blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2713c7fe674a209ade5ed49a86832860ffe54892 | [
"self.LOGS = settings.logger\nself.dataset = settings.dataset\nself.LOGS.info('DATASET: Instantiating Dataset object')\nmodule = self._load_module(settings, client)\nremote_check = core.get_date(module.url)\nif self.dataset in settings.modules.keys() and remote_check > settings.modules[self.dataset]:\n msg = 'Re... | <|body_start_0|>
self.LOGS = settings.logger
self.dataset = settings.dataset
self.LOGS.info('DATASET: Instantiating Dataset object')
module = self._load_module(settings, client)
remote_check = core.get_date(module.url)
if self.dataset in settings.modules.keys() and remote... | Class to retrieve the required DHTK extension (dataset) module | ExtensionLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtensionLoader:
"""Class to retrieve the required DHTK extension (dataset) module"""
def __init__(self, settings: object, client: object):
"""Method to retrieve the required the DHTK extension module. Parameters ---------- settings: DHTK Settings object Configurations to use client:... | stack_v2_sparse_classes_10k_train_001200 | 3,777 | no_license | [
{
"docstring": "Method to retrieve the required the DHTK extension module. Parameters ---------- settings: DHTK Settings object Configurations to use client: DHTK Client object Client to use Returns ------- Extension module selected by the user as the .module attribute",
"name": "__init__",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_000790 | Implement the Python class `ExtensionLoader` described below.
Class description:
Class to retrieve the required DHTK extension (dataset) module
Method signatures and docstrings:
- def __init__(self, settings: object, client: object): Method to retrieve the required the DHTK extension module. Parameters ---------- set... | Implement the Python class `ExtensionLoader` described below.
Class description:
Class to retrieve the required DHTK extension (dataset) module
Method signatures and docstrings:
- def __init__(self, settings: object, client: object): Method to retrieve the required the DHTK extension module. Parameters ---------- set... | 54d9104c8b04af0fb368a499372d7ea0337be3d2 | <|skeleton|>
class ExtensionLoader:
"""Class to retrieve the required DHTK extension (dataset) module"""
def __init__(self, settings: object, client: object):
"""Method to retrieve the required the DHTK extension module. Parameters ---------- settings: DHTK Settings object Configurations to use client:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExtensionLoader:
"""Class to retrieve the required DHTK extension (dataset) module"""
def __init__(self, settings: object, client: object):
"""Method to retrieve the required the DHTK extension module. Parameters ---------- settings: DHTK Settings object Configurations to use client: DHTK Client ... | the_stack_v2_python_sparse | venv/Lib/site-packages/dhtk/core/loader.py | sorchawalsh/semanticweb | train | 0 |
1975f136643f26728a6846cbca65cdafcf5c2a1b | [
"if N == 1:\n return 1\nif N == 2:\n return 2\ndp = [1 for _ in range(N + 1)]\ndp[2] = 2\nfor i in range(3, N + 1):\n dp[i] = (2 * dp[i - 1] + dp[i - 3]) % int(1000000000.0 + 7)\nreturn dp[-1]",
"import numpy as np\nif N == 1:\n return 1\nif N == 2:\n return 2\nif N % 2 == 1:\n k = (N - 2) // 2\... | <|body_start_0|>
if N == 1:
return 1
if N == 2:
return 2
dp = [1 for _ in range(N + 1)]
dp[2] = 2
for i in range(3, N + 1):
dp[i] = (2 * dp[i - 1] + dp[i - 3]) % int(1000000000.0 + 7)
return dp[-1]
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numTilings(self, N):
""":type N: int :rtype: int 35MS"""
<|body_0|>
def numTilings_1(self, N):
""":type N: int :rtype: int 95MS"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if N == 1:
return 1
if N == 2:
... | stack_v2_sparse_classes_10k_train_001201 | 1,973 | no_license | [
{
"docstring": ":type N: int :rtype: int 35MS",
"name": "numTilings",
"signature": "def numTilings(self, N)"
},
{
"docstring": ":type N: int :rtype: int 95MS",
"name": "numTilings_1",
"signature": "def numTilings_1(self, N)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002825 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numTilings(self, N): :type N: int :rtype: int 35MS
- def numTilings_1(self, N): :type N: int :rtype: int 95MS | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numTilings(self, N): :type N: int :rtype: int 35MS
- def numTilings_1(self, N): :type N: int :rtype: int 95MS
<|skeleton|>
class Solution:
def numTilings(self, N):
... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def numTilings(self, N):
""":type N: int :rtype: int 35MS"""
<|body_0|>
def numTilings_1(self, N):
""":type N: int :rtype: int 95MS"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def numTilings(self, N):
""":type N: int :rtype: int 35MS"""
if N == 1:
return 1
if N == 2:
return 2
dp = [1 for _ in range(N + 1)]
dp[2] = 2
for i in range(3, N + 1):
dp[i] = (2 * dp[i - 1] + dp[i - 3]) % int(100000... | the_stack_v2_python_sparse | DominoAndTrominoTiling_MID_790.py | 953250587/leetcode-python | train | 2 | |
46387d7f47da692898cc02ef9a31660e46dc86dc | [
"device = get_object_or_404(Device, slug=slug)\nself.check_object_permissions(request, device)\nserializer = DeviceRetrieveUpdateDestroySerializer(device, many=False)\nreturn Response(data=serializer.data, status=status.HTTP_200_OK)",
"device = get_object_or_404(Device, slug=slug)\nself.check_object_permissions(r... | <|body_start_0|>
device = get_object_or_404(Device, slug=slug)
self.check_object_permissions(request, device)
serializer = DeviceRetrieveUpdateDestroySerializer(device, many=False)
return Response(data=serializer.data, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
d... | DeviceRetrieveUpdateDestroyAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceRetrieveUpdateDestroyAPIView:
def get(self, request, slug=None):
"""Retrieve"""
<|body_0|>
def put(self, request, slug=None):
"""Update"""
<|body_1|>
def delete(self, request, slug=None):
"""Delete"""
<|body_2|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_001202 | 5,225 | permissive | [
{
"docstring": "Retrieve",
"name": "get",
"signature": "def get(self, request, slug=None)"
},
{
"docstring": "Update",
"name": "put",
"signature": "def put(self, request, slug=None)"
},
{
"docstring": "Delete",
"name": "delete",
"signature": "def delete(self, request, slu... | 3 | null | Implement the Python class `DeviceRetrieveUpdateDestroyAPIView` described below.
Class description:
Implement the DeviceRetrieveUpdateDestroyAPIView class.
Method signatures and docstrings:
- def get(self, request, slug=None): Retrieve
- def put(self, request, slug=None): Update
- def delete(self, request, slug=None)... | Implement the Python class `DeviceRetrieveUpdateDestroyAPIView` described below.
Class description:
Implement the DeviceRetrieveUpdateDestroyAPIView class.
Method signatures and docstrings:
- def get(self, request, slug=None): Retrieve
- def put(self, request, slug=None): Update
- def delete(self, request, slug=None)... | 98e1ff8bab7dda3492e5ff637bf5aafd111c840c | <|skeleton|>
class DeviceRetrieveUpdateDestroyAPIView:
def get(self, request, slug=None):
"""Retrieve"""
<|body_0|>
def put(self, request, slug=None):
"""Update"""
<|body_1|>
def delete(self, request, slug=None):
"""Delete"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeviceRetrieveUpdateDestroyAPIView:
def get(self, request, slug=None):
"""Retrieve"""
device = get_object_or_404(Device, slug=slug)
self.check_object_permissions(request, device)
serializer = DeviceRetrieveUpdateDestroySerializer(device, many=False)
return Response(data... | the_stack_v2_python_sparse | mikaponics/device/views/resources/device_crud_api_views.py | mikaponics/mikaponics-back | train | 4 | |
7e98a1f7014d23634fa7967fa88a9ffeff019a2b | [
"tl = self._grid.GetSelectionBlockTopLeft()\nbr = self._grid.GetSelectionBlockBottomRight()\nif tl == [(0, 0)] and br == [(self._grid.GetNumberRows() - 1, self._grid.GetNumberCols() - 1)]:\n self._grid.ClearSelection()\nfor (tlrow, tlcolumn), (brrow, brcolumn) in zip(tl, br):\n for row in range(tlrow, brrow +... | <|body_start_0|>
tl = self._grid.GetSelectionBlockTopLeft()
br = self._grid.GetSelectionBlockBottomRight()
if tl == [(0, 0)] and br == [(self._grid.GetNumberRows() - 1, self._grid.GetNumberCols() - 1)]:
self._grid.ClearSelection()
for (tlrow, tlcolumn), (brrow, brcolumn) in z... | s3dcGridMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class s3dcGridMixin:
def _handlerGridRangeSelect(self, event):
"""This event handler is a fix for the fact that the row selection in the wxGrid is deliberately broken. It's also used to activate and deactivate relevant menubar items. Whenever a user clicks on a cell, the grid SHOWS its row to ... | stack_v2_sparse_classes_10k_train_001203 | 3,119 | no_license | [
{
"docstring": "This event handler is a fix for the fact that the row selection in the wxGrid is deliberately broken. It's also used to activate and deactivate relevant menubar items. Whenever a user clicks on a cell, the grid SHOWS its row to be selected, but GetSelectedRows() doesn't think so. This event hand... | 2 | stack_v2_sparse_classes_30k_train_000382 | Implement the Python class `s3dcGridMixin` described below.
Class description:
Implement the s3dcGridMixin class.
Method signatures and docstrings:
- def _handlerGridRangeSelect(self, event): This event handler is a fix for the fact that the row selection in the wxGrid is deliberately broken. It's also used to activa... | Implement the Python class `s3dcGridMixin` described below.
Class description:
Implement the s3dcGridMixin class.
Method signatures and docstrings:
- def _handlerGridRangeSelect(self, event): This event handler is a fix for the fact that the row selection in the wxGrid is deliberately broken. It's also used to activa... | 586225d68b079e2a96007bd33784113b3a19a538 | <|skeleton|>
class s3dcGridMixin:
def _handlerGridRangeSelect(self, event):
"""This event handler is a fix for the fact that the row selection in the wxGrid is deliberately broken. It's also used to activate and deactivate relevant menubar items. Whenever a user clicks on a cell, the grid SHOWS its row to ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class s3dcGridMixin:
def _handlerGridRangeSelect(self, event):
"""This event handler is a fix for the fact that the row selection in the wxGrid is deliberately broken. It's also used to activate and deactivate relevant menubar items. Whenever a user clicks on a cell, the grid SHOWS its row to be selected, b... | the_stack_v2_python_sparse | modules/viewers/slice3dVWRmodules/shared.py | JoonVan/devide | train | 0 | |
ee26eb86a6a90c6b4badd59216bb48100934e49e | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('medinad', 'medinad')\npolice = repo.medinad.police\nneighborhoods = repo.medinad.neighbor\n\ndef product(R, S):\n return [(t, u) for t in R for u in S]\n\ndef project(R, p):\n return [p(t) for t in... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('medinad', 'medinad')
police = repo.medinad.police
neighborhoods = repo.medinad.neighbor
def product(R, S):
return [(t, u) for... | policeneighbors | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class policeneighbors:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythi... | stack_v2_sparse_classes_10k_train_001204 | 5,402 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_003213 | Implement the Python class `policeneighbors` described below.
Class description:
Implement the policeneighbors class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=Non... | Implement the Python class `policeneighbors` described below.
Class description:
Implement the policeneighbors class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=Non... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class policeneighbors:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class policeneighbors:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('medinad', 'medinad')
police... | the_stack_v2_python_sparse | jtbloom_rfballes_medinad/medinad/policeneighbors.py | ROODAY/course-2017-fal-proj | train | 3 | |
a28524f6dbeae83f1a9e2ccab6f5337877b53d81 | [
"truck_sheet = TruckSheet.query.get_sheet_or_404(truck_sheet_id)\norder_sheet = OrderSheet.query.get_sheet_or_404(order_sheet_id)\nreturn Planning.query.get_or_404((truck_sheet.id, order_sheet.id))",
"truck_sheet = TruckSheet.query.get_sheet_or_404(truck_sheet_id)\norder_sheet = OrderSheet.query.get_sheet_or_404(... | <|body_start_0|>
truck_sheet = TruckSheet.query.get_sheet_or_404(truck_sheet_id)
order_sheet = OrderSheet.query.get_sheet_or_404(order_sheet_id)
return Planning.query.get_or_404((truck_sheet.id, order_sheet.id))
<|end_body_0|>
<|body_start_1|>
truck_sheet = TruckSheet.query.get_sheet_or... | PlanningByID | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlanningByID:
def get(self, truck_sheet_id, order_sheet_id):
"""Get a single planning. `Truck_sheet_id` and `order_sheet_id` can both be the primary key of the sheets, or `latest` to use the latest sheet. Roles required: View-only, planner, administrator"""
<|body_0|>
def po... | stack_v2_sparse_classes_10k_train_001205 | 3,651 | permissive | [
{
"docstring": "Get a single planning. `Truck_sheet_id` and `order_sheet_id` can both be the primary key of the sheets, or `latest` to use the latest sheet. Roles required: View-only, planner, administrator",
"name": "get",
"signature": "def get(self, truck_sheet_id, order_sheet_id)"
},
{
"docst... | 2 | stack_v2_sparse_classes_30k_train_003058 | Implement the Python class `PlanningByID` described below.
Class description:
Implement the PlanningByID class.
Method signatures and docstrings:
- def get(self, truck_sheet_id, order_sheet_id): Get a single planning. `Truck_sheet_id` and `order_sheet_id` can both be the primary key of the sheets, or `latest` to use ... | Implement the Python class `PlanningByID` described below.
Class description:
Implement the PlanningByID class.
Method signatures and docstrings:
- def get(self, truck_sheet_id, order_sheet_id): Get a single planning. `Truck_sheet_id` and `order_sheet_id` can both be the primary key of the sheets, or `latest` to use ... | a74faa30139a7c32ce2b872544eb2fac588716cd | <|skeleton|>
class PlanningByID:
def get(self, truck_sheet_id, order_sheet_id):
"""Get a single planning. `Truck_sheet_id` and `order_sheet_id` can both be the primary key of the sheets, or `latest` to use the latest sheet. Roles required: View-only, planner, administrator"""
<|body_0|>
def po... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PlanningByID:
def get(self, truck_sheet_id, order_sheet_id):
"""Get a single planning. `Truck_sheet_id` and `order_sheet_id` can both be the primary key of the sheets, or `latest` to use the latest sheet. Roles required: View-only, planner, administrator"""
truck_sheet = TruckSheet.query.get_s... | the_stack_v2_python_sparse | backend/api/plannings/resources.py | Hori1234/otmdservices | train | 0 | |
5c20b2f84bb4c04d8a273c447b6eb80ceede38c0 | [
"print('压缩 %s 到 %s' % (source_dir, target_jar))\nfilex.check_and_create_dir(target_jar)\ntranslation_file_list = []\nfor root, dirs, files in os.walk(source_dir):\n for file_name in files:\n path = root + '/' + file_name\n translation_file_list.append(path.replace(source_dir, '').replace('\\\\', '/... | <|body_start_0|>
print('压缩 %s 到 %s' % (source_dir, target_jar))
filex.check_and_create_dir(target_jar)
translation_file_list = []
for root, dirs, files in os.walk(source_dir):
for file_name in files:
path = root + '/' + file_name
translation_fi... | ZipTools | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZipTools:
def zip_jar(source_dir, target_jar, rename_cn=False, rename_tips=False):
"""压缩文件夹 :param source_dir: :param target_jar: :param rename_cn: 是否将 _zh_CN 重命名再压缩 :return:"""
<|body_0|>
def extra_file(zip_file_path, file_path, output, print_msg=True):
"""解压文件"""
... | stack_v2_sparse_classes_10k_train_001206 | 37,444 | no_license | [
{
"docstring": "压缩文件夹 :param source_dir: :param target_jar: :param rename_cn: 是否将 _zh_CN 重命名再压缩 :return:",
"name": "zip_jar",
"signature": "def zip_jar(source_dir, target_jar, rename_cn=False, rename_tips=False)"
},
{
"docstring": "解压文件",
"name": "extra_file",
"signature": "def extra_fil... | 2 | null | Implement the Python class `ZipTools` described below.
Class description:
Implement the ZipTools class.
Method signatures and docstrings:
- def zip_jar(source_dir, target_jar, rename_cn=False, rename_tips=False): 压缩文件夹 :param source_dir: :param target_jar: :param rename_cn: 是否将 _zh_CN 重命名再压缩 :return:
- def extra_file... | Implement the Python class `ZipTools` described below.
Class description:
Implement the ZipTools class.
Method signatures and docstrings:
- def zip_jar(source_dir, target_jar, rename_cn=False, rename_tips=False): 压缩文件夹 :param source_dir: :param target_jar: :param rename_cn: 是否将 _zh_CN 重命名再压缩 :return:
- def extra_file... | efea806d49f07d78e3db0390696778d4a7fc6c28 | <|skeleton|>
class ZipTools:
def zip_jar(source_dir, target_jar, rename_cn=False, rename_tips=False):
"""压缩文件夹 :param source_dir: :param target_jar: :param rename_cn: 是否将 _zh_CN 重命名再压缩 :return:"""
<|body_0|>
def extra_file(zip_file_path, file_path, output, print_msg=True):
"""解压文件"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ZipTools:
def zip_jar(source_dir, target_jar, rename_cn=False, rename_tips=False):
"""压缩文件夹 :param source_dir: :param target_jar: :param rename_cn: 是否将 _zh_CN 重命名再压缩 :return:"""
print('压缩 %s 到 %s' % (source_dir, target_jar))
filex.check_and_create_dir(target_jar)
translation_fi... | the_stack_v2_python_sparse | ToolsX/tool/android/android_studio_translator/jet_brains_translator/jet_brains_translator.py | JunLei-MI/PythonX | train | 0 | |
38842145fb4093a1e86ed8ef81538bde37835646 | [
"if not language in ACCEPTED_LANGUAGES:\n raise ValueError(f'Language {language} is not supported yet')\nelif descriptive_indices is not None and descriptive_indices.language != language:\n raise ValueError(f'The descriptive indices analyzer must be of the same language as the word information analyzer.')\nse... | <|body_start_0|>
if not language in ACCEPTED_LANGUAGES:
raise ValueError(f'Language {language} is not supported yet')
elif descriptive_indices is not None and descriptive_indices.language != language:
raise ValueError(f'The descriptive indices analyzer must be of the same languag... | This class will handle all operations to find the readability indices of a text according to Coh-Metrix. | ReadabilityIndices | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadabilityIndices:
"""This class will handle all operations to find the readability indices of a text according to Coh-Metrix."""
def __init__(self, nlp, language: str='es', descriptive_indices: DescriptiveIndices=None) -> None:
"""The constructor will initialize this object that ca... | stack_v2_sparse_classes_10k_train_001207 | 3,373 | no_license | [
{
"docstring": "The constructor will initialize this object that calculates the readability indices for a specific language of those that are available. Parameters: nlp: The spacy model that corresponds to a language. language(str): The language that the texts to process will have. descriptive_indices(Descripti... | 2 | stack_v2_sparse_classes_30k_train_000363 | Implement the Python class `ReadabilityIndices` described below.
Class description:
This class will handle all operations to find the readability indices of a text according to Coh-Metrix.
Method signatures and docstrings:
- def __init__(self, nlp, language: str='es', descriptive_indices: DescriptiveIndices=None) -> ... | Implement the Python class `ReadabilityIndices` described below.
Class description:
This class will handle all operations to find the readability indices of a text according to Coh-Metrix.
Method signatures and docstrings:
- def __init__(self, nlp, language: str='es', descriptive_indices: DescriptiveIndices=None) -> ... | f23342fbf2cb54a89cd381813ad9eee754b61094 | <|skeleton|>
class ReadabilityIndices:
"""This class will handle all operations to find the readability indices of a text according to Coh-Metrix."""
def __init__(self, nlp, language: str='es', descriptive_indices: DescriptiveIndices=None) -> None:
"""The constructor will initialize this object that ca... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ReadabilityIndices:
"""This class will handle all operations to find the readability indices of a text according to Coh-Metrix."""
def __init__(self, nlp, language: str='es', descriptive_indices: DescriptiveIndices=None) -> None:
"""The constructor will initialize this object that calculates the ... | the_stack_v2_python_sparse | src/processing/coh_metrix_indices/readability_indices.py | persuaide/Tesis_Chatbot | train | 0 |
1437c9583dbb261184023f7ca5008c03ae81243e | [
"graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges)\ntested_pass = AddIsCyclicAttribute()\ntested_pass.find_and_replace_pattern(graph)\nassert graph.graph['is_cyclic'] is False",
"graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges, new_edg... | <|body_start_0|>
graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges)
tested_pass = AddIsCyclicAttribute()
tested_pass.find_and_replace_pattern(graph)
assert graph.graph['is_cyclic'] is False
<|end_body_0|>
<|body_start_1|>
graph = build_graph... | AddIsCyclicAttributeTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddIsCyclicAttributeTest:
def test_1(self):
"""Acyclic case => graph.graph['is_cyclic'] should be False."""
<|body_0|>
def test_2(self):
"""Cyclic case => graph.graph['is_cyclic'] should be True. :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_001208 | 1,771 | permissive | [
{
"docstring": "Acyclic case => graph.graph['is_cyclic'] should be False.",
"name": "test_1",
"signature": "def test_1(self)"
},
{
"docstring": "Cyclic case => graph.graph['is_cyclic'] should be True. :return:",
"name": "test_2",
"signature": "def test_2(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003095 | Implement the Python class `AddIsCyclicAttributeTest` described below.
Class description:
Implement the AddIsCyclicAttributeTest class.
Method signatures and docstrings:
- def test_1(self): Acyclic case => graph.graph['is_cyclic'] should be False.
- def test_2(self): Cyclic case => graph.graph['is_cyclic'] should be ... | Implement the Python class `AddIsCyclicAttributeTest` described below.
Class description:
Implement the AddIsCyclicAttributeTest class.
Method signatures and docstrings:
- def test_1(self): Acyclic case => graph.graph['is_cyclic'] should be False.
- def test_2(self): Cyclic case => graph.graph['is_cyclic'] should be ... | 2e6c95f389b195f6d3ff8597147d1f817433cfb3 | <|skeleton|>
class AddIsCyclicAttributeTest:
def test_1(self):
"""Acyclic case => graph.graph['is_cyclic'] should be False."""
<|body_0|>
def test_2(self):
"""Cyclic case => graph.graph['is_cyclic'] should be True. :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddIsCyclicAttributeTest:
def test_1(self):
"""Acyclic case => graph.graph['is_cyclic'] should be False."""
graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges)
tested_pass = AddIsCyclicAttribute()
tested_pass.find_and_replace_pattern(graph)
... | the_stack_v2_python_sparse | model-optimizer/extensions/middle/AddIsCyclicAttribute_test.py | 0xF6/openvino | train | 2 | |
56d67561858ea517483ad47f76c4b85a1913e0ba | [
"ctx = super().get_panel_context(view, request, context)\nif isinstance(view, StockLocationDetail):\n ctx['location'] = view.get_object()\nreturn ctx",
"panels = [{'title': 'No Content'}]\nif self.get_setting('ENABLE_HELLO_WORLD'):\n content = \"\\n <strong>Hello world!</strong>\\n <hr... | <|body_start_0|>
ctx = super().get_panel_context(view, request, context)
if isinstance(view, StockLocationDetail):
ctx['location'] = view.get_object()
return ctx
<|end_body_0|>
<|body_start_1|>
panels = [{'title': 'No Content'}]
if self.get_setting('ENABLE_HELLO_WORL... | A sample plugin which renders some custom panels. | CustomPanelSample | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomPanelSample:
"""A sample plugin which renders some custom panels."""
def get_panel_context(self, view, request, context):
"""Returns enriched context."""
<|body_0|>
def get_custom_panels(self, view, request):
"""You can decide at run-time which custom panel... | stack_v2_sparse_classes_10k_train_001209 | 4,420 | permissive | [
{
"docstring": "Returns enriched context.",
"name": "get_panel_context",
"signature": "def get_panel_context(self, view, request, context)"
},
{
"docstring": "You can decide at run-time which custom panels you want to display! - Display on every page - Only on a single page or set of pages - Onl... | 2 | stack_v2_sparse_classes_30k_train_003845 | Implement the Python class `CustomPanelSample` described below.
Class description:
A sample plugin which renders some custom panels.
Method signatures and docstrings:
- def get_panel_context(self, view, request, context): Returns enriched context.
- def get_custom_panels(self, view, request): You can decide at run-ti... | Implement the Python class `CustomPanelSample` described below.
Class description:
A sample plugin which renders some custom panels.
Method signatures and docstrings:
- def get_panel_context(self, view, request, context): Returns enriched context.
- def get_custom_panels(self, view, request): You can decide at run-ti... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class CustomPanelSample:
"""A sample plugin which renders some custom panels."""
def get_panel_context(self, view, request, context):
"""Returns enriched context."""
<|body_0|>
def get_custom_panels(self, view, request):
"""You can decide at run-time which custom panel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CustomPanelSample:
"""A sample plugin which renders some custom panels."""
def get_panel_context(self, view, request, context):
"""Returns enriched context."""
ctx = super().get_panel_context(view, request, context)
if isinstance(view, StockLocationDetail):
ctx['locati... | the_stack_v2_python_sparse | InvenTree/plugin/samples/integration/custom_panel_sample.py | inventree/InvenTree | train | 3,077 |
a97e4bcaa8292daec01217899686888da783db12 | [
"params = kwarg['params']\ncmd = 'df '\nreturn cmd",
"disk = []\nrecords = output.split('\\n')[1:]\nfor r in records:\n r = r.strip()\n if not r:\n continue\n tokens = r.split()\n filesystem = tokens.pop(0)\n size = int(tokens.pop(0))\n used = int(tokens.pop(0))\n available = int(token... | <|body_start_0|>
params = kwarg['params']
cmd = 'df '
return cmd
<|end_body_0|>
<|body_start_1|>
disk = []
records = output.split('\n')[1:]
for r in records:
r = r.strip()
if not r:
continue
tokens = r.split()
... | Disk free inforamtion | LinuxDiskFreeImpl | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinuxDiskFreeImpl:
"""Disk free inforamtion"""
def format_show(self, command, *argv, **kwarg):
"""> df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 603M 34% /mnt/onl/images /dev/sda1 123M 29M 89M 25% /mnt/o... | stack_v2_sparse_classes_10k_train_001210 | 2,420 | permissive | [
{
"docstring": "> df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 603M 34% /mnt/onl/images /dev/sda1 123M 29M 89M 25% /mnt/onl/boot /dev/sda2 120M 1.6M 110M 2% /mnt/onl/config tmpfs 3.9G 0 3.9G 0% /dev/shm tmpfs 3.9G 8.9M 3.9G 1% /run... | 2 | stack_v2_sparse_classes_30k_train_002673 | Implement the Python class `LinuxDiskFreeImpl` described below.
Class description:
Disk free inforamtion
Method signatures and docstrings:
- def format_show(self, command, *argv, **kwarg): > df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 6... | Implement the Python class `LinuxDiskFreeImpl` described below.
Class description:
Disk free inforamtion
Method signatures and docstrings:
- def format_show(self, command, *argv, **kwarg): > df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 6... | e4c8221e18cd94e7424c30e12eb0fb82f7767267 | <|skeleton|>
class LinuxDiskFreeImpl:
"""Disk free inforamtion"""
def format_show(self, command, *argv, **kwarg):
"""> df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 603M 34% /mnt/onl/images /dev/sda1 123M 29M 89M 25% /mnt/o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LinuxDiskFreeImpl:
"""Disk free inforamtion"""
def format_show(self, command, *argv, **kwarg):
"""> df -h Filesystem Size Used Avail Use% Mounted on devtmpfs 1.0M 0 1.0M 0% /dev /dev/sda4 24G 1.2G 22G 6% / /dev/sda3 976M 306M 603M 34% /mnt/onl/images /dev/sda1 123M 29M 89M 25% /mnt/onl/boot /dev/... | the_stack_v2_python_sparse | Amazon_Framework/DentOsTestbedLib/src/dent_os_testbed/lib/os/linux/linux_disk_free_impl.py | tld3daniel/testing | train | 0 |
27a65d72eb227977ba2fc0414ff3462275cdb4b8 | [
"self.estrutura = frame(frame=fram)\nself.e = self.estrutura\nself.size = size\nself.cor_dos_detalhes = c\nself.desenha_as_partes_do_bloco()",
"s = self.size / 2\nfr, ns = (self.estrutura, (-s, s))\nconvex(pos=[(x, ht * z / self.size, y) for x in ns for y in ns for z in ns if x - y or x - s], color=self.cor_dos_d... | <|body_start_0|>
self.estrutura = frame(frame=fram)
self.e = self.estrutura
self.size = size
self.cor_dos_detalhes = c
self.desenha_as_partes_do_bloco()
<|end_body_0|>
<|body_start_1|>
s = self.size / 2
fr, ns = (self.estrutura, (-s, s))
convex(pos=[(x, h... | Esse eu fiz para vocês: um prisma triangular que representa um telhado | prism | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class prism:
"""Esse eu fiz para vocês: um prisma triangular que representa um telhado"""
def __init__(self, fram=frame(), size=10.0, c=color.white):
"""ontogênese: assim que é criado, o bloco se desenha"""
<|body_0|>
def desenha_as_partes_do_bloco(self):
"""cria um ob... | stack_v2_sparse_classes_10k_train_001211 | 5,267 | no_license | [
{
"docstring": "ontogênese: assim que é criado, o bloco se desenha",
"name": "__init__",
"signature": "def __init__(self, fram=frame(), size=10.0, c=color.white)"
},
{
"docstring": "cria um objeto convexo que passa por seis pontos no espaço",
"name": "desenha_as_partes_do_bloco",
"signat... | 2 | stack_v2_sparse_classes_30k_train_000190 | Implement the Python class `prism` described below.
Class description:
Esse eu fiz para vocês: um prisma triangular que representa um telhado
Method signatures and docstrings:
- def __init__(self, fram=frame(), size=10.0, c=color.white): ontogênese: assim que é criado, o bloco se desenha
- def desenha_as_partes_do_bl... | Implement the Python class `prism` described below.
Class description:
Esse eu fiz para vocês: um prisma triangular que representa um telhado
Method signatures and docstrings:
- def __init__(self, fram=frame(), size=10.0, c=color.white): ontogênese: assim que é criado, o bloco se desenha
- def desenha_as_partes_do_bl... | 91a88b5a9b15f324a64afc18607a5d1d0a25c4d0 | <|skeleton|>
class prism:
"""Esse eu fiz para vocês: um prisma triangular que representa um telhado"""
def __init__(self, fram=frame(), size=10.0, c=color.white):
"""ontogênese: assim que é criado, o bloco se desenha"""
<|body_0|>
def desenha_as_partes_do_bloco(self):
"""cria um ob... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class prism:
"""Esse eu fiz para vocês: um prisma triangular que representa um telhado"""
def __init__(self, fram=frame(), size=10.0, c=color.white):
"""ontogênese: assim que é criado, o bloco se desenha"""
self.estrutura = frame(frame=fram)
self.e = self.estrutura
self.size = s... | the_stack_v2_python_sparse | artwork/abrapa/abrapa.py | cetoli/labase-draft | train | 0 |
957af1f455c3986a871f29441c61d050dc21fe4c | [
"try:\n account_id = resource_utils.get_account_id(request)\n if account_id is None:\n return resource_utils.account_required_response()\n if not authorized(account_id, jwt):\n return resource_utils.unauthorized_error_response(account_id)\n username = 'anonymous'\n user = User.find_by_j... | <|body_start_0|>
try:
account_id = resource_utils.get_account_id(request)
if account_id is None:
return resource_utils.account_required_response()
if not authorized(account_id, jwt):
return resource_utils.unauthorized_error_response(account_id)... | Resource for executing draft statements. | DraftResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DraftResource:
"""Resource for executing draft statements."""
def get():
"""Get the list of draft statements belonging to the header account ID."""
<|body_0|>
def post():
"""Create a new draft statement."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_001212 | 9,959 | permissive | [
{
"docstring": "Get the list of draft statements belonging to the header account ID.",
"name": "get",
"signature": "def get()"
},
{
"docstring": "Create a new draft statement.",
"name": "post",
"signature": "def post()"
}
] | 2 | stack_v2_sparse_classes_30k_val_000223 | Implement the Python class `DraftResource` described below.
Class description:
Resource for executing draft statements.
Method signatures and docstrings:
- def get(): Get the list of draft statements belonging to the header account ID.
- def post(): Create a new draft statement. | Implement the Python class `DraftResource` described below.
Class description:
Resource for executing draft statements.
Method signatures and docstrings:
- def get(): Get the list of draft statements belonging to the header account ID.
- def post(): Create a new draft statement.
<|skeleton|>
class DraftResource:
... | af1a4458bb78c16ecca484514d4bd0d1d8c24b5d | <|skeleton|>
class DraftResource:
"""Resource for executing draft statements."""
def get():
"""Get the list of draft statements belonging to the header account ID."""
<|body_0|>
def post():
"""Create a new draft statement."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DraftResource:
"""Resource for executing draft statements."""
def get():
"""Get the list of draft statements belonging to the header account ID."""
try:
account_id = resource_utils.get_account_id(request)
if account_id is None:
return resource_utils... | the_stack_v2_python_sparse | ppr-api/src/ppr_api/resources/drafts.py | bcgov/ppr | train | 4 |
43879ca3aef1ae28c37716e2c2f4fd66486cf481 | [
"\"\"\"找出所有的pair, 如果符合条件，计数器加1 O(n^2)\"\"\"\ncount = 0\nfor i in range(len(nums)):\n for j in range(i + 1, len(nums)):\n if abs(nums[i] - nums[j]) == k:\n count += 1\nreturn count",
"\"\"\"\n 思路：如果k不等于零的话，那就是nums和nums数组每个数加k集合的交，如果k等于零的话，那就统计数组中相同的数字即可\n 区分开k=0的情况\n \... | <|body_start_0|>
"""找出所有的pair, 如果符合条件，计数器加1 O(n^2)"""
count = 0
for i in range(len(nums)):
for j in range(i + 1, len(nums)):
if abs(nums[i] - nums[j]) == k:
count += 1
return count
<|end_body_0|>
<|body_start_1|>
"""
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findPairs_simple(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def findPairs_map(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
def findPairs_pointer(self, nums, k):
... | stack_v2_sparse_classes_10k_train_001213 | 2,289 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findPairs_simple",
"signature": "def findPairs_simple(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findPairs_map",
"signature": "def findPairs_map(self, nums, k)"
}... | 3 | stack_v2_sparse_classes_30k_train_004591 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPairs_simple(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findPairs_map(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findP... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPairs_simple(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findPairs_map(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def findP... | a0f270c1adce25be11df92877813037f2e73e28b | <|skeleton|>
class Solution:
def findPairs_simple(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def findPairs_map(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
def findPairs_pointer(self, nums, k):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findPairs_simple(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
"""找出所有的pair, 如果符合条件，计数器加1 O(n^2)"""
count = 0
for i in range(len(nums)):
for j in range(i + 1, len(nums)):
if abs(nums[i] - nums[j]) == k:
... | the_stack_v2_python_sparse | leetcode/532_k_diff_pairs_in_an_array.py | lvraikkonen/GoodCode | train | 0 | |
394828d907cf0f2b3ee48f0e5351684adb771078 | [
"assert bias.shape[0] == 4\nassert weight_hh.shape[0] == 4\nassert weight_hh.shape[1] == 1\nself.hidden_size: int = 1\nself.input_size: int = input_size\nself.bias: np.ndarray = bias\nself.weight_hh: np.ndarray = weight_hh\nself.weight_xh: np.ndarray = weight_xh\nself.hx: np.ndarray = np.asarray([])\nself.c: np.nda... | <|body_start_0|>
assert bias.shape[0] == 4
assert weight_hh.shape[0] == 4
assert weight_hh.shape[1] == 1
self.hidden_size: int = 1
self.input_size: int = input_size
self.bias: np.ndarray = bias
self.weight_hh: np.ndarray = weight_hh
self.weight_xh: np.ndar... | Custom implementation of the single LSTM-cell. | LSTMCell | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTMCell:
"""Custom implementation of the single LSTM-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the LSTM-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bia... | stack_v2_sparse_classes_10k_train_001214 | 2,345 | permissive | [
{
"docstring": "Create the LSTM-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bias: Bias-vector from each of the internal nodes :param weight_hh: Weight-vector from hidden to hidden states :param weight_xh: Weight-vector from input to hidden states",
"name... | 2 | stack_v2_sparse_classes_30k_test_000111 | Implement the Python class `LSTMCell` described below.
Class description:
Custom implementation of the single LSTM-cell.
Method signatures and docstrings:
- def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray): Create the LSTM-cell with the provided parameters. :param in... | Implement the Python class `LSTMCell` described below.
Class description:
Custom implementation of the single LSTM-cell.
Method signatures and docstrings:
- def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray): Create the LSTM-cell with the provided parameters. :param in... | 818a4ce941536611c0f1780f7c4a6238f0e1884e | <|skeleton|>
class LSTMCell:
"""Custom implementation of the single LSTM-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the LSTM-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bia... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LSTMCell:
"""Custom implementation of the single LSTM-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the LSTM-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bias: Bias-vecto... | the_stack_v2_python_sparse | population/utils/rnn_cell_util/lstm.py | RubenPants/EvolvableRNN | train | 1 |
195615d77634f7bba2f28f8323e06311ab8d04a8 | [
"super(Monitor, self).__init__(agent)\nself._baseagent += '_Monitor'\nself.update_delay = 0.5\nself.last_time = time.time() + 5\nself.history = {}",
"self.render()\ns_time = env.get_current_time()\ns_date = s_time.split(' ')[0]\nd_position = {}\nfor s_symbol, instr in iter(self._instr_stack.items()):\n d_posit... | <|body_start_0|>
super(Monitor, self).__init__(agent)
self._baseagent += '_Monitor'
self.update_delay = 0.5
self.last_time = time.time() + 5
self.history = {}
<|end_body_0|>
<|body_start_1|>
self.render()
s_time = env.get_current_time()
s_date = s_time.sp... | Monitor is used to including new methods to the agent that are not used in production environment and render information to be used in an external data visualization | Monitor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Monitor:
"""Monitor is used to including new methods to the agent that are not used in production environment and render information to be used in an external data visualization"""
def __init__(self, agent):
"""Initiate a Tester instance. Save all parameters as attributes :param agen... | stack_v2_sparse_classes_10k_train_001215 | 4,389 | permissive | [
{
"docstring": "Initiate a Tester instance. Save all parameters as attributes :param agent: Agent object.",
"name": "__init__",
"signature": "def __init__(self, agent)"
},
{
"docstring": "Flush all relevant monitor information :param env: Environment Object.",
"name": "flush",
"signature... | 4 | stack_v2_sparse_classes_30k_train_005537 | Implement the Python class `Monitor` described below.
Class description:
Monitor is used to including new methods to the agent that are not used in production environment and render information to be used in an external data visualization
Method signatures and docstrings:
- def __init__(self, agent): Initiate a Teste... | Implement the Python class `Monitor` described below.
Class description:
Monitor is used to including new methods to the agent that are not used in production environment and render information to be used in an external data visualization
Method signatures and docstrings:
- def __init__(self, agent): Initiate a Teste... | 2d52bdc46895e5659f4ffbc6ffa2629392ed4f9a | <|skeleton|>
class Monitor:
"""Monitor is used to including new methods to the agent that are not used in production environment and render information to be used in an external data visualization"""
def __init__(self, agent):
"""Initiate a Tester instance. Save all parameters as attributes :param agen... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Monitor:
"""Monitor is used to including new methods to the agent that are not used in production environment and render information to be used in an external data visualization"""
def __init__(self, agent):
"""Initiate a Tester instance. Save all parameters as attributes :param agent: Agent obje... | the_stack_v2_python_sparse | gymV02/wrappers/monitoring.py | onesoftsa/neutrino-lab | train | 8 |
07c94975c2840d4c2d2c22e8ec4ba0f112fba832 | [
"assert first_available_dim < 0, first_available_dim\nself.next_available_dim = first_available_dim\nself.next_available_id = 0\nself.dim_to_id = {}",
"id_ = self.next_available_id\nself.next_available_id += 1\ndim = self.next_available_dim\nif dim == -float('inf'):\n raise ValueError('max_plate_nesting must b... | <|body_start_0|>
assert first_available_dim < 0, first_available_dim
self.next_available_dim = first_available_dim
self.next_available_id = 0
self.dim_to_id = {}
<|end_body_0|>
<|body_start_1|>
id_ = self.next_available_id
self.next_available_id += 1
dim = self.n... | Dimension allocator for internal use by :func:`~pyro.poutine.markov`. There is a single global instance. Note that dimensions are indexed from the right, e.g. -1, -2. Note that ids are simply nonnegative integers here. | _EnumAllocator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _EnumAllocator:
"""Dimension allocator for internal use by :func:`~pyro.poutine.markov`. There is a single global instance. Note that dimensions are indexed from the right, e.g. -1, -2. Note that ids are simply nonnegative integers here."""
def set_first_available_dim(self, first_available_d... | stack_v2_sparse_classes_10k_train_001216 | 10,402 | permissive | [
{
"docstring": "Set the first available dim, which should be to the left of all :class:`plate` dimensions, e.g. ``-1 - max_plate_nesting``. This should be called once per program. In SVI this should be called only once per (guide,model) pair.",
"name": "set_first_available_dim",
"signature": "def set_fi... | 2 | null | Implement the Python class `_EnumAllocator` described below.
Class description:
Dimension allocator for internal use by :func:`~pyro.poutine.markov`. There is a single global instance. Note that dimensions are indexed from the right, e.g. -1, -2. Note that ids are simply nonnegative integers here.
Method signatures a... | Implement the Python class `_EnumAllocator` described below.
Class description:
Dimension allocator for internal use by :func:`~pyro.poutine.markov`. There is a single global instance. Note that dimensions are indexed from the right, e.g. -1, -2. Note that ids are simply nonnegative integers here.
Method signatures a... | 0e82cad30f75b892a07e6c9a5f9e24f2cb5d0d81 | <|skeleton|>
class _EnumAllocator:
"""Dimension allocator for internal use by :func:`~pyro.poutine.markov`. There is a single global instance. Note that dimensions are indexed from the right, e.g. -1, -2. Note that ids are simply nonnegative integers here."""
def set_first_available_dim(self, first_available_d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _EnumAllocator:
"""Dimension allocator for internal use by :func:`~pyro.poutine.markov`. There is a single global instance. Note that dimensions are indexed from the right, e.g. -1, -2. Note that ids are simply nonnegative integers here."""
def set_first_available_dim(self, first_available_dim):
... | the_stack_v2_python_sparse | pyro/poutine/runtime.py | pyro-ppl/pyro | train | 3,647 |
3ceb2508bd521f24c76178c55d01e5a72ab9efb8 | [
"if 'output' in results:\n self.data = P.YamboOutputParser(results['output'], verbose=verbose, extendOut=extendOut)\nelse:\n print('There are no o-* files in the %s dictionary. Please check...' % results)\nfor key, value in results.items():\n if key == 'dipoles':\n self.dipoles = P.YamboDipolesParse... | <|body_start_0|>
if 'output' in results:
self.data = P.YamboOutputParser(results['output'], verbose=verbose, extendOut=extendOut)
else:
print('There are no o-* files in the %s dictionary. Please check...' % results)
for key, value in results.items():
if key ==... | Class that perform the parsing starting from the results :py:class:`dict` built by the :class:`YamboCalculator` class. In the actual implementation of the class the parser is able to deal with the o- files, the dipoles database, the ``ndb.RT_G_PAR`` and the ``ns.db1`` database written in the SAVE folder. Args: results ... | YamboParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YamboParser:
"""Class that perform the parsing starting from the results :py:class:`dict` built by the :class:`YamboCalculator` class. In the actual implementation of the class the parser is able to deal with the o- files, the dipoles database, the ``ndb.RT_G_PAR`` and the ``ns.db1`` database wri... | stack_v2_sparse_classes_10k_train_001217 | 4,923 | permissive | [
{
"docstring": "Initialize the data member of the class.",
"name": "__init__",
"signature": "def __init__(self, results, verbose=False, extendOut=True)"
},
{
"docstring": "Init the a :class:`YamboParser` instance using the 'o-' files found inside the outputPath, the ``ns.db1`` database in the SA... | 3 | stack_v2_sparse_classes_30k_train_006942 | Implement the Python class `YamboParser` described below.
Class description:
Class that perform the parsing starting from the results :py:class:`dict` built by the :class:`YamboCalculator` class. In the actual implementation of the class the parser is able to deal with the o- files, the dipoles database, the ``ndb.RT_... | Implement the Python class `YamboParser` described below.
Class description:
Class that perform the parsing starting from the results :py:class:`dict` built by the :class:`YamboCalculator` class. In the actual implementation of the class the parser is able to deal with the o- files, the dipoles database, the ``ndb.RT_... | 6ddac37ce8da1c7e1e0291cc5e49591a0e230389 | <|skeleton|>
class YamboParser:
"""Class that perform the parsing starting from the results :py:class:`dict` built by the :class:`YamboCalculator` class. In the actual implementation of the class the parser is able to deal with the o- files, the dipoles database, the ``ndb.RT_G_PAR`` and the ``ns.db1`` database wri... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class YamboParser:
"""Class that perform the parsing starting from the results :py:class:`dict` built by the :class:`YamboCalculator` class. In the actual implementation of the class the parser is able to deal with the o- files, the dipoles database, the ``ndb.RT_G_PAR`` and the ``ns.db1`` database written in the S... | the_stack_v2_python_sparse | mppi/Parsers/YamboParser.py | marcodalessandro76/MPPI | train | 1 |
1404d761efab744c4f0a44dacc0f55e9ff39dd05 | [
"if kwargs.get('units', None):\n kwargs['units'] = UNITS[kwargs['units']]\nsuper(IPerfParser, self).__init__(*args, **kwargs)\nself.format = iperfexpressions.ParserKeys.human",
"results = []\nfor line in output.splitlines():\n match = self.search(line)\n if match:\n start = float(match[iperfexpres... | <|body_start_0|>
if kwargs.get('units', None):
kwargs['units'] = UNITS[kwargs['units']]
super(IPerfParser, self).__init__(*args, **kwargs)
self.format = iperfexpressions.ParserKeys.human
<|end_body_0|>
<|body_start_1|>
results = []
for line in output.splitlines():
... | Class for parsing Iperf output. | IPerfParser | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IPerfParser:
"""Class for parsing Iperf output."""
def __init__(self, *args, **kwargs):
"""Initialize IPerfParser class."""
<|body_0|>
def parse(self, output):
"""Parse output from iperf execution. Args: output(str): iperf output Returns: list: list of parsed ipe... | stack_v2_sparse_classes_10k_train_001218 | 4,769 | permissive | [
{
"docstring": "Initialize IPerfParser class.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Parse output from iperf execution. Args: output(str): iperf output Returns: list: list of parsed iperf results",
"name": "parse",
"signature": "def pa... | 2 | stack_v2_sparse_classes_30k_train_000385 | Implement the Python class `IPerfParser` described below.
Class description:
Class for parsing Iperf output.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize IPerfParser class.
- def parse(self, output): Parse output from iperf execution. Args: output(str): iperf output Returns: lis... | Implement the Python class `IPerfParser` described below.
Class description:
Class for parsing Iperf output.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize IPerfParser class.
- def parse(self, output): Parse output from iperf execution. Args: output(str): iperf output Returns: lis... | 2007bf3fe66edfe704e485141c55caed54fe13aa | <|skeleton|>
class IPerfParser:
"""Class for parsing Iperf output."""
def __init__(self, *args, **kwargs):
"""Initialize IPerfParser class."""
<|body_0|>
def parse(self, output):
"""Parse output from iperf execution. Args: output(str): iperf output Returns: list: list of parsed ipe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IPerfParser:
"""Class for parsing Iperf output."""
def __init__(self, *args, **kwargs):
"""Initialize IPerfParser class."""
if kwargs.get('units', None):
kwargs['units'] = UNITS[kwargs['units']]
super(IPerfParser, self).__init__(*args, **kwargs)
self.format = i... | the_stack_v2_python_sparse | taf/testlib/linux/iperf/iperf.py | AndriyZabavskyy/taf | train | 0 |
4e5482a04ac19e211e8a7243b39d011b11e367f1 | [
"nginx_conf = self.GenerateNginxConfig(umpire_config, env)\nif not nginx_conf:\n return []\nproc_config = {'executable': HTTP_BIN, 'name': HTTP_SERVICE_NAME, 'args': ['-c', nginx_conf], 'path': '/tmp'}\nproc = umpire_service.ServiceProcess(self)\nproc.SetConfig(proc_config)\nreturn [proc]",
"if 'services' not ... | <|body_start_0|>
nginx_conf = self.GenerateNginxConfig(umpire_config, env)
if not nginx_conf:
return []
proc_config = {'executable': HTTP_BIN, 'name': HTTP_SERVICE_NAME, 'args': ['-c', nginx_conf], 'path': '/tmp'}
proc = umpire_service.ServiceProcess(self)
proc.SetCon... | HTTP service. Example: svc = SimpleService() procs = svc.CreateProcesses(umpire_config_dict) svc.Start(procs) | HTTPService | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTTPService:
"""HTTP service. Example: svc = SimpleService() procs = svc.CreateProcesses(umpire_config_dict) svc.Start(procs)"""
def CreateProcesses(self, umpire_config, env):
"""Creates list of processes via config. Args: umpire_config: Umpire config dict. env: UmpireEnv object. Ret... | stack_v2_sparse_classes_10k_train_001219 | 6,432 | permissive | [
{
"docstring": "Creates list of processes via config. Args: umpire_config: Umpire config dict. env: UmpireEnv object. Returns: A list of ServiceProcess.",
"name": "CreateProcesses",
"signature": "def CreateProcesses(self, umpire_config, env)"
},
{
"docstring": "Generates a nginx config. Args: um... | 3 | stack_v2_sparse_classes_30k_train_000791 | Implement the Python class `HTTPService` described below.
Class description:
HTTP service. Example: svc = SimpleService() procs = svc.CreateProcesses(umpire_config_dict) svc.Start(procs)
Method signatures and docstrings:
- def CreateProcesses(self, umpire_config, env): Creates list of processes via config. Args: umpi... | Implement the Python class `HTTPService` described below.
Class description:
HTTP service. Example: svc = SimpleService() procs = svc.CreateProcesses(umpire_config_dict) svc.Start(procs)
Method signatures and docstrings:
- def CreateProcesses(self, umpire_config, env): Creates list of processes via config. Args: umpi... | a1b0fccd68987d8cd9c89710adc3c04b868347ec | <|skeleton|>
class HTTPService:
"""HTTP service. Example: svc = SimpleService() procs = svc.CreateProcesses(umpire_config_dict) svc.Start(procs)"""
def CreateProcesses(self, umpire_config, env):
"""Creates list of processes via config. Args: umpire_config: Umpire config dict. env: UmpireEnv object. Ret... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HTTPService:
"""HTTP service. Example: svc = SimpleService() procs = svc.CreateProcesses(umpire_config_dict) svc.Start(procs)"""
def CreateProcesses(self, umpire_config, env):
"""Creates list of processes via config. Args: umpire_config: Umpire config dict. env: UmpireEnv object. Returns: A list ... | the_stack_v2_python_sparse | py/umpire/server/service/umpire_http.py | bridder/factory | train | 0 |
55a7236e91d68b4fea2ab75fa0ca764aeff6c166 | [
"self.audio_type = audio_type\nself.audio_format = audio_format\nif audio_type in SERIALIZABLE_AUDIO_TYPES:\n self.audio = raw_data if isinstance(raw_data, io.BytesIO) else io.BytesIO(raw_data)\n self.duration = read_duration(audio_type, self.audio)\nelse:\n self.audio = raw_data\n if self.audio_format ... | <|body_start_0|>
self.audio_type = audio_type
self.audio_format = audio_format
if audio_type in SERIALIZABLE_AUDIO_TYPES:
self.audio = raw_data if isinstance(raw_data, io.BytesIO) else io.BytesIO(raw_data)
self.duration = read_duration(audio_type, self.audio)
else... | Represents in-memory audio data of a certain (convertible) representation. Attributes: audio_type (str): See `__init__`. audio_format (tuple:(int, int, int)): See `__init__`. audio (obj): Audio data represented as indicated by `audio_type` duration (float): Audio duration of the sample in seconds | Sample | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"CC-BY-4.0",
"CC-BY-SA-3.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sample:
"""Represents in-memory audio data of a certain (convertible) representation. Attributes: audio_type (str): See `__init__`. audio_format (tuple:(int, int, int)): See `__init__`. audio (obj): Audio data represented as indicated by `audio_type` duration (float): Audio duration of the sample... | stack_v2_sparse_classes_10k_train_001220 | 15,981 | permissive | [
{
"docstring": "Creates a Sample from a raw audio representation. :param audio_type: Audio data representation type CSupported types: - AUDIO_TYPE_OPUS: Memory file representation (BytesIO) of Opus encoded audio wrapped by a custom container format (used in SDBs) - AUDIO_TYPE_WAV: Memory file representation (By... | 2 | stack_v2_sparse_classes_30k_train_001094 | Implement the Python class `Sample` described below.
Class description:
Represents in-memory audio data of a certain (convertible) representation. Attributes: audio_type (str): See `__init__`. audio_format (tuple:(int, int, int)): See `__init__`. audio (obj): Audio data represented as indicated by `audio_type` duratio... | Implement the Python class `Sample` described below.
Class description:
Represents in-memory audio data of a certain (convertible) representation. Attributes: audio_type (str): See `__init__`. audio_format (tuple:(int, int, int)): See `__init__`. audio (obj): Audio data represented as indicated by `audio_type` duratio... | 93c4a42c95cd610c76dbd98de480dbb21f484c31 | <|skeleton|>
class Sample:
"""Represents in-memory audio data of a certain (convertible) representation. Attributes: audio_type (str): See `__init__`. audio_format (tuple:(int, int, int)): See `__init__`. audio (obj): Audio data represented as indicated by `audio_type` duration (float): Audio duration of the sample... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Sample:
"""Represents in-memory audio data of a certain (convertible) representation. Attributes: audio_type (str): See `__init__`. audio_format (tuple:(int, int, int)): See `__init__`. audio (obj): Audio data represented as indicated by `audio_type` duration (float): Audio duration of the sample in seconds""... | the_stack_v2_python_sparse | galvasr2/align/audio.py | Ciroye/peoples-speech | train | 0 |
171aff9e6483768a821a2bfa7a0eceafcb83882d | [
"if n <= 0:\n raise ValueError('n must be a positive value')\nif p < 0 or p > 1:\n raise ValueError('p must be greater than 0 and less than 1')\nself.n = int(n)\nself.p = float(p)\nif data is None:\n self.n = self.n\n self.p = self.p\nelse:\n if type(data) is not list:\n raise TypeError('data ... | <|body_start_0|>
if n <= 0:
raise ValueError('n must be a positive value')
if p < 0 or p > 1:
raise ValueError('p must be greater than 0 and less than 1')
self.n = int(n)
self.p = float(p)
if data is None:
self.n = self.n
self.p = s... | represents a binomial distribution | Binomial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Binomial:
"""represents a binomial distribution"""
def __init__(self, data=None, n=1, p=0.5):
"""Binomial contructor"""
<|body_0|>
def pmf(self, k):
"""Calculates the value of the PMF for a given number"""
<|body_1|>
def cdf(self, k):
"""Calc... | stack_v2_sparse_classes_10k_train_001221 | 1,886 | no_license | [
{
"docstring": "Binomial contructor",
"name": "__init__",
"signature": "def __init__(self, data=None, n=1, p=0.5)"
},
{
"docstring": "Calculates the value of the PMF for a given number",
"name": "pmf",
"signature": "def pmf(self, k)"
},
{
"docstring": "Calculates the value of the... | 3 | stack_v2_sparse_classes_30k_train_002294 | Implement the Python class `Binomial` described below.
Class description:
represents a binomial distribution
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): Binomial contructor
- def pmf(self, k): Calculates the value of the PMF for a given number
- def cdf(self, k): Calculates the valu... | Implement the Python class `Binomial` described below.
Class description:
represents a binomial distribution
Method signatures and docstrings:
- def __init__(self, data=None, n=1, p=0.5): Binomial contructor
- def pmf(self, k): Calculates the value of the PMF for a given number
- def cdf(self, k): Calculates the valu... | 4adb0b69ab12ebeec08b1cf603e5c738378f6806 | <|skeleton|>
class Binomial:
"""represents a binomial distribution"""
def __init__(self, data=None, n=1, p=0.5):
"""Binomial contructor"""
<|body_0|>
def pmf(self, k):
"""Calculates the value of the PMF for a given number"""
<|body_1|>
def cdf(self, k):
"""Calc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Binomial:
"""represents a binomial distribution"""
def __init__(self, data=None, n=1, p=0.5):
"""Binomial contructor"""
if n <= 0:
raise ValueError('n must be a positive value')
if p < 0 or p > 1:
raise ValueError('p must be greater than 0 and less than 1')... | the_stack_v2_python_sparse | math/0x03-probability/binomial.py | Jdavp/holbertonschool-machine_learning | train | 0 |
9952f694bb8ef912ef3ce1c4e089c40a803fd9f5 | [
"Parametre.__init__(self, 'voir', 'view')\nself.schema = '<cle>'\nself.aide_courte = \"affiche le détail d'un cap\"\nself.aide_longue = \"Cette commande permet d'obtenir plus d'informations sur un cap maritime : son point de départ, ses points intermédiaires et son point d'arrivée.\"",
"cle = dic_masques['cle'].c... | <|body_start_0|>
Parametre.__init__(self, 'voir', 'view')
self.schema = '<cle>'
self.aide_courte = "affiche le détail d'un cap"
self.aide_longue = "Cette commande permet d'obtenir plus d'informations sur un cap maritime : son point de départ, ses points intermédiaires et son point d'arri... | Commande 'cap voir'. | PrmVoir | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmVoir:
"""Commande 'cap voir'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Parametre.__init__(... | stack_v2_sparse_classes_10k_train_001222 | 3,921 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | null | Implement the Python class `PrmVoir` described below.
Class description:
Commande 'cap voir'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmVoir` described below.
Class description:
Commande 'cap voir'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmVoir:
"""Commande 'cap voir'."""
... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmVoir:
"""Commande 'cap voir'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrmVoir:
"""Commande 'cap voir'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'voir', 'view')
self.schema = '<cle>'
self.aide_courte = "affiche le détail d'un cap"
self.aide_longue = "Cette commande permet d'obtenir plus d'informa... | the_stack_v2_python_sparse | src/secondaires/navigation/commandes/cap/voir.py | vincent-lg/tsunami | train | 5 |
031c1d960d11127c13f1f2bc7b4f5bf4f6917765 | [
"super(Network, self).__init__()\nself.seed = torch.manual_seed(seed)\n'*** YOUR CODE HERE ***'\nfeature_size = 64\nself.feature_layer = nn.Sequential(nn.Linear(state_size, feature_size), nn.ReLU())\nvalue_size = 64\nself.value_layer = nn.Sequential(nn.Linear(feature_size, value_size), nn.ReLU(), nn.Linear(value_si... | <|body_start_0|>
super(Network, self).__init__()
self.seed = torch.manual_seed(seed)
'*** YOUR CODE HERE ***'
feature_size = 64
self.feature_layer = nn.Sequential(nn.Linear(state_size, feature_size), nn.ReLU())
value_size = 64
self.value_layer = nn.Sequential(nn.L... | Actor (Policy) Model. | Network | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Network:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
<|body_0|>
def... | stack_v2_sparse_classes_10k_train_001223 | 1,441 | permissive | [
{
"docstring": "Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed",
"name": "__init__",
"signature": "def __init__(self, state_size, action_size, seed)"
},
{
"docstring": "Build a net... | 2 | stack_v2_sparse_classes_30k_train_000418 | Implement the Python class `Network` described below.
Class description:
Actor (Policy) Model.
Method signatures and docstrings:
- def __init__(self, state_size, action_size, seed): Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each acti... | Implement the Python class `Network` described below.
Class description:
Actor (Policy) Model.
Method signatures and docstrings:
- def __init__(self, state_size, action_size, seed): Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each acti... | 9b1653b7aedeb4dc0e4aab9351cc4a7f4ccb4f32 | <|skeleton|>
class Network:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
<|body_0|>
def... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Network:
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model. Params ====== state_size (int): Dimension of each state action_size (int): Dimension of each action seed (int): Random seed"""
super(Network, self).__init__()
... | the_stack_v2_python_sparse | p1_navigation/dueling_network.py | weicheng113/deep-reinforcement-learning | train | 0 |
ad0d27e392f0368fbf41bf4a4c80c9d7d7917a9c | [
"if not nums:\n return 0\nsums = [0] * len(nums)\nsums[0] = nums[0]\nres = sums[0]\nfor i in range(1, len(nums)):\n sums[i] = sums[i - 1] + nums[i] if sums[i - 1] > 0 else nums[i]\n res = max(sums[i], res)\nreturn res",
"localMaxSum, globalMaxSum = (nums[0], nums[0])\nfor i in range(1, len(nums)):\n l... | <|body_start_0|>
if not nums:
return 0
sums = [0] * len(nums)
sums[0] = nums[0]
res = sums[0]
for i in range(1, len(nums)):
sums[i] = sums[i - 1] + nums[i] if sums[i - 1] > 0 else nums[i]
res = max(sums[i], res)
return res
<|end_body_0|... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return 0
su... | stack_v2_sparse_classes_10k_train_001224 | 1,509 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray2",
"signature": "def maxSubArray2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007176 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxSubArra... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 0
sums = [0] * len(nums)
sums[0] = nums[0]
res = sums[0]
for i in range(1, len(nums)):
sums[i] = sums[i - 1] + nums[i] if sums[i - 1] > 0 e... | the_stack_v2_python_sparse | M/MaximumSubarray.py | bssrdf/pyleet | train | 2 | |
2fa1d40dd1b9ac75816c7b9fd3aaab5657ace752 | [
"super().__init__()\nself.visual = visual\nself.hidden = hidden\nself.n_layers = n_layers\nself.attn_heads = attn_heads\nself.feed_forward_hidden = hidden * 2\nself.token_embedding = TokenEmbedding(vocab_size=vocab_size, embed_size=hidden)\nself.relation_embedding = RelationEmbedding(hidden, max_relative_1d_positio... | <|body_start_0|>
super().__init__()
self.visual = visual
self.hidden = hidden
self.n_layers = n_layers
self.attn_heads = attn_heads
self.feed_forward_hidden = hidden * 2
self.token_embedding = TokenEmbedding(vocab_size=vocab_size, embed_size=hidden)
self.r... | Language Model for proteins | ProEncoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProEncoder:
"""Language Model for proteins"""
def __init__(self, vocab_size, hidden=512, n_layers=5, attn_heads=1, dropout=0.0, max_relative_1d_positions=300, visual=False):
""":param vocab_size: vocab_size of total words :param hidden: BERT model hidden size :param n_layers: numbers... | stack_v2_sparse_classes_10k_train_001225 | 9,053 | no_license | [
{
"docstring": ":param vocab_size: vocab_size of total words :param hidden: BERT model hidden size :param n_layers: numbers of Transformer blocks(layers) :param attn_heads: number of attention heads :param dropout: dropout rate",
"name": "__init__",
"signature": "def __init__(self, vocab_size, hidden=51... | 2 | stack_v2_sparse_classes_30k_train_004328 | Implement the Python class `ProEncoder` described below.
Class description:
Language Model for proteins
Method signatures and docstrings:
- def __init__(self, vocab_size, hidden=512, n_layers=5, attn_heads=1, dropout=0.0, max_relative_1d_positions=300, visual=False): :param vocab_size: vocab_size of total words :para... | Implement the Python class `ProEncoder` described below.
Class description:
Language Model for proteins
Method signatures and docstrings:
- def __init__(self, vocab_size, hidden=512, n_layers=5, attn_heads=1, dropout=0.0, max_relative_1d_positions=300, visual=False): :param vocab_size: vocab_size of total words :para... | 51b03ad1426794704027e0bc6658aae5d55a6e90 | <|skeleton|>
class ProEncoder:
"""Language Model for proteins"""
def __init__(self, vocab_size, hidden=512, n_layers=5, attn_heads=1, dropout=0.0, max_relative_1d_positions=300, visual=False):
""":param vocab_size: vocab_size of total words :param hidden: BERT model hidden size :param n_layers: numbers... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProEncoder:
"""Language Model for proteins"""
def __init__(self, vocab_size, hidden=512, n_layers=5, attn_heads=1, dropout=0.0, max_relative_1d_positions=300, visual=False):
""":param vocab_size: vocab_size of total words :param hidden: BERT model hidden size :param n_layers: numbers of Transform... | the_stack_v2_python_sparse | model/prolm_relative.py | lahplover/unippi | train | 1 |
2704c06c675e5399e382153e58b1c61b38180c88 | [
"self.sleeptime = sleep_param\nself.looplimit = looplimit\nself.temperatureTask = TempSensorEmulatorTask.TempSensorEmulator()",
"i = 0\nif self.sleeptime < 0 or self.looplimit < 0:\n logging.error('looplimit or sleeptime is less than 0')\n return False\nif self.enableTempEmulatorAdapter == True:\n while ... | <|body_start_0|>
self.sleeptime = sleep_param
self.looplimit = looplimit
self.temperatureTask = TempSensorEmulatorTask.TempSensorEmulator()
<|end_body_0|>
<|body_start_1|>
i = 0
if self.sleeptime < 0 or self.looplimit < 0:
logging.error('looplimit or sleeptime is les... | This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations | TempEmulatorAdapter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempEmulatorAdapter:
"""This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations"""
def __init__(self, sleep_param=sleepDefault, looplimit=loopDefault):
"""Constructor which sets... | stack_v2_sparse_classes_10k_train_001226 | 1,894 | no_license | [
{
"docstring": "Constructor which sets the sleep timer for the thread, and a looplimit if needed.",
"name": "__init__",
"signature": "def __init__(self, sleep_param=sleepDefault, looplimit=loopDefault)"
},
{
"docstring": "This method runs the emulation if enableTempEmulatorAdapter is set to True... | 2 | stack_v2_sparse_classes_30k_train_006419 | Implement the Python class `TempEmulatorAdapter` described below.
Class description:
This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations
Method signatures and docstrings:
- def __init__(self, sleep_param=sle... | Implement the Python class `TempEmulatorAdapter` described below.
Class description:
This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations
Method signatures and docstrings:
- def __init__(self, sleep_param=sle... | dfd5fd8c757cae8b1306ae3e4eb2cfc9bf124fee | <|skeleton|>
class TempEmulatorAdapter:
"""This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations"""
def __init__(self, sleep_param=sleepDefault, looplimit=loopDefault):
"""Constructor which sets... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TempEmulatorAdapter:
"""This class is responsible for running the temperature generation emulator Has inputs like the sleeptimer and looplimit so we can control the running of iterations"""
def __init__(self, sleep_param=sleepDefault, looplimit=loopDefault):
"""Constructor which sets the sleep ti... | the_stack_v2_python_sparse | apps/labs/module02/TempEmulatorAdapter.py | mnk400/iot-device | train | 0 |
88d165f5fc315b95204ac15beefffaee1f79a6dd | [
"collateral = {'collateralId': self.id, 'addedDateTime': ''}\nif self.status and self.status == STATUS_ADDED:\n collateral['descriptionAdd'] = self.description\nelif self.status and self.status == STATUS_DELETED:\n collateral['descriptionDelete'] = self.description\nelse:\n collateral['description'] = self... | <|body_start_0|>
collateral = {'collateralId': self.id, 'addedDateTime': ''}
if self.status and self.status == STATUS_ADDED:
collateral['descriptionAdd'] = self.description
elif self.status and self.status == STATUS_DELETED:
collateral['descriptionDelete'] = self.descript... | This class manages all of the legacy application general collateral information. | GeneralCollateralLegacy | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneralCollateralLegacy:
"""This class manages all of the legacy application general collateral information."""
def current_json(self) -> dict:
"""Generate a Financing Statement current view of the general collateral as json/dict."""
<|body_0|>
def json(self) -> dict:
... | stack_v2_sparse_classes_10k_train_001227 | 4,718 | permissive | [
{
"docstring": "Generate a Financing Statement current view of the general collateral as json/dict.",
"name": "current_json",
"signature": "def current_json(self) -> dict"
},
{
"docstring": "Generate the default view of the general collateral as json/a dict.",
"name": "json",
"signature"... | 5 | stack_v2_sparse_classes_30k_train_004467 | Implement the Python class `GeneralCollateralLegacy` described below.
Class description:
This class manages all of the legacy application general collateral information.
Method signatures and docstrings:
- def current_json(self) -> dict: Generate a Financing Statement current view of the general collateral as json/di... | Implement the Python class `GeneralCollateralLegacy` described below.
Class description:
This class manages all of the legacy application general collateral information.
Method signatures and docstrings:
- def current_json(self) -> dict: Generate a Financing Statement current view of the general collateral as json/di... | af1a4458bb78c16ecca484514d4bd0d1d8c24b5d | <|skeleton|>
class GeneralCollateralLegacy:
"""This class manages all of the legacy application general collateral information."""
def current_json(self) -> dict:
"""Generate a Financing Statement current view of the general collateral as json/dict."""
<|body_0|>
def json(self) -> dict:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GeneralCollateralLegacy:
"""This class manages all of the legacy application general collateral information."""
def current_json(self) -> dict:
"""Generate a Financing Statement current view of the general collateral as json/dict."""
collateral = {'collateralId': self.id, 'addedDateTime':... | the_stack_v2_python_sparse | ppr-api/src/ppr_api/models/general_collateral_legacy.py | bcgov/ppr | train | 4 |
595216bae5a4661f03cce2a802de9cd329219ad5 | [
"super(AddFlyerDatesForm, self).__init__(*args, **kwargs)\nif checked_data:\n self.fields['subdivision_consumer_count'].initial = checked_data.get('subdivision_consumer_count', 0)\nelse:\n self.fields['subdivision_consumer_count'].initial = subdivision_consumer_count\nfor flyer_month in available_flyer_dates_... | <|body_start_0|>
super(AddFlyerDatesForm, self).__init__(*args, **kwargs)
if checked_data:
self.fields['subdivision_consumer_count'].initial = checked_data.get('subdivision_consumer_count', 0)
else:
self.fields['subdivision_consumer_count'].initial = subdivision_consumer_... | The Add Flyer Dates Form. | AddFlyerDatesForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddFlyerDatesForm:
"""The Add Flyer Dates Form."""
def __init__(self, available_flyer_dates_list, subdivision_consumer_count=None, checked_data=None, *args, **kwargs):
"""Dynamically create 10 sets of location fields."""
<|body_0|>
def clean_dynamic_fields(self, post_dat... | stack_v2_sparse_classes_10k_train_001228 | 27,686 | no_license | [
{
"docstring": "Dynamically create 10 sets of location fields.",
"name": "__init__",
"signature": "def __init__(self, available_flyer_dates_list, subdivision_consumer_count=None, checked_data=None, *args, **kwargs)"
},
{
"docstring": "Clean method for this form.",
"name": "clean_dynamic_fiel... | 3 | null | Implement the Python class `AddFlyerDatesForm` described below.
Class description:
The Add Flyer Dates Form.
Method signatures and docstrings:
- def __init__(self, available_flyer_dates_list, subdivision_consumer_count=None, checked_data=None, *args, **kwargs): Dynamically create 10 sets of location fields.
- def cle... | Implement the Python class `AddFlyerDatesForm` described below.
Class description:
The Add Flyer Dates Form.
Method signatures and docstrings:
- def __init__(self, available_flyer_dates_list, subdivision_consumer_count=None, checked_data=None, *args, **kwargs): Dynamically create 10 sets of location fields.
- def cle... | a780ccdc3350d4b5c7990c65d1af8d71060c62cc | <|skeleton|>
class AddFlyerDatesForm:
"""The Add Flyer Dates Form."""
def __init__(self, available_flyer_dates_list, subdivision_consumer_count=None, checked_data=None, *args, **kwargs):
"""Dynamically create 10 sets of location fields."""
<|body_0|>
def clean_dynamic_fields(self, post_dat... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddFlyerDatesForm:
"""The Add Flyer Dates Form."""
def __init__(self, available_flyer_dates_list, subdivision_consumer_count=None, checked_data=None, *args, **kwargs):
"""Dynamically create 10 sets of location fields."""
super(AddFlyerDatesForm, self).__init__(*args, **kwargs)
if ... | the_stack_v2_python_sparse | coupon/forms.py | wcirillo/ten | train | 0 |
cb9fe1aa66539a3e7f70b36de15de47f2ed19484 | [
"minutes_spent = previous_request_time.total_minutes()\nif minutes_spent == 0:\n self._current_range = self.DEFAULT_RANGE_DAYS\nelse:\n days_per_minute = self._current_range / minutes_spent\n next_range = math.floor(days_per_minute / self.REQUEST_PER_MINUTE_LIMIT)\n self._current_range = min(next_range ... | <|body_start_0|>
minutes_spent = previous_request_time.total_minutes()
if minutes_spent == 0:
self._current_range = self.DEFAULT_RANGE_DAYS
else:
days_per_minute = self._current_range / minutes_spent
next_range = math.floor(days_per_minute / self.REQUEST_PER_M... | Generate slices from start_date up to current date. Every next slice could have different range based on was the previous slice processed successfully and how much time it took. The alghorithm is following: 1. First slice have INITIAL_RANGE_DAYS (30 days) length. 2. When slice is processed by stream this class expect "... | AdjustableSliceGenerator | [
"MIT",
"Elastic-2.0",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdjustableSliceGenerator:
"""Generate slices from start_date up to current date. Every next slice could have different range based on was the previous slice processed successfully and how much time it took. The alghorithm is following: 1. First slice have INITIAL_RANGE_DAYS (30 days) length. 2. W... | stack_v2_sparse_classes_10k_train_001229 | 6,343 | permissive | [
{
"docstring": "Calculate next slice length in days based on previous slice length and processing time.",
"name": "adjust_range",
"signature": "def adjust_range(self, previous_request_time: Period)"
},
{
"docstring": "This method is supposed to be called when slice processing failed. Reset next ... | 3 | stack_v2_sparse_classes_30k_train_002562 | Implement the Python class `AdjustableSliceGenerator` described below.
Class description:
Generate slices from start_date up to current date. Every next slice could have different range based on was the previous slice processed successfully and how much time it took. The alghorithm is following: 1. First slice have IN... | Implement the Python class `AdjustableSliceGenerator` described below.
Class description:
Generate slices from start_date up to current date. Every next slice could have different range based on was the previous slice processed successfully and how much time it took. The alghorithm is following: 1. First slice have IN... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class AdjustableSliceGenerator:
"""Generate slices from start_date up to current date. Every next slice could have different range based on was the previous slice processed successfully and how much time it took. The alghorithm is following: 1. First slice have INITIAL_RANGE_DAYS (30 days) length. 2. W... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AdjustableSliceGenerator:
"""Generate slices from start_date up to current date. Every next slice could have different range based on was the previous slice processed successfully and how much time it took. The alghorithm is following: 1. First slice have INITIAL_RANGE_DAYS (30 days) length. 2. When slice is ... | the_stack_v2_python_sparse | dts/airbyte/airbyte-integrations/connectors/source-iterable/source_iterable/slice_generators.py | alldatacenter/alldata | train | 774 |
40d4c959dfab70ff3362e055e620a0eaa5c21411 | [
"if do_generate:\n self.game_map = self.generate(size)\nelse:\n self.game_map = []",
"trap_count = int(size ** 2 / RATIO_TRAPS)\ntreasure_count = int(size ** 2 / RATIO_TREASURE)\nif trap_count <= 0:\n raise MapInitError('Error initializing trap count. Try larger map size.')\nif treasure_count < config.PL... | <|body_start_0|>
if do_generate:
self.game_map = self.generate(size)
else:
self.game_map = []
<|end_body_0|>
<|body_start_1|>
trap_count = int(size ** 2 / RATIO_TRAPS)
treasure_count = int(size ** 2 / RATIO_TREASURE)
if trap_count <= 0:
raise ... | DungeonMap | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DungeonMap:
def __init__(self, size, do_generate=True):
"""Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation"""
<|body_0|>
def generate(self, size):
"""Generates map for Dungeon Game :param size: Map square size ... | stack_v2_sparse_classes_10k_train_001230 | 5,735 | permissive | [
{
"docstring": "Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation",
"name": "__init__",
"signature": "def __init__(self, size, do_generate=True)"
},
{
"docstring": "Generates map for Dungeon Game :param size: Map square size :return: None",
... | 6 | stack_v2_sparse_classes_30k_train_002082 | Implement the Python class `DungeonMap` described below.
Class description:
Implement the DungeonMap class.
Method signatures and docstrings:
- def __init__(self, size, do_generate=True): Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation
- def generate(self, size... | Implement the Python class `DungeonMap` described below.
Class description:
Implement the DungeonMap class.
Method signatures and docstrings:
- def __init__(self, size, do_generate=True): Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation
- def generate(self, size... | 291592e97b6d8fe9f9e6627dc0023875918d3463 | <|skeleton|>
class DungeonMap:
def __init__(self, size, do_generate=True):
"""Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation"""
<|body_0|>
def generate(self, size):
"""Generates map for Dungeon Game :param size: Map square size ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DungeonMap:
def __init__(self, size, do_generate=True):
"""Class constructor :param size: Generated map size :param do_generate: Whether to initiate map generation"""
if do_generate:
self.game_map = self.generate(size)
else:
self.game_map = []
def generate(... | the_stack_v2_python_sparse | Kyrylo_Yeremenko/10/dungeon_game/dungeon_map.py | SmischenkoB/campus_2018_python | train | 0 | |
c7d4d9c555f6a4d6ea6c1d92f47256ba6f4e935d | [
"self.mode = mode\nself.ids_rulesets = ids_rulesets\nself.protected_networks = protected_networks",
"if dictionary is None:\n return None\nmode = dictionary.get('mode')\nids_rulesets = dictionary.get('idsRulesets')\nprotected_networks = meraki_sdk.models.protected_networks_model.ProtectedNetworksModel.from_dic... | <|body_start_0|>
self.mode = mode
self.ids_rulesets = ids_rulesets
self.protected_networks = protected_networks
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
mode = dictionary.get('mode')
ids_rulesets = dictionary.get('idsRulesets')
... | Implementation of the 'updateNetworkSecurityIntrusionSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'disabled'/'detection'/'prevention' (optional - omitting will leave current config unchanged) ids_rulesets (string): Set the detection ruleset 'connectivity'/'balanced'/'securi... | UpdateNetworkSecurityIntrusionSettingsModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkSecurityIntrusionSettingsModel:
"""Implementation of the 'updateNetworkSecurityIntrusionSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'disabled'/'detection'/'prevention' (optional - omitting will leave current config unchanged) ids_ruleset... | stack_v2_sparse_classes_10k_train_001231 | 2,701 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkSecurityIntrusionSettingsModel class",
"name": "__init__",
"signature": "def __init__(self, mode=None, ids_rulesets=None, protected_networks=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary... | 2 | null | Implement the Python class `UpdateNetworkSecurityIntrusionSettingsModel` described below.
Class description:
Implementation of the 'updateNetworkSecurityIntrusionSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'disabled'/'detection'/'prevention' (optional - omitting will leav... | Implement the Python class `UpdateNetworkSecurityIntrusionSettingsModel` described below.
Class description:
Implementation of the 'updateNetworkSecurityIntrusionSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'disabled'/'detection'/'prevention' (optional - omitting will leav... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkSecurityIntrusionSettingsModel:
"""Implementation of the 'updateNetworkSecurityIntrusionSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'disabled'/'detection'/'prevention' (optional - omitting will leave current config unchanged) ids_ruleset... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateNetworkSecurityIntrusionSettingsModel:
"""Implementation of the 'updateNetworkSecurityIntrusionSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'disabled'/'detection'/'prevention' (optional - omitting will leave current config unchanged) ids_rulesets (string): S... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_security_intrusion_settings_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
77ea59edc75bc37bbb84ebc9e8b4a6a458150b94 | [
"name = read_unicode_string(fp)\nclassID = read_length_and_key(fp)\nkeyID = read_length_and_key(fp)\nreturn cls(name, classID, keyID)",
"written = write_unicode_string(fp, self.name)\nwritten += write_length_and_key(fp, self.classID)\nwritten += write_length_and_key(fp, self.keyID)\nreturn written"
] | <|body_start_0|>
name = read_unicode_string(fp)
classID = read_length_and_key(fp)
keyID = read_length_and_key(fp)
return cls(name, classID, keyID)
<|end_body_0|>
<|body_start_1|>
written = write_unicode_string(fp, self.name)
written += write_length_and_key(fp, self.class... | Property structure. .. py:attribute:: name | Property | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Property:
"""Property structure. .. py:attribute:: name"""
def read(cls, fp):
"""Read the element from a file-like object. :param fp: file-like object"""
<|body_0|>
def write(self, fp):
"""Write the element to a file-like object. :param fp: file-like object"""
... | stack_v2_sparse_classes_10k_train_001232 | 19,890 | permissive | [
{
"docstring": "Read the element from a file-like object. :param fp: file-like object",
"name": "read",
"signature": "def read(cls, fp)"
},
{
"docstring": "Write the element to a file-like object. :param fp: file-like object",
"name": "write",
"signature": "def write(self, fp)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005542 | Implement the Python class `Property` described below.
Class description:
Property structure. .. py:attribute:: name
Method signatures and docstrings:
- def read(cls, fp): Read the element from a file-like object. :param fp: file-like object
- def write(self, fp): Write the element to a file-like object. :param fp: f... | Implement the Python class `Property` described below.
Class description:
Property structure. .. py:attribute:: name
Method signatures and docstrings:
- def read(cls, fp): Read the element from a file-like object. :param fp: file-like object
- def write(self, fp): Write the element to a file-like object. :param fp: f... | 0e3ac5b64061c7eb87c6eeacce4b9792d1f479b5 | <|skeleton|>
class Property:
"""Property structure. .. py:attribute:: name"""
def read(cls, fp):
"""Read the element from a file-like object. :param fp: file-like object"""
<|body_0|>
def write(self, fp):
"""Write the element to a file-like object. :param fp: file-like object"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Property:
"""Property structure. .. py:attribute:: name"""
def read(cls, fp):
"""Read the element from a file-like object. :param fp: file-like object"""
name = read_unicode_string(fp)
classID = read_length_and_key(fp)
keyID = read_length_and_key(fp)
return cls(nam... | the_stack_v2_python_sparse | psd_tools/psd/descriptor.py | sfneal/psd-tools3 | train | 30 |
29d15c4c250ca4850556ce4ef32048387d4e4249 | [
"result = data_types.WebTestResult('foo', ['debug'], 'Pass', 'step', 'build_id')\nresult.SetDuration(str(1), str(2000))\nself.assertTrue(result.is_slow_result)",
"result = data_types.WebTestResult('foo', ['debug'], 'Pass', 'step', 'build_id')\nresult.SetDuration(30, 100000)\nself.assertFalse(result.is_slow_result... | <|body_start_0|>
result = data_types.WebTestResult('foo', ['debug'], 'Pass', 'step', 'build_id')
result.SetDuration(str(1), str(2000))
self.assertTrue(result.is_slow_result)
<|end_body_0|>
<|body_start_1|>
result = data_types.WebTestResult('foo', ['debug'], 'Pass', 'step', 'build_id')
... | WebTestResultUnittest | [
"LGPL-2.0-or-later",
"LicenseRef-scancode-warranty-disclaimer",
"LGPL-2.1-only",
"GPL-1.0-or-later",
"GPL-2.0-only",
"LGPL-2.0-only",
"BSD-2-Clause",
"LicenseRef-scancode-other-copyleft",
"BSD-3-Clause",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebTestResultUnittest:
def testSetDurationString(self):
"""Tests that strings are properly converted when setting durations."""
<|body_0|>
def testSetDurationNotSlow(self):
"""Tests that setting a duration for a non-slow result works."""
<|body_1|>
def t... | stack_v2_sparse_classes_10k_train_001233 | 10,707 | permissive | [
{
"docstring": "Tests that strings are properly converted when setting durations.",
"name": "testSetDurationString",
"signature": "def testSetDurationString(self)"
},
{
"docstring": "Tests that setting a duration for a non-slow result works.",
"name": "testSetDurationNotSlow",
"signature... | 5 | stack_v2_sparse_classes_30k_train_007125 | Implement the Python class `WebTestResultUnittest` described below.
Class description:
Implement the WebTestResultUnittest class.
Method signatures and docstrings:
- def testSetDurationString(self): Tests that strings are properly converted when setting durations.
- def testSetDurationNotSlow(self): Tests that settin... | Implement the Python class `WebTestResultUnittest` described below.
Class description:
Implement the WebTestResultUnittest class.
Method signatures and docstrings:
- def testSetDurationString(self): Tests that strings are properly converted when setting durations.
- def testSetDurationNotSlow(self): Tests that settin... | fd8a8914ca0183f0add65ae55f04e287543c7d4a | <|skeleton|>
class WebTestResultUnittest:
def testSetDurationString(self):
"""Tests that strings are properly converted when setting durations."""
<|body_0|>
def testSetDurationNotSlow(self):
"""Tests that setting a duration for a non-slow result works."""
<|body_1|>
def t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WebTestResultUnittest:
def testSetDurationString(self):
"""Tests that strings are properly converted when setting durations."""
result = data_types.WebTestResult('foo', ['debug'], 'Pass', 'step', 'build_id')
result.SetDuration(str(1), str(2000))
self.assertTrue(result.is_slow_r... | the_stack_v2_python_sparse | third_party/blink/tools/blinkpy/web_tests/stale_expectation_removal/data_types_unittest.py | SREERAGI18/chromium | train | 1 | |
6100f1a09996674b67a958a7026ada368ae699fb | [
"nn.Module.__init__(self)\nself.c = c\nself.nu = nu\nself.eps = eps\nself.soft_boundary = soft_boundary",
"dist = torch.sum((self.c - input) ** 2, dim=1)\nif self.soft_boundary:\n scores = dist - R ** 2\n loss = R ** 2 + 1 / self.nu * torch.mean(torch.max(torch.zeros_like(scores), scores))\nelse:\n loss ... | <|body_start_0|>
nn.Module.__init__(self)
self.c = c
self.nu = nu
self.eps = eps
self.soft_boundary = soft_boundary
<|end_body_0|>
<|body_start_1|>
dist = torch.sum((self.c - input) ** 2, dim=1)
if self.soft_boundary:
scores = dist - R ** 2
... | Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019) | DeepSVDDLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeepSVDDLoss:
"""Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)"""
def __init__(self, c, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor) the center of the hypersphere as a multidimensional vec... | stack_v2_sparse_classes_10k_train_001234 | 18,386 | permissive | [
{
"docstring": "Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor) the center of the hypersphere as a multidimensional vector. |---- nu (float) a priory fraction of outliers. |---- eps (float) epsilon to ensure numerical stability in the | inverse distance. |---- soft_boundary (bool) whet... | 2 | stack_v2_sparse_classes_30k_train_001265 | Implement the Python class `DeepSVDDLoss` described below.
Class description:
Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)
Method signatures and docstrings:
- def __init__(self, c, nu, eps=1e-06, soft_boundary=False): Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor... | Implement the Python class `DeepSVDDLoss` described below.
Class description:
Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)
Method signatures and docstrings:
- def __init__(self, c, nu, eps=1e-06, soft_boundary=False): Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor... | 850b6195d6290a50eee865b4d5a66f5db5260e8f | <|skeleton|>
class DeepSVDDLoss:
"""Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)"""
def __init__(self, c, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor) the center of the hypersphere as a multidimensional vec... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeepSVDDLoss:
"""Implementation of the DeepSVDD loss proposed by Lukas Ruff et al. (2019)"""
def __init__(self, c, nu, eps=1e-06, soft_boundary=False):
"""Constructor of the DeepSVDD loss. ---------- INPUT |---- c (torch.Tensor) the center of the hypersphere as a multidimensional vector. |---- nu... | the_stack_v2_python_sparse | Code/src/models/optim/CustomLosses.py | antoine-spahr/X-ray-Anomaly-Detection | train | 3 |
0a2449e76df8df27abfc4329685d69d939e1530c | [
"startTime = datetime.datetime.now()\nif trial:\n endTime = datetime.datetime.now()\n return {'start': startTime, 'end': endTime}\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate(TEAM_NAME, TEAM_NAME)\nurl = FUSION_TABLE_URL\ncsv_string = urllib.request.urlopen(url).read().decode('ut... | <|body_start_0|>
startTime = datetime.datetime.now()
if trial:
endTime = datetime.datetime.now()
return {'start': startTime, 'end': endTime}
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate(TEAM_NAME, TEAM_NAME)
url = FUSION_... | countyShapes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class countyShapes:
def execute(trial=False):
"""Read from Google Fusion table (uploaded to datamechanics.io) to get geoJSON data about each county and insert into collection ex) { "_id" : "7322", "Name" : Barnstable, "Shape" : "<Polygon> ... ", "Geo_ID" : "25001", }"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_001235 | 4,703 | no_license | [
{
"docstring": "Read from Google Fusion table (uploaded to datamechanics.io) to get geoJSON data about each county and insert into collection ex) { \"_id\" : \"7322\", \"Name\" : Barnstable, \"Shape\" : \"<Polygon> ... \", \"Geo_ID\" : \"25001\", }",
"name": "execute",
"signature": "def execute(trial=Fa... | 2 | stack_v2_sparse_classes_30k_train_006222 | Implement the Python class `countyShapes` described below.
Class description:
Implement the countyShapes class.
Method signatures and docstrings:
- def execute(trial=False): Read from Google Fusion table (uploaded to datamechanics.io) to get geoJSON data about each county and insert into collection ex) { "_id" : "732... | Implement the Python class `countyShapes` described below.
Class description:
Implement the countyShapes class.
Method signatures and docstrings:
- def execute(trial=False): Read from Google Fusion table (uploaded to datamechanics.io) to get geoJSON data about each county and insert into collection ex) { "_id" : "732... | 90284cf3debbac36eead07b8d2339cdd191b86cf | <|skeleton|>
class countyShapes:
def execute(trial=False):
"""Read from Google Fusion table (uploaded to datamechanics.io) to get geoJSON data about each county and insert into collection ex) { "_id" : "7322", "Name" : Barnstable, "Shape" : "<Polygon> ... ", "Geo_ID" : "25001", }"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class countyShapes:
def execute(trial=False):
"""Read from Google Fusion table (uploaded to datamechanics.io) to get geoJSON data about each county and insert into collection ex) { "_id" : "7322", "Name" : Barnstable, "Shape" : "<Polygon> ... ", "Geo_ID" : "25001", }"""
startTime = datetime.datetime... | the_stack_v2_python_sparse | ldisalvo_skeesara_vidyaap/countyShapes.py | maximega/course-2019-spr-proj | train | 2 | |
ddc2789d2459299c4f6c6be9ade9c56644d87a52 | [
"if server_ip == '' and server_port != 0 or (server_ip != '' and server_port == 0):\n raise Exception('server_ip和server_port必须同时指定')\nself._server_ip = server_ip\nself._server_port = server_port\nself._service_name = service_name\nself._host = host",
"headers = {'org': org, 'user': user}\nroute_name = ''\nserv... | <|body_start_0|>
if server_ip == '' and server_port != 0 or (server_ip != '' and server_port == 0):
raise Exception('server_ip和server_port必须同时指定')
self._server_ip = server_ip
self._server_port = server_port
self._service_name = service_name
self._host = host
<|end_bod... | DeployClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeployClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和servic... | stack_v2_sparse_classes_10k_train_001236 | 7,561 | permissive | [
{
"docstring": "初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和service_name同时设置，server_ip优先级更高 :param host: 指定sdk请求服务的host名称, 如cmdb.easyops-only.com",
"name": "__ini... | 5 | null | Implement the Python class `DeployClient` described below.
Class description:
Implement the DeployClient class.
Method signatures and docstrings:
- def __init__(self, server_ip='', server_port=0, service_name='', host=''): 初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_por... | Implement the Python class `DeployClient` described below.
Class description:
Implement the DeployClient class.
Method signatures and docstrings:
- def __init__(self, server_ip='', server_port=0, service_name='', host=''): 初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_por... | adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0 | <|skeleton|>
class DeployClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和servic... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeployClient:
def __init__(self, server_ip='', server_port=0, service_name='', host=''):
"""初始化client :param server_ip: 指定sdk请求的server_ip，为空时走名字服务路由 :param server_port: 指定sdk请求的server_port，与server_ip一起使用, 为空时走名字服务路由 :param service_name: 指定sdk请求的service_name, 为空时按契约名称路由。如果server_ip和service_name同时设置，ser... | the_stack_v2_python_sparse | easy_flow_sdk/api/deploy/deploy_client.py | easyopsapis/easyops-api-python | train | 5 | |
441f89298b13bb0c31797197fa30fb941cb26afa | [
"assert colors1() == ('white', 'white', 'white', 'white')\nassert colors1('red', 'blue', 'yellow', 'chartreuse') == ('red', 'blue', 'yellow', 'chartreuse')\nassert colors1(link_color='red', back_color='blue') == ('white', 'blue', 'red', 'white')\nassert colors1('purple', link_color='red', back_color='blue') == ('pu... | <|body_start_0|>
assert colors1() == ('white', 'white', 'white', 'white')
assert colors1('red', 'blue', 'yellow', 'chartreuse') == ('red', 'blue', 'yellow', 'chartreuse')
assert colors1(link_color='red', back_color='blue') == ('white', 'blue', 'red', 'white')
assert colors1('purple', lin... | Class to test args_kwargs_lab | ArgsKwargsTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArgsKwargsTest:
"""Class to test args_kwargs_lab"""
def test_colors1(self):
"""Test assertions for colors1 function"""
<|body_0|>
def test_colors2(self):
"""Test assertions for colors2 function"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ass... | stack_v2_sparse_classes_10k_train_001237 | 1,798 | no_license | [
{
"docstring": "Test assertions for colors1 function",
"name": "test_colors1",
"signature": "def test_colors1(self)"
},
{
"docstring": "Test assertions for colors2 function",
"name": "test_colors2",
"signature": "def test_colors2(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005791 | Implement the Python class `ArgsKwargsTest` described below.
Class description:
Class to test args_kwargs_lab
Method signatures and docstrings:
- def test_colors1(self): Test assertions for colors1 function
- def test_colors2(self): Test assertions for colors2 function | Implement the Python class `ArgsKwargsTest` described below.
Class description:
Class to test args_kwargs_lab
Method signatures and docstrings:
- def test_colors1(self): Test assertions for colors1 function
- def test_colors2(self): Test assertions for colors2 function
<|skeleton|>
class ArgsKwargsTest:
"""Class... | 661903cd9dc49b294fb9a0c905133a4c3f9d8d0f | <|skeleton|>
class ArgsKwargsTest:
"""Class to test args_kwargs_lab"""
def test_colors1(self):
"""Test assertions for colors1 function"""
<|body_0|>
def test_colors2(self):
"""Test assertions for colors2 function"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ArgsKwargsTest:
"""Class to test args_kwargs_lab"""
def test_colors1(self):
"""Test assertions for colors1 function"""
assert colors1() == ('white', 'white', 'white', 'white')
assert colors1('red', 'blue', 'yellow', 'chartreuse') == ('red', 'blue', 'yellow', 'chartreuse')
... | the_stack_v2_python_sparse | students/douglas_klos/session6/lab/test_args_kwargs_lab.py | pauleclifton/GP_Python210B_Winter_2019 | train | 0 |
a295cb7cef40c671d9f5f71efe8d7701ebfedbca | [
"cur = 0\ntotal = 0\nstart = 0\nfor i in range(len(gas)):\n cur += gas[i] - cost[i]\n total += gas[i] - cost[i]\n if cur < 0:\n start = i + 1\n cur = 0\nif total < 0:\n return -1\nreturn start",
"n = len(gas)\nfor i in range(n):\n start = (i + 1) % n\n count = gas[i] - cost[i]\n ... | <|body_start_0|>
cur = 0
total = 0
start = 0
for i in range(len(gas)):
cur += gas[i] - cost[i]
total += gas[i] - cost[i]
if cur < 0:
start = i + 1
cur = 0
if total < 0:
return -1
return start
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canCompleteCircuit(self, gas, cost):
""":type gas: List[int] :type cost: List[int] :rtype: int"""
<|body_0|>
def canCompleteCircuit0(self, gas, cost):
""":type gas: List[int] :type cost: List[int] :rtype: int 暴力解法"""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_10k_train_001238 | 1,268 | no_license | [
{
"docstring": ":type gas: List[int] :type cost: List[int] :rtype: int",
"name": "canCompleteCircuit",
"signature": "def canCompleteCircuit(self, gas, cost)"
},
{
"docstring": ":type gas: List[int] :type cost: List[int] :rtype: int 暴力解法",
"name": "canCompleteCircuit0",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_test_000370 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canCompleteCircuit(self, gas, cost): :type gas: List[int] :type cost: List[int] :rtype: int
- def canCompleteCircuit0(self, gas, cost): :type gas: List[int] :type cost: List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canCompleteCircuit(self, gas, cost): :type gas: List[int] :type cost: List[int] :rtype: int
- def canCompleteCircuit0(self, gas, cost): :type gas: List[int] :type cost: List[... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def canCompleteCircuit(self, gas, cost):
""":type gas: List[int] :type cost: List[int] :rtype: int"""
<|body_0|>
def canCompleteCircuit0(self, gas, cost):
""":type gas: List[int] :type cost: List[int] :rtype: int 暴力解法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def canCompleteCircuit(self, gas, cost):
""":type gas: List[int] :type cost: List[int] :rtype: int"""
cur = 0
total = 0
start = 0
for i in range(len(gas)):
cur += gas[i] - cost[i]
total += gas[i] - cost[i]
if cur < 0:
... | the_stack_v2_python_sparse | 134.加油站.py | yangyuxiang1996/leetcode | train | 0 | |
66e82b10565295776b2d233ffe48370631c5fd94 | [
"if not node:\n return None\nroot = UndirectedGraphNode(node.label)\nd_old_copy = {node: root}\ncur_layer = [node]\nself.bfs(cur_layer, d_old_copy)\nreturn root",
"while cur_layer:\n node = cur_layer.pop()\n for nb in node.neighbors:\n if nb not in d_old_copy:\n d_old_copy[nb] = Undirec... | <|body_start_0|>
if not node:
return None
root = UndirectedGraphNode(node.label)
d_old_copy = {node: root}
cur_layer = [node]
self.bfs(cur_layer, d_old_copy)
return root
<|end_body_0|>
<|body_start_1|>
while cur_layer:
node = cur_layer.pop... | Solution description | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Solution description"""
def cloneGraph(self, node):
"""Solution function description"""
<|body_0|>
def bfs(self, cur_layer, d_old_copy):
"""breadth first"""
<|body_1|>
def dfs(self, node, d_old_copy):
"""depth first"""
<|... | stack_v2_sparse_classes_10k_train_001239 | 1,512 | permissive | [
{
"docstring": "Solution function description",
"name": "cloneGraph",
"signature": "def cloneGraph(self, node)"
},
{
"docstring": "breadth first",
"name": "bfs",
"signature": "def bfs(self, cur_layer, d_old_copy)"
},
{
"docstring": "depth first",
"name": "dfs",
"signature... | 3 | stack_v2_sparse_classes_30k_train_004180 | Implement the Python class `Solution` described below.
Class description:
Solution description
Method signatures and docstrings:
- def cloneGraph(self, node): Solution function description
- def bfs(self, cur_layer, d_old_copy): breadth first
- def dfs(self, node, d_old_copy): depth first | Implement the Python class `Solution` described below.
Class description:
Solution description
Method signatures and docstrings:
- def cloneGraph(self, node): Solution function description
- def bfs(self, cur_layer, d_old_copy): breadth first
- def dfs(self, node, d_old_copy): depth first
<|skeleton|>
class Solution... | 869ee24c50c08403b170e8f7868699185e9dfdd1 | <|skeleton|>
class Solution:
"""Solution description"""
def cloneGraph(self, node):
"""Solution function description"""
<|body_0|>
def bfs(self, cur_layer, d_old_copy):
"""breadth first"""
<|body_1|>
def dfs(self, node, d_old_copy):
"""depth first"""
<|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
"""Solution description"""
def cloneGraph(self, node):
"""Solution function description"""
if not node:
return None
root = UndirectedGraphNode(node.label)
d_old_copy = {node: root}
cur_layer = [node]
self.bfs(cur_layer, d_old_copy)
... | the_stack_v2_python_sparse | 133.clone.graph/1.py | cerebrumaize/leetcode | train | 0 |
27de8bfe64a91ccf13abf24aa4004908ae3be567 | [
"self.matrix = matrix\nif not matrix:\n return\nm = len(matrix)\nn = len(matrix[0])\nself.dp = [[0] * (n + 1) for _ in range(m)]\nfor i in range(m):\n for j in range(1, n + 1):\n self.dp[i][j] = self.dp[i][j - 1] + matrix[i][j - 1]",
"res = 0\nfor k in range(row1, row2 + 1):\n res += self.dp[k][co... | <|body_start_0|>
self.matrix = matrix
if not matrix:
return
m = len(matrix)
n = len(matrix[0])
self.dp = [[0] * (n + 1) for _ in range(m)]
for i in range(m):
for j in range(1, n + 1):
self.dp[i][j] = self.dp[i][j - 1] + matrix[i][j ... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_10k_train_001240 | 1,170 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col2)"
... | 2 | null | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
self.matrix = matrix
if not matrix:
return
m = len(matrix)
n = len(matrix[0])
self.dp = [[0] * (n + 1) for _ in range(m)]
for i in range(m):
for j in range... | the_stack_v2_python_sparse | 0304_Range_Sum_Query_2D-Immutable.py | bingli8802/leetcode | train | 0 | |
57900062f3a74beb96084c6028884f8f6ae41c53 | [
"if REQUEST is not None:\n self.__dict__.update(REQUEST)\nif kw is not None:\n self.__dict__.update(kw)",
"if REQUEST is not None:\n aq_base(self).__dict__.update(REQUEST)\nif kw is not None:\n aq_base(self).__dict__.update(kw)\nif context is not None:\n return self.__of__(context)\nelse:\n retu... | <|body_start_0|>
if REQUEST is not None:
self.__dict__.update(REQUEST)
if kw is not None:
self.__dict__.update(kw)
<|end_body_0|>
<|body_start_1|>
if REQUEST is not None:
aq_base(self).__dict__.update(REQUEST)
if kw is not None:
aq_base(se... | Context objects are used all over ERP5 in so-called context dependent function. Examples of context dependent methods include: - price methods (price depends on the context: customer, quantity, etc.) - BOM methods | Context | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Context:
"""Context objects are used all over ERP5 in so-called context dependent function. Examples of context dependent methods include: - price methods (price depends on the context: customer, quantity, etc.) - BOM methods"""
def __init__(self, context=None, REQUEST=None, **kw):
"... | stack_v2_sparse_classes_10k_train_001241 | 2,898 | no_license | [
{
"docstring": "context -- The REQUEST -- the request object kw -- user specified parameters",
"name": "__init__",
"signature": "def __init__(self, context=None, REQUEST=None, **kw)"
},
{
"docstring": "Update args of context",
"name": "asContext",
"signature": "def asContext(self, contex... | 2 | null | Implement the Python class `Context` described below.
Class description:
Context objects are used all over ERP5 in so-called context dependent function. Examples of context dependent methods include: - price methods (price depends on the context: customer, quantity, etc.) - BOM methods
Method signatures and docstring... | Implement the Python class `Context` described below.
Class description:
Context objects are used all over ERP5 in so-called context dependent function. Examples of context dependent methods include: - price methods (price depends on the context: customer, quantity, etc.) - BOM methods
Method signatures and docstring... | dc02bfa887ffab9841abebc3f5c16d874388cef5 | <|skeleton|>
class Context:
"""Context objects are used all over ERP5 in so-called context dependent function. Examples of context dependent methods include: - price methods (price depends on the context: customer, quantity, etc.) - BOM methods"""
def __init__(self, context=None, REQUEST=None, **kw):
"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Context:
"""Context objects are used all over ERP5 in so-called context dependent function. Examples of context dependent methods include: - price methods (price depends on the context: customer, quantity, etc.) - BOM methods"""
def __init__(self, context=None, REQUEST=None, **kw):
"""context -- ... | the_stack_v2_python_sparse | product/ERP5Type/Context.py | jgpjuniorj/j | train | 1 |
a0de415e928a3c4f271ac4937288ce4d351668d6 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn OnenoteSection()",
"from .notebook import Notebook\nfrom .onenote_entity_hierarchy_model import OnenoteEntityHierarchyModel\nfrom .onenote_page import OnenotePage\nfrom .section_group import SectionGroup\nfrom .section_links import Sec... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return OnenoteSection()
<|end_body_0|>
<|body_start_1|>
from .notebook import Notebook
from .onenote_entity_hierarchy_model import OnenoteEntityHierarchyModel
from .onenote_page import ... | OnenoteSection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OnenoteSection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection:
"""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 Retur... | stack_v2_sparse_classes_10k_train_001242 | 4,298 | 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: OnenoteSection",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | stack_v2_sparse_classes_30k_train_001741 | Implement the Python class `OnenoteSection` described below.
Class description:
Implement the OnenoteSection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `OnenoteSection` described below.
Class description:
Implement the OnenoteSection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class OnenoteSection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection:
"""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 Retur... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OnenoteSection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OnenoteSection:
"""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: OnenoteSec... | the_stack_v2_python_sparse | msgraph/generated/models/onenote_section.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
74feaa5bc2b7f188fe1ccb62c12a7e9381a925b6 | [
"self.max_read_throughput = max_read_throughput\nself.max_write_throughput = max_write_throughput\nself.read_throughput_samples = read_throughput_samples\nself.write_throughput_samples = write_throughput_samples",
"if dictionary is None:\n return None\nmax_read_throughput = dictionary.get('maxReadThroughput')\... | <|body_start_0|>
self.max_read_throughput = max_read_throughput
self.max_write_throughput = max_write_throughput
self.read_throughput_samples = read_throughput_samples
self.write_throughput_samples = write_throughput_samples
<|end_body_0|>
<|body_start_1|>
if dictionary is None:... | Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 hours. read_throughput_samples (list of Sample): Read throughput samples taken for... | ThroughputTile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThroughputTile:
"""Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 hours. read_throughput_samples (list of ... | stack_v2_sparse_classes_10k_train_001243 | 3,283 | permissive | [
{
"docstring": "Constructor for the ThroughputTile class",
"name": "__init__",
"signature": "def __init__(self, max_read_throughput=None, max_write_throughput=None, read_throughput_samples=None, write_throughput_samples=None)"
},
{
"docstring": "Creates an instance of this model from a dictionar... | 2 | null | Implement the Python class `ThroughputTile` described below.
Class description:
Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 h... | Implement the Python class `ThroughputTile` described below.
Class description:
Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 h... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ThroughputTile:
"""Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 hours. read_throughput_samples (list of ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ThroughputTile:
"""Implementation of the 'ThroughputTile' model. Throughput information for dashboard. Attributes: max_read_throughput (long|int): Maxium Read throughput in last 24 hours. max_write_throughput (long|int): Maximum Write throughput in last 24 hours. read_throughput_samples (list of Sample): Read... | the_stack_v2_python_sparse | cohesity_management_sdk/models/throughput_tile.py | cohesity/management-sdk-python | train | 24 |
f1cb71ed6a45a6a81068504dfb916292bcdfe8cf | [
"host = DEFAULT_HOST if host is None else host\nport = DEFAULT_PORT if port is None else port\nself._socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nself._current_list = list()\nself.is_alive = True\ntry:\n self._socket.connect((host, port))\n self._receiver = Thread(target=self._hear_message_from... | <|body_start_0|>
host = DEFAULT_HOST if host is None else host
port = DEFAULT_PORT if port is None else port
self._socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self._current_list = list()
self.is_alive = True
try:
self._socket.connect((host, port... | Client | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Client:
def __init__(self, host=None, port=None):
"""Esta clase representa a un cliente, el cual se conecta a un servidor en host:port. Ademas, puede enviar y recibir mensajes del servidor"""
<|body_0|>
def _hear_message_from_server(self):
"""Esta funcion es la que q... | stack_v2_sparse_classes_10k_train_001244 | 2,503 | no_license | [
{
"docstring": "Esta clase representa a un cliente, el cual se conecta a un servidor en host:port. Ademas, puede enviar y recibir mensajes del servidor",
"name": "__init__",
"signature": "def __init__(self, host=None, port=None)"
},
{
"docstring": "Esta funcion es la que queda en un thread auxil... | 4 | stack_v2_sparse_classes_30k_train_001023 | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def __init__(self, host=None, port=None): Esta clase representa a un cliente, el cual se conecta a un servidor en host:port. Ademas, puede enviar y recibir mensajes del servidor
- de... | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def __init__(self, host=None, port=None): Esta clase representa a un cliente, el cual se conecta a un servidor en host:port. Ademas, puede enviar y recibir mensajes del servidor
- de... | 1458756a37d927d8dd365ba21cef4490360f1985 | <|skeleton|>
class Client:
def __init__(self, host=None, port=None):
"""Esta clase representa a un cliente, el cual se conecta a un servidor en host:port. Ademas, puede enviar y recibir mensajes del servidor"""
<|body_0|>
def _hear_message_from_server(self):
"""Esta funcion es la que q... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Client:
def __init__(self, host=None, port=None):
"""Esta clase representa a un cliente, el cual se conecta a un servidor en host:port. Ademas, puede enviar y recibir mensajes del servidor"""
host = DEFAULT_HOST if host is None else host
port = DEFAULT_PORT if port is None else port
... | the_stack_v2_python_sparse | Ayudantias/11 - Networking/Ejemplo - Envio de objetos/client.py | frhuerta/Syllabus | train | 0 | |
ceac4fbeb7f222f38b417db5ad228228169e6991 | [
"M, INT_MAX, d = (len(dungeon), 2 ** 31 - 1, dungeon)\nif M < 1:\n return 1\nN = len(d[0])\nd[M - 1][N - 1] = 1 if d[M - 1][N - 1] >= 0 else 1 - d[M - 1][N - 1]\nfor i in range(M - 1, -1, -1):\n for j in range(N - 1, -1, -1):\n if i == M - 1 and j == N - 1:\n continue\n right = max(1,... | <|body_start_0|>
M, INT_MAX, d = (len(dungeon), 2 ** 31 - 1, dungeon)
if M < 1:
return 1
N = len(d[0])
d[M - 1][N - 1] = 1 if d[M - 1][N - 1] >= 0 else 1 - d[M - 1][N - 1]
for i in range(M - 1, -1, -1):
for j in range(N - 1, -1, -1):
if i =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_0|>
def calculateMinimumHP2(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
M, INT... | stack_v2_sparse_classes_10k_train_001245 | 3,940 | no_license | [
{
"docstring": ":type dungeon: List[List[int]] :rtype: int",
"name": "calculateMinimumHP",
"signature": "def calculateMinimumHP(self, dungeon)"
},
{
"docstring": ":type dungeon: List[List[int]] :rtype: int",
"name": "calculateMinimumHP2",
"signature": "def calculateMinimumHP2(self, dunge... | 2 | stack_v2_sparse_classes_30k_train_006665 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calculateMinimumHP(self, dungeon): :type dungeon: List[List[int]] :rtype: int
- def calculateMinimumHP2(self, dungeon): :type dungeon: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def calculateMinimumHP(self, dungeon): :type dungeon: List[List[int]] :rtype: int
- def calculateMinimumHP2(self, dungeon): :type dungeon: List[List[int]] :rtype: int
<|skeleton... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_0|>
def calculateMinimumHP2(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def calculateMinimumHP(self, dungeon):
""":type dungeon: List[List[int]] :rtype: int"""
M, INT_MAX, d = (len(dungeon), 2 ** 31 - 1, dungeon)
if M < 1:
return 1
N = len(d[0])
d[M - 1][N - 1] = 1 if d[M - 1][N - 1] >= 0 else 1 - d[M - 1][N - 1]
... | the_stack_v2_python_sparse | code174DungeonGame.py | cybelewang/leetcode-python | train | 0 | |
43734b78b5aa22cb8e7882f19a78f3dc93fbfaf1 | [
"A.sort()\nfor i, a in enumerate(A):\n if a >= 0 or K <= 0:\n break\n A[i] = -a\n K -= 1\nif K % 2:\n return sum(A) - 2 * min(A)\nreturn sum(A)",
"heapq.heapify(A)\nwhile K:\n min_ = heapq.heappop(A)\n heapq.heappush(A, -min_)\n K -= 1\nreturn sum(A)"
] | <|body_start_0|>
A.sort()
for i, a in enumerate(A):
if a >= 0 or K <= 0:
break
A[i] = -a
K -= 1
if K % 2:
return sum(A) - 2 * min(A)
return sum(A)
<|end_body_0|>
<|body_start_1|>
heapq.heapify(A)
while K:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestSumAfterKNegations1(self, A: List[int], K: int) -> int:
"""执行用时 :68 ms, 在所有 Python3 提交中击败了61.61%的用户 内存消耗 :13.8 MB, 在所有 Python3 提交中击败了20.00%的用户 :param A: :param K: :return:"""
<|body_0|>
def largestSumAfterKNegations2(self, A: List[int], K: int) -> int:
... | stack_v2_sparse_classes_10k_train_001246 | 2,143 | no_license | [
{
"docstring": "执行用时 :68 ms, 在所有 Python3 提交中击败了61.61%的用户 内存消耗 :13.8 MB, 在所有 Python3 提交中击败了20.00%的用户 :param A: :param K: :return:",
"name": "largestSumAfterKNegations1",
"signature": "def largestSumAfterKNegations1(self, A: List[int], K: int) -> int"
},
{
"docstring": "思路：每次修改堆顶元素 @param A: @para... | 2 | stack_v2_sparse_classes_30k_train_003154 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestSumAfterKNegations1(self, A: List[int], K: int) -> int: 执行用时 :68 ms, 在所有 Python3 提交中击败了61.61%的用户 内存消耗 :13.8 MB, 在所有 Python3 提交中击败了20.00%的用户 :param A: :param K: :return... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestSumAfterKNegations1(self, A: List[int], K: int) -> int: 执行用时 :68 ms, 在所有 Python3 提交中击败了61.61%的用户 内存消耗 :13.8 MB, 在所有 Python3 提交中击败了20.00%的用户 :param A: :param K: :return... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def largestSumAfterKNegations1(self, A: List[int], K: int) -> int:
"""执行用时 :68 ms, 在所有 Python3 提交中击败了61.61%的用户 内存消耗 :13.8 MB, 在所有 Python3 提交中击败了20.00%的用户 :param A: :param K: :return:"""
<|body_0|>
def largestSumAfterKNegations2(self, A: List[int], K: int) -> int:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def largestSumAfterKNegations1(self, A: List[int], K: int) -> int:
"""执行用时 :68 ms, 在所有 Python3 提交中击败了61.61%的用户 内存消耗 :13.8 MB, 在所有 Python3 提交中击败了20.00%的用户 :param A: :param K: :return:"""
A.sort()
for i, a in enumerate(A):
if a >= 0 or K <= 0:
break
... | the_stack_v2_python_sparse | LeetCode/贪心算法/1005. Maximize Sum Of Array After K Negations.py | yiming1012/MyLeetCode | train | 2 | |
292264cfc982b8615c66907afe2794555183e64b | [
"if head == None or head.next == None:\n return head\ndummy = ListNode(-1000)\ndummy.next = head\nslow = dummy\nfast = dummy.next\nwhile fast:\n if fast.next and fast.next.val == fast.val:\n tmp = fast.val\n while fast and tmp == fast.val:\n fast = fast.next\n else:\n slow.n... | <|body_start_0|>
if head == None or head.next == None:
return head
dummy = ListNode(-1000)
dummy.next = head
slow = dummy
fast = dummy.next
while fast:
if fast.next and fast.next.val == fast.val:
tmp = fast.val
while... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteDuplicates(self, head: ListNode) -> ListNode:
"""迭代 :param head: :return:"""
<|body_0|>
def deleteDuplicates2(self, head: ListNode) -> ListNode:
"""感觉会用到两个循环 假设第一个virtual_node为自己创建的，node后面跟head 快指针指向head.next 慢指针指向head 当 head存在，循环遍历head.next 如果存在，... | stack_v2_sparse_classes_10k_train_001247 | 2,768 | permissive | [
{
"docstring": "迭代 :param head: :return:",
"name": "deleteDuplicates",
"signature": "def deleteDuplicates(self, head: ListNode) -> ListNode"
},
{
"docstring": "感觉会用到两个循环 假设第一个virtual_node为自己创建的，node后面跟head 快指针指向head.next 慢指针指向head 当 head存在，循环遍历head.next 如果存在，判断是否相等。如果不等，head为head.next 慢指针指向head ... | 4 | stack_v2_sparse_classes_30k_train_001714 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates(self, head: ListNode) -> ListNode: 迭代 :param head: :return:
- def deleteDuplicates2(self, head: ListNode) -> ListNode: 感觉会用到两个循环 假设第一个virtual_node为自己创建的，node... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates(self, head: ListNode) -> ListNode: 迭代 :param head: :return:
- def deleteDuplicates2(self, head: ListNode) -> ListNode: 感觉会用到两个循环 假设第一个virtual_node为自己创建的，node... | 41f4b8b557cf15cbd602f187f6550184b3a108ec | <|skeleton|>
class Solution:
def deleteDuplicates(self, head: ListNode) -> ListNode:
"""迭代 :param head: :return:"""
<|body_0|>
def deleteDuplicates2(self, head: ListNode) -> ListNode:
"""感觉会用到两个循环 假设第一个virtual_node为自己创建的，node后面跟head 快指针指向head.next 慢指针指向head 当 head存在，循环遍历head.next 如果存在，... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteDuplicates(self, head: ListNode) -> ListNode:
"""迭代 :param head: :return:"""
if head == None or head.next == None:
return head
dummy = ListNode(-1000)
dummy.next = head
slow = dummy
fast = dummy.next
while fast:
... | the_stack_v2_python_sparse | leetcode/82. 删除排序链表中的重复元素 II.py | zhongmb/suanfa | train | 0 | |
a3a777a18022111b81a565503bf9a2246dd90bbb | [
"super().__init__()\nself.normalizer = normalizer\nif self.normalizer is None:\n self.fitted = True\nif aggregator is None:\n aggregator = AverageAggregator()\nself.aggregator = aggregator",
"if self.normalizer is not None:\n x = self.normalizer(x)\nx = self.aggregator(x)\nreturn x",
"if self.normalize... | <|body_start_0|>
super().__init__()
self.normalizer = normalizer
if self.normalizer is None:
self.fitted = True
if aggregator is None:
aggregator = AverageAggregator()
self.aggregator = aggregator
<|end_body_0|>
<|body_start_1|>
if self.normalizer... | Ensembler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ensembler:
def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None):
"""An Ensembler applies normalization and aggregation operations to the scores of an ensemble of detectors. Parameters ---------- normalizer `BaseFittedTransformTorch` objec... | stack_v2_sparse_classes_10k_train_001248 | 9,337 | permissive | [
{
"docstring": "An Ensembler applies normalization and aggregation operations to the scores of an ensemble of detectors. Parameters ---------- normalizer `BaseFittedTransformTorch` object to normalize the scores. If ``None`` then no normalization is applied. aggregator `BaseTransformTorch` object to aggregate t... | 3 | stack_v2_sparse_classes_30k_train_003575 | Implement the Python class `Ensembler` described below.
Class description:
Implement the Ensembler class.
Method signatures and docstrings:
- def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None): An Ensembler applies normalization and aggregation operations to the sco... | Implement the Python class `Ensembler` described below.
Class description:
Implement the Ensembler class.
Method signatures and docstrings:
- def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None): An Ensembler applies normalization and aggregation operations to the sco... | 4a1b4f74a8590117965421e86c2295bff0f33e89 | <|skeleton|>
class Ensembler:
def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None):
"""An Ensembler applies normalization and aggregation operations to the scores of an ensemble of detectors. Parameters ---------- normalizer `BaseFittedTransformTorch` objec... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Ensembler:
def __init__(self, normalizer: Optional[BaseTransformTorch]=None, aggregator: BaseTransformTorch=None):
"""An Ensembler applies normalization and aggregation operations to the scores of an ensemble of detectors. Parameters ---------- normalizer `BaseFittedTransformTorch` object to normalize... | the_stack_v2_python_sparse | alibi_detect/od/pytorch/ensemble.py | SeldonIO/alibi-detect | train | 1,922 | |
19a9ba593a2291e326679f61412abae28c0f07cc | [
"super().__init__(nup, ndown, cuda)\nself.cusp_weights = None\nself.fc1 = nn.Linear(1, size1, bias=False)\nself.fc2 = nn.Linear(size1, size2, bias=False)\nself.fc3 = nn.Linear(size2, 1, bias=False)\neps = 1e-06\nself.fc1.weight.data *= eps\nself.fc2.weight.data *= eps\nself.fc3.weight.data *= eps\nself.nl_func = ac... | <|body_start_0|>
super().__init__(nup, ndown, cuda)
self.cusp_weights = None
self.fc1 = nn.Linear(1, size1, bias=False)
self.fc2 = nn.Linear(size1, size2, bias=False)
self.fc3 = nn.Linear(size2, 1, bias=False)
eps = 1e-06
self.fc1.weight.data *= eps
self.f... | FullyConnectedJastrowKernel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FullyConnectedJastrowKernel:
def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True):
"""Defines a fully connected jastrow factors."""
<|body_0|>
def get_var_weight(self):
"""define the variational weight."""
... | stack_v2_sparse_classes_10k_train_001249 | 3,241 | permissive | [
{
"docstring": "Defines a fully connected jastrow factors.",
"name": "__init__",
"signature": "def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True)"
},
{
"docstring": "define the variational weight.",
"name": "get_var_weight",
"... | 4 | stack_v2_sparse_classes_30k_test_000205 | Implement the Python class `FullyConnectedJastrowKernel` described below.
Class description:
Implement the FullyConnectedJastrowKernel class.
Method signatures and docstrings:
- def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True): Defines a fully connected ... | Implement the Python class `FullyConnectedJastrowKernel` described below.
Class description:
Implement the FullyConnectedJastrowKernel class.
Method signatures and docstrings:
- def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True): Defines a fully connected ... | 439a79e97ee63057e3032d28a1a5ebafd2d5b5e4 | <|skeleton|>
class FullyConnectedJastrowKernel:
def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True):
"""Defines a fully connected jastrow factors."""
<|body_0|>
def get_var_weight(self):
"""define the variational weight."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FullyConnectedJastrowKernel:
def __init__(self, nup, ndown, cuda, size1=16, size2=8, activation=torch.nn.Sigmoid(), include_cusp_weight=True):
"""Defines a fully connected jastrow factors."""
super().__init__(nup, ndown, cuda)
self.cusp_weights = None
self.fc1 = nn.Linear(1, si... | the_stack_v2_python_sparse | qmctorch/wavefunction/jastrows/elec_elec/kernels/fully_connected_jastrow_kernel.py | NLESC-JCER/QMCTorch | train | 22 | |
eae781e58493abcefc29f5b15efb3bc5bd34b850 | [
"super().__init__(form=form, bTxt=self.START_TEXT, bCmd=lambda: self.__toggleMic())\nself.__start = True\nself.__configure()",
"self.__mic = Microphone()\nself._button.configure(foreground=self.FOREGROUND)\nself._button.configure(background=self.START_COLOR)",
"if self.__start:\n self._button['text'] = self.... | <|body_start_0|>
super().__init__(form=form, bTxt=self.START_TEXT, bCmd=lambda: self.__toggleMic())
self.__start = True
self.__configure()
<|end_body_0|>
<|body_start_1|>
self.__mic = Microphone()
self._button.configure(foreground=self.FOREGROUND)
self._button.configure(... | Class for selecting sound file. | MicButton | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MicButton:
"""Class for selecting sound file."""
def __init__(self, form):
"""Construct object."""
<|body_0|>
def __configure(self):
"""Initialize the look/location of the Button."""
<|body_1|>
def __toggleMic(self):
"""Toggle the microphone ... | stack_v2_sparse_classes_10k_train_001250 | 1,853 | no_license | [
{
"docstring": "Construct object.",
"name": "__init__",
"signature": "def __init__(self, form)"
},
{
"docstring": "Initialize the look/location of the Button.",
"name": "__configure",
"signature": "def __configure(self)"
},
{
"docstring": "Toggle the microphone button to start/st... | 3 | stack_v2_sparse_classes_30k_train_000767 | Implement the Python class `MicButton` described below.
Class description:
Class for selecting sound file.
Method signatures and docstrings:
- def __init__(self, form): Construct object.
- def __configure(self): Initialize the look/location of the Button.
- def __toggleMic(self): Toggle the microphone button to start... | Implement the Python class `MicButton` described below.
Class description:
Class for selecting sound file.
Method signatures and docstrings:
- def __init__(self, form): Construct object.
- def __configure(self): Initialize the look/location of the Button.
- def __toggleMic(self): Toggle the microphone button to start... | 6d29e1e0b2335c90452a832373dcf3058cec33e9 | <|skeleton|>
class MicButton:
"""Class for selecting sound file."""
def __init__(self, form):
"""Construct object."""
<|body_0|>
def __configure(self):
"""Initialize the look/location of the Button."""
<|body_1|>
def __toggleMic(self):
"""Toggle the microphone ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MicButton:
"""Class for selecting sound file."""
def __init__(self, form):
"""Construct object."""
super().__init__(form=form, bTxt=self.START_TEXT, bCmd=lambda: self.__toggleMic())
self.__start = True
self.__configure()
def __configure(self):
"""Initialize th... | the_stack_v2_python_sparse | emotionAnalyzer/gui/micButton.py | vkepuska/LivePitchTracking | train | 0 |
934cc4adf4784cdbedeaa5bc022b4ec99423d927 | [
"if project == 'CMIP6':\n required = [{'short_name': 'o3'}, {'short_name': 'ps'}]\nelse:\n required = [{'short_name': 'tro3'}, {'short_name': 'ps'}]\nreturn required",
"tro3_cube = cubes.extract_cube(iris.Constraint(name='mole_fraction_of_ozone_in_air'))\nps_cube = cubes.extract_cube(iris.Constraint(name='s... | <|body_start_0|>
if project == 'CMIP6':
required = [{'short_name': 'o3'}, {'short_name': 'ps'}]
else:
required = [{'short_name': 'tro3'}, {'short_name': 'ps'}]
return required
<|end_body_0|>
<|body_start_1|>
tro3_cube = cubes.extract_cube(iris.Constraint(name='mo... | Derivation of variable `toz`. | DerivedVariable | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DerivedVariable:
"""Derivation of variable `toz`."""
def required(project):
"""Declare the variables needed for derivation."""
<|body_0|>
def calculate(cubes):
"""Compute total column ozone. Note ---- The surface pressure is used as a lower integration bound. A f... | stack_v2_sparse_classes_10k_train_001251 | 2,234 | permissive | [
{
"docstring": "Declare the variables needed for derivation.",
"name": "required",
"signature": "def required(project)"
},
{
"docstring": "Compute total column ozone. Note ---- The surface pressure is used as a lower integration bound. A fixed upper integration bound of 0 Pa is used.",
"name... | 2 | null | Implement the Python class `DerivedVariable` described below.
Class description:
Derivation of variable `toz`.
Method signatures and docstrings:
- def required(project): Declare the variables needed for derivation.
- def calculate(cubes): Compute total column ozone. Note ---- The surface pressure is used as a lower i... | Implement the Python class `DerivedVariable` described below.
Class description:
Derivation of variable `toz`.
Method signatures and docstrings:
- def required(project): Declare the variables needed for derivation.
- def calculate(cubes): Compute total column ozone. Note ---- The surface pressure is used as a lower i... | d5187438fea2928644cb53ecb26c6adb1e4cc947 | <|skeleton|>
class DerivedVariable:
"""Derivation of variable `toz`."""
def required(project):
"""Declare the variables needed for derivation."""
<|body_0|>
def calculate(cubes):
"""Compute total column ozone. Note ---- The surface pressure is used as a lower integration bound. A f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DerivedVariable:
"""Derivation of variable `toz`."""
def required(project):
"""Declare the variables needed for derivation."""
if project == 'CMIP6':
required = [{'short_name': 'o3'}, {'short_name': 'ps'}]
else:
required = [{'short_name': 'tro3'}, {'short_n... | the_stack_v2_python_sparse | esmvalcore/preprocessor/_derive/toz.py | ESMValGroup/ESMValCore | train | 41 |
dead2d5b1ed5133c132853e6c076fc4cb996b7bb | [
"if not root:\n return ''\nencoded = []\nq = deque()\nq.appendleft(root)\nwhile q:\n node = q.pop()\n if node is None or node == 'None':\n encoded.append('None')\n else:\n encoded.append(str(node.val))\n q.appendleft(node.left)\n q.appendleft(node.right)\nreturn ' '.join(enco... | <|body_start_0|>
if not root:
return ''
encoded = []
q = deque()
q.appendleft(root)
while q:
node = q.pop()
if node is None or node == 'None':
encoded.append('None')
else:
encoded.append(str(node.val)... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_001252 | 3,104 | permissive | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 6a83cb798cc317d1e4357ac6b2b1fbf76fa034fb | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
encoded = []
q = deque()
q.appendleft(root)
while q:
node = q.pop()
if node is None or node == ... | the_stack_v2_python_sparse | Month 03/Week 04/Day 05/a.py | KevinKnott/Coding-Review | train | 0 | |
08793fa7d6a00fc8468ad092b5e84b8a69dc36d6 | [
"cache_key = (model_year, drive_system)\nstart_years = WorkFactor.start_years[drive_system]\nif len([yr for yr in start_years if yr <= model_year]) > 0:\n model_year = max([yr for yr in start_years if yr <= model_year])\n xwd = WorkFactor._cache[model_year, drive_system]['xwd']\n workfactor = eval(WorkFact... | <|body_start_0|>
cache_key = (model_year, drive_system)
start_years = WorkFactor.start_years[drive_system]
if len([yr for yr in start_years if yr <= model_year]) > 0:
model_year = max([yr for yr in start_years if yr <= model_year])
xwd = WorkFactor._cache[model_year, driv... | **Work factor definition and calculations.** | WorkFactor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkFactor:
"""**Work factor definition and calculations.**"""
def calc_workfactor(model_year, curbweight_lbs, gvwr_lbs, gcwr_lbs, drive_system):
"""Calculate vehicle workfactor. Args: model_year (int): vehicle model year curbweight_lbs (float): vehicle curb weight in lbs gvwr_lbs (f... | stack_v2_sparse_classes_10k_train_001253 | 5,474 | no_license | [
{
"docstring": "Calculate vehicle workfactor. Args: model_year (int): vehicle model year curbweight_lbs (float): vehicle curb weight in lbs gvwr_lbs (float): vehicle gross vehicle weight rating in lbs gcwr_lbs (float): vehicle combined weight rating in lbs drive_system (int): drive system, 2=two wheel drive, 4=... | 2 | stack_v2_sparse_classes_30k_train_005177 | Implement the Python class `WorkFactor` described below.
Class description:
**Work factor definition and calculations.**
Method signatures and docstrings:
- def calc_workfactor(model_year, curbweight_lbs, gvwr_lbs, gcwr_lbs, drive_system): Calculate vehicle workfactor. Args: model_year (int): vehicle model year curbw... | Implement the Python class `WorkFactor` described below.
Class description:
**Work factor definition and calculations.**
Method signatures and docstrings:
- def calc_workfactor(model_year, curbweight_lbs, gvwr_lbs, gcwr_lbs, drive_system): Calculate vehicle workfactor. Args: model_year (int): vehicle model year curbw... | afe912c57383b9de90ef30820f7977c3367a30c4 | <|skeleton|>
class WorkFactor:
"""**Work factor definition and calculations.**"""
def calc_workfactor(model_year, curbweight_lbs, gvwr_lbs, gcwr_lbs, drive_system):
"""Calculate vehicle workfactor. Args: model_year (int): vehicle model year curbweight_lbs (float): vehicle curb weight in lbs gvwr_lbs (f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WorkFactor:
"""**Work factor definition and calculations.**"""
def calc_workfactor(model_year, curbweight_lbs, gvwr_lbs, gcwr_lbs, drive_system):
"""Calculate vehicle workfactor. Args: model_year (int): vehicle model year curbweight_lbs (float): vehicle curb weight in lbs gvwr_lbs (float): vehicl... | the_stack_v2_python_sparse | omega_model/policy/workfactor_definition.py | USEPA/EPA_OMEGA_Model | train | 17 |
f3037a1d461ece66e5fae87be3335f615c2ece9d | [
"if table_size < 1:\n raise ValueError('table_size must be at least 1.')\nif repetitions < 3:\n raise ValueError('repetitions must be at least 3.')\nif rescale_factor <= 0 or rescale_factor > table_size - 1:\n raise ValueError(f'rescale_factor must be positive and no greater than table_size - 1. Found tabl... | <|body_start_0|>
if table_size < 1:
raise ValueError('table_size must be at least 1.')
if repetitions < 3:
raise ValueError('repetitions must be at least 3.')
if rescale_factor <= 0 or rescale_factor > table_size - 1:
raise ValueError(f'rescale_factor must be ... | Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf. | CoupledHyperEdgeHasher | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoupledHyperEdgeHasher:
"""Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf."""
def __init__(self, seed: int, table_size: int, repetitions: int, rescale... | stack_v2_sparse_classes_10k_train_001254 | 10,259 | permissive | [
{
"docstring": "Initialize CoupledHyperEdgeHasher. Args: seed: An integer seed for hash functions. table_size: The hash table size of the IBLT. Must be a positive integer. repetitions: The number of repetitions in IBLT data structure. Must be at least 3. rescale_factor: A float to rescale `table_size` to `table... | 6 | stack_v2_sparse_classes_30k_train_001620 | Implement the Python class `CoupledHyperEdgeHasher` described below.
Class description:
Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf.
Method signatures and docstrings:
- def ... | Implement the Python class `CoupledHyperEdgeHasher` described below.
Class description:
Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf.
Method signatures and docstrings:
- def ... | ad4bca66f4b483e09d8396e9948630813a343d27 | <|skeleton|>
class CoupledHyperEdgeHasher:
"""Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf."""
def __init__(self, seed: int, table_size: int, repetitions: int, rescale... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CoupledHyperEdgeHasher:
"""Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf."""
def __init__(self, seed: int, table_size: int, repetitions: int, rescale_factor: floa... | the_stack_v2_python_sparse | tensorflow_federated/python/analytics/heavy_hitters/iblt/hyperedge_hashers.py | tensorflow/federated | train | 2,297 |
098e483da95d13d2ebe99bd4da1def90324f1f66 | [
"if not isinstance(min_length, int):\n raise TypeError('min_length must be Integer')\nif min_length < 0:\n raise ValueError('min_length must be lager 0')\nif not isinstance(max_length, int):\n raise TypeError('max_length must be Integer')\nif min_length > max_length:\n raise ValueError('must (min_length... | <|body_start_0|>
if not isinstance(min_length, int):
raise TypeError('min_length must be Integer')
if min_length < 0:
raise ValueError('min_length must be lager 0')
if not isinstance(max_length, int):
raise TypeError('max_length must be Integer')
if mi... | 字符串类型的数据描述符 | CharField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CharField:
"""字符串类型的数据描述符"""
def __init__(self, *args, min_length=0, max_length=256, regx='', **kwargs):
""":param args: :param min_length: :param max_length: :param regx: 用于验证value是否匹配规则 :param kwargs:"""
<|body_0|>
def _validate(self, value):
"""value必须是字符串，同时长... | stack_v2_sparse_classes_10k_train_001255 | 3,660 | no_license | [
{
"docstring": ":param args: :param min_length: :param max_length: :param regx: 用于验证value是否匹配规则 :param kwargs:",
"name": "__init__",
"signature": "def __init__(self, *args, min_length=0, max_length=256, regx='', **kwargs)"
},
{
"docstring": "value必须是字符串，同时长度在min_length和max_length之间，能和regx完全匹配 :p... | 2 | stack_v2_sparse_classes_30k_train_005433 | Implement the Python class `CharField` described below.
Class description:
字符串类型的数据描述符
Method signatures and docstrings:
- def __init__(self, *args, min_length=0, max_length=256, regx='', **kwargs): :param args: :param min_length: :param max_length: :param regx: 用于验证value是否匹配规则 :param kwargs:
- def _validate(self, va... | Implement the Python class `CharField` described below.
Class description:
字符串类型的数据描述符
Method signatures and docstrings:
- def __init__(self, *args, min_length=0, max_length=256, regx='', **kwargs): :param args: :param min_length: :param max_length: :param regx: 用于验证value是否匹配规则 :param kwargs:
- def _validate(self, va... | 5e28d5db63ebe23d5004fff19104f2ef7fdbd327 | <|skeleton|>
class CharField:
"""字符串类型的数据描述符"""
def __init__(self, *args, min_length=0, max_length=256, regx='', **kwargs):
""":param args: :param min_length: :param max_length: :param regx: 用于验证value是否匹配规则 :param kwargs:"""
<|body_0|>
def _validate(self, value):
"""value必须是字符串，同时长... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CharField:
"""字符串类型的数据描述符"""
def __init__(self, *args, min_length=0, max_length=256, regx='', **kwargs):
""":param args: :param min_length: :param max_length: :param regx: 用于验证value是否匹配规则 :param kwargs:"""
if not isinstance(min_length, int):
raise TypeError('min_length must be... | the_stack_v2_python_sparse | FluentPython/20属性描述符/03属性描述符.py | cpfyjjs/python | train | 0 |
76b32fa7c5391276630065e732f3ea6cd35f34c3 | [
"end = self.end\nu = Mi32SlidingWindow()\nu.ADDR_WIDTH = end.ADDR_WIDTH\nu.DATA_WIDTH = end.DATA_WIDTH\nu.WINDOW_SIZE = window_size\nu.M_ADDR_WIDTH = new_addr_width\nsetattr(self.parent, self._findSuitableName('mi32SlidingWindow'), u)\nself._propagateClkRstn(u)\nu.s(self.end)\nself.lastComp = u\nself.end = u.m\nret... | <|body_start_0|>
end = self.end
u = Mi32SlidingWindow()
u.ADDR_WIDTH = end.ADDR_WIDTH
u.DATA_WIDTH = end.DATA_WIDTH
u.WINDOW_SIZE = window_size
u.M_ADDR_WIDTH = new_addr_width
setattr(self.parent, self._findSuitableName('mi32SlidingWindow'), u)
self._propa... | Mi32Builder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mi32Builder:
def sliding_window(self, window_size: int, new_addr_width: int):
"""Instanciate a sliding window with an offset register which allows to virtually extend the addressable memory space"""
<|body_0|>
def from_axi(cls, parent, axi, name=None):
"""convertor A... | stack_v2_sparse_classes_10k_train_001256 | 2,536 | permissive | [
{
"docstring": "Instanciate a sliding window with an offset register which allows to virtually extend the addressable memory space",
"name": "sliding_window",
"signature": "def sliding_window(self, window_size: int, new_addr_width: int)"
},
{
"docstring": "convertor AXI/AxiLite -> Mi32",
"na... | 3 | null | Implement the Python class `Mi32Builder` described below.
Class description:
Implement the Mi32Builder class.
Method signatures and docstrings:
- def sliding_window(self, window_size: int, new_addr_width: int): Instanciate a sliding window with an offset register which allows to virtually extend the addressable memor... | Implement the Python class `Mi32Builder` described below.
Class description:
Implement the Mi32Builder class.
Method signatures and docstrings:
- def sliding_window(self, window_size: int, new_addr_width: int): Instanciate a sliding window with an offset register which allows to virtually extend the addressable memor... | 4c1d54c7b15929032ad2ba984bf48b45f3549c49 | <|skeleton|>
class Mi32Builder:
def sliding_window(self, window_size: int, new_addr_width: int):
"""Instanciate a sliding window with an offset register which allows to virtually extend the addressable memory space"""
<|body_0|>
def from_axi(cls, parent, axi, name=None):
"""convertor A... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Mi32Builder:
def sliding_window(self, window_size: int, new_addr_width: int):
"""Instanciate a sliding window with an offset register which allows to virtually extend the addressable memory space"""
end = self.end
u = Mi32SlidingWindow()
u.ADDR_WIDTH = end.ADDR_WIDTH
u.... | the_stack_v2_python_sparse | hwtLib/cesnet/mi32/builder.py | Nic30/hwtLib | train | 36 | |
fb03b8f9596d80fc944313d6d5bd695032b4dfa2 | [
"self.file_type = file_type\nself.full_path = full_path\nself.size_bytes = size_bytes",
"if dictionary is None:\n return None\nfile_type = dictionary.get('fileType')\nfull_path = dictionary.get('fullPath')\nsize_bytes = dictionary.get('sizeBytes')\nreturn cls(file_type, full_path, size_bytes)"
] | <|body_start_0|>
self.file_type = file_type
self.full_path = full_path
self.size_bytes = size_bytes
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
file_type = dictionary.get('fileType')
full_path = dictionary.get('fullPath')
size_b... | Implementation of the 'DbFileInfo' model. Specifies information about a database file. Attributes: file_type (FileTypeEnum): Specifies the format type of the file that SQL database stores the data. Specifies the format type of the file that SQL database stores the data. 'kRows' refers to a data file 'kLog' refers to a ... | DbFileInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DbFileInfo:
"""Implementation of the 'DbFileInfo' model. Specifies information about a database file. Attributes: file_type (FileTypeEnum): Specifies the format type of the file that SQL database stores the data. Specifies the format type of the file that SQL database stores the data. 'kRows' ref... | stack_v2_sparse_classes_10k_train_001257 | 2,285 | permissive | [
{
"docstring": "Constructor for the DbFileInfo class",
"name": "__init__",
"signature": "def __init__(self, file_type=None, full_path=None, size_bytes=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the o... | 2 | null | Implement the Python class `DbFileInfo` described below.
Class description:
Implementation of the 'DbFileInfo' model. Specifies information about a database file. Attributes: file_type (FileTypeEnum): Specifies the format type of the file that SQL database stores the data. Specifies the format type of the file that SQ... | Implement the Python class `DbFileInfo` described below.
Class description:
Implementation of the 'DbFileInfo' model. Specifies information about a database file. Attributes: file_type (FileTypeEnum): Specifies the format type of the file that SQL database stores the data. Specifies the format type of the file that SQ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class DbFileInfo:
"""Implementation of the 'DbFileInfo' model. Specifies information about a database file. Attributes: file_type (FileTypeEnum): Specifies the format type of the file that SQL database stores the data. Specifies the format type of the file that SQL database stores the data. 'kRows' ref... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DbFileInfo:
"""Implementation of the 'DbFileInfo' model. Specifies information about a database file. Attributes: file_type (FileTypeEnum): Specifies the format type of the file that SQL database stores the data. Specifies the format type of the file that SQL database stores the data. 'kRows' refers to a data... | the_stack_v2_python_sparse | cohesity_management_sdk/models/db_file_info.py | cohesity/management-sdk-python | train | 24 |
e7cfa87a9d556bbafe2b7b82cb82f2c2de694aa9 | [
"return_fields = ['timestamp']\nevents = self.event_stream(query_string=self.query, return_fields=return_fields)\nsession_num = 0\ntry:\n first_event = next(events)\n last_timestamp = first_event.source.get('timestamp')\n session_num = 1\n self.annotateEvent(first_event, session_num)\n for event in e... | <|body_start_0|>
return_fields = ['timestamp']
events = self.event_stream(query_string=self.query, return_fields=return_fields)
session_num = 0
try:
first_event = next(events)
last_timestamp = first_event.source.get('timestamp')
session_num = 1
... | Sessionizing analyzer. All events in sketch with id sketch_id are grouped in sessions based on the time difference between them. Two consecutive events are in the same session if the time difference between them is less or equal then max_time_diff_micros. Attributes: NAME (str): The name of the sessionizer. max_time_di... | SessionizerSketchPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionizerSketchPlugin:
"""Sessionizing analyzer. All events in sketch with id sketch_id are grouped in sessions based on the time difference between them. Two consecutive events are in the same session if the time difference between them is less or equal then max_time_diff_micros. Attributes: N... | stack_v2_sparse_classes_10k_train_001258 | 3,075 | permissive | [
{
"docstring": "Entry point for the analyzer. Allocates each event a session_id attribute. Returns: String containing the number of sessions created.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Annotate an event with a session ID. Store IDs as dictionary entries correspondin... | 2 | stack_v2_sparse_classes_30k_train_006709 | Implement the Python class `SessionizerSketchPlugin` described below.
Class description:
Sessionizing analyzer. All events in sketch with id sketch_id are grouped in sessions based on the time difference between them. Two consecutive events are in the same session if the time difference between them is less or equal t... | Implement the Python class `SessionizerSketchPlugin` described below.
Class description:
Sessionizing analyzer. All events in sketch with id sketch_id are grouped in sessions based on the time difference between them. Two consecutive events are in the same session if the time difference between them is less or equal t... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class SessionizerSketchPlugin:
"""Sessionizing analyzer. All events in sketch with id sketch_id are grouped in sessions based on the time difference between them. Two consecutive events are in the same session if the time difference between them is less or equal then max_time_diff_micros. Attributes: N... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SessionizerSketchPlugin:
"""Sessionizing analyzer. All events in sketch with id sketch_id are grouped in sessions based on the time difference between them. Two consecutive events are in the same session if the time difference between them is less or equal then max_time_diff_micros. Attributes: NAME (str): Th... | the_stack_v2_python_sparse | timesketch/lib/analyzers/sessionizer.py | google/timesketch | train | 2,263 |
6227349e50a3342bba8833ce3ea221cf5796cba0 | [
"super()._init_layers()\nself.ref_point_head = MLP(self.embed_dims * 2, self.embed_dims, self.embed_dims, 2)\nself.norm = nn.LayerNorm(self.embed_dims)",
"intermediate = []\nintermediate_reference_points = [reference_points]\nfor lid, layer in enumerate(self.layers):\n if reference_points.shape[-1] == 4:\n ... | <|body_start_0|>
super()._init_layers()
self.ref_point_head = MLP(self.embed_dims * 2, self.embed_dims, self.embed_dims, 2)
self.norm = nn.LayerNorm(self.embed_dims)
<|end_body_0|>
<|body_start_1|>
intermediate = []
intermediate_reference_points = [reference_points]
for ... | Transformer encoder of DINO. | DinoTransformerDecoder | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DinoTransformerDecoder:
"""Transformer encoder of DINO."""
def _init_layers(self) -> None:
"""Initialize decoder layers."""
<|body_0|>
def forward(self, query: Tensor, value: Tensor, key_padding_mask: Tensor, self_attn_mask: Tensor, reference_points: Tensor, spatial_shap... | stack_v2_sparse_classes_10k_train_001259 | 26,710 | permissive | [
{
"docstring": "Initialize decoder layers.",
"name": "_init_layers",
"signature": "def _init_layers(self) -> None"
},
{
"docstring": "Forward function of Transformer encoder. Args: query (Tensor): The input query, has shape (num_queries, bs, dim). value (Tensor): The input values, has shape (num... | 2 | stack_v2_sparse_classes_30k_train_002437 | Implement the Python class `DinoTransformerDecoder` described below.
Class description:
Transformer encoder of DINO.
Method signatures and docstrings:
- def _init_layers(self) -> None: Initialize decoder layers.
- def forward(self, query: Tensor, value: Tensor, key_padding_mask: Tensor, self_attn_mask: Tensor, refere... | Implement the Python class `DinoTransformerDecoder` described below.
Class description:
Transformer encoder of DINO.
Method signatures and docstrings:
- def _init_layers(self) -> None: Initialize decoder layers.
- def forward(self, query: Tensor, value: Tensor, key_padding_mask: Tensor, self_attn_mask: Tensor, refere... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class DinoTransformerDecoder:
"""Transformer encoder of DINO."""
def _init_layers(self) -> None:
"""Initialize decoder layers."""
<|body_0|>
def forward(self, query: Tensor, value: Tensor, key_padding_mask: Tensor, self_attn_mask: Tensor, reference_points: Tensor, spatial_shap... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DinoTransformerDecoder:
"""Transformer encoder of DINO."""
def _init_layers(self) -> None:
"""Initialize decoder layers."""
super()._init_layers()
self.ref_point_head = MLP(self.embed_dims * 2, self.embed_dims, self.embed_dims, 2)
self.norm = nn.LayerNorm(self.embed_dims)
... | the_stack_v2_python_sparse | ai/mmdetection/mmdet/models/layers/transformer/dino_layers.py | alldatacenter/alldata | train | 774 |
15a52e613ca529ef39b8b96e2ad9ef34659bd067 | [
"self.cluster_dir = cluster_dir\nself.year_id = year_id\nself.input_me = input_me\nself.output_me = output_me\nself.conn_def = 'cod'\nself.gbd_round = 4",
"query = 'SELECT location_id, most_detailed FROM shared.location_hierarchy_history WHERE location_set_version_id=(SELECT location_set_version_id FROM {DATABASE... | <|body_start_0|>
self.cluster_dir = cluster_dir
self.year_id = year_id
self.input_me = input_me
self.output_me = output_me
self.conn_def = 'cod'
self.gbd_round = 4
<|end_body_0|>
<|body_start_1|>
query = 'SELECT location_id, most_detailed FROM shared.location_hie... | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
def __init__(self, cluster_dir, year_id, input_me, output_me):
"""This class incorporates all the functions that all the specific causes use, but all in different sequence"""
<|body_0|>
def get_locations(self, location_set_id):
"""Pulls the location hierarchy u... | stack_v2_sparse_classes_10k_train_001260 | 4,519 | no_license | [
{
"docstring": "This class incorporates all the functions that all the specific causes use, but all in different sequence",
"name": "__init__",
"signature": "def __init__(self, cluster_dir, year_id, input_me, output_me)"
},
{
"docstring": "Pulls the location hierarchy upon which this code is to ... | 6 | stack_v2_sparse_classes_30k_train_001613 | Implement the Python class `Base` described below.
Class description:
Implement the Base class.
Method signatures and docstrings:
- def __init__(self, cluster_dir, year_id, input_me, output_me): This class incorporates all the functions that all the specific causes use, but all in different sequence
- def get_locatio... | Implement the Python class `Base` described below.
Class description:
Implement the Base class.
Method signatures and docstrings:
- def __init__(self, cluster_dir, year_id, input_me, output_me): This class incorporates all the functions that all the specific causes use, but all in different sequence
- def get_locatio... | 746ea5fb76a9c049c37a8c15aa089c041a90a6d5 | <|skeleton|>
class Base:
def __init__(self, cluster_dir, year_id, input_me, output_me):
"""This class incorporates all the functions that all the specific causes use, but all in different sequence"""
<|body_0|>
def get_locations(self, location_set_id):
"""Pulls the location hierarchy u... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Base:
def __init__(self, cluster_dir, year_id, input_me, output_me):
"""This class incorporates all the functions that all the specific causes use, but all in different sequence"""
self.cluster_dir = cluster_dir
self.year_id = year_id
self.input_me = input_me
self.outpu... | the_stack_v2_python_sparse | nonfatal_code/obstetric_fistula/fistula_zero_out_locations_GATHER.py | Nermin-Ghith/ihme-modeling | train | 0 | |
a43cfac00faeef26915e339301d1118a0b5a8b3c | [
"gdf1.crs = 'epsg:4326'\ngdf2.crs = 'epsg:4326'\nreturn gpd.sjoin(gdf1, gdf2).drop('index_right', axis=1)",
"AREA_SIZE_DIVIDER = 25000\nMIN_BUFFER_SIZE = 3\nMAX_BUFFER_SIZE = 10\nwall_gdf = relevant_floorplan_gdf.loc[relevant_floorplan_gdf['category'] == 'wall'].copy()\narea = wall_gdf.unary_union.buffer(0.01).co... | <|body_start_0|>
gdf1.crs = 'epsg:4326'
gdf2.crs = 'epsg:4326'
return gpd.sjoin(gdf1, gdf2).drop('index_right', axis=1)
<|end_body_0|>
<|body_start_1|>
AREA_SIZE_DIVIDER = 25000
MIN_BUFFER_SIZE = 3
MAX_BUFFER_SIZE = 10
wall_gdf = relevant_floorplan_gdf.loc[releva... | Image structure generator class, to generate windows and doors in walls. | ImageStructureGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageStructureGenerator:
"""Image structure generator class, to generate windows and doors in walls."""
def find_overlap(self, gdf1, gdf2):
"""Find overlap between 2 geodataframes. Args: gdf1: geodataframe of which you want to have the overlapping elements returned gdf2: geodataframe... | stack_v2_sparse_classes_10k_train_001261 | 3,582 | no_license | [
{
"docstring": "Find overlap between 2 geodataframes. Args: gdf1: geodataframe of which you want to have the overlapping elements returned gdf2: geodataframe that the overlap needs to be found against.",
"name": "find_overlap",
"signature": "def find_overlap(self, gdf1, gdf2)"
},
{
"docstring": ... | 3 | stack_v2_sparse_classes_30k_train_002620 | Implement the Python class `ImageStructureGenerator` described below.
Class description:
Image structure generator class, to generate windows and doors in walls.
Method signatures and docstrings:
- def find_overlap(self, gdf1, gdf2): Find overlap between 2 geodataframes. Args: gdf1: geodataframe of which you want to ... | Implement the Python class `ImageStructureGenerator` described below.
Class description:
Image structure generator class, to generate windows and doors in walls.
Method signatures and docstrings:
- def find_overlap(self, gdf1, gdf2): Find overlap between 2 geodataframes. Args: gdf1: geodataframe of which you want to ... | 1b953d87968dac46ebbc9b1d5c254ea9493ee328 | <|skeleton|>
class ImageStructureGenerator:
"""Image structure generator class, to generate windows and doors in walls."""
def find_overlap(self, gdf1, gdf2):
"""Find overlap between 2 geodataframes. Args: gdf1: geodataframe of which you want to have the overlapping elements returned gdf2: geodataframe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ImageStructureGenerator:
"""Image structure generator class, to generate windows and doors in walls."""
def find_overlap(self, gdf1, gdf2):
"""Find overlap between 2 geodataframes. Args: gdf1: geodataframe of which you want to have the overlapping elements returned gdf2: geodataframe that the ove... | the_stack_v2_python_sparse | fmlwright/dataset_builder/ImageStructureGenerator.py | rgresia-umd/fml-wright | train | 0 |
221af954ec827e037fdab8c1c32d0d14bcb7daeb | [
"if self == other:\n return self\nelif type(self) == type(other):\n return type(self)(self.vars | other.vars)\nelif isinstance(other, SymbolicSubringRejectingVarsFunctor):\n if not self.vars & other.vars:\n return other",
"if R is not SR:\n raise NotImplementedError('This functor can only be ap... | <|body_start_0|>
if self == other:
return self
elif type(self) == type(other):
return type(self)(self.vars | other.vars)
elif isinstance(other, SymbolicSubringRejectingVarsFunctor):
if not self.vars & other.vars:
return other
<|end_body_0|>
<|... | SymbolicSubringAcceptingVarsFunctor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SymbolicSubringAcceptingVarsFunctor:
def merge(self, other):
"""Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or ``None``. EXAMPLES:: sage: from sage.symbolic.subring import SymbolicSubring sage: F = SymbolicSubring(accepting_variables=... | stack_v2_sparse_classes_10k_train_001262 | 31,870 | no_license | [
{
"docstring": "Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or ``None``. EXAMPLES:: sage: from sage.symbolic.subring import SymbolicSubring sage: F = SymbolicSubring(accepting_variables=('a',)).construction()[0] sage: G = SymbolicSubring(rejecting_variables=... | 2 | null | Implement the Python class `SymbolicSubringAcceptingVarsFunctor` described below.
Class description:
Implement the SymbolicSubringAcceptingVarsFunctor class.
Method signatures and docstrings:
- def merge(self, other): Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or... | Implement the Python class `SymbolicSubringAcceptingVarsFunctor` described below.
Class description:
Implement the SymbolicSubringAcceptingVarsFunctor class.
Method signatures and docstrings:
- def merge(self, other): Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class SymbolicSubringAcceptingVarsFunctor:
def merge(self, other):
"""Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or ``None``. EXAMPLES:: sage: from sage.symbolic.subring import SymbolicSubring sage: F = SymbolicSubring(accepting_variables=... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SymbolicSubringAcceptingVarsFunctor:
def merge(self, other):
"""Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or ``None``. EXAMPLES:: sage: from sage.symbolic.subring import SymbolicSubring sage: F = SymbolicSubring(accepting_variables=('a',)).constr... | the_stack_v2_python_sparse | sage/src/sage/symbolic/subring.py | bopopescu/geosci | train | 0 | |
d01e533c15be3ffa5d7717e6909ec649a258309c | [
"self.__ops = ops\nself.__nops = len(ops)\nfor iop in range(self.__nops):\n if not isinstance(self.__ops[iop], operator):\n raise Exception('Elements of ops list must be of type operator')\nif self.__nops != len(dims):\n raise Exception('Number of dimensions (%d) must equal number of operators (%d)' % ... | <|body_start_0|>
self.__ops = ops
self.__nops = len(ops)
for iop in range(self.__nops):
if not isinstance(self.__ops[iop], operator):
raise Exception('Elements of ops list must be of type operator')
if self.__nops != len(dims):
raise Exception('Num... | Column operator | colop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class colop:
"""Column operator"""
def __init__(self, ops, dims, epss):
"""colop constructor Parameters: ops - a list of operators used to form the column operator dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows'... | stack_v2_sparse_classes_10k_train_001263 | 13,837 | no_license | [
{
"docstring": "colop constructor Parameters: ops - a list of operators used to form the column operator dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols': 10},...] epss - a list of scalar values to be applied to the outpu... | 4 | stack_v2_sparse_classes_30k_train_000959 | Implement the Python class `colop` described below.
Class description:
Column operator
Method signatures and docstrings:
- def __init__(self, ops, dims, epss): colop constructor Parameters: ops - a list of operators used to form the column operator dims - a list of dictionaries that contain the dimensions of the inpu... | Implement the Python class `colop` described below.
Class description:
Column operator
Method signatures and docstrings:
- def __init__(self, ops, dims, epss): colop constructor Parameters: ops - a list of operators used to form the column operator dims - a list of dictionaries that contain the dimensions of the inpu... | 32a303eddd13385d8778b8bb3b4fbbfbe78bea51 | <|skeleton|>
class colop:
"""Column operator"""
def __init__(self, ops, dims, epss):
"""colop constructor Parameters: ops - a list of operators used to form the column operator dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows'... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class colop:
"""Column operator"""
def __init__(self, ops, dims, epss):
"""colop constructor Parameters: ops - a list of operators used to form the column operator dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols'... | the_stack_v2_python_sparse | opt/linopt/combops.py | ke0m/scaas | train | 2 |
f12f8afcf191d78c912a5d274a50189ab3ade460 | [
"crypto_power = CryptoPower(power_ups=Ursula._default_crypto_powerups)\nif claim_signing_key:\n crypto_power.consume_power_up(SigningPower(pubkey=target_ursula.stamp.as_umbral_pubkey()))\nvladimir = cls(crypto_power=crypto_power, rest_host=target_ursula.rest_information()[0].host, rest_port=target_ursula.rest_in... | <|body_start_0|>
crypto_power = CryptoPower(power_ups=Ursula._default_crypto_powerups)
if claim_signing_key:
crypto_power.consume_power_up(SigningPower(pubkey=target_ursula.stamp.as_umbral_pubkey()))
vladimir = cls(crypto_power=crypto_power, rest_host=target_ursula.rest_information()... | The power of Ursula, but with a heart forged deep in the mountains of Microsoft or a State Actor or whatever. | Vladimir | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vladimir:
"""The power of Ursula, but with a heart forged deep in the mountains of Microsoft or a State Actor or whatever."""
def from_target_ursula(cls, target_ursula, claim_signing_key=False):
"""Sometimes Vladimir seeks to attack or imitate a *specific* target Ursula. TODO: This i... | stack_v2_sparse_classes_10k_train_001264 | 2,381 | no_license | [
{
"docstring": "Sometimes Vladimir seeks to attack or imitate a *specific* target Ursula. TODO: This is probably a more instructive method if it takes a bytes representation instead of the entire Ursula.",
"name": "from_target_ursula",
"signature": "def from_target_ursula(cls, target_ursula, claim_signi... | 2 | stack_v2_sparse_classes_30k_train_005042 | Implement the Python class `Vladimir` described below.
Class description:
The power of Ursula, but with a heart forged deep in the mountains of Microsoft or a State Actor or whatever.
Method signatures and docstrings:
- def from_target_ursula(cls, target_ursula, claim_signing_key=False): Sometimes Vladimir seeks to a... | Implement the Python class `Vladimir` described below.
Class description:
The power of Ursula, but with a heart forged deep in the mountains of Microsoft or a State Actor or whatever.
Method signatures and docstrings:
- def from_target_ursula(cls, target_ursula, claim_signing_key=False): Sometimes Vladimir seeks to a... | 9a8a5ba75c04e14d5f393ebd0a626c046948c003 | <|skeleton|>
class Vladimir:
"""The power of Ursula, but with a heart forged deep in the mountains of Microsoft or a State Actor or whatever."""
def from_target_ursula(cls, target_ursula, claim_signing_key=False):
"""Sometimes Vladimir seeks to attack or imitate a *specific* target Ursula. TODO: This i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Vladimir:
"""The power of Ursula, but with a heart forged deep in the mountains of Microsoft or a State Actor or whatever."""
def from_target_ursula(cls, target_ursula, claim_signing_key=False):
"""Sometimes Vladimir seeks to attack or imitate a *specific* target Ursula. TODO: This is probably a ... | the_stack_v2_python_sparse | nucypher/characters/unlawful.py | OnGridSystems/nucypher | train | 0 |
cc5ab1aaf9dca2627793290b85057c2845a6ed16 | [
"user = get_object_or_404(self.queryset, pk=pk)\nserializer = self.get_serializer(user)\nreturn Response(serializer.data)",
"print(request.version)\nusers = self.queryset.values('id', 'username', 'is_staff')\nreturn Response({'data': users})",
"username = request.data.get('username', None)\npassword = request.d... | <|body_start_0|>
user = get_object_or_404(self.queryset, pk=pk)
serializer = self.get_serializer(user)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
print(request.version)
users = self.queryset.values('id', 'username', 'is_staff')
return Response({'dat... | 通过session确定认证，这个viewset下面的api需要session认证通过才能访问 | UsersViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UsersViewSet:
"""通过session确定认证，这个viewset下面的api需要session认证通过才能访问"""
def retrieve(self, request, pk=None):
"""指定用户信息"""
<|body_0|>
def list(self, request):
"""users列表"""
<|body_1|>
def create(self, request):
"""创建用户"""
<|body_2|>
d... | stack_v2_sparse_classes_10k_train_001265 | 5,186 | no_license | [
{
"docstring": "指定用户信息",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
},
{
"docstring": "users列表",
"name": "list",
"signature": "def list(self, request)"
},
{
"docstring": "创建用户",
"name": "create",
"signature": "def create(self, request)"
},
... | 5 | stack_v2_sparse_classes_30k_train_003738 | Implement the Python class `UsersViewSet` described below.
Class description:
通过session确定认证，这个viewset下面的api需要session认证通过才能访问
Method signatures and docstrings:
- def retrieve(self, request, pk=None): 指定用户信息
- def list(self, request): users列表
- def create(self, request): 创建用户
- def destroy(self, request, pk=None): 删除用户... | Implement the Python class `UsersViewSet` described below.
Class description:
通过session确定认证，这个viewset下面的api需要session认证通过才能访问
Method signatures and docstrings:
- def retrieve(self, request, pk=None): 指定用户信息
- def list(self, request): users列表
- def create(self, request): 创建用户
- def destroy(self, request, pk=None): 删除用户... | 28a0b04ee3b9ca7e2d6e84e522047c63b0d19c8f | <|skeleton|>
class UsersViewSet:
"""通过session确定认证，这个viewset下面的api需要session认证通过才能访问"""
def retrieve(self, request, pk=None):
"""指定用户信息"""
<|body_0|>
def list(self, request):
"""users列表"""
<|body_1|>
def create(self, request):
"""创建用户"""
<|body_2|>
d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UsersViewSet:
"""通过session确定认证，这个viewset下面的api需要session认证通过才能访问"""
def retrieve(self, request, pk=None):
"""指定用户信息"""
user = get_object_or_404(self.queryset, pk=pk)
serializer = self.get_serializer(user)
return Response(serializer.data)
def list(self, request):
... | the_stack_v2_python_sparse | mysite/users/views/users.py | 26huitailang/django-tutorial | train | 1 |
ede13065510e4903d5f52abfd5b7ae28abab7134 | [
"identifier = self.data['id']\nitem = self.core.item_manager.items.get(identifier)\nif not item:\n return self.error(ERROR_ITEM_NOT_FOUND, f'No item found with identifier {identifier}', 404)\nreturn self.json({'item': item.identifier, 'type': item.type, 'states': await item.states.dump()})",
"identifier = self... | <|body_start_0|>
identifier = self.data['id']
item = self.core.item_manager.items.get(identifier)
if not item:
return self.error(ERROR_ITEM_NOT_FOUND, f'No item found with identifier {identifier}', 404)
return self.json({'item': item.identifier, 'type': item.type, 'states': a... | Item states view | ItemStatesView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ItemStatesView:
"""Item states view"""
async def get(self) -> JSONResponse:
"""GET /item/{id}/states"""
<|body_0|>
async def post(self) -> JSONResponse:
"""POST /item/{id}/states"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
identifier = self.... | stack_v2_sparse_classes_10k_train_001266 | 10,547 | permissive | [
{
"docstring": "GET /item/{id}/states",
"name": "get",
"signature": "async def get(self) -> JSONResponse"
},
{
"docstring": "POST /item/{id}/states",
"name": "post",
"signature": "async def post(self) -> JSONResponse"
}
] | 2 | stack_v2_sparse_classes_30k_train_002285 | Implement the Python class `ItemStatesView` described below.
Class description:
Item states view
Method signatures and docstrings:
- async def get(self) -> JSONResponse: GET /item/{id}/states
- async def post(self) -> JSONResponse: POST /item/{id}/states | Implement the Python class `ItemStatesView` described below.
Class description:
Item states view
Method signatures and docstrings:
- async def get(self) -> JSONResponse: GET /item/{id}/states
- async def post(self) -> JSONResponse: POST /item/{id}/states
<|skeleton|>
class ItemStatesView:
"""Item states view"""
... | ee630d3ebf96d5b1d2055487d49968bdbb93d5b9 | <|skeleton|>
class ItemStatesView:
"""Item states view"""
async def get(self) -> JSONResponse:
"""GET /item/{id}/states"""
<|body_0|>
async def post(self) -> JSONResponse:
"""POST /item/{id}/states"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ItemStatesView:
"""Item states view"""
async def get(self) -> JSONResponse:
"""GET /item/{id}/states"""
identifier = self.data['id']
item = self.core.item_manager.items.get(identifier)
if not item:
return self.error(ERROR_ITEM_NOT_FOUND, f'No item found with id... | the_stack_v2_python_sparse | homecontrol/modules/api/endpoints.py | lennart-k/HomeControl | train | 7 |
1a1ed9851ca902d01ba558addcbc9bdcb49e8c6f | [
"for u_file in workspace.iter_files():\n if self.BIB_FILE.search(u_file.name):\n self._check_for_missing_bbl_file(workspace, u_file)",
"base_path, name = os.path.split(u_file.path)\nbase, _ = os.path.splitext(name)\nbbl_file = f'{base}.bbl'\nbbl_path = os.path.join(base_path, bbl_file)\nif workspace.exi... | <|body_start_0|>
for u_file in workspace.iter_files():
if self.BIB_FILE.search(u_file.name):
self._check_for_missing_bbl_file(workspace, u_file)
<|end_body_0|>
<|body_start_1|>
base_path, name = os.path.split(u_file.path)
base, _ = os.path.splitext(name)
bbl_... | Checks for .bib files, and removes them if a .bbl file is present. New modified handling of .bib without .bbl. We no longer delete .bib UNLESS we detect .bbl file. Generate error until we have .bbl. | CheckForMissingReferences | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckForMissingReferences:
"""Checks for .bib files, and removes them if a .bbl file is present. New modified handling of .bib without .bbl. We no longer delete .bib UNLESS we detect .bbl file. Generate error until we have .bbl."""
def check_workspace(self, workspace: Workspace) -> None:
... | stack_v2_sparse_classes_10k_train_001267 | 3,488 | no_license | [
{
"docstring": "Check for a .bib file, and remove if a .bbl file is present.",
"name": "check_workspace",
"signature": "def check_workspace(self, workspace: Workspace) -> None"
},
{
"docstring": "Look for a sibling .bbl file. If found, delete the .bib file. Otherwise, add an error, as this is ve... | 2 | stack_v2_sparse_classes_30k_train_005436 | Implement the Python class `CheckForMissingReferences` described below.
Class description:
Checks for .bib files, and removes them if a .bbl file is present. New modified handling of .bib without .bbl. We no longer delete .bib UNLESS we detect .bbl file. Generate error until we have .bbl.
Method signatures and docstr... | Implement the Python class `CheckForMissingReferences` described below.
Class description:
Checks for .bib files, and removes them if a .bbl file is present. New modified handling of .bib without .bbl. We no longer delete .bib UNLESS we detect .bbl file. Generate error until we have .bbl.
Method signatures and docstr... | dfb71a40125324b1c1f4eb865c84cd9d2e512e6c | <|skeleton|>
class CheckForMissingReferences:
"""Checks for .bib files, and removes them if a .bbl file is present. New modified handling of .bib without .bbl. We no longer delete .bib UNLESS we detect .bbl file. Generate error until we have .bbl."""
def check_workspace(self, workspace: Workspace) -> None:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CheckForMissingReferences:
"""Checks for .bib files, and removes them if a .bbl file is present. New modified handling of .bib without .bbl. We no longer delete .bib UNLESS we detect .bbl file. Generate error until we have .bbl."""
def check_workspace(self, workspace: Workspace) -> None:
"""Check... | the_stack_v2_python_sparse | filemanager/process/check/missing_references.py | arXiv/arxiv-filemanager | train | 5 |
479c8b711df7bd95d1c9d587ade2469d33f3b92f | [
"self.DetectorObj = Detector(light_type, position, angle)\nself.detector_type = self.DetectorObj.detector_type\nself.psd = self.DetectorObj.psd\nself.intensity = self.DetectorObj.intensity\nself.database = self.DetectorObj.database\nself.position = self.DetectorObj.position\nself.angle = self.DetectorObj.angle\nsel... | <|body_start_0|>
self.DetectorObj = Detector(light_type, position, angle)
self.detector_type = self.DetectorObj.detector_type
self.psd = self.DetectorObj.psd
self.intensity = self.DetectorObj.intensity
self.database = self.DetectorObj.database
self.position = self.Detecto... | TestDetectorTypes | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDetectorTypes:
def setUp(self):
"""Setup function TestTypes for class Detector"""
<|body_0|>
def test_types(self):
"""Function to test data types for class Detector"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.DetectorObj = Detector(ligh... | stack_v2_sparse_classes_10k_train_001268 | 1,617 | permissive | [
{
"docstring": "Setup function TestTypes for class Detector",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Function to test data types for class Detector",
"name": "test_types",
"signature": "def test_types(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004063 | Implement the Python class `TestDetectorTypes` described below.
Class description:
Implement the TestDetectorTypes class.
Method signatures and docstrings:
- def setUp(self): Setup function TestTypes for class Detector
- def test_types(self): Function to test data types for class Detector | Implement the Python class `TestDetectorTypes` described below.
Class description:
Implement the TestDetectorTypes class.
Method signatures and docstrings:
- def setUp(self): Setup function TestTypes for class Detector
- def test_types(self): Function to test data types for class Detector
<|skeleton|>
class TestDete... | 825a0eab64be709efe161b9a48eb54c4bc5c1bef | <|skeleton|>
class TestDetectorTypes:
def setUp(self):
"""Setup function TestTypes for class Detector"""
<|body_0|>
def test_types(self):
"""Function to test data types for class Detector"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestDetectorTypes:
def setUp(self):
"""Setup function TestTypes for class Detector"""
self.DetectorObj = Detector(light_type, position, angle)
self.detector_type = self.DetectorObj.detector_type
self.psd = self.DetectorObj.psd
self.intensity = self.DetectorObj.intensity... | the_stack_v2_python_sparse | VLC_devel/class_structure/__auto_gen__/test_Detector.py | wenh81/vlc_simulator | train | 0 | |
c5afd837def6a6ec93ab77a5746a49b3d3ffd86d | [
"self.name = name\nconv2d = functools.partial(LayerConv, w=3, n=[nc, nc], stride=1, padding=padding, use_scaling=use_scaling, relu_slope=relu_slope)\nself.blocks = []\nwith tf.variable_scope(self.name):\n with tf.variable_scope('res0'):\n if use_dropout:\n self.blocks.append(LayerPipe([conv2d('... | <|body_start_0|>
self.name = name
conv2d = functools.partial(LayerConv, w=3, n=[nc, nc], stride=1, padding=padding, use_scaling=use_scaling, relu_slope=relu_slope)
self.blocks = []
with tf.variable_scope(self.name):
with tf.variable_scope('res0'):
if use_dropo... | ResBlock | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResBlock:
def __init__(self, name, nc, norm_layer_constructor, activation, padding='SAME', use_scaling=False, relu_slope=1.0, use_dropout=False):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. nc: 2-tuple of ints, input an... | stack_v2_sparse_classes_10k_train_001269 | 13,442 | permissive | [
{
"docstring": "Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. nc: 2-tuple of ints, input and output channel depths. padding: string, the padding method {SAME, VALID, REFLECT}. use_scaling: bool, whether to use weight norm and scaling. relu_slope: f... | 2 | stack_v2_sparse_classes_30k_train_000429 | Implement the Python class `ResBlock` described below.
Class description:
Implement the ResBlock class.
Method signatures and docstrings:
- def __init__(self, name, nc, norm_layer_constructor, activation, padding='SAME', use_scaling=False, relu_slope=1.0, use_dropout=False): Layer constructor. Args: name: string, lay... | Implement the Python class `ResBlock` described below.
Class description:
Implement the ResBlock class.
Method signatures and docstrings:
- def __init__(self, name, nc, norm_layer_constructor, activation, padding='SAME', use_scaling=False, relu_slope=1.0, use_dropout=False): Layer constructor. Args: name: string, lay... | 091d6ae9e087cf5a6e18b00bce7d8f7ede9d9d08 | <|skeleton|>
class ResBlock:
def __init__(self, name, nc, norm_layer_constructor, activation, padding='SAME', use_scaling=False, relu_slope=1.0, use_dropout=False):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. nc: 2-tuple of ints, input an... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResBlock:
def __init__(self, name, nc, norm_layer_constructor, activation, padding='SAME', use_scaling=False, relu_slope=1.0, use_dropout=False):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. nc: 2-tuple of ints, input and output chann... | the_stack_v2_python_sparse | layers.py | MoustafaMeshry/StEP | train | 6 | |
fe1b68be12c5b5606e3c516dd1543be259d091e3 | [
"data_list = []\nresults = self.query.all()\nformatter = self.request.locale.dates.getFormatter('date', 'short')\nfor result in results:\n data = {}\n data['qid'] = 'm_' + str(result.motion_id)\n data['subject'] = u'M ' + str(result.motion_number) + u' ' + result.short_name\n data['title'] = result.shor... | <|body_start_0|>
data_list = []
results = self.query.all()
formatter = self.request.locale.dates.getFormatter('date', 'short')
for result in results:
data = {}
data['qid'] = 'm_' + str(result.motion_id)
data['subject'] = u'M ' + str(result.motion_numbe... | MotionInStateViewlet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MotionInStateViewlet:
def getData(self):
"""return the data of the query"""
<|body_0|>
def update(self):
"""refresh the query"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data_list = []
results = self.query.all()
formatter = self.... | stack_v2_sparse_classes_10k_train_001270 | 35,739 | no_license | [
{
"docstring": "return the data of the query",
"name": "getData",
"signature": "def getData(self)"
},
{
"docstring": "refresh the query",
"name": "update",
"signature": "def update(self)"
}
] | 2 | null | Implement the Python class `MotionInStateViewlet` described below.
Class description:
Implement the MotionInStateViewlet class.
Method signatures and docstrings:
- def getData(self): return the data of the query
- def update(self): refresh the query | Implement the Python class `MotionInStateViewlet` described below.
Class description:
Implement the MotionInStateViewlet class.
Method signatures and docstrings:
- def getData(self): return the data of the query
- def update(self): refresh the query
<|skeleton|>
class MotionInStateViewlet:
def getData(self):
... | 5cf0ba31dfbff8d2c1b4aa8ab6f69c7a0ae9870d | <|skeleton|>
class MotionInStateViewlet:
def getData(self):
"""return the data of the query"""
<|body_0|>
def update(self):
"""refresh the query"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MotionInStateViewlet:
def getData(self):
"""return the data of the query"""
data_list = []
results = self.query.all()
formatter = self.request.locale.dates.getFormatter('date', 'short')
for result in results:
data = {}
data['qid'] = 'm_' + str(re... | the_stack_v2_python_sparse | bungeni.buildout/branches/bungeni.buildout-refactor-2010-06-02/src/bungeni.main/bungeni/ui/viewlets/workspace.py | malangalanga/bungeni-portal | train | 0 | |
62f2e3555a08a9233e79638ad61e7e08be4ea68c | [
"if not data_kinds:\n data_kinds = [DataKind.WEIGHT_DIFF, DataKind.WEIGHTS]\nsuper().__init__(supported_data_kinds=[DataKind.WEIGHTS, DataKind.WEIGHT_DIFF], data_kinds_to_filter=data_kinds)\nself.exclude_vars = exclude_vars\nself.skip = False\nif self.exclude_vars is not None:\n if not (isinstance(self.exclud... | <|body_start_0|>
if not data_kinds:
data_kinds = [DataKind.WEIGHT_DIFF, DataKind.WEIGHTS]
super().__init__(supported_data_kinds=[DataKind.WEIGHTS, DataKind.WEIGHT_DIFF], data_kinds_to_filter=data_kinds)
self.exclude_vars = exclude_vars
self.skip = False
if self.exclud... | ExcludeVars | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExcludeVars:
def __init__(self, exclude_vars: Union[List[str], str, None]=None, data_kinds: List[str]=None):
"""Exclude/Remove variables from Shareable. Args: exclude_vars (Union[List[str], str, None] , optional): variables/layer names to be excluded. data_kinds: kinds of DXO object to f... | stack_v2_sparse_classes_10k_train_001271 | 4,804 | permissive | [
{
"docstring": "Exclude/Remove variables from Shareable. Args: exclude_vars (Union[List[str], str, None] , optional): variables/layer names to be excluded. data_kinds: kinds of DXO object to filter Notes: Based on different types of exclude_vars, this filter has different behavior: if a list of variable/layer n... | 2 | null | Implement the Python class `ExcludeVars` described below.
Class description:
Implement the ExcludeVars class.
Method signatures and docstrings:
- def __init__(self, exclude_vars: Union[List[str], str, None]=None, data_kinds: List[str]=None): Exclude/Remove variables from Shareable. Args: exclude_vars (Union[List[str]... | Implement the Python class `ExcludeVars` described below.
Class description:
Implement the ExcludeVars class.
Method signatures and docstrings:
- def __init__(self, exclude_vars: Union[List[str], str, None]=None, data_kinds: List[str]=None): Exclude/Remove variables from Shareable. Args: exclude_vars (Union[List[str]... | 1433290c203bd23f34c29e11795ce592bc067888 | <|skeleton|>
class ExcludeVars:
def __init__(self, exclude_vars: Union[List[str], str, None]=None, data_kinds: List[str]=None):
"""Exclude/Remove variables from Shareable. Args: exclude_vars (Union[List[str], str, None] , optional): variables/layer names to be excluded. data_kinds: kinds of DXO object to f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExcludeVars:
def __init__(self, exclude_vars: Union[List[str], str, None]=None, data_kinds: List[str]=None):
"""Exclude/Remove variables from Shareable. Args: exclude_vars (Union[List[str], str, None] , optional): variables/layer names to be excluded. data_kinds: kinds of DXO object to filter Notes: B... | the_stack_v2_python_sparse | nvflare/app_common/filters/exclude_vars.py | NVIDIA/NVFlare | train | 442 | |
c528b65351ac1d5e000c4844dcd29781b8bac9e3 | [
"i, j = (0, len(nums) - 1)\nwhile i < j:\n m = i + (j - i) // 2\n e = 2 * (m // 2)\n o = e + 1\n if nums[e] == nums[o]:\n i = o + 1\n else:\n j = e - 1\nreturn nums[i]",
"if len(nums) == 1:\n return nums[0]\ns, e = (0, (len(nums) + 1) // 2 - 1)\nwhile s <= e:\n m = s + (e - s) /... | <|body_start_0|>
i, j = (0, len(nums) - 1)
while i < j:
m = i + (j - i) // 2
e = 2 * (m // 2)
o = e + 1
if nums[e] == nums[o]:
i = o + 1
else:
j = e - 1
return nums[i]
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def singleNonDuplicate(self, nums: List[int]) -> int:
"""06/03/2020 21:59"""
<|body_0|>
def singleNonDuplicate(self, nums: List[int]) -> int:
"""Nov 30, 2021 21:40"""
<|body_1|>
def singleNonDuplicate(self, nums: List[int]) -> int:
"""N... | stack_v2_sparse_classes_10k_train_001272 | 3,053 | no_license | [
{
"docstring": "06/03/2020 21:59",
"name": "singleNonDuplicate",
"signature": "def singleNonDuplicate(self, nums: List[int]) -> int"
},
{
"docstring": "Nov 30, 2021 21:40",
"name": "singleNonDuplicate",
"signature": "def singleNonDuplicate(self, nums: List[int]) -> int"
},
{
"doc... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def singleNonDuplicate(self, nums: List[int]) -> int: 06/03/2020 21:59
- def singleNonDuplicate(self, nums: List[int]) -> int: Nov 30, 2021 21:40
- def singleNonDuplicate(self, n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def singleNonDuplicate(self, nums: List[int]) -> int: 06/03/2020 21:59
- def singleNonDuplicate(self, nums: List[int]) -> int: Nov 30, 2021 21:40
- def singleNonDuplicate(self, n... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def singleNonDuplicate(self, nums: List[int]) -> int:
"""06/03/2020 21:59"""
<|body_0|>
def singleNonDuplicate(self, nums: List[int]) -> int:
"""Nov 30, 2021 21:40"""
<|body_1|>
def singleNonDuplicate(self, nums: List[int]) -> int:
"""N... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def singleNonDuplicate(self, nums: List[int]) -> int:
"""06/03/2020 21:59"""
i, j = (0, len(nums) - 1)
while i < j:
m = i + (j - i) // 2
e = 2 * (m // 2)
o = e + 1
if nums[e] == nums[o]:
i = o + 1
els... | the_stack_v2_python_sparse | leetcode/solved/540_Single_Element_in_a_Sorted_Array/solution.py | sungminoh/algorithms | train | 0 | |
7d99a8f2d15085cbb9b8f21f29c5400f4f37a6a0 | [
"if sourceSplineObj is None:\n raise TypeError('Expect a spline object got {0}'.format(sourceSplineObj.__class__.__name__))\nif sourceSplineObj.IsInstanceOf(c4d.Onull):\n return None\nif not sourceSplineObj.IsInstanceOf(c4d.Oline) and (not sourceSplineObj.GetInfo() & c4d.OBJECT_ISSPLINE):\n raise TypeError... | <|body_start_0|>
if sourceSplineObj is None:
raise TypeError('Expect a spline object got {0}'.format(sourceSplineObj.__class__.__name__))
if sourceSplineObj.IsInstanceOf(c4d.Onull):
return None
if not sourceSplineObj.IsInstanceOf(c4d.Oline) and (not sourceSplineObj.GetInf... | SplineInputGeneratorHelper | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SplineInputGeneratorHelper:
def FinalSpline(sourceSplineObj):
"""Retrieves the final (deformed) representation of the spline. Args: sourceSplineObj (c4d.BaseObject or c4d.SplineObject or LineObject): A c4d.BaseObject that can be represented as a Spline. Returns: c4d.SplineObject: The fin... | stack_v2_sparse_classes_10k_train_001273 | 14,416 | permissive | [
{
"docstring": "Retrieves the final (deformed) representation of the spline. Args: sourceSplineObj (c4d.BaseObject or c4d.SplineObject or LineObject): A c4d.BaseObject that can be represented as a Spline. Returns: c4d.SplineObject: The final Spline/Line Object, SplineObject should be returned when it's possible... | 4 | stack_v2_sparse_classes_30k_train_000305 | Implement the Python class `SplineInputGeneratorHelper` described below.
Class description:
Implement the SplineInputGeneratorHelper class.
Method signatures and docstrings:
- def FinalSpline(sourceSplineObj): Retrieves the final (deformed) representation of the spline. Args: sourceSplineObj (c4d.BaseObject or c4d.Sp... | Implement the Python class `SplineInputGeneratorHelper` described below.
Class description:
Implement the SplineInputGeneratorHelper class.
Method signatures and docstrings:
- def FinalSpline(sourceSplineObj): Retrieves the final (deformed) representation of the spline. Args: sourceSplineObj (c4d.BaseObject or c4d.Sp... | b1ea3fce533df34094bc3d0bd6460dfb84306e53 | <|skeleton|>
class SplineInputGeneratorHelper:
def FinalSpline(sourceSplineObj):
"""Retrieves the final (deformed) representation of the spline. Args: sourceSplineObj (c4d.BaseObject or c4d.SplineObject or LineObject): A c4d.BaseObject that can be represented as a Spline. Returns: c4d.SplineObject: The fin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SplineInputGeneratorHelper:
def FinalSpline(sourceSplineObj):
"""Retrieves the final (deformed) representation of the spline. Args: sourceSplineObj (c4d.BaseObject or c4d.SplineObject or LineObject): A c4d.BaseObject that can be represented as a Spline. Returns: c4d.SplineObject: The final Spline/Line... | the_stack_v2_python_sparse | plugins/py-osffset_y_spline_r16/py-osffset_y_spline_r16.pyp | PluginCafe/cinema4d_py_sdk_extended | train | 112 | |
bc403fcdd9722d84dd2b72e1f64e8c21370e268f | [
"self.graph = graph\nself.point_dict = dict()\nself.radius = 1.0",
"if root is None:\n algorithm = TreeCenter(self.graph)\n algorithm.run()\n root = algorithm.tree_center[0]\nself.plot(root, 0.0, 2.0 * math.pi, level=0)",
"angle = 0.5 * (left + right)\nx = self.radius * level * math.cos(angle)\ny = sel... | <|body_start_0|>
self.graph = graph
self.point_dict = dict()
self.radius = 1.0
<|end_body_0|>
<|body_start_1|>
if root is None:
algorithm = TreeCenter(self.graph)
algorithm.run()
root = algorithm.tree_center[0]
self.plot(root, 0.0, 2.0 * math.... | Finding the positions of tree nodes in the plane. This is not suitable for large trees (|V| > 1e4) due to numerical errors. For large trees use TreePlotRadiusAngle with fractions. | TreePlot | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreePlot:
"""Finding the positions of tree nodes in the plane. This is not suitable for large trees (|V| > 1e4) due to numerical errors. For large trees use TreePlotRadiusAngle with fractions."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
d... | stack_v2_sparse_classes_10k_train_001274 | 3,663 | permissive | [
{
"docstring": "The algorithm initialization.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self, root=None)"
},
{
"docstring": "Find node positions. Parameters ---------- source : c... | 3 | stack_v2_sparse_classes_30k_val_000132 | Implement the Python class `TreePlot` described below.
Class description:
Finding the positions of tree nodes in the plane. This is not suitable for large trees (|V| > 1e4) due to numerical errors. For large trees use TreePlotRadiusAngle with fractions.
Method signatures and docstrings:
- def __init__(self, graph): T... | Implement the Python class `TreePlot` described below.
Class description:
Finding the positions of tree nodes in the plane. This is not suitable for large trees (|V| > 1e4) due to numerical errors. For large trees use TreePlotRadiusAngle with fractions.
Method signatures and docstrings:
- def __init__(self, graph): T... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class TreePlot:
"""Finding the positions of tree nodes in the plane. This is not suitable for large trees (|V| > 1e4) due to numerical errors. For large trees use TreePlotRadiusAngle with fractions."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TreePlot:
"""Finding the positions of tree nodes in the plane. This is not suitable for large trees (|V| > 1e4) due to numerical errors. For large trees use TreePlotRadiusAngle with fractions."""
def __init__(self, graph):
"""The algorithm initialization."""
self.graph = graph
sel... | the_stack_v2_python_sparse | graphtheory/forests/treeplot.py | kgashok/graphs-dict | train | 0 |
a5df710216898b36bd489aec2be984a72a5188e3 | [
"try:\n verify_token(request.headers)\nexcept Exception as err:\n ns.abort(401, message=err)\ntry:\n dep = dependencias.read(id)\nexcept psycopg2.Error as err:\n ns.abort(400, message=get_msg_pgerror(err))\nexcept EmptySetError:\n ns.abort(404, message=self.dep_not_found)\nexcept Exception as err:\n ... | <|body_start_0|>
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
try:
dep = dependencias.read(id)
except psycopg2.Error as err:
ns.abort(400, message=get_msg_pgerror(err))
except EmptySetError:... | Dependencia | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dependencia:
def get(self, id):
"""Recuperar una dependencia"""
<|body_0|>
def put(self, id):
"""Actualizar una dependencia"""
<|body_1|>
def delete(self, id):
"""Eliminar una dependencia"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_001275 | 6,772 | no_license | [
{
"docstring": "Recuperar una dependencia",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Actualizar una dependencia",
"name": "put",
"signature": "def put(self, id)"
},
{
"docstring": "Eliminar una dependencia",
"name": "delete",
"signature": "def de... | 3 | stack_v2_sparse_classes_30k_train_002857 | Implement the Python class `Dependencia` described below.
Class description:
Implement the Dependencia class.
Method signatures and docstrings:
- def get(self, id): Recuperar una dependencia
- def put(self, id): Actualizar una dependencia
- def delete(self, id): Eliminar una dependencia | Implement the Python class `Dependencia` described below.
Class description:
Implement the Dependencia class.
Method signatures and docstrings:
- def get(self, id): Recuperar una dependencia
- def put(self, id): Actualizar una dependencia
- def delete(self, id): Eliminar una dependencia
<|skeleton|>
class Dependenci... | e00610fac26ef3ca078fd037c0649b70fa0e9a09 | <|skeleton|>
class Dependencia:
def get(self, id):
"""Recuperar una dependencia"""
<|body_0|>
def put(self, id):
"""Actualizar una dependencia"""
<|body_1|>
def delete(self, id):
"""Eliminar una dependencia"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Dependencia:
def get(self, id):
"""Recuperar una dependencia"""
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
try:
dep = dependencias.read(id)
except psycopg2.Error as err:
ns.abort... | the_stack_v2_python_sparse | DOS/soa/service/genl/endpoints/dependencias.py | Telematica/knight-rider | train | 1 | |
c6a89f14f95b00f4923eac9b31d5efc959457afd | [
"if len(initial_counter_block) == prefix_len + counter_len:\n self.nonce = _copy_bytes(None, prefix_len, initial_counter_block)\n 'Nonce; not available if there is a fixed suffix'\nself._state = VoidPointer()\nresult = raw_ctr_lib.CTR_start_operation(block_cipher.get(), c_uint8_ptr(initial_counter_block), c_s... | <|body_start_0|>
if len(initial_counter_block) == prefix_len + counter_len:
self.nonce = _copy_bytes(None, prefix_len, initial_counter_block)
'Nonce; not available if there is a fixed suffix'
self._state = VoidPointer()
result = raw_ctr_lib.CTR_start_operation(block_ciphe... | *CounTeR (CTR)* mode. This mode is very similar to ECB, in that encryption of one block is done independently of all other blocks. Unlike ECB, the block *position* contributes to the encryption and no information leaks about symbol frequency. Each message block is associated to a *counter* which must be unique across a... | CtrMode | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CtrMode:
"""*CounTeR (CTR)* mode. This mode is very similar to ECB, in that encryption of one block is done independently of all other blocks. Unlike ECB, the block *position* contributes to the encryption and no information leaks about symbol frequency. Each message block is associated to a *cou... | stack_v2_sparse_classes_10k_train_001276 | 15,880 | permissive | [
{
"docstring": "Create a new block cipher, configured in CTR mode. :Parameters: block_cipher : C pointer A smart pointer to the low-level block cipher instance. initial_counter_block : bytes/bytearray/memoryview The initial plaintext to use to generate the key stream. It is as large as the cipher block, and it ... | 3 | stack_v2_sparse_classes_30k_train_000024 | Implement the Python class `CtrMode` described below.
Class description:
*CounTeR (CTR)* mode. This mode is very similar to ECB, in that encryption of one block is done independently of all other blocks. Unlike ECB, the block *position* contributes to the encryption and no information leaks about symbol frequency. Eac... | Implement the Python class `CtrMode` described below.
Class description:
*CounTeR (CTR)* mode. This mode is very similar to ECB, in that encryption of one block is done independently of all other blocks. Unlike ECB, the block *position* contributes to the encryption and no information leaks about symbol frequency. Eac... | fa82044a2dc2f0f1f7454f5394e6d68fa923c289 | <|skeleton|>
class CtrMode:
"""*CounTeR (CTR)* mode. This mode is very similar to ECB, in that encryption of one block is done independently of all other blocks. Unlike ECB, the block *position* contributes to the encryption and no information leaks about symbol frequency. Each message block is associated to a *cou... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CtrMode:
"""*CounTeR (CTR)* mode. This mode is very similar to ECB, in that encryption of one block is done independently of all other blocks. Unlike ECB, the block *position* contributes to the encryption and no information leaks about symbol frequency. Each message block is associated to a *counter* which m... | the_stack_v2_python_sparse | venv/lib/python3.6/site-packages/Crypto/Cipher/_mode_ctr.py | masora1030/eigoyurusan | train | 11 |
6c6596da1613c2ae2d0dd27c1024a310728691bd | [
"self.mv_21_mv_71 = mv_21_mv_71\nself.mv_12_mv_22_mv_72 = mv_12_mv_22_mv_72\nself.mv_32 = mv_32\nself.mv_12_we = mv_12_we",
"if dictionary is None:\n return None\nmv_21_mv_71 = meraki_sdk.models.mv_21_mv_71_model.MV21MV71Model.from_dictionary(dictionary.get('MV21/MV71')) if dictionary.get('MV21/MV71') else Non... | <|body_start_0|>
self.mv_21_mv_71 = mv_21_mv_71
self.mv_12_mv_22_mv_72 = mv_12_mv_22_mv_72
self.mv_32 = mv_32
self.mv_12_we = mv_12_we
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
mv_21_mv_71 = meraki_sdk.models.mv_21_mv_71_model.MV21MV7... | Implementation of the 'VideoSettings' model. Video quality and resolution settings for all the camera models. Attributes: mv_21_mv_71 (MV21MV71Model): Quality and resolution for MV21/MV71 camera models. mv_12_mv_22_mv_72 (MV12MV22MV72Model): Quality and resolution for MV12/MV22/MV72 camera models. mv_32 (MV32Model): Qu... | VideoSettingsModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VideoSettingsModel:
"""Implementation of the 'VideoSettings' model. Video quality and resolution settings for all the camera models. Attributes: mv_21_mv_71 (MV21MV71Model): Quality and resolution for MV21/MV71 camera models. mv_12_mv_22_mv_72 (MV12MV22MV72Model): Quality and resolution for MV12/... | stack_v2_sparse_classes_10k_train_001277 | 2,971 | permissive | [
{
"docstring": "Constructor for the VideoSettingsModel class",
"name": "__init__",
"signature": "def __init__(self, mv_21_mv_71=None, mv_12_mv_22_mv_72=None, mv_32=None, mv_12_we=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictio... | 2 | null | Implement the Python class `VideoSettingsModel` described below.
Class description:
Implementation of the 'VideoSettings' model. Video quality and resolution settings for all the camera models. Attributes: mv_21_mv_71 (MV21MV71Model): Quality and resolution for MV21/MV71 camera models. mv_12_mv_22_mv_72 (MV12MV22MV72M... | Implement the Python class `VideoSettingsModel` described below.
Class description:
Implementation of the 'VideoSettings' model. Video quality and resolution settings for all the camera models. Attributes: mv_21_mv_71 (MV21MV71Model): Quality and resolution for MV21/MV71 camera models. mv_12_mv_22_mv_72 (MV12MV22MV72M... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class VideoSettingsModel:
"""Implementation of the 'VideoSettings' model. Video quality and resolution settings for all the camera models. Attributes: mv_21_mv_71 (MV21MV71Model): Quality and resolution for MV21/MV71 camera models. mv_12_mv_22_mv_72 (MV12MV22MV72Model): Quality and resolution for MV12/... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VideoSettingsModel:
"""Implementation of the 'VideoSettings' model. Video quality and resolution settings for all the camera models. Attributes: mv_21_mv_71 (MV21MV71Model): Quality and resolution for MV21/MV71 camera models. mv_12_mv_22_mv_72 (MV12MV22MV72Model): Quality and resolution for MV12/MV22/MV72 cam... | the_stack_v2_python_sparse | meraki_sdk/models/video_settings_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
1c30e177e19b9845715f0ad9a2e0f01622919a2d | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn RiskDetection()",
"from .activity_type import ActivityType\nfrom .entity import Entity\nfrom .risk_detail import RiskDetail\nfrom .risk_detection_timing_type import RiskDetectionTimingType\nfrom .risk_level import RiskLevel\nfrom .risk... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return RiskDetection()
<|end_body_0|>
<|body_start_1|>
from .activity_type import ActivityType
from .entity import Entity
from .risk_detail import RiskDetail
from .risk_detectio... | RiskDetection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection:
"""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... | stack_v2_sparse_classes_10k_train_001278 | 10,613 | 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: RiskDetection",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value... | 3 | stack_v2_sparse_classes_30k_test_000093 | Implement the Python class `RiskDetection` described below.
Class description:
Implement the RiskDetection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection: Creates a new instance of the appropriate class based on discriminator value... | Implement the Python class `RiskDetection` described below.
Class description:
Implement the RiskDetection class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection: Creates a new instance of the appropriate class based on discriminator value... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class RiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection:
"""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... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RiskDetection:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> RiskDetection:
"""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: RiskDetectio... | the_stack_v2_python_sparse | msgraph/generated/models/risk_detection.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e5d1fbd725e3dcfa1fa4c667e06a871641547634 | [
"user = User.objects.create_user(username='some_username', password='some_password', email='some_email@gmail.com')\nProfile.objects.create_player(username='some_username')\nself.client.credentials(HTTP_AUTHORIZATION='Token {}'.format(user.auth_token.key))\nresponse = self.client.get(self.url)\nself.assertEqual(resp... | <|body_start_0|>
user = User.objects.create_user(username='some_username', password='some_password', email='some_email@gmail.com')
Profile.objects.create_player(username='some_username')
self.client.credentials(HTTP_AUTHORIZATION='Token {}'.format(user.auth_token.key))
response = self.cl... | UserViewTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserViewTests:
def test_get_user_details(self):
"""Ensure the user is setup properly and no unwanted details are revealed"""
<|body_0|>
def test_update_user_details(self):
"""Ensure that the change in the fields are saved"""
<|body_1|>
def test_last_seen... | stack_v2_sparse_classes_10k_train_001279 | 13,549 | permissive | [
{
"docstring": "Ensure the user is setup properly and no unwanted details are revealed",
"name": "test_get_user_details",
"signature": "def test_get_user_details(self)"
},
{
"docstring": "Ensure that the change in the fields are saved",
"name": "test_update_user_details",
"signature": "d... | 3 | stack_v2_sparse_classes_30k_train_002903 | Implement the Python class `UserViewTests` described below.
Class description:
Implement the UserViewTests class.
Method signatures and docstrings:
- def test_get_user_details(self): Ensure the user is setup properly and no unwanted details are revealed
- def test_update_user_details(self): Ensure that the change in ... | Implement the Python class `UserViewTests` described below.
Class description:
Implement the UserViewTests class.
Method signatures and docstrings:
- def test_get_user_details(self): Ensure the user is setup properly and no unwanted details are revealed
- def test_update_user_details(self): Ensure that the change in ... | 9fa31e01c8fc3496f92540081a8c078474d59c0f | <|skeleton|>
class UserViewTests:
def test_get_user_details(self):
"""Ensure the user is setup properly and no unwanted details are revealed"""
<|body_0|>
def test_update_user_details(self):
"""Ensure that the change in the fields are saved"""
<|body_1|>
def test_last_seen... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserViewTests:
def test_get_user_details(self):
"""Ensure the user is setup properly and no unwanted details are revealed"""
user = User.objects.create_user(username='some_username', password='some_password', email='some_email@gmail.com')
Profile.objects.create_player(username='some_us... | the_stack_v2_python_sparse | player/tests.py | apoorvaeternity/DirectMe | train | 1 | |
54c4f3520d5d633aec41806b924b17ff1faf61a8 | [
"QtWidgets.QDialog.__init__(self)\nself.findText = QtWidgets.QLineEdit()\nself.replaceText = QtWidgets.QLineEdit()\nself.layout = QtWidgets.QGridLayout(self)\nself.layout.addWidget(self.findText, 0, 1)\nself.layout.addWidget(QtWidgets.QLabel('Text to Find:'), 0, 0)\nself.layout.addWidget(self.replaceText, 1, 1)\nse... | <|body_start_0|>
QtWidgets.QDialog.__init__(self)
self.findText = QtWidgets.QLineEdit()
self.replaceText = QtWidgets.QLineEdit()
self.layout = QtWidgets.QGridLayout(self)
self.layout.addWidget(self.findText, 0, 1)
self.layout.addWidget(QtWidgets.QLabel('Text to Find:'), 0... | A dialog box to retrieve the two text values required by the findAndReplace function. | FindAndReplaceDialogBox | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FindAndReplaceDialogBox:
"""A dialog box to retrieve the two text values required by the findAndReplace function."""
def __init__(self, parent):
"""Initializes the UI and sets the properties."""
<|body_0|>
def getResults(self, parent=None):
"""Returns the user's ... | stack_v2_sparse_classes_10k_train_001280 | 29,548 | no_license | [
{
"docstring": "Initializes the UI and sets the properties.",
"name": "__init__",
"signature": "def __init__(self, parent)"
},
{
"docstring": "Returns the user's input",
"name": "getResults",
"signature": "def getResults(self, parent=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002313 | Implement the Python class `FindAndReplaceDialogBox` described below.
Class description:
A dialog box to retrieve the two text values required by the findAndReplace function.
Method signatures and docstrings:
- def __init__(self, parent): Initializes the UI and sets the properties.
- def getResults(self, parent=None)... | Implement the Python class `FindAndReplaceDialogBox` described below.
Class description:
A dialog box to retrieve the two text values required by the findAndReplace function.
Method signatures and docstrings:
- def __init__(self, parent): Initializes the UI and sets the properties.
- def getResults(self, parent=None)... | 1a3c5ad967472faf66236a311cc07a5128f5f911 | <|skeleton|>
class FindAndReplaceDialogBox:
"""A dialog box to retrieve the two text values required by the findAndReplace function."""
def __init__(self, parent):
"""Initializes the UI and sets the properties."""
<|body_0|>
def getResults(self, parent=None):
"""Returns the user's ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FindAndReplaceDialogBox:
"""A dialog box to retrieve the two text values required by the findAndReplace function."""
def __init__(self, parent):
"""Initializes the UI and sets the properties."""
QtWidgets.QDialog.__init__(self)
self.findText = QtWidgets.QLineEdit()
self.re... | the_stack_v2_python_sparse | datatool/gui/Model.py | scottawalton/datatool | train | 0 |
5816870a201e7830f4752728b303fc9eabcfd0d9 | [
"_wavelet = pywt.Wavelet(wavelet)\nlogger.debug('Calculating wavelet coefficients with {w} wavelet'.format(w=_wavelet.family_name))\n_wavedec = pywt.wavedec(data=x, wavelet=_wavelet, axis=1, level=level)\nreturn cls._subset_coefficients(x=_wavedec, gid_count=x.shape[0], indices=indices)",
"indices = indices or ra... | <|body_start_0|>
_wavelet = pywt.Wavelet(wavelet)
logger.debug('Calculating wavelet coefficients with {w} wavelet'.format(w=_wavelet.family_name))
_wavedec = pywt.wavedec(data=x, wavelet=_wavelet, axis=1, level=level)
return cls._subset_coefficients(x=_wavedec, gid_count=x.shape[0], indi... | Base class for RPM wavelets | RPMWavelets | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RPMWavelets:
"""Base class for RPM wavelets"""
def get_dwt_coefficients(cls, x, wavelet='Haar', level=None, indices=None):
"""Collect wavelet coefficients for time series <x> using mother wavelet <wavelet> at levels <level>. Parameters ---------- x : ndarray time series values wavele... | stack_v2_sparse_classes_10k_train_001281 | 21,915 | permissive | [
{
"docstring": "Collect wavelet coefficients for time series <x> using mother wavelet <wavelet> at levels <level>. Parameters ---------- x : ndarray time series values wavelet : string mother wavelet type level : int optional wavelet computation level indices : ndarray coefficient array levels to keep Returns -... | 2 | stack_v2_sparse_classes_30k_train_006529 | Implement the Python class `RPMWavelets` described below.
Class description:
Base class for RPM wavelets
Method signatures and docstrings:
- def get_dwt_coefficients(cls, x, wavelet='Haar', level=None, indices=None): Collect wavelet coefficients for time series <x> using mother wavelet <wavelet> at levels <level>. Pa... | Implement the Python class `RPMWavelets` described below.
Class description:
Base class for RPM wavelets
Method signatures and docstrings:
- def get_dwt_coefficients(cls, x, wavelet='Haar', level=None, indices=None): Collect wavelet coefficients for time series <x> using mother wavelet <wavelet> at levels <level>. Pa... | 2dd05402c9c05ca0bf7f0e5bc2849ede0d0bc3cb | <|skeleton|>
class RPMWavelets:
"""Base class for RPM wavelets"""
def get_dwt_coefficients(cls, x, wavelet='Haar', level=None, indices=None):
"""Collect wavelet coefficients for time series <x> using mother wavelet <wavelet> at levels <level>. Parameters ---------- x : ndarray time series values wavele... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RPMWavelets:
"""Base class for RPM wavelets"""
def get_dwt_coefficients(cls, x, wavelet='Haar', level=None, indices=None):
"""Collect wavelet coefficients for time series <x> using mother wavelet <wavelet> at levels <level>. Parameters ---------- x : ndarray time series values wavelet : string mo... | the_stack_v2_python_sparse | reVX/rpm/rpm_clusters.py | NREL/reVX | train | 10 |
019c9362a9d03118b14561e470d5de8aafeae4aa | [
"self.id = str(identity)\nself.direction = 'none'\nself.speed = 0",
"self.speed = speed\noutput = '0' + self.id\nif self.speed < 11 and self.speed > -11:\n self.speed = 0\nelif self.speed < 0:\n output += '-'\n self.speed = self.speed * -1\nfor _ in range(4 - len(str(self.speed))):\n output += '0'\nou... | <|body_start_0|>
self.id = str(identity)
self.direction = 'none'
self.speed = 0
<|end_body_0|>
<|body_start_1|>
self.speed = speed
output = '0' + self.id
if self.speed < 11 and self.speed > -11:
self.speed = 0
elif self.speed < 0:
output +... | A Wheel class representing a wheel of the emubot | Wheel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Wheel:
"""A Wheel class representing a wheel of the emubot"""
def __init__(self, identity):
"""Wheel.__init__(ID): parameters - the ID of the wheel"""
<|body_0|>
def move_wheel(self, speed):
"""Move the wheel"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_10k_train_001282 | 2,748 | permissive | [
{
"docstring": "Wheel.__init__(ID): parameters - the ID of the wheel",
"name": "__init__",
"signature": "def __init__(self, identity)"
},
{
"docstring": "Move the wheel",
"name": "move_wheel",
"signature": "def move_wheel(self, speed)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006380 | Implement the Python class `Wheel` described below.
Class description:
A Wheel class representing a wheel of the emubot
Method signatures and docstrings:
- def __init__(self, identity): Wheel.__init__(ID): parameters - the ID of the wheel
- def move_wheel(self, speed): Move the wheel | Implement the Python class `Wheel` described below.
Class description:
A Wheel class representing a wheel of the emubot
Method signatures and docstrings:
- def __init__(self, identity): Wheel.__init__(ID): parameters - the ID of the wheel
- def move_wheel(self, speed): Move the wheel
<|skeleton|>
class Wheel:
""... | a39dc01f7c1213c8079216d49d376b317efbf5f3 | <|skeleton|>
class Wheel:
"""A Wheel class representing a wheel of the emubot"""
def __init__(self, identity):
"""Wheel.__init__(ID): parameters - the ID of the wheel"""
<|body_0|>
def move_wheel(self, speed):
"""Move the wheel"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Wheel:
"""A Wheel class representing a wheel of the emubot"""
def __init__(self, identity):
"""Wheel.__init__(ID): parameters - the ID of the wheel"""
self.id = str(identity)
self.direction = 'none'
self.speed = 0
def move_wheel(self, speed):
"""Move the wheel... | the_stack_v2_python_sparse | Client-Code-2018/CurrentEmuBotCode2/basic_classes.py | maxgodfrey2004/RoboCup-2018-Driving-Code | train | 1 |
54dcc8891439a5350d8ec44525b64eda8554423c | [
"n = len(s)\nm = len(t)\ndp = [[0] * (m + 1) for _ in range(n + 1)]\ni = 0\nwhile i <= n:\n j = 0\n while j <= m:\n if i == j == 0:\n dp[i][j] = 0\n elif s[i - 1] == t[j - 1]:\n dp[i][j] = dp[i - 1][j - 1]\n else:\n dp[i][j] = min([dp[i - 1][j - 1] + 1, dp... | <|body_start_0|>
n = len(s)
m = len(t)
dp = [[0] * (m + 1) for _ in range(n + 1)]
i = 0
while i <= n:
j = 0
while j <= m:
if i == j == 0:
dp[i][j] = 0
elif s[i - 1] == t[j - 1]:
dp[i][... | @param s: a string @param t: a string @return: true if they are both one edit distance apart or false | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""@param s: a string @param t: a string @return: true if they are both one edit distance apart or false"""
def isOneEditDistance(self, s, t):
"""Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) space https://leetcode-cn.com/problems/edit-distance/soluti... | stack_v2_sparse_classes_10k_train_001283 | 1,840 | no_license | [
{
"docstring": "Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) space https://leetcode-cn.com/problems/edit-distance/solution/edit-distance-by-ikaruga/",
"name": "isOneEditDistance",
"signature": "def isOneEditDistance(self, s, t)"
},
{
"docstring": "O(n) runtime, O(1) space... | 2 | null | Implement the Python class `Solution` described below.
Class description:
@param s: a string @param t: a string @return: true if they are both one edit distance apart or false
Method signatures and docstrings:
- def isOneEditDistance(self, s, t): Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) sp... | Implement the Python class `Solution` described below.
Class description:
@param s: a string @param t: a string @return: true if they are both one edit distance apart or false
Method signatures and docstrings:
- def isOneEditDistance(self, s, t): Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) sp... | 3ea03cd8b1fa507553ebee4fd765c4cc4b5814b6 | <|skeleton|>
class Solution:
"""@param s: a string @param t: a string @return: true if they are both one edit distance apart or false"""
def isOneEditDistance(self, s, t):
"""Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) space https://leetcode-cn.com/problems/edit-distance/soluti... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
"""@param s: a string @param t: a string @return: true if they are both one edit distance apart or false"""
def isOneEditDistance(self, s, t):
"""Dynamic Programming solution (not recommended): O(n2) runtime, O(n2) space https://leetcode-cn.com/problems/edit-distance/solution/edit-dista... | the_stack_v2_python_sparse | One_Edit_Distance_14.py | jay6413682/Leetcode | train | 0 |
7ba0a47cf51fc0b55be038ea136715870d3a13e3 | [
"email = form.data.get('email')\nif User.objects.filter(email=email).first():\n messages.info(self.request, 'You already have an account on FireCARES. If you\\'ve forgotten your password or username, use the \"Forgot Password or Username\" links below.')\n return redirect('login')\nif RegistrationWhitelist.i... | <|body_start_0|>
email = form.data.get('email')
if User.objects.filter(email=email).first():
messages.info(self.request, 'You already have an account on FireCARES. If you\'ve forgotten your password or username, use the "Forgot Password or Username" links below.')
return redirec... | Processes account requests. | AccountRequestView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountRequestView:
"""Processes account requests."""
def form_valid(self, form):
"""If the form is valid AND the email is whitelisted, then send to registration; otherwise capture email address."""
<|body_0|>
def form_invalid(self, form):
"""If the form is inval... | stack_v2_sparse_classes_10k_train_001284 | 23,296 | permissive | [
{
"docstring": "If the form is valid AND the email is whitelisted, then send to registration; otherwise capture email address.",
"name": "form_valid",
"signature": "def form_valid(self, form)"
},
{
"docstring": "If the form is invalid, re-render the context data with the data-filled form and err... | 3 | stack_v2_sparse_classes_30k_train_007235 | Implement the Python class `AccountRequestView` described below.
Class description:
Processes account requests.
Method signatures and docstrings:
- def form_valid(self, form): If the form is valid AND the email is whitelisted, then send to registration; otherwise capture email address.
- def form_invalid(self, form):... | Implement the Python class `AccountRequestView` described below.
Class description:
Processes account requests.
Method signatures and docstrings:
- def form_valid(self, form): If the form is valid AND the email is whitelisted, then send to registration; otherwise capture email address.
- def form_invalid(self, form):... | aa708d441790263206dd3a0a480eb6ca9031439d | <|skeleton|>
class AccountRequestView:
"""Processes account requests."""
def form_valid(self, form):
"""If the form is valid AND the email is whitelisted, then send to registration; otherwise capture email address."""
<|body_0|>
def form_invalid(self, form):
"""If the form is inval... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AccountRequestView:
"""Processes account requests."""
def form_valid(self, form):
"""If the form is valid AND the email is whitelisted, then send to registration; otherwise capture email address."""
email = form.data.get('email')
if User.objects.filter(email=email).first():
... | the_stack_v2_python_sparse | firecares/firecares_core/views.py | FireCARES/firecares | train | 12 |
c2b33c3ac0039fdfa820f0eda8b5b2975c5975c4 | [
"self.food = deque(food)\nself.width = width\nself.height = height\nself.bodyQueue = deque([(0, 0)])\nself.hashSet = set([(0, 0)])\nself.score = 0\nself.moveOps = {'U': (-1, 0), 'D': (1, 0), 'L': (0, -1), 'R': (0, 1)}",
"s = self.hashSet\nq = self.bodyQueue\nops = self.moveOps\nwidth = self.width\nheight = self.h... | <|body_start_0|>
self.food = deque(food)
self.width = width
self.height = height
self.bodyQueue = deque([(0, 0)])
self.hashSet = set([(0, 0)])
self.score = 0
self.moveOps = {'U': (-1, 0), 'D': (1, 0), 'L': (0, -1), 'R': (0, 1)}
<|end_body_0|>
<|body_start_1|>
... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""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], t... | stack_v2_sparse_classes_10k_train_001285 | 1,997 | no_license | [
{
"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].",
"name": "__init__",
"signature": "def __init__(self, widt... | 2 | null | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food: List[List[int]]): Initialize your data structure here. @param width - screen width @param height - screen height @param food -... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food: List[List[int]]): Initialize your data structure here. @param width - screen width @param height - screen height @param food -... | 00bf9a8164008aa17507b1c87ce72a3374bcb7b9 | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""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], t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width: int, height: int, food: List[List[int]]):
"""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 a... | the_stack_v2_python_sparse | solutions/353.design-snake-game.py | quixoteji/Leetcode | train | 1 | |
fa749a20fd799ae09726cb63bad95964bdcfb268 | [
"self.machine = machine\nself.text = str(text)\nself._change_callback = None",
"try:\n f = MpfFormatter(self.machine, parameters, False)\n return f.format(self.text)\nexcept Exception as e:\n raise AssertionError('Failed to format {} with {}'.format(self.text, parameters)) from e",
"f = MpfFormatter(se... | <|body_start_0|>
self.machine = machine
self.text = str(text)
self._change_callback = None
<|end_body_0|>
<|body_start_1|>
try:
f = MpfFormatter(self.machine, parameters, False)
return f.format(self.text)
except Exception as e:
raise Assertion... | Text placeholder. | TextTemplate | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextTemplate:
"""Text placeholder."""
def __init__(self, machine: 'MachineController', text: str) -> None:
"""Initialise placeholder."""
<|body_0|>
def evaluate(self, parameters) -> str:
"""Evaluate placeholder to string."""
<|body_1|>
def evaluate_a... | stack_v2_sparse_classes_10k_train_001286 | 32,295 | permissive | [
{
"docstring": "Initialise placeholder.",
"name": "__init__",
"signature": "def __init__(self, machine: 'MachineController', text: str) -> None"
},
{
"docstring": "Evaluate placeholder to string.",
"name": "evaluate",
"signature": "def evaluate(self, parameters) -> str"
},
{
"doc... | 3 | null | Implement the Python class `TextTemplate` described below.
Class description:
Text placeholder.
Method signatures and docstrings:
- def __init__(self, machine: 'MachineController', text: str) -> None: Initialise placeholder.
- def evaluate(self, parameters) -> str: Evaluate placeholder to string.
- def evaluate_and_s... | Implement the Python class `TextTemplate` described below.
Class description:
Text placeholder.
Method signatures and docstrings:
- def __init__(self, machine: 'MachineController', text: str) -> None: Initialise placeholder.
- def evaluate(self, parameters) -> str: Evaluate placeholder to string.
- def evaluate_and_s... | 9f90c8b1586363b65340017bfa3af5d56d32c6d9 | <|skeleton|>
class TextTemplate:
"""Text placeholder."""
def __init__(self, machine: 'MachineController', text: str) -> None:
"""Initialise placeholder."""
<|body_0|>
def evaluate(self, parameters) -> str:
"""Evaluate placeholder to string."""
<|body_1|>
def evaluate_a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TextTemplate:
"""Text placeholder."""
def __init__(self, machine: 'MachineController', text: str) -> None:
"""Initialise placeholder."""
self.machine = machine
self.text = str(text)
self._change_callback = None
def evaluate(self, parameters) -> str:
"""Evaluat... | the_stack_v2_python_sparse | mpf/core/placeholder_manager.py | missionpinball/mpf | train | 191 |
8fd103c2892d529f5fd66ed603ad285900c9f5c9 | [
"nbm = self.notebook_manager\nnbm.restore_checkpoint(notebook_id, checkpoint_id)\nself.set_status(204)\nself.finish()",
"nbm = self.notebook_manager\nnbm.delte_checkpoint(notebook_id, checkpoint_id)\nself.set_status(204)\nself.finish()"
] | <|body_start_0|>
nbm = self.notebook_manager
nbm.restore_checkpoint(notebook_id, checkpoint_id)
self.set_status(204)
self.finish()
<|end_body_0|>
<|body_start_1|>
nbm = self.notebook_manager
nbm.delte_checkpoint(notebook_id, checkpoint_id)
self.set_status(204)
... | ModifyNotebookCheckpointsHandler | [
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModifyNotebookCheckpointsHandler:
def post(self, notebook_id, checkpoint_id):
"""post restores a notebook from a checkpoint"""
<|body_0|>
def delete(self, notebook_id, checkpoint_id):
"""delete clears a checkpoint for a given notebook"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_10k_train_001287 | 5,267 | permissive | [
{
"docstring": "post restores a notebook from a checkpoint",
"name": "post",
"signature": "def post(self, notebook_id, checkpoint_id)"
},
{
"docstring": "delete clears a checkpoint for a given notebook",
"name": "delete",
"signature": "def delete(self, notebook_id, checkpoint_id)"
}
] | 2 | null | Implement the Python class `ModifyNotebookCheckpointsHandler` described below.
Class description:
Implement the ModifyNotebookCheckpointsHandler class.
Method signatures and docstrings:
- def post(self, notebook_id, checkpoint_id): post restores a notebook from a checkpoint
- def delete(self, notebook_id, checkpoint_... | Implement the Python class `ModifyNotebookCheckpointsHandler` described below.
Class description:
Implement the ModifyNotebookCheckpointsHandler class.
Method signatures and docstrings:
- def post(self, notebook_id, checkpoint_id): post restores a notebook from a checkpoint
- def delete(self, notebook_id, checkpoint_... | 2c9002f16bb5c265e0d14f4a2314c86eeaa35cb6 | <|skeleton|>
class ModifyNotebookCheckpointsHandler:
def post(self, notebook_id, checkpoint_id):
"""post restores a notebook from a checkpoint"""
<|body_0|>
def delete(self, notebook_id, checkpoint_id):
"""delete clears a checkpoint for a given notebook"""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ModifyNotebookCheckpointsHandler:
def post(self, notebook_id, checkpoint_id):
"""post restores a notebook from a checkpoint"""
nbm = self.notebook_manager
nbm.restore_checkpoint(notebook_id, checkpoint_id)
self.set_status(204)
self.finish()
def delete(self, noteboo... | the_stack_v2_python_sparse | pkgs/ipython-1.2.1-py27_0/lib/python2.7/site-packages/IPython/html/services/notebooks/handlers.py | wangyum/Anaconda | train | 11 | |
7821f9731758664f91ed28101a4ac3279495276e | [
"temp_feature_keys = column_values\nkeys_features_length = len(temp_feature_keys)\nvariables_length = len(variables)\nfeature_keys = []\nfor i in range(keys_features_length * variables_length):\n quotient = int(i / keys_features_length)\n feature_keys.append(self.variables[quotient] + '_' + temp_feature_keys[... | <|body_start_0|>
temp_feature_keys = column_values
keys_features_length = len(temp_feature_keys)
variables_length = len(variables)
feature_keys = []
for i in range(keys_features_length * variables_length):
quotient = int(i / keys_features_length)
feature_k... | A class that does feature engineering by using the tsfresh package. It also extract the feature keys in order to be able to see the importances of the XGBoost classifier. | FeatureEngineering | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureEngineering:
"""A class that does feature engineering by using the tsfresh package. It also extract the feature keys in order to be able to see the importances of the XGBoost classifier."""
def _construct_feature_keys(self, column_values, variables):
"""Get the column values o... | stack_v2_sparse_classes_10k_train_001288 | 3,951 | no_license | [
{
"docstring": "Get the column values of one of the variables and since they are the same for all the variables because of tsfresh it expands the features by prepending the name of the variable. Parameters ---------- column_values: list A list with the values of the keys returned by tsfresh Returns ------- feat... | 2 | stack_v2_sparse_classes_30k_train_004976 | Implement the Python class `FeatureEngineering` described below.
Class description:
A class that does feature engineering by using the tsfresh package. It also extract the feature keys in order to be able to see the importances of the XGBoost classifier.
Method signatures and docstrings:
- def _construct_feature_keys... | Implement the Python class `FeatureEngineering` described below.
Class description:
A class that does feature engineering by using the tsfresh package. It also extract the feature keys in order to be able to see the importances of the XGBoost classifier.
Method signatures and docstrings:
- def _construct_feature_keys... | d7e42676b64d177ded11d4731e11130c129d477b | <|skeleton|>
class FeatureEngineering:
"""A class that does feature engineering by using the tsfresh package. It also extract the feature keys in order to be able to see the importances of the XGBoost classifier."""
def _construct_feature_keys(self, column_values, variables):
"""Get the column values o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FeatureEngineering:
"""A class that does feature engineering by using the tsfresh package. It also extract the feature keys in order to be able to see the importances of the XGBoost classifier."""
def _construct_feature_keys(self, column_values, variables):
"""Get the column values of one of the ... | the_stack_v2_python_sparse | code/classification/feature_engineering.py | mcbuehler/ssw-prediction | train | 1 |
8276ec5dbe9c157bdb75502dcc89dec1cec3e946 | [
"_, path = url_prefix.split(':')\npath = path.lstrip('/').rstrip('/')\npath_items = path.split('/')\nself.bucket = path_items.pop(0)\nself.prefix = '/'.join(path_items)\nself.s3 = boto3.client('s3')",
"if not os.path.exists(output_dir):\n os.makedirs(output_dir)\nkey = f'{self.prefix}/{file_name}'\noutput_file... | <|body_start_0|>
_, path = url_prefix.split(':')
path = path.lstrip('/').rstrip('/')
path_items = path.split('/')
self.bucket = path_items.pop(0)
self.prefix = '/'.join(path_items)
self.s3 = boto3.client('s3')
<|end_body_0|>
<|body_start_1|>
if not os.path.exists... | Downloader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Downloader:
def __init__(self, url_prefix):
"""URL includes the bucket name and prefix, without filename, ie: s3://my_bucket/path/to/file/"""
<|body_0|>
def download(self, file_name, output_dir):
"""Download file from s3 into given file_path directory file_name: myfi... | stack_v2_sparse_classes_10k_train_001289 | 1,052 | no_license | [
{
"docstring": "URL includes the bucket name and prefix, without filename, ie: s3://my_bucket/path/to/file/",
"name": "__init__",
"signature": "def __init__(self, url_prefix)"
},
{
"docstring": "Download file from s3 into given file_path directory file_name: myfile.zip output_dir: /tmp/",
"n... | 2 | stack_v2_sparse_classes_30k_train_005978 | Implement the Python class `Downloader` described below.
Class description:
Implement the Downloader class.
Method signatures and docstrings:
- def __init__(self, url_prefix): URL includes the bucket name and prefix, without filename, ie: s3://my_bucket/path/to/file/
- def download(self, file_name, output_dir): Downl... | Implement the Python class `Downloader` described below.
Class description:
Implement the Downloader class.
Method signatures and docstrings:
- def __init__(self, url_prefix): URL includes the bucket name and prefix, without filename, ie: s3://my_bucket/path/to/file/
- def download(self, file_name, output_dir): Downl... | 5f673f3238c0d13f2a5401573de0c1dd68e2a53f | <|skeleton|>
class Downloader:
def __init__(self, url_prefix):
"""URL includes the bucket name and prefix, without filename, ie: s3://my_bucket/path/to/file/"""
<|body_0|>
def download(self, file_name, output_dir):
"""Download file from s3 into given file_path directory file_name: myfi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Downloader:
def __init__(self, url_prefix):
"""URL includes the bucket name and prefix, without filename, ie: s3://my_bucket/path/to/file/"""
_, path = url_prefix.split(':')
path = path.lstrip('/').rstrip('/')
path_items = path.split('/')
self.bucket = path_items.pop(0)... | the_stack_v2_python_sparse | importer/downloaders/s3.py | kflavin/importer | train | 0 | |
aaa53f0cccb3c0e1243abf6daa5670d7468b10e5 | [
"super(Crash, self).__init__(Crash.__name__)\nif time is None:\n raise ValueError('Parameter \"time\": a time abstraction object expected but \"None\" value given!')\ncheck_argument_type(Crash.__name__, 'nodes_number', int, nodes_number, self.logger)\nif nodes_number <= 0:\n raise ValueError('Parameter \"node... | <|body_start_0|>
super(Crash, self).__init__(Crash.__name__)
if time is None:
raise ValueError('Parameter "time": a time abstraction object expected but "None" value given!')
check_argument_type(Crash.__name__, 'nodes_number', int, nodes_number, self.logger)
if nodes_number <... | This class implements the process crash model. .. note:: It is presumed that the :meth:`node_failure` method is called at each step of the simulation. | Crash | [
"MIT",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Crash:
"""This class implements the process crash model. .. note:: It is presumed that the :meth:`node_failure` method is called at each step of the simulation."""
def __init__(self, time, nodes_number, crash_probability, maximum_crash_number, total_simulation_steps, transient_steps=0):
... | stack_v2_sparse_classes_10k_train_001290 | 11,001 | permissive | [
{
"docstring": "*Parameters*: - **time**: a simulation time object of the :class:`sim2net._time.Time` class; - **nodes_number** (`int`): the total number of nodes in the simulated network; - **crash_probability** (`float`): the probability that a single process will crash during the total simulation time; - **m... | 3 | stack_v2_sparse_classes_30k_train_002279 | Implement the Python class `Crash` described below.
Class description:
This class implements the process crash model. .. note:: It is presumed that the :meth:`node_failure` method is called at each step of the simulation.
Method signatures and docstrings:
- def __init__(self, time, nodes_number, crash_probability, ma... | Implement the Python class `Crash` described below.
Class description:
This class implements the process crash model. .. note:: It is presumed that the :meth:`node_failure` method is called at each step of the simulation.
Method signatures and docstrings:
- def __init__(self, time, nodes_number, crash_probability, ma... | ed93d1e3067c569dd4194658b0d02da6b0ab4bed | <|skeleton|>
class Crash:
"""This class implements the process crash model. .. note:: It is presumed that the :meth:`node_failure` method is called at each step of the simulation."""
def __init__(self, time, nodes_number, crash_probability, maximum_crash_number, total_simulation_steps, transient_steps=0):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Crash:
"""This class implements the process crash model. .. note:: It is presumed that the :meth:`node_failure` method is called at each step of the simulation."""
def __init__(self, time, nodes_number, crash_probability, maximum_crash_number, total_simulation_steps, transient_steps=0):
"""*Param... | the_stack_v2_python_sparse | sim2net/failure/crash.py | mkalewski/sim2net | train | 14 |
eec269b1d989d34ae5f80122a3d62ee2dd7fe227 | [
"t0 = Triangle()\nself.assertIsNot(t0, None)\nself.assertIsInstance(t0, Triangle)",
"t1 = Triangle([1, 2, 3])\nself.assertIsNot(t1, None)\nself.assertIsInstance(t1, Triangle)\nt2 = Triangle('xyz')\nself.assertIsNot(t2, None)\nself.assertIsInstance(t2, Triangle)\nt3 = Triangle(['x', 'y', 'z'])\nself.assertIsNot(t3... | <|body_start_0|>
t0 = Triangle()
self.assertIsNot(t0, None)
self.assertIsInstance(t0, Triangle)
<|end_body_0|>
<|body_start_1|>
t1 = Triangle([1, 2, 3])
self.assertIsNot(t1, None)
self.assertIsInstance(t1, Triangle)
t2 = Triangle('xyz')
self.assertIsNot(t... | Test Triangle class call | TestConstructor_Triangle | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestConstructor_Triangle:
"""Test Triangle class call"""
def test_none(self):
"""Calling Triangle class with no key (key = None)"""
<|body_0|>
def test_iterable(self):
"""Calling Vertex class with iterable key"""
<|body_1|>
def test_iterable_specific... | stack_v2_sparse_classes_10k_train_001291 | 11,224 | permissive | [
{
"docstring": "Calling Triangle class with no key (key = None)",
"name": "test_none",
"signature": "def test_none(self)"
},
{
"docstring": "Calling Vertex class with iterable key",
"name": "test_iterable",
"signature": "def test_iterable(self)"
},
{
"docstring": "Calling Vertex ... | 3 | stack_v2_sparse_classes_30k_val_000278 | Implement the Python class `TestConstructor_Triangle` described below.
Class description:
Test Triangle class call
Method signatures and docstrings:
- def test_none(self): Calling Triangle class with no key (key = None)
- def test_iterable(self): Calling Vertex class with iterable key
- def test_iterable_specific(sel... | Implement the Python class `TestConstructor_Triangle` described below.
Class description:
Test Triangle class call
Method signatures and docstrings:
- def test_none(self): Calling Triangle class with no key (key = None)
- def test_iterable(self): Calling Vertex class with iterable key
- def test_iterable_specific(sel... | f9b00a39bc16aea4abac60c0dd0aab2acac5adcf | <|skeleton|>
class TestConstructor_Triangle:
"""Test Triangle class call"""
def test_none(self):
"""Calling Triangle class with no key (key = None)"""
<|body_0|>
def test_iterable(self):
"""Calling Vertex class with iterable key"""
<|body_1|>
def test_iterable_specific... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestConstructor_Triangle:
"""Test Triangle class call"""
def test_none(self):
"""Calling Triangle class with no key (key = None)"""
t0 = Triangle()
self.assertIsNot(t0, None)
self.assertIsInstance(t0, Triangle)
def test_iterable(self):
"""Calling Vertex class ... | the_stack_v2_python_sparse | _BACKUPS_V4/v4_5/LightPicture_Test.py | nagame/LightPicture | train | 0 |
351cb3a3bf7348bdaf05dab2e109e3567874f0a1 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('jgrishey', 'jgrishey')\nif trial:\n crimes = list(repo['jgrishey.crime'].find(None, ['lat', 'long']))[:20]\nelse:\n crimes = list(repo['jgrishey.crime'].find(None, ['lat', 'long']))\ncrimes = np.ar... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('jgrishey', 'jgrishey')
if trial:
crimes = list(repo['jgrishey.crime'].find(None, ['lat', 'long']))[:20]
else:
crimes = lis... | kMeansCrime | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class kMeansCrime:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything h... | stack_v2_sparse_classes_10k_train_001292 | 3,668 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_test_000390 | Implement the Python class `kMeansCrime` described below.
Class description:
Implement the kMeansCrime class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTi... | Implement the Python class `kMeansCrime` described below.
Class description:
Implement the kMeansCrime class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTi... | 0df485d0469c5451ebdcd684bed2a0960ba3ab84 | <|skeleton|>
class kMeansCrime:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything h... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class kMeansCrime:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('jgrishey', 'jgrishey')
if trial... | the_stack_v2_python_sparse | jgrishey/kMeansCrime.py | lingyigu/course-2017-spr-proj | train | 0 | |
daa40f592ecc9818acb7844861c0b8aff3cb9c13 | [
"self.safe_views = []\nif hasattr(demo_settings, 'DEMO_SAFE_VIEWS'):\n for view_path in demo_settings.DEMO_SAFE_VIEWS:\n view = self._get_view(view_path)\n self.safe_views.append(view)",
"right_most_dot = view_path.rfind('.')\nmodule_path, view_name = (view_path[:right_most_dot], view_path[right_... | <|body_start_0|>
self.safe_views = []
if hasattr(demo_settings, 'DEMO_SAFE_VIEWS'):
for view_path in demo_settings.DEMO_SAFE_VIEWS:
view = self._get_view(view_path)
self.safe_views.append(view)
<|end_body_0|>
<|body_start_1|>
right_most_dot = view_pat... | Disable all views except those that are explicitly allowed. Safe views are listed in conf/demo_settings.py. | DisabledInDemoModeMiddleware | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DisabledInDemoModeMiddleware:
"""Disable all views except those that are explicitly allowed. Safe views are listed in conf/demo_settings.py."""
def __init__(self):
"""Constructor."""
<|body_0|>
def _get_view(self, view_path):
"""Get the View from the path to help... | stack_v2_sparse_classes_10k_train_001293 | 1,588 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Get the View from the path to help build the list of safe views.",
"name": "_get_view",
"signature": "def _get_view(self, view_path)"
},
{
"docstring": "Override to implement M... | 3 | stack_v2_sparse_classes_30k_train_005377 | Implement the Python class `DisabledInDemoModeMiddleware` described below.
Class description:
Disable all views except those that are explicitly allowed. Safe views are listed in conf/demo_settings.py.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def _get_view(self, view_path): Get the View ... | Implement the Python class `DisabledInDemoModeMiddleware` described below.
Class description:
Disable all views except those that are explicitly allowed. Safe views are listed in conf/demo_settings.py.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def _get_view(self, view_path): Get the View ... | 898936072a716a799462c113286056690a7723d1 | <|skeleton|>
class DisabledInDemoModeMiddleware:
"""Disable all views except those that are explicitly allowed. Safe views are listed in conf/demo_settings.py."""
def __init__(self):
"""Constructor."""
<|body_0|>
def _get_view(self, view_path):
"""Get the View from the path to help... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DisabledInDemoModeMiddleware:
"""Disable all views except those that are explicitly allowed. Safe views are listed in conf/demo_settings.py."""
def __init__(self):
"""Constructor."""
self.safe_views = []
if hasattr(demo_settings, 'DEMO_SAFE_VIEWS'):
for view_path in de... | the_stack_v2_python_sparse | genome_designer/main/middleware.py | RubensZimbres/millstone | train | 1 |
f89ada51cac44a510353917b7303911918fb30c9 | [
"self.surface = pygame.Surface(dim)\nself.rect = rect\nself.width = dim[0] // scale\nself.height = dim[1] // scale\nself.scale = scale\nself.drawsurface = pygame.Surface((self.width, self.height))\nself.drawsurface.fill((0, 0, 0))\nself.array2d = None\nself.fire = None\nself.palette = None\nself.initialize()",
"s... | <|body_start_0|>
self.surface = pygame.Surface(dim)
self.rect = rect
self.width = dim[0] // scale
self.height = dim[1] // scale
self.scale = scale
self.drawsurface = pygame.Surface((self.width, self.height))
self.drawsurface.fill((0, 0, 0))
self.array2d = ... | Simulated Fire, 2d effect idea and basic algorithm from http://lodev.org/cgtutor/fire.html | Fire | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Fire:
"""Simulated Fire, 2d effect idea and basic algorithm from http://lodev.org/cgtutor/fire.html"""
def __init__(self, dim, rect, scale=4):
"""(pygame.surface) surface - to draw on (pygame.Rect) dest - rect to blit fire on (int) width - width of fire (int) height - height of fire ... | stack_v2_sparse_classes_10k_train_001294 | 4,189 | no_license | [
{
"docstring": "(pygame.surface) surface - to draw on (pygame.Rect) dest - rect to blit fire on (int) width - width of fire (int) height - height of fire (int) scale - scale fire",
"name": "__init__",
"signature": "def __init__(self, dim, rect, scale=4)"
},
{
"docstring": "generate palette and s... | 3 | stack_v2_sparse_classes_30k_train_002978 | Implement the Python class `Fire` described below.
Class description:
Simulated Fire, 2d effect idea and basic algorithm from http://lodev.org/cgtutor/fire.html
Method signatures and docstrings:
- def __init__(self, dim, rect, scale=4): (pygame.surface) surface - to draw on (pygame.Rect) dest - rect to blit fire on (... | Implement the Python class `Fire` described below.
Class description:
Simulated Fire, 2d effect idea and basic algorithm from http://lodev.org/cgtutor/fire.html
Method signatures and docstrings:
- def __init__(self, dim, rect, scale=4): (pygame.surface) surface - to draw on (pygame.Rect) dest - rect to blit fire on (... | 1fd421195a2888c0588a49f5a043a1110eedcdbf | <|skeleton|>
class Fire:
"""Simulated Fire, 2d effect idea and basic algorithm from http://lodev.org/cgtutor/fire.html"""
def __init__(self, dim, rect, scale=4):
"""(pygame.surface) surface - to draw on (pygame.Rect) dest - rect to blit fire on (int) width - width of fire (int) height - height of fire ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Fire:
"""Simulated Fire, 2d effect idea and basic algorithm from http://lodev.org/cgtutor/fire.html"""
def __init__(self, dim, rect, scale=4):
"""(pygame.surface) surface - to draw on (pygame.Rect) dest - rect to blit fire on (int) width - width of fire (int) height - height of fire (int) scale -... | the_stack_v2_python_sparse | effects/Fire.py | gunny26/pygame | train | 5 |
2b3a2315d2e725cc090c15d11f5da6a2af57fb67 | [
"try:\n success_log = info.getLogger(module)\n success_log.info(log)\nexcept Exception as e:\n print(e)",
"try:\n error_log = info.getLogger(module)\n error_log.error(log)\nexcept Exception as e:\n print(e)",
"try:\n warning_log = info.getLogger(module)\n warning_log.warning(log)\nexcept... | <|body_start_0|>
try:
success_log = info.getLogger(module)
success_log.info(log)
except Exception as e:
print(e)
<|end_body_0|>
<|body_start_1|>
try:
error_log = info.getLogger(module)
error_log.error(log)
except Exception as e... | Logger | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Logger:
def create_success_log(module: str, log: str) -> None:
"""create success log from this method"""
<|body_0|>
def create_error_log(module: str, log: str):
"""create error log from this method"""
<|body_1|>
def create_warning_log(module: str, log: s... | stack_v2_sparse_classes_10k_train_001295 | 2,056 | no_license | [
{
"docstring": "create success log from this method",
"name": "create_success_log",
"signature": "def create_success_log(module: str, log: str) -> None"
},
{
"docstring": "create error log from this method",
"name": "create_error_log",
"signature": "def create_error_log(module: str, log:... | 4 | stack_v2_sparse_classes_30k_train_003403 | Implement the Python class `Logger` described below.
Class description:
Implement the Logger class.
Method signatures and docstrings:
- def create_success_log(module: str, log: str) -> None: create success log from this method
- def create_error_log(module: str, log: str): create error log from this method
- def crea... | Implement the Python class `Logger` described below.
Class description:
Implement the Logger class.
Method signatures and docstrings:
- def create_success_log(module: str, log: str) -> None: create success log from this method
- def create_error_log(module: str, log: str): create error log from this method
- def crea... | c267cb76c5eacf30d893c4d3d1dcbaa717080471 | <|skeleton|>
class Logger:
def create_success_log(module: str, log: str) -> None:
"""create success log from this method"""
<|body_0|>
def create_error_log(module: str, log: str):
"""create error log from this method"""
<|body_1|>
def create_warning_log(module: str, log: s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Logger:
def create_success_log(module: str, log: str) -> None:
"""create success log from this method"""
try:
success_log = info.getLogger(module)
success_log.info(log)
except Exception as e:
print(e)
def create_error_log(module: str, log: str):... | the_stack_v2_python_sparse | config/logger.py | ganeshsingamaneni/Flask-ordermanagement | train | 0 | |
0c60df827ef68aa87cf300f137aaa9d9d6725dcc | [
"self.disk_to_overwrite = disk_to_overwrite\nself.src_disk = src_disk\nself.target_location = target_location",
"if dictionary is None:\n return None\ndisk_to_overwrite = cohesity_management_sdk.models.virtual_disk_id.VirtualDiskId.from_dictionary(dictionary.get('diskToOverwrite')) if dictionary.get('diskToOve... | <|body_start_0|>
self.disk_to_overwrite = disk_to_overwrite
self.src_disk = src_disk
self.target_location = target_location
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
disk_to_overwrite = cohesity_management_sdk.models.virtual_disk_id.VirtualDi... | Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this will capture the target disk info. NOTE: If this is specified, then power_off_vm_before_recovery must be true. s... | RecoverVirtualDiskParams_VirtualDiskMapping | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecoverVirtualDiskParams_VirtualDiskMapping:
"""Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this will capture the target disk info. NOTE: ... | stack_v2_sparse_classes_10k_train_001296 | 2,838 | permissive | [
{
"docstring": "Constructor for the RecoverVirtualDiskParams_VirtualDiskMapping class",
"name": "__init__",
"signature": "def __init__(self, disk_to_overwrite=None, src_disk=None, target_location=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dict... | 2 | stack_v2_sparse_classes_30k_train_004068 | Implement the Python class `RecoverVirtualDiskParams_VirtualDiskMapping` described below.
Class description:
Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this wi... | Implement the Python class `RecoverVirtualDiskParams_VirtualDiskMapping` described below.
Class description:
Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this wi... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RecoverVirtualDiskParams_VirtualDiskMapping:
"""Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this will capture the target disk info. NOTE: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RecoverVirtualDiskParams_VirtualDiskMapping:
"""Implementation of the 'RecoverVirtualDiskParams_VirtualDiskMapping' model. TODO: type description here. Attributes: disk_to_overwrite (VirtualDiskId): If the user is overwriting a destination disk, then this will capture the target disk info. NOTE: If this is sp... | the_stack_v2_python_sparse | cohesity_management_sdk/models/recover_virtual_disk_params_virtual_disk_mapping.py | cohesity/management-sdk-python | train | 24 |
7bb549de5553836e43f1d8d5c837f3e00b775291 | [
"super(MEltPOSTagger, self).__init__()\nself._melt_command = ''\nself._encoding = encoding\nif language == language_support.KBLanguage.FRENCH:\n model_directory = path.join(MELT_MODEL_DIRECTORY, 'fr')\n self._melt_command = 'python %s -m %s -d %s -l %s -e %s' % (MELT_EXEC, model_directory, path.join(model_dir... | <|body_start_0|>
super(MEltPOSTagger, self).__init__()
self._melt_command = ''
self._encoding = encoding
if language == language_support.KBLanguage.FRENCH:
model_directory = path.join(MELT_MODEL_DIRECTORY, 'fr')
self._melt_command = 'python %s -m %s -d %s -l %s -e... | MElt Part-of-Speech tagger. MElt Part-of-Speech tagger. It currently only supports French (C{keybench.main.language_support.KBLanguage.FRENCH}) and English (C{keybench.main.language_support.KBLanguage.English}). | MEltPOSTagger | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MEltPOSTagger:
"""MElt Part-of-Speech tagger. MElt Part-of-Speech tagger. It currently only supports French (C{keybench.main.language_support.KBLanguage.FRENCH}) and English (C{keybench.main.language_support.KBLanguage.English})."""
def __init__(self, language, encoding):
"""Construc... | stack_v2_sparse_classes_10k_train_001297 | 6,186 | no_license | [
{
"docstring": "Constructor. Args: language: The C{string} name of the language of the data to treat (see C{keybench.main.language_support.KBLanguage}). encoding: The C{string} encoding of the data to treat.",
"name": "__init__",
"signature": "def __init__(self, language, encoding)"
},
{
"docstr... | 2 | stack_v2_sparse_classes_30k_train_000078 | Implement the Python class `MEltPOSTagger` described below.
Class description:
MElt Part-of-Speech tagger. MElt Part-of-Speech tagger. It currently only supports French (C{keybench.main.language_support.KBLanguage.FRENCH}) and English (C{keybench.main.language_support.KBLanguage.English}).
Method signatures and docst... | Implement the Python class `MEltPOSTagger` described below.
Class description:
MElt Part-of-Speech tagger. MElt Part-of-Speech tagger. It currently only supports French (C{keybench.main.language_support.KBLanguage.FRENCH}) and English (C{keybench.main.language_support.KBLanguage.English}).
Method signatures and docst... | a66cf98b11260d2b74cd990f36f5dcde192b0346 | <|skeleton|>
class MEltPOSTagger:
"""MElt Part-of-Speech tagger. MElt Part-of-Speech tagger. It currently only supports French (C{keybench.main.language_support.KBLanguage.FRENCH}) and English (C{keybench.main.language_support.KBLanguage.English})."""
def __init__(self, language, encoding):
"""Construc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MEltPOSTagger:
"""MElt Part-of-Speech tagger. MElt Part-of-Speech tagger. It currently only supports French (C{keybench.main.language_support.KBLanguage.FRENCH}) and English (C{keybench.main.language_support.KBLanguage.English})."""
def __init__(self, language, encoding):
"""Constructor. Args: la... | the_stack_v2_python_sparse | src/keybench/main/nlp_tool/implementation/pos_tagger/melt_pos_tagger.py | Archer-W/KeyBench | train | 0 |
51159822727d1eef0074618b80366d8c8ae8d915 | [
"super(ExamSheetSerializer, self).__init__(*args, **kwargs)\nusers = User.objects.filter(id=self.context['request'].user.id)\nself.fields['owner'].queryset = users",
"queryset = Question.objects.filter(sheet=obj)\nquestions = []\nfor q in queryset:\n questions.append(q.text)\nreturn questions"
] | <|body_start_0|>
super(ExamSheetSerializer, self).__init__(*args, **kwargs)
users = User.objects.filter(id=self.context['request'].user.id)
self.fields['owner'].queryset = users
<|end_body_0|>
<|body_start_1|>
queryset = Question.objects.filter(sheet=obj)
questions = []
... | ExamSheetSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExamSheetSerializer:
def __init__(self, *args, **kwargs):
"""Teacher can only add examsheet with himself as an owner"""
<|body_0|>
def get_questions(self, obj):
"""Simply returns all questions which belongs to this examsheet"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_001298 | 3,922 | no_license | [
{
"docstring": "Teacher can only add examsheet with himself as an owner",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Simply returns all questions which belongs to this examsheet",
"name": "get_questions",
"signature": "def get_questions(self... | 2 | stack_v2_sparse_classes_30k_train_002351 | Implement the Python class `ExamSheetSerializer` described below.
Class description:
Implement the ExamSheetSerializer class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Teacher can only add examsheet with himself as an owner
- def get_questions(self, obj): Simply returns all questions wh... | Implement the Python class `ExamSheetSerializer` described below.
Class description:
Implement the ExamSheetSerializer class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Teacher can only add examsheet with himself as an owner
- def get_questions(self, obj): Simply returns all questions wh... | 2651ac12078c7d5435d1fb23585bb275c974ce30 | <|skeleton|>
class ExamSheetSerializer:
def __init__(self, *args, **kwargs):
"""Teacher can only add examsheet with himself as an owner"""
<|body_0|>
def get_questions(self, obj):
"""Simply returns all questions which belongs to this examsheet"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExamSheetSerializer:
def __init__(self, *args, **kwargs):
"""Teacher can only add examsheet with himself as an owner"""
super(ExamSheetSerializer, self).__init__(*args, **kwargs)
users = User.objects.filter(id=self.context['request'].user.id)
self.fields['owner'].queryset = use... | the_stack_v2_python_sparse | ExamAPI/Sheets/serializers.py | mtyton/ExamSheetEvaluator-API | train | 0 | |
19ef9eafcaee282c20d5097a625eec1dc607db6a | [
"super(InverseGamma, self).__init__(transform)\nself.covariance_prior = False\nself.alpha = alpha\nself.beta = beta",
"if self.transform is not None:\n x = self.transform(x)\nreturn (-self.alpha - 1) * np.log(x) - self.beta / float(x)",
"if self.transform is not None:\n x = self.transform(x)\nreturn x ** ... | <|body_start_0|>
super(InverseGamma, self).__init__(transform)
self.covariance_prior = False
self.alpha = alpha
self.beta = beta
<|end_body_0|>
<|body_start_1|>
if self.transform is not None:
x = self.transform(x)
return (-self.alpha - 1) * np.log(x) - self.b... | Inverse Gamma Distribution ---- This class contains methods relating to the inverse gamma distribution for time series. | InverseGamma | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InverseGamma:
"""Inverse Gamma Distribution ---- This class contains methods relating to the inverse gamma distribution for time series."""
def __init__(self, alpha, beta, transform=None, **kwargs):
"""Parameters ---------- alpha : float Alpha parameter for the Inverse Gamma distribu... | stack_v2_sparse_classes_10k_train_001299 | 1,641 | permissive | [
{
"docstring": "Parameters ---------- alpha : float Alpha parameter for the Inverse Gamma distribution beta : float Beta parameter for the Inverse Gamma distribution transform : str Whether to apply a transformation - e.g. 'exp' or 'logit'",
"name": "__init__",
"signature": "def __init__(self, alpha, be... | 3 | stack_v2_sparse_classes_30k_train_002597 | Implement the Python class `InverseGamma` described below.
Class description:
Inverse Gamma Distribution ---- This class contains methods relating to the inverse gamma distribution for time series.
Method signatures and docstrings:
- def __init__(self, alpha, beta, transform=None, **kwargs): Parameters ---------- alp... | Implement the Python class `InverseGamma` described below.
Class description:
Inverse Gamma Distribution ---- This class contains methods relating to the inverse gamma distribution for time series.
Method signatures and docstrings:
- def __init__(self, alpha, beta, transform=None, **kwargs): Parameters ---------- alp... | f5166854bb4a24c997fc2b9b4e3e37325a740d34 | <|skeleton|>
class InverseGamma:
"""Inverse Gamma Distribution ---- This class contains methods relating to the inverse gamma distribution for time series."""
def __init__(self, alpha, beta, transform=None, **kwargs):
"""Parameters ---------- alpha : float Alpha parameter for the Inverse Gamma distribu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InverseGamma:
"""Inverse Gamma Distribution ---- This class contains methods relating to the inverse gamma distribution for time series."""
def __init__(self, alpha, beta, transform=None, **kwargs):
"""Parameters ---------- alpha : float Alpha parameter for the Inverse Gamma distribution beta : f... | the_stack_v2_python_sparse | pyflux/families/inverse_gamma.py | ecastrow/pyflux | train | 0 |
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