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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
30e95d22f0c92190090e870f6152c549a5e30e74 | [
"super(PretrainedImageEncoding, self).__init__()\nnum_blocks = num_blocks\ncnn = getattr(torchvision.models, cnn_model)(pretrained=True)\nlayers = [cnn.conv1, cnn.bn1, cnn.relu, cnn.maxpool]\nfor i in range(num_blocks):\n name = 'layer%d' % (i + 1)\n layers.append(getattr(cnn, name))\nself.model = torch.nn.Se... | <|body_start_0|>
super(PretrainedImageEncoding, self).__init__()
num_blocks = num_blocks
cnn = getattr(torchvision.models, cnn_model)(pretrained=True)
layers = [cnn.conv1, cnn.bn1, cnn.relu, cnn.maxpool]
for i in range(num_blocks):
name = 'layer%d' % (i + 1)
... | Image encoding using pretrained resnetXX from torchvision. | PretrainedImageEncoding | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PretrainedImageEncoding:
"""Image encoding using pretrained resnetXX from torchvision."""
def __init__(self, cnn_model='resnet18', num_blocks=2):
"""Constructor of the PretrainedImageEncoding class. :param cnn_model: select which resnet pretrained model to load :param num_blocks: num... | stack_v2_sparse_classes_36k_train_021400 | 4,377 | permissive | [
{
"docstring": "Constructor of the PretrainedImageEncoding class. :param cnn_model: select which resnet pretrained model to load :param num_blocks: num of resnet blocks to be used",
"name": "__init__",
"signature": "def __init__(self, cnn_model='resnet18', num_blocks=2)"
},
{
"docstring": "Apply... | 2 | null | Implement the Python class `PretrainedImageEncoding` described below.
Class description:
Image encoding using pretrained resnetXX from torchvision.
Method signatures and docstrings:
- def __init__(self, cnn_model='resnet18', num_blocks=2): Constructor of the PretrainedImageEncoding class. :param cnn_model: select whi... | Implement the Python class `PretrainedImageEncoding` described below.
Class description:
Image encoding using pretrained resnetXX from torchvision.
Method signatures and docstrings:
- def __init__(self, cnn_model='resnet18', num_blocks=2): Constructor of the PretrainedImageEncoding class. :param cnn_model: select whi... | c655c88cc6aec4d0724c19ea95209f1c2dd6770d | <|skeleton|>
class PretrainedImageEncoding:
"""Image encoding using pretrained resnetXX from torchvision."""
def __init__(self, cnn_model='resnet18', num_blocks=2):
"""Constructor of the PretrainedImageEncoding class. :param cnn_model: select which resnet pretrained model to load :param num_blocks: num... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PretrainedImageEncoding:
"""Image encoding using pretrained resnetXX from torchvision."""
def __init__(self, cnn_model='resnet18', num_blocks=2):
"""Constructor of the PretrainedImageEncoding class. :param cnn_model: select which resnet pretrained model to load :param num_blocks: num of resnet bl... | the_stack_v2_python_sparse | models/stacked_attention_vqa/image_encoding.py | aasseman/mi-prometheus | train | 0 |
aff37f6c081fd90494bba0996de2d664e56a4044 | [
"for parser in parsers:\n if parser.media_type in SCIM_CONTENT_TYPES:\n return parser",
"for renderer in renderers:\n if renderer.media_type in SCIM_CONTENT_TYPES:\n return (renderer, renderer.media_type)"
] | <|body_start_0|>
for parser in parsers:
if parser.media_type in SCIM_CONTENT_TYPES:
return parser
<|end_body_0|>
<|body_start_1|>
for renderer in renderers:
if renderer.media_type in SCIM_CONTENT_TYPES:
return (renderer, renderer.media_type)
<|end... | SCIMClientNegotiation | [
"Apache-2.0",
"BUSL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SCIMClientNegotiation:
def select_parser(self, request: Request, parsers):
"""Select the first parser in the `.parser_classes` list."""
<|body_0|>
def select_renderer(self, request: Request, renderers, format_suffix):
"""Select the first renderer in the `.renderer_cl... | stack_v2_sparse_classes_36k_train_021401 | 7,038 | permissive | [
{
"docstring": "Select the first parser in the `.parser_classes` list.",
"name": "select_parser",
"signature": "def select_parser(self, request: Request, parsers)"
},
{
"docstring": "Select the first renderer in the `.renderer_classes` list.",
"name": "select_renderer",
"signature": "def... | 2 | null | Implement the Python class `SCIMClientNegotiation` described below.
Class description:
Implement the SCIMClientNegotiation class.
Method signatures and docstrings:
- def select_parser(self, request: Request, parsers): Select the first parser in the `.parser_classes` list.
- def select_renderer(self, request: Request,... | Implement the Python class `SCIMClientNegotiation` described below.
Class description:
Implement the SCIMClientNegotiation class.
Method signatures and docstrings:
- def select_parser(self, request: Request, parsers): Select the first parser in the `.parser_classes` list.
- def select_renderer(self, request: Request,... | d9dd4f382f96b5c4576b64cbf015db651556c18b | <|skeleton|>
class SCIMClientNegotiation:
def select_parser(self, request: Request, parsers):
"""Select the first parser in the `.parser_classes` list."""
<|body_0|>
def select_renderer(self, request: Request, renderers, format_suffix):
"""Select the first renderer in the `.renderer_cl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SCIMClientNegotiation:
def select_parser(self, request: Request, parsers):
"""Select the first parser in the `.parser_classes` list."""
for parser in parsers:
if parser.media_type in SCIM_CONTENT_TYPES:
return parser
def select_renderer(self, request: Request, ... | the_stack_v2_python_sparse | src/sentry/scim/endpoints/utils.py | nagyist/sentry | train | 0 | |
d4bb48a59e901403ec1aab75b8983dac7f391fdb | [
"self.src = src\nself.exe = exe\nself.cond = cond\nself.dest = dest\nself.mode = mode\nself.optional = optional\nself.strip = strip\nself.blacklist = self.DEFAULT_BLACKLIST\nif blacklist is not None:\n self.blacklist += tuple(blacklist)",
"for pattern in self.blacklist:\n if re.match(pattern, path):\n ... | <|body_start_0|>
self.src = src
self.exe = exe
self.cond = cond
self.dest = dest
self.mode = mode
self.optional = optional
self.strip = strip
self.blacklist = self.DEFAULT_BLACKLIST
if blacklist is not None:
self.blacklist += tuple(blac... | Represents an artifact to be copied from build dir to staging dir. | Path | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Path:
"""Represents an artifact to be copied from build dir to staging dir."""
def __init__(self, src, exe=False, cond=None, dest=None, mode=None, optional=False, strip=True, blacklist=None):
"""Initializes the object. Args: src: The relative path of the artifact. Can be a file or a ... | stack_v2_sparse_classes_36k_train_021402 | 16,433 | permissive | [
{
"docstring": "Initializes the object. Args: src: The relative path of the artifact. Can be a file or a directory. Can be a glob pattern. exe: Identifes the path as either being an executable or containing executables. Executables may be stripped during copy, and have special permissions set. We currently only... | 3 | stack_v2_sparse_classes_30k_train_015046 | Implement the Python class `Path` described below.
Class description:
Represents an artifact to be copied from build dir to staging dir.
Method signatures and docstrings:
- def __init__(self, src, exe=False, cond=None, dest=None, mode=None, optional=False, strip=True, blacklist=None): Initializes the object. Args: sr... | Implement the Python class `Path` described below.
Class description:
Represents an artifact to be copied from build dir to staging dir.
Method signatures and docstrings:
- def __init__(self, src, exe=False, cond=None, dest=None, mode=None, optional=False, strip=True, blacklist=None): Initializes the object. Args: sr... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class Path:
"""Represents an artifact to be copied from build dir to staging dir."""
def __init__(self, src, exe=False, cond=None, dest=None, mode=None, optional=False, strip=True, blacklist=None):
"""Initializes the object. Args: src: The relative path of the artifact. Can be a file or a ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Path:
"""Represents an artifact to be copied from build dir to staging dir."""
def __init__(self, src, exe=False, cond=None, dest=None, mode=None, optional=False, strip=True, blacklist=None):
"""Initializes the object. Args: src: The relative path of the artifact. Can be a file or a directory. Ca... | the_stack_v2_python_sparse | third_party/chromite/lib/chrome_util.py | metux/chromium-suckless | train | 5 |
639c879674e4028b92c59d215b35f7bcf8022c21 | [
"self._scope = []\nfor path in scope:\n if path.startswith('^'):\n self._scope.append(re.compile(path))\n else:\n self._scope.append(path)",
"for exclusion_path in self._scope:\n if hasattr(exclusion_path, 'match'):\n if exclusion_path.match(proj_dir):\n return True\n e... | <|body_start_0|>
self._scope = []
for path in scope:
if path.startswith('^'):
self._scope.append(re.compile(path))
else:
self._scope.append(path)
<|end_body_0|>
<|body_start_1|>
for exclusion_path in self._scope:
if hasattr(exc... | Exclusion scope for a hook. An exclusion scope can be used to determine if a hook has been disabled for a specific project. | ExclusionScope | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExclusionScope:
"""Exclusion scope for a hook. An exclusion scope can be used to determine if a hook has been disabled for a specific project."""
def __init__(self, scope):
"""Initialize. Args: scope: A list of shell-style wildcards (fnmatch) or regular expression. Regular expression... | stack_v2_sparse_classes_36k_train_021403 | 37,276 | no_license | [
{
"docstring": "Initialize. Args: scope: A list of shell-style wildcards (fnmatch) or regular expression. Regular expressions must start with the ^ character.",
"name": "__init__",
"signature": "def __init__(self, scope)"
},
{
"docstring": "Checks if |proj_dir| matches the excluded paths. Args: ... | 2 | stack_v2_sparse_classes_30k_test_000610 | Implement the Python class `ExclusionScope` described below.
Class description:
Exclusion scope for a hook. An exclusion scope can be used to determine if a hook has been disabled for a specific project.
Method signatures and docstrings:
- def __init__(self, scope): Initialize. Args: scope: A list of shell-style wild... | Implement the Python class `ExclusionScope` described below.
Class description:
Exclusion scope for a hook. An exclusion scope can be used to determine if a hook has been disabled for a specific project.
Method signatures and docstrings:
- def __init__(self, scope): Initialize. Args: scope: A list of shell-style wild... | 78a61ca023cbf1a0cecfef8b97df2b274ac3a988 | <|skeleton|>
class ExclusionScope:
"""Exclusion scope for a hook. An exclusion scope can be used to determine if a hook has been disabled for a specific project."""
def __init__(self, scope):
"""Initialize. Args: scope: A list of shell-style wildcards (fnmatch) or regular expression. Regular expression... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExclusionScope:
"""Exclusion scope for a hook. An exclusion scope can be used to determine if a hook has been disabled for a specific project."""
def __init__(self, scope):
"""Initialize. Args: scope: A list of shell-style wildcards (fnmatch) or regular expression. Regular expressions must start ... | the_stack_v2_python_sparse | tools/repohooks/rh/hooks.py | ZYHGOD-1/Aosp11 | train | 0 |
8f7e0dec1976d6cb361cd35f86a6a7b12fd5184f | [
"super(QBCStabilityAgent, self).__init__(candidate_data=candidate_data, seed_data=seed_data, n_query=n_query, hull_distance=hull_distance, parallel=parallel)\nself.alpha = alpha\nself.model = model\nself.n_members = n_members\nself.qbc = QBC(n_members=n_members, training_fraction=training_fraction, model=model)",
... | <|body_start_0|>
super(QBCStabilityAgent, self).__init__(candidate_data=candidate_data, seed_data=seed_data, n_query=n_query, hull_distance=hull_distance, parallel=parallel)
self.alpha = alpha
self.model = model
self.n_members = n_members
self.qbc = QBC(n_members=n_members, train... | Agent which uses QBC to determine optimal hypotheses | QBCStabilityAgent | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QBCStabilityAgent:
"""Agent which uses QBC to determine optimal hypotheses"""
def __init__(self, candidate_data=None, seed_data=None, n_query=1, hull_distance=0.0, parallel=cpu_count(), alpha=0.5, training_fraction=0.5, model=None, n_members=10):
"""Args: candidate_data (DataFrame): ... | stack_v2_sparse_classes_36k_train_021404 | 38,060 | permissive | [
{
"docstring": "Args: candidate_data (DataFrame): data about the candidates seed_data (DataFrame): data which to fit the Agent to n_query (int): number of hypotheses to generate hull_distance (float): hull distance as a criteria for which to deem a given material as \"stable\" parallel (bool): whether to use mu... | 2 | stack_v2_sparse_classes_30k_test_000736 | Implement the Python class `QBCStabilityAgent` described below.
Class description:
Agent which uses QBC to determine optimal hypotheses
Method signatures and docstrings:
- def __init__(self, candidate_data=None, seed_data=None, n_query=1, hull_distance=0.0, parallel=cpu_count(), alpha=0.5, training_fraction=0.5, mode... | Implement the Python class `QBCStabilityAgent` described below.
Class description:
Agent which uses QBC to determine optimal hypotheses
Method signatures and docstrings:
- def __init__(self, candidate_data=None, seed_data=None, n_query=1, hull_distance=0.0, parallel=cpu_count(), alpha=0.5, training_fraction=0.5, mode... | 905f5d577513d1ca5a54fac3d381525e0fe3576a | <|skeleton|>
class QBCStabilityAgent:
"""Agent which uses QBC to determine optimal hypotheses"""
def __init__(self, candidate_data=None, seed_data=None, n_query=1, hull_distance=0.0, parallel=cpu_count(), alpha=0.5, training_fraction=0.5, model=None, n_members=10):
"""Args: candidate_data (DataFrame): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QBCStabilityAgent:
"""Agent which uses QBC to determine optimal hypotheses"""
def __init__(self, candidate_data=None, seed_data=None, n_query=1, hull_distance=0.0, parallel=cpu_count(), alpha=0.5, training_fraction=0.5, model=None, n_members=10):
"""Args: candidate_data (DataFrame): data about th... | the_stack_v2_python_sparse | camd/agent/stability.py | apalizha/CAMD | train | 0 |
c9b26b95d1890e17806162f3c42619bfc8f4636c | [
"header('Access-Control-Allow-Origin', ctx.env.get('HTTP_ORIGIN'))\nheader('Access-Control-Allow-Headers', ctx.env.get('HTTP_ACCESS_CONTROL_REQUEST_HEADERS'))\nheader('Access-Control-Allow-Methods', '*')\nheader('Access-Control-Allow-Credentials', 'true')\nheader('Access-Control-Expose-Headers', 'X-Rucio-Auth-Token... | <|body_start_0|>
header('Access-Control-Allow-Origin', ctx.env.get('HTTP_ORIGIN'))
header('Access-Control-Allow-Headers', ctx.env.get('HTTP_ACCESS_CONTROL_REQUEST_HEADERS'))
header('Access-Control-Allow-Methods', '*')
header('Access-Control-Allow-Credentials', 'true')
header('Acc... | Authenticate a Rucio account temporarily via a GSS token. | GSS | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GSS:
"""Authenticate a Rucio account temporarily via a GSS token."""
def OPTIONS(self):
"""HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication."""
<|body_0|>
def GET(self):
"""HTTP Success: 200 OK HTTP Error: 401 Unauthorized :param Rucio... | stack_v2_sparse_classes_36k_train_021405 | 18,732 | permissive | [
{
"docstring": "HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication.",
"name": "OPTIONS",
"signature": "def OPTIONS(self)"
},
{
"docstring": "HTTP Success: 200 OK HTTP Error: 401 Unauthorized :param Rucio-Account: Account identifier as a string. :param Rucio-AppID: Appli... | 2 | null | Implement the Python class `GSS` described below.
Class description:
Authenticate a Rucio account temporarily via a GSS token.
Method signatures and docstrings:
- def OPTIONS(self): HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication.
- def GET(self): HTTP Success: 200 OK HTTP Error: 401 Unau... | Implement the Python class `GSS` described below.
Class description:
Authenticate a Rucio account temporarily via a GSS token.
Method signatures and docstrings:
- def OPTIONS(self): HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication.
- def GET(self): HTTP Success: 200 OK HTTP Error: 401 Unau... | 355a997a5ea213c427a5d841ab151ceb01073eb4 | <|skeleton|>
class GSS:
"""Authenticate a Rucio account temporarily via a GSS token."""
def OPTIONS(self):
"""HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication."""
<|body_0|>
def GET(self):
"""HTTP Success: 200 OK HTTP Error: 401 Unauthorized :param Rucio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GSS:
"""Authenticate a Rucio account temporarily via a GSS token."""
def OPTIONS(self):
"""HTTP Success: 200 OK Allow cross-site scripting. Explicit for Authentication."""
header('Access-Control-Allow-Origin', ctx.env.get('HTTP_ORIGIN'))
header('Access-Control-Allow-Headers', ctx.... | the_stack_v2_python_sparse | lib/rucio/web/rest/webpy/v1/authentication.py | pujanm/rucio | train | 1 |
721a103147f06d42aad444ed245e06ee090796be | [
"self.parent = list(range(len(ensemble)))\nself.identifiants = {elem: i for i, elem in enumerate(ensemble)}\nself.rang = [0] * len(ensemble)",
"racine = self.identifiants[element]\nelements_rencontres = set()\nwhile self.parent[racine] != racine:\n elements_rencontres.add(racine)\n racine = self.parent[raci... | <|body_start_0|>
self.parent = list(range(len(ensemble)))
self.identifiants = {elem: i for i, elem in enumerate(ensemble)}
self.rang = [0] * len(ensemble)
<|end_body_0|>
<|body_start_1|>
racine = self.identifiants[element]
elements_rencontres = set()
while self.parent[ra... | Implémentation de la structure de données Union-Find. | UnionFind | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnionFind:
"""Implémentation de la structure de données Union-Find."""
def __init__(self, ensemble):
"""Initialisation des structures de données nécessaires."""
<|body_0|>
def find(self, element):
"""Renvoie le numéro de la classe à laquelle appartient l'élément.... | stack_v2_sparse_classes_36k_train_021406 | 2,968 | no_license | [
{
"docstring": "Initialisation des structures de données nécessaires.",
"name": "__init__",
"signature": "def __init__(self, ensemble)"
},
{
"docstring": "Renvoie le numéro de la classe à laquelle appartient l'élément.",
"name": "find",
"signature": "def find(self, element)"
},
{
... | 3 | null | Implement the Python class `UnionFind` described below.
Class description:
Implémentation de la structure de données Union-Find.
Method signatures and docstrings:
- def __init__(self, ensemble): Initialisation des structures de données nécessaires.
- def find(self, element): Renvoie le numéro de la classe à laquelle ... | Implement the Python class `UnionFind` described below.
Class description:
Implémentation de la structure de données Union-Find.
Method signatures and docstrings:
- def __init__(self, ensemble): Initialisation des structures de données nécessaires.
- def find(self, element): Renvoie le numéro de la classe à laquelle ... | 8208f08562a7ea573aa0d010b4b28085e73d0f30 | <|skeleton|>
class UnionFind:
"""Implémentation de la structure de données Union-Find."""
def __init__(self, ensemble):
"""Initialisation des structures de données nécessaires."""
<|body_0|>
def find(self, element):
"""Renvoie le numéro de la classe à laquelle appartient l'élément.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnionFind:
"""Implémentation de la structure de données Union-Find."""
def __init__(self, ensemble):
"""Initialisation des structures de données nécessaires."""
self.parent = list(range(len(ensemble)))
self.identifiants = {elem: i for i, elem in enumerate(ensemble)}
self.r... | the_stack_v2_python_sparse | ComputerScience/AnthonyLabarre/L3-algographes/rendus/2020/rendu02-acpm/unionfind.py | PremierLangage/Yggdrasil | train | 6 |
9a0618a319d26b2bb0507d2fb88a68ef2606fdf9 | [
"context = ssl._create_unverified_context()\nwith request.urlopen(url, context=context) as r:\n return r.read()",
"try:\n if not file:\n file = url.split('/')[-1]\n with open(file, 'wb') as f:\n f.write(NetworkUtil.get(url))\n return True\nexcept Exception as err:\n LogUtil.e('downloa... | <|body_start_0|>
context = ssl._create_unverified_context()
with request.urlopen(url, context=context) as r:
return r.read()
<|end_body_0|>
<|body_start_1|>
try:
if not file:
file = url.split('/')[-1]
with open(file, 'wb') as f:
... | NetworkUtil | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkUtil:
def get(url):
"""获取URL的内容 :param url: URL地址 :return: 网址内容"""
<|body_0|>
def downloadFile(url, file=None):
"""下载文件 :param url: 文件URL地址 :param file: 本地文件路径 :return: True 下载成功"""
<|body_1|>
def downloadPackage(url, downloadFile=None, retryTimes... | stack_v2_sparse_classes_36k_train_021407 | 1,842 | permissive | [
{
"docstring": "获取URL的内容 :param url: URL地址 :return: 网址内容",
"name": "get",
"signature": "def get(url)"
},
{
"docstring": "下载文件 :param url: 文件URL地址 :param file: 本地文件路径 :return: True 下载成功",
"name": "downloadFile",
"signature": "def downloadFile(url, file=None)"
},
{
"docstring": "下载... | 3 | stack_v2_sparse_classes_30k_train_002123 | Implement the Python class `NetworkUtil` described below.
Class description:
Implement the NetworkUtil class.
Method signatures and docstrings:
- def get(url): 获取URL的内容 :param url: URL地址 :return: 网址内容
- def downloadFile(url, file=None): 下载文件 :param url: 文件URL地址 :param file: 本地文件路径 :return: True 下载成功
- def downloadPac... | Implement the Python class `NetworkUtil` described below.
Class description:
Implement the NetworkUtil class.
Method signatures and docstrings:
- def get(url): 获取URL的内容 :param url: URL地址 :return: 网址内容
- def downloadFile(url, file=None): 下载文件 :param url: 文件URL地址 :param file: 本地文件路径 :return: True 下载成功
- def downloadPac... | 24cca5e9aaa56392200da48a1692201e2dfa25c8 | <|skeleton|>
class NetworkUtil:
def get(url):
"""获取URL的内容 :param url: URL地址 :return: 网址内容"""
<|body_0|>
def downloadFile(url, file=None):
"""下载文件 :param url: 文件URL地址 :param file: 本地文件路径 :return: True 下载成功"""
<|body_1|>
def downloadPackage(url, downloadFile=None, retryTimes... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetworkUtil:
def get(url):
"""获取URL的内容 :param url: URL地址 :return: 网址内容"""
context = ssl._create_unverified_context()
with request.urlopen(url, context=context) as r:
return r.read()
def downloadFile(url, file=None):
"""下载文件 :param url: 文件URL地址 :param file: 本地文件... | the_stack_v2_python_sparse | util/NetworkUtil.py | lkl22/CommonTools | train | 2 | |
56c2faa588cefda07595751a68ba5e7a454773bf | [
"idea = self.get_object()\nif self.request.user == idea.conceiver:\n form = process_idea_form(self.request, form)\n messages.success(self.request, _('Your idea has been successfully updated.'))\nelse:\n messages.warning(self.request, _('You are not allowed to update this idea.'))\n return redirect('idea... | <|body_start_0|>
idea = self.get_object()
if self.request.user == idea.conceiver:
form = process_idea_form(self.request, form)
messages.success(self.request, _('Your idea has been successfully updated.'))
else:
messages.warning(self.request, _('You are not all... | Allows only conceivers to update their idea | IdeaUpdateView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IdeaUpdateView:
"""Allows only conceivers to update their idea"""
def form_valid(self, form):
"""Check whether the user logged in is the one updating the idea."""
<|body_0|>
def test_func(self):
"""ensuring the conceiver themselves is updating their idea"""
... | stack_v2_sparse_classes_36k_train_021408 | 11,512 | permissive | [
{
"docstring": "Check whether the user logged in is the one updating the idea.",
"name": "form_valid",
"signature": "def form_valid(self, form)"
},
{
"docstring": "ensuring the conceiver themselves is updating their idea",
"name": "test_func",
"signature": "def test_func(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009600 | Implement the Python class `IdeaUpdateView` described below.
Class description:
Allows only conceivers to update their idea
Method signatures and docstrings:
- def form_valid(self, form): Check whether the user logged in is the one updating the idea.
- def test_func(self): ensuring the conceiver themselves is updatin... | Implement the Python class `IdeaUpdateView` described below.
Class description:
Allows only conceivers to update their idea
Method signatures and docstrings:
- def form_valid(self, form): Check whether the user logged in is the one updating the idea.
- def test_func(self): ensuring the conceiver themselves is updatin... | 9b0819fc999c6f923346b4ac0399bafe58207ab1 | <|skeleton|>
class IdeaUpdateView:
"""Allows only conceivers to update their idea"""
def form_valid(self, form):
"""Check whether the user logged in is the one updating the idea."""
<|body_0|>
def test_func(self):
"""ensuring the conceiver themselves is updating their idea"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IdeaUpdateView:
"""Allows only conceivers to update their idea"""
def form_valid(self, form):
"""Check whether the user logged in is the one updating the idea."""
idea = self.get_object()
if self.request.user == idea.conceiver:
form = process_idea_form(self.request, fo... | the_stack_v2_python_sparse | ideas/views.py | abhiabhi94/idea-fare | train | 0 |
75316ed6b1e36d938bea1e10466f3ba774ddac00 | [
"check_arg(dirpath, u._('Directory path'), str)\ndirpath = safe_decode(dirpath)\nif not os.path.exists(dirpath):\n raise InvalidArgument(u._('Directory path: {path} does not exist').format(path=dirpath))\ndumpfile_path = dump(dirpath)\nreturn dumpfile_path",
"check_arg(dirpath, u._('Directory path'), str)\ndir... | <|body_start_0|>
check_arg(dirpath, u._('Directory path'), str)
dirpath = safe_decode(dirpath)
if not os.path.exists(dirpath):
raise InvalidArgument(u._('Directory path: {path} does not exist').format(path=dirpath))
dumpfile_path = dump(dirpath)
return dumpfile_path
<... | SupportApi | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SupportApi:
def support_dump(self, dirpath):
"""Dumps configuration data for debugging. Dumps most files in /etc/kolla and /usr/share/kolla into a tar file so be given to support / development to help with debugging problems. :param dirpath: path to directory where dump will be placed :t... | stack_v2_sparse_classes_36k_train_021409 | 3,067 | permissive | [
{
"docstring": "Dumps configuration data for debugging. Dumps most files in /etc/kolla and /usr/share/kolla into a tar file so be given to support / development to help with debugging problems. :param dirpath: path to directory where dump will be placed :type dirpath: string :return: path to dump file :rtype: s... | 2 | stack_v2_sparse_classes_30k_train_004346 | Implement the Python class `SupportApi` described below.
Class description:
Implement the SupportApi class.
Method signatures and docstrings:
- def support_dump(self, dirpath): Dumps configuration data for debugging. Dumps most files in /etc/kolla and /usr/share/kolla into a tar file so be given to support / developm... | Implement the Python class `SupportApi` described below.
Class description:
Implement the SupportApi class.
Method signatures and docstrings:
- def support_dump(self, dirpath): Dumps configuration data for debugging. Dumps most files in /etc/kolla and /usr/share/kolla into a tar file so be given to support / developm... | dc38107ff2462f62124b5feab275fa369e223169 | <|skeleton|>
class SupportApi:
def support_dump(self, dirpath):
"""Dumps configuration data for debugging. Dumps most files in /etc/kolla and /usr/share/kolla into a tar file so be given to support / development to help with debugging problems. :param dirpath: path to directory where dump will be placed :t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SupportApi:
def support_dump(self, dirpath):
"""Dumps configuration data for debugging. Dumps most files in /etc/kolla and /usr/share/kolla into a tar file so be given to support / development to help with debugging problems. :param dirpath: path to directory where dump will be placed :type dirpath: s... | the_stack_v2_python_sparse | kolla_cli/api/support.py | iputra/kolla-cli | train | 0 | |
507f3aacc54f026643bb024751df7217ba49a7db | [
"self.cluster_id = cluster_id\nself.cluster_name = cluster_name\nself.cluster_sw_version = cluster_sw_version\nself.healthy_nodes = healthy_nodes\nself.incarnation_id = incarnation_id\nself.message = message\nself.unhealthy_nodes = unhealthy_nodes",
"if dictionary is None:\n return None\ncluster_id = dictionar... | <|body_start_0|>
self.cluster_id = cluster_id
self.cluster_name = cluster_name
self.cluster_sw_version = cluster_sw_version
self.healthy_nodes = healthy_nodes
self.incarnation_id = incarnation_id
self.message = message
self.unhealthy_nodes = unhealthy_nodes
<|end_... | Implementation of the 'CreateClusterResult' model. Specifies the immediate result of a Cluster creation request. Contains validation results for each node. If the request is valid, it also indicates that the individual node bringup operation is started in the background. Attributes: cluster_id (long|int): Specifies the... | CreateClusterResult | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateClusterResult:
"""Implementation of the 'CreateClusterResult' model. Specifies the immediate result of a Cluster creation request. Contains validation results for each node. If the request is valid, it also indicates that the individual node bringup operation is started in the background. A... | stack_v2_sparse_classes_36k_train_021410 | 4,007 | permissive | [
{
"docstring": "Constructor for the CreateClusterResult class",
"name": "__init__",
"signature": "def __init__(self, cluster_id=None, cluster_name=None, cluster_sw_version=None, healthy_nodes=None, incarnation_id=None, message=None, unhealthy_nodes=None)"
},
{
"docstring": "Creates an instance o... | 2 | stack_v2_sparse_classes_30k_train_010575 | Implement the Python class `CreateClusterResult` described below.
Class description:
Implementation of the 'CreateClusterResult' model. Specifies the immediate result of a Cluster creation request. Contains validation results for each node. If the request is valid, it also indicates that the individual node bringup op... | Implement the Python class `CreateClusterResult` described below.
Class description:
Implementation of the 'CreateClusterResult' model. Specifies the immediate result of a Cluster creation request. Contains validation results for each node. If the request is valid, it also indicates that the individual node bringup op... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CreateClusterResult:
"""Implementation of the 'CreateClusterResult' model. Specifies the immediate result of a Cluster creation request. Contains validation results for each node. If the request is valid, it also indicates that the individual node bringup operation is started in the background. A... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateClusterResult:
"""Implementation of the 'CreateClusterResult' model. Specifies the immediate result of a Cluster creation request. Contains validation results for each node. If the request is valid, it also indicates that the individual node bringup operation is started in the background. Attributes: cl... | the_stack_v2_python_sparse | cohesity_management_sdk/models/create_cluster_result.py | cohesity/management-sdk-python | train | 24 |
4f38f6bb13d11c9d185e13a4eb6602637ad00205 | [
"confusion_matrix = metrics.confusion_matrix(test_labels, labels).astype(np.float32)\nconfusion_matrix = confusion_matrix / confusion_matrix.sum(axis=1)[:, np.newaxis]\ndf_cm = pd.DataFrame(confusion_matrix, index=class_names, columns=class_names)\nplt.figure(figsize=(10, 7))\nsns.heatmap(df_cm, annot=True)\nplt.yl... | <|body_start_0|>
confusion_matrix = metrics.confusion_matrix(test_labels, labels).astype(np.float32)
confusion_matrix = confusion_matrix / confusion_matrix.sum(axis=1)[:, np.newaxis]
df_cm = pd.DataFrame(confusion_matrix, index=class_names, columns=class_names)
plt.figure(figsize=(10, 7)... | Visualisation helper for the classifiers. Contains functionality for plotting a confusion matrix from predicted and true labels, and a method for visualising the incorrect classifications. | ClassificationVisualiser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassificationVisualiser:
"""Visualisation helper for the classifiers. Contains functionality for plotting a confusion matrix from predicted and true labels, and a method for visualising the incorrect classifications."""
def plot_confusion_matrix(self, labels, test_labels, class_names, title... | stack_v2_sparse_classes_36k_train_021411 | 3,314 | no_license | [
{
"docstring": "Plots a confusion matrix for the given labels. Parameters ---------- labels : array-like Predicted labels from the classifier. test_labels : array-like Ground truth labels. class_names : array-like The names of the classes in the data. title : str Title of the plot and name of the file.",
"n... | 2 | stack_v2_sparse_classes_30k_train_006546 | Implement the Python class `ClassificationVisualiser` described below.
Class description:
Visualisation helper for the classifiers. Contains functionality for plotting a confusion matrix from predicted and true labels, and a method for visualising the incorrect classifications.
Method signatures and docstrings:
- def... | Implement the Python class `ClassificationVisualiser` described below.
Class description:
Visualisation helper for the classifiers. Contains functionality for plotting a confusion matrix from predicted and true labels, and a method for visualising the incorrect classifications.
Method signatures and docstrings:
- def... | 0e95ca353335acdb2f9e15958c59a1074d705441 | <|skeleton|>
class ClassificationVisualiser:
"""Visualisation helper for the classifiers. Contains functionality for plotting a confusion matrix from predicted and true labels, and a method for visualising the incorrect classifications."""
def plot_confusion_matrix(self, labels, test_labels, class_names, title... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassificationVisualiser:
"""Visualisation helper for the classifiers. Contains functionality for plotting a confusion matrix from predicted and true labels, and a method for visualising the incorrect classifications."""
def plot_confusion_matrix(self, labels, test_labels, class_names, title):
""... | the_stack_v2_python_sparse | action_recognition/classifiers/classification_visualiser.py | CamiloAguilar/openpose-tda-action-recognition | train | 0 |
b21618ed3065593fc20aeb76162cbfd563ac55a7 | [
"func = helper.current_loc()\nself.assertTrue(type(func) is dict)\nself.assertTrue(type(func['latitude']) is float)\nself.assertTrue(type(func['longitude']) is float)",
"func = helper.yelp_by_id('hackbright-academy-san-francisco')\nself.assertTrue(type(func) is dict)\nself.assertEqual(func['name'], 'Hackbright Ac... | <|body_start_0|>
func = helper.current_loc()
self.assertTrue(type(func) is dict)
self.assertTrue(type(func['latitude']) is float)
self.assertTrue(type(func['longitude']) is float)
<|end_body_0|>
<|body_start_1|>
func = helper.yelp_by_id('hackbright-academy-san-francisco')
... | TestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCase:
def test_current_loc(self):
"""tests lat/long function"""
<|body_0|>
def test_yelp_by_id(self):
"""tests that yelp id query works"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
func = helper.current_loc()
self.assertTrue(type(func... | stack_v2_sparse_classes_36k_train_021412 | 8,665 | no_license | [
{
"docstring": "tests lat/long function",
"name": "test_current_loc",
"signature": "def test_current_loc(self)"
},
{
"docstring": "tests that yelp id query works",
"name": "test_yelp_by_id",
"signature": "def test_yelp_by_id(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015472 | Implement the Python class `TestCase` described below.
Class description:
Implement the TestCase class.
Method signatures and docstrings:
- def test_current_loc(self): tests lat/long function
- def test_yelp_by_id(self): tests that yelp id query works | Implement the Python class `TestCase` described below.
Class description:
Implement the TestCase class.
Method signatures and docstrings:
- def test_current_loc(self): tests lat/long function
- def test_yelp_by_id(self): tests that yelp id query works
<|skeleton|>
class TestCase:
def test_current_loc(self):
... | 3c8b87c0f5dd0d77af9d2c2b85886230b01fd9bd | <|skeleton|>
class TestCase:
def test_current_loc(self):
"""tests lat/long function"""
<|body_0|>
def test_yelp_by_id(self):
"""tests that yelp id query works"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCase:
def test_current_loc(self):
"""tests lat/long function"""
func = helper.current_loc()
self.assertTrue(type(func) is dict)
self.assertTrue(type(func['latitude']) is float)
self.assertTrue(type(func['longitude']) is float)
def test_yelp_by_id(self):
... | the_stack_v2_python_sparse | tests.py | Aisling-Dempsey/Haven | train | 3 | |
e1e2074cd9c8f90baffffb2d96d4f32b5f4b0646 | [
"test_jobposting = JobPosting(title='Postdoctoral Researcher', description='Some description', link='http:/jobs.com/awesomejob', active=True)\ntest_jobposting.save()\nself.assertEqual(test_jobposting.pk, 1)",
"test_jobposting = JobPosting(title='Postdoctoral Researcher', description='Some description', link='http... | <|body_start_0|>
test_jobposting = JobPosting(title='Postdoctoral Researcher', description='Some description', link='http:/jobs.com/awesomejob', active=True)
test_jobposting.save()
self.assertEqual(test_jobposting.pk, 1)
<|end_body_0|>
<|body_start_1|>
test_jobposting = JobPosting(title... | Tests the model attributes of ::class:`JobPosting` objects contained in the ::mod:`personnel` app. | JobPostingModelTests | [
"CC0-1.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobPostingModelTests:
"""Tests the model attributes of ::class:`JobPosting` objects contained in the ::mod:`personnel` app."""
def test_create_jobposting_minimal(self):
"""This is a test for creating a new ::class:`JobPosting` object, with only the minimum fields being entered"""
... | stack_v2_sparse_classes_36k_train_021413 | 5,452 | permissive | [
{
"docstring": "This is a test for creating a new ::class:`JobPosting` object, with only the minimum fields being entered",
"name": "test_create_jobposting_minimal",
"signature": "def test_create_jobposting_minimal(self)"
},
{
"docstring": "This is a test for creating a new ::class:`JobPosting` ... | 3 | stack_v2_sparse_classes_30k_train_005741 | Implement the Python class `JobPostingModelTests` described below.
Class description:
Tests the model attributes of ::class:`JobPosting` objects contained in the ::mod:`personnel` app.
Method signatures and docstrings:
- def test_create_jobposting_minimal(self): This is a test for creating a new ::class:`JobPosting` ... | Implement the Python class `JobPostingModelTests` described below.
Class description:
Tests the model attributes of ::class:`JobPosting` objects contained in the ::mod:`personnel` app.
Method signatures and docstrings:
- def test_create_jobposting_minimal(self): This is a test for creating a new ::class:`JobPosting` ... | d6f6c9c068bbf668c253e5943d9514947023e66d | <|skeleton|>
class JobPostingModelTests:
"""Tests the model attributes of ::class:`JobPosting` objects contained in the ::mod:`personnel` app."""
def test_create_jobposting_minimal(self):
"""This is a test for creating a new ::class:`JobPosting` object, with only the minimum fields being entered"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobPostingModelTests:
"""Tests the model attributes of ::class:`JobPosting` objects contained in the ::mod:`personnel` app."""
def test_create_jobposting_minimal(self):
"""This is a test for creating a new ::class:`JobPosting` object, with only the minimum fields being entered"""
test_job... | the_stack_v2_python_sparse | personnel/tests.py | BridgesLab/Lab-Website | train | 0 |
587fcc5493081aa26787413f58e6f8e5d8782256 | [
"adm = ProjektAdministration()\npersons = adm.get_all_persons()\nreturn persons",
"userId = request.args.get('id')\nname = request.args.get('name')\nemail = request.args.get('email')\nadm = ProjektAdministration()\nuser = adm.get_person_by_id(userId)\nuser.set_name(name)\nuser.set_email(email)\nadm.update_person_... | <|body_start_0|>
adm = ProjektAdministration()
persons = adm.get_all_persons()
return persons
<|end_body_0|>
<|body_start_1|>
userId = request.args.get('id')
name = request.args.get('name')
email = request.args.get('email')
adm = ProjektAdministration()
u... | PersonOperationen | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersonOperationen:
def get(self):
"""Auslesen aller Personen-Objekte. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben."""
<|body_0|>
def put(self):
"""Update des User-Objekts."""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_021414 | 29,521 | no_license | [
{
"docstring": "Auslesen aller Personen-Objekte. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Update des User-Objekts.",
"name": "put",
"signature": "def put(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007841 | Implement the Python class `PersonOperationen` described below.
Class description:
Implement the PersonOperationen class.
Method signatures and docstrings:
- def get(self): Auslesen aller Personen-Objekte. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben.
- def put(self): Update des... | Implement the Python class `PersonOperationen` described below.
Class description:
Implement the PersonOperationen class.
Method signatures and docstrings:
- def get(self): Auslesen aller Personen-Objekte. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben.
- def put(self): Update des... | 9014f16fed08956bd28216e1373b60139e5caea1 | <|skeleton|>
class PersonOperationen:
def get(self):
"""Auslesen aller Personen-Objekte. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben."""
<|body_0|>
def put(self):
"""Update des User-Objekts."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PersonOperationen:
def get(self):
"""Auslesen aller Personen-Objekte. Sollten keine User-Objekte verfügbar sein, so wird eine leere Sequenz zurückgegeben."""
adm = ProjektAdministration()
persons = adm.get_all_persons()
return persons
def put(self):
"""Update des U... | the_stack_v2_python_sparse | src/main.py | leanderpeter/university_project_selector | train | 3 | |
e35fcfb888c3e8a56b96e620800fa37a345c1777 | [
"nums.sort()\nans = set()\nfor i in range(len(nums)):\n for j in range(i + 1, len(nums)):\n t = target - nums[i] - nums[j]\n dic = set()\n for k in range(j + 1, len(nums)):\n diff = t - nums[k]\n if diff in dic:\n ans.add((nums[i], nums[j], diff, nums[k])... | <|body_start_0|>
nums.sort()
ans = set()
for i in range(len(nums)):
for j in range(i + 1, len(nums)):
t = target - nums[i] - nums[j]
dic = set()
for k in range(j + 1, len(nums)):
diff = t - nums[k]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_021415 | 2,270 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]]",
"name": "fourSum",
"signature": "def fourSum(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]]",
"name": "fourSum",
"signature": "def fourSum(self, nums... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]]
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]]
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]]"""
nums.sort()
ans = set()
for i in range(len(nums)):
for j in range(i + 1, len(nums)):
t = target - nums[i] - nums[j]
dic =... | the_stack_v2_python_sparse | medium/twopointer/test_18_4Sum.py | wuxu1019/leetcode_sophia | train | 1 | |
c2dad5c69981fc815e3c0878c4b852f0c3da5a04 | [
"f = self.dtype_f(self.init)\nself.AMat.mult(u, f.impl)\nfa = self.init.getVecArray(f.expl)\nxa = self.init.getVecArray(u)\nfor i in range(self.xs, self.xe):\n for j in range(self.ys, self.ye):\n fa[i, j, 0] = -xa[i, j, 0] * xa[i, j, 1] ** 2 + self.A * (1 - xa[i, j, 0])\n fa[i, j, 1] = xa[i, j, 0] ... | <|body_start_0|>
f = self.dtype_f(self.init)
self.AMat.mult(u, f.impl)
fa = self.init.getVecArray(f.expl)
xa = self.init.getVecArray(u)
for i in range(self.xs, self.xe):
for j in range(self.ys, self.ye):
fa[i, j, 0] = -xa[i, j, 0] * xa[i, j, 1] ** 2 + ... | Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc | petsc_grayscott_semiimplicit | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class petsc_grayscott_semiimplicit:
"""Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc"""
def eval_f(self, u, t):
"""Routine to evaluate the RHS Args: u (dtype_u): current values t (float): current time Returns: dtype_f: the... | stack_v2_sparse_classes_36k_train_021416 | 20,605 | permissive | [
{
"docstring": "Routine to evaluate the RHS Args: u (dtype_u): current values t (float): current time Returns: dtype_f: the RHS",
"name": "eval_f",
"signature": "def eval_f(self, u, t)"
},
{
"docstring": "Linear solver for (I-factor*A)u = rhs Args: rhs (dtype_f): right-hand side for the linear s... | 2 | null | Implement the Python class `petsc_grayscott_semiimplicit` described below.
Class description:
Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc
Method signatures and docstrings:
- def eval_f(self, u, t): Routine to evaluate the RHS Args: u (dtype_u): cur... | Implement the Python class `petsc_grayscott_semiimplicit` described below.
Class description:
Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc
Method signatures and docstrings:
- def eval_f(self, u, t): Routine to evaluate the RHS Args: u (dtype_u): cur... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class petsc_grayscott_semiimplicit:
"""Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc"""
def eval_f(self, u, t):
"""Routine to evaluate the RHS Args: u (dtype_u): current values t (float): current time Returns: dtype_f: the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class petsc_grayscott_semiimplicit:
"""Problem class implementing the semi-implicit 2D Gray-Scott reaction-diffusion equation with periodic BC and PETSc"""
def eval_f(self, u, t):
"""Routine to evaluate the RHS Args: u (dtype_u): current values t (float): current time Returns: dtype_f: the RHS"""
... | the_stack_v2_python_sparse | pySDC/implementations/problem_classes/GrayScott_2D_PETSc_periodic.py | Parallel-in-Time/pySDC | train | 30 |
a840284b1be36201f2559685cd4b9e180feaa469 | [
"for event in pygame.event.get():\n if event.type == pygame.QUIT:\n return True\n elif event.type == pygame.KEYUP:\n if self._is_quit_shortcut(event.key):\n return True\n elif event.key == K_b:\n self.vehicle_control_manual_override = not self.vehicle_control_manual_... | <|body_start_0|>
for event in pygame.event.get():
if event.type == pygame.QUIT:
return True
elif event.type == pygame.KEYUP:
if self._is_quit_shortcut(event.key):
return True
elif event.key == K_b:
se... | Handle input events | KeyboardControl | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeyboardControl:
"""Handle input events"""
def parse_events(self, clock):
"""parse an input event"""
<|body_0|>
def _parse_vehicle_keys(self, keys, milliseconds):
"""parse key events"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for event in p... | stack_v2_sparse_classes_36k_train_021417 | 9,713 | permissive | [
{
"docstring": "parse an input event",
"name": "parse_events",
"signature": "def parse_events(self, clock)"
},
{
"docstring": "parse key events",
"name": "_parse_vehicle_keys",
"signature": "def _parse_vehicle_keys(self, keys, milliseconds)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000721 | Implement the Python class `KeyboardControl` described below.
Class description:
Handle input events
Method signatures and docstrings:
- def parse_events(self, clock): parse an input event
- def _parse_vehicle_keys(self, keys, milliseconds): parse key events | Implement the Python class `KeyboardControl` described below.
Class description:
Handle input events
Method signatures and docstrings:
- def parse_events(self, clock): parse an input event
- def _parse_vehicle_keys(self, keys, milliseconds): parse key events
<|skeleton|>
class KeyboardControl:
"""Handle input ev... | 020704a3b7087bc426f5ff97655c7e676c8b01bf | <|skeleton|>
class KeyboardControl:
"""Handle input events"""
def parse_events(self, clock):
"""parse an input event"""
<|body_0|>
def _parse_vehicle_keys(self, keys, milliseconds):
"""parse key events"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KeyboardControl:
"""Handle input events"""
def parse_events(self, clock):
"""parse an input event"""
for event in pygame.event.get():
if event.type == pygame.QUIT:
return True
elif event.type == pygame.KEYUP:
if self._is_quit_shortcu... | the_stack_v2_python_sparse | telecarla_manual_control/src/telecarla_manual_control_ctrl.py | Intuitio-OU/telecarla | train | 0 |
bb079f4259e17cd96abdf91270557d437c874948 | [
"seconds = int(3600 * hours)\ndays, seconds = divmod(seconds, 86400)\nhours, seconds = divmod(seconds, 3600)\nminutes, seconds = divmod(seconds, 60)\nif days > 0:\n return '%dd %dh %dm' % (days, hours, minutes)\nif hours > 0:\n return '%dh %dm' % (hours, minutes)\nreturn '%dm' % minutes",
"if len(period) !=... | <|body_start_0|>
seconds = int(3600 * hours)
days, seconds = divmod(seconds, 86400)
hours, seconds = divmod(seconds, 3600)
minutes, seconds = divmod(seconds, 60)
if days > 0:
return '%dd %dh %dm' % (days, hours, minutes)
if hours > 0:
return '%dh %... | Static methods to make the HistoryStatsSensor code lighter. | HistoryStatsHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HistoryStatsHelper:
"""Static methods to make the HistoryStatsSensor code lighter."""
def pretty_duration(hours):
"""Format a duration in days, hours, minutes, seconds."""
<|body_0|>
def pretty_ratio(value, period):
"""Format the ratio of value / period duration.... | stack_v2_sparse_classes_36k_train_021418 | 11,604 | permissive | [
{
"docstring": "Format a duration in days, hours, minutes, seconds.",
"name": "pretty_duration",
"signature": "def pretty_duration(hours)"
},
{
"docstring": "Format the ratio of value / period duration.",
"name": "pretty_ratio",
"signature": "def pretty_ratio(value, period)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_006325 | Implement the Python class `HistoryStatsHelper` described below.
Class description:
Static methods to make the HistoryStatsSensor code lighter.
Method signatures and docstrings:
- def pretty_duration(hours): Format a duration in days, hours, minutes, seconds.
- def pretty_ratio(value, period): Format the ratio of val... | Implement the Python class `HistoryStatsHelper` described below.
Class description:
Static methods to make the HistoryStatsSensor code lighter.
Method signatures and docstrings:
- def pretty_duration(hours): Format a duration in days, hours, minutes, seconds.
- def pretty_ratio(value, period): Format the ratio of val... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class HistoryStatsHelper:
"""Static methods to make the HistoryStatsSensor code lighter."""
def pretty_duration(hours):
"""Format a duration in days, hours, minutes, seconds."""
<|body_0|>
def pretty_ratio(value, period):
"""Format the ratio of value / period duration.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HistoryStatsHelper:
"""Static methods to make the HistoryStatsSensor code lighter."""
def pretty_duration(hours):
"""Format a duration in days, hours, minutes, seconds."""
seconds = int(3600 * hours)
days, seconds = divmod(seconds, 86400)
hours, seconds = divmod(seconds, 3... | the_stack_v2_python_sparse | homeassistant/components/history_stats/sensor.py | BenWoodford/home-assistant | train | 11 |
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_36k_train_021419 | 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 | stack_v2_sparse_classes_30k_train_016755 | 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_36k | 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 | |
e0e78dbfe4fd009bfd60945323fdb6255f4c53fb | [
"self._header_state = {}\nheader_key_list = DEFAULT_HEADER_KEY_LIST\nfor header_key in header_key_list:\n self._header_state[header_key] = None\nself._metadata_extracted = False\nif DataSetDriverConfigKeys.PARTICLE_CLASSES_DICT in config:\n particle_classes_dict = config.get(DataSetDriverConfigKeys.PARTICLE_C... | <|body_start_0|>
self._header_state = {}
header_key_list = DEFAULT_HEADER_KEY_LIST
for header_key in header_key_list:
self._header_state[header_key] = None
self._metadata_extracted = False
if DataSetDriverConfigKeys.PARTICLE_CLASSES_DICT in config:
particl... | NutnrJCsppParser | [
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NutnrJCsppParser:
def __init__(self, config, stream_handle, exception_callback):
"""This the constructor which instantiates the NutnrJCsppParser"""
<|body_0|>
def _process_data_match(self, data_match):
"""This method processes a data match. It will extract a metadata... | stack_v2_sparse_classes_36k_train_021420 | 17,304 | permissive | [
{
"docstring": "This the constructor which instantiates the NutnrJCsppParser",
"name": "__init__",
"signature": "def __init__(self, config, stream_handle, exception_callback)"
},
{
"docstring": "This method processes a data match. It will extract a metadata particle and insert it into the record... | 3 | null | Implement the Python class `NutnrJCsppParser` described below.
Class description:
Implement the NutnrJCsppParser class.
Method signatures and docstrings:
- def __init__(self, config, stream_handle, exception_callback): This the constructor which instantiates the NutnrJCsppParser
- def _process_data_match(self, data_m... | Implement the Python class `NutnrJCsppParser` described below.
Class description:
Implement the NutnrJCsppParser class.
Method signatures and docstrings:
- def __init__(self, config, stream_handle, exception_callback): This the constructor which instantiates the NutnrJCsppParser
- def _process_data_match(self, data_m... | bdbf01f5614e7188ce19596704794466e5683b30 | <|skeleton|>
class NutnrJCsppParser:
def __init__(self, config, stream_handle, exception_callback):
"""This the constructor which instantiates the NutnrJCsppParser"""
<|body_0|>
def _process_data_match(self, data_match):
"""This method processes a data match. It will extract a metadata... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NutnrJCsppParser:
def __init__(self, config, stream_handle, exception_callback):
"""This the constructor which instantiates the NutnrJCsppParser"""
self._header_state = {}
header_key_list = DEFAULT_HEADER_KEY_LIST
for header_key in header_key_list:
self._header_stat... | the_stack_v2_python_sparse | mi/dataset/parser/nutnr_j_cspp.py | oceanobservatories/mi-instrument | train | 1 | |
70f33b4ce9e669293dfb6c0a599db2a964ee4677 | [
"idx = cuda.blockIdx.x * cuda.blockDim.x + cuda.threadIdx.x\nidy = cuda.blockIdx.y * cuda.blockDim.y + cuda.threadIdx.y\nindex = idx * size + idy\nif idx < size and idy < size:\n if idx > i:\n mul = A[idx * size + i] / A[i * size + i]\n if idy >= i:\n A[index] -= A[i * size + idy] * mul\... | <|body_start_0|>
idx = cuda.blockIdx.x * cuda.blockDim.x + cuda.threadIdx.x
idy = cuda.blockIdx.y * cuda.blockDim.y + cuda.threadIdx.y
index = idx * size + idy
if idx < size and idy < size:
if idx > i:
mul = A[idx * size + i] / A[i * size + i]
... | GuassianLUDecomposition | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GuassianLUDecomposition:
def gaussian_lu_decomposition(A, L, size, i):
"""Performs Gaussian LU elimination. @param A Coefficient matrix A. @param L Matrix in which to store the multipliers. @param size Size of coefficiente matrix. @param i Integer representing the current column in which... | stack_v2_sparse_classes_36k_train_021421 | 4,828 | no_license | [
{
"docstring": "Performs Gaussian LU elimination. @param A Coefficient matrix A. @param L Matrix in which to store the multipliers. @param size Size of coefficiente matrix. @param i Integer representing the current column in which all threads are performing row operations. @return None",
"name": "gaussian_l... | 6 | stack_v2_sparse_classes_30k_train_012757 | Implement the Python class `GuassianLUDecomposition` described below.
Class description:
Implement the GuassianLUDecomposition class.
Method signatures and docstrings:
- def gaussian_lu_decomposition(A, L, size, i): Performs Gaussian LU elimination. @param A Coefficient matrix A. @param L Matrix in which to store the... | Implement the Python class `GuassianLUDecomposition` described below.
Class description:
Implement the GuassianLUDecomposition class.
Method signatures and docstrings:
- def gaussian_lu_decomposition(A, L, size, i): Performs Gaussian LU elimination. @param A Coefficient matrix A. @param L Matrix in which to store the... | b2b89a18260c25134d50c37a4fbb48981de79218 | <|skeleton|>
class GuassianLUDecomposition:
def gaussian_lu_decomposition(A, L, size, i):
"""Performs Gaussian LU elimination. @param A Coefficient matrix A. @param L Matrix in which to store the multipliers. @param size Size of coefficiente matrix. @param i Integer representing the current column in which... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GuassianLUDecomposition:
def gaussian_lu_decomposition(A, L, size, i):
"""Performs Gaussian LU elimination. @param A Coefficient matrix A. @param L Matrix in which to store the multipliers. @param size Size of coefficiente matrix. @param i Integer representing the current column in which all threads a... | the_stack_v2_python_sparse | project/lu_decomposition/gaussian_lu_decomposition.py | tllano11/Numerical-Methods | train | 3 | |
28d03ac4162639a97cb6ecfd0f3ae095d3b5bf29 | [
"num_train_examples = 1281167\nnum_validation_examples = int(num_train_examples * validation_percent)\nnum_train_examples -= num_validation_examples\nsuper(ImageNetDataset, self).__init__(name='imagenet', num_train_examples=num_train_examples, num_validation_examples=num_validation_examples, num_test_examples=50000... | <|body_start_0|>
num_train_examples = 1281167
num_validation_examples = int(num_train_examples * validation_percent)
num_train_examples -= num_validation_examples
super(ImageNetDataset, self).__init__(name='imagenet', num_train_examples=num_train_examples, num_validation_examples=num_val... | ImageNet dataset builder class. | ImageNetDataset | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageNetDataset:
"""ImageNet dataset builder class."""
def __init__(self, batch_size: int, eval_batch_size: int, validation_percent: float=0.0, shuffle_buffer_size: int=None, num_parallel_parser_calls: int=64, data_dir: Optional[str]=None, **unused_kwargs: Dict[str, Any]):
"""Create ... | stack_v2_sparse_classes_36k_train_021422 | 4,922 | permissive | [
{
"docstring": "Create an ImageNet tf.data.Dataset builder. Args: batch_size: the training batch size. eval_batch_size: the validation and test batch size. validation_percent: the percent of the training set to use as a validation set. shuffle_buffer_size: the number of example to use in the shuffle buffer for ... | 3 | stack_v2_sparse_classes_30k_train_019704 | Implement the Python class `ImageNetDataset` described below.
Class description:
ImageNet dataset builder class.
Method signatures and docstrings:
- def __init__(self, batch_size: int, eval_batch_size: int, validation_percent: float=0.0, shuffle_buffer_size: int=None, num_parallel_parser_calls: int=64, data_dir: Opti... | Implement the Python class `ImageNetDataset` described below.
Class description:
ImageNet dataset builder class.
Method signatures and docstrings:
- def __init__(self, batch_size: int, eval_batch_size: int, validation_percent: float=0.0, shuffle_buffer_size: int=None, num_parallel_parser_calls: int=64, data_dir: Opti... | 88f78028fdfa6ed7a59eb79b549b14f328da5ba4 | <|skeleton|>
class ImageNetDataset:
"""ImageNet dataset builder class."""
def __init__(self, batch_size: int, eval_batch_size: int, validation_percent: float=0.0, shuffle_buffer_size: int=None, num_parallel_parser_calls: int=64, data_dir: Optional[str]=None, **unused_kwargs: Dict[str, Any]):
"""Create ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageNetDataset:
"""ImageNet dataset builder class."""
def __init__(self, batch_size: int, eval_batch_size: int, validation_percent: float=0.0, shuffle_buffer_size: int=None, num_parallel_parser_calls: int=64, data_dir: Optional[str]=None, **unused_kwargs: Dict[str, Any]):
"""Create an ImageNet t... | the_stack_v2_python_sparse | uncertainty_baselines/datasets/imagenet.py | kiminh/uncertainty-baselines | train | 1 |
a8825179e1a07d5aa485bd6c8eba0f3b8f4488b4 | [
"rospy.loginfo('Moving %s to handover position.' % limb)\nif limb == 'left':\n handover_position_joints = {'left_w0': 0.47016511148687934, 'left_w1': -0.42798063982003043, 'left_w2': 0.18676216092504913, 'left_e0': -1.1616069516262295, 'left_e1': 1.889097340280887, 'left_s0': 0.1499466220157992, 'left_s1': -0.91... | <|body_start_0|>
rospy.loginfo('Moving %s to handover position.' % limb)
if limb == 'left':
handover_position_joints = {'left_w0': 0.47016511148687934, 'left_w1': -0.42798063982003043, 'left_w2': 0.18676216092504913, 'left_e0': -1.1616069516262295, 'left_e1': 1.889097340280887, 'left_s0': 0.... | OfferingObjectServer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OfferingObjectServer:
def move_to_handover(self, baxter_arm, limb):
"""Moves specified limb to the handover position. :param baxter_arm: arm to move :param limb: which arm, 'right' or 'left :return:"""
<|body_0|>
def callback(self, request=None):
"""Call back for han... | stack_v2_sparse_classes_36k_train_021423 | 3,257 | permissive | [
{
"docstring": "Moves specified limb to the handover position. :param baxter_arm: arm to move :param limb: which arm, 'right' or 'left :return:",
"name": "move_to_handover",
"signature": "def move_to_handover(self, baxter_arm, limb)"
},
{
"docstring": "Call back for handover service. :param requ... | 2 | stack_v2_sparse_classes_30k_train_000744 | Implement the Python class `OfferingObjectServer` described below.
Class description:
Implement the OfferingObjectServer class.
Method signatures and docstrings:
- def move_to_handover(self, baxter_arm, limb): Moves specified limb to the handover position. :param baxter_arm: arm to move :param limb: which arm, 'right... | Implement the Python class `OfferingObjectServer` described below.
Class description:
Implement the OfferingObjectServer class.
Method signatures and docstrings:
- def move_to_handover(self, baxter_arm, limb): Moves specified limb to the handover position. :param baxter_arm: arm to move :param limb: which arm, 'right... | 1f9d05b7232cb9e76eff975e5ef1c8bf3fb5cde6 | <|skeleton|>
class OfferingObjectServer:
def move_to_handover(self, baxter_arm, limb):
"""Moves specified limb to the handover position. :param baxter_arm: arm to move :param limb: which arm, 'right' or 'left :return:"""
<|body_0|>
def callback(self, request=None):
"""Call back for han... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OfferingObjectServer:
def move_to_handover(self, baxter_arm, limb):
"""Moves specified limb to the handover position. :param baxter_arm: arm to move :param limb: which arm, 'right' or 'left :return:"""
rospy.loginfo('Moving %s to handover position.' % limb)
if limb == 'left':
... | the_stack_v2_python_sparse | grasping/src/offering_object_server.py | Hankfirst/de_niro | train | 1 | |
121bdc61beba5b5d852de631dbf69fd2a25ed35d | [
"jsonpath = pathlib.Path(jsonpath)\ndata = json.load(jsonpath.open('r', encoding='utf-8'), object_pairs_hook=OrderedDict)\ncategory = ''\nproduct = data['product']\ntotal_review = data['total_review']\ntotal_text = data['total_text']\ntexts = tuple((TextWithAttrAnnotation.from_json_content(text) for text in data['t... | <|body_start_0|>
jsonpath = pathlib.Path(jsonpath)
data = json.load(jsonpath.open('r', encoding='utf-8'), object_pairs_hook=OrderedDict)
category = ''
product = data['product']
total_review = data['total_review']
total_text = data['total_text']
texts = tuple((Text... | 属性抽出の評価をするためのデータ Attributes: category (str): 商品カテゴリ product (str): 商品名 total_review (int): 総レビュー数 total_text (int): 総文数 texts (Tuple[TextWithAttrAnnotation, ...]): 正解データ一覧 | AttrEvaluationData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttrEvaluationData:
"""属性抽出の評価をするためのデータ Attributes: category (str): 商品カテゴリ product (str): 商品名 total_review (int): 総レビュー数 total_text (int): 総文数 texts (Tuple[TextWithAttrAnnotation, ...]): 正解データ一覧"""
def load(cls, jsonpath: Union[str, pathlib.Path]):
"""JSON ファイルからインスタンス化 Args: jsonpat... | stack_v2_sparse_classes_36k_train_021424 | 3,444 | no_license | [
{
"docstring": "JSON ファイルからインスタンス化 Args: jsonpath (Union[str, pathlib.Path]): JSON ファイルのパス Returns: AttrEvaluationDataインスタンス",
"name": "load",
"signature": "def load(cls, jsonpath: Union[str, pathlib.Path])"
},
{
"docstring": "JSON 形式で保存する Args: jsonpath (Union[str, pathlib.Path]): 保存ファイルパス",
... | 2 | null | Implement the Python class `AttrEvaluationData` described below.
Class description:
属性抽出の評価をするためのデータ Attributes: category (str): 商品カテゴリ product (str): 商品名 total_review (int): 総レビュー数 total_text (int): 総文数 texts (Tuple[TextWithAttrAnnotation, ...]): 正解データ一覧
Method signatures and docstrings:
- def load(cls, jsonpath: Un... | Implement the Python class `AttrEvaluationData` described below.
Class description:
属性抽出の評価をするためのデータ Attributes: category (str): 商品カテゴリ product (str): 商品名 total_review (int): 総レビュー数 total_text (int): 総文数 texts (Tuple[TextWithAttrAnnotation, ...]): 正解データ一覧
Method signatures and docstrings:
- def load(cls, jsonpath: Un... | a4c6334b779a94814b7798a0fbfe9a148bf18d3a | <|skeleton|>
class AttrEvaluationData:
"""属性抽出の評価をするためのデータ Attributes: category (str): 商品カテゴリ product (str): 商品名 total_review (int): 総レビュー数 total_text (int): 総文数 texts (Tuple[TextWithAttrAnnotation, ...]): 正解データ一覧"""
def load(cls, jsonpath: Union[str, pathlib.Path]):
"""JSON ファイルからインスタンス化 Args: jsonpat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttrEvaluationData:
"""属性抽出の評価をするためのデータ Attributes: category (str): 商品カテゴリ product (str): 商品名 total_review (int): 総レビュー数 total_text (int): 総文数 texts (Tuple[TextWithAttrAnnotation, ...]): 正解データ一覧"""
def load(cls, jsonpath: Union[str, pathlib.Path]):
"""JSON ファイルからインスタンス化 Args: jsonpath (Union[str,... | the_stack_v2_python_sparse | src/review_research/evaluation/attr_evaluation_data.py | S38knt-ks/ReviewResearch | train | 0 |
119f5eea3ac45ebb4bf557b1d9a637a810a459c9 | [
"parameters = list(inspect.signature(udf).parameters.keys())\ninput_parameters = self._get_input_params(udf)\nif len(input_parameters) < 1:\n raise ValueError('feature_processor expects at least 1 input parameter.')\nnum_data_sources = len(fp_config.inputs)\nif len(input_parameters) != num_data_sources:\n rai... | <|body_start_0|>
parameters = list(inspect.signature(udf).parameters.keys())
input_parameters = self._get_input_params(udf)
if len(input_parameters) < 1:
raise ValueError('feature_processor expects at least 1 input parameter.')
num_data_sources = len(fp_config.inputs)
... | A validator for PySpark UDF signatures. | SparkUDFSignatureValidator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparkUDFSignatureValidator:
"""A validator for PySpark UDF signatures."""
def validate(self, udf: Callable[..., Any], fp_config: FeatureProcessorConfig) -> None:
"""Validate the signature of the UDF based on the configurations provided to the decorator. Args: udf (Callable[..., T]): ... | stack_v2_sparse_classes_36k_train_021425 | 7,056 | permissive | [
{
"docstring": "Validate the signature of the UDF based on the configurations provided to the decorator. Args: udf (Callable[..., T]): The feature_processor wrapped user function. fp_config (FeatureProcessorConfig): The configuration for the feature_processor. Raises (ValueError): raises ValueError when any of ... | 2 | stack_v2_sparse_classes_30k_train_002980 | Implement the Python class `SparkUDFSignatureValidator` described below.
Class description:
A validator for PySpark UDF signatures.
Method signatures and docstrings:
- def validate(self, udf: Callable[..., Any], fp_config: FeatureProcessorConfig) -> None: Validate the signature of the UDF based on the configurations ... | Implement the Python class `SparkUDFSignatureValidator` described below.
Class description:
A validator for PySpark UDF signatures.
Method signatures and docstrings:
- def validate(self, udf: Callable[..., Any], fp_config: FeatureProcessorConfig) -> None: Validate the signature of the UDF based on the configurations ... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class SparkUDFSignatureValidator:
"""A validator for PySpark UDF signatures."""
def validate(self, udf: Callable[..., Any], fp_config: FeatureProcessorConfig) -> None:
"""Validate the signature of the UDF based on the configurations provided to the decorator. Args: udf (Callable[..., T]): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SparkUDFSignatureValidator:
"""A validator for PySpark UDF signatures."""
def validate(self, udf: Callable[..., Any], fp_config: FeatureProcessorConfig) -> None:
"""Validate the signature of the UDF based on the configurations provided to the decorator. Args: udf (Callable[..., T]): The feature_p... | the_stack_v2_python_sparse | src/sagemaker/feature_store/feature_processor/_validation.py | aws/sagemaker-python-sdk | train | 2,050 |
5387360372fa674be695cc9aa2ef1c0cb4c8a047 | [
"seq1 = 'AAAA'\nres = geneutil.sequenceEntropy(seq1)\nself.assertAlmostEqual(res.entropy, 0.0)\nself.assertTrue(res.counts['A'] == 4)",
"seq1 = 'ACDEFGHIKLMNPQRSTVWY'\nres = geneutil.sequenceEntropy(seq1, base=20)\nself.assertAlmostEqual(res.entropy, 1.0)\nfor aa in seq1:\n self.assertTrue(res.counts[aa] == 1)... | <|body_start_0|>
seq1 = 'AAAA'
res = geneutil.sequenceEntropy(seq1)
self.assertAlmostEqual(res.entropy, 0.0)
self.assertTrue(res.counts['A'] == 4)
<|end_body_0|>
<|body_start_1|>
seq1 = 'ACDEFGHIKLMNPQRSTVWY'
res = geneutil.sequenceEntropy(seq1, base=20)
self.ass... | test004 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test004:
def test_entropy(self):
"""Entropy of a homopolymer"""
<|body_0|>
def test_max_entropy(self):
"""Maximum possible entropy"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
seq1 = 'AAAA'
res = geneutil.sequenceEntropy(seq1)
sel... | stack_v2_sparse_classes_36k_train_021426 | 2,692 | no_license | [
{
"docstring": "Entropy of a homopolymer",
"name": "test_entropy",
"signature": "def test_entropy(self)"
},
{
"docstring": "Maximum possible entropy",
"name": "test_max_entropy",
"signature": "def test_max_entropy(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015463 | Implement the Python class `test004` described below.
Class description:
Implement the test004 class.
Method signatures and docstrings:
- def test_entropy(self): Entropy of a homopolymer
- def test_max_entropy(self): Maximum possible entropy | Implement the Python class `test004` described below.
Class description:
Implement the test004 class.
Method signatures and docstrings:
- def test_entropy(self): Entropy of a homopolymer
- def test_max_entropy(self): Maximum possible entropy
<|skeleton|>
class test004:
def test_entropy(self):
"""Entropy... | d7ddd2b585a841c6d986974a24a53e4d1abe71ba | <|skeleton|>
class test004:
def test_entropy(self):
"""Entropy of a homopolymer"""
<|body_0|>
def test_max_entropy(self):
"""Maximum possible entropy"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test004:
def test_entropy(self):
"""Entropy of a homopolymer"""
seq1 = 'AAAA'
res = geneutil.sequenceEntropy(seq1)
self.assertAlmostEqual(res.entropy, 0.0)
self.assertTrue(res.counts['A'] == 4)
def test_max_entropy(self):
"""Maximum possible entropy"""
... | the_stack_v2_python_sparse | src/geneutil_test.py | dad/base | train | 0 | |
99886541ee5d86ec350d9f5ec2426543c98cb185 | [
"self.csv_name = f'{self.csv_dir}/{os.path.basename(self.path)}.csv'\nself._convert_dump_to_csv(bgpscanner)\nutils.csv_to_db(MRT_Announcements_Table, self.csv_name)\nutils.delete_paths([self.path, self.csv_name])\nutils.incriment_bar(logging.root.level)",
"args = self._bgpscanner_args() if bgpscanner else self._b... | <|body_start_0|>
self.csv_name = f'{self.csv_dir}/{os.path.basename(self.path)}.csv'
self._convert_dump_to_csv(bgpscanner)
utils.csv_to_db(MRT_Announcements_Table, self.csv_name)
utils.delete_paths([self.path, self.csv_name])
utils.incriment_bar(logging.root.level)
<|end_body_0|>... | Converts MRT files to CSVs and then inserts them into a database. In depth explanation in README. | MRT_File | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MRT_File:
"""Converts MRT files to CSVs and then inserts them into a database. In depth explanation in README."""
def parse_file(self, bgpscanner=True):
"""Parses a downloaded file and inserts it into the database if bgpscanner is set to True, bgpscanner is used to parser files which... | stack_v2_sparse_classes_36k_train_021427 | 8,323 | permissive | [
{
"docstring": "Parses a downloaded file and inserts it into the database if bgpscanner is set to True, bgpscanner is used to parser files which is faster, but ignores malformed announcements. While these malformed announcements are few and far between, bgpdump does not ignore them and should be used for full d... | 4 | stack_v2_sparse_classes_30k_train_020496 | Implement the Python class `MRT_File` described below.
Class description:
Converts MRT files to CSVs and then inserts them into a database. In depth explanation in README.
Method signatures and docstrings:
- def parse_file(self, bgpscanner=True): Parses a downloaded file and inserts it into the database if bgpscanner... | Implement the Python class `MRT_File` described below.
Class description:
Converts MRT files to CSVs and then inserts them into a database. In depth explanation in README.
Method signatures and docstrings:
- def parse_file(self, bgpscanner=True): Parses a downloaded file and inserts it into the database if bgpscanner... | 91c92584b31bd128d818c7fee86c738367c0712e | <|skeleton|>
class MRT_File:
"""Converts MRT files to CSVs and then inserts them into a database. In depth explanation in README."""
def parse_file(self, bgpscanner=True):
"""Parses a downloaded file and inserts it into the database if bgpscanner is set to True, bgpscanner is used to parser files which... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MRT_File:
"""Converts MRT files to CSVs and then inserts them into a database. In depth explanation in README."""
def parse_file(self, bgpscanner=True):
"""Parses a downloaded file and inserts it into the database if bgpscanner is set to True, bgpscanner is used to parser files which is faster, b... | the_stack_v2_python_sparse | lib_bgp_data/collectors/mrt/mrt_base/mrt_file.py | jfuruness/lib_bgp_data | train | 16 |
856601f7348d491c89af97d715f7e406504b0d1f | [
"tmp_file_name = 'test.json'\ntmp_dir_name = tempfile.gettempdir()\njson_file_path = tmp_dir_name + '/' + tmp_file_name\nwith open(json_file_path, 'w') as f:\n f.write(policy_json.strip())\ngrd_text = '\\n <grit base_dir=\".\" latest_public_release=\"0\" current_release=\"1\" source_lang_id=\"en\">\\n <r... | <|body_start_0|>
tmp_file_name = 'test.json'
tmp_dir_name = tempfile.gettempdir()
json_file_path = tmp_dir_name + '/' + tmp_file_name
with open(json_file_path, 'w') as f:
f.write(policy_json.strip())
grd_text = '\n <grit base_dir="." latest_public_release="0" curre... | Common class for unittesting writers. | WriterUnittestCommon | [
"BSD-3-Clause",
"LGPL-2.0-or-later",
"LicenseRef-scancode-unknown-license-reference",
"GPL-2.0-only",
"Apache-2.0",
"LicenseRef-scancode-unknown",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WriterUnittestCommon:
"""Common class for unittesting writers."""
def PrepareTest(self, policy_json):
"""Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in JSON format."""
<|body_0|>
def GetOutput(self... | stack_v2_sparse_classes_36k_train_021428 | 2,618 | permissive | [
{
"docstring": "Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in JSON format.",
"name": "PrepareTest",
"signature": "def PrepareTest(self, policy_json)"
},
{
"docstring": "Generates an output of a writer. Args: grd: The root... | 2 | stack_v2_sparse_classes_30k_train_018655 | Implement the Python class `WriterUnittestCommon` described below.
Class description:
Common class for unittesting writers.
Method signatures and docstrings:
- def PrepareTest(self, policy_json): Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in J... | Implement the Python class `WriterUnittestCommon` described below.
Class description:
Common class for unittesting writers.
Method signatures and docstrings:
- def PrepareTest(self, policy_json): Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in J... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class WriterUnittestCommon:
"""Common class for unittesting writers."""
def PrepareTest(self, policy_json):
"""Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in JSON format."""
<|body_0|>
def GetOutput(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WriterUnittestCommon:
"""Common class for unittesting writers."""
def PrepareTest(self, policy_json):
"""Prepares and parses a grit tree along with a data structure of policies. Args: policy_json: The policy data structure in JSON format."""
tmp_file_name = 'test.json'
tmp_dir_nam... | the_stack_v2_python_sparse | tools/grit/grit/format/policy_templates/writers/writer_unittest_common.py | metux/chromium-suckless | train | 5 |
459ff43098b6cdea39fe1f50a99b4a6cc52e7072 | [
"retval = dict(default_)\nretval['keyword'].append(value)\nreturn [retval]",
"retval = dict(default_)\nretval['date'] = value\nreturn [retval]",
"retval = dict(default_)\nretval['id'] = value\nreturn [retval]"
] | <|body_start_0|>
retval = dict(default_)
retval['keyword'].append(value)
return [retval]
<|end_body_0|>
<|body_start_1|>
retval = dict(default_)
retval['date'] = value
return [retval]
<|end_body_1|>
<|body_start_2|>
retval = dict(default_)
retval['id'] =... | Dummy engine class, returns a dict object for certain methods called | Dummy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dummy:
"""Dummy engine class, returns a dict object for certain methods called"""
def keyword(self, value, num, request):
"""Returns at most num dict objects, as an iterable, with keyword as a keyword in the dict."""
<|body_0|>
def date(self, value, num, request):
... | stack_v2_sparse_classes_36k_train_021429 | 1,206 | permissive | [
{
"docstring": "Returns at most num dict objects, as an iterable, with keyword as a keyword in the dict.",
"name": "keyword",
"signature": "def keyword(self, value, num, request)"
},
{
"docstring": "Returns at most num dict objects, as an iterable, with all dict objects matching the date passed"... | 3 | stack_v2_sparse_classes_30k_train_005454 | Implement the Python class `Dummy` described below.
Class description:
Dummy engine class, returns a dict object for certain methods called
Method signatures and docstrings:
- def keyword(self, value, num, request): Returns at most num dict objects, as an iterable, with keyword as a keyword in the dict.
- def date(se... | Implement the Python class `Dummy` described below.
Class description:
Dummy engine class, returns a dict object for certain methods called
Method signatures and docstrings:
- def keyword(self, value, num, request): Returns at most num dict objects, as an iterable, with keyword as a keyword in the dict.
- def date(se... | 1d8105e91c3fac53e65882af0ba01bbb7186f424 | <|skeleton|>
class Dummy:
"""Dummy engine class, returns a dict object for certain methods called"""
def keyword(self, value, num, request):
"""Returns at most num dict objects, as an iterable, with keyword as a keyword in the dict."""
<|body_0|>
def date(self, value, num, request):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dummy:
"""Dummy engine class, returns a dict object for certain methods called"""
def keyword(self, value, num, request):
"""Returns at most num dict objects, as an iterable, with keyword as a keyword in the dict."""
retval = dict(default_)
retval['keyword'].append(value)
... | the_stack_v2_python_sparse | apibert/engines/dummy.py | ofu/brisbert | train | 0 |
bd23cfdf47d4f71b9032c2adc5026dc142d0844f | [
"definition_node = ElementTree.Element('definition')\ndefinition_node.attrib['class'] = 'org.jenkinsci.plugins.workflow.cps.CpsScmFlowDefinition'\ndefinition_node.attrib['plugin'] = 'workflow-cps'\ndefinition_node.append(scm.node)\nscript_node = ElementTree.Element('scriptPath')\nscript_node.text = script_path\ndef... | <|body_start_0|>
definition_node = ElementTree.Element('definition')
definition_node.attrib['class'] = 'org.jenkinsci.plugins.workflow.cps.CpsScmFlowDefinition'
definition_node.attrib['plugin'] = 'workflow-cps'
definition_node.append(scm.node)
script_node = ElementTree.Element('s... | Object that manages the config.xml for a pipeline job | PipelineXML | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PipelineXML:
"""Object that manages the config.xml for a pipeline job"""
def scm_definition(self, scm, script_path, lightweight):
"""Defines the Pipeline groovy script used by this job from files stored in a source code repository Args: scm (XMLPlugin): PyJen object defining the sour... | stack_v2_sparse_classes_36k_train_021430 | 6,850 | permissive | [
{
"docstring": "Defines the Pipeline groovy script used by this job from files stored in a source code repository Args: scm (XMLPlugin): PyJen object defining the source code repository to use script_path (str): Path within the repository where the groovy script to be run is found. lightweight (bool): Set to Tr... | 4 | stack_v2_sparse_classes_30k_val_000618 | Implement the Python class `PipelineXML` described below.
Class description:
Object that manages the config.xml for a pipeline job
Method signatures and docstrings:
- def scm_definition(self, scm, script_path, lightweight): Defines the Pipeline groovy script used by this job from files stored in a source code reposit... | Implement the Python class `PipelineXML` described below.
Class description:
Object that manages the config.xml for a pipeline job
Method signatures and docstrings:
- def scm_definition(self, scm, script_path, lightweight): Defines the Pipeline groovy script used by this job from files stored in a source code reposit... | 6ada1209b1e88f4a8aa7bde22f874168f1592e0e | <|skeleton|>
class PipelineXML:
"""Object that manages the config.xml for a pipeline job"""
def scm_definition(self, scm, script_path, lightweight):
"""Defines the Pipeline groovy script used by this job from files stored in a source code repository Args: scm (XMLPlugin): PyJen object defining the sour... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PipelineXML:
"""Object that manages the config.xml for a pipeline job"""
def scm_definition(self, scm, script_path, lightweight):
"""Defines the Pipeline groovy script used by this job from files stored in a source code repository Args: scm (XMLPlugin): PyJen object defining the source code repos... | the_stack_v2_python_sparse | src/pyjen/plugins/pipelinejob.py | TheFriendlyCoder/pyjen | train | 6 |
e8d7ed4dbab440e99cde9eb793498261f4249ad1 | [
"if not is_exe(exe_path):\n msg = '{0} is not an executable'.format(exe_path)\n raise NotExecutableError(msg)\nself._exe_path = exe_path",
"self.__build_cmd(infnames, outdir)\nif not os.path.exists(self._outdirname):\n os.makedirs(self._outdirname)\npipe = subprocess.run(self._cmd, shell=True, stdout=sub... | <|body_start_0|>
if not is_exe(exe_path):
msg = '{0} is not an executable'.format(exe_path)
raise NotExecutableError(msg)
self._exe_path = exe_path
<|end_body_0|>
<|body_start_1|>
self.__build_cmd(infnames, outdir)
if not os.path.exists(self._outdirname):
... | Class for working with FastQC | FastQC | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastQC:
"""Class for working with FastQC"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, infnames, outdir, dry_run=False):
"""Run fastqc on the passed file"""
<|body_1|>
def __build_cmd(self, in... | stack_v2_sparse_classes_36k_train_021431 | 2,209 | permissive | [
{
"docstring": "Instantiate with location of executable",
"name": "__init__",
"signature": "def __init__(self, exe_path)"
},
{
"docstring": "Run fastqc on the passed file",
"name": "run",
"signature": "def run(self, infnames, outdir, dry_run=False)"
},
{
"docstring": "Build a com... | 3 | stack_v2_sparse_classes_30k_train_019982 | Implement the Python class `FastQC` described below.
Class description:
Class for working with FastQC
Method signatures and docstrings:
- def __init__(self, exe_path): Instantiate with location of executable
- def run(self, infnames, outdir, dry_run=False): Run fastqc on the passed file
- def __build_cmd(self, infnam... | Implement the Python class `FastQC` described below.
Class description:
Class for working with FastQC
Method signatures and docstrings:
- def __init__(self, exe_path): Instantiate with location of executable
- def run(self, infnames, outdir, dry_run=False): Run fastqc on the passed file
- def __build_cmd(self, infnam... | a3c64198aad3709a5c4d969f48ae0af11fdc25db | <|skeleton|>
class FastQC:
"""Class for working with FastQC"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
<|body_0|>
def run(self, infnames, outdir, dry_run=False):
"""Run fastqc on the passed file"""
<|body_1|>
def __build_cmd(self, in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FastQC:
"""Class for working with FastQC"""
def __init__(self, exe_path):
"""Instantiate with location of executable"""
if not is_exe(exe_path):
msg = '{0} is not an executable'.format(exe_path)
raise NotExecutableError(msg)
self._exe_path = exe_path
d... | the_stack_v2_python_sparse | metapy/pycits/fastqc.py | peterthorpe5/public_scripts | train | 35 |
975c513fb390cf934b4c683289d0a80c97bc8644 | [
"context = super(EntryListView, self).get_context_data(**kwargs)\ncontext['num_entries'] = self.get_queryset().count()\ncontext['unapproved'] = False\ncontext['project_slug'] = self.project_slug\ncontext['version_slug'] = self.version_slug\nreturn context",
"if self.queryset is None:\n self.project_slug = self... | <|body_start_0|>
context = super(EntryListView, self).get_context_data(**kwargs)
context['num_entries'] = self.get_queryset().count()
context['unapproved'] = False
context['project_slug'] = self.project_slug
context['version_slug'] = self.version_slug
return context
<|end... | List view for Entry. | EntryListView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntryListView:
"""List view for Entry."""
def get_context_data(self, **kwargs):
"""Get the context data which is passed to a template. :param kwargs: Any arguments to pass to the superclass. :type kwargs: dict :returns: Context data which will be passed to the template. :rtype: dict"... | stack_v2_sparse_classes_36k_train_021432 | 13,902 | no_license | [
{
"docstring": "Get the context data which is passed to a template. :param kwargs: Any arguments to pass to the superclass. :type kwargs: dict :returns: Context data which will be passed to the template. :rtype: dict",
"name": "get_context_data",
"signature": "def get_context_data(self, **kwargs)"
},
... | 2 | stack_v2_sparse_classes_30k_train_010650 | Implement the Python class `EntryListView` described below.
Class description:
List view for Entry.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Get the context data which is passed to a template. :param kwargs: Any arguments to pass to the superclass. :type kwargs: dict :returns: Context... | Implement the Python class `EntryListView` described below.
Class description:
List view for Entry.
Method signatures and docstrings:
- def get_context_data(self, **kwargs): Get the context data which is passed to a template. :param kwargs: Any arguments to pass to the superclass. :type kwargs: dict :returns: Context... | ca489c38fdfde29f75c9c1e7f4b4c55d78d91c79 | <|skeleton|>
class EntryListView:
"""List view for Entry."""
def get_context_data(self, **kwargs):
"""Get the context data which is passed to a template. :param kwargs: Any arguments to pass to the superclass. :type kwargs: dict :returns: Context data which will be passed to the template. :rtype: dict"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EntryListView:
"""List view for Entry."""
def get_context_data(self, **kwargs):
"""Get the context data which is passed to a template. :param kwargs: Any arguments to pass to the superclass. :type kwargs: dict :returns: Context data which will be passed to the template. :rtype: dict"""
co... | the_stack_v2_python_sparse | django_project/changes/views/entry.py | gitter-badger/projecta | train | 0 |
84226a5cbbbc20574e0196f961a32180eb439412 | [
"if can_send_sequence():\n data = parser_seq_add.parse_args()\n program = data['code']\n name = escape(data['name'])\n try:\n queue_manager.process_pool.put(ThreadWithTrace(name, target=perform, args=(program,)), block=False)\n return format_response('Sequence saved', True)\n except que... | <|body_start_0|>
if can_send_sequence():
data = parser_seq_add.parse_args()
program = data['code']
name = escape(data['name'])
try:
queue_manager.process_pool.put(ThreadWithTrace(name, target=perform, args=(program,)), block=False)
... | Class resource of sequence route:/seq This class manage all the request to manage sequence | Sequence | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sequence:
"""Class resource of sequence route:/seq This class manage all the request to manage sequence"""
def post(self):
"""post function of sequence Add a sequence to queue :return information of request"""
<|body_0|>
def delete(self):
"""delete function of se... | stack_v2_sparse_classes_36k_train_021433 | 16,281 | no_license | [
{
"docstring": "post function of sequence Add a sequence to queue :return information of request",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "delete function of sequence delete a sequence in the queue :return information of request",
"name": "delete",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_000748 | Implement the Python class `Sequence` described below.
Class description:
Class resource of sequence route:/seq This class manage all the request to manage sequence
Method signatures and docstrings:
- def post(self): post function of sequence Add a sequence to queue :return information of request
- def delete(self): ... | Implement the Python class `Sequence` described below.
Class description:
Class resource of sequence route:/seq This class manage all the request to manage sequence
Method signatures and docstrings:
- def post(self): post function of sequence Add a sequence to queue :return information of request
- def delete(self): ... | de1408317d5071b7e0c6b2fea6f281660115d728 | <|skeleton|>
class Sequence:
"""Class resource of sequence route:/seq This class manage all the request to manage sequence"""
def post(self):
"""post function of sequence Add a sequence to queue :return information of request"""
<|body_0|>
def delete(self):
"""delete function of se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sequence:
"""Class resource of sequence route:/seq This class manage all the request to manage sequence"""
def post(self):
"""post function of sequence Add a sequence to queue :return information of request"""
if can_send_sequence():
data = parser_seq_add.parse_args()
... | the_stack_v2_python_sparse | api/resources.py | HE-Arc/Extrusion---web-interface | train | 4 |
ff0578471ca1b97f482e6d8b7a5f9b03d2100caa | [
"self.node = node\nself.number = number\nself.platform = platform",
"fade_time = 12\ndata = bytearray([fade_time, brightness])\nself.platform.send_cmd(self.node, SpikeNodebus.SetLed + self.number, data)"
] | <|body_start_0|>
self.node = node
self.number = number
self.platform = platform
<|end_body_0|>
<|body_start_1|>
fade_time = 12
data = bytearray([fade_time, brightness])
self.platform.send_cmd(self.node, SpikeNodebus.SetLed + self.number, data)
<|end_body_1|>
| A light on a Stern Spike node board. | SpikeLight | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpikeLight:
"""A light on a Stern Spike node board."""
def __init__(self, node, number, platform):
"""Initialise switch."""
<|body_0|>
def on(self, brightness=255):
"""Set brightness of channel."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
se... | stack_v2_sparse_classes_36k_train_021434 | 19,451 | permissive | [
{
"docstring": "Initialise switch.",
"name": "__init__",
"signature": "def __init__(self, node, number, platform)"
},
{
"docstring": "Set brightness of channel.",
"name": "on",
"signature": "def on(self, brightness=255)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013394 | Implement the Python class `SpikeLight` described below.
Class description:
A light on a Stern Spike node board.
Method signatures and docstrings:
- def __init__(self, node, number, platform): Initialise switch.
- def on(self, brightness=255): Set brightness of channel. | Implement the Python class `SpikeLight` described below.
Class description:
A light on a Stern Spike node board.
Method signatures and docstrings:
- def __init__(self, node, number, platform): Initialise switch.
- def on(self, brightness=255): Set brightness of channel.
<|skeleton|>
class SpikeLight:
"""A light ... | 00937ab2ff51b1dc668bf465282ffa8ff1eebbd8 | <|skeleton|>
class SpikeLight:
"""A light on a Stern Spike node board."""
def __init__(self, node, number, platform):
"""Initialise switch."""
<|body_0|>
def on(self, brightness=255):
"""Set brightness of channel."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpikeLight:
"""A light on a Stern Spike node board."""
def __init__(self, node, number, platform):
"""Initialise switch."""
self.node = node
self.number = number
self.platform = platform
def on(self, brightness=255):
"""Set brightness of channel."""
fa... | the_stack_v2_python_sparse | mpf/platforms/spike/spike.py | vgrillot/mpf | train | 0 |
cc13d79a4b151a0bbc7c117f974e4fb6299b8ace | [
"soup = BeautifulSoup(response.content, 'html.parser')\nmenu_tag = soup.find_all(class_='uk-nav uk-nav-side')[1]\nfor li in menu_tag.find_all('li'):\n url = li.a.get('href')\n if not url.satrtswith('http'):\n url = ''.join([self.domain, url])\n yield url",
"try:\n soup = BeautifulSoup(response.... | <|body_start_0|>
soup = BeautifulSoup(response.content, 'html.parser')
menu_tag = soup.find_all(class_='uk-nav uk-nav-side')[1]
for li in menu_tag.find_all('li'):
url = li.a.get('href')
if not url.satrtswith('http'):
url = ''.join([self.domain, url])
... | 廖雪峰python3教程 | LiaoXueFengPythonCrawler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LiaoXueFengPythonCrawler:
"""廖雪峰python3教程"""
def parse_menu(self, response):
"""解析目录结构，获取所有URL目录列表 :param response: 爬虫所返回的response对象 :return: url生成器"""
<|body_0|>
def parse_body(self, response):
"""解析正文 :param response: 爬虫返回的response对象 :return: url生成器"""
... | stack_v2_sparse_classes_36k_train_021435 | 2,528 | no_license | [
{
"docstring": "解析目录结构，获取所有URL目录列表 :param response: 爬虫所返回的response对象 :return: url生成器",
"name": "parse_menu",
"signature": "def parse_menu(self, response)"
},
{
"docstring": "解析正文 :param response: 爬虫返回的response对象 :return: url生成器",
"name": "parse_body",
"signature": "def parse_body(self, r... | 2 | stack_v2_sparse_classes_30k_train_018696 | Implement the Python class `LiaoXueFengPythonCrawler` described below.
Class description:
廖雪峰python3教程
Method signatures and docstrings:
- def parse_menu(self, response): 解析目录结构，获取所有URL目录列表 :param response: 爬虫所返回的response对象 :return: url生成器
- def parse_body(self, response): 解析正文 :param response: 爬虫返回的response对象 :retur... | Implement the Python class `LiaoXueFengPythonCrawler` described below.
Class description:
廖雪峰python3教程
Method signatures and docstrings:
- def parse_menu(self, response): 解析目录结构，获取所有URL目录列表 :param response: 爬虫所返回的response对象 :return: url生成器
- def parse_body(self, response): 解析正文 :param response: 爬虫返回的response对象 :retur... | 9dc81fc32c18ef4e988fcdff2d9274d1a7cb8497 | <|skeleton|>
class LiaoXueFengPythonCrawler:
"""廖雪峰python3教程"""
def parse_menu(self, response):
"""解析目录结构，获取所有URL目录列表 :param response: 爬虫所返回的response对象 :return: url生成器"""
<|body_0|>
def parse_body(self, response):
"""解析正文 :param response: 爬虫返回的response对象 :return: url生成器"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LiaoXueFengPythonCrawler:
"""廖雪峰python3教程"""
def parse_menu(self, response):
"""解析目录结构，获取所有URL目录列表 :param response: 爬虫所返回的response对象 :return: url生成器"""
soup = BeautifulSoup(response.content, 'html.parser')
menu_tag = soup.find_all(class_='uk-nav uk-nav-side')[1]
for li in ... | the_stack_v2_python_sparse | pdf/liaoxuefeng_python_crawler.py | qq34384878/Spider | train | 0 |
5f65fe330f6d5effb9c36f6ccae8c30d48f10334 | [
"i, j = (0, len(nums) - 1)\nwhile i < j:\n tmp = nums[i] + nums[j]\n if target < tmp:\n j -= 1\n elif target > tmp:\n i += 1\n else:\n return [nums[i], nums[j]]\nreturn None",
"i, j = (0, len(nums) - 1)\nwhile i < j:\n if target - nums[i] < nums[j]:\n i += 1\n elif ta... | <|body_start_0|>
i, j = (0, len(nums) - 1)
while i < j:
tmp = nums[i] + nums[j]
if target < tmp:
j -= 1
elif target > tmp:
i += 1
else:
return [nums[i], nums[j]]
return None
<|end_body_0|>
<|body_sta... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum1(self, nums: List[int], target: int) -> List[int]:
"""因为它是一个递增排序的数组，所以我考虑从两边开始找，这样效率会高一些 复杂度分析： 时间复杂度：O(n) n为数组nums的长度，双指针共同遍历整个数组 空间复杂度：O(1) 变量 i, j 使用常数大小的额外空间"""
<|body_0|>
def twoSum2(self, nums: List[int], target: int) -> List[int]:
"""对上面版本... | stack_v2_sparse_classes_36k_train_021436 | 2,371 | no_license | [
{
"docstring": "因为它是一个递增排序的数组，所以我考虑从两边开始找，这样效率会高一些 复杂度分析： 时间复杂度：O(n) n为数组nums的长度，双指针共同遍历整个数组 空间复杂度：O(1) 变量 i, j 使用常数大小的额外空间",
"name": "twoSum1",
"signature": "def twoSum1(self, nums: List[int], target: int) -> List[int]"
},
{
"docstring": "对上面版本进行修改，考虑到溢出问题， 这里将判断条件改成 target-nums[i] 与 nums[j] 相比... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum1(self, nums: List[int], target: int) -> List[int]: 因为它是一个递增排序的数组，所以我考虑从两边开始找，这样效率会高一些 复杂度分析： 时间复杂度：O(n) n为数组nums的长度，双指针共同遍历整个数组 空间复杂度：O(1) 变量 i, j 使用常数大小的额外空间
- def tw... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum1(self, nums: List[int], target: int) -> List[int]: 因为它是一个递增排序的数组，所以我考虑从两边开始找，这样效率会高一些 复杂度分析： 时间复杂度：O(n) n为数组nums的长度，双指针共同遍历整个数组 空间复杂度：O(1) 变量 i, j 使用常数大小的额外空间
- def tw... | 51943e2c2c4ec70c7c1d5b53c9fdf0a719428d7a | <|skeleton|>
class Solution:
def twoSum1(self, nums: List[int], target: int) -> List[int]:
"""因为它是一个递增排序的数组，所以我考虑从两边开始找，这样效率会高一些 复杂度分析： 时间复杂度：O(n) n为数组nums的长度，双指针共同遍历整个数组 空间复杂度：O(1) 变量 i, j 使用常数大小的额外空间"""
<|body_0|>
def twoSum2(self, nums: List[int], target: int) -> List[int]:
"""对上面版本... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def twoSum1(self, nums: List[int], target: int) -> List[int]:
"""因为它是一个递增排序的数组，所以我考虑从两边开始找，这样效率会高一些 复杂度分析： 时间复杂度：O(n) n为数组nums的长度，双指针共同遍历整个数组 空间复杂度：O(1) 变量 i, j 使用常数大小的额外空间"""
i, j = (0, len(nums) - 1)
while i < j:
tmp = nums[i] + nums[j]
if target < t... | the_stack_v2_python_sparse | 剑指offer/PythonVersion/57_1_和为s的两个数字.py | LeBron-Jian/BasicAlgorithmPractice | train | 13 | |
13b9b9aeb501acab44ed348ab9eb5aed926cf3a3 | [
"super(Registry, self).__init__(name, bases, attrs)\nif getattr(bases[0], '__metaclass__', None) != Registry:\n return\nif not attrs.get(attr_name, None):\n raise TypeError(\"You must define a '%(attr)s' for the %(class)s class\" % {'attr': attr_name, 'class': name})\nattr_val = attrs[attr_name]\nif attr_val ... | <|body_start_0|>
super(Registry, self).__init__(name, bases, attrs)
if getattr(bases[0], '__metaclass__', None) != Registry:
return
if not attrs.get(attr_name, None):
raise TypeError("You must define a '%(attr)s' for the %(class)s class" % {'attr': attr_name, 'class': nam... | An abstract registry for objects keyed by an attribute value. | Registry | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Registry:
"""An abstract registry for objects keyed by an attribute value."""
def __init__(self, name, bases, attrs):
"""Update our object registry, keyed by an attribute value."""
<|body_0|>
def get_registry_item(self, attr_val):
"""Return the class registered u... | stack_v2_sparse_classes_36k_train_021437 | 1,405 | permissive | [
{
"docstring": "Update our object registry, keyed by an attribute value.",
"name": "__init__",
"signature": "def __init__(self, name, bases, attrs)"
},
{
"docstring": "Return the class registered under the given attribute name. If the class instance cannot be found, a ValueError is raised.",
... | 2 | null | Implement the Python class `Registry` described below.
Class description:
An abstract registry for objects keyed by an attribute value.
Method signatures and docstrings:
- def __init__(self, name, bases, attrs): Update our object registry, keyed by an attribute value.
- def get_registry_item(self, attr_val): Return t... | Implement the Python class `Registry` described below.
Class description:
An abstract registry for objects keyed by an attribute value.
Method signatures and docstrings:
- def __init__(self, name, bases, attrs): Update our object registry, keyed by an attribute value.
- def get_registry_item(self, attr_val): Return t... | 24e354769841dd6962f38cef3bd45f8297b040c6 | <|skeleton|>
class Registry:
"""An abstract registry for objects keyed by an attribute value."""
def __init__(self, name, bases, attrs):
"""Update our object registry, keyed by an attribute value."""
<|body_0|>
def get_registry_item(self, attr_val):
"""Return the class registered u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Registry:
"""An abstract registry for objects keyed by an attribute value."""
def __init__(self, name, bases, attrs):
"""Update our object registry, keyed by an attribute value."""
super(Registry, self).__init__(name, bases, attrs)
if getattr(bases[0], '__metaclass__', None) != Re... | the_stack_v2_python_sparse | pressgang/utils/registry.py | cilcoberlin/pressgang | train | 1 |
51fe80a3003d5499c5da29bc61022165f2784152 | [
"input = '日本語'\nexpected_result = '5pel5pys6Kqe'\nactual_result, output = encode(input)\nassert actual_result == expected_result\nassert output == {'Base64': {'encoded': expected_result}}",
"input = 'test'\nexpected_result = 'dGVzdA=='\nactual_result, output = encode(input)\nassert actual_result == expected_resul... | <|body_start_0|>
input = '日本語'
expected_result = '5pel5pys6Kqe'
actual_result, output = encode(input)
assert actual_result == expected_result
assert output == {'Base64': {'encoded': expected_result}}
<|end_body_0|>
<|body_start_1|>
input = 'test'
expected_result ... | Base64EncodeV2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base64EncodeV2:
def test_encode_japanese(self):
"""Given: Japanese characters. When: Encoding the characters using Base64. Then: Validate that the human readable and context outputs are properly formatted and that the input was encoded correctly."""
<|body_0|>
def test_encod... | stack_v2_sparse_classes_36k_train_021438 | 3,044 | permissive | [
{
"docstring": "Given: Japanese characters. When: Encoding the characters using Base64. Then: Validate that the human readable and context outputs are properly formatted and that the input was encoded correctly.",
"name": "test_encode_japanese",
"signature": "def test_encode_japanese(self)"
},
{
... | 5 | null | Implement the Python class `Base64EncodeV2` described below.
Class description:
Implement the Base64EncodeV2 class.
Method signatures and docstrings:
- def test_encode_japanese(self): Given: Japanese characters. When: Encoding the characters using Base64. Then: Validate that the human readable and context outputs are... | Implement the Python class `Base64EncodeV2` described below.
Class description:
Implement the Base64EncodeV2 class.
Method signatures and docstrings:
- def test_encode_japanese(self): Given: Japanese characters. When: Encoding the characters using Base64. Then: Validate that the human readable and context outputs are... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class Base64EncodeV2:
def test_encode_japanese(self):
"""Given: Japanese characters. When: Encoding the characters using Base64. Then: Validate that the human readable and context outputs are properly formatted and that the input was encoded correctly."""
<|body_0|>
def test_encod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Base64EncodeV2:
def test_encode_japanese(self):
"""Given: Japanese characters. When: Encoding the characters using Base64. Then: Validate that the human readable and context outputs are properly formatted and that the input was encoded correctly."""
input = '日本語'
expected_result = '5pe... | the_stack_v2_python_sparse | Packs/CommonScripts/Scripts/Base64EncodeV2/Base64EncodeV2_test.py | demisto/content | train | 1,023 | |
06770868690021bfa5ea42778e21ff7285bb20b1 | [
"if A.shape[0] != A.shape[1]:\n print('Matrix must be square')\nself.dim = A.shape[0]\nif view is None:\n view = self.dim\nelse:\n assert view <= self.dim\nself._A_buf = A[:, :]\nself.n = view\nself.A = self._A_buf[:view, :view]",
"assert view <= self.dim\nself.n = view\nself.A = self._A_buf[:view, :view... | <|body_start_0|>
if A.shape[0] != A.shape[1]:
print('Matrix must be square')
self.dim = A.shape[0]
if view is None:
view = self.dim
else:
assert view <= self.dim
self._A_buf = A[:, :]
self.n = view
self.A = self._A_buf[:view, :v... | ScipyHessenberg | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScipyHessenberg:
def __init__(self, A, view=None):
"""Constructor :param A: Full storage real symmetric matrix to be tridiagonalized (is not overwritten) :param view: Integer, if present selects a sub-matrix of A starting from the top-left element, up until the row/column n = view. This ... | stack_v2_sparse_classes_36k_train_021439 | 5,175 | permissive | [
{
"docstring": "Constructor :param A: Full storage real symmetric matrix to be tridiagonalized (is not overwritten) :param view: Integer, if present selects a sub-matrix of A starting from the top-left element, up until the row/column n = view. This sub-matrix is then tridiagonalized instead of the full A",
... | 6 | stack_v2_sparse_classes_30k_train_020313 | Implement the Python class `ScipyHessenberg` described below.
Class description:
Implement the ScipyHessenberg class.
Method signatures and docstrings:
- def __init__(self, A, view=None): Constructor :param A: Full storage real symmetric matrix to be tridiagonalized (is not overwritten) :param view: Integer, if prese... | Implement the Python class `ScipyHessenberg` described below.
Class description:
Implement the ScipyHessenberg class.
Method signatures and docstrings:
- def __init__(self, A, view=None): Constructor :param A: Full storage real symmetric matrix to be tridiagonalized (is not overwritten) :param view: Integer, if prese... | daf37f522f8acb6af2285d44f39cab31f34b01a4 | <|skeleton|>
class ScipyHessenberg:
def __init__(self, A, view=None):
"""Constructor :param A: Full storage real symmetric matrix to be tridiagonalized (is not overwritten) :param view: Integer, if present selects a sub-matrix of A starting from the top-left element, up until the row/column n = view. This ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScipyHessenberg:
def __init__(self, A, view=None):
"""Constructor :param A: Full storage real symmetric matrix to be tridiagonalized (is not overwritten) :param view: Integer, if present selects a sub-matrix of A starting from the top-left element, up until the row/column n = view. This sub-matrix is ... | the_stack_v2_python_sparse | mapping/tridiag/scipy_hessenberg/full.py | fhoeb/py-mapping | train | 2 | |
407a5cc2239767789366aac65dc362cc9f6001bf | [
"self.current_usage_gib = current_usage_gib\nself.feature_name = feature_name\nself.num_vm = num_vm",
"if dictionary is None:\n return None\ncurrent_usage_gib = dictionary.get('currentUsageGiB')\nfeature_name = dictionary.get('featureName')\nnum_vm = dictionary.get('numVm')\nreturn cls(current_usage_gib, featu... | <|body_start_0|>
self.current_usage_gib = current_usage_gib
self.feature_name = feature_name
self.num_vm = num_vm
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
current_usage_gib = dictionary.get('currentUsageGiB')
feature_name = dictionar... | Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned. | FeatureUsage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, fea... | stack_v2_sparse_classes_36k_train_021440 | 1,804 | permissive | [
{
"docstring": "Constructor for the FeatureUsage class",
"name": "__init__",
"signature": "def __init__(self, current_usage_gib=None, feature_name=None, num_vm=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation... | 2 | stack_v2_sparse_classes_30k_train_019978 | Implement the Python class `FeatureUsage` described below.
Class description:
Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned.
Method signatu... | Implement the Python class `FeatureUsage` described below.
Class description:
Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned.
Method signatu... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, fea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeatureUsage:
"""Implementation of the 'FeatureUsage' model. TODO: type description here. Attributes: current_usage_gib (long|int): Feature usage by the cluster. feature_name (string): Name of feature. num_vm (long|int): Number of VM spinned."""
def __init__(self, current_usage_gib=None, feature_name=Non... | the_stack_v2_python_sparse | cohesity_management_sdk/models/feature_usage.py | cohesity/management-sdk-python | train | 24 |
7020c10ae6df9a131d61ab910d907159c820a7ff | [
"if Flavour.objects.filter(flavour=value.lower()):\n raise serializers.ValidationError('There already exist such flavour')\nreturn value",
"ret = super().to_representation(instance)\nret['flavour'] = ret['flavour'].lower()\nreturn ret"
] | <|body_start_0|>
if Flavour.objects.filter(flavour=value.lower()):
raise serializers.ValidationError('There already exist such flavour')
return value
<|end_body_0|>
<|body_start_1|>
ret = super().to_representation(instance)
ret['flavour'] = ret['flavour'].lower()
ret... | AddFlavourSerializers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddFlavourSerializers:
def validate_flavour(self, value):
"""Check the duplicate"""
<|body_0|>
def to_representation(self, instance):
"""Convert `flavour` to lowercase."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if Flavour.objects.filter(flavou... | stack_v2_sparse_classes_36k_train_021441 | 4,598 | permissive | [
{
"docstring": "Check the duplicate",
"name": "validate_flavour",
"signature": "def validate_flavour(self, value)"
},
{
"docstring": "Convert `flavour` to lowercase.",
"name": "to_representation",
"signature": "def to_representation(self, instance)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001203 | Implement the Python class `AddFlavourSerializers` described below.
Class description:
Implement the AddFlavourSerializers class.
Method signatures and docstrings:
- def validate_flavour(self, value): Check the duplicate
- def to_representation(self, instance): Convert `flavour` to lowercase. | Implement the Python class `AddFlavourSerializers` described below.
Class description:
Implement the AddFlavourSerializers class.
Method signatures and docstrings:
- def validate_flavour(self, value): Check the duplicate
- def to_representation(self, instance): Convert `flavour` to lowercase.
<|skeleton|>
class AddF... | 6a935bb77db3996dcf14b71deed8d7ca5c8f0fa3 | <|skeleton|>
class AddFlavourSerializers:
def validate_flavour(self, value):
"""Check the duplicate"""
<|body_0|>
def to_representation(self, instance):
"""Convert `flavour` to lowercase."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AddFlavourSerializers:
def validate_flavour(self, value):
"""Check the duplicate"""
if Flavour.objects.filter(flavour=value.lower()):
raise serializers.ValidationError('There already exist such flavour')
return value
def to_representation(self, instance):
"""Co... | the_stack_v2_python_sparse | drf_api/serializers.py | destro6984/LynxWasp | train | 0 | |
ca0842636576f6fdfe376aa78447e85642129def | [
"legalMoves = gameState.getLegalActions()\nscores = [self.evaluationFunction(gameState, action) for action in legalMoves]\nbestScore = max(scores)\nbestIndices = [index for index in range(len(scores)) if scores[index] == bestScore]\nchosenIndex = random.choice(bestIndices)\n'Add more of your code here if you want t... | <|body_start_0|>
legalMoves = gameState.getLegalActions()
scores = [self.evaluationFunction(gameState, action) for action in legalMoves]
bestScore = max(scores)
bestIndices = [index for index in range(len(scores)) if scores[index] == bestScore]
chosenIndex = random.choice(bestInd... | A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our method headers. | ReflexAgent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReflexAgent:
"""A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our method headers."""
def getAction(sel... | stack_v2_sparse_classes_36k_train_021442 | 16,868 | no_license | [
{
"docstring": "You do not need to change this method, but you're welcome to. getAction chooses among the best options according to the evaluation function. Just like in the previous project, getAction takes a GameState and returns some Directions.X for some X in the set {North, South, West, East, Stop}",
"... | 2 | stack_v2_sparse_classes_30k_train_007346 | Implement the Python class `ReflexAgent` described below.
Class description:
A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our me... | Implement the Python class `ReflexAgent` described below.
Class description:
A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our me... | fad5d28d3202056975a7e18805c1b20bd0d02d3e | <|skeleton|>
class ReflexAgent:
"""A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our method headers."""
def getAction(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReflexAgent:
"""A reflex agent chooses an action at each choice point by examining its alternatives via a state evaluation function. The code below is provided as a guide. You are welcome to change it in any way you see fit, so long as you don't touch our method headers."""
def getAction(self, gameState)... | the_stack_v2_python_sparse | Year 3/Computer Science 3346/Assignment 2/multiagent/multiAgents.py | UvSandhu13/School | train | 0 |
61ec6565de9752f5c567aa81cf1e4c403c4d9b24 | [
"if ref is not None:\n if not isinstance(ref, pd.Index):\n if hasattr(ref, 'columns') and isinstance(ref.index, pd.Index):\n ref = ref.columns\n else:\n ref = pd.Index(ref)\n obj = self._get_indices(ref, obj)\nif np.issubdtype(type(obj), np.integer):\n obj = int(obj)\nif isinsta... | <|body_start_0|>
if ref is not None:
if not isinstance(ref, pd.Index):
if hasattr(ref, 'columns') and isinstance(ref.index, pd.Index):
ref = ref.columns
else:
ref = pd.Index(ref)
obj = self._get_indices(ref, obj)
if ... | Mixin class with utilities for by-column applicates. | _ColumnEstimator | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ColumnEstimator:
"""Mixin class with utilities for by-column applicates."""
def _coerce_to_pd_index(self, obj, ref=None):
"""Coerce obj to pandas Index, replacing ints by index elements. Parameters ---------- obj : iterable of pandas compatible index elements or int ref : reference ... | stack_v2_sparse_classes_36k_train_021443 | 36,566 | permissive | [
{
"docstring": "Coerce obj to pandas Index, replacing ints by index elements. Parameters ---------- obj : iterable of pandas compatible index elements or int ref : reference index, coercible to pd.Index, optional, default=None Returns ------- obj coerced to pd.Index if ref was passed, and if obj had int or np.i... | 4 | stack_v2_sparse_classes_30k_train_020279 | Implement the Python class `_ColumnEstimator` described below.
Class description:
Mixin class with utilities for by-column applicates.
Method signatures and docstrings:
- def _coerce_to_pd_index(self, obj, ref=None): Coerce obj to pandas Index, replacing ints by index elements. Parameters ---------- obj : iterable of... | Implement the Python class `_ColumnEstimator` described below.
Class description:
Mixin class with utilities for by-column applicates.
Method signatures and docstrings:
- def _coerce_to_pd_index(self, obj, ref=None): Coerce obj to pandas Index, replacing ints by index elements. Parameters ---------- obj : iterable of... | 70b2bfaaa597eb31bc3a1032366dcc0e1f4c8a9f | <|skeleton|>
class _ColumnEstimator:
"""Mixin class with utilities for by-column applicates."""
def _coerce_to_pd_index(self, obj, ref=None):
"""Coerce obj to pandas Index, replacing ints by index elements. Parameters ---------- obj : iterable of pandas compatible index elements or int ref : reference ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _ColumnEstimator:
"""Mixin class with utilities for by-column applicates."""
def _coerce_to_pd_index(self, obj, ref=None):
"""Coerce obj to pandas Index, replacing ints by index elements. Parameters ---------- obj : iterable of pandas compatible index elements or int ref : reference index, coerci... | the_stack_v2_python_sparse | sktime/base/_meta.py | sktime/sktime | train | 1,117 |
4e589f8922519877ee6234a81b63ea36292a13a8 | [
"super().__init__()\nself.recursion_degree = recursion_degree\nself._sk = SolovayKitaevDecomposition(basic_approximations)",
"for node in dag.op_nodes():\n if not node.op.num_qubits == 1:\n continue\n check_input = not isinstance(node.op, Gate)\n if not hasattr(node.op, 'to_matrix'):\n rais... | <|body_start_0|>
super().__init__()
self.recursion_degree = recursion_degree
self._sk = SolovayKitaevDecomposition(basic_approximations)
<|end_body_0|>
<|body_start_1|>
for node in dag.op_nodes():
if not node.op.num_qubits == 1:
continue
check_inp... | Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if the set generates a dense subset in :math:`SU(2)`. This is an important result, si... | SolovayKitaev | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SolovayKitaev:
"""Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if the set generates a dense subset in :math... | stack_v2_sparse_classes_36k_train_021444 | 10,726 | permissive | [
{
"docstring": "Args: recursion_degree: The recursion depth for the Solovay-Kitaev algorithm. A larger recursion depth increases the accuracy and length of the decomposition. basic_approximations: The basic approximations for the finding the best discrete decomposition at the root of the recursion. If a string,... | 2 | stack_v2_sparse_classes_30k_train_000951 | Implement the Python class `SolovayKitaev` described below.
Class description:
Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if th... | Implement the Python class `SolovayKitaev` described below.
Class description:
Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if th... | 0b51250e219ca303654fc28a318c21366584ccd3 | <|skeleton|>
class SolovayKitaev:
"""Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if the set generates a dense subset in :math... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SolovayKitaev:
"""Approximately decompose 1q gates to a discrete basis using the Solovay-Kitaev algorithm. The Solovay-Kitaev theorem [1] states that any single qubit gate can be approximated to arbitrary precision by a set of fixed single-qubit gates, if the set generates a dense subset in :math:`SU(2)`. Thi... | the_stack_v2_python_sparse | qiskit/transpiler/passes/synthesis/solovay_kitaev_synthesis.py | 1ucian0/qiskit-terra | train | 6 |
ff300a3e0cd1d2a0e9bee71b1d60ec77a2cf763c | [
"super().__init__(thresholds=[1], threshold_units=threshold_units, comparison_operator=comparison_operator)\nif not callable(threshold_function):\n raise TypeError('Threshold must be callable')\nself.threshold_function = threshold_function",
"coord = iris.coords.AuxCoord(threshold.astype(FLOAT_DTYPE), units=cu... | <|body_start_0|>
super().__init__(thresholds=[1], threshold_units=threshold_units, comparison_operator=comparison_operator)
if not callable(threshold_function):
raise TypeError('Threshold must be callable')
self.threshold_function = threshold_function
<|end_body_0|>
<|body_start_1|>... | Apply a latitude-dependent threshold truth criterion to a cube. Calculates the threshold truth values based on the threshold function provided. A cube will be returned with a new threshold dimension auxillary coordinate on the latitude axis. Can operate on multiple time sequences within a cube. | LatitudeDependentThreshold | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LatitudeDependentThreshold:
"""Apply a latitude-dependent threshold truth criterion to a cube. Calculates the threshold truth values based on the threshold function provided. A cube will be returned with a new threshold dimension auxillary coordinate on the latitude axis. Can operate on multiple ... | stack_v2_sparse_classes_36k_train_021445 | 20,830 | permissive | [
{
"docstring": "Sets up latitude-dependent threshold class Args: threshold_function: A function which takes a latitude value (in degrees) and returns the desired threshold. threshold_units: Units of the threshold values. If not provided the units are assumed to be the same as those of the input cube. comparison... | 3 | null | Implement the Python class `LatitudeDependentThreshold` described below.
Class description:
Apply a latitude-dependent threshold truth criterion to a cube. Calculates the threshold truth values based on the threshold function provided. A cube will be returned with a new threshold dimension auxillary coordinate on the ... | Implement the Python class `LatitudeDependentThreshold` described below.
Class description:
Apply a latitude-dependent threshold truth criterion to a cube. Calculates the threshold truth values based on the threshold function provided. A cube will be returned with a new threshold dimension auxillary coordinate on the ... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class LatitudeDependentThreshold:
"""Apply a latitude-dependent threshold truth criterion to a cube. Calculates the threshold truth values based on the threshold function provided. A cube will be returned with a new threshold dimension auxillary coordinate on the latitude axis. Can operate on multiple ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LatitudeDependentThreshold:
"""Apply a latitude-dependent threshold truth criterion to a cube. Calculates the threshold truth values based on the threshold function provided. A cube will be returned with a new threshold dimension auxillary coordinate on the latitude axis. Can operate on multiple time sequence... | the_stack_v2_python_sparse | improver/threshold.py | metoppv/improver | train | 101 |
150f1f7d865ca13bed2d3a2dddd51e4ba8c8616d | [
"full_list = self.get_updated_list_from_DB('destination')\nfull_list.pop(0)\ndest_code = 0\nfor line in full_list:\n try:\n if int(line[8]) > dest_code:\n dest_code = int(line[8])\n except IndexError:\n continue\nadded_zero = ''\nif dest_code < 10:\n added_zero = '0'\ndestination_c... | <|body_start_0|>
full_list = self.get_updated_list_from_DB('destination')
full_list.pop(0)
dest_code = 0
for line in full_list:
try:
if int(line[8]) > dest_code:
dest_code = int(line[8])
except IndexError:
contin... | DestinationLL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DestinationLL:
def create_dest_code(self):
"""Creates a destination code fo destinations"""
<|body_0|>
def create_destination(self, destination_identity):
"""Creates a new destination and saves to database. destination_identity = ('',destination,country,flight_time,d... | stack_v2_sparse_classes_36k_train_021446 | 3,028 | no_license | [
{
"docstring": "Creates a destination code fo destinations",
"name": "create_dest_code",
"signature": "def create_dest_code(self)"
},
{
"docstring": "Creates a new destination and saves to database. destination_identity = ('',destination,country,flight_time,distance,contact,emergency_number,airp... | 5 | stack_v2_sparse_classes_30k_train_006189 | Implement the Python class `DestinationLL` described below.
Class description:
Implement the DestinationLL class.
Method signatures and docstrings:
- def create_dest_code(self): Creates a destination code fo destinations
- def create_destination(self, destination_identity): Creates a new destination and saves to data... | Implement the Python class `DestinationLL` described below.
Class description:
Implement the DestinationLL class.
Method signatures and docstrings:
- def create_dest_code(self): Creates a destination code fo destinations
- def create_destination(self, destination_identity): Creates a new destination and saves to data... | ee2b2e6c1422ebab40e36ed3ed23f6f70ee7adb2 | <|skeleton|>
class DestinationLL:
def create_dest_code(self):
"""Creates a destination code fo destinations"""
<|body_0|>
def create_destination(self, destination_identity):
"""Creates a new destination and saves to database. destination_identity = ('',destination,country,flight_time,d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DestinationLL:
def create_dest_code(self):
"""Creates a destination code fo destinations"""
full_list = self.get_updated_list_from_DB('destination')
full_list.pop(0)
dest_code = 0
for line in full_list:
try:
if int(line[8]) > dest_code:
... | the_stack_v2_python_sparse | program_code/LL/DestinationLL.py | heidars19/3ja-vikna-verkefni | train | 3 | |
a9352774fc72ec62d7d5e61b5d75d8b1be8d3c3c | [
"self.high_time = NI_HIGH_TIME\nself.frequency = NI_FREQUENCY\nself.low_time = 1.0 / self.frequency - self.high_time\nif self.low_time < NI_MINIMUM_LOW_TIME:\n self.low_time = NI_MINIMUM_LOW_TIME\nself.dev_name = NI_DEV_NAME\nself.out_pin = TRIG_GEN_PIN_OUT\nself.taskHandle = functions.TaskHandle(0)\nfunctions.D... | <|body_start_0|>
self.high_time = NI_HIGH_TIME
self.frequency = NI_FREQUENCY
self.low_time = 1.0 / self.frequency - self.high_time
if self.low_time < NI_MINIMUM_LOW_TIME:
self.low_time = NI_MINIMUM_LOW_TIME
self.dev_name = NI_DEV_NAME
self.out_pin = TRIG_GEN_P... | Controls the SEPIA and SuperK trigger signals, as produced by the NI Unit via commands sent down a USB port. | TriggerGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TriggerGenerator:
"""Controls the SEPIA and SuperK trigger signals, as produced by the NI Unit via commands sent down a USB port."""
def _setup(self):
"""Set up the single-pulse parameters - the high time and the low time, and the digital output channel X to be used. The channel stri... | stack_v2_sparse_classes_36k_train_021447 | 2,247 | no_license | [
{
"docstring": "Set up the single-pulse parameters - the high time and the low time, and the digital output channel X to be used. The channel string must be of the form `deviceName/digitalOutputPin`, i.e. `Dev1/Ctr0`. /Ctr0 is used by default, but can be changed in config.py if required.",
"name": "_setup",... | 3 | stack_v2_sparse_classes_30k_train_013444 | Implement the Python class `TriggerGenerator` described below.
Class description:
Controls the SEPIA and SuperK trigger signals, as produced by the NI Unit via commands sent down a USB port.
Method signatures and docstrings:
- def _setup(self): Set up the single-pulse parameters - the high time and the low time, and ... | Implement the Python class `TriggerGenerator` described below.
Class description:
Controls the SEPIA and SuperK trigger signals, as produced by the NI Unit via commands sent down a USB port.
Method signatures and docstrings:
- def _setup(self): Set up the single-pulse parameters - the high time and the low time, and ... | 9f7129c299f003e98259b1f141c22986535754af | <|skeleton|>
class TriggerGenerator:
"""Controls the SEPIA and SuperK trigger signals, as produced by the NI Unit via commands sent down a USB port."""
def _setup(self):
"""Set up the single-pulse parameters - the high time and the low time, and the digital output channel X to be used. The channel stri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TriggerGenerator:
"""Controls the SEPIA and SuperK trigger signals, as produced by the NI Unit via commands sent down a USB port."""
def _setup(self):
"""Set up the single-pulse parameters - the high time and the low time, and the digital output channel X to be used. The channel string must be of... | the_stack_v2_python_sparse | smellie/ni_trigger_generator.py | jackdunger/newSmellie | train | 0 |
d7b1d47e2b5ccd60b1b402c0bdcefd3d5153f836 | [
"from __builtin__ import xrange\ngraph = {i: [] for i in xrange(n)}\nfor e in edges:\n graph[e[0]] += (e[1],)\n graph[e[1]] += (e[0],)\n\ndef dfs(key):\n child = graph.pop(key, [])\n for c in child:\n dfs(c)\ncnt = 0\nwhile graph:\n key = graph.keys()[0]\n dfs(key)\n cnt += 1\nreturn cnt... | <|body_start_0|>
from __builtin__ import xrange
graph = {i: [] for i in xrange(n)}
for e in edges:
graph[e[0]] += (e[1],)
graph[e[1]] += (e[0],)
def dfs(key):
child = graph.pop(key, [])
for c in child:
dfs(c)
cnt = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countComponents(self, n, edges):
""":type n: int :type edges: List[List[int]] :rtype: int"""
<|body_0|>
def rewrite(self, n, edges):
""":type n: int :type edges: List[List[int]] :rtype: int"""
<|body_1|>
def rewrite2(self, n, edges):
... | stack_v2_sparse_classes_36k_train_021448 | 3,101 | no_license | [
{
"docstring": ":type n: int :type edges: List[List[int]] :rtype: int",
"name": "countComponents",
"signature": "def countComponents(self, n, edges)"
},
{
"docstring": ":type n: int :type edges: List[List[int]] :rtype: int",
"name": "rewrite",
"signature": "def rewrite(self, n, edges)"
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countComponents(self, n, edges): :type n: int :type edges: List[List[int]] :rtype: int
- def rewrite(self, n, edges): :type n: int :type edges: List[List[int]] :rtype: int
- ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countComponents(self, n, edges): :type n: int :type edges: List[List[int]] :rtype: int
- def rewrite(self, n, edges): :type n: int :type edges: List[List[int]] :rtype: int
- ... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def countComponents(self, n, edges):
""":type n: int :type edges: List[List[int]] :rtype: int"""
<|body_0|>
def rewrite(self, n, edges):
""":type n: int :type edges: List[List[int]] :rtype: int"""
<|body_1|>
def rewrite2(self, n, edges):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countComponents(self, n, edges):
""":type n: int :type edges: List[List[int]] :rtype: int"""
from __builtin__ import xrange
graph = {i: [] for i in xrange(n)}
for e in edges:
graph[e[0]] += (e[1],)
graph[e[1]] += (e[0],)
def dfs(ke... | the_stack_v2_python_sparse | graph/323_Number_of_Connected_Components_in_an_Undirected_Graph.py | vsdrun/lc_public | train | 6 | |
dc5e90251ee087fa66c612d57b10581085b11404 | [
"if x < 0:\n return False\ny = self.reverse(x)\nreturn y == x",
"if x is None:\n return None\nif x == 0:\n return 0\nx_str = str(x)\nif x_str.find('-') == -1:\n x_array = list(x_str)\n reversed_array = x_array\n reversed_array.reverse()\n i = 0\n while reversed_array[i] == '0':\n i ... | <|body_start_0|>
if x < 0:
return False
y = self.reverse(x)
return y == x
<|end_body_0|>
<|body_start_1|>
if x is None:
return None
if x == 0:
return 0
x_str = str(x)
if x_str.find('-') == -1:
x_array = list(x_str)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_0|>
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if x < 0:
return False
y = self.reverse(x)
... | stack_v2_sparse_classes_36k_train_021449 | 2,674 | no_license | [
{
"docstring": ":type x: int :rtype: bool",
"name": "isPalindrome",
"signature": "def isPalindrome(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse",
"signature": "def reverse(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013700 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, x): :type x: int :rtype: bool
- def reverse(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, x): :type x: int :rtype: bool
- def reverse(self, x): :type x: int :rtype: int
<|skeleton|>
class Solution:
def isPalindrome(self, x):
""":ty... | 71a02a2c6bc12e86119502c9c4a4b2047b9f3966 | <|skeleton|>
class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
<|body_0|>
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, x):
""":type x: int :rtype: bool"""
if x < 0:
return False
y = self.reverse(x)
return y == x
def reverse(self, x):
""":type x: int :rtype: int"""
if x is None:
return None
if x == 0:
... | the_stack_v2_python_sparse | Math/9. Palindrome Number(easy).py | xilixjd/leetcode | train | 1 | |
9fbb26001a4626f2cae63159fd5b981d93e044d6 | [
"astCtxt = self.Triton.getAstContext()\nwhile pc:\n opcode = self.Triton.getConcreteMemoryAreaValue(pc, 16)\n instruction = Instruction()\n instruction.setOpcode(opcode)\n instruction.setAddress(pc)\n self.Triton.processing(instruction)\n self.assertTrue(checkAstIntegrity(instruction))\n if ins... | <|body_start_0|>
astCtxt = self.Triton.getAstContext()
while pc:
opcode = self.Triton.getConcreteMemoryAreaValue(pc, 16)
instruction = Instruction()
instruction.setOpcode(opcode)
instruction.setAddress(pc)
self.Triton.processing(instruction)
... | Test for DefCamp2015 challenge. | DefCamp2015 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefCamp2015:
"""Test for DefCamp2015 challenge."""
def emulate(self, pc):
"""Emulate every opcode from pc. * Process instruction until the end and search for constraint resolution on cmp eax, 1 then self.Triton.set the new correct value and keep going."""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_021450 | 18,108 | permissive | [
{
"docstring": "Emulate every opcode from pc. * Process instruction until the end and search for constraint resolution on cmp eax, 1 then self.Triton.set the new correct value and keep going.",
"name": "emulate",
"signature": "def emulate(self, pc)"
},
{
"docstring": "Load in memory every opcode... | 3 | stack_v2_sparse_classes_30k_train_021400 | Implement the Python class `DefCamp2015` described below.
Class description:
Test for DefCamp2015 challenge.
Method signatures and docstrings:
- def emulate(self, pc): Emulate every opcode from pc. * Process instruction until the end and search for constraint resolution on cmp eax, 1 then self.Triton.set the new corr... | Implement the Python class `DefCamp2015` described below.
Class description:
Test for DefCamp2015 challenge.
Method signatures and docstrings:
- def emulate(self, pc): Emulate every opcode from pc. * Process instruction until the end and search for constraint resolution on cmp eax, 1 then self.Triton.set the new corr... | a61651ce331ac53ec09e1d8fef5eab744e98c9de | <|skeleton|>
class DefCamp2015:
"""Test for DefCamp2015 challenge."""
def emulate(self, pc):
"""Emulate every opcode from pc. * Process instruction until the end and search for constraint resolution on cmp eax, 1 then self.Triton.set the new correct value and keep going."""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DefCamp2015:
"""Test for DefCamp2015 challenge."""
def emulate(self, pc):
"""Emulate every opcode from pc. * Process instruction until the end and search for constraint resolution on cmp eax, 1 then self.Triton.set the new correct value and keep going."""
astCtxt = self.Triton.getAstConte... | the_stack_v2_python_sparse | src/testers/unittests/test_simulation.py | JonathanSalwan/Triton | train | 3,163 |
b77cb76ad8480d5843c9005817fdd15e26b278a8 | [
"super(QtEnum, self).__init__()\nself._default_value = value\nEnum.__init__(self, value, *args, choices=choices, **kwargs)\nself._layout = QtWidgets.QHBoxLayout()\nself._init_ui()\nself.setLayout(self._layout)",
"if self._default_value not in self.choices:\n self._combo.insertItem(0, '----Undefined----')\n ... | <|body_start_0|>
super(QtEnum, self).__init__()
self._default_value = value
Enum.__init__(self, value, *args, choices=choices, **kwargs)
self._layout = QtWidgets.QHBoxLayout()
self._init_ui()
self.setLayout(self._layout)
<|end_body_0|>
<|body_start_1|>
if self._d... | Define an enum user selection control. | QtEnum | [
"LicenseRef-scancode-cecill-b-en"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QtEnum:
"""Define an enum user selection control."""
def __init__(self, choices, value=None, *args, **kwargs):
"""Initialize the 'QtEnum' class. Parameters ---------- choices: list of str the different choices. value: object (optional, default None) the parameter value."""
<|... | stack_v2_sparse_classes_36k_train_021451 | 2,900 | permissive | [
{
"docstring": "Initialize the 'QtEnum' class. Parameters ---------- choices: list of str the different choices. value: object (optional, default None) the parameter value.",
"name": "__init__",
"signature": "def __init__(self, choices, value=None, *args, **kwargs)"
},
{
"docstring": "Reset the ... | 4 | stack_v2_sparse_classes_30k_train_019010 | Implement the Python class `QtEnum` described below.
Class description:
Define an enum user selection control.
Method signatures and docstrings:
- def __init__(self, choices, value=None, *args, **kwargs): Initialize the 'QtEnum' class. Parameters ---------- choices: list of str the different choices. value: object (o... | Implement the Python class `QtEnum` described below.
Class description:
Define an enum user selection control.
Method signatures and docstrings:
- def __init__(self, choices, value=None, *args, **kwargs): Initialize the 'QtEnum' class. Parameters ---------- choices: list of str the different choices. value: object (o... | a77fc2c81cb469535b650c79718f811c5c056238 | <|skeleton|>
class QtEnum:
"""Define an enum user selection control."""
def __init__(self, choices, value=None, *args, **kwargs):
"""Initialize the 'QtEnum' class. Parameters ---------- choices: list of str the different choices. value: object (optional, default None) the parameter value."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QtEnum:
"""Define an enum user selection control."""
def __init__(self, choices, value=None, *args, **kwargs):
"""Initialize the 'QtEnum' class. Parameters ---------- choices: list of str the different choices. value: object (optional, default None) the parameter value."""
super(QtEnum, s... | the_stack_v2_python_sparse | pypipe/gui/controls/enum.py | AGrigis/pypipe | train | 0 |
0a98861fa43c1a7bd2ebcadb706761d0b98bec02 | [
"self.res = []\ncol, left, right = (defaultdict(int), defaultdict(int), defaultdict(int))\nboard = [['.' for i in range(n)] for j in range(n)]\nself.dfs(n, board, -1, col, left, right)\nreturn self.res",
"if k == n - 1:\n self.res.append([''.join(board[i]) for i in range(n)])\n return\nfor c in range(n):\n ... | <|body_start_0|>
self.res = []
col, left, right = (defaultdict(int), defaultdict(int), defaultdict(int))
board = [['.' for i in range(n)] for j in range(n)]
self.dfs(n, board, -1, col, left, right)
return self.res
<|end_body_0|>
<|body_start_1|>
if k == n - 1:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def solveNQueens(self, n):
""":type n: int :rtype: List[List[str]]"""
<|body_0|>
def dfs(self, n, board, k, col, left, right):
""":type board: List[str] :type k: int (k queens has been in the board) :type res: List[List[str]] :type col: dict[int] :rtype: bo... | stack_v2_sparse_classes_36k_train_021452 | 1,234 | no_license | [
{
"docstring": ":type n: int :rtype: List[List[str]]",
"name": "solveNQueens",
"signature": "def solveNQueens(self, n)"
},
{
"docstring": ":type board: List[str] :type k: int (k queens has been in the board) :type res: List[List[str]] :type col: dict[int] :rtype: boolean",
"name": "dfs",
... | 2 | stack_v2_sparse_classes_30k_train_012561 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solveNQueens(self, n): :type n: int :rtype: List[List[str]]
- def dfs(self, n, board, k, col, left, right): :type board: List[str] :type k: int (k queens has been in the boar... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solveNQueens(self, n): :type n: int :rtype: List[List[str]]
- def dfs(self, n, board, k, col, left, right): :type board: List[str] :type k: int (k queens has been in the boar... | 2f46f85e1e297b0a50fdb66956b1d05622a4063d | <|skeleton|>
class Solution:
def solveNQueens(self, n):
""":type n: int :rtype: List[List[str]]"""
<|body_0|>
def dfs(self, n, board, k, col, left, right):
""":type board: List[str] :type k: int (k queens has been in the board) :type res: List[List[str]] :type col: dict[int] :rtype: bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def solveNQueens(self, n):
""":type n: int :rtype: List[List[str]]"""
self.res = []
col, left, right = (defaultdict(int), defaultdict(int), defaultdict(int))
board = [['.' for i in range(n)] for j in range(n)]
self.dfs(n, board, -1, col, left, right)
r... | the_stack_v2_python_sparse | dan/Problems/Hard/Backtracking/51. N-Queens/solution.py | xudaaaaan/Leetcode | train | 0 | |
5ff8001c1a25fd4c65e3f890857be1f62c4ad09f | [
"self.model_names = []\nself.model_weights = {}\nself.cv_results = {}\nself.predictions_by_model = {}\nself.weighted_average_predictions = {}\nself.metadata = {}\nself.rank_scheme = {1: 0.4, 2: 0.3, 3: 0.2, 4: 0.1, 5: 0.0, 6: 0.0}",
"cv_scores = []\nfor model_name in self.cv_results:\n cv_scores.append(self.cv... | <|body_start_0|>
self.model_names = []
self.model_weights = {}
self.cv_results = {}
self.predictions_by_model = {}
self.weighted_average_predictions = {}
self.metadata = {}
self.rank_scheme = {1: 0.4, 2: 0.3, 3: 0.2, 4: 0.1, 5: 0.0, 6: 0.0}
<|end_body_0|>
<|body_... | Methods and attributes to average the predictions of a group of models. | WeightedAverage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeightedAverage:
"""Methods and attributes to average the predictions of a group of models."""
def __init__(self):
"""rank_scheme: weights applied to each model rank, where the first-ranked model is the best."""
<|body_0|>
def calculate_model_weights(self):
"""As... | stack_v2_sparse_classes_36k_train_021453 | 3,100 | permissive | [
{
"docstring": "rank_scheme: weights applied to each model rank, where the first-ranked model is the best.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Assign weights to each model's prediction.",
"name": "calculate_model_weights",
"signature": "def calculat... | 5 | stack_v2_sparse_classes_30k_train_003221 | Implement the Python class `WeightedAverage` described below.
Class description:
Methods and attributes to average the predictions of a group of models.
Method signatures and docstrings:
- def __init__(self): rank_scheme: weights applied to each model rank, where the first-ranked model is the best.
- def calculate_mo... | Implement the Python class `WeightedAverage` described below.
Class description:
Methods and attributes to average the predictions of a group of models.
Method signatures and docstrings:
- def __init__(self): rank_scheme: weights applied to each model rank, where the first-ranked model is the best.
- def calculate_mo... | 7e73d6a51bb3e8d2963c6d2f021caac2108cc4c0 | <|skeleton|>
class WeightedAverage:
"""Methods and attributes to average the predictions of a group of models."""
def __init__(self):
"""rank_scheme: weights applied to each model rank, where the first-ranked model is the best."""
<|body_0|>
def calculate_model_weights(self):
"""As... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WeightedAverage:
"""Methods and attributes to average the predictions of a group of models."""
def __init__(self):
"""rank_scheme: weights applied to each model rank, where the first-ranked model is the best."""
self.model_names = []
self.model_weights = {}
self.cv_results... | the_stack_v2_python_sparse | models/weighted_average.py | tzhangwps/Recession-Predictor | train | 26 |
10323c3277187b84d7be49819f9c117b2bfc966f | [
"self.capacity = capacity\nself.cache = dict()\nself.usedtime = dict()\nself.usedtimeheap = []\nself.time = -1",
"if key not in self.cache:\n return -1\nself.time += 1\nheapq.heappush(self.usedtimeheap, (self.time, key))\nself.usedtime[key] = self.time\nreturn self.cache[key]",
"self.time += 1\nif key in sel... | <|body_start_0|>
self.capacity = capacity
self.cache = dict()
self.usedtime = dict()
self.usedtimeheap = []
self.time = -1
<|end_body_0|>
<|body_start_1|>
if key not in self.cache:
return -1
self.time += 1
heapq.heappush(self.usedtimeheap, (se... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_021454 | 1,462 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: void",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void
<|sk... | 4d340a45fb2e9459d47cbe179ebfa7a82e5f1b8c | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.cache = dict()
self.usedtime = dict()
self.usedtimeheap = []
self.time = -1
def get(self, key):
""":type key: int :rtype: int"""
if key not in se... | the_stack_v2_python_sparse | 146_LRUCache/solution2.py | llgeek/leetcode | train | 1 | |
0992cd38aa81bb34086865ad3d282a3a5460bb7a | [
"ret = Trie(a_ignorecase=True)\nfor lexpath_i in a_lexicons:\n lexname = os.path.splitext(os.path.basename(lexpath_i))[0]\n self._logger.debug('Reading lexicon %s...', lexname)\n lexicon = pd.read_table(lexpath_i, header=None, names=LEX_CLMS, dtype=LEX_TYPES, encoding=a_encoding, error_bad_lines=False, war... | <|body_start_0|>
ret = Trie(a_ignorecase=True)
for lexpath_i in a_lexicons:
lexname = os.path.splitext(os.path.basename(lexpath_i))[0]
self._logger.debug('Reading lexicon %s...', lexname)
lexicon = pd.read_table(lexpath_i, header=None, names=LEX_CLMS, dtype=LEX_TYPES,... | Abstract class for lexicon-based SA using conditional probabilities. | CondProbLexiconBaseAnalyzer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CondProbLexiconBaseAnalyzer:
"""Abstract class for lexicon-based SA using conditional probabilities."""
def _read_lexicons(self, a_lexicons, a_encoding=ENCODING):
"""Overrides the method of the parent class, superseding. Args: a_lexicons (list): tags of the input instance a_encoding ... | stack_v2_sparse_classes_36k_train_021455 | 21,801 | permissive | [
{
"docstring": "Overrides the method of the parent class, superseding. Args: a_lexicons (list): tags of the input instance a_encoding (str): input encoding Returns: cgsa.utils.trie.Trie: constructed polar terms trie",
"name": "_read_lexicons",
"signature": "def _read_lexicons(self, a_lexicons, a_encodin... | 2 | stack_v2_sparse_classes_30k_train_015205 | Implement the Python class `CondProbLexiconBaseAnalyzer` described below.
Class description:
Abstract class for lexicon-based SA using conditional probabilities.
Method signatures and docstrings:
- def _read_lexicons(self, a_lexicons, a_encoding=ENCODING): Overrides the method of the parent class, superseding. Args: ... | Implement the Python class `CondProbLexiconBaseAnalyzer` described below.
Class description:
Abstract class for lexicon-based SA using conditional probabilities.
Method signatures and docstrings:
- def _read_lexicons(self, a_lexicons, a_encoding=ENCODING): Overrides the method of the parent class, superseding. Args: ... | c5af073f064db67d92b22705899c0d0263caec58 | <|skeleton|>
class CondProbLexiconBaseAnalyzer:
"""Abstract class for lexicon-based SA using conditional probabilities."""
def _read_lexicons(self, a_lexicons, a_encoding=ENCODING):
"""Overrides the method of the parent class, superseding. Args: a_lexicons (list): tags of the input instance a_encoding ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CondProbLexiconBaseAnalyzer:
"""Abstract class for lexicon-based SA using conditional probabilities."""
def _read_lexicons(self, a_lexicons, a_encoding=ENCODING):
"""Overrides the method of the parent class, superseding. Args: a_lexicons (list): tags of the input instance a_encoding (str): input ... | the_stack_v2_python_sparse | cgsa/lexicon/base.py | gghidiu/CGSA | train | 0 |
90bb4f0e13c4dfbad464e855fa6ce8530677ba8b | [
"if not -2 ** 31 < x < 2 ** 31 - 1:\n return 0\nif x < 0:\n y = int(str(-x)[::-1]) * -1\nelse:\n y = int(str(x)[::-1])\nif not -2 ** 31 < y < 2 ** 31 - 1:\n return 0\nreturn y",
"x = str(x)\nif '-' not in str(x):\n y = int(str(x)[::-1])\nelse:\n x = [v for v in x if v != '-']\n x = ''.join(x)... | <|body_start_0|>
if not -2 ** 31 < x < 2 ** 31 - 1:
return 0
if x < 0:
y = int(str(-x)[::-1]) * -1
else:
y = int(str(x)[::-1])
if not -2 ** 31 < y < 2 ** 31 - 1:
return 0
return y
<|end_body_0|>
<|body_start_1|>
x = str(x)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse_str(self, x):
""":type x: int :rtype: int"""
<|body_1|>
def reverse_math(self, x):
""":type x: int :rtype: int"""
<|body_2|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_021456 | 1,905 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "reverse",
"signature": "def reverse(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse_str",
"signature": "def reverse_str(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse_math",... | 3 | stack_v2_sparse_classes_30k_test_000801 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): :type x: int :rtype: int
- def reverse_str(self, x): :type x: int :rtype: int
- def reverse_math(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse(self, x): :type x: int :rtype: int
- def reverse_str(self, x): :type x: int :rtype: int
- def reverse_math(self, x): :type x: int :rtype: int
<|skeleton|>
class Solu... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse_str(self, x):
""":type x: int :rtype: int"""
<|body_1|>
def reverse_math(self, x):
""":type x: int :rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse(self, x):
""":type x: int :rtype: int"""
if not -2 ** 31 < x < 2 ** 31 - 1:
return 0
if x < 0:
y = int(str(-x)[::-1]) * -1
else:
y = int(str(x)[::-1])
if not -2 ** 31 < y < 2 ** 31 - 1:
return 0
... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00007.Reverse Integer.py | roger6blog/LeetCode | train | 0 | |
3035c4c4d58d458eafadde25f21844f34872f05a | [
"super(HistoryWithEarlyStopping, self).__init__(historydir)\nassert isinstance(max_patience, int), '\"max_patience\" should be a positive integer.'\nassert isinstance(max_change, int), '\"max_change\" should be a positive integer.'\nself.patience = 0\nself.change = 0\nself.max_patience = max_patience\nself.max_chan... | <|body_start_0|>
super(HistoryWithEarlyStopping, self).__init__(historydir)
assert isinstance(max_patience, int), '"max_patience" should be a positive integer.'
assert isinstance(max_change, int), '"max_change" should be a positive integer.'
self.patience = 0
self.change = 0
... | This class implements History class with early stopping signals. Control (or try to control) training by returning behavior flags. Early stopping is applied. | HistoryWithEarlyStopping | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HistoryWithEarlyStopping:
"""This class implements History class with early stopping signals. Control (or try to control) training by returning behavior flags. Early stopping is applied."""
def __init__(self, historydir, max_patience=10, max_change=3):
"""This function initializes th... | stack_v2_sparse_classes_36k_train_021457 | 12,468 | permissive | [
{
"docstring": "This function initializes the class. Initialize with how long we wait and how many times we change learning rate. Learning rate change is done by a scheduler, not by this class. Parameters --------- historydir: string a string of path where we should make history directory. training history will... | 2 | stack_v2_sparse_classes_30k_train_017454 | Implement the Python class `HistoryWithEarlyStopping` described below.
Class description:
This class implements History class with early stopping signals. Control (or try to control) training by returning behavior flags. Early stopping is applied.
Method signatures and docstrings:
- def __init__(self, historydir, max... | Implement the Python class `HistoryWithEarlyStopping` described below.
Class description:
This class implements History class with early stopping signals. Control (or try to control) training by returning behavior flags. Early stopping is applied.
Method signatures and docstrings:
- def __init__(self, historydir, max... | 7585261dd1b1c6c99dada5d2d1aabf482e89e880 | <|skeleton|>
class HistoryWithEarlyStopping:
"""This class implements History class with early stopping signals. Control (or try to control) training by returning behavior flags. Early stopping is applied."""
def __init__(self, historydir, max_patience=10, max_change=3):
"""This function initializes th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HistoryWithEarlyStopping:
"""This class implements History class with early stopping signals. Control (or try to control) training by returning behavior flags. Early stopping is applied."""
def __init__(self, historydir, max_patience=10, max_change=3):
"""This function initializes the class. Init... | the_stack_v2_python_sparse | lemontree/controls/history.py | khshim/lemontree | train | 3 |
34289ca0ce5ec0431cbe4dbfe9942e3e5fa84c72 | [
"if not value:\n return []\ndelimters = '[, \\\\-!?:\\t]+'\nreturn list(filter(None, re.split(delimters, value)))",
"super(MultiPriceField, self).validate(value)\nif len(value) > 0 and len(value) != 11:\n raise ValidationError('Must have 11 values, separated by commas, spaces or tabs.')\nfor price in value:... | <|body_start_0|>
if not value:
return []
delimters = '[, \\-!?:\t]+'
return list(filter(None, re.split(delimters, value)))
<|end_body_0|>
<|body_start_1|>
super(MultiPriceField, self).validate(value)
if len(value) > 0 and len(value) != 11:
raise Validatio... | MultiPriceField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiPriceField:
def to_python(self, value):
"""Normalize data to a list of strings."""
<|body_0|>
def validate(self, value):
"""Check if value consists only of valid emails."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not value:
... | stack_v2_sparse_classes_36k_train_021458 | 6,902 | no_license | [
{
"docstring": "Normalize data to a list of strings.",
"name": "to_python",
"signature": "def to_python(self, value)"
},
{
"docstring": "Check if value consists only of valid emails.",
"name": "validate",
"signature": "def validate(self, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000109 | Implement the Python class `MultiPriceField` described below.
Class description:
Implement the MultiPriceField class.
Method signatures and docstrings:
- def to_python(self, value): Normalize data to a list of strings.
- def validate(self, value): Check if value consists only of valid emails. | Implement the Python class `MultiPriceField` described below.
Class description:
Implement the MultiPriceField class.
Method signatures and docstrings:
- def to_python(self, value): Normalize data to a list of strings.
- def validate(self, value): Check if value consists only of valid emails.
<|skeleton|>
class Mult... | ebff02b1e6c95b653f027f0e05125b754c6af5af | <|skeleton|>
class MultiPriceField:
def to_python(self, value):
"""Normalize data to a list of strings."""
<|body_0|>
def validate(self, value):
"""Check if value consists only of valid emails."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiPriceField:
def to_python(self, value):
"""Normalize data to a list of strings."""
if not value:
return []
delimters = '[, \\-!?:\t]+'
return list(filter(None, re.split(delimters, value)))
def validate(self, value):
"""Check if value consists only ... | the_stack_v2_python_sparse | lcf/forms.py | gamzatti/lcf | train | 0 | |
5dc9fdf5b7156f915f03771ce9dca1b36c9413d6 | [
"data = request.query_params\nnext_month_only = data.get('next_month_only', True)\nnext_month_days_off = get_ua_days_off(next_month_only)\nreturn json_response_success(data=next_month_days_off)",
"email = request.data.get('email', None)\nif not email:\n return json_response_error(\"Should provide customer's em... | <|body_start_0|>
data = request.query_params
next_month_only = data.get('next_month_only', True)
next_month_days_off = get_ua_days_off(next_month_only)
return json_response_success(data=next_month_days_off)
<|end_body_0|>
<|body_start_1|>
email = request.data.get('email', None)
... | DaysOff | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DaysOff:
def get(self, request):
"""parameters: - name: next_month_only description: show only next month days off required: false type: bool"""
<|body_0|>
def post(self, request):
"""parameters: - name: email description: client's email to whom we should send an ema... | stack_v2_sparse_classes_36k_train_021459 | 43,187 | no_license | [
{
"docstring": "parameters: - name: next_month_only description: show only next month days off required: false type: bool",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "parameters: - name: email description: client's email to whom we should send an email required: true... | 2 | stack_v2_sparse_classes_30k_test_000698 | Implement the Python class `DaysOff` described below.
Class description:
Implement the DaysOff class.
Method signatures and docstrings:
- def get(self, request): parameters: - name: next_month_only description: show only next month days off required: false type: bool
- def post(self, request): parameters: - name: ema... | Implement the Python class `DaysOff` described below.
Class description:
Implement the DaysOff class.
Method signatures and docstrings:
- def get(self, request): parameters: - name: next_month_only description: show only next month days off required: false type: bool
- def post(self, request): parameters: - name: ema... | ef392f0ec6f5a4eac2ecb48606ccfe753ffacd2e | <|skeleton|>
class DaysOff:
def get(self, request):
"""parameters: - name: next_month_only description: show only next month days off required: false type: bool"""
<|body_0|>
def post(self, request):
"""parameters: - name: email description: client's email to whom we should send an ema... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DaysOff:
def get(self, request):
"""parameters: - name: next_month_only description: show only next month days off required: false type: bool"""
data = request.query_params
next_month_only = data.get('next_month_only', True)
next_month_days_off = get_ua_days_off(next_month_only... | the_stack_v2_python_sparse | erp_django/apps/core/views.py | Uvik-Software/erp-django | train | 0 | |
2bd6a5b6804b37d8349b5cf1512d564ac77dcf6d | [
"super(BcombCombiner, self).__init__(prob_estimators=prob_estimators, verbose=verbose)\nself.k = k\nself.s = s\nself.beta = beta\nself.bcomb_prior_log_prob = None\nself.prev_word2id = {}",
"if self.bcomb_prior_log_prob is None or self.prev_word2id != word2id:\n self.bcomb_prior_log_prob = self.get_prior_log_pr... | <|body_start_0|>
super(BcombCombiner, self).__init__(prob_estimators=prob_estimators, verbose=verbose)
self.k = k
self.s = s
self.beta = beta
self.bcomb_prior_log_prob = None
self.prev_word2id = {}
<|end_body_0|>
<|body_start_1|>
if self.bcomb_prior_log_prob is N... | BcombCombiner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BcombCombiner:
def __init__(self, prob_estimators: List[BaseProbEstimator], k: float=4.0, s: float=1.05, beta: float=0.0, verbose: bool=False):
"""Combines models predictions with the log-probs that comes from embedding similarity scores according to the formula :math:`P(w|C, T) \\propto... | stack_v2_sparse_classes_36k_train_021460 | 12,750 | permissive | [
{
"docstring": "Combines models predictions with the log-probs that comes from embedding similarity scores according to the formula :math:`P(w|C, T) \\\\propto \\\\displaystyle \\\\frac{P(w|C)P(w|T)}{P(w)^\\\\beta}`, where :math:`\\\\beta` -- is a parameter controlling how we penalize frequent words and :math:`... | 4 | stack_v2_sparse_classes_30k_train_013108 | Implement the Python class `BcombCombiner` described below.
Class description:
Implement the BcombCombiner class.
Method signatures and docstrings:
- def __init__(self, prob_estimators: List[BaseProbEstimator], k: float=4.0, s: float=1.05, beta: float=0.0, verbose: bool=False): Combines models predictions with the lo... | Implement the Python class `BcombCombiner` described below.
Class description:
Implement the BcombCombiner class.
Method signatures and docstrings:
- def __init__(self, prob_estimators: List[BaseProbEstimator], k: float=4.0, s: float=1.05, beta: float=0.0, verbose: bool=False): Combines models predictions with the lo... | c87f67e5fe51fc8307b5d5ff8f404f202f17ab5e | <|skeleton|>
class BcombCombiner:
def __init__(self, prob_estimators: List[BaseProbEstimator], k: float=4.0, s: float=1.05, beta: float=0.0, verbose: bool=False):
"""Combines models predictions with the log-probs that comes from embedding similarity scores according to the formula :math:`P(w|C, T) \\propto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BcombCombiner:
def __init__(self, prob_estimators: List[BaseProbEstimator], k: float=4.0, s: float=1.05, beta: float=0.0, verbose: bool=False):
"""Combines models predictions with the log-probs that comes from embedding similarity scores according to the formula :math:`P(w|C, T) \\propto \\displaystyl... | the_stack_v2_python_sparse | lexsubgen/prob_estimators/combiner.py | agoel00/LexSubGen | train | 0 | |
658244538eaa6488439b4d4dab8e124db83a6892 | [
"from heapq import *\nself.l = []\nself.r = []",
"if len(self.l) == len(self.r):\n heappush(self.r, -heappushpop(self.l, -num))\nelse:\n heappush(self.l, -heappushpop(self.r, num))",
"if len(self.l) == len(self.r):\n return (self.r[0] - self.l[0]) / 2.0\nelse:\n return self.r[0]"
] | <|body_start_0|>
from heapq import *
self.l = []
self.r = []
<|end_body_0|>
<|body_start_1|>
if len(self.l) == len(self.r):
heappush(self.r, -heappushpop(self.l, -num))
else:
heappush(self.l, -heappushpop(self.r, num))
<|end_body_1|>
<|body_start_2|>
... | MedianFinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: None"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_021461 | 1,661 | no_license | [
{
"docstring": "initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type num: int :rtype: None",
"name": "addNum",
"signature": "def addNum(self, num)"
},
{
"docstring": ":rtype: float",
"name": "findMedian",
"s... | 3 | null | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: None
- def findMedian(self): :rtype: float | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: None
- def findMedian(self): :rtype: float
<|skeleton|>
class Me... | 45be00e9451ea0b3a8fe8f77f9b0d28d92b6482b | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: None"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
from heapq import *
self.l = []
self.r = []
def addNum(self, num):
""":type num: int :rtype: None"""
if len(self.l) == len(self.r):
heappush(self.r, -heappushpop(self.l... | the_stack_v2_python_sparse | Python/C295.py | reyllama/leetcode | train | 0 | |
20c2dcae35bc686dfc4a705b25d016f285dd72f6 | [
"self.X = X_init\nself.Y = Y_init\nself.L = L\nself.sigma_f = sigma_f\nself.K = self.kernel(self.X, self.X)",
"sqdist = np.sum(X1 ** 2, 1).reshape(-1, 1) + np.sum(X2 ** 2, 1) - 2 * np.dot(X1, X2.T)\ncovMatrix = self.sigma_f ** 2 * np.exp(-0.5 / self.L ** 2 * sqdist)\nprint(covMatrix)\nreturn covMatrix",
"kern =... | <|body_start_0|>
self.X = X_init
self.Y = Y_init
self.L = L
self.sigma_f = sigma_f
self.K = self.kernel(self.X, self.X)
<|end_body_0|>
<|body_start_1|>
sqdist = np.sum(X1 ** 2, 1).reshape(-1, 1) + np.sum(X2 ** 2, 1) - 2 * np.dot(X1, X2.T)
covMatrix = self.sigma_f... | Class reoresents noisless 1D Gaussian Process | GaussianProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianProcess:
"""Class reoresents noisless 1D Gaussian Process"""
def __init__(self, X_init, Y_init, L=1, sigma_f=1):
"""class comstructor :param self: :param X_init: np.ndarray (t,1) imputs sampled with black-box function :param Y_init:np.ndarray (t, 1) outputs of the black box f... | stack_v2_sparse_classes_36k_train_021462 | 2,465 | no_license | [
{
"docstring": "class comstructor :param self: :param X_init: np.ndarray (t,1) imputs sampled with black-box function :param Y_init:np.ndarray (t, 1) outputs of the black box function for X_init :param L: length parameter for the kernel :param sigma_f: standard deviation given output :return: covariance np.ndar... | 3 | null | Implement the Python class `GaussianProcess` described below.
Class description:
Class reoresents noisless 1D Gaussian Process
Method signatures and docstrings:
- def __init__(self, X_init, Y_init, L=1, sigma_f=1): class comstructor :param self: :param X_init: np.ndarray (t,1) imputs sampled with black-box function :... | Implement the Python class `GaussianProcess` described below.
Class description:
Class reoresents noisless 1D Gaussian Process
Method signatures and docstrings:
- def __init__(self, X_init, Y_init, L=1, sigma_f=1): class comstructor :param self: :param X_init: np.ndarray (t,1) imputs sampled with black-box function :... | 4ac942126918c7acaa9ef88d18efe299b2f726fe | <|skeleton|>
class GaussianProcess:
"""Class reoresents noisless 1D Gaussian Process"""
def __init__(self, X_init, Y_init, L=1, sigma_f=1):
"""class comstructor :param self: :param X_init: np.ndarray (t,1) imputs sampled with black-box function :param Y_init:np.ndarray (t, 1) outputs of the black box f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaussianProcess:
"""Class reoresents noisless 1D Gaussian Process"""
def __init__(self, X_init, Y_init, L=1, sigma_f=1):
"""class comstructor :param self: :param X_init: np.ndarray (t,1) imputs sampled with black-box function :param Y_init:np.ndarray (t, 1) outputs of the black box function for X... | the_stack_v2_python_sparse | unsupervised_learning/ 0x03-hyperparameter_tuning/1-gp.py | DracoMindz/holbertonschool-machine_learning | train | 2 |
31381aad5e917d9b8ff41b2af4452ae061562f69 | [
"if o not in '^v':\n raise ValueError(\"Invalid triangle order: '{}'\".format(o))\nif a not in '<^>':\n raise ValueError(\"Invalid triangle alignment: '{}'\".format(a))\nif isinstance(char, str):\n char = [char]\nself.char = char\nself.nlevels = nlevels\nself.n1 = n1\nself.rm = rm\nself.lm = lm\nself.add =... | <|body_start_0|>
if o not in '^v':
raise ValueError("Invalid triangle order: '{}'".format(o))
if a not in '<^>':
raise ValueError("Invalid triangle alignment: '{}'".format(a))
if isinstance(char, str):
char = [char]
self.char = char
self.nlevel... | An ASCII text triangle. Formula for the amount of characters in each level of the triangle:: first level: nchars[1] = n1 following levels: nchars[i] = nchars[i-1]*rm + i*lm + add The triangle can be constructed of a string consisting of a single character (see the first example), a string consisting of multiple charact... | TextTriangle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextTriangle:
"""An ASCII text triangle. Formula for the amount of characters in each level of the triangle:: first level: nchars[1] = n1 following levels: nchars[i] = nchars[i-1]*rm + i*lm + add The triangle can be constructed of a string consisting of a single character (see the first example),... | stack_v2_sparse_classes_36k_train_021463 | 7,606 | no_license | [
{
"docstring": "Create a new text triangle.",
"name": "__init__",
"signature": "def __init__(self, char='*', n1=1, rm=0, lm=1, add=1, nlevels=5, o='^', a='<')"
},
{
"docstring": "Format a text triangle as a string.",
"name": "__str__",
"signature": "def __str__(self)"
},
{
"docst... | 3 | stack_v2_sparse_classes_30k_train_014727 | Implement the Python class `TextTriangle` described below.
Class description:
An ASCII text triangle. Formula for the amount of characters in each level of the triangle:: first level: nchars[1] = n1 following levels: nchars[i] = nchars[i-1]*rm + i*lm + add The triangle can be constructed of a string consisting of a si... | Implement the Python class `TextTriangle` described below.
Class description:
An ASCII text triangle. Formula for the amount of characters in each level of the triangle:: first level: nchars[1] = n1 following levels: nchars[i] = nchars[i-1]*rm + i*lm + add The triangle can be constructed of a string consisting of a si... | c80ea145c758f3b392f956e4311f11cfc099a149 | <|skeleton|>
class TextTriangle:
"""An ASCII text triangle. Formula for the amount of characters in each level of the triangle:: first level: nchars[1] = n1 following levels: nchars[i] = nchars[i-1]*rm + i*lm + add The triangle can be constructed of a string consisting of a single character (see the first example),... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextTriangle:
"""An ASCII text triangle. Formula for the amount of characters in each level of the triangle:: first level: nchars[1] = n1 following levels: nchars[i] = nchars[i-1]*rm + i*lm + add The triangle can be constructed of a string consisting of a single character (see the first example), a string con... | the_stack_v2_python_sparse | dailyprogrammer/plugins/asciiart.py | UltimateTimmeh/r-daily-programmer | train | 0 |
75bc9682a1a29cb00f318098445f6f7a8c801b6c | [
"city_link_list = response.xpath('//div[@class=\"all\"]//a/@href').extract()\ncity_name_list = response.xpath('//div[@class=\"all\"]//a/text()').extract()\nfor city_link, city_name in zip(city_link_list, city_name_list):\n yield scrapy.Request(url=self.base_url + city_link, meta={'city': city_name}, callback=sel... | <|body_start_0|>
city_link_list = response.xpath('//div[@class="all"]//a/@href').extract()
city_name_list = response.xpath('//div[@class="all"]//a/text()').extract()
for city_link, city_name in zip(city_link_list, city_name_list):
yield scrapy.Request(url=self.base_url + city_link, m... | AqiRedisSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AqiRedisSpider:
def parse(self, response):
"""解析城市列表页, 获得所有城市的链接"""
<|body_0|>
def parse_month(self, response):
"""解析每个城市的月份链接"""
<|body_1|>
def parse_day(self, response):
"""解析每天的数据"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_021464 | 3,175 | no_license | [
{
"docstring": "解析城市列表页, 获得所有城市的链接",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "解析每个城市的月份链接",
"name": "parse_month",
"signature": "def parse_month(self, response)"
},
{
"docstring": "解析每天的数据",
"name": "parse_day",
"signature": "def parse_... | 3 | stack_v2_sparse_classes_30k_train_009380 | Implement the Python class `AqiRedisSpider` described below.
Class description:
Implement the AqiRedisSpider class.
Method signatures and docstrings:
- def parse(self, response): 解析城市列表页, 获得所有城市的链接
- def parse_month(self, response): 解析每个城市的月份链接
- def parse_day(self, response): 解析每天的数据 | Implement the Python class `AqiRedisSpider` described below.
Class description:
Implement the AqiRedisSpider class.
Method signatures and docstrings:
- def parse(self, response): 解析城市列表页, 获得所有城市的链接
- def parse_month(self, response): 解析每个城市的月份链接
- def parse_day(self, response): 解析每天的数据
<|skeleton|>
class AqiRedisSpid... | 298869fa9fb0291b9e364fbf4a6d8bd992840eb2 | <|skeleton|>
class AqiRedisSpider:
def parse(self, response):
"""解析城市列表页, 获得所有城市的链接"""
<|body_0|>
def parse_month(self, response):
"""解析每个城市的月份链接"""
<|body_1|>
def parse_day(self, response):
"""解析每天的数据"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AqiRedisSpider:
def parse(self, response):
"""解析城市列表页, 获得所有城市的链接"""
city_link_list = response.xpath('//div[@class="all"]//a/@href').extract()
city_name_list = response.xpath('//div[@class="all"]//a/text()').extract()
for city_link, city_name in zip(city_link_list, city_name_lis... | the_stack_v2_python_sparse | Scrapy/AQI/AQI/AQI/spiders/aqi_spider_redis.py | AssassinHotstrip/personal_spider_pra | train | 0 | |
bf244c8d59f7592201f06cb1c6b38b4b540dd931 | [
"if not request.user.has_perm('Users.props_list'):\n return HttpResponseForbidden()\nuser = user_backend.get(username=name)\nprops = property_backend.list(user=user)\nreturn HttpRestAuthResponse(request, props)",
"if not request.user.has_perm('Users.prop_create'):\n return HttpResponseForbidden()\nkey, valu... | <|body_start_0|>
if not request.user.has_perm('Users.props_list'):
return HttpResponseForbidden()
user = user_backend.get(username=name)
props = property_backend.list(user=user)
return HttpRestAuthResponse(request, props)
<|end_body_0|>
<|body_start_1|>
if not reques... | Handle requests to ``/users/<user>/props/``. | UserPropsIndex | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserPropsIndex:
"""Handle requests to ``/users/<user>/props/``."""
def get(self, request, largs, name):
"""Get all properties of a user."""
<|body_0|>
def post(self, request, largs, name, dry=False):
"""Create a new property."""
<|body_1|>
def put(se... | stack_v2_sparse_classes_36k_train_021465 | 9,743 | no_license | [
{
"docstring": "Get all properties of a user.",
"name": "get",
"signature": "def get(self, request, largs, name)"
},
{
"docstring": "Create a new property.",
"name": "post",
"signature": "def post(self, request, largs, name, dry=False)"
},
{
"docstring": "Set multiple properties.... | 3 | stack_v2_sparse_classes_30k_train_015201 | Implement the Python class `UserPropsIndex` described below.
Class description:
Handle requests to ``/users/<user>/props/``.
Method signatures and docstrings:
- def get(self, request, largs, name): Get all properties of a user.
- def post(self, request, largs, name, dry=False): Create a new property.
- def put(self, ... | Implement the Python class `UserPropsIndex` described below.
Class description:
Handle requests to ``/users/<user>/props/``.
Method signatures and docstrings:
- def get(self, request, largs, name): Get all properties of a user.
- def post(self, request, largs, name, dry=False): Create a new property.
- def put(self, ... | 60769f6b4965836b2220878cfa2e1bc403d8f8a3 | <|skeleton|>
class UserPropsIndex:
"""Handle requests to ``/users/<user>/props/``."""
def get(self, request, largs, name):
"""Get all properties of a user."""
<|body_0|>
def post(self, request, largs, name, dry=False):
"""Create a new property."""
<|body_1|>
def put(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserPropsIndex:
"""Handle requests to ``/users/<user>/props/``."""
def get(self, request, largs, name):
"""Get all properties of a user."""
if not request.user.has_perm('Users.props_list'):
return HttpResponseForbidden()
user = user_backend.get(username=name)
p... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/RestAuth/Users/views.py | sachinlokesh05/login-registration-forgotpassword-and-resetpassword-using-django-rest-framework- | train | 3 |
5b02ee3954eca5435824b3b552575275d60cac50 | [
"wx.Frame.__init__(self, parent, id, 'wxYield Test')\nwx.Button(self, ID_START, 'Start', pos=(0, 0))\nwx.Button(self, ID_STOP, 'Stop', pos=(0, 50))\nself.status = wx.StaticText(self, -1, '', pos=(0, 100))\nself.Bind(wx.EVT_BUTTON, self.OnStart, id=ID_START)\nself.Bind(wx.EVT_BUTTON, self.OnStop, id=ID_STOP)\nself.w... | <|body_start_0|>
wx.Frame.__init__(self, parent, id, 'wxYield Test')
wx.Button(self, ID_START, 'Start', pos=(0, 0))
wx.Button(self, ID_STOP, 'Stop', pos=(0, 50))
self.status = wx.StaticText(self, -1, '', pos=(0, 100))
self.Bind(wx.EVT_BUTTON, self.OnStart, id=ID_START)
se... | Class MainFrame. | MainFrame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainFrame:
"""Class MainFrame."""
def __init__(self, parent, id):
"""Create the MainFrame."""
<|body_0|>
def OnStart(self, event):
"""Start Computation."""
<|body_1|>
def OnStop(self, event):
"""Stop Computation."""
<|body_2|>
<|end_... | stack_v2_sparse_classes_36k_train_021466 | 3,167 | no_license | [
{
"docstring": "Create the MainFrame.",
"name": "__init__",
"signature": "def __init__(self, parent, id)"
},
{
"docstring": "Start Computation.",
"name": "OnStart",
"signature": "def OnStart(self, event)"
},
{
"docstring": "Stop Computation.",
"name": "OnStop",
"signature... | 3 | stack_v2_sparse_classes_30k_train_016214 | Implement the Python class `MainFrame` described below.
Class description:
Class MainFrame.
Method signatures and docstrings:
- def __init__(self, parent, id): Create the MainFrame.
- def OnStart(self, event): Start Computation.
- def OnStop(self, event): Stop Computation. | Implement the Python class `MainFrame` described below.
Class description:
Class MainFrame.
Method signatures and docstrings:
- def __init__(self, parent, id): Create the MainFrame.
- def OnStart(self, event): Start Computation.
- def OnStop(self, event): Stop Computation.
<|skeleton|>
class MainFrame:
"""Class ... | 979436525c57fdaeaa832e960985e0406e123587 | <|skeleton|>
class MainFrame:
"""Class MainFrame."""
def __init__(self, parent, id):
"""Create the MainFrame."""
<|body_0|>
def OnStart(self, event):
"""Start Computation."""
<|body_1|>
def OnStop(self, event):
"""Stop Computation."""
<|body_2|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MainFrame:
"""Class MainFrame."""
def __init__(self, parent, id):
"""Create the MainFrame."""
wx.Frame.__init__(self, parent, id, 'wxYield Test')
wx.Button(self, ID_START, 'Start', pos=(0, 0))
wx.Button(self, ID_STOP, 'Stop', pos=(0, 50))
self.status = wx.StaticTex... | the_stack_v2_python_sparse | Research/wx doco/somelongthread2_yield.py | abulka/pynsource | train | 271 |
f7b0d716b3202ae85f8593e8e999a52f1a143b04 | [
"timestamp = self._GetRowValue(query_hash, row, value_name)\nif timestamp is None:\n return None\nreturn dfdatetime_cocoa_time.CocoaTime(timestamp=timestamp)",
"query_hash = hash(query)\nevent_data = IOSDatausageEventData()\nevent_data.bundle_identifier = self._GetRowValue(query_hash, row, 'ZBUNDLENAME')\neven... | <|body_start_0|>
timestamp = self._GetRowValue(query_hash, row, value_name)
if timestamp is None:
return None
return dfdatetime_cocoa_time.CocoaTime(timestamp=timestamp)
<|end_body_0|>
<|body_start_1|>
query_hash = hash(query)
event_data = IOSDatausageEventData()
... | SQLite parser plugin for iOS DataUsage database. | IOSDatausagePlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IOSDatausagePlugin:
"""SQLite parser plugin for iOS DataUsage database."""
def _GetTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query that produced the row. ro... | stack_v2_sparse_classes_36k_train_021467 | 4,379 | permissive | [
{
"docstring": "Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query that produced the row. row (sqlite3.Row): row. value_name (str): name of the value. Returns: dfdatetime.CocoaTime: date and time value or None if not available.",
"name... | 2 | stack_v2_sparse_classes_30k_train_013237 | Implement the Python class `IOSDatausagePlugin` described below.
Class description:
SQLite parser plugin for iOS DataUsage database.
Method signatures and docstrings:
- def _GetTimeRowValue(self, query_hash, row, value_name): Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, tha... | Implement the Python class `IOSDatausagePlugin` described below.
Class description:
SQLite parser plugin for iOS DataUsage database.
Method signatures and docstrings:
- def _GetTimeRowValue(self, query_hash, row, value_name): Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, tha... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class IOSDatausagePlugin:
"""SQLite parser plugin for iOS DataUsage database."""
def _GetTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query that produced the row. ro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IOSDatausagePlugin:
"""SQLite parser plugin for iOS DataUsage database."""
def _GetTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query that produced the row. row (sqlite3.Ro... | the_stack_v2_python_sparse | plaso/parsers/sqlite_plugins/ios_datausage.py | log2timeline/plaso | train | 1,506 |
820fbc8c0f80aef66fee06ac927ec4a4e7525741 | [
"supported_hashes = ', '.join(cls._SUPPORTED_HASHES)\nargument_group.add_argument('--viper-hash', '--viper_hash', dest='viper_hash', type=str, action='store', choices=cls._SUPPORTED_HASHES, default=cls._DEFAULT_HASH, metavar='HASH', help=f'Type of hash to use to query the Viper server, the default is: {cls._DEFAULT... | <|body_start_0|>
supported_hashes = ', '.join(cls._SUPPORTED_HASHES)
argument_group.add_argument('--viper-hash', '--viper_hash', dest='viper_hash', type=str, action='store', choices=cls._SUPPORTED_HASHES, default=cls._DEFAULT_HASH, metavar='HASH', help=f'Type of hash to use to query the Viper server, th... | Viper analysis plugin CLI arguments helper. | ViperAnalysisArgumentsHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViperAnalysisArgumentsHelper:
"""Viper analysis plugin CLI arguments helper."""
def AddArguments(cls, argument_group):
"""Adds command line arguments the helper supports to an argument group. This function takes an argument parser or an argument group object and adds to it all the co... | stack_v2_sparse_classes_36k_train_021468 | 4,018 | permissive | [
{
"docstring": "Adds command line arguments the helper supports to an argument group. This function takes an argument parser or an argument group object and adds to it all the command line arguments this helper supports. Args: argument_group (argparse._ArgumentGroup|argparse.ArgumentParser): argparse group.",
... | 2 | stack_v2_sparse_classes_30k_train_007376 | Implement the Python class `ViperAnalysisArgumentsHelper` described below.
Class description:
Viper analysis plugin CLI arguments helper.
Method signatures and docstrings:
- def AddArguments(cls, argument_group): Adds command line arguments the helper supports to an argument group. This function takes an argument par... | Implement the Python class `ViperAnalysisArgumentsHelper` described below.
Class description:
Viper analysis plugin CLI arguments helper.
Method signatures and docstrings:
- def AddArguments(cls, argument_group): Adds command line arguments the helper supports to an argument group. This function takes an argument par... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class ViperAnalysisArgumentsHelper:
"""Viper analysis plugin CLI arguments helper."""
def AddArguments(cls, argument_group):
"""Adds command line arguments the helper supports to an argument group. This function takes an argument parser or an argument group object and adds to it all the co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViperAnalysisArgumentsHelper:
"""Viper analysis plugin CLI arguments helper."""
def AddArguments(cls, argument_group):
"""Adds command line arguments the helper supports to an argument group. This function takes an argument parser or an argument group object and adds to it all the command line ar... | the_stack_v2_python_sparse | plaso/cli/helpers/viper_analysis.py | log2timeline/plaso | train | 1,506 |
2b446500bba1d59b8c8ce810d52a2c75100ed38f | [
"if n == 0:\n return False\nwhile not n % 2:\n n = n / 2\nreturn n == 1",
"if n == 0:\n return False\nwhile not n % base:\n n = n / base\nreturn n == 1"
] | <|body_start_0|>
if n == 0:
return False
while not n % 2:
n = n / 2
return n == 1
<|end_body_0|>
<|body_start_1|>
if n == 0:
return False
while not n % base:
n = n / base
return n == 1
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPowerOfTwo(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isPowerOf(self, n, base):
""":type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 0:
return False
while not n % 2:
... | stack_v2_sparse_classes_36k_train_021469 | 545 | no_license | [
{
"docstring": ":type n: int :rtype: bool",
"name": "isPowerOfTwo",
"signature": "def isPowerOfTwo(self, n)"
},
{
"docstring": ":type n: int :rtype: bool",
"name": "isPowerOf",
"signature": "def isPowerOf(self, n, base)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012850 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfTwo(self, n): :type n: int :rtype: bool
- def isPowerOf(self, n, base): :type n: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfTwo(self, n): :type n: int :rtype: bool
- def isPowerOf(self, n, base): :type n: int :rtype: bool
<|skeleton|>
class Solution:
def isPowerOfTwo(self, n):
... | 6ea4e05adf246942949f7faa15ec5175ed646760 | <|skeleton|>
class Solution:
def isPowerOfTwo(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isPowerOf(self, n, base):
""":type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPowerOfTwo(self, n):
""":type n: int :rtype: bool"""
if n == 0:
return False
while not n % 2:
n = n / 2
return n == 1
def isPowerOf(self, n, base):
""":type n: int :rtype: bool"""
if n == 0:
return False
... | the_stack_v2_python_sparse | algorithms/Power of Two.py | abos5/leetcode | train | 0 | |
cf991326c363f170393697abb3b6859ba1801bf4 | [
"timestamp = self._GetRowValue(query_hash, row, value_name)\nif timestamp is None:\n return None\nreturn dfdatetime_posix_time.PosixTime(timestamp=timestamp)",
"query_hash = hash(query)\nevent_data = IOSPowerlogApplicationUsageEventData()\nevent_data.background_time = self._GetRowValue(query_hash, row, 'Backgr... | <|body_start_0|>
timestamp = self._GetRowValue(query_hash, row, value_name)
if timestamp is None:
return None
return dfdatetime_posix_time.PosixTime(timestamp=timestamp)
<|end_body_0|>
<|body_start_1|>
query_hash = hash(query)
event_data = IOSPowerlogApplicationUsage... | SQLite parser plugin for iOS powerlog database files. | IOSPowerlogApplicationUsagePlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IOSPowerlogApplicationUsagePlugin:
"""SQLite parser plugin for iOS powerlog database files."""
def _GetDateTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query t... | stack_v2_sparse_classes_36k_train_021470 | 3,949 | permissive | [
{
"docstring": "Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query that produced the row. row (sqlite3.Row): row. value_name (str): name of the value. Returns: dfdatetime.PosixTime: date and time value or None if not available.",
"name... | 2 | null | Implement the Python class `IOSPowerlogApplicationUsagePlugin` described below.
Class description:
SQLite parser plugin for iOS powerlog database files.
Method signatures and docstrings:
- def _GetDateTimeRowValue(self, query_hash, row, value_name): Retrieves a date and time value from the row. Args: query_hash (int)... | Implement the Python class `IOSPowerlogApplicationUsagePlugin` described below.
Class description:
SQLite parser plugin for iOS powerlog database files.
Method signatures and docstrings:
- def _GetDateTimeRowValue(self, query_hash, row, value_name): Retrieves a date and time value from the row. Args: query_hash (int)... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class IOSPowerlogApplicationUsagePlugin:
"""SQLite parser plugin for iOS powerlog database files."""
def _GetDateTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IOSPowerlogApplicationUsagePlugin:
"""SQLite parser plugin for iOS powerlog database files."""
def _GetDateTimeRowValue(self, query_hash, row, value_name):
"""Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query that produced ... | the_stack_v2_python_sparse | plaso/parsers/sqlite_plugins/ios_powerlog.py | log2timeline/plaso | train | 1,506 |
7180d87c16adf53abb10af49603bc77db6a29b2a | [
"self.capacity = capacity\nself.size = 0\nself.mem = dict()\nself.head = None\nself.tail = None",
"node.next = self.head\nif self.head:\n self.head.prev = node\nself.head = node\nif self.tail is None:\n self.tail = node",
"if node == self.head and node == self.tail:\n self.head = None\n self.tail = ... | <|body_start_0|>
self.capacity = capacity
self.size = 0
self.mem = dict()
self.head = None
self.tail = None
<|end_body_0|>
<|body_start_1|>
node.next = self.head
if self.head:
self.head.prev = node
self.head = node
if self.tail is None... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def add_node(self, node):
"""Add a node to the head of the DLL"""
<|body_1|>
def remove_node(self, node):
"""Remove a node in the DLL"""
<|body_2|>
def get(... | stack_v2_sparse_classes_36k_train_021471 | 3,216 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": "Add a node to the head of the DLL",
"name": "add_node",
"signature": "def add_node(self, node)"
},
{
"docstring": "Remove a node in the DLL",
"name": "remo... | 5 | stack_v2_sparse_classes_30k_train_017551 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def add_node(self, node): Add a node to the head of the DLL
- def remove_node(self, node): Remove a node in the DLL
- def get(... | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def add_node(self, node): Add a node to the head of the DLL
- def remove_node(self, node): Remove a node in the DLL
- def get(... | 43dbcc129de3092d1ef24b95eaf35e20363cbd93 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def add_node(self, node):
"""Add a node to the head of the DLL"""
<|body_1|>
def remove_node(self, node):
"""Remove a node in the DLL"""
<|body_2|>
def get(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.capacity = capacity
self.size = 0
self.mem = dict()
self.head = None
self.tail = None
def add_node(self, node):
"""Add a node to the head of the DLL"""
node.next = self.h... | the_stack_v2_python_sparse | lru-cache.py | iyyuan/leetcode-practice | train | 0 | |
d4697daa605f3eb2e3917e55d3cce49d4259465c | [
"sentiment = global_cons.NEUTRAL\nif score <= thresholds[0]:\n sentiment = global_cons.NEGATIVE\nif score >= thresholds[1]:\n sentiment = global_cons.POSITIVE\nreturn sentiment",
"if not scores:\n logger.warning(msg='Empty baseline (scores) to calculate thresholds.')\n return (None, None)\nmu, std = n... | <|body_start_0|>
sentiment = global_cons.NEUTRAL
if score <= thresholds[0]:
sentiment = global_cons.NEGATIVE
if score >= thresholds[1]:
sentiment = global_cons.POSITIVE
return sentiment
<|end_body_0|>
<|body_start_1|>
if not scores:
logger.war... | InterfaceLabel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterfaceLabel:
def label_sentiment(score: float, thresholds: tuple) -> str:
"""Label sentiment on interface :param score: score of the text :param thresholds: thresholds of negative and positive sentiment :return: sentiment label"""
<|body_0|>
def calculate_threshold_positi... | stack_v2_sparse_classes_36k_train_021472 | 1,312 | permissive | [
{
"docstring": "Label sentiment on interface :param score: score of the text :param thresholds: thresholds of negative and positive sentiment :return: sentiment label",
"name": "label_sentiment",
"signature": "def label_sentiment(score: float, thresholds: tuple) -> str"
},
{
"docstring": "Calcul... | 2 | stack_v2_sparse_classes_30k_train_016459 | Implement the Python class `InterfaceLabel` described below.
Class description:
Implement the InterfaceLabel class.
Method signatures and docstrings:
- def label_sentiment(score: float, thresholds: tuple) -> str: Label sentiment on interface :param score: score of the text :param thresholds: thresholds of negative an... | Implement the Python class `InterfaceLabel` described below.
Class description:
Implement the InterfaceLabel class.
Method signatures and docstrings:
- def label_sentiment(score: float, thresholds: tuple) -> str: Label sentiment on interface :param score: score of the text :param thresholds: thresholds of negative an... | c98eb8c483a05af938a2f6f49d8ea803f5711572 | <|skeleton|>
class InterfaceLabel:
def label_sentiment(score: float, thresholds: tuple) -> str:
"""Label sentiment on interface :param score: score of the text :param thresholds: thresholds of negative and positive sentiment :return: sentiment label"""
<|body_0|>
def calculate_threshold_positi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InterfaceLabel:
def label_sentiment(score: float, thresholds: tuple) -> str:
"""Label sentiment on interface :param score: score of the text :param thresholds: thresholds of negative and positive sentiment :return: sentiment label"""
sentiment = global_cons.NEUTRAL
if score <= threshol... | the_stack_v2_python_sparse | engage-analytics/sentiment_analysis/src/model/labelling_interface.py | oliveriopt/mood-analytics | train | 0 | |
04b147bd293668441c54403ba4023e5ea646c183 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ExpirationPattern()",
"from .expiration_pattern_type import ExpirationPatternType\nfrom .expiration_pattern_type import ExpirationPatternType\nfields: Dict[str, Callable[[Any], None]] = {'duration': lambda n: setattr(self, 'duration', ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ExpirationPattern()
<|end_body_0|>
<|body_start_1|>
from .expiration_pattern_type import ExpirationPatternType
from .expiration_pattern_type import ExpirationPatternType
fields: ... | ExpirationPattern | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExpirationPattern:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ExpirationPattern:
"""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... | stack_v2_sparse_classes_36k_train_021473 | 3,644 | 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: ExpirationPattern",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_v... | 3 | null | Implement the Python class `ExpirationPattern` described below.
Class description:
Implement the ExpirationPattern class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ExpirationPattern: Creates a new instance of the appropriate class based on discrim... | Implement the Python class `ExpirationPattern` described below.
Class description:
Implement the ExpirationPattern class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ExpirationPattern: Creates a new instance of the appropriate class based on discrim... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ExpirationPattern:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ExpirationPattern:
"""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... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExpirationPattern:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ExpirationPattern:
"""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: Expi... | the_stack_v2_python_sparse | msgraph/generated/models/expiration_pattern.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
d73af10547f6b8d92a5debc38b9ffd2694363908 | [
"news = response.xpath(\"//a[@target='_blank']\")\nfor new in news:\n item = CDagency()\n item['col_name'] = 'CD06dangxiao'\n href = new.xpath('./@href').extract_first()\n detail_url = 'https://www.cddx.gov.cn' + href\n item['detail_url'] = detail_url\n yield scrapy.Request(detail_url, callback=se... | <|body_start_0|>
news = response.xpath("//a[@target='_blank']")
for new in news:
item = CDagency()
item['col_name'] = 'CD06dangxiao'
href = new.xpath('./@href').extract_first()
detail_url = 'https://www.cddx.gov.cn' + href
item['detail_url'] = ... | CdDangxiaoSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CdDangxiaoSpider:
def parse(self, response):
""""默认的解析回调函数"""
<|body_0|>
def get_text(self, response):
"""获取详细的文本信息"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
news = response.xpath("//a[@target='_blank']")
for new in news:
i... | stack_v2_sparse_classes_36k_train_021474 | 2,954 | no_license | [
{
"docstring": "\"默认的解析回调函数",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "获取详细的文本信息",
"name": "get_text",
"signature": "def get_text(self, response)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020847 | Implement the Python class `CdDangxiaoSpider` described below.
Class description:
Implement the CdDangxiaoSpider class.
Method signatures and docstrings:
- def parse(self, response): "默认的解析回调函数
- def get_text(self, response): 获取详细的文本信息 | Implement the Python class `CdDangxiaoSpider` described below.
Class description:
Implement the CdDangxiaoSpider class.
Method signatures and docstrings:
- def parse(self, response): "默认的解析回调函数
- def get_text(self, response): 获取详细的文本信息
<|skeleton|>
class CdDangxiaoSpider:
def parse(self, response):
""""... | d2d66206d799afbfe68cafcc9bd7cd6d9533685d | <|skeleton|>
class CdDangxiaoSpider:
def parse(self, response):
""""默认的解析回调函数"""
<|body_0|>
def get_text(self, response):
"""获取详细的文本信息"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CdDangxiaoSpider:
def parse(self, response):
""""默认的解析回调函数"""
news = response.xpath("//a[@target='_blank']")
for new in news:
item = CDagency()
item['col_name'] = 'CD06dangxiao'
href = new.xpath('./@href').extract_first()
detail_url = 'ht... | the_stack_v2_python_sparse | CDagency/spiders/cd06_dangxiao.py | gongdx/CDagency | train | 0 | |
41f8c7ff6393be932c3033fddd821c8b11a77842 | [
"course_run, user = create_purchasable_course_run()\norder = create_unfulfilled_order(course_run.edx_course_key, user)\nassert 'MM-{}-{}'.format(CYBERSOURCE_REFERENCE_PREFIX, order.id) == make_reference_id(order)",
"course_run, user = create_purchasable_course_run()\norder = create_unfulfilled_order(course_run.ed... | <|body_start_0|>
course_run, user = create_purchasable_course_run()
order = create_unfulfilled_order(course_run.edx_course_key, user)
assert 'MM-{}-{}'.format(CYBERSOURCE_REFERENCE_PREFIX, order.id) == make_reference_id(order)
<|end_body_0|>
<|body_start_1|>
course_run, user = create_pu... | Tests for get_order_by_reference_number and make_reference_id | ReferenceNumberTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReferenceNumberTests:
"""Tests for get_order_by_reference_number and make_reference_id"""
def test_make_reference_id(self):
"""make_reference_id should concatenate the reference prefix and the order id"""
<|body_0|>
def test_get_new_order_by_reference_number(self):
... | stack_v2_sparse_classes_36k_train_021475 | 41,111 | permissive | [
{
"docstring": "make_reference_id should concatenate the reference prefix and the order id",
"name": "test_make_reference_id",
"signature": "def test_make_reference_id(self)"
},
{
"docstring": "get_new_order_by_reference_number returns an Order with status created",
"name": "test_get_new_ord... | 4 | null | Implement the Python class `ReferenceNumberTests` described below.
Class description:
Tests for get_order_by_reference_number and make_reference_id
Method signatures and docstrings:
- def test_make_reference_id(self): make_reference_id should concatenate the reference prefix and the order id
- def test_get_new_order_... | Implement the Python class `ReferenceNumberTests` described below.
Class description:
Tests for get_order_by_reference_number and make_reference_id
Method signatures and docstrings:
- def test_make_reference_id(self): make_reference_id should concatenate the reference prefix and the order id
- def test_get_new_order_... | d6564caca0b7bbfd31e67a751564107fd17d6eb0 | <|skeleton|>
class ReferenceNumberTests:
"""Tests for get_order_by_reference_number and make_reference_id"""
def test_make_reference_id(self):
"""make_reference_id should concatenate the reference prefix and the order id"""
<|body_0|>
def test_get_new_order_by_reference_number(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReferenceNumberTests:
"""Tests for get_order_by_reference_number and make_reference_id"""
def test_make_reference_id(self):
"""make_reference_id should concatenate the reference prefix and the order id"""
course_run, user = create_purchasable_course_run()
order = create_unfulfille... | the_stack_v2_python_sparse | ecommerce/api_test.py | mitodl/micromasters | train | 35 |
8c62399eef4cef5a5f4b58d009a3a47feaaea1fd | [
"self.dx = dx\nself.grid_size_y = grid_size_y\nself.grid_size_x = grid_size_x\nself.real_t = real_t\nself.bc_type = bc_type\npoisson_matrix_x, poisson_matrix_y = self._construct_poisson_matrices()\nself._apply_boundary_conds_to_poisson_matrices(poisson_matrix_x, poisson_matrix_y)\nself._compute_spectral_decomp_of_p... | <|body_start_0|>
self.dx = dx
self.grid_size_y = grid_size_y
self.grid_size_x = grid_size_x
self.real_t = real_t
self.bc_type = bc_type
poisson_matrix_x, poisson_matrix_y = self._construct_poisson_matrices()
self._apply_boundary_conds_to_poisson_matrices(poisson_m... | Class for Poisson solver in 2D via Fast Diagonalisation. | FastDiagPoissonSolver2D | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastDiagPoissonSolver2D:
"""Class for Poisson solver in 2D via Fast Diagonalisation."""
def __init__(self, grid_size_y: int, grid_size_x: int, dx: float, real_t: type=np.float64, bc_type: Literal['homogenous_neumann_along_xy']='homogenous_neumann_along_xy') -> None:
"""Class initiali... | stack_v2_sparse_classes_36k_train_021476 | 4,807 | permissive | [
{
"docstring": "Class initialiser.",
"name": "__init__",
"signature": "def __init__(self, grid_size_y: int, grid_size_x: int, dx: float, real_t: type=np.float64, bc_type: Literal['homogenous_neumann_along_xy']='homogenous_neumann_along_xy') -> None"
},
{
"docstring": "Construct the finite differ... | 5 | stack_v2_sparse_classes_30k_train_003461 | Implement the Python class `FastDiagPoissonSolver2D` described below.
Class description:
Class for Poisson solver in 2D via Fast Diagonalisation.
Method signatures and docstrings:
- def __init__(self, grid_size_y: int, grid_size_x: int, dx: float, real_t: type=np.float64, bc_type: Literal['homogenous_neumann_along_xy... | Implement the Python class `FastDiagPoissonSolver2D` described below.
Class description:
Class for Poisson solver in 2D via Fast Diagonalisation.
Method signatures and docstrings:
- def __init__(self, grid_size_y: int, grid_size_x: int, dx: float, real_t: type=np.float64, bc_type: Literal['homogenous_neumann_along_xy... | 99a094e0d6e635e5b2385a69bdee239a4d1fb530 | <|skeleton|>
class FastDiagPoissonSolver2D:
"""Class for Poisson solver in 2D via Fast Diagonalisation."""
def __init__(self, grid_size_y: int, grid_size_x: int, dx: float, real_t: type=np.float64, bc_type: Literal['homogenous_neumann_along_xy']='homogenous_neumann_along_xy') -> None:
"""Class initiali... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FastDiagPoissonSolver2D:
"""Class for Poisson solver in 2D via Fast Diagonalisation."""
def __init__(self, grid_size_y: int, grid_size_x: int, dx: float, real_t: type=np.float64, bc_type: Literal['homogenous_neumann_along_xy']='homogenous_neumann_along_xy') -> None:
"""Class initialiser."""
... | the_stack_v2_python_sparse | sopht/numeric/eulerian_grid_ops/poisson_solver_2d/FastDiagPoissonSolver2D.py | SophT-Team/SophT | train | 2 |
a3043aed42f777162310312dc6d1c4bea78690c2 | [
"super().__init__(parent)\nlayout = QVBoxLayout()\nlayout.setContentsMargins(0, 0, 0, 0)\ntoggle = QToolButton(clicked=self._on_toggle_clicked)\ntoggle.setStyleSheet('border: none;')\ntoggle.setFont(QGuiApplication.font())\ntoggle.setToolButtonStyle(Qt.ToolButtonTextBesideIcon)\ntoggle.setArrowType(Qt.RightArrow if... | <|body_start_0|>
super().__init__(parent)
layout = QVBoxLayout()
layout.setContentsMargins(0, 0, 0, 0)
toggle = QToolButton(clicked=self._on_toggle_clicked)
toggle.setStyleSheet('border: none;')
toggle.setFont(QGuiApplication.font())
toggle.setToolButtonStyle(Qt.T... | A widget that can be expanded or collapsed (ie. made visible or hidden) by the user clicking on a button. | CollapsibleWidget | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollapsibleWidget:
"""A widget that can be expanded or collapsed (ie. made visible or hidden) by the user clicking on a button."""
def __init__(self, title, collapsed=True, parent=None):
"""Initialise the widget."""
<|body_0|>
def _on_toggle_clicked(self, checked):
... | stack_v2_sparse_classes_36k_train_021477 | 3,100 | permissive | [
{
"docstring": "Initialise the widget.",
"name": "__init__",
"signature": "def __init__(self, title, collapsed=True, parent=None)"
},
{
"docstring": "Invoked when the user clicks to expand or collapse the widget.",
"name": "_on_toggle_clicked",
"signature": "def _on_toggle_clicked(self, ... | 3 | stack_v2_sparse_classes_30k_train_020652 | Implement the Python class `CollapsibleWidget` described below.
Class description:
A widget that can be expanded or collapsed (ie. made visible or hidden) by the user clicking on a button.
Method signatures and docstrings:
- def __init__(self, title, collapsed=True, parent=None): Initialise the widget.
- def _on_togg... | Implement the Python class `CollapsibleWidget` described below.
Class description:
A widget that can be expanded or collapsed (ie. made visible or hidden) by the user clicking on a button.
Method signatures and docstrings:
- def __init__(self, title, collapsed=True, parent=None): Initialise the widget.
- def _on_togg... | 4ed2b1b9a2407afcbffdf304020d42b81c4c8cdc | <|skeleton|>
class CollapsibleWidget:
"""A widget that can be expanded or collapsed (ie. made visible or hidden) by the user clicking on a button."""
def __init__(self, title, collapsed=True, parent=None):
"""Initialise the widget."""
<|body_0|>
def _on_toggle_clicked(self, checked):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollapsibleWidget:
"""A widget that can be expanded or collapsed (ie. made visible or hidden) by the user clicking on a button."""
def __init__(self, title, collapsed=True, parent=None):
"""Initialise the widget."""
super().__init__(parent)
layout = QVBoxLayout()
layout.se... | the_stack_v2_python_sparse | note/demo/pyqt_demo/pyqtdeploy-3.3.0/pyqtdeploy/gui/collapsible_widget.py | onsunsl/onsunsl.github.io | train | 1 |
55b9e0147b69520e91074e5af18e3b79796987b5 | [
"if bubble['is_user']:\n t = 'user'\nelif bubble['is_system']:\n t = 'system'\nelif bubble['is_info']:\n t = 'info'\nelse:\n t = 'status'\nreturn t",
"self.type = self._demultiplex_bubbletype(bubble)\nself.html = bubble['message']\nself.url = bubble['bubble_url'] if bubble['bubble_url'] != '' else Non... | <|body_start_0|>
if bubble['is_user']:
t = 'user'
elif bubble['is_system']:
t = 'system'
elif bubble['is_info']:
t = 'info'
else:
t = 'status'
return t
<|end_body_0|>
<|body_start_1|>
self.type = self._demultiplex_bubbletyp... | Converted bubble which is returned by the API. | DataBubble | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataBubble:
"""Converted bubble which is returned by the API."""
def _demultiplex_bubbletype(bubble):
"""Use a single field to dispatch the type and resolve BubbleTypes-Enum. :param bubble: Constructed bubble :return:"""
<|body_0|>
def __init__(self, bubble):
"""... | stack_v2_sparse_classes_36k_train_021478 | 3,741 | permissive | [
{
"docstring": "Use a single field to dispatch the type and resolve BubbleTypes-Enum. :param bubble: Constructed bubble :return:",
"name": "_demultiplex_bubbletype",
"signature": "def _demultiplex_bubbletype(bubble)"
},
{
"docstring": "Convert given bubble to reduced bubble holding only the core... | 2 | stack_v2_sparse_classes_30k_train_011900 | Implement the Python class `DataBubble` described below.
Class description:
Converted bubble which is returned by the API.
Method signatures and docstrings:
- def _demultiplex_bubbletype(bubble): Use a single field to dispatch the type and resolve BubbleTypes-Enum. :param bubble: Constructed bubble :return:
- def __i... | Implement the Python class `DataBubble` described below.
Class description:
Converted bubble which is returned by the API.
Method signatures and docstrings:
- def _demultiplex_bubbletype(bubble): Use a single field to dispatch the type and resolve BubbleTypes-Enum. :param bubble: Constructed bubble :return:
- def __i... | 7996dbe0c66149c710217839877a1ec4e7eb46ed | <|skeleton|>
class DataBubble:
"""Converted bubble which is returned by the API."""
def _demultiplex_bubbletype(bubble):
"""Use a single field to dispatch the type and resolve BubbleTypes-Enum. :param bubble: Constructed bubble :return:"""
<|body_0|>
def __init__(self, bubble):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataBubble:
"""Converted bubble which is returned by the API."""
def _demultiplex_bubbletype(bubble):
"""Use a single field to dispatch the type and resolve BubbleTypes-Enum. :param bubble: Constructed bubble :return:"""
if bubble['is_user']:
t = 'user'
elif bubble['is... | the_stack_v2_python_sparse | api/models.py | hhucn/dbas | train | 25 |
f10a69c6899f188bb33c02016d6ce3d428bf267f | [
"ans = 0\nfor i in range(3, n):\n if i % 3 == 0 or i % 5 == 0:\n ans += i\nreturn ans",
"values = set()\nfor i in range(3, n, 3):\n values.add(i)\nfor j in range(5, n, 5):\n values.add(j)\nreturn sum(values)",
"def get_multiples_of_x(x, n):\n num_values = n // x\n lb = x\n ub = n - n % ... | <|body_start_0|>
ans = 0
for i in range(3, n):
if i % 3 == 0 or i % 5 == 0:
ans += i
return ans
<|end_body_0|>
<|body_start_1|>
values = set()
for i in range(3, n, 3):
values.add(i)
for j in range(5, n, 5):
values.add(j... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def method1(self, n):
"""Use division. Complexity: O(N)"""
<|body_0|>
def method2(self, n):
"""Use multifications. Complexity O(N/3) + O(N/5) = O(N)"""
<|body_1|>
def method3(self, n):
"""Get the theoretical answer. Complexity: O(1)"""
... | stack_v2_sparse_classes_36k_train_021479 | 1,736 | no_license | [
{
"docstring": "Use division. Complexity: O(N)",
"name": "method1",
"signature": "def method1(self, n)"
},
{
"docstring": "Use multifications. Complexity O(N/3) + O(N/5) = O(N)",
"name": "method2",
"signature": "def method2(self, n)"
},
{
"docstring": "Get the theoretical answer.... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def method1(self, n): Use division. Complexity: O(N)
- def method2(self, n): Use multifications. Complexity O(N/3) + O(N/5) = O(N)
- def method3(self, n): Get the theoretical ans... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def method1(self, n): Use division. Complexity: O(N)
- def method2(self, n): Use multifications. Complexity O(N/3) + O(N/5) = O(N)
- def method3(self, n): Get the theoretical ans... | 97a2386f5e3adbd7138fd123810c3232bdf7f622 | <|skeleton|>
class Solution:
def method1(self, n):
"""Use division. Complexity: O(N)"""
<|body_0|>
def method2(self, n):
"""Use multifications. Complexity O(N/3) + O(N/5) = O(N)"""
<|body_1|>
def method3(self, n):
"""Get the theoretical answer. Complexity: O(1)"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def method1(self, n):
"""Use division. Complexity: O(N)"""
ans = 0
for i in range(3, n):
if i % 3 == 0 or i % 5 == 0:
ans += i
return ans
def method2(self, n):
"""Use multifications. Complexity O(N/3) + O(N/5) = O(N)"""
... | the_stack_v2_python_sparse | python3/euler/1.multiples_of_3_and_5.py | victorchu/algorithms | train | 0 | |
df775fed2f6fb900ed19dc13c614d1300a8521d2 | [
"if content is not None:\n if hasattr(content, 'render'):\n self.contents = [content]\n else:\n self.contents = [TextWrapper(str(content))]\nelse:\n self.contents = []\nself.style = kwargs",
"if new_content is not None:\n if hasattr(new_content, 'render'):\n self.contents.append(n... | <|body_start_0|>
if content is not None:
if hasattr(content, 'render'):
self.contents = [content]
else:
self.contents = [TextWrapper(str(content))]
else:
self.contents = []
self.style = kwargs
<|end_body_0|>
<|body_start_1|>
... | Element is an HTML element that holds a list of contents. The list hold information describing the HTML element as well as a class attribute describing the HTML tag called tag. It also contains instance attributes such as contents which is a list that contains the contents. It is very likely that the contents could inc... | Element | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Element:
"""Element is an HTML element that holds a list of contents. The list hold information describing the HTML element as well as a class attribute describing the HTML tag called tag. It also contains instance attributes such as contents which is a list that contains the contents. It is very... | stack_v2_sparse_classes_36k_train_021480 | 8,529 | no_license | [
{
"docstring": "Initialises the Element class. Args: content: Accepts the first content in its contents list, otherwise it will be empty contents list. kwargs: Are additional arguments that define the style of the element.",
"name": "__init__",
"signature": "def __init__(self, content=None, **kwargs)"
... | 5 | null | Implement the Python class `Element` described below.
Class description:
Element is an HTML element that holds a list of contents. The list hold information describing the HTML element as well as a class attribute describing the HTML tag called tag. It also contains instance attributes such as contents which is a list... | Implement the Python class `Element` described below.
Class description:
Element is an HTML element that holds a list of contents. The list hold information describing the HTML element as well as a class attribute describing the HTML tag called tag. It also contains instance attributes such as contents which is a list... | 76224d0fb871d0bf0b838f3fccf01022edd70f82 | <|skeleton|>
class Element:
"""Element is an HTML element that holds a list of contents. The list hold information describing the HTML element as well as a class attribute describing the HTML tag called tag. It also contains instance attributes such as contents which is a list that contains the contents. It is very... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Element:
"""Element is an HTML element that holds a list of contents. The list hold information describing the HTML element as well as a class attribute describing the HTML tag called tag. It also contains instance attributes such as contents which is a list that contains the contents. It is very likely that ... | the_stack_v2_python_sparse | students/Pirouz_N/lesson07/html_render.py | UWPCE-PythonCert-ClassRepos/SP_Online_PY210 | train | 19 |
07bb56677c0d05ef476e9fd344774bcc54542634 | [
"if self.host == '':\n self.error_message = 'Email Error: host is empty'\nelif self.username == '':\n self.error_message = 'Email Error: username is empty'\nelif self.password == '':\n self.error_message = 'Email Error: password is empty'\nelse:\n self.available = True\n self.postman = Postman(host=s... | <|body_start_0|>
if self.host == '':
self.error_message = 'Email Error: host is empty'
elif self.username == '':
self.error_message = 'Email Error: username is empty'
elif self.password == '':
self.error_message = 'Email Error: password is empty'
else:... | Provide Emails Sending Service Example for config.py: "email": { "host": "smtp.gmail.com", "port": 587, "username": "james2015@gmail.com", "password": "88888888" } | Email | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Email:
"""Provide Emails Sending Service Example for config.py: "email": { "host": "smtp.gmail.com", "port": 587, "username": "james2015@gmail.com", "password": "88888888" }"""
def __init__(self):
"""check email-service parameters from config.py"""
<|body_0|>
def send_em... | stack_v2_sparse_classes_36k_train_021481 | 22,148 | permissive | [
{
"docstring": "check email-service parameters from config.py",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Send emails notes: No all email-service providers support. if using Gmail, enable \"Access for less secure apps\" for the sender's account, Examples: xxx.send_... | 2 | stack_v2_sparse_classes_30k_train_019636 | Implement the Python class `Email` described below.
Class description:
Provide Emails Sending Service Example for config.py: "email": { "host": "smtp.gmail.com", "port": 587, "username": "james2015@gmail.com", "password": "88888888" }
Method signatures and docstrings:
- def __init__(self): check email-service paramet... | Implement the Python class `Email` described below.
Class description:
Provide Emails Sending Service Example for config.py: "email": { "host": "smtp.gmail.com", "port": 587, "username": "james2015@gmail.com", "password": "88888888" }
Method signatures and docstrings:
- def __init__(self): check email-service paramet... | 945c4fd2755f5b0dea11e54eb649eeb37ec93d01 | <|skeleton|>
class Email:
"""Provide Emails Sending Service Example for config.py: "email": { "host": "smtp.gmail.com", "port": 587, "username": "james2015@gmail.com", "password": "88888888" }"""
def __init__(self):
"""check email-service parameters from config.py"""
<|body_0|>
def send_em... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Email:
"""Provide Emails Sending Service Example for config.py: "email": { "host": "smtp.gmail.com", "port": 587, "username": "james2015@gmail.com", "password": "88888888" }"""
def __init__(self):
"""check email-service parameters from config.py"""
if self.host == '':
self.err... | the_stack_v2_python_sparse | open-hackathon-server/src/hackathon/util.py | kaiyuanshe/open-hackathon | train | 46 |
66fd272a579ab5d000ccb2e60e9185c9a3b49964 | [
"base_path = os.path.split(os.path.dirname(os.path.abspath(__file__)))[0]\ntest_dir = 'cinder_tempest_plugin'\nfull_test_dir = os.path.join(base_path, test_dir)\nreturn (full_test_dir, base_path)",
"config.register_opt_group(conf, config.volume_feature_group, project_config.cinder_option)\nif 'barbican_tempest_pl... | <|body_start_0|>
base_path = os.path.split(os.path.dirname(os.path.abspath(__file__)))[0]
test_dir = 'cinder_tempest_plugin'
full_test_dir = os.path.join(base_path, test_dir)
return (full_test_dir, base_path)
<|end_body_0|>
<|body_start_1|>
config.register_opt_group(conf, config... | CinderTempestPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CinderTempestPlugin:
def load_tests(self):
"""Provides information to load the plugin tests. :return: A tuple with the first value being the test dir and the second being the top level dir."""
<|body_0|>
def register_opts(self, conf):
"""Adds additional configuration... | stack_v2_sparse_classes_36k_train_021482 | 2,695 | permissive | [
{
"docstring": "Provides information to load the plugin tests. :return: A tuple with the first value being the test dir and the second being the top level dir.",
"name": "load_tests",
"signature": "def load_tests(self)"
},
{
"docstring": "Adds additional configuration options to tempest. This me... | 3 | stack_v2_sparse_classes_30k_val_000832 | Implement the Python class `CinderTempestPlugin` described below.
Class description:
Implement the CinderTempestPlugin class.
Method signatures and docstrings:
- def load_tests(self): Provides information to load the plugin tests. :return: A tuple with the first value being the test dir and the second being the top l... | Implement the Python class `CinderTempestPlugin` described below.
Class description:
Implement the CinderTempestPlugin class.
Method signatures and docstrings:
- def load_tests(self): Provides information to load the plugin tests. :return: A tuple with the first value being the test dir and the second being the top l... | e5ae1ed54a7a07133ec103006dbf430d8457b29a | <|skeleton|>
class CinderTempestPlugin:
def load_tests(self):
"""Provides information to load the plugin tests. :return: A tuple with the first value being the test dir and the second being the top level dir."""
<|body_0|>
def register_opts(self, conf):
"""Adds additional configuration... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CinderTempestPlugin:
def load_tests(self):
"""Provides information to load the plugin tests. :return: A tuple with the first value being the test dir and the second being the top level dir."""
base_path = os.path.split(os.path.dirname(os.path.abspath(__file__)))[0]
test_dir = 'cinder_t... | the_stack_v2_python_sparse | cinder_tempest_plugin/plugin.py | sapcc/cinder-tempest-plugin | train | 0 | |
937f48ab9de736cb316fc386c140bf686bcfdca5 | [
"bottom_spatial_size = calculate_output_dimension(spatial_size, kernel_sizes, stride_sizes)\ntorch.nn.Module.__init__(self)\nself.basic_num = basic_num\nself.level_depth = len(kernel_sizes)\nself.inp = scn.InputLayer(dim, spatial_size)\nself.convBN = ConvBNBlock(start_planes, init_conv_nplanes, init_conv_kernel, mo... | <|body_start_0|>
bottom_spatial_size = calculate_output_dimension(spatial_size, kernel_sizes, stride_sizes)
torch.nn.Module.__init__(self)
self.basic_num = basic_num
self.level_depth = len(kernel_sizes)
self.inp = scn.InputLayer(dim, spatial_size)
self.convBN = ConvBNBloc... | This class implements a UNet structure, built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the UNet ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. init_conv_nplaness : int Number of planes we want afte... | UNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UNet:
"""This class implements a UNet structure, built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the UNet ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. init_conv_nplaness : i... | stack_v2_sparse_classes_36k_train_021483 | 11,953 | no_license | [
{
"docstring": "Parameters ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. init_conv_nplaness : int Number of planes we want after the initial SubmanifoldConvolution, that is, to begin downsampling. init_conv_kernel : int Kernel for the first convolu... | 2 | stack_v2_sparse_classes_30k_train_007135 | Implement the Python class `UNet` described below.
Class description:
This class implements a UNet structure, built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the UNet ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is als... | Implement the Python class `UNet` described below.
Class description:
This class implements a UNet structure, built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the UNet ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is als... | 4c2cf181c6f503bf2a9c09bbe16810e727b052e7 | <|skeleton|>
class UNet:
"""This class implements a UNet structure, built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the UNet ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. init_conv_nplaness : i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UNet:
"""This class implements a UNet structure, built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the UNet ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. init_conv_nplaness : int Number of ... | the_stack_v2_python_sparse | next_sparseconvnet/networks/architectures.py | next-exp/NEXT_SPARSECONVNET | train | 0 |
122b0681a25c45b66b89c7f99c1b562d6e44ffbd | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(email=MyUserManager.normalize_email(email), date_of_birth=date_of_birth or timezone.now(), first_name=first_name or '', last_name=last_name or '')\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"if ... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=MyUserManager.normalize_email(email), date_of_birth=date_of_birth or timezone.now(), first_name=first_name or '', last_name=last_name or '')
user.set_password(password)
... | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, date_of_birth, first_name, last_name... | stack_v2_sparse_classes_36k_train_021484 | 1,411 | no_license | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given emai... | 2 | stack_v2_sparse_classes_30k_train_011535 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None): Creates and saves a User with the given email, date of birth and passw... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None): Creates and saves a User with the given email, date of birth and passw... | 42654f6c058de095ac6ff540bdd89854b7f864f9 | <|skeleton|>
class MyUserManager:
def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, date_of_birth, first_name, last_name... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyUserManager:
def create_user(self, email, first_name=None, last_name=None, date_of_birth=None, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
if not email:
raise ValueError('Users must have an email address')
user = self.m... | the_stack_v2_python_sparse | thesis/DavideCrestini/tesi-crestini/Piattaforma/services/managers.py | lbedogni/iot | train | 0 | |
47cd03935e70b3a8e3233d9cde6b530864dca5ce | [
"super().__init__()\nself.unbiased_pcnt = unbiased_pcnt\nself.mixing_factors = mixing_factors\nself.seed = seed\nself.data_efficient = data_efficient",
"mixing_factor = self.mixing_factors[split_id]\nbiased, unbiased = get_biased_subset(data, mixing_factor, self.unbiased_pcnt, self.seed, self.data_efficient)\nret... | <|body_start_0|>
super().__init__()
self.unbiased_pcnt = unbiased_pcnt
self.mixing_factors = mixing_factors
self.seed = seed
self.data_efficient = data_efficient
<|end_body_0|>
<|body_start_1|>
mixing_factor = self.mixing_factors[split_id]
biased, unbiased = get_... | Split the given data into a biased subset and a normal subset. | BiasedSubset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiasedSubset:
"""Split the given data into a biased subset and a normal subset."""
def __init__(self, unbiased_pcnt: float, mixing_factors: Sequence[float]=(0,), seed: int=42, data_efficient: bool=True):
"""The constructor takes the following arguments. Args: mixing_factors: List of ... | stack_v2_sparse_classes_36k_train_021485 | 10,886 | no_license | [
{
"docstring": "The constructor takes the following arguments. Args: mixing_factors: List of mixing factors; they are chosen based on the split ID unbiased_pcnt: how much of the data should be reserved for the unbiased subset seed: random seed for the splitting data_efficient: if True, try to keep as many data ... | 2 | null | Implement the Python class `BiasedSubset` described below.
Class description:
Split the given data into a biased subset and a normal subset.
Method signatures and docstrings:
- def __init__(self, unbiased_pcnt: float, mixing_factors: Sequence[float]=(0,), seed: int=42, data_efficient: bool=True): The constructor take... | Implement the Python class `BiasedSubset` described below.
Class description:
Split the given data into a biased subset and a normal subset.
Method signatures and docstrings:
- def __init__(self, unbiased_pcnt: float, mixing_factors: Sequence[float]=(0,), seed: int=42, data_efficient: bool=True): The constructor take... | 3aecb7642d9611ae0a61cd47948931f8f47b6f76 | <|skeleton|>
class BiasedSubset:
"""Split the given data into a biased subset and a normal subset."""
def __init__(self, unbiased_pcnt: float, mixing_factors: Sequence[float]=(0,), seed: int=42, data_efficient: bool=True):
"""The constructor takes the following arguments. Args: mixing_factors: List of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BiasedSubset:
"""Split the given data into a biased subset and a normal subset."""
def __init__(self, unbiased_pcnt: float, mixing_factors: Sequence[float]=(0,), seed: int=42, data_efficient: bool=True):
"""The constructor takes the following arguments. Args: mixing_factors: List of mixing factor... | the_stack_v2_python_sparse | ethicml/preprocessing/biased_split.py | anonymous-iclr-3518/code-for-submission | train | 0 |
dfac652566853639b4474859abadb4fa756796fd | [
"self.width = width\nself.nr_lanes = nr_lanes\nself.nr_dots = nr_dots\nself.dots = np.empty((nr_lanes, nr_dots, 2, 2))",
"y = 0.0\nfor i in range(self.nr_lanes):\n x = 0\n for j in range(self.nr_dots):\n self.dots[i, j] = [[x, y], [x, y + self.width]]\n x += 1\n y += self.width\nreturn self... | <|body_start_0|>
self.width = width
self.nr_lanes = nr_lanes
self.nr_dots = nr_dots
self.dots = np.empty((nr_lanes, nr_dots, 2, 2))
<|end_body_0|>
<|body_start_1|>
y = 0.0
for i in range(self.nr_lanes):
x = 0
for j in range(self.nr_dots):
... | Generates mock-up data for lane positions. Generates a matrix consisting of lanes with 100 pairs of coordinates indicating the lanes' position. All lanes are straight and the purpose is to test the visualiser. Attributes: width: width of the lanes in m, taken as the average lane width. nr_lanes: number of lanes on the ... | Generator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Generator:
"""Generates mock-up data for lane positions. Generates a matrix consisting of lanes with 100 pairs of coordinates indicating the lanes' position. All lanes are straight and the purpose is to test the visualiser. Attributes: width: width of the lanes in m, taken as the average lane wid... | stack_v2_sparse_classes_36k_train_021486 | 1,335 | permissive | [
{
"docstring": "Initializes the Generator class, width is set at 3.7m.",
"name": "__init__",
"signature": "def __init__(self, nr_lanes, nr_dots, width=3.7)"
},
{
"docstring": "Generates mock-up data for nr_lanes amount of lanes. The starting position on the same y as the Ego vehicle, but 50 mete... | 2 | null | Implement the Python class `Generator` described below.
Class description:
Generates mock-up data for lane positions. Generates a matrix consisting of lanes with 100 pairs of coordinates indicating the lanes' position. All lanes are straight and the purpose is to test the visualiser. Attributes: width: width of the la... | Implement the Python class `Generator` described below.
Class description:
Generates mock-up data for lane positions. Generates a matrix consisting of lanes with 100 pairs of coordinates indicating the lanes' position. All lanes are straight and the purpose is to test the visualiser. Attributes: width: width of the la... | 2dd5c5e90adf2c29e5c1e81e8639813edbf65903 | <|skeleton|>
class Generator:
"""Generates mock-up data for lane positions. Generates a matrix consisting of lanes with 100 pairs of coordinates indicating the lanes' position. All lanes are straight and the purpose is to test the visualiser. Attributes: width: width of the lanes in m, taken as the average lane wid... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Generator:
"""Generates mock-up data for lane positions. Generates a matrix consisting of lanes with 100 pairs of coordinates indicating the lanes' position. All lanes are straight and the purpose is to test the visualiser. Attributes: width: width of the lanes in m, taken as the average lane width. nr_lanes:... | the_stack_v2_python_sparse | Tools/Generator.py | florias/TNO-RU-Lane-detection-project | train | 2 |
59ed3e63410910f4775c503f287f03115e2938db | [
"super(ListInterestCategoryInterest, self).__init__(*args, **kwargs)\nself.endpoint = 'lists'\nself.list_id = None\nself.category_id = None\nself.interest_id = None",
"self.list_id = list_id\nself.category_id = category_id\nif 'name' not in data:\n raise KeyError('The list interest category interest must have ... | <|body_start_0|>
super(ListInterestCategoryInterest, self).__init__(*args, **kwargs)
self.endpoint = 'lists'
self.list_id = None
self.category_id = None
self.interest_id = None
<|end_body_0|>
<|body_start_1|>
self.list_id = list_id
self.category_id = category_id
... | Manage interests for a specific MailChimp list. Assign subscribers to interests to group them together. Interests are referred to as ‘group names’ in the MailChimp application. | ListInterestCategoryInterest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListInterestCategoryInterest:
"""Manage interests for a specific MailChimp list. Assign subscribers to interests to group them together. Interests are referred to as ‘group names’ in the MailChimp application."""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
... | stack_v2_sparse_classes_36k_train_021487 | 5,847 | permissive | [
{
"docstring": "Initialize the endpoint",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Create a new interest or ‘group name’ for a specific category. The documentation lists only the name request body parameter so it is being documented and error-chec... | 6 | stack_v2_sparse_classes_30k_train_013143 | Implement the Python class `ListInterestCategoryInterest` described below.
Class description:
Manage interests for a specific MailChimp list. Assign subscribers to interests to group them together. Interests are referred to as ‘group names’ in the MailChimp application.
Method signatures and docstrings:
- def __init_... | Implement the Python class `ListInterestCategoryInterest` described below.
Class description:
Manage interests for a specific MailChimp list. Assign subscribers to interests to group them together. Interests are referred to as ‘group names’ in the MailChimp application.
Method signatures and docstrings:
- def __init_... | bf61cd602dc44cbff32fbf6f6dcdd33cf6f782e8 | <|skeleton|>
class ListInterestCategoryInterest:
"""Manage interests for a specific MailChimp list. Assign subscribers to interests to group them together. Interests are referred to as ‘group names’ in the MailChimp application."""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListInterestCategoryInterest:
"""Manage interests for a specific MailChimp list. Assign subscribers to interests to group them together. Interests are referred to as ‘group names’ in the MailChimp application."""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
super(Lis... | the_stack_v2_python_sparse | mailchimp3/entities/listinterestcategoryinterest.py | VingtCinq/python-mailchimp | train | 190 |
31276cb08d68250bcb13adb19566408462a34556 | [
"problem = get_SALib_problem(uncertainties)\nsamples = self.sample(problem, size)\ntemp = {}\nfor i, unc in enumerate(uncertainties):\n sample = samples[:, i]\n if isinstance(unc, IntegerParameter):\n sample = np.floor(sample)\n temp[unc.name] = sample\nreturn temp",
"parameters = sorted(parameter... | <|body_start_0|>
problem = get_SALib_problem(uncertainties)
samples = self.sample(problem, size)
temp = {}
for i, unc in enumerate(uncertainties):
sample = samples[:, i]
if isinstance(unc, IntegerParameter):
sample = np.floor(sample)
te... | SALibSampler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SALibSampler:
def generate_samples(self, uncertainties, size):
"""The main method of :class: `~sampler.Sampler` and its children. This will call the sample method for each of the uncertainties and return the resulting designs. Parameters ---------- uncertainties : collection a collection... | stack_v2_sparse_classes_36k_train_021488 | 5,372 | permissive | [
{
"docstring": "The main method of :class: `~sampler.Sampler` and its children. This will call the sample method for each of the uncertainties and return the resulting designs. Parameters ---------- uncertainties : collection a collection of Parameter instances size : int the number of samples to generate. Retu... | 2 | stack_v2_sparse_classes_30k_train_005213 | Implement the Python class `SALibSampler` described below.
Class description:
Implement the SALibSampler class.
Method signatures and docstrings:
- def generate_samples(self, uncertainties, size): The main method of :class: `~sampler.Sampler` and its children. This will call the sample method for each of the uncertai... | Implement the Python class `SALibSampler` described below.
Class description:
Implement the SALibSampler class.
Method signatures and docstrings:
- def generate_samples(self, uncertainties, size): The main method of :class: `~sampler.Sampler` and its children. This will call the sample method for each of the uncertai... | 9d13fb6fc8e8e3fc8cc693102f85966c5876f9ac | <|skeleton|>
class SALibSampler:
def generate_samples(self, uncertainties, size):
"""The main method of :class: `~sampler.Sampler` and its children. This will call the sample method for each of the uncertainties and return the resulting designs. Parameters ---------- uncertainties : collection a collection... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SALibSampler:
def generate_samples(self, uncertainties, size):
"""The main method of :class: `~sampler.Sampler` and its children. This will call the sample method for each of the uncertainties and return the resulting designs. Parameters ---------- uncertainties : collection a collection of Parameter ... | the_stack_v2_python_sparse | ema_workbench/em_framework/salib_samplers.py | quaquel/EMAworkbench | train | 102 | |
226fd2d91c9515b22f84840de175b4987f303df1 | [
"if not root:\n return ''\nq = deque()\nq.append(root)\nans = []\nwhile q:\n length = len(q)\n for _ in range(length):\n node = q.popleft()\n ans.append(str(node.val) if node else 'null')\n if node:\n q.append(node.left)\n q.append(node.right)\nreturn ','.join(ans... | <|body_start_0|>
if not root:
return ''
q = deque()
q.append(root)
ans = []
while q:
length = len(q)
for _ in range(length):
node = q.popleft()
ans.append(str(node.val) if node else 'null')
if nod... | Codec | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_021489 | 2,741 | 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:... | 226cecde136531341ce23cdf88529345be1912fc | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
q = deque()
q.append(root)
ans = []
while q:
length = len(q)
for _ in range(length):
... | the_stack_v2_python_sparse | Leetcode/Intermediate/Design/297_Serialize_and_Deserialize_Binary_Tree.py | ZR-Huang/AlgorithmsPractices | train | 1 | |
6b1bd643f5b63c2aeaf1fbae0d86b98e6914dead | [
"result = []\nleft, right = (0, 0)\n\ndef backtracking(partial, left, right, n):\n if left >= right >= 0:\n if len(partial) == n * 2:\n result.append(partial)\n if left < n:\n backtracking(partial + '(', left + 1, right, n)\n if right < left:\n backtracking(p... | <|body_start_0|>
result = []
left, right = (0, 0)
def backtracking(partial, left, right, n):
if left >= right >= 0:
if len(partial) == n * 2:
result.append(partial)
if left < n:
backtracking(partial + '(', left ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generateParenthesis_add_1(self, n):
""":type n: int :rtype: List[str]"""
<|body_0|>
def generateParenthesis_minus_1(self, n):
""":type n: int :rtype: List[str]"""
<|body_1|>
def generateParenthesis_refer(self, n):
""":type n: int :r... | stack_v2_sparse_classes_36k_train_021490 | 3,026 | no_license | [
{
"docstring": ":type n: int :rtype: List[str]",
"name": "generateParenthesis_add_1",
"signature": "def generateParenthesis_add_1(self, n)"
},
{
"docstring": ":type n: int :rtype: List[str]",
"name": "generateParenthesis_minus_1",
"signature": "def generateParenthesis_minus_1(self, n)"
... | 3 | stack_v2_sparse_classes_30k_train_009481 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateParenthesis_add_1(self, n): :type n: int :rtype: List[str]
- def generateParenthesis_minus_1(self, n): :type n: int :rtype: List[str]
- def generateParenthesis_refer(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateParenthesis_add_1(self, n): :type n: int :rtype: List[str]
- def generateParenthesis_minus_1(self, n): :type n: int :rtype: List[str]
- def generateParenthesis_refer(... | f3fc71f344cd758cfce77f16ab72992c99ab288e | <|skeleton|>
class Solution:
def generateParenthesis_add_1(self, n):
""":type n: int :rtype: List[str]"""
<|body_0|>
def generateParenthesis_minus_1(self, n):
""":type n: int :rtype: List[str]"""
<|body_1|>
def generateParenthesis_refer(self, n):
""":type n: int :r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def generateParenthesis_add_1(self, n):
""":type n: int :rtype: List[str]"""
result = []
left, right = (0, 0)
def backtracking(partial, left, right, n):
if left >= right >= 0:
if len(partial) == n * 2:
result.append(par... | the_stack_v2_python_sparse | 22_generateParenthesis.py | jennyChing/leetCode | train | 2 | |
01429cf2f85a8c1b0b70cc09bc86cecabd6fb5c8 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | RPCApi are "private" rpc methods for an instance related to a specific log. This should only be available to trusted parties. | LogRPCServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogRPCServicer:
"""RPCApi are "private" rpc methods for an instance related to a specific log. This should only be available to trusted parties."""
def GetHead(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def GetLogEn... | stack_v2_sparse_classes_36k_train_021491 | 12,917 | no_license | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "GetHead",
"signature": "def GetHead(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "GetLogEntries",
"signature": "def GetLogEntries(self, re... | 4 | stack_v2_sparse_classes_30k_train_018702 | Implement the Python class `LogRPCServicer` described below.
Class description:
RPCApi are "private" rpc methods for an instance related to a specific log. This should only be available to trusted parties.
Method signatures and docstrings:
- def GetHead(self, request, context): Missing associated documentation commen... | Implement the Python class `LogRPCServicer` described below.
Class description:
RPCApi are "private" rpc methods for an instance related to a specific log. This should only be available to trusted parties.
Method signatures and docstrings:
- def GetHead(self, request, context): Missing associated documentation commen... | 9bf6f32ab9b28c49fdc12c6e7a847a2b6dc1aa00 | <|skeleton|>
class LogRPCServicer:
"""RPCApi are "private" rpc methods for an instance related to a specific log. This should only be available to trusted parties."""
def GetHead(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def GetLogEn... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogRPCServicer:
"""RPCApi are "private" rpc methods for an instance related to a specific log. This should only be available to trusted parties."""
def GetHead(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEM... | the_stack_v2_python_sparse | packages/trustix-python/trustix_python/rpc/rpc_pb2_grpc.py | daotlresearch/trustix | train | 0 |
af4427f3e83a54bf497d24818e6a9b052df23ff3 | [
"if ADAPTIVE_AVG_POOL_BUG and module.input0.is_cuda and (self.N == 3):\n warn('Be careful when computing gradients of AdaptiveAvgPool3d. There is a bug using autograd.grad on cuda with AdaptiveAvgPool3d. https://discuss.pytorch.org/t/bug-report-autograd-grad-adaptiveavgpool3d-cuda/124614 BackPACK derivatives are... | <|body_start_0|>
if ADAPTIVE_AVG_POOL_BUG and module.input0.is_cuda and (self.N == 3):
warn('Be careful when computing gradients of AdaptiveAvgPool3d. There is a bug using autograd.grad on cuda with AdaptiveAvgPool3d. https://discuss.pytorch.org/t/bug-report-autograd-grad-adaptiveavgpool3d-cuda/1246... | Implements the derivatives for AdaptiveAvgPool. | AdaptiveAvgPoolNDDerivatives | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdaptiveAvgPoolNDDerivatives:
"""Implements the derivatives for AdaptiveAvgPool."""
def check_parameters(self, module: Union[AdaptiveAvgPool1d, AdaptiveAvgPool2d, AdaptiveAvgPool3d]) -> None:
"""Checks if the parameters are supported. Specifically checks if input shape is multiple of... | stack_v2_sparse_classes_36k_train_021492 | 3,807 | permissive | [
{
"docstring": "Checks if the parameters are supported. Specifically checks if input shape is multiple of output shape. In this case, there are parameters for AvgPoolND that are equivalent. https://stackoverflow.com/questions/53841509/how-does-adaptive-pooling-in-pytorch-work/63603993#63603993 # noqa: B950 Args... | 2 | stack_v2_sparse_classes_30k_train_003625 | Implement the Python class `AdaptiveAvgPoolNDDerivatives` described below.
Class description:
Implements the derivatives for AdaptiveAvgPool.
Method signatures and docstrings:
- def check_parameters(self, module: Union[AdaptiveAvgPool1d, AdaptiveAvgPool2d, AdaptiveAvgPool3d]) -> None: Checks if the parameters are sup... | Implement the Python class `AdaptiveAvgPoolNDDerivatives` described below.
Class description:
Implements the derivatives for AdaptiveAvgPool.
Method signatures and docstrings:
- def check_parameters(self, module: Union[AdaptiveAvgPool1d, AdaptiveAvgPool2d, AdaptiveAvgPool3d]) -> None: Checks if the parameters are sup... | 1ebfb4055be72ed9e0f9d101d78806bd4119645e | <|skeleton|>
class AdaptiveAvgPoolNDDerivatives:
"""Implements the derivatives for AdaptiveAvgPool."""
def check_parameters(self, module: Union[AdaptiveAvgPool1d, AdaptiveAvgPool2d, AdaptiveAvgPool3d]) -> None:
"""Checks if the parameters are supported. Specifically checks if input shape is multiple of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdaptiveAvgPoolNDDerivatives:
"""Implements the derivatives for AdaptiveAvgPool."""
def check_parameters(self, module: Union[AdaptiveAvgPool1d, AdaptiveAvgPool2d, AdaptiveAvgPool3d]) -> None:
"""Checks if the parameters are supported. Specifically checks if input shape is multiple of output shape... | the_stack_v2_python_sparse | backpack/core/derivatives/adaptive_avg_pool_nd.py | f-dangel/backpack | train | 505 |
38ffc5575f6db97d916bc84c55ad6bde5c6d1f6d | [
"res = 0\ntmp = 1\nloop = 0\nfor num in range(N, 0, -1):\n if loop == 0:\n tmp *= num\n elif loop == 1:\n tmp *= num\n elif loop == 2:\n tmp = tmp // num\n tmp = sign * tmp\n loop = (loop + 1) % 4\n res += tmp\n tmp = 1\nreturn res",
"import collections\nimport heapq\... | <|body_start_0|>
res = 0
tmp = 1
loop = 0
for num in range(N, 0, -1):
if loop == 0:
tmp *= num
elif loop == 1:
tmp *= num
elif loop == 2:
tmp = tmp // num
tmp = sign * tmp
loop... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def clumsy(self, N: int) -> int:
"""通常，正整数 n 的阶乘是所有小于或等于 n 的正整数的乘积。例如，factorial(10) = 10 * 9 * 8 * 7 * 6 * 5 * 4 * 3 * 2 * 1。 相反，我们设计了一个笨阶乘 clumsy：在整数的递减序列中，我们以一个固定顺序的操作符序列来依次替换原有的乘法操作符： 乘法(*)，除法(/)，加法(+)和减法(-)。 例如，clumsy(10) = 10 * 9 / 8 + 7 - 6 * 5 / 4 + 3 - 2 * 1。然而，这些运算仍然使用... | stack_v2_sparse_classes_36k_train_021493 | 2,717 | no_license | [
{
"docstring": "通常，正整数 n 的阶乘是所有小于或等于 n 的正整数的乘积。例如，factorial(10) = 10 * 9 * 8 * 7 * 6 * 5 * 4 * 3 * 2 * 1。 相反，我们设计了一个笨阶乘 clumsy：在整数的递减序列中，我们以一个固定顺序的操作符序列来依次替换原有的乘法操作符： 乘法(*)，除法(/)，加法(+)和减法(-)。 例如，clumsy(10) = 10 * 9 / 8 + 7 - 6 * 5 / 4 + 3 - 2 * 1。然而，这些运算仍然使用通常的算术运算顺序： 我们在任何加、减步骤之前执行所有的乘法和除法步骤，并且按从左到右处理乘法和除法步骤。 ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def clumsy(self, N: int) -> int: 通常，正整数 n 的阶乘是所有小于或等于 n 的正整数的乘积。例如，factorial(10) = 10 * 9 * 8 * 7 * 6 * 5 * 4 * 3 * 2 * 1。 相反，我们设计了一个笨阶乘 clumsy：在整数的递减序列中，我们以一个固定顺序的操作符序列来依次替换原有的乘... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def clumsy(self, N: int) -> int: 通常，正整数 n 的阶乘是所有小于或等于 n 的正整数的乘积。例如，factorial(10) = 10 * 9 * 8 * 7 * 6 * 5 * 4 * 3 * 2 * 1。 相反，我们设计了一个笨阶乘 clumsy：在整数的递减序列中，我们以一个固定顺序的操作符序列来依次替换原有的乘... | 330330ef6bc42eeb17f4dea53c30d230506b4e8f | <|skeleton|>
class Solution:
def clumsy(self, N: int) -> int:
"""通常，正整数 n 的阶乘是所有小于或等于 n 的正整数的乘积。例如，factorial(10) = 10 * 9 * 8 * 7 * 6 * 5 * 4 * 3 * 2 * 1。 相反，我们设计了一个笨阶乘 clumsy：在整数的递减序列中，我们以一个固定顺序的操作符序列来依次替换原有的乘法操作符： 乘法(*)，除法(/)，加法(+)和减法(-)。 例如，clumsy(10) = 10 * 9 / 8 + 7 - 6 * 5 / 4 + 3 - 2 * 1。然而，这些运算仍然使用... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def clumsy(self, N: int) -> int:
"""通常，正整数 n 的阶乘是所有小于或等于 n 的正整数的乘积。例如，factorial(10) = 10 * 9 * 8 * 7 * 6 * 5 * 4 * 3 * 2 * 1。 相反，我们设计了一个笨阶乘 clumsy：在整数的递减序列中，我们以一个固定顺序的操作符序列来依次替换原有的乘法操作符： 乘法(*)，除法(/)，加法(+)和减法(-)。 例如，clumsy(10) = 10 * 9 / 8 + 7 - 6 * 5 / 4 + 3 - 2 * 1。然而，这些运算仍然使用通常的算术运算顺序： 我们在... | the_stack_v2_python_sparse | Code/leetcode_everyday/0401.py | NiceToMeeetU/ToGetReady | train | 0 | |
c4fe4105eaa1555c6bb452e20b8d972c34fec537 | [
"from anima.dcc.blackmagic import get_fusion\nfusion = get_fusion()\ncomp = fusion.GetCurrentComp()\nreturn comp.ActiveTool",
"node_input_list = node.GetInputList()\nfor input_entry_key in node_input_list.keys():\n input_entry = node_input_list[input_entry_key]\n input_id = input_entry.GetAttrs()['INPS_ID']... | <|body_start_0|>
from anima.dcc.blackmagic import get_fusion
fusion = get_fusion()
comp = fusion.GetCurrentComp()
return comp.ActiveTool
<|end_body_0|>
<|body_start_1|>
node_input_list = node.GetInputList()
for input_entry_key in node_input_list.keys():
input... | Node related utils for Fusion | NodeUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeUtils:
"""Node related utils for Fusion"""
def get_active_node(self):
"""returns the active node"""
<|body_0|>
def list_input_ids(cls, node):
"""List input ids of the given node :param node: :return:"""
<|body_1|>
def get_node_attr(cls, node, att... | stack_v2_sparse_classes_36k_train_021494 | 10,465 | permissive | [
{
"docstring": "returns the active node",
"name": "get_active_node",
"signature": "def get_active_node(self)"
},
{
"docstring": "List input ids of the given node :param node: :return:",
"name": "list_input_ids",
"signature": "def list_input_ids(cls, node)"
},
{
"docstring": "gets... | 6 | stack_v2_sparse_classes_30k_train_007153 | Implement the Python class `NodeUtils` described below.
Class description:
Node related utils for Fusion
Method signatures and docstrings:
- def get_active_node(self): returns the active node
- def list_input_ids(cls, node): List input ids of the given node :param node: :return:
- def get_node_attr(cls, node, attr): ... | Implement the Python class `NodeUtils` described below.
Class description:
Node related utils for Fusion
Method signatures and docstrings:
- def get_active_node(self): returns the active node
- def list_input_ids(cls, node): List input ids of the given node :param node: :return:
- def get_node_attr(cls, node, attr): ... | 7b4cf60cb17f00435ecc3e03d573a9e2d0b44fe0 | <|skeleton|>
class NodeUtils:
"""Node related utils for Fusion"""
def get_active_node(self):
"""returns the active node"""
<|body_0|>
def list_input_ids(cls, node):
"""List input ids of the given node :param node: :return:"""
<|body_1|>
def get_node_attr(cls, node, att... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NodeUtils:
"""Node related utils for Fusion"""
def get_active_node(self):
"""returns the active node"""
from anima.dcc.blackmagic import get_fusion
fusion = get_fusion()
comp = fusion.GetCurrentComp()
return comp.ActiveTool
def list_input_ids(cls, node):
... | the_stack_v2_python_sparse | anima/dcc/fusion/utils.py | eoyilmaz/anima | train | 113 |
f6f602813e8d149331f616953fcebe2f7c6aa15e | [
"cu = Change_Param(username, password, prod)\ngu = cu.get_params()\nself.suffix = self.c.get_value('Member', 'members_nocice_logs')\nself.url = self.url_joint(prod) + gu[1]\nlogs.info('test url:%s' % self.url)\nreturn self.get_requests(self.url, gu[0], data)",
"cu = Change_Param(username, password, prod)\ngu = cu... | <|body_start_0|>
cu = Change_Param(username, password, prod)
gu = cu.get_params()
self.suffix = self.c.get_value('Member', 'members_nocice_logs')
self.url = self.url_joint(prod) + gu[1]
logs.info('test url:%s' % self.url)
return self.get_requests(self.url, gu[0], data)
<|... | Member_Notice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Member_Notice:
def get_member_nocice_logs(self, username=None, password=None, data=None, prod=None):
"""相关参数有: page_no 页码 page_size 每页显示数量 read 是否已读，1已读，0未读,可用值:0,1"""
<|body_0|>
def del_member_nocice_logs_ids(self, ids, username=None, password=None, data=None, prod=None):
... | stack_v2_sparse_classes_36k_train_021495 | 2,683 | no_license | [
{
"docstring": "相关参数有: page_no 页码 page_size 每页显示数量 read 是否已读，1已读，0未读,可用值:0,1",
"name": "get_member_nocice_logs",
"signature": "def get_member_nocice_logs(self, username=None, password=None, data=None, prod=None)"
},
{
"docstring": "相关参数有: ids 要删除的消息主键",
"name": "del_member_nocice_logs_ids",
... | 3 | stack_v2_sparse_classes_30k_train_012967 | Implement the Python class `Member_Notice` described below.
Class description:
Implement the Member_Notice class.
Method signatures and docstrings:
- def get_member_nocice_logs(self, username=None, password=None, data=None, prod=None): 相关参数有: page_no 页码 page_size 每页显示数量 read 是否已读，1已读，0未读,可用值:0,1
- def del_member_noci... | Implement the Python class `Member_Notice` described below.
Class description:
Implement the Member_Notice class.
Method signatures and docstrings:
- def get_member_nocice_logs(self, username=None, password=None, data=None, prod=None): 相关参数有: page_no 页码 page_size 每页显示数量 read 是否已读，1已读，0未读,可用值:0,1
- def del_member_noci... | 235200a67c1fb125f75f9771808f6655a7b14202 | <|skeleton|>
class Member_Notice:
def get_member_nocice_logs(self, username=None, password=None, data=None, prod=None):
"""相关参数有: page_no 页码 page_size 每页显示数量 read 是否已读，1已读，0未读,可用值:0,1"""
<|body_0|>
def del_member_nocice_logs_ids(self, ids, username=None, password=None, data=None, prod=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Member_Notice:
def get_member_nocice_logs(self, username=None, password=None, data=None, prod=None):
"""相关参数有: page_no 页码 page_size 每页显示数量 read 是否已读，1已读，0未读,可用值:0,1"""
cu = Change_Param(username, password, prod)
gu = cu.get_params()
self.suffix = self.c.get_value('Member', 'mem... | the_stack_v2_python_sparse | business/member/member_notice.py | vothin/requsets_test | train | 0 | |
ca92d368ab50f16b736a3b6ad0ebb54ab61b9efe | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ServiceAnnouncementAttachment()",
"from .entity import Entity\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'content': lambda n: setattr(self, 'content', n.get_bytes_value()), 'contentType': lambda n: setattr... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ServiceAnnouncementAttachment()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .entity import Entity
fields: Dict[str, Callable[[Any], None]] = {'content': lambd... | ServiceAnnouncementAttachment | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceAnnouncementAttachment:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServiceAnnouncementAttachment:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_36k_train_021496 | 2,908 | 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: ServiceAnnouncementAttachment",
"name": "create_from_discriminator_value",
"signature": "def create_from_dis... | 3 | stack_v2_sparse_classes_30k_train_003177 | Implement the Python class `ServiceAnnouncementAttachment` described below.
Class description:
Implement the ServiceAnnouncementAttachment class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServiceAnnouncementAttachment: Creates a new instance of th... | Implement the Python class `ServiceAnnouncementAttachment` described below.
Class description:
Implement the ServiceAnnouncementAttachment class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServiceAnnouncementAttachment: Creates a new instance of th... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ServiceAnnouncementAttachment:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServiceAnnouncementAttachment:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServiceAnnouncementAttachment:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ServiceAnnouncementAttachment:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | the_stack_v2_python_sparse | msgraph/generated/models/service_announcement_attachment.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
6aa8c0779bd00888b721a590794288949f64008c | [
"cfg = self.model.cfg\nif cfg.get('inference_pipeline', None):\n test_pipeline = cfg.inference_pipeline\nelif cfg.get('demo_pipeline', None):\n test_pipeline = cfg.demo_pipeline\nelif cfg.get('test_pipeline', None):\n test_pipeline = cfg.test_pipeline\nelse:\n test_pipeline = cfg.val_pipeline\nkeys_to_r... | <|body_start_0|>
cfg = self.model.cfg
if cfg.get('inference_pipeline', None):
test_pipeline = cfg.inference_pipeline
elif cfg.get('demo_pipeline', None):
test_pipeline = cfg.demo_pipeline
elif cfg.get('test_pipeline', None):
test_pipeline = cfg.test_pi... | inferencer that predicts with restoration models. | ImageSuperResolutionInferencer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageSuperResolutionInferencer:
"""inferencer that predicts with restoration models."""
def preprocess(self, img: InputsType, ref: InputsType=None) -> Dict:
"""Process the inputs into a model-feedable format. Args: img(InputsType): Image to be restored by models. ref(InputsType): Ref... | stack_v2_sparse_classes_36k_train_021497 | 3,447 | permissive | [
{
"docstring": "Process the inputs into a model-feedable format. Args: img(InputsType): Image to be restored by models. ref(InputsType): Reference image for restoration models. Defaults to None. Returns: data(Dict): Results of preprocess.",
"name": "preprocess",
"signature": "def preprocess(self, img: I... | 3 | null | Implement the Python class `ImageSuperResolutionInferencer` described below.
Class description:
inferencer that predicts with restoration models.
Method signatures and docstrings:
- def preprocess(self, img: InputsType, ref: InputsType=None) -> Dict: Process the inputs into a model-feedable format. Args: img(InputsTy... | Implement the Python class `ImageSuperResolutionInferencer` described below.
Class description:
inferencer that predicts with restoration models.
Method signatures and docstrings:
- def preprocess(self, img: InputsType, ref: InputsType=None) -> Dict: Process the inputs into a model-feedable format. Args: img(InputsTy... | a382f143c0fd20d227e1e5524831ba26a568190d | <|skeleton|>
class ImageSuperResolutionInferencer:
"""inferencer that predicts with restoration models."""
def preprocess(self, img: InputsType, ref: InputsType=None) -> Dict:
"""Process the inputs into a model-feedable format. Args: img(InputsType): Image to be restored by models. ref(InputsType): Ref... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageSuperResolutionInferencer:
"""inferencer that predicts with restoration models."""
def preprocess(self, img: InputsType, ref: InputsType=None) -> Dict:
"""Process the inputs into a model-feedable format. Args: img(InputsType): Image to be restored by models. ref(InputsType): Reference image ... | the_stack_v2_python_sparse | mmagic/apis/inferencers/image_super_resolution_inferencer.py | open-mmlab/mmagic | train | 1,370 |
fd3efb49add7c77ae52f40d058fcbc78f0d5ed7d | [
"length = len(s)\np = np.zeros(shape=(length, length))\nmax_len = 0\nmax_str = ''\nfor l in range(1, length + 1):\n for start in range(0, length):\n end = start + l - 1\n if end >= length:\n break\n p[start][end] = (l == 1 or l == 2 or p[start + 1][end - 1]) and s[start] == s[end]... | <|body_start_0|>
length = len(s)
p = np.zeros(shape=(length, length))
max_len = 0
max_str = ''
for l in range(1, length + 1):
for start in range(0, length):
end = start + l - 1
if end >= length:
break
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome2(self, s):
""":type s: str :rtype: str 状态转移方程 p[i][j] = p[i+1][j-1] and s[i]==s[j] 空间优化： 实际只需要内存循环的值保留就行了 p[j] = p[j-1] and s[i]==s[j]"""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k_train_021498 | 1,483 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": ":type s: str :rtype: str 状态转移方程 p[i][j] = p[i+1][j-1] and s[i]==s[j] 空间优化： 实际只需要内存循环的值保留就行了 p[j] = p[j-1] and s[i]==s[j]",
"name": "longestPalindrome2",
... | 2 | stack_v2_sparse_classes_30k_train_019894 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: str
- def longestPalindrome2(self, s): :type s: str :rtype: str 状态转移方程 p[i][j] = p[i+1][j-1] and s[i]==s[j] 空间优化： 实际只需要内存循环的值... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: str
- def longestPalindrome2(self, s): :type s: str :rtype: str 状态转移方程 p[i][j] = p[i+1][j-1] and s[i]==s[j] 空间优化： 实际只需要内存循环的值... | 013f6f222c6c2a617787b258f8a37003a9f51526 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def longestPalindrome2(self, s):
""":type s: str :rtype: str 状态转移方程 p[i][j] = p[i+1][j-1] and s[i]==s[j] 空间优化： 实际只需要内存循环的值保留就行了 p[j] = p[j-1] and s[i]==s[j]"""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
length = len(s)
p = np.zeros(shape=(length, length))
max_len = 0
max_str = ''
for l in range(1, length + 1):
for start in range(0, length):
end = start + l - 1
... | the_stack_v2_python_sparse | dp/longest_palindrome.py | terrifyzhao/leetcode | train | 0 | |
639b4b2bf2b5f83f0582d98c72464a1f936b3055 | [
"if n == 1:\n return 1\nelif n == 2:\n return 2\nelse:\n temp1, temp2 = (1, 2)\n for i in range(2, n):\n temp1, temp2 = (temp2, temp1 + temp2)\nreturn temp2",
"def f(n):\n if n <= 2:\n return n\n else:\n return f(n - 1) + f(n - 2)\nreturn f(n)"
] | <|body_start_0|>
if n == 1:
return 1
elif n == 2:
return 2
else:
temp1, temp2 = (1, 2)
for i in range(2, n):
temp1, temp2 = (temp2, temp1 + temp2)
return temp2
<|end_body_0|>
<|body_start_1|>
def f(n):
i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs(self, n: int) -> int:
"""动态规划： 1. 设定目标：n级台阶有m种爬法 2. 迁移方程：m(n)=m(n-1) + m(n-2) 3. 初始状态：m（1）= 1, m(2) = 2"""
<|body_0|>
def climbStairs(self, n: int) -> int:
"""递归实现:超出时间限制"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n... | stack_v2_sparse_classes_36k_train_021499 | 793 | no_license | [
{
"docstring": "动态规划： 1. 设定目标：n级台阶有m种爬法 2. 迁移方程：m(n)=m(n-1) + m(n-2) 3. 初始状态：m（1）= 1, m(2) = 2",
"name": "climbStairs",
"signature": "def climbStairs(self, n: int) -> int"
},
{
"docstring": "递归实现:超出时间限制",
"name": "climbStairs",
"signature": "def climbStairs(self, n: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n: int) -> int: 动态规划： 1. 设定目标：n级台阶有m种爬法 2. 迁移方程：m(n)=m(n-1) + m(n-2) 3. 初始状态：m（1）= 1, m(2) = 2
- def climbStairs(self, n: int) -> int: 递归实现:超出时间限制 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n: int) -> int: 动态规划： 1. 设定目标：n级台阶有m种爬法 2. 迁移方程：m(n)=m(n-1) + m(n-2) 3. 初始状态：m（1）= 1, m(2) = 2
- def climbStairs(self, n: int) -> int: 递归实现:超出时间限制
<|skelet... | f0f4ba0cb91096e55e21b7a2240afbd347187351 | <|skeleton|>
class Solution:
def climbStairs(self, n: int) -> int:
"""动态规划： 1. 设定目标：n级台阶有m种爬法 2. 迁移方程：m(n)=m(n-1) + m(n-2) 3. 初始状态：m（1）= 1, m(2) = 2"""
<|body_0|>
def climbStairs(self, n: int) -> int:
"""递归实现:超出时间限制"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs(self, n: int) -> int:
"""动态规划： 1. 设定目标：n级台阶有m种爬法 2. 迁移方程：m(n)=m(n-1) + m(n-2) 3. 初始状态：m（1）= 1, m(2) = 2"""
if n == 1:
return 1
elif n == 2:
return 2
else:
temp1, temp2 = (1, 2)
for i in range(2, n):
... | the_stack_v2_python_sparse | coding_test/70_climbStairs.py | zhuheng-mark/myDL | train | 2 |
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