMainPage, cls).setUpClass()\ncls.pagelogin = NCPLogin(cls.browserclass.get_driver())\ncls.pageindex = PageIndex(cls.browserclass.get_driver())",
"self.log.info('--------- Start Login ---------')\nself.browserclass.get_driver().get(self.loginurl)\nself.pagelogin.NCPuserlogin('admin', '88888888')\ncheck... | <|body_start_0|>
super(CheckMainPage, cls).setUpClass()
cls.pagelogin = NCPLogin(cls.browserclass.get_driver())
cls.pageindex = PageIndex(cls.browserclass.get_driver())
<|end_body_0|>
<|body_start_1|>
self.log.info('--------- Start Login ---------')
self.browserclass.get_driver(... | CheckMainPage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckMainPage:
def setUpClass(cls):
"""测试类中所有测试方法执行前执行的方法"""
<|body_0|>
def test_a_weblogin(self):
"""登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:"""
<|body_1|>
def test_b_pagecheck(self, menu1, menu2, menu3, check_a):
"""数据驱动，左侧菜单点击及页面显示check 三个参数依... | stack_v2_sparse_classes_36k_train_022562 | 6,726 | no_license | [
{
"docstring": "测试类中所有测试方法执行前执行的方法",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:",
"name": "test_a_weblogin",
"signature": "def test_a_weblogin(self)"
},
{
"docstring": "数据驱动，左侧菜单点击及页面显示check 三个参数依次是 一级菜单 二... | 3 | stack_v2_sparse_classes_30k_train_014200 | Implement the Python class `CheckMainPage` described below.
Class description:
Implement the CheckMainPage class.
Method signatures and docstrings:
- def setUpClass(cls): 测试类中所有测试方法执行前执行的方法
- def test_a_weblogin(self): 登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:
- def test_b_pagecheck(self, menu1, menu2, menu3, check_a... | Implement the Python class `CheckMainPage` described below.
Class description:
Implement the CheckMainPage class.
Method signatures and docstrings:
- def setUpClass(cls): 测试类中所有测试方法执行前执行的方法
- def test_a_weblogin(self): 登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:
- def test_b_pagecheck(self, menu1, menu2, menu3, check_a... | 08b98e08b76ed2a4984efb7f543ed63eabe30757 | <|skeleton|>
class CheckMainPage:
def setUpClass(cls):
"""测试类中所有测试方法执行前执行的方法"""
<|body_0|>
def test_a_weblogin(self):
"""登录测试，并为后面的菜单页面check测试，提供登录后的系统操作 :return:"""
<|body_1|>
def test_b_pagecheck(self, menu1, menu2, menu3, check_a):
"""数据驱动，左侧菜单点击及页面显示check 三个参数依... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckMainPage:
def setUpClass(cls):
"""测试类中所有测试方法执行前执行的方法"""
super(CheckMainPage, cls).setUpClass()
cls.pagelogin = NCPLogin(cls.browserclass.get_driver())
cls.pageindex = PageIndex(cls.browserclass.get_driver())
def test_a_weblogin(self):
"""登录测试，并为后面的菜单页面check测试，... | the_stack_v2_python_sparse | Sys_NCP/TestClass/checkMainPage.py | duozi/webUITestLight | train | 0 | |
a61acef0341ef1e902641da8ed0a0506f5334f30 | [
"job_log = JobLog.get(job_id=job_id)\nif not job_log:\n job_log = JobLog(job_id=job_id)\njob_log.last_run = datetime.utcnow()\ncommit()",
"job_log = JobLog.get(job_id=job_id)\nif not job_log:\n return False\nreturn job_log.last_run > datetime.utcnow() - timedelta(minutes=recent_minutes)"
] | <|body_start_0|>
job_log = JobLog.get(job_id=job_id)
if not job_log:
job_log = JobLog(job_id=job_id)
job_log.last_run = datetime.utcnow()
commit()
<|end_body_0|>
<|body_start_1|>
job_log = JobLog.get(job_id=job_id)
if not job_log:
return False
... | JobLogService | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobLogService:
def update_job_log(self, job_id):
"""Updates the last run datetime of a specific job"""
<|body_0|>
def has_run_recently(self, job_id, recent_minutes=5):
""":returns True if specified job has been run in the last recent_minutes minutes, False if not"""
... | stack_v2_sparse_classes_36k_train_022563 | 923 | no_license | [
{
"docstring": "Updates the last run datetime of a specific job",
"name": "update_job_log",
"signature": "def update_job_log(self, job_id)"
},
{
"docstring": ":returns True if specified job has been run in the last recent_minutes minutes, False if not",
"name": "has_run_recently",
"signa... | 2 | stack_v2_sparse_classes_30k_train_001256 | Implement the Python class `JobLogService` described below.
Class description:
Implement the JobLogService class.
Method signatures and docstrings:
- def update_job_log(self, job_id): Updates the last run datetime of a specific job
- def has_run_recently(self, job_id, recent_minutes=5): :returns True if specified job... | Implement the Python class `JobLogService` described below.
Class description:
Implement the JobLogService class.
Method signatures and docstrings:
- def update_job_log(self, job_id): Updates the last run datetime of a specific job
- def has_run_recently(self, job_id, recent_minutes=5): :returns True if specified job... | d1be650663224c24b41f675627fff37dfdbcde97 | <|skeleton|>
class JobLogService:
def update_job_log(self, job_id):
"""Updates the last run datetime of a specific job"""
<|body_0|>
def has_run_recently(self, job_id, recent_minutes=5):
""":returns True if specified job has been run in the last recent_minutes minutes, False if not"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobLogService:
def update_job_log(self, job_id):
"""Updates the last run datetime of a specific job"""
job_log = JobLog.get(job_id=job_id)
if not job_log:
job_log = JobLog(job_id=job_id)
job_log.last_run = datetime.utcnow()
commit()
def has_run_recently... | the_stack_v2_python_sparse | components/core/job_log_service.py | jbinder/doforme-bot | train | 7 | |
e22c1450a935cdee39f03b1614daccdfea4f962b | [
"super().__init__(batch_size, **kwargs)\n_, num_classes, X_train, y_train, X_val, y_val = load_mnist_shard(shard_num=int(data_path), **kwargs)\nself.training_data_size = len(X_train)\nself.validation_data_size = len(X_val)\nself.num_classes = num_classes\nself.train_loader = self.create_loader(X=X_train, y=y_train,... | <|body_start_0|>
super().__init__(batch_size, **kwargs)
_, num_classes, X_train, y_train, X_val, y_val = load_mnist_shard(shard_num=int(data_path), **kwargs)
self.training_data_size = len(X_train)
self.validation_data_size = len(X_val)
self.num_classes = num_classes
self.... | PyTorch data loader for MNIST dataset | PyTorchMNISTInMemory | [
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-protobuf",
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyTorchMNISTInMemory:
"""PyTorch data loader for MNIST dataset"""
def __init__(self, data_path, batch_size, **kwargs):
"""Instantiate the data object Args: data_path: The file path to the data batch_size: The batch size of the data loader **kwargs: Additional arguments, passed to sup... | stack_v2_sparse_classes_36k_train_022564 | 5,563 | permissive | [
{
"docstring": "Instantiate the data object Args: data_path: The file path to the data batch_size: The batch size of the data loader **kwargs: Additional arguments, passed to super init and load_mnist_shard",
"name": "__init__",
"signature": "def __init__(self, data_path, batch_size, **kwargs)"
},
{... | 2 | null | Implement the Python class `PyTorchMNISTInMemory` described below.
Class description:
PyTorch data loader for MNIST dataset
Method signatures and docstrings:
- def __init__(self, data_path, batch_size, **kwargs): Instantiate the data object Args: data_path: The file path to the data batch_size: The batch size of the ... | Implement the Python class `PyTorchMNISTInMemory` described below.
Class description:
PyTorch data loader for MNIST dataset
Method signatures and docstrings:
- def __init__(self, data_path, batch_size, **kwargs): Instantiate the data object Args: data_path: The file path to the data batch_size: The batch size of the ... | d8e2d22dfccfb8488f70f1fb5593d4e6ee1eca1f | <|skeleton|>
class PyTorchMNISTInMemory:
"""PyTorch data loader for MNIST dataset"""
def __init__(self, data_path, batch_size, **kwargs):
"""Instantiate the data object Args: data_path: The file path to the data batch_size: The batch size of the data loader **kwargs: Additional arguments, passed to sup... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PyTorchMNISTInMemory:
"""PyTorch data loader for MNIST dataset"""
def __init__(self, data_path, batch_size, **kwargs):
"""Instantiate the data object Args: data_path: The file path to the data batch_size: The batch size of the data loader **kwargs: Additional arguments, passed to super init and l... | the_stack_v2_python_sparse | openfl/data/pytorch/ptmnist_inmemory.py | sbakas/OpenFederatedLearning-1 | train | 0 |
6d6094adc8bc950a34834930feb7cb148fffd8ce | [
"expected = '{\\n \"status\": \"created\"\\n}'\nfuture = event(EventType.PING)\nactual = future.result()\nself.assertEqual(actual, expected)",
"duration_max = 0.001\nstart = time.time()\nevent(EventType.PING)\nduration_actual = time.time() - start\nself.assertLess(duration_actual, duration_max)",
"expected =... | <|body_start_0|>
expected = '{\n "status": "created"\n}'
future = event(EventType.PING)
actual = future.result()
self.assertEqual(actual, expected)
<|end_body_0|>
<|body_start_1|>
duration_max = 0.001
start = time.time()
event(EventType.PING)
duration_... | Tests for the telemetry module. | TelemetryTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TelemetryTest:
"""Tests for the telemetry module."""
def test_event(self) -> None:
"""Test if sending works against the actual API."""
<|body_0|>
def test_not_blocking(self) -> None:
"""Test if the code is blocking. If the code does not block duration_actual shou... | stack_v2_sparse_classes_36k_train_022565 | 3,345 | permissive | [
{
"docstring": "Test if sending works against the actual API.",
"name": "test_event",
"signature": "def test_event(self) -> None"
},
{
"docstring": "Test if the code is blocking. If the code does not block duration_actual should be less than 0.001s.",
"name": "test_not_blocking",
"signat... | 5 | null | Implement the Python class `TelemetryTest` described below.
Class description:
Tests for the telemetry module.
Method signatures and docstrings:
- def test_event(self) -> None: Test if sending works against the actual API.
- def test_not_blocking(self) -> None: Test if the code is blocking. If the code does not block... | Implement the Python class `TelemetryTest` described below.
Class description:
Tests for the telemetry module.
Method signatures and docstrings:
- def test_event(self) -> None: Test if sending works against the actual API.
- def test_not_blocking(self) -> None: Test if the code is blocking. If the code does not block... | 55be690535e5f3feb33c888c3e4a586b7bdbf489 | <|skeleton|>
class TelemetryTest:
"""Tests for the telemetry module."""
def test_event(self) -> None:
"""Test if sending works against the actual API."""
<|body_0|>
def test_not_blocking(self) -> None:
"""Test if the code is blocking. If the code does not block duration_actual shou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TelemetryTest:
"""Tests for the telemetry module."""
def test_event(self) -> None:
"""Test if sending works against the actual API."""
expected = '{\n "status": "created"\n}'
future = event(EventType.PING)
actual = future.result()
self.assertEqual(actual, expect... | the_stack_v2_python_sparse | src/py/flwr/common/telemetry_test.py | adap/flower | train | 2,999 |
bc948902a4877fcb219627d213bc93d6063e7b5f | [
"self.model_conf = model_conf\nself.inputs = inputs\nself.utils = utils\nself.layer = None",
"with tf.keras.backend.name_scope('GRU'):\n mask = tf.keras.layers.Masking()(self.inputs)\n self.layer = tf.keras.layers.GRU(units=self.model_conf.units_num * 2, return_sequences=True, input_shape=mask.shape)\n o... | <|body_start_0|>
self.model_conf = model_conf
self.inputs = inputs
self.utils = utils
self.layer = None
<|end_body_0|>
<|body_start_1|>
with tf.keras.backend.name_scope('GRU'):
mask = tf.keras.layers.Masking()(self.inputs)
self.layer = tf.keras.layers.GRU... | GRU | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRU:
def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils):
""":param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类"""
<|body_0|>
def build(self):
"""循环层构建参数 :return: 返回循环层的输出层"""
<|bo... | stack_v2_sparse_classes_36k_train_022566 | 2,557 | permissive | [
{
"docstring": ":param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类",
"name": "__init__",
"signature": "def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils)"
},
{
"docstring": "循环层构建参数 :return: 返回循环层的输出层",
"name": "... | 2 | stack_v2_sparse_classes_30k_train_002427 | Implement the Python class `GRU` described below.
Class description:
Implement the GRU class.
Method signatures and docstrings:
- def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils): :param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类
- def... | Implement the Python class `GRU` described below.
Class description:
Implement the GRU class.
Method signatures and docstrings:
- def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils): :param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类
- def... | 6fd35c0c789aaa43130de46d4c04622ec2948052 | <|skeleton|>
class GRU:
def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils):
""":param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类"""
<|body_0|>
def build(self):
"""循环层构建参数 :return: 返回循环层的输出层"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GRU:
def __init__(self, model_conf: ModelConfig, inputs: tf.Tensor, utils: NetworkUtils):
""":param model_conf: 配置 :param inputs: 网络上一层输入tf.keras.layers.Input/tf.Tensor类型 :param utils: 网络工具类"""
self.model_conf = model_conf
self.inputs = inputs
self.utils = utils
self.la... | the_stack_v2_python_sparse | network/GRU.py | kerlomz/captcha_trainer | train | 2,977 | |
8e44b4f33e8737c96f56d1b20c70c8ba3488d83f | [
"y_pred_clipped = np.clip(y_pred, 1e-07, 1 - 1e-07)\nsample_losses = -(y_true * np.log(y_pred_clipped) + (1 - y_true) * np.log(1 - y_pred_clipped))\nsample_losses = np.mean(sample_losses, axis=-1)\nreturn sample_losses",
"samples = len(derivated_values)\noutputs = len(derivated_values[0])\nclipped_derivated_value... | <|body_start_0|>
y_pred_clipped = np.clip(y_pred, 1e-07, 1 - 1e-07)
sample_losses = -(y_true * np.log(y_pred_clipped) + (1 - y_true) * np.log(1 - y_pred_clipped))
sample_losses = np.mean(sample_losses, axis=-1)
return sample_losses
<|end_body_0|>
<|body_start_1|>
samples = len(d... | The class computes the binary crossentropy by applying the formula. Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.407-412] | BinaryCrossentropy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryCrossentropy:
"""The class computes the binary crossentropy by applying the formula. Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.407-412]"""
def forward(self, y_pred, y_true):
"""Performs the forward pass. Args : y_pred(np.array): Model predi... | stack_v2_sparse_classes_36k_train_022567 | 1,927 | no_license | [
{
"docstring": "Performs the forward pass. Args : y_pred(np.array): Model predictions y_true(np.array): Actual values Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.112-116]",
"name": "forward",
"signature": "def forward(self, y_pred, y_true)"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_val_000333 | Implement the Python class `BinaryCrossentropy` described below.
Class description:
The class computes the binary crossentropy by applying the formula. Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.407-412]
Method signatures and docstrings:
- def forward(self, y_pred, y_true): Perfor... | Implement the Python class `BinaryCrossentropy` described below.
Class description:
The class computes the binary crossentropy by applying the formula. Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.407-412]
Method signatures and docstrings:
- def forward(self, y_pred, y_true): Perfor... | 8ffd24971d8808e7c9caa722a7ff4df306b75b90 | <|skeleton|>
class BinaryCrossentropy:
"""The class computes the binary crossentropy by applying the formula. Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.407-412]"""
def forward(self, y_pred, y_true):
"""Performs the forward pass. Args : y_pred(np.array): Model predi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryCrossentropy:
"""The class computes the binary crossentropy by applying the formula. Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.407-412]"""
def forward(self, y_pred, y_true):
"""Performs the forward pass. Args : y_pred(np.array): Model predictions y_true... | the_stack_v2_python_sparse | Music Recognizer/Metrics/BinaryCrossentropy.py | andutzu7/Lucrare-Licenta-MusicRecognizer | train | 0 |
b601b0fd8c0a11b9cf0413e7f0c39a1a0f62453a | [
"print('\\nrunning test method:{}'.format(inspect.stack()[0][3]))\nreal_result = MathOperation(10, 2).division()\nexcept_result = 5\nmsg = '两个正数相除失败'\ntry:\n self.assertEqual(except_result, real_result, msg=msg)\nexcept AssertionError as e:\n print('具体异常为：{}'.format(e))\n file.write('{},执行结果为：{}\\n具体异常为：{}... | <|body_start_0|>
print('\nrunning test method:{}'.format(inspect.stack()[0][3]))
real_result = MathOperation(10, 2).division()
except_result = 5
msg = '两个正数相除失败'
try:
self.assertEqual(except_result, real_result, msg=msg)
except AssertionError as e:
... | 测试两数相乘 | TestDivide | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDivide:
"""测试两数相乘"""
def test_two_pos_divide(self):
"""1.两个正数相除 :return:"""
<|body_0|>
def test_two_neg_divide(self):
"""2.两个负数相除 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
print('\nrunning test method:{}'.format(inspect.stack(... | stack_v2_sparse_classes_36k_train_022568 | 7,546 | no_license | [
{
"docstring": "1.两个正数相除 :return:",
"name": "test_two_pos_divide",
"signature": "def test_two_pos_divide(self)"
},
{
"docstring": "2.两个负数相除 :return:",
"name": "test_two_neg_divide",
"signature": "def test_two_neg_divide(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016804 | Implement the Python class `TestDivide` described below.
Class description:
测试两数相乘
Method signatures and docstrings:
- def test_two_pos_divide(self): 1.两个正数相除 :return:
- def test_two_neg_divide(self): 2.两个负数相除 :return: | Implement the Python class `TestDivide` described below.
Class description:
测试两数相乘
Method signatures and docstrings:
- def test_two_pos_divide(self): 1.两个正数相除 :return:
- def test_two_neg_divide(self): 2.两个负数相除 :return:
<|skeleton|>
class TestDivide:
"""测试两数相乘"""
def test_two_pos_divide(self):
"""1.两... | 09d6bf79f46002b590289fdb94cbf1febe891184 | <|skeleton|>
class TestDivide:
"""测试两数相乘"""
def test_two_pos_divide(self):
"""1.两个正数相除 :return:"""
<|body_0|>
def test_two_neg_divide(self):
"""2.两个负数相除 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDivide:
"""测试两数相乘"""
def test_two_pos_divide(self):
"""1.两个正数相除 :return:"""
print('\nrunning test method:{}'.format(inspect.stack()[0][3]))
real_result = MathOperation(10, 2).division()
except_result = 5
msg = '两个正数相除失败'
try:
self.assertEqua... | the_stack_v2_python_sparse | pythonbase_class_1/Class_11_Unittest_start_end_handle.py | 2353501820/erp | train | 0 |
f3b8b4b5ecc3204b58dfa5059fd88cfc957a9927 | [
"if instance.pk and instance.name_changed:\n works = instance.digitizedwork_set.all()\n if works.exists():\n logger.debug('collection save, reindexing %d related works', works.count())\n DigitizedWork.index_items(works)",
"logger.debug('collection delete')\ndigwork_ids = instance.digitizedwork... | <|body_start_0|>
if instance.pk and instance.name_changed:
works = instance.digitizedwork_set.all()
if works.exists():
logger.debug('collection save, reindexing %d related works', works.count())
DigitizedWork.index_items(works)
<|end_body_0|>
<|body_start... | Signal handlers for indexing :class:`DigitizedWork` records when :class:`Collection` records are saved or deleted. | CollectionSignalHandlers | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectionSignalHandlers:
"""Signal handlers for indexing :class:`DigitizedWork` records when :class:`Collection` records are saved or deleted."""
def save(sender, instance, **kwargs):
"""signal handler for collection save; reindex associated digitized works"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_022569 | 46,514 | permissive | [
{
"docstring": "signal handler for collection save; reindex associated digitized works",
"name": "save",
"signature": "def save(sender, instance, **kwargs)"
},
{
"docstring": "signal handler for collection delete; clear associated digitized works and reindex",
"name": "delete",
"signatur... | 2 | null | Implement the Python class `CollectionSignalHandlers` described below.
Class description:
Signal handlers for indexing :class:`DigitizedWork` records when :class:`Collection` records are saved or deleted.
Method signatures and docstrings:
- def save(sender, instance, **kwargs): signal handler for collection save; rei... | Implement the Python class `CollectionSignalHandlers` described below.
Class description:
Signal handlers for indexing :class:`DigitizedWork` records when :class:`Collection` records are saved or deleted.
Method signatures and docstrings:
- def save(sender, instance, **kwargs): signal handler for collection save; rei... | 99e751b0d656d0d28c7e995cc44c351622313593 | <|skeleton|>
class CollectionSignalHandlers:
"""Signal handlers for indexing :class:`DigitizedWork` records when :class:`Collection` records are saved or deleted."""
def save(sender, instance, **kwargs):
"""signal handler for collection save; reindex associated digitized works"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollectionSignalHandlers:
"""Signal handlers for indexing :class:`DigitizedWork` records when :class:`Collection` records are saved or deleted."""
def save(sender, instance, **kwargs):
"""signal handler for collection save; reindex associated digitized works"""
if instance.pk and instance... | the_stack_v2_python_sparse | ppa/archive/models.py | Princeton-CDH/ppa-django | train | 5 |
9f77000fba4809829eb5dd4e313488b10c14cf5f | [
"self.organisms = 0\nself.hyperparameters = hyperparameters\nself.grid_dim = self.hyperparameters['grid_dim']\nself.mutation_prob = self.hyperparameters['mutation_prob']\nself.replication_prob = self.hyperparameters['replication_prob']\nself.grid_range = list(range(self.grid_dim))\nself.grid = [None for _ in range(... | <|body_start_0|>
self.organisms = 0
self.hyperparameters = hyperparameters
self.grid_dim = self.hyperparameters['grid_dim']
self.mutation_prob = self.hyperparameters['mutation_prob']
self.replication_prob = self.hyperparameters['replication_prob']
self.grid_range = list(r... | 1-Dimensional grid containing replicators -- the medium with which replication occurs | ReplicationGrid | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReplicationGrid:
"""1-Dimensional grid containing replicators -- the medium with which replication occurs"""
def __init__(self, hyperparameters):
"""Initialize grid parameters :param hyperparameters: (dict) dictionary of hyperparameters"""
<|body_0|>
def step(self):
... | stack_v2_sparse_classes_36k_train_022570 | 8,990 | permissive | [
{
"docstring": "Initialize grid parameters :param hyperparameters: (dict) dictionary of hyperparameters",
"name": "__init__",
"signature": "def __init__(self, hyperparameters)"
},
{
"docstring": "Replicator's interaction with environment including replication, creation, and death :return: (list(... | 4 | stack_v2_sparse_classes_30k_train_014859 | Implement the Python class `ReplicationGrid` described below.
Class description:
1-Dimensional grid containing replicators -- the medium with which replication occurs
Method signatures and docstrings:
- def __init__(self, hyperparameters): Initialize grid parameters :param hyperparameters: (dict) dictionary of hyperp... | Implement the Python class `ReplicationGrid` described below.
Class description:
1-Dimensional grid containing replicators -- the medium with which replication occurs
Method signatures and docstrings:
- def __init__(self, hyperparameters): Initialize grid parameters :param hyperparameters: (dict) dictionary of hyperp... | 1a6f8225378b59423a97b439b56710bbed2754e9 | <|skeleton|>
class ReplicationGrid:
"""1-Dimensional grid containing replicators -- the medium with which replication occurs"""
def __init__(self, hyperparameters):
"""Initialize grid parameters :param hyperparameters: (dict) dictionary of hyperparameters"""
<|body_0|>
def step(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReplicationGrid:
"""1-Dimensional grid containing replicators -- the medium with which replication occurs"""
def __init__(self, hyperparameters):
"""Initialize grid parameters :param hyperparameters: (dict) dictionary of hyperparameters"""
self.organisms = 0
self.hyperparameters =... | the_stack_v2_python_sparse | evo_replicators/evolutionary_replicator.py | SamuelSchmidgall/EvolutionarySelfReplication | train | 14 |
61848fc0e4c64324609b447cad36e68f3ba86a3f | [
"self._logger = None\nif need_log:\n self._logger = LoggerFactory.get_global_instance()",
"if self._logger is None:\n return\nclass_name = '[{}]'.format(type(self).__name__.upper())\ncontent = class_name + ' ' + str(content)\nif level == constant.LogLevel.INFO:\n self._logger.info(content)\nelif level ==... | <|body_start_0|>
self._logger = None
if need_log:
self._logger = LoggerFactory.get_global_instance()
<|end_body_0|>
<|body_start_1|>
if self._logger is None:
return
class_name = '[{}]'.format(type(self).__name__.upper())
content = class_name + ' ' + str(c... | The operator base class | Operator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Operator:
"""The operator base class"""
def __init__(self, need_log):
""":param need_log: bool"""
<|body_0|>
def _log(self, content, level=constant.LogLevel.INFO):
""":param content: str :param level: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_36k_train_022571 | 1,019 | no_license | [
{
"docstring": ":param need_log: bool",
"name": "__init__",
"signature": "def __init__(self, need_log)"
},
{
"docstring": ":param content: str :param level: :return:",
"name": "_log",
"signature": "def _log(self, content, level=constant.LogLevel.INFO)"
}
] | 2 | null | Implement the Python class `Operator` described below.
Class description:
The operator base class
Method signatures and docstrings:
- def __init__(self, need_log): :param need_log: bool
- def _log(self, content, level=constant.LogLevel.INFO): :param content: str :param level: :return: | Implement the Python class `Operator` described below.
Class description:
The operator base class
Method signatures and docstrings:
- def __init__(self, need_log): :param need_log: bool
- def _log(self, content, level=constant.LogLevel.INFO): :param content: str :param level: :return:
<|skeleton|>
class Operator:
... | db959eef96f95fcdd92185f0cb728d1d0b99857b | <|skeleton|>
class Operator:
"""The operator base class"""
def __init__(self, need_log):
""":param need_log: bool"""
<|body_0|>
def _log(self, content, level=constant.LogLevel.INFO):
""":param content: str :param level: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Operator:
"""The operator base class"""
def __init__(self, need_log):
""":param need_log: bool"""
self._logger = None
if need_log:
self._logger = LoggerFactory.get_global_instance()
def _log(self, content, level=constant.LogLevel.INFO):
""":param content: ... | the_stack_v2_python_sparse | fl/operator/operator.py | som-don/jeddak | train | 0 |
9689eeca03569387815b68344597f6e1c00654f0 | [
"super(InformationRatio, self).__init__()\nself.mtm = mtm\nself.benchmark = benchmark\npReturns = AnnualReturn(self.mtm)\nbReturns = AnnualReturn(self.benchmark)\nself.portfolioReturn = pReturns.getValue()\nself.benchmarkReturn = bReturns.getValue()\nvolatility = Volatility(self.mtm.shift() / self.mtm - self.benchm... | <|body_start_0|>
super(InformationRatio, self).__init__()
self.mtm = mtm
self.benchmark = benchmark
pReturns = AnnualReturn(self.mtm)
bReturns = AnnualReturn(self.benchmark)
self.portfolioReturn = pReturns.getValue()
self.benchmarkReturn = bReturns.getValue()
... | Information ratio of the data. | InformationRatio | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InformationRatio:
"""Information ratio of the data."""
def __init__(self, mtm, benchmark):
"""Initialize a volatility calculator. Parameters ---------- mtm : pandas.Series daily mark-to-market indexed by trading date as strings in the format %Y%m%d. benchmark : pandas.Series benchmar... | stack_v2_sparse_classes_36k_train_022572 | 10,010 | permissive | [
{
"docstring": "Initialize a volatility calculator. Parameters ---------- mtm : pandas.Series daily mark-to-market indexed by trading date as strings in the format %Y%m%d. benchmark : pandas.Series benchmark daily mark-to-market indexed by trading date as strings in the format %Y%m%d.",
"name": "__init__",
... | 2 | stack_v2_sparse_classes_30k_train_010988 | Implement the Python class `InformationRatio` described below.
Class description:
Information ratio of the data.
Method signatures and docstrings:
- def __init__(self, mtm, benchmark): Initialize a volatility calculator. Parameters ---------- mtm : pandas.Series daily mark-to-market indexed by trading date as strings... | Implement the Python class `InformationRatio` described below.
Class description:
Information ratio of the data.
Method signatures and docstrings:
- def __init__(self, mtm, benchmark): Initialize a volatility calculator. Parameters ---------- mtm : pandas.Series daily mark-to-market indexed by trading date as strings... | 139d604177da3855503643e0fcfa87711ba7e588 | <|skeleton|>
class InformationRatio:
"""Information ratio of the data."""
def __init__(self, mtm, benchmark):
"""Initialize a volatility calculator. Parameters ---------- mtm : pandas.Series daily mark-to-market indexed by trading date as strings in the format %Y%m%d. benchmark : pandas.Series benchmar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InformationRatio:
"""Information ratio of the data."""
def __init__(self, mtm, benchmark):
"""Initialize a volatility calculator. Parameters ---------- mtm : pandas.Series daily mark-to-market indexed by trading date as strings in the format %Y%m%d. benchmark : pandas.Series benchmark daily mark-... | the_stack_v2_python_sparse | analytics/riskMeasurement/riskMetric.py | WinQuant/arsenal | train | 0 |
972f50f66d68d56cd5f0aa063a2d86df62a83f5b | [
"self._data = data\nself._offset = offset\nself._limit = limit",
"limit = self._limit\noffset = self._offset\nvalue = limit - offset >> 2\nreturn value",
"index = index << 2\noffset = self._offset + index\nvalue = int.from_bytes(self._data[offset:offset + 4], 'big')\nreturn value",
"data = self._data\noffset ... | <|body_start_0|>
self._data = data
self._offset = offset
self._limit = limit
<|end_body_0|>
<|body_start_1|>
limit = self._limit
offset = self._offset
value = limit - offset >> 2
return value
<|end_body_1|>
<|body_start_2|>
index = index << 2
off... | Implements an uint32 array casted on bytes. Attributes ---------- _data : `bytes` The source `bytes` object. _offset : `int` The first byte what is inside of the array. _limit : `int` The first byte, what is not inside of the array after `._offset`. | Array_uint_32b | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Array_uint_32b:
"""Implements an uint32 array casted on bytes. Attributes ---------- _data : `bytes` The source `bytes` object. _offset : `int` The first byte what is inside of the array. _limit : `int` The first byte, what is not inside of the array after `._offset`."""
def __init__(self, d... | stack_v2_sparse_classes_36k_train_022573 | 11,434 | permissive | [
{
"docstring": "Creates a new uint32 array from the given parameters. Parameters ---------- data : `bytes` The source `bytes` object. offset : `int` The first byte what is inside of the array. limit : `int` The first byte, what is not inside of the array after `._offset`.",
"name": "__init__",
"signatur... | 4 | stack_v2_sparse_classes_30k_train_016615 | Implement the Python class `Array_uint_32b` described below.
Class description:
Implements an uint32 array casted on bytes. Attributes ---------- _data : `bytes` The source `bytes` object. _offset : `int` The first byte what is inside of the array. _limit : `int` The first byte, what is not inside of the array after `... | Implement the Python class `Array_uint_32b` described below.
Class description:
Implements an uint32 array casted on bytes. Attributes ---------- _data : `bytes` The source `bytes` object. _offset : `int` The first byte what is inside of the array. _limit : `int` The first byte, what is not inside of the array after `... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class Array_uint_32b:
"""Implements an uint32 array casted on bytes. Attributes ---------- _data : `bytes` The source `bytes` object. _offset : `int` The first byte what is inside of the array. _limit : `int` The first byte, what is not inside of the array after `._offset`."""
def __init__(self, d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Array_uint_32b:
"""Implements an uint32 array casted on bytes. Attributes ---------- _data : `bytes` The source `bytes` object. _offset : `int` The first byte what is inside of the array. _limit : `int` The first byte, what is not inside of the array after `._offset`."""
def __init__(self, data, offset, ... | the_stack_v2_python_sparse | hata/discord/voice/rtp_packet.py | HuyaneMatsu/hata | train | 3 |
a67641ea4f1551885e3affc5f0d98ec102f5bff1 | [
"self.max_age = max_age\nself.min_hits = min_hits\nself.iou_threshold = iou_threshold\nself.trackers = []\nself.frame_count = 0",
"self.frame_count += 1\ntrks = np.zeros((len(self.trackers), 5))\nto_del = []\nret = []\nfor t, trk in enumerate(trks):\n pos = self.trackers[t].predict()[0]\n trk[:] = [pos[0], ... | <|body_start_0|>
self.max_age = max_age
self.min_hits = min_hits
self.iou_threshold = iou_threshold
self.trackers = []
self.frame_count = 0
<|end_body_0|>
<|body_start_1|>
self.frame_count += 1
trks = np.zeros((len(self.trackers), 5))
to_del = []
... | Sort | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sort:
def __init__(self, max_age=1, min_hits=3, iou_threshold=0.3):
"""Sets key parameters for SORT"""
<|body_0|>
def update(self, dets=np.empty((0, 5))):
"""Params: dets - a numpy array of detections in the format [[x1,y1,x2,y2,score],[x1,y1,x2,y2,score],...] Requir... | stack_v2_sparse_classes_36k_train_022574 | 11,642 | permissive | [
{
"docstring": "Sets key parameters for SORT",
"name": "__init__",
"signature": "def __init__(self, max_age=1, min_hits=3, iou_threshold=0.3)"
},
{
"docstring": "Params: dets - a numpy array of detections in the format [[x1,y1,x2,y2,score],[x1,y1,x2,y2,score],...] Requires: this method must be c... | 2 | null | Implement the Python class `Sort` described below.
Class description:
Implement the Sort class.
Method signatures and docstrings:
- def __init__(self, max_age=1, min_hits=3, iou_threshold=0.3): Sets key parameters for SORT
- def update(self, dets=np.empty((0, 5))): Params: dets - a numpy array of detections in the fo... | Implement the Python class `Sort` described below.
Class description:
Implement the Sort class.
Method signatures and docstrings:
- def __init__(self, max_age=1, min_hits=3, iou_threshold=0.3): Sets key parameters for SORT
- def update(self, dets=np.empty((0, 5))): Params: dets - a numpy array of detections in the fo... | d6a135b098c3e1ee3b2a2f63b7dfeaa11f51fb30 | <|skeleton|>
class Sort:
def __init__(self, max_age=1, min_hits=3, iou_threshold=0.3):
"""Sets key parameters for SORT"""
<|body_0|>
def update(self, dets=np.empty((0, 5))):
"""Params: dets - a numpy array of detections in the format [[x1,y1,x2,y2,score],[x1,y1,x2,y2,score],...] Requir... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sort:
def __init__(self, max_age=1, min_hits=3, iou_threshold=0.3):
"""Sets key parameters for SORT"""
self.max_age = max_age
self.min_hits = min_hits
self.iou_threshold = iou_threshold
self.trackers = []
self.frame_count = 0
def update(self, dets=np.empty(... | the_stack_v2_python_sparse | tracking/model/sort/sort.py | david8862/keras-YOLOv3-model-set | train | 673 | |
4b145d551c66638757662eacfdf533667286a83e | [
"is_prime = [True] * max(n, 2)\nis_prime[0], is_prime[1] = (False, False)\nx = 2\nwhile x * x < n:\n if is_prime[x]:\n p = x * x\n while p < n:\n is_prime[p] = False\n p += x\n x += 1\nreturn sum(is_prime)",
"is_prime = [True] * max(n, 2)\nis_prime[0], is_prime[1] = (Fals... | <|body_start_0|>
is_prime = [True] * max(n, 2)
is_prime[0], is_prime[1] = (False, False)
x = 2
while x * x < n:
if is_prime[x]:
p = x * x
while p < n:
is_prime[p] = False
p += x
x += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def countPrimes_v0(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
is_prime = [True] * max(n, 2)
is_prime[0], is_prime[1] = (... | stack_v2_sparse_classes_36k_train_022575 | 2,525 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "countPrimes",
"signature": "def countPrimes(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "countPrimes_v0",
"signature": "def countPrimes_v0(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n): :type n: int :rtype: int
- def countPrimes_v0(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimes(self, n): :type n: int :rtype: int
- def countPrimes_v0(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def countPrimes(self, n):
""... | b5e09f24e8e96454dc99e20281e853fb9fcc85ed | <|skeleton|>
class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def countPrimes_v0(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countPrimes(self, n):
""":type n: int :rtype: int"""
is_prime = [True] * max(n, 2)
is_prime[0], is_prime[1] = (False, False)
x = 2
while x * x < n:
if is_prime[x]:
p = x * x
while p < n:
is_pr... | the_stack_v2_python_sparse | python/204_Count_Primes.py | Moby5/myleetcode | train | 2 | |
36411adfecc59a959c1b034ba26157f728bf06a8 | [
"self.fileHandle = fileHandle\nself.dagPath = dagPath\nself.light = OpenMaya.MFnPointLight(dagPath)",
"color = self.light.color()\nintensity = self.light.intensity()\ncolorR = self.rgcAndClamp(color.r * intensity)\ncolorG = self.rgcAndClamp(color.g * intensity)\ncolorB = self.rgcAndClamp(color.b * intensity)\nsel... | <|body_start_0|>
self.fileHandle = fileHandle
self.dagPath = dagPath
self.light = OpenMaya.MFnPointLight(dagPath)
<|end_body_0|>
<|body_start_1|>
color = self.light.color()
intensity = self.light.intensity()
colorR = self.rgcAndClamp(color.r * intensity)
colorG =... | Point light type. | PointLight | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointLight:
"""Point light type."""
def __init__(self, fileHandle, dagPath):
"""Constructor. Sets up this object's data."""
<|body_0|>
def getOutput(self):
"""Return lux LightSource "point" from the given pointlight node."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_022576 | 4,533 | no_license | [
{
"docstring": "Constructor. Sets up this object's data.",
"name": "__init__",
"signature": "def __init__(self, fileHandle, dagPath)"
},
{
"docstring": "Return lux LightSource \"point\" from the given pointlight node.",
"name": "getOutput",
"signature": "def getOutput(self)"
}
] | 2 | null | Implement the Python class `PointLight` described below.
Class description:
Point light type.
Method signatures and docstrings:
- def __init__(self, fileHandle, dagPath): Constructor. Sets up this object's data.
- def getOutput(self): Return lux LightSource "point" from the given pointlight node. | Implement the Python class `PointLight` described below.
Class description:
Point light type.
Method signatures and docstrings:
- def __init__(self, fileHandle, dagPath): Constructor. Sets up this object's data.
- def getOutput(self): Return lux LightSource "point" from the given pointlight node.
<|skeleton|>
class ... | 3891e40c3c4c3a054e5ff1ff16d051d4e690cc4a | <|skeleton|>
class PointLight:
"""Point light type."""
def __init__(self, fileHandle, dagPath):
"""Constructor. Sets up this object's data."""
<|body_0|>
def getOutput(self):
"""Return lux LightSource "point" from the given pointlight node."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointLight:
"""Point light type."""
def __init__(self, fileHandle, dagPath):
"""Constructor. Sets up this object's data."""
self.fileHandle = fileHandle
self.dagPath = dagPath
self.light = OpenMaya.MFnPointLight(dagPath)
def getOutput(self):
"""Return lux Ligh... | the_stack_v2_python_sparse | luxPlugin/Lux/LuxExportModules/Light.py | LuxRender/LuxMaya | train | 0 |
d2bb2c890a0934bd0f1a7c378bcf8eb2832bcd7a | [
"data = {'aerodrome': airport_icao, 'aerodromeRole': 'DEPARTURE'}\nresponse = self.client.service.queryFlightsByAerodrome(**data)\nreturn response",
"now = datetime.now()\ndata = {'sendTime': now.strftime('%Y-%m-%d %H:%M:%S'), 'dataset': {'type': 'OPERATIONAL'}, 'includeProposalFlights': False, 'includeForecastFl... | <|body_start_0|>
data = {'aerodrome': airport_icao, 'aerodromeRole': 'DEPARTURE'}
response = self.client.service.queryFlightsByAerodrome(**data)
return response
<|end_body_0|>
<|body_start_1|>
now = datetime.now()
data = {'sendTime': now.strftime('%Y-%m-%d %H:%M:%S'), 'dataset':... | FlightManagementService | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlightManagementService:
def get_departures(self, airport_icao: str) -> List[str]:
""":param airport_icao: :return:"""
<|body_0|>
def get_arrivals(self, airport_icao: str) -> List[str]:
""":param airport_icao: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_022577 | 3,070 | permissive | [
{
"docstring": ":param airport_icao: :return:",
"name": "get_departures",
"signature": "def get_departures(self, airport_icao: str) -> List[str]"
},
{
"docstring": ":param airport_icao: :return:",
"name": "get_arrivals",
"signature": "def get_arrivals(self, airport_icao: str) -> List[str... | 2 | stack_v2_sparse_classes_30k_train_007288 | Implement the Python class `FlightManagementService` described below.
Class description:
Implement the FlightManagementService class.
Method signatures and docstrings:
- def get_departures(self, airport_icao: str) -> List[str]: :param airport_icao: :return:
- def get_arrivals(self, airport_icao: str) -> List[str]: :p... | Implement the Python class `FlightManagementService` described below.
Class description:
Implement the FlightManagementService class.
Method signatures and docstrings:
- def get_departures(self, airport_icao: str) -> List[str]: :param airport_icao: :return:
- def get_arrivals(self, airport_icao: str) -> List[str]: :p... | d1dd3ce9d4abd84a5d16a877a86b6daaed5e6b49 | <|skeleton|>
class FlightManagementService:
def get_departures(self, airport_icao: str) -> List[str]:
""":param airport_icao: :return:"""
<|body_0|>
def get_arrivals(self, airport_icao: str) -> List[str]:
""":param airport_icao: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlightManagementService:
def get_departures(self, airport_icao: str) -> List[str]:
""":param airport_icao: :return:"""
data = {'aerodrome': airport_icao, 'aerodromeRole': 'DEPARTURE'}
response = self.client.service.queryFlightsByAerodrome(**data)
return response
def get_ar... | the_stack_v2_python_sparse | swim_aim/network_manager/services/flight_management.py | eurocontrol-swim/swim-aim | train | 0 | |
e46ed043ea5a36b0f0974ddb8f084e6e813cd5e5 | [
"logger.info('Overriding class: Optimizer -> SSA.')\nsuper(SSA, self).__init__()\nself.build(params)\nlogger.info('Class overrided.')",
"c1 = 2 * np.exp(-(4 * iteration / n_iterations) ** 2)\nfor i, _ in enumerate(space.agents):\n if i == 0:\n for j, (lb, ub) in enumerate(zip(space.agents[i].lb, space.a... | <|body_start_0|>
logger.info('Overriding class: Optimizer -> SSA.')
super(SSA, self).__init__()
self.build(params)
logger.info('Class overrided.')
<|end_body_0|>
<|body_start_1|>
c1 = 2 * np.exp(-(4 * iteration / n_iterations) ** 2)
for i, _ in enumerate(space.agents):
... | A SSA class, inherited from Optimizer. This is the designed class to define SSA-related variables and methods. References: S. Mirjalili et al. Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Software (2017). | SSA | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSA:
"""A SSA class, inherited from Optimizer. This is the designed class to define SSA-related variables and methods. References: S. Mirjalili et al. Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Software (2017)."""
def __init__(self... | stack_v2_sparse_classes_36k_train_022578 | 2,550 | permissive | [
{
"docstring": "Initialization method. Args: params: Contains key-value parameters to the meta-heuristics.",
"name": "__init__",
"signature": "def __init__(self, params: Optional[Dict[str, Any]]=None) -> None"
},
{
"docstring": "Wraps Salp Swarm Algorithm over all agents and variables. Args: spa... | 2 | stack_v2_sparse_classes_30k_train_002590 | Implement the Python class `SSA` described below.
Class description:
A SSA class, inherited from Optimizer. This is the designed class to define SSA-related variables and methods. References: S. Mirjalili et al. Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Sof... | Implement the Python class `SSA` described below.
Class description:
A SSA class, inherited from Optimizer. This is the designed class to define SSA-related variables and methods. References: S. Mirjalili et al. Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Sof... | 7326a887ed8e3858bc99c8815048d56d02edf88c | <|skeleton|>
class SSA:
"""A SSA class, inherited from Optimizer. This is the designed class to define SSA-related variables and methods. References: S. Mirjalili et al. Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Software (2017)."""
def __init__(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SSA:
"""A SSA class, inherited from Optimizer. This is the designed class to define SSA-related variables and methods. References: S. Mirjalili et al. Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Software (2017)."""
def __init__(self, params: Opt... | the_stack_v2_python_sparse | opytimizer/optimizers/swarm/ssa.py | gugarosa/opytimizer | train | 602 |
d623b02e7b2d98227866e3cfc49467a30e2cd2fc | [
"permissions = [IsAuthenticated]\nif self.action in ['update', 'partial_update']:\n permissions.append(IsCircleAdmin)\nreturn [p() for p in permissions]",
"queryset = Circle.objects.all()\nif self.action == 'list':\n queryset = Circle.objects.filter(is_public=True)\nreturn queryset",
"user = self.request.... | <|body_start_0|>
permissions = [IsAuthenticated]
if self.action in ['update', 'partial_update']:
permissions.append(IsCircleAdmin)
return [p() for p in permissions]
<|end_body_0|>
<|body_start_1|>
queryset = Circle.objects.all()
if self.action == 'list':
... | Circle viewset. | CircleViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CircleViewSet:
"""Circle viewset."""
def get_permissions(self):
"""Permissions based in actions."""
<|body_0|>
def get_queryset(self):
"""Specify and limit queryset in list action."""
<|body_1|>
def perform_create(self, serializer):
"""Create... | stack_v2_sparse_classes_36k_train_022579 | 1,656 | permissive | [
{
"docstring": "Permissions based in actions.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Specify and limit queryset in list action.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Create the relation... | 3 | stack_v2_sparse_classes_30k_train_011590 | Implement the Python class `CircleViewSet` described below.
Class description:
Circle viewset.
Method signatures and docstrings:
- def get_permissions(self): Permissions based in actions.
- def get_queryset(self): Specify and limit queryset in list action.
- def perform_create(self, serializer): Create the relationsh... | Implement the Python class `CircleViewSet` described below.
Class description:
Circle viewset.
Method signatures and docstrings:
- def get_permissions(self): Permissions based in actions.
- def get_queryset(self): Specify and limit queryset in list action.
- def perform_create(self, serializer): Create the relationsh... | 5c3b7e97400170c20864ad74af7f524bccf87cf9 | <|skeleton|>
class CircleViewSet:
"""Circle viewset."""
def get_permissions(self):
"""Permissions based in actions."""
<|body_0|>
def get_queryset(self):
"""Specify and limit queryset in list action."""
<|body_1|>
def perform_create(self, serializer):
"""Create... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CircleViewSet:
"""Circle viewset."""
def get_permissions(self):
"""Permissions based in actions."""
permissions = [IsAuthenticated]
if self.action in ['update', 'partial_update']:
permissions.append(IsCircleAdmin)
return [p() for p in permissions]
def get_... | the_stack_v2_python_sparse | bookshare/circles/views/circles.py | ezecavallo/bookshare | train | 0 |
5128e83fb502b228cb40431be2f8594450d43ebe | [
"self.wb = openpyxl.load_workbook(file_name)\nself.sheet = self.wb[sheet_name]\nself.list = list1",
"rows_data = list(self.sheet.rows)\ntitles = []\ntitles.append(rows_data[0][self.list[0] - 1].value)\ntitles.append(rows_data[0][self.list[1] - 1].value)\ncases = []\nfor i in range(2, self.sheet.max_row + 1):\n ... | <|body_start_0|>
self.wb = openpyxl.load_workbook(file_name)
self.sheet = self.wb[sheet_name]
self.list = list1
<|end_body_0|>
<|body_start_1|>
rows_data = list(self.sheet.rows)
titles = []
titles.append(rows_data[0][self.list[0] - 1].value)
titles.append(rows_da... | 读取Excel数据 | ReadExcel_dict | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadExcel_dict:
"""读取Excel数据"""
def __init__(self, file_name, sheet_name, list):
"""初始化读取对象 :param file_name: 文件名称 --> str :param sheet_name: 表单名称 --> str :param list1: 指定列 --> list"""
<|body_0|>
def read_date(self):
"""执行读取数据 :return:"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k_train_022580 | 2,188 | no_license | [
{
"docstring": "初始化读取对象 :param file_name: 文件名称 --> str :param sheet_name: 表单名称 --> str :param list1: 指定列 --> list",
"name": "__init__",
"signature": "def __init__(self, file_name, sheet_name, list)"
},
{
"docstring": "执行读取数据 :return:",
"name": "read_date",
"signature": "def read_date(sel... | 2 | null | Implement the Python class `ReadExcel_dict` described below.
Class description:
读取Excel数据
Method signatures and docstrings:
- def __init__(self, file_name, sheet_name, list): 初始化读取对象 :param file_name: 文件名称 --> str :param sheet_name: 表单名称 --> str :param list1: 指定列 --> list
- def read_date(self): 执行读取数据 :return: | Implement the Python class `ReadExcel_dict` described below.
Class description:
读取Excel数据
Method signatures and docstrings:
- def __init__(self, file_name, sheet_name, list): 初始化读取对象 :param file_name: 文件名称 --> str :param sheet_name: 表单名称 --> str :param list1: 指定列 --> list
- def read_date(self): 执行读取数据 :return:
<|ske... | f8a98389fa09f95e72914afa4935afc5c68eaccd | <|skeleton|>
class ReadExcel_dict:
"""读取Excel数据"""
def __init__(self, file_name, sheet_name, list):
"""初始化读取对象 :param file_name: 文件名称 --> str :param sheet_name: 表单名称 --> str :param list1: 指定列 --> list"""
<|body_0|>
def read_date(self):
"""执行读取数据 :return:"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReadExcel_dict:
"""读取Excel数据"""
def __init__(self, file_name, sheet_name, list):
"""初始化读取对象 :param file_name: 文件名称 --> str :param sheet_name: 表单名称 --> str :param list1: 指定列 --> list"""
self.wb = openpyxl.load_workbook(file_name)
self.sheet = self.wb[sheet_name]
self.list =... | the_stack_v2_python_sparse | py_1816_readexcel/py_1816_excelclass_dict.py | 2020668/python2019 | train | 0 |
5a4a2e05c4b732b0e74ddf0027af83494308d0ee | [
"ans = ''\nfor w in words:\n if any((not self.is_subseq(s, w), len(w) < len(ans), len(w) == len(ans) and w >= ans)):\n continue\n ans = w\nreturn ans",
"m, n = (len(s), len(t))\ni = j = 0\nwhile i < m and j < n:\n if s[i] == t[j]:\n j += 1\n i += 1\nreturn j == n"
] | <|body_start_0|>
ans = ''
for w in words:
if any((not self.is_subseq(s, w), len(w) < len(ans), len(w) == len(ans) and w >= ans)):
continue
ans = w
return ans
<|end_body_0|>
<|body_start_1|>
m, n = (len(s), len(t))
i = j = 0
while i... | 1. to check the word in list is subsequence of given s 2. ignoring if the length less than current ans 3. ignoring if the length equal current ans but has larger lexicographical order | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""1. to check the word in list is subsequence of given s 2. ignoring if the length less than current ans 3. ignoring if the length equal current ans but has larger lexicographical order"""
def findLongestWord(self, s, words):
""":type s: str :type words: List[str] :rtype: ... | stack_v2_sparse_classes_36k_train_022581 | 1,814 | no_license | [
{
"docstring": ":type s: str :type words: List[str] :rtype: str",
"name": "findLongestWord",
"signature": "def findLongestWord(self, s, words)"
},
{
"docstring": "return True if `t` is subsequence of `s`",
"name": "is_subseq",
"signature": "def is_subseq(self, s, t)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
1. to check the word in list is subsequence of given s 2. ignoring if the length less than current ans 3. ignoring if the length equal current ans but has larger lexicographical order
Method signatures and docstrings:
- def findLongestWord(self... | Implement the Python class `Solution` described below.
Class description:
1. to check the word in list is subsequence of given s 2. ignoring if the length less than current ans 3. ignoring if the length equal current ans but has larger lexicographical order
Method signatures and docstrings:
- def findLongestWord(self... | 91892fd64281d96b8a9d5c0d57b938c314ae71be | <|skeleton|>
class Solution:
"""1. to check the word in list is subsequence of given s 2. ignoring if the length less than current ans 3. ignoring if the length equal current ans but has larger lexicographical order"""
def findLongestWord(self, s, words):
""":type s: str :type words: List[str] :rtype: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""1. to check the word in list is subsequence of given s 2. ignoring if the length less than current ans 3. ignoring if the length equal current ans but has larger lexicographical order"""
def findLongestWord(self, s, words):
""":type s: str :type words: List[str] :rtype: str"""
... | the_stack_v2_python_sparse | leetcode/524_longest_word_in_dictionary_through_deleting.py | jaychsu/algorithm | train | 143 |
ad141647a7c3bceeca57e8ebbbaeb62e6e2f1a45 | [
"def PreOrder(root: TreeNode, Trace: [], TraceSet: set):\n if root.val in TraceSet:\n root.val = str(root.val) + '_' + str(random.randint(0, 99999))\n Trace.append(root.val)\n else:\n TraceSet.add(root.val)\n Trace.append(str(root.val))\n if root.left:\n PreOrder(root.lef... | <|body_start_0|>
def PreOrder(root: TreeNode, Trace: [], TraceSet: set):
if root.val in TraceSet:
root.val = str(root.val) + '_' + str(random.randint(0, 99999))
Trace.append(root.val)
else:
TraceSet.add(root.val)
Trace.appen... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|b... | stack_v2_sparse_classes_36k_train_022582 | 2,331 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature"... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded dat... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded dat... | 45cabf05251711c6421c8c2ddbcc3fec9222f70a | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def PreOrder(root: TreeNode, Trace: [], TraceSet: set):
if root.val in TraceSet:
root.val = str(root.val) + '_' + str(random.randint(0, 99999... | the_stack_v2_python_sparse | Hard/297/297.py | GuoYunZheSE/Leetcode | train | 1 | |
64be43b9300501a54ff610bf9b52c471e37b7c6d | [
"values = self.getValues('SELECT max(c.coverage_anysense_pcovered) FROM \\n %(track)s_transcript_counts as c,\\n %(reference)s_transcript2gene as i\\n WHERE c.coverage_anysense_nval > %(min_... | <|body_start_0|>
values = self.getValues('SELECT max(c.coverage_anysense_pcovered) FROM \n %(track)s_transcript_counts as c,\n %(reference)s_transcript2gene as i\n WHERE c.coverage_anyse... | status information on transcriptome building. | TranscriptStatus | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TranscriptStatus:
"""status information on transcriptome building."""
def testGeneCoverage(self, track):
"""test coverage of known protein coding transcript models with reads. PASS: >= 20% of expressed genes >90% covered WARN: <= 20% of expressed genes >90% covered FAIL: <= 10% of ex... | stack_v2_sparse_classes_36k_train_022583 | 3,919 | permissive | [
{
"docstring": "test coverage of known protein coding transcript models with reads. PASS: >= 20% of expressed genes >90% covered WARN: <= 20% of expressed genes >90% covered FAIL: <= 10% of expressed genes >90% covered Only genes with at least 5 reads mapping to them are used in order to only take into account ... | 3 | null | Implement the Python class `TranscriptStatus` described below.
Class description:
status information on transcriptome building.
Method signatures and docstrings:
- def testGeneCoverage(self, track): test coverage of known protein coding transcript models with reads. PASS: >= 20% of expressed genes >90% covered WARN: ... | Implement the Python class `TranscriptStatus` described below.
Class description:
status information on transcriptome building.
Method signatures and docstrings:
- def testGeneCoverage(self, track): test coverage of known protein coding transcript models with reads. PASS: >= 20% of expressed genes >90% covered WARN: ... | fe39fc42e1e919690426c9f34c68770f4f360d5a | <|skeleton|>
class TranscriptStatus:
"""status information on transcriptome building."""
def testGeneCoverage(self, track):
"""test coverage of known protein coding transcript models with reads. PASS: >= 20% of expressed genes >90% covered WARN: <= 20% of expressed genes >90% covered FAIL: <= 10% of ex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TranscriptStatus:
"""status information on transcriptome building."""
def testGeneCoverage(self, track):
"""test coverage of known protein coding transcript models with reads. PASS: >= 20% of expressed genes >90% covered WARN: <= 20% of expressed genes >90% covered FAIL: <= 10% of expressed genes... | the_stack_v2_python_sparse | CGATPipelines/pipeline_docs/pipeline_rnaseqtranscripts/trackers/Status.py | Acribbs/CGATPipelines | train | 1 |
6445011fae0a63971ef3f22d24228138feb73828 | [
"func_name = sys._getframe().f_code.co_name\nres = self.get_result(func_name)\nerrmsg = res[0].json()['errmsg']\ncouponrule_list = res[0].json()['data']\ngl.set_value('couponrule_list', couponrule_list)\nexpect_errmsg = self.get_expect_result(func_name)\nrow = self.get_case_row_index(func_name)\nself.update_result(... | <|body_start_0|>
func_name = sys._getframe().f_code.co_name
res = self.get_result(func_name)
errmsg = res[0].json()['errmsg']
couponrule_list = res[0].json()['data']
gl.set_value('couponrule_list', couponrule_list)
expect_errmsg = self.get_expect_result(func_name)
... | UserList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserList:
def test_urine_v2_couponManager_getAllCouponRules(self):
"""查询所有优惠券 :return:"""
<|body_0|>
def test_urine_v2_userInfo_getUserList(self):
"""查询用户列表 :return:"""
<|body_1|>
def test_urine_v2_userInfo_giftCoupons(self):
"""赠送优惠券 :return:"""... | stack_v2_sparse_classes_36k_train_022584 | 2,541 | no_license | [
{
"docstring": "查询所有优惠券 :return:",
"name": "test_urine_v2_couponManager_getAllCouponRules",
"signature": "def test_urine_v2_couponManager_getAllCouponRules(self)"
},
{
"docstring": "查询用户列表 :return:",
"name": "test_urine_v2_userInfo_getUserList",
"signature": "def test_urine_v2_userInfo_g... | 3 | null | Implement the Python class `UserList` described below.
Class description:
Implement the UserList class.
Method signatures and docstrings:
- def test_urine_v2_couponManager_getAllCouponRules(self): 查询所有优惠券 :return:
- def test_urine_v2_userInfo_getUserList(self): 查询用户列表 :return:
- def test_urine_v2_userInfo_giftCoupons... | Implement the Python class `UserList` described below.
Class description:
Implement the UserList class.
Method signatures and docstrings:
- def test_urine_v2_couponManager_getAllCouponRules(self): 查询所有优惠券 :return:
- def test_urine_v2_userInfo_getUserList(self): 查询用户列表 :return:
- def test_urine_v2_userInfo_giftCoupons... | 6837a07ff200b610e7ba799a52543493848b6026 | <|skeleton|>
class UserList:
def test_urine_v2_couponManager_getAllCouponRules(self):
"""查询所有优惠券 :return:"""
<|body_0|>
def test_urine_v2_userInfo_getUserList(self):
"""查询用户列表 :return:"""
<|body_1|>
def test_urine_v2_userInfo_giftCoupons(self):
"""赠送优惠券 :return:"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserList:
def test_urine_v2_couponManager_getAllCouponRules(self):
"""查询所有优惠券 :return:"""
func_name = sys._getframe().f_code.co_name
res = self.get_result(func_name)
errmsg = res[0].json()['errmsg']
couponrule_list = res[0].json()['data']
gl.set_value('couponrul... | the_stack_v2_python_sparse | run/user_management/test_user_list.py | liwei123a/APITestFrame | train | 0 | |
e1234ffcaeecb11cc6b6beac88eb5414b5c6a852 | [
"self.window = collections.deque(maxlen=size)\nself.sum = 0\nself.size = size",
"if len(self.window) == self.size:\n self.sum -= self.window[0]\nself.sum += val\nself.window.append(val)\nreturn self.sum / float(len(self.window))"
] | <|body_start_0|>
self.window = collections.deque(maxlen=size)
self.sum = 0
self.size = size
<|end_body_0|>
<|body_start_1|>
if len(self.window) == self.size:
self.sum -= self.window[0]
self.sum += val
self.window.append(val)
return self.sum / float(le... | MovingAverage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.window = collections.deque(maxle... | stack_v2_sparse_classes_36k_train_022585 | 793 | no_license | [
{
"docstring": "Initialize your data structure here. :type size: int",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": ":type val: int :rtype: float",
"name": "next",
"signature": "def next(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000262 | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, size): Initialize your data structure here. :type size: int
- def next(self, val): :type val: int :rtype: float
<|skeleton|>
class MovingAverage:
... | 94472f9b742571a4325b069a4c931610f1715542 | <|skeleton|>
class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
<|body_0|>
def next(self, val):
""":type val: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, size):
"""Initialize your data structure here. :type size: int"""
self.window = collections.deque(maxlen=size)
self.sum = 0
self.size = size
def next(self, val):
""":type val: int :rtype: float"""
if len(self.window) == sel... | the_stack_v2_python_sparse | leetcode-algorithms/346. Moving Average from Data Stream/MovingAverage.py | zzhyzzh/Leetcode | train | 0 | |
313840de514e25988a1b9083493f72b6e01afdcc | [
"json_dict = json.loads(request.body.decode())\nsku_id = json_dict.get('sku_id')\nfrom goods.models import SKU\ntry:\n SKU.objects.get(id=sku_id)\nexcept SKU.DoesNotExist:\n return http.HttpResponseForbidden('sku不存在')\nredis_conn = get_redis_connection('history')\npl = redis_conn.pipeline()\nuser_id = request... | <|body_start_0|>
json_dict = json.loads(request.body.decode())
sku_id = json_dict.get('sku_id')
from goods.models import SKU
try:
SKU.objects.get(id=sku_id)
except SKU.DoesNotExist:
return http.HttpResponseForbidden('sku不存在')
redis_conn = get_redis... | 用户浏览记录 | UserBrowseHistory | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def post(self, request):
"""保存用户浏览记录"""
<|body_0|>
def get(self, request):
"""获取用户浏览记录"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
json_dict = json.loads(request.body.decode())
sku_id = json_dict.get('... | stack_v2_sparse_classes_36k_train_022586 | 24,646 | permissive | [
{
"docstring": "保存用户浏览记录",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "获取用户浏览记录",
"name": "get",
"signature": "def get(self, request)"
}
] | 2 | null | Implement the Python class `UserBrowseHistory` described below.
Class description:
用户浏览记录
Method signatures and docstrings:
- def post(self, request): 保存用户浏览记录
- def get(self, request): 获取用户浏览记录 | Implement the Python class `UserBrowseHistory` described below.
Class description:
用户浏览记录
Method signatures and docstrings:
- def post(self, request): 保存用户浏览记录
- def get(self, request): 获取用户浏览记录
<|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def post(self, request):
"""保存用户浏览记录"""
<|body... | f89c80a22c5065b46900a20bd505614b5bcb2e6e | <|skeleton|>
class UserBrowseHistory:
"""用户浏览记录"""
def post(self, request):
"""保存用户浏览记录"""
<|body_0|>
def get(self, request):
"""获取用户浏览记录"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserBrowseHistory:
"""用户浏览记录"""
def post(self, request):
"""保存用户浏览记录"""
json_dict = json.loads(request.body.decode())
sku_id = json_dict.get('sku_id')
from goods.models import SKU
try:
SKU.objects.get(id=sku_id)
except SKU.DoesNotExist:
... | the_stack_v2_python_sparse | meiduo_mall/meiduo_mall/apps/users/views.py | ZHD165/Django_- | train | 0 |
eda8de8ccada37bedd3845bd948fc30cfa7d0ad1 | [
"cube1 = Cube('red', 6)\ncube2 = Cube('blue', 5)\nstacked_list = [cube1, cube2]\nself.assertEqual(calc_height(stacked_list), 'The maximum tower height is 11')",
"cube1 = Cube('red', 5)\ncube2 = Cube('red', 5)\ncube_list = [cube1, cube2]\nwith self.assertRaises(ValueError):\n stack_cubes(cube_list)",
"cube1 =... | <|body_start_0|>
cube1 = Cube('red', 6)
cube2 = Cube('blue', 5)
stacked_list = [cube1, cube2]
self.assertEqual(calc_height(stacked_list), 'The maximum tower height is 11')
<|end_body_0|>
<|body_start_1|>
cube1 = Cube('red', 5)
cube2 = Cube('red', 5)
cube_list = [... | UnitTest | UnitTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnitTest:
"""UnitTest"""
def test_calc_height(self):
"""test_calc_height: Testing calculate_height function"""
<|body_0|>
def test_failure(self):
"""test_failure: Make sure a ValueError is raised if you cannot stack the cubes"""
<|body_1|>
def test_w... | stack_v2_sparse_classes_36k_train_022587 | 1,393 | no_license | [
{
"docstring": "test_calc_height: Testing calculate_height function",
"name": "test_calc_height",
"signature": "def test_calc_height(self)"
},
{
"docstring": "test_failure: Make sure a ValueError is raised if you cannot stack the cubes",
"name": "test_failure",
"signature": "def test_fai... | 3 | stack_v2_sparse_classes_30k_train_014164 | Implement the Python class `UnitTest` described below.
Class description:
UnitTest
Method signatures and docstrings:
- def test_calc_height(self): test_calc_height: Testing calculate_height function
- def test_failure(self): test_failure: Make sure a ValueError is raised if you cannot stack the cubes
- def test_wides... | Implement the Python class `UnitTest` described below.
Class description:
UnitTest
Method signatures and docstrings:
- def test_calc_height(self): test_calc_height: Testing calculate_height function
- def test_failure(self): test_failure: Make sure a ValueError is raised if you cannot stack the cubes
- def test_wides... | 78f8f8d575e69da8d0c48929a562b0e9f64ab68d | <|skeleton|>
class UnitTest:
"""UnitTest"""
def test_calc_height(self):
"""test_calc_height: Testing calculate_height function"""
<|body_0|>
def test_failure(self):
"""test_failure: Make sure a ValueError is raised if you cannot stack the cubes"""
<|body_1|>
def test_w... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnitTest:
"""UnitTest"""
def test_calc_height(self):
"""test_calc_height: Testing calculate_height function"""
cube1 = Cube('red', 6)
cube2 = Cube('blue', 5)
stacked_list = [cube1, cube2]
self.assertEqual(calc_height(stacked_list), 'The maximum tower height is 11')... | the_stack_v2_python_sparse | task3/unit_test.py | jamesl33/210CT-Course-Work | train | 0 |
436c414299ee28c6925d701acf6c3a137544a930 | [
"ac = ActivityTypes.objects.filter(type_status=1)\npg = MyNumberPagination()\nret = ActiviyTypeSerializer(instance=ac, many=True)\nreturn Response(ret.data)",
"ret = {'code': '1000', 'msg': None}\ntype_info = request.data\nprint(type_info)\nActivityTypes.objects.get(pk=2)\nActivityTypes.objects.create(type_name=t... | <|body_start_0|>
ac = ActivityTypes.objects.filter(type_status=1)
pg = MyNumberPagination()
ret = ActiviyTypeSerializer(instance=ac, many=True)
return Response(ret.data)
<|end_body_0|>
<|body_start_1|>
ret = {'code': '1000', 'msg': None}
type_info = request.data
... | ActivityType | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActivityType:
def get(self, request, *args, **kwargs):
"""获取所有活动类型"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""添加活动类型"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ac = ActivityTypes.objects.filter(type_status=1)
pg = MyNumb... | stack_v2_sparse_classes_36k_train_022588 | 33,770 | no_license | [
{
"docstring": "获取所有活动类型",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "添加活动类型",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014562 | Implement the Python class `ActivityType` described below.
Class description:
Implement the ActivityType class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 获取所有活动类型
- def post(self, request, *args, **kwargs): 添加活动类型 | Implement the Python class `ActivityType` described below.
Class description:
Implement the ActivityType class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 获取所有活动类型
- def post(self, request, *args, **kwargs): 添加活动类型
<|skeleton|>
class ActivityType:
def get(self, request, *args, ... | 1d85ddac5c99094e943b6b736b6a2c873240b2d4 | <|skeleton|>
class ActivityType:
def get(self, request, *args, **kwargs):
"""获取所有活动类型"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""添加活动类型"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActivityType:
def get(self, request, *args, **kwargs):
"""获取所有活动类型"""
ac = ActivityTypes.objects.filter(type_status=1)
pg = MyNumberPagination()
ret = ActiviyTypeSerializer(instance=ac, many=True)
return Response(ret.data)
def post(self, request, *args, **kwargs):
... | the_stack_v2_python_sparse | SecondClass/activities/views.py | akengakenga/myProjects | train | 1 | |
f5b32c67abb169fe308f80d1b337d293044c3b15 | [
"self.scannr = env.nextScanID\nenv.nextScanID += 1\nu.verbose.set_level(3)\ndata = u.Param()\ndata.shape = 128\ndata.num_frames = 100\ndata.density = 0.2\ndata.min_frames = 1\ndata.label = None\ndata.psize = 0.000172\ndata.energy = 6.2\ndata.center = 'fftshift'\ndata.distance = 7\ndata.auto_center = True\ndata.orie... | <|body_start_0|>
self.scannr = env.nextScanID
env.nextScanID += 1
u.verbose.set_level(3)
data = u.Param()
data.shape = 128
data.num_frames = 100
data.density = 0.2
data.min_frames = 1
data.label = None
data.psize = 0.000172
data.ene... | Dummy macro which produces data from ptypy's MoonFlowerScan. Does not use actual detectors or motors, but puts data in all active recorders. | Dummy_Ptycho | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dummy_Ptycho:
"""Dummy macro which produces data from ptypy's MoonFlowerScan. Does not use actual detectors or motors, but puts data in all active recorders."""
def __init__(self):
"""The constructor should parse parameters."""
<|body_0|>
def run(self):
"""This m... | stack_v2_sparse_classes_36k_train_022589 | 3,306 | permissive | [
{
"docstring": "The constructor should parse parameters.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "This method does all the serious interaction with motors, detectors, and data recorders.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | null | Implement the Python class `Dummy_Ptycho` described below.
Class description:
Dummy macro which produces data from ptypy's MoonFlowerScan. Does not use actual detectors or motors, but puts data in all active recorders.
Method signatures and docstrings:
- def __init__(self): The constructor should parse parameters.
- ... | Implement the Python class `Dummy_Ptycho` described below.
Class description:
Dummy macro which produces data from ptypy's MoonFlowerScan. Does not use actual detectors or motors, but puts data in all active recorders.
Method signatures and docstrings:
- def __init__(self): The constructor should parse parameters.
- ... | 65a3b754068478fd518ab3b554397f0682c5d8ac | <|skeleton|>
class Dummy_Ptycho:
"""Dummy macro which produces data from ptypy's MoonFlowerScan. Does not use actual detectors or motors, but puts data in all active recorders."""
def __init__(self):
"""The constructor should parse parameters."""
<|body_0|>
def run(self):
"""This m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dummy_Ptycho:
"""Dummy macro which produces data from ptypy's MoonFlowerScan. Does not use actual detectors or motors, but puts data in all active recorders."""
def __init__(self):
"""The constructor should parse parameters."""
self.scannr = env.nextScanID
env.nextScanID += 1
... | the_stack_v2_python_sparse | contrast-master/beamlines/dummy/Ptycho_scan_v2.py | Lexelius/Contrast-ptycho | train | 1 |
9495ccc6c21bd33d4569f3b40b22860e6fc2821b | [
"if not self.ITEM_MODEL:\n raise NotImplementedError(f'ITEM_MODEL attribute not defined for {__class__}')\nids = []\nfor k in [self.ITEM_KEY + x for x in ['', '[]', 's', 's[]']]:\n if (ids := self.request.query_params.getlist(k, [])):\n break\nvalid_ids = []\nfor id in ids:\n try:\n valid_ids... | <|body_start_0|>
if not self.ITEM_MODEL:
raise NotImplementedError(f'ITEM_MODEL attribute not defined for {__class__}')
ids = []
for k in [self.ITEM_KEY + x for x in ['', '[]', 's', 's[]']]:
if (ids := self.request.query_params.getlist(k, [])):
break
... | Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which provides a generic implementation to return a list of matching database model instances | ReportFilterMixin | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReportFilterMixin:
"""Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which provides a generic implementation to return... | stack_v2_sparse_classes_36k_train_022590 | 19,444 | permissive | [
{
"docstring": "Return a list of database objects from query parameters",
"name": "get_items",
"signature": "def get_items(self)"
},
{
"docstring": "Filter the queryset based on the provided report ID values. As each 'report' instance may optionally define its own filters, the resulting queryset... | 2 | stack_v2_sparse_classes_30k_train_003591 | Implement the Python class `ReportFilterMixin` described below.
Class description:
Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which prov... | Implement the Python class `ReportFilterMixin` described below.
Class description:
Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which prov... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class ReportFilterMixin:
"""Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which provides a generic implementation to return... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReportFilterMixin:
"""Mixin for extracting multiple objects from query params. Each subclass *must* have an attribute called 'ITEM_KEY', which is used to determine what 'key' is used in the query parameters. This mixin defines a 'get_items' method which provides a generic implementation to return a list of ma... | the_stack_v2_python_sparse | InvenTree/report/api.py | inventree/InvenTree | train | 3,077 |
4c308c06c751e5f143037c31c71b45ff8c37d022 | [
"array = self.format_and_eval_string(self.target_array)\nif self.column_name:\n array = array[self.column_name]\nval = self.format_and_eval_string(self.value)\ntry:\n ind = np.where(np.abs(array - val) < 1e-12)[0][0]\nexcept IndexError as e:\n msg = 'Could not find {} in array {} ({})'\n raise ValueErro... | <|body_start_0|>
array = self.format_and_eval_string(self.target_array)
if self.column_name:
array = array[self.column_name]
val = self.format_and_eval_string(self.value)
try:
ind = np.where(np.abs(array - val) < 1e-12)[0][0]
except IndexError as e:
... | Store the index of the first occurence of a value in an array. Wait for any parallel operation before execution. | ArrayFindValueTask | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArrayFindValueTask:
"""Store the index of the first occurence of a value in an array. Wait for any parallel operation before execution."""
def perform(self):
"""Find index of value array and store index in database."""
<|body_0|>
def check(self, *args, **kwargs):
... | stack_v2_sparse_classes_36k_train_022591 | 6,289 | permissive | [
{
"docstring": "Find index of value array and store index in database.",
"name": "perform",
"signature": "def perform(self)"
},
{
"docstring": "Check the target array can be found and has the right column.",
"name": "check",
"signature": "def check(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009664 | Implement the Python class `ArrayFindValueTask` described below.
Class description:
Store the index of the first occurence of a value in an array. Wait for any parallel operation before execution.
Method signatures and docstrings:
- def perform(self): Find index of value array and store index in database.
- def check... | Implement the Python class `ArrayFindValueTask` described below.
Class description:
Store the index of the first occurence of a value in an array. Wait for any parallel operation before execution.
Method signatures and docstrings:
- def perform(self): Find index of value array and store index in database.
- def check... | b6f1f5b236c7a4e28d9a3bc8da9820c52d789309 | <|skeleton|>
class ArrayFindValueTask:
"""Store the index of the first occurence of a value in an array. Wait for any parallel operation before execution."""
def perform(self):
"""Find index of value array and store index in database."""
<|body_0|>
def check(self, *args, **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArrayFindValueTask:
"""Store the index of the first occurence of a value in an array. Wait for any parallel operation before execution."""
def perform(self):
"""Find index of value array and store index in database."""
array = self.format_and_eval_string(self.target_array)
if self... | the_stack_v2_python_sparse | exopy_hqc_legacy/tasks/tasks/util/array_tasks.py | Exopy/exopy_hqc_legacy | train | 0 |
0eeeee4084d8e99ceb462fc67f8ef41a15ef6f9b | [
"logger.info('Overriding class: PSO -> SAVPSO.')\nsuper(SAVPSO, self).__init__(params)\nlogger.info('Class overrided.')",
"positions = np.zeros((space.agents[0].position.shape[0], space.agents[0].position.shape[1]))\nfor agent in space.agents:\n positions += agent.position\npositions /= len(space.agents)\nfor ... | <|body_start_0|>
logger.info('Overriding class: PSO -> SAVPSO.')
super(SAVPSO, self).__init__(params)
logger.info('Class overrided.')
<|end_body_0|>
<|body_start_1|>
positions = np.zeros((space.agents[0].position.shape[0], space.agents[0].position.shape[1]))
for agent in space.a... | An SAVPSO class, inherited from Optimizer. This is the designed class to define SAVPSO-related variables and methods. References: H. Lu and W. Chen. Self-adaptive velocity particle swarm optimization for solving constrained optimization problems. Journal of global optimization (2008). | SAVPSO | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SAVPSO:
"""An SAVPSO class, inherited from Optimizer. This is the designed class to define SAVPSO-related variables and methods. References: H. Lu and W. Chen. Self-adaptive velocity particle swarm optimization for solving constrained optimization problems. Journal of global optimization (2008)."... | stack_v2_sparse_classes_36k_train_022592 | 15,941 | permissive | [
{
"docstring": "Initialization method. Args: params: Contains key-value parameters to the meta-heuristics.",
"name": "__init__",
"signature": "def __init__(self, params: Optional[Dict[str, Any]]=None) -> None"
},
{
"docstring": "Wraps Self-adaptive Velocity Particle Swarm Optimization over all a... | 2 | stack_v2_sparse_classes_30k_train_014871 | Implement the Python class `SAVPSO` described below.
Class description:
An SAVPSO class, inherited from Optimizer. This is the designed class to define SAVPSO-related variables and methods. References: H. Lu and W. Chen. Self-adaptive velocity particle swarm optimization for solving constrained optimization problems. ... | Implement the Python class `SAVPSO` described below.
Class description:
An SAVPSO class, inherited from Optimizer. This is the designed class to define SAVPSO-related variables and methods. References: H. Lu and W. Chen. Self-adaptive velocity particle swarm optimization for solving constrained optimization problems. ... | 7326a887ed8e3858bc99c8815048d56d02edf88c | <|skeleton|>
class SAVPSO:
"""An SAVPSO class, inherited from Optimizer. This is the designed class to define SAVPSO-related variables and methods. References: H. Lu and W. Chen. Self-adaptive velocity particle swarm optimization for solving constrained optimization problems. Journal of global optimization (2008)."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SAVPSO:
"""An SAVPSO class, inherited from Optimizer. This is the designed class to define SAVPSO-related variables and methods. References: H. Lu and W. Chen. Self-adaptive velocity particle swarm optimization for solving constrained optimization problems. Journal of global optimization (2008)."""
def _... | the_stack_v2_python_sparse | opytimizer/optimizers/swarm/pso.py | gugarosa/opytimizer | train | 602 |
0f05afc3dd0e3dbe5d069a74e1614d5bc86e7d56 | [
"tableview.superview['search_field'].end_editing()\nif tableview.editing:\n tableview.superview['editbar']['delete'].enabled = True\n tableview.superview['editbar']['share'].enabled = True\nelse:\n item = vocab.tableview_cell_for_row(tableview, section, row)\n load_word_view(item.text_label.text)",
"i... | <|body_start_0|>
tableview.superview['search_field'].end_editing()
if tableview.editing:
tableview.superview['editbar']['delete'].enabled = True
tableview.superview['editbar']['share'].enabled = True
else:
item = vocab.tableview_cell_for_row(tableview, section... | The delegate class to handle the vocabulary table. | TableViewDelegate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TableViewDelegate:
"""The delegate class to handle the vocabulary table."""
def tableview_did_select(self, tableview, section, row):
"""Call when the user selects a table row. For some reason, setting the `action` attribute in the UI designer passes an empty ui.ListDataSource as the ... | stack_v2_sparse_classes_36k_train_022593 | 21,181 | permissive | [
{
"docstring": "Call when the user selects a table row. For some reason, setting the `action` attribute in the UI designer passes an empty ui.ListDataSource as the sender. This method fixes it.",
"name": "tableview_did_select",
"signature": "def tableview_did_select(self, tableview, section, row)"
},
... | 2 | stack_v2_sparse_classes_30k_train_004134 | Implement the Python class `TableViewDelegate` described below.
Class description:
The delegate class to handle the vocabulary table.
Method signatures and docstrings:
- def tableview_did_select(self, tableview, section, row): Call when the user selects a table row. For some reason, setting the `action` attribute in ... | Implement the Python class `TableViewDelegate` described below.
Class description:
The delegate class to handle the vocabulary table.
Method signatures and docstrings:
- def tableview_did_select(self, tableview, section, row): Call when the user selects a table row. For some reason, setting the `action` attribute in ... | 1d62f21c3492bfcf3e2ab360cfae52e5fc1b2853 | <|skeleton|>
class TableViewDelegate:
"""The delegate class to handle the vocabulary table."""
def tableview_did_select(self, tableview, section, row):
"""Call when the user selects a table row. For some reason, setting the `action` attribute in the UI designer passes an empty ui.ListDataSource as the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TableViewDelegate:
"""The delegate class to handle the vocabulary table."""
def tableview_did_select(self, tableview, section, row):
"""Call when the user selects a table row. For some reason, setting the `action` attribute in the UI designer passes an empty ui.ListDataSource as the sender. This ... | the_stack_v2_python_sparse | WordRoom.py | johnridesabike/WordRoom | train | 10 |
ce1f2b01c6c37c68e2892c96180f66f6fa7e013d | [
"value = bytes(json.dumps(message, cls=DjangoJSONEncoder), encoding='utf-8')\nif self.crypter:\n value = self.crypter.encrypt(value)\nrandom_prefix = random.getrandbits(8 * 12).to_bytes(12, 'big')\nreturn random_prefix + value",
"message = message[12:]\nmessage = message.decode('utf-8')\nif self.crypter:\n ... | <|body_start_0|>
value = bytes(json.dumps(message, cls=DjangoJSONEncoder), encoding='utf-8')
if self.crypter:
value = self.crypter.encrypt(value)
random_prefix = random.getrandbits(8 * 12).to_bytes(12, 'big')
return random_prefix + value
<|end_body_0|>
<|body_start_1|>
... | Use json to serialize and deserialize messages. | JsonRedisChannelLayer | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JsonRedisChannelLayer:
"""Use json to serialize and deserialize messages."""
def serialize(self, message):
"""Serializes message in json."""
<|body_0|>
def deserialize(self, message):
"""Deserializes from a byte string."""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_022594 | 1,096 | permissive | [
{
"docstring": "Serializes message in json.",
"name": "serialize",
"signature": "def serialize(self, message)"
},
{
"docstring": "Deserializes from a byte string.",
"name": "deserialize",
"signature": "def deserialize(self, message)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017068 | Implement the Python class `JsonRedisChannelLayer` described below.
Class description:
Use json to serialize and deserialize messages.
Method signatures and docstrings:
- def serialize(self, message): Serializes message in json.
- def deserialize(self, message): Deserializes from a byte string. | Implement the Python class `JsonRedisChannelLayer` described below.
Class description:
Use json to serialize and deserialize messages.
Method signatures and docstrings:
- def serialize(self, message): Serializes message in json.
- def deserialize(self, message): Deserializes from a byte string.
<|skeleton|>
class Js... | f767f1bdc12c9712f26ea17cb8b19f536389f0ed | <|skeleton|>
class JsonRedisChannelLayer:
"""Use json to serialize and deserialize messages."""
def serialize(self, message):
"""Serializes message in json."""
<|body_0|>
def deserialize(self, message):
"""Deserializes from a byte string."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JsonRedisChannelLayer:
"""Use json to serialize and deserialize messages."""
def serialize(self, message):
"""Serializes message in json."""
value = bytes(json.dumps(message, cls=DjangoJSONEncoder), encoding='utf-8')
if self.crypter:
value = self.crypter.encrypt(value)... | the_stack_v2_python_sparse | src/backend/marsha/websocket/layers.py | openfun/marsha | train | 92 |
09daefadd62d7cd18f007346ed627bd2468cc59c | [
"from ..misc import RelativePath\nsuper(CallProcess, self).__init__(maxtrials=maxtrials)\nself.functional = functional\n' Functional to execute. '\ntry:\n self.functional = self.functional\nexcept:\n pass\nself.outdir = RelativePath(outdir)\n' Execution directory of the folder. '\nself.outdir = RelativePath(o... | <|body_start_0|>
from ..misc import RelativePath
super(CallProcess, self).__init__(maxtrials=maxtrials)
self.functional = functional
' Functional to execute. '
try:
self.functional = self.functional
except:
pass
self.outdir = RelativePath(o... | Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html | CallProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CallProcess:
"""Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html"""
def __init__(self, functional, outdir, stdout=None, stderr=None, maxtrials=1, dom... | stack_v2_sparse_classes_36k_train_022595 | 5,576 | no_license | [
{
"docstring": "Initializes a process. :param functional: A python callable. It should also be pickle-able. :param str outdir: Path where the python child process should be executed. :param str stdout: Optional path to an output file where the callable's output shall be streamed. :param str stderr: Optional pat... | 6 | null | Implement the Python class `CallProcess` described below.
Class description:
Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html
Method signatures and docstrings:
- def __init__(... | Implement the Python class `CallProcess` described below.
Class description:
Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html
Method signatures and docstrings:
- def __init__(... | 9c0ab667f94dc4629404a8ec99cbeaa323f0c8b3 | <|skeleton|>
class CallProcess:
"""Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html"""
def __init__(self, functional, outdir, stdout=None, stderr=None, maxtrials=1, dom... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CallProcess:
"""Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html"""
def __init__(self, functional, outdir, stdout=None, stderr=None, maxtrials=1, dompi=False, **k... | the_stack_v2_python_sparse | process/call.py | Shibu778/LaDa | train | 0 |
e40fbbeb90abfe8662eb148e1475bf7bc8542ee3 | [
"self.Wh = np.random.normal(size=(i + h, h))\nself.Wy = np.random.normal(size=(h, o))\nself.bh = np.zeros((1, h))\nself.by = np.zeros((1, o))",
"xh = np.concatenate((h_prev, x_t), axis=1)\na_next = np.tanh(np.dot(xh, self.Wh) + self.bh)\ny_pred = np.dot(a_next, self.Wy) + self.by\ny_pred = np.exp(y_pred) / np.sum... | <|body_start_0|>
self.Wh = np.random.normal(size=(i + h, h))
self.Wy = np.random.normal(size=(h, o))
self.bh = np.zeros((1, h))
self.by = np.zeros((1, o))
<|end_body_0|>
<|body_start_1|>
xh = np.concatenate((h_prev, x_t), axis=1)
a_next = np.tanh(np.dot(xh, self.Wh) + se... | RNN cell | RNNCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNCell:
"""RNN cell"""
def __init__(self, i, h, o):
"""* The weights will be used on the right side for matrix multiplication * The biases should be initialized as zeros"""
<|body_0|>
def forward(self, h_prev, x_t):
"""Returns: h_next, y"""
<|body_1|>
<... | stack_v2_sparse_classes_36k_train_022596 | 818 | no_license | [
{
"docstring": "* The weights will be used on the right side for matrix multiplication * The biases should be initialized as zeros",
"name": "__init__",
"signature": "def __init__(self, i, h, o)"
},
{
"docstring": "Returns: h_next, y",
"name": "forward",
"signature": "def forward(self, h... | 2 | stack_v2_sparse_classes_30k_train_013975 | Implement the Python class `RNNCell` described below.
Class description:
RNN cell
Method signatures and docstrings:
- def __init__(self, i, h, o): * The weights will be used on the right side for matrix multiplication * The biases should be initialized as zeros
- def forward(self, h_prev, x_t): Returns: h_next, y | Implement the Python class `RNNCell` described below.
Class description:
RNN cell
Method signatures and docstrings:
- def __init__(self, i, h, o): * The weights will be used on the right side for matrix multiplication * The biases should be initialized as zeros
- def forward(self, h_prev, x_t): Returns: h_next, y
<|... | 9ff78818c132d1233c11b8fc8fd469878b23b14e | <|skeleton|>
class RNNCell:
"""RNN cell"""
def __init__(self, i, h, o):
"""* The weights will be used on the right side for matrix multiplication * The biases should be initialized as zeros"""
<|body_0|>
def forward(self, h_prev, x_t):
"""Returns: h_next, y"""
<|body_1|>
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNCell:
"""RNN cell"""
def __init__(self, i, h, o):
"""* The weights will be used on the right side for matrix multiplication * The biases should be initialized as zeros"""
self.Wh = np.random.normal(size=(i + h, h))
self.Wy = np.random.normal(size=(h, o))
self.bh = np.ze... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/0-rnn_cell.py | Nzparra/holbertonschool-machine_learning | train | 0 |
b5128df92e50f6c44c562ea1f21d955df952237b | [
"self.original_data = tmp_tuple\nself.original_data = sorted(self.original_data)\nself.target = target",
"result = 'To find: %d' % self.target\nresult += '\\nIn the sequence: %s' % str(self.original_data)\nresult += '\\nRecursive result: %s' % self._isMemberR(self.original_data)\nresult += '\\nIterative result: %... | <|body_start_0|>
self.original_data = tmp_tuple
self.original_data = sorted(self.original_data)
self.target = target
<|end_body_0|>
<|body_start_1|>
result = 'To find: %d' % self.target
result += '\nIn the sequence: %s' % str(self.original_data)
result += '\nRecursive re... | database | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class database:
def __init__(self, tmp_tuple, target):
"""(Tuple, number) -> None Effect: To initail the class, sorting the tuple and setting the target Input: Tuple needed to search and target No output at this moment"""
<|body_0|>
def __str__(self):
"""() -> None Effect:... | stack_v2_sparse_classes_36k_train_022597 | 6,575 | no_license | [
{
"docstring": "(Tuple, number) -> None Effect: To initail the class, sorting the tuple and setting the target Input: Tuple needed to search and target No output at this moment",
"name": "__init__",
"signature": "def __init__(self, tmp_tuple, target)"
},
{
"docstring": "() -> None Effect: Make t... | 4 | null | Implement the Python class `database` described below.
Class description:
Implement the database class.
Method signatures and docstrings:
- def __init__(self, tmp_tuple, target): (Tuple, number) -> None Effect: To initail the class, sorting the tuple and setting the target Input: Tuple needed to search and target No ... | Implement the Python class `database` described below.
Class description:
Implement the database class.
Method signatures and docstrings:
- def __init__(self, tmp_tuple, target): (Tuple, number) -> None Effect: To initail the class, sorting the tuple and setting the target Input: Tuple needed to search and target No ... | 8dcc64c2746c908c4121b550ae839a5b75a3edaa | <|skeleton|>
class database:
def __init__(self, tmp_tuple, target):
"""(Tuple, number) -> None Effect: To initail the class, sorting the tuple and setting the target Input: Tuple needed to search and target No output at this moment"""
<|body_0|>
def __str__(self):
"""() -> None Effect:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class database:
def __init__(self, tmp_tuple, target):
"""(Tuple, number) -> None Effect: To initail the class, sorting the tuple and setting the target Input: Tuple needed to search and target No output at this moment"""
self.original_data = tmp_tuple
self.original_data = sorted(self.origin... | the_stack_v2_python_sparse | python/is_member.py | xzpjerry/learning | train | 1 | |
dd4e8dd9fe073747786f729ea5d57c32bbcb92ad | [
"super(ResourcesAPITestCase, cls).setUpTestData()\nfor name, _definition in utils.get_user_limit_templates():\n cls.localconfig.parameters.set_value('deflt_user_{0}_limit'.format(name), 2)\ncls.localconfig.save()\npopulate_database()\ncls.user = User.objects.get(username='admin@test.com')\ncls.da_token = Token.o... | <|body_start_0|>
super(ResourcesAPITestCase, cls).setUpTestData()
for name, _definition in utils.get_user_limit_templates():
cls.localconfig.parameters.set_value('deflt_user_{0}_limit'.format(name), 2)
cls.localconfig.save()
populate_database()
cls.user = User.objects... | Check resources API. | ResourcesAPITestCase | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResourcesAPITestCase:
"""Check resources API."""
def setUpTestData(cls):
"""Create test data."""
<|body_0|>
def test_get_admin_resources(self):
"""Retrieve admin resources."""
<|body_1|>
def test_update_resources(self):
"""Update resources.""... | stack_v2_sparse_classes_36k_train_022598 | 13,614 | permissive | [
{
"docstring": "Create test data.",
"name": "setUpTestData",
"signature": "def setUpTestData(cls)"
},
{
"docstring": "Retrieve admin resources.",
"name": "test_get_admin_resources",
"signature": "def test_get_admin_resources(self)"
},
{
"docstring": "Update resources.",
"name... | 3 | null | Implement the Python class `ResourcesAPITestCase` described below.
Class description:
Check resources API.
Method signatures and docstrings:
- def setUpTestData(cls): Create test data.
- def test_get_admin_resources(self): Retrieve admin resources.
- def test_update_resources(self): Update resources. | Implement the Python class `ResourcesAPITestCase` described below.
Class description:
Check resources API.
Method signatures and docstrings:
- def setUpTestData(cls): Create test data.
- def test_get_admin_resources(self): Retrieve admin resources.
- def test_update_resources(self): Update resources.
<|skeleton|>
cl... | df699aab0799ec1725b6b89be38e56285821c889 | <|skeleton|>
class ResourcesAPITestCase:
"""Check resources API."""
def setUpTestData(cls):
"""Create test data."""
<|body_0|>
def test_get_admin_resources(self):
"""Retrieve admin resources."""
<|body_1|>
def test_update_resources(self):
"""Update resources.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResourcesAPITestCase:
"""Check resources API."""
def setUpTestData(cls):
"""Create test data."""
super(ResourcesAPITestCase, cls).setUpTestData()
for name, _definition in utils.get_user_limit_templates():
cls.localconfig.parameters.set_value('deflt_user_{0}_limit'.form... | the_stack_v2_python_sparse | modoboa/limits/api/v1/tests.py | modoboa/modoboa | train | 2,201 |
dc8a6e7011c61f047f1c5224b7fb35e556324f34 | [
"super(HighwayNet, self).__init__()\nself.idim = idim\nself.projection = torch.nn.Sequential(torch.nn.Linear(idim, idim), torch.nn.ReLU())\nself.gate = torch.nn.Sequential(torch.nn.Linear(idim, idim), torch.nn.Sigmoid())",
"proj = self.projection(x)\ngate = self.gate(x)\nreturn proj * gate + x * (1.0 - gate)"
] | <|body_start_0|>
super(HighwayNet, self).__init__()
self.idim = idim
self.projection = torch.nn.Sequential(torch.nn.Linear(idim, idim), torch.nn.ReLU())
self.gate = torch.nn.Sequential(torch.nn.Linear(idim, idim), torch.nn.Sigmoid())
<|end_body_0|>
<|body_start_1|>
proj = self.p... | Highway Network module. This is a module of Highway Network introduced in `Highway Networks`_. .. _`Highway Networks`: https://arxiv.org/abs/1505.00387 | HighwayNet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HighwayNet:
"""Highway Network module. This is a module of Highway Network introduced in `Highway Networks`_. .. _`Highway Networks`: https://arxiv.org/abs/1505.00387"""
def __init__(self, idim):
"""Initialize Highway Network module. Args: idim (int): Dimension of the inputs."""
... | stack_v2_sparse_classes_36k_train_022599 | 9,068 | permissive | [
{
"docstring": "Initialize Highway Network module. Args: idim (int): Dimension of the inputs.",
"name": "__init__",
"signature": "def __init__(self, idim)"
},
{
"docstring": "Calculate forward propagation. Args: x (Tensor): Batch of inputs (B, ..., idim). Returns: Tensor: Batch of outputs, which... | 2 | null | Implement the Python class `HighwayNet` described below.
Class description:
Highway Network module. This is a module of Highway Network introduced in `Highway Networks`_. .. _`Highway Networks`: https://arxiv.org/abs/1505.00387
Method signatures and docstrings:
- def __init__(self, idim): Initialize Highway Network m... | Implement the Python class `HighwayNet` described below.
Class description:
Highway Network module. This is a module of Highway Network introduced in `Highway Networks`_. .. _`Highway Networks`: https://arxiv.org/abs/1505.00387
Method signatures and docstrings:
- def __init__(self, idim): Initialize Highway Network m... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class HighwayNet:
"""Highway Network module. This is a module of Highway Network introduced in `Highway Networks`_. .. _`Highway Networks`: https://arxiv.org/abs/1505.00387"""
def __init__(self, idim):
"""Initialize Highway Network module. Args: idim (int): Dimension of the inputs."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HighwayNet:
"""Highway Network module. This is a module of Highway Network introduced in `Highway Networks`_. .. _`Highway Networks`: https://arxiv.org/abs/1505.00387"""
def __init__(self, idim):
"""Initialize Highway Network module. Args: idim (int): Dimension of the inputs."""
super(Hig... | the_stack_v2_python_sparse | espnet/nets/pytorch_backend/tacotron2/cbhg.py | espnet/espnet | train | 7,242 |
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