blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9f36fc4dee7fef4ff76ff39992ba012bcf394447 | [
"page = convert_safely(int, request.args.get('page'), 1)\nfeatures = FeatureDB.query.paginate(page, per_page=LIMIT_PER_PAGE, error_out=False).items\nreturn (features, HTTPStatus.OK)",
"feature = FeatureDB.get_by_name(api.payload.get('name'))\ntry:\n if feature:\n feature.add_users(api.payload.get('users... | <|body_start_0|>
page = convert_safely(int, request.args.get('page'), 1)
features = FeatureDB.query.paginate(page, per_page=LIMIT_PER_PAGE, error_out=False).items
return (features, HTTPStatus.OK)
<|end_body_0|>
<|body_start_1|>
feature = FeatureDB.get_by_name(api.payload.get('name'))
... | List and Add features. | ListFeatures | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListFeatures:
"""List and Add features."""
def get(self):
"""List of paginated features"""
<|body_0|>
def post(self):
"""Add new feature, update it with users if name is identical"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
page = convert_sa... | stack_v2_sparse_classes_36k_train_034700 | 3,855 | permissive | [
{
"docstring": "List of paginated features",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Add new feature, update it with users if name is identical",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005554 | Implement the Python class `ListFeatures` described below.
Class description:
List and Add features.
Method signatures and docstrings:
- def get(self): List of paginated features
- def post(self): Add new feature, update it with users if name is identical | Implement the Python class `ListFeatures` described below.
Class description:
List and Add features.
Method signatures and docstrings:
- def get(self): List of paginated features
- def post(self): Add new feature, update it with users if name is identical
<|skeleton|>
class ListFeatures:
"""List and Add features... | 18e9ed6d2a660a9fe188881d4af79af3638cdd73 | <|skeleton|>
class ListFeatures:
"""List and Add features."""
def get(self):
"""List of paginated features"""
<|body_0|>
def post(self):
"""Add new feature, update it with users if name is identical"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListFeatures:
"""List and Add features."""
def get(self):
"""List of paginated features"""
page = convert_safely(int, request.args.get('page'), 1)
features = FeatureDB.query.paginate(page, per_page=LIMIT_PER_PAGE, error_out=False).items
return (features, HTTPStatus.OK)
... | the_stack_v2_python_sparse | requester/api/endpoints/features.py | mrf345/flask_restful_api_production_example | train | 1 |
092bdb9a602ae0f2f00413fa5729592b6f90b7ca | [
"prop = typeFor(ref)\nif not isinstance(prop, TypeProperty):\n return False\nassert isinstance(prop, TypeProperty)\nassert isinstance(prop.parent, TypeContainer), 'Invalid parent for %s' % prop\nif prop.parent.isValid(self):\n descriptor, _clazz = getAttrAndClass(self.__class__, prop.name)\n if not isinsta... | <|body_start_0|>
prop = typeFor(ref)
if not isinstance(prop, TypeProperty):
return False
assert isinstance(prop, TypeProperty)
assert isinstance(prop.parent, TypeContainer), 'Invalid parent for %s' % prop
if prop.parent.isValid(self):
descriptor, _clazz = ... | Support class for containers. | Container | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Container:
"""Support class for containers."""
def __contains__(self, ref):
"""Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @return: boolean True if a value for the reference is prese... | stack_v2_sparse_classes_36k_train_034701 | 16,647 | no_license | [
{
"docstring": "Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @return: boolean True if a value for the reference is present, false otherwise.",
"name": "__contains__",
"signature": "def __contains__(self,... | 2 | stack_v2_sparse_classes_30k_train_019493 | Implement the Python class `Container` described below.
Class description:
Support class for containers.
Method signatures and docstrings:
- def __contains__(self, ref): Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @r... | Implement the Python class `Container` described below.
Class description:
Support class for containers.
Method signatures and docstrings:
- def __contains__(self, ref): Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @r... | e0b3466b34d31548996d57be4a9dac134d904380 | <|skeleton|>
class Container:
"""Support class for containers."""
def __contains__(self, ref):
"""Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @return: boolean True if a value for the reference is prese... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Container:
"""Support class for containers."""
def __contains__(self, ref):
"""Checks if the object contains a value for the property even if that value is None. @param ref: TypeProperty reference The type property to check. @return: boolean True if a value for the reference is present, false oth... | the_stack_v2_python_sparse | components/ally-api/ally/api/operator/descriptor.py | cristidomsa/Ally-Py | train | 0 |
e9b6bf2dd1eb7ddd3c48b9f328ed2be0afecd239 | [
"queryset = self.filter_queryset(self.get_queryset())\nuid = force_text(urlsafe_base64_decode(self.kwargs['uid']))\ntoken = self.kwargs['token']\nobj = get_object_or_404(queryset, pk=uid)\nself.check_object_permissions(self.request, obj)\nif not default_token_generator.check_token(user=obj, token=token):\n raise... | <|body_start_0|>
queryset = self.filter_queryset(self.get_queryset())
uid = force_text(urlsafe_base64_decode(self.kwargs['uid']))
token = self.kwargs['token']
obj = get_object_or_404(queryset, pk=uid)
self.check_object_permissions(self.request, obj)
if not default_token_g... | User activate view. | UserActivation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserActivation:
"""User activate view."""
def get_object(self) -> User:
"""Get user by uid and check permissions. :return: User."""
<|body_0|>
def get(self, request: Request, *args: tuple, **kwargs: dict) -> Response:
"""Activate user. :param request: :return:"""... | stack_v2_sparse_classes_36k_train_034702 | 5,061 | no_license | [
{
"docstring": "Get user by uid and check permissions. :return: User.",
"name": "get_object",
"signature": "def get_object(self) -> User"
},
{
"docstring": "Activate user. :param request: :return:",
"name": "get",
"signature": "def get(self, request: Request, *args: tuple, **kwargs: dict... | 2 | stack_v2_sparse_classes_30k_train_011306 | Implement the Python class `UserActivation` described below.
Class description:
User activate view.
Method signatures and docstrings:
- def get_object(self) -> User: Get user by uid and check permissions. :return: User.
- def get(self, request: Request, *args: tuple, **kwargs: dict) -> Response: Activate user. :param... | Implement the Python class `UserActivation` described below.
Class description:
User activate view.
Method signatures and docstrings:
- def get_object(self) -> User: Get user by uid and check permissions. :return: User.
- def get(self, request: Request, *args: tuple, **kwargs: dict) -> Response: Activate user. :param... | 713b9d84ac70d964d46f189ab1f9c7b944b9684b | <|skeleton|>
class UserActivation:
"""User activate view."""
def get_object(self) -> User:
"""Get user by uid and check permissions. :return: User."""
<|body_0|>
def get(self, request: Request, *args: tuple, **kwargs: dict) -> Response:
"""Activate user. :param request: :return:"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserActivation:
"""User activate view."""
def get_object(self) -> User:
"""Get user by uid and check permissions. :return: User."""
queryset = self.filter_queryset(self.get_queryset())
uid = force_text(urlsafe_base64_decode(self.kwargs['uid']))
token = self.kwargs['token']... | the_stack_v2_python_sparse | jobadvisor/users/views/registration.py | ewgen19892/jobadvisor | train | 0 |
6d6181025affe70786e96cfe13f44c618e7f1338 | [
"super().__init__()\nself.num_embeddings = num_embeddings\nself.embedding_dim = embedding_dim\nself.num_positions = positonal_max_length\nself.token_embedding = nn.Embedding(num_embeddings, embedding_dim, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)\nself.pos_embedding = None\nif positional_learned... | <|body_start_0|>
super().__init__()
self.num_embeddings = num_embeddings
self.embedding_dim = embedding_dim
self.num_positions = positonal_max_length
self.token_embedding = nn.Embedding(num_embeddings, embedding_dim, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
... | Implement an Embeddings module. This object replicates the usage of nn.Embedding but registers the from_pretrained classmethod to be used inside a Flambé configuration, as this does not happen automatically during the registration of PyTorch objects. The module also adds optional positional encoding, which can either b... | Embeddings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Embeddings:
"""Implement an Embeddings module. This object replicates the usage of nn.Embedding but registers the from_pretrained classmethod to be used inside a Flambé configuration, as this does not happen automatically during the registration of PyTorch objects. The module also adds optional p... | stack_v2_sparse_classes_36k_train_034703 | 12,470 | permissive | [
{
"docstring": "Initialize an Embeddings module. Parameters ---------- num_embeddings : int Size of the dictionary of embeddings. embedding_dim : int The size of each embedding vector. padding_idx : int, optional Pads the output with the embedding vector at :attr:`padding_idx` (initialized to zeros) whenever it... | 3 | null | Implement the Python class `Embeddings` described below.
Class description:
Implement an Embeddings module. This object replicates the usage of nn.Embedding but registers the from_pretrained classmethod to be used inside a Flambé configuration, as this does not happen automatically during the registration of PyTorch o... | Implement the Python class `Embeddings` described below.
Class description:
Implement an Embeddings module. This object replicates the usage of nn.Embedding but registers the from_pretrained classmethod to be used inside a Flambé configuration, as this does not happen automatically during the registration of PyTorch o... | 0dc2f5b2b286694defe8abf450fe5be9ae12c097 | <|skeleton|>
class Embeddings:
"""Implement an Embeddings module. This object replicates the usage of nn.Embedding but registers the from_pretrained classmethod to be used inside a Flambé configuration, as this does not happen automatically during the registration of PyTorch objects. The module also adds optional p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Embeddings:
"""Implement an Embeddings module. This object replicates the usage of nn.Embedding but registers the from_pretrained classmethod to be used inside a Flambé configuration, as this does not happen automatically during the registration of PyTorch objects. The module also adds optional positional enc... | the_stack_v2_python_sparse | flambe/nn/embedding.py | cle-ros/flambe | train | 1 |
a8281337f686779f4107e173868b74f7914328df | [
"if n <= 3:\n return n - 1\na, b = (n // 3, n % 3)\nif b == 1:\n return 3 ** (a - 1) * 4\nelif b == 2:\n return 3 ** a * b\nelse:\n return 3 ** a",
"dp = [0, 1, 1, 2]\nfor i in range(4, n + 1):\n dp.append(1)\n for j in range(2, i):\n dp[i] = max(dp[i], j * (i - j), j * dp[i - j])\nreturn... | <|body_start_0|>
if n <= 3:
return n - 1
a, b = (n // 3, n % 3)
if b == 1:
return 3 ** (a - 1) * 4
elif b == 2:
return 3 ** a * b
else:
return 3 ** a
<|end_body_0|>
<|body_start_1|>
dp = [0, 1, 1, 2]
for i in range(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def cuttingRope(self, n: int) -> int:
"""offer 14-I 剪绳子 绳子优先距离：3>2>1"""
<|body_0|>
def cuttingRope1(self, n: int) -> int:
"""动态规划 转移方程：dp[i] = max(dp[i],max(j*(i-j),j*dp[i-j]) dp存放结果，绳长i剪j剩下i-j"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_034704 | 886 | no_license | [
{
"docstring": "offer 14-I 剪绳子 绳子优先距离：3>2>1",
"name": "cuttingRope",
"signature": "def cuttingRope(self, n: int) -> int"
},
{
"docstring": "动态规划 转移方程：dp[i] = max(dp[i],max(j*(i-j),j*dp[i-j]) dp存放结果，绳长i剪j剩下i-j",
"name": "cuttingRope1",
"signature": "def cuttingRope1(self, n: int) -> int"
... | 2 | stack_v2_sparse_classes_30k_test_000173 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cuttingRope(self, n: int) -> int: offer 14-I 剪绳子 绳子优先距离：3>2>1
- def cuttingRope1(self, n: int) -> int: 动态规划 转移方程：dp[i] = max(dp[i],max(j*(i-j),j*dp[i-j]) dp存放结果，绳长i剪j剩下i-j | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def cuttingRope(self, n: int) -> int: offer 14-I 剪绳子 绳子优先距离：3>2>1
- def cuttingRope1(self, n: int) -> int: 动态规划 转移方程：dp[i] = max(dp[i],max(j*(i-j),j*dp[i-j]) dp存放结果，绳长i剪j剩下i-j
<... | 3fd69b85f52af861ff7e2c74d8aacc515b192615 | <|skeleton|>
class Solution:
def cuttingRope(self, n: int) -> int:
"""offer 14-I 剪绳子 绳子优先距离：3>2>1"""
<|body_0|>
def cuttingRope1(self, n: int) -> int:
"""动态规划 转移方程：dp[i] = max(dp[i],max(j*(i-j),j*dp[i-j]) dp存放结果，绳长i剪j剩下i-j"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def cuttingRope(self, n: int) -> int:
"""offer 14-I 剪绳子 绳子优先距离：3>2>1"""
if n <= 3:
return n - 1
a, b = (n // 3, n % 3)
if b == 1:
return 3 ** (a - 1) * 4
elif b == 2:
return 3 ** a * b
else:
return 3 ** a... | the_stack_v2_python_sparse | Offer/14_cuttingRope.py | helloprogram6/leetcode_Cookbook_python | train | 0 | |
ca0fe48d0190032d9ce9eae85a31bee848ca21b1 | [
"assert onehot_name in ['A_cat', 'A_hour', 'A_his', 'B_cat', 'B_cat_xgb', 'A_cat_xgb', 'A_hour_xgb', 'A_his_xgb'], 'onehot name error'\nprint(X_train.shape, ' , ', y_train.shape)\nif data_begin != 'all':\n data_begin = 'begin{0}'.format(data_begin)\nss.save_npz(output_path + '{0}_X_{1}_{2}'.format(file_name, one... | <|body_start_0|>
assert onehot_name in ['A_cat', 'A_hour', 'A_his', 'B_cat', 'B_cat_xgb', 'A_cat_xgb', 'A_hour_xgb', 'A_his_xgb'], 'onehot name error'
print(X_train.shape, ' , ', y_train.shape)
if data_begin != 'all':
data_begin = 'begin{0}'.format(data_begin)
ss.save_npz(out... | ss.npz小工具 | NpzUtils | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NpzUtils:
"""ss.npz小工具"""
def SaveNpz(self, X_train, y_train, output_path, file_name, data_begin, onehot_name):
"""保存稀疏矩阵"""
<|body_0|>
def LoadNpz(self, data_path, file_name, data_begin, onehot_name):
"""导入稀疏矩阵"""
<|body_1|>
def MergeNpz(self, outpu... | stack_v2_sparse_classes_36k_train_034705 | 20,177 | no_license | [
{
"docstring": "保存稀疏矩阵",
"name": "SaveNpz",
"signature": "def SaveNpz(self, X_train, y_train, output_path, file_name, data_begin, onehot_name)"
},
{
"docstring": "导入稀疏矩阵",
"name": "LoadNpz",
"signature": "def LoadNpz(self, data_path, file_name, data_begin, onehot_name)"
},
{
"doc... | 3 | stack_v2_sparse_classes_30k_val_001112 | Implement the Python class `NpzUtils` described below.
Class description:
ss.npz小工具
Method signatures and docstrings:
- def SaveNpz(self, X_train, y_train, output_path, file_name, data_begin, onehot_name): 保存稀疏矩阵
- def LoadNpz(self, data_path, file_name, data_begin, onehot_name): 导入稀疏矩阵
- def MergeNpz(self, output_pa... | Implement the Python class `NpzUtils` described below.
Class description:
ss.npz小工具
Method signatures and docstrings:
- def SaveNpz(self, X_train, y_train, output_path, file_name, data_begin, onehot_name): 保存稀疏矩阵
- def LoadNpz(self, data_path, file_name, data_begin, onehot_name): 导入稀疏矩阵
- def MergeNpz(self, output_pa... | 9b4abb6fe3eae6c54a0c7076755519f910e53ca6 | <|skeleton|>
class NpzUtils:
"""ss.npz小工具"""
def SaveNpz(self, X_train, y_train, output_path, file_name, data_begin, onehot_name):
"""保存稀疏矩阵"""
<|body_0|>
def LoadNpz(self, data_path, file_name, data_begin, onehot_name):
"""导入稀疏矩阵"""
<|body_1|>
def MergeNpz(self, outpu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NpzUtils:
"""ss.npz小工具"""
def SaveNpz(self, X_train, y_train, output_path, file_name, data_begin, onehot_name):
"""保存稀疏矩阵"""
assert onehot_name in ['A_cat', 'A_hour', 'A_his', 'B_cat', 'B_cat_xgb', 'A_cat_xgb', 'A_hour_xgb', 'A_his_xgb'], 'onehot name error'
print(X_train.shape, '... | the_stack_v2_python_sparse | utils.py | zhouzhiqi/avazu_CTR | train | 5 |
53b2f554872c64a8281ecbc67c258810da5c46f7 | [
"pygame.sprite.Sprite.__init__(self)\nself.screen = screenParam\nself.image = pygame.image.load('../res/images/blood/blood06.png')\nself.tranColor = self.image.get_at((1, 1))\nself.image.set_colorkey(self.tranColor)\nself.rect = self.image.get_rect()\nself.imagePath = '../res/images/blood/blood0'\nself.imageList = ... | <|body_start_0|>
pygame.sprite.Sprite.__init__(self)
self.screen = screenParam
self.image = pygame.image.load('../res/images/blood/blood06.png')
self.tranColor = self.image.get_at((1, 1))
self.image.set_colorkey(self.tranColor)
self.rect = self.image.get_rect()
se... | Blood | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Blood:
def __init__(self, screenParam, x, y):
"""Initialize variables. @param screenParam: The surface to draw the resources onto."""
<|body_0|>
def update(self):
"""Update object. Invoked each tick."""
<|body_1|>
def loadPics(self):
"""Load all ... | stack_v2_sparse_classes_36k_train_034706 | 1,546 | permissive | [
{
"docstring": "Initialize variables. @param screenParam: The surface to draw the resources onto.",
"name": "__init__",
"signature": "def __init__(self, screenParam, x, y)"
},
{
"docstring": "Update object. Invoked each tick.",
"name": "update",
"signature": "def update(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_007486 | Implement the Python class `Blood` described below.
Class description:
Implement the Blood class.
Method signatures and docstrings:
- def __init__(self, screenParam, x, y): Initialize variables. @param screenParam: The surface to draw the resources onto.
- def update(self): Update object. Invoked each tick.
- def loa... | Implement the Python class `Blood` described below.
Class description:
Implement the Blood class.
Method signatures and docstrings:
- def __init__(self, screenParam, x, y): Initialize variables. @param screenParam: The surface to draw the resources onto.
- def update(self): Update object. Invoked each tick.
- def loa... | c59bc7e74c8e66044c7454f606b836797d88fdab | <|skeleton|>
class Blood:
def __init__(self, screenParam, x, y):
"""Initialize variables. @param screenParam: The surface to draw the resources onto."""
<|body_0|>
def update(self):
"""Update object. Invoked each tick."""
<|body_1|>
def loadPics(self):
"""Load all ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Blood:
def __init__(self, screenParam, x, y):
"""Initialize variables. @param screenParam: The surface to draw the resources onto."""
pygame.sprite.Sprite.__init__(self)
self.screen = screenParam
self.image = pygame.image.load('../res/images/blood/blood06.png')
self.tra... | the_stack_v2_python_sparse | src/Blood.py | RichardFlanagan/SonusOculi | train | 0 | |
16324b3148081cd2f78ada89def01d512a8da70e | [
"if sum(nums) == len(nums) // 2 and len(nums) % 2 == 0:\n return len(nums)\nself.dicts = {}\nsum_1 = 0\ncount = 1\nself.dicts[0] = [0, -1]\nfor i in nums:\n if i == 0:\n sum_1 -= 1\n else:\n sum_1 += 1\n if sum_1 not in self.dicts.keys():\n self.dicts[sum_1] = [count, -1]\n else:... | <|body_start_0|>
if sum(nums) == len(nums) // 2 and len(nums) % 2 == 0:
return len(nums)
self.dicts = {}
sum_1 = 0
count = 1
self.dicts[0] = [0, -1]
for i in nums:
if i == 0:
sum_1 -= 1
else:
sum_1 += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaxLength(self, nums):
""":type nums: List[int] :rtype: int 1862ms"""
<|body_0|>
def findMaxLength_1(self, nums):
"""315ms :param nums: :return:"""
<|body_1|>
def findMaxLength_2(self, nums):
""":type nums: List[int] :rtype: int... | stack_v2_sparse_classes_36k_train_034707 | 2,531 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int 1862ms",
"name": "findMaxLength",
"signature": "def findMaxLength(self, nums)"
},
{
"docstring": "315ms :param nums: :return:",
"name": "findMaxLength_1",
"signature": "def findMaxLength_1(self, nums)"
},
{
"docstring": ":type num... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxLength(self, nums): :type nums: List[int] :rtype: int 1862ms
- def findMaxLength_1(self, nums): 315ms :param nums: :return:
- def findMaxLength_2(self, nums): :type nu... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxLength(self, nums): :type nums: List[int] :rtype: int 1862ms
- def findMaxLength_1(self, nums): 315ms :param nums: :return:
- def findMaxLength_2(self, nums): :type nu... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def findMaxLength(self, nums):
""":type nums: List[int] :rtype: int 1862ms"""
<|body_0|>
def findMaxLength_1(self, nums):
"""315ms :param nums: :return:"""
<|body_1|>
def findMaxLength_2(self, nums):
""":type nums: List[int] :rtype: int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMaxLength(self, nums):
""":type nums: List[int] :rtype: int 1862ms"""
if sum(nums) == len(nums) // 2 and len(nums) % 2 == 0:
return len(nums)
self.dicts = {}
sum_1 = 0
count = 1
self.dicts[0] = [0, -1]
for i in nums:
... | the_stack_v2_python_sparse | ContiguousArray_MID_525.py | 953250587/leetcode-python | train | 2 | |
91a5687d4c4396e68d100be19e5339ffe3d70d6f | [
"id = str(id)\nconfig = dict(self.config[id])\nwidget_class = get_widget_class(config.pop('class'))\nreturn widget_class(id=id, **config)",
"widgets = []\nfor grid_item in self.layout:\n widget = self.get_widget(grid_item['id'])\n widget.set_layout(grid_item)\n widgets.append(widget)\nreturn widgets",
... | <|body_start_0|>
id = str(id)
config = dict(self.config[id])
widget_class = get_widget_class(config.pop('class'))
return widget_class(id=id, **config)
<|end_body_0|>
<|body_start_1|>
widgets = []
for grid_item in self.layout:
widget = self.get_widget(grid_ite... | Dashboard | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dashboard:
def get_widget(self, id):
"""Instantiate and return a widget by its ID"""
<|body_0|>
def get_layout(self):
"""Return the dashboard's configured layout, suitable for rendering with gridstack.js."""
<|body_1|>
def add_widget(self, widget, x=None... | stack_v2_sparse_classes_36k_train_034708 | 1,918 | permissive | [
{
"docstring": "Instantiate and return a widget by its ID",
"name": "get_widget",
"signature": "def get_widget(self, id)"
},
{
"docstring": "Return the dashboard's configured layout, suitable for rendering with gridstack.js.",
"name": "get_layout",
"signature": "def get_layout(self)"
}... | 4 | null | Implement the Python class `Dashboard` described below.
Class description:
Implement the Dashboard class.
Method signatures and docstrings:
- def get_widget(self, id): Instantiate and return a widget by its ID
- def get_layout(self): Return the dashboard's configured layout, suitable for rendering with gridstack.js.
... | Implement the Python class `Dashboard` described below.
Class description:
Implement the Dashboard class.
Method signatures and docstrings:
- def get_widget(self, id): Instantiate and return a widget by its ID
- def get_layout(self): Return the dashboard's configured layout, suitable for rendering with gridstack.js.
... | 506884bc4dc70299db3e2a7ad577dd7fd808065e | <|skeleton|>
class Dashboard:
def get_widget(self, id):
"""Instantiate and return a widget by its ID"""
<|body_0|>
def get_layout(self):
"""Return the dashboard's configured layout, suitable for rendering with gridstack.js."""
<|body_1|>
def add_widget(self, widget, x=None... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dashboard:
def get_widget(self, id):
"""Instantiate and return a widget by its ID"""
id = str(id)
config = dict(self.config[id])
widget_class = get_widget_class(config.pop('class'))
return widget_class(id=id, **config)
def get_layout(self):
"""Return the da... | the_stack_v2_python_sparse | netbox/extras/models/dashboard.py | netbox-community/netbox | train | 8,122 | |
863a1e173e008b1447b4f4667388beaa1206113b | [
"token = request.query_params.get('apptoken')\nif token:\n return self.authenticate_credentials(token)\nreturn super().authenticate(request)",
"model = AppToken\ntry:\n token = model.objects.get(key=key)\nexcept model.DoesNotExist:\n raise exceptions.AuthenticationFailed('Invalid token.')\nif not token.a... | <|body_start_0|>
token = request.query_params.get('apptoken')
if token:
return self.authenticate_credentials(token)
return super().authenticate(request)
<|end_body_0|>
<|body_start_1|>
model = AppToken
try:
token = model.objects.get(key=key)
excep... | Similar to Token, but users AppToken as model (belongs to apps not users) and accepts url param token One App <>> Many Tokens | AppTokenAuthentication | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AppTokenAuthentication:
"""Similar to Token, but users AppToken as model (belongs to apps not users) and accepts url param token One App <>> Many Tokens"""
def authenticate(self, request):
"""Override TokenAuthentication.authenticate to support url query param"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_034709 | 1,468 | permissive | [
{
"docstring": "Override TokenAuthentication.authenticate to support url query param",
"name": "authenticate",
"signature": "def authenticate(self, request)"
},
{
"docstring": "Override TokenAuthentication.authenticate to support url query param",
"name": "authenticate_credentials",
"sig... | 2 | stack_v2_sparse_classes_30k_train_020539 | Implement the Python class `AppTokenAuthentication` described below.
Class description:
Similar to Token, but users AppToken as model (belongs to apps not users) and accepts url param token One App <>> Many Tokens
Method signatures and docstrings:
- def authenticate(self, request): Override TokenAuthentication.authen... | Implement the Python class `AppTokenAuthentication` described below.
Class description:
Similar to Token, but users AppToken as model (belongs to apps not users) and accepts url param token One App <>> Many Tokens
Method signatures and docstrings:
- def authenticate(self, request): Override TokenAuthentication.authen... | 3533b3558f3f247672840b2c2c33d6ffd71d2517 | <|skeleton|>
class AppTokenAuthentication:
"""Similar to Token, but users AppToken as model (belongs to apps not users) and accepts url param token One App <>> Many Tokens"""
def authenticate(self, request):
"""Override TokenAuthentication.authenticate to support url query param"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AppTokenAuthentication:
"""Similar to Token, but users AppToken as model (belongs to apps not users) and accepts url param token One App <>> Many Tokens"""
def authenticate(self, request):
"""Override TokenAuthentication.authenticate to support url query param"""
token = request.query_par... | the_stack_v2_python_sparse | backend/recordbin/authentication.py | recordbinco/recordbin-api | train | 0 |
a29f067e6153c1fa2643583f70c2567c597ea6ff | [
"self.npart = npart\nself.ndim = ndim\nself.bounds = bounds",
"self.swarm = np.zeros((self.npart, self.ndim))\nif self.bounds == None:\n lo = np.zeros(self.ndim)\n hi = np.ones(self.ndim)\nelse:\n lo = self.bounds.Lower()\n hi = self.bounds.Upper()\nradius = 0.5\nfor i in range(self.npart):\n p = n... | <|body_start_0|>
self.npart = npart
self.ndim = ndim
self.bounds = bounds
<|end_body_0|>
<|body_start_1|>
self.swarm = np.zeros((self.npart, self.ndim))
if self.bounds == None:
lo = np.zeros(self.ndim)
hi = np.ones(self.ndim)
else:
lo ... | Initialize a swarm on a hypersphere | SphereInitializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SphereInitializer:
"""Initialize a swarm on a hypersphere"""
def __init__(self, npart=10, ndim=3, bounds=None):
"""Constructor"""
<|body_0|>
def InitializeSwarm(self):
"""Return a quasirandomly initialized swarm"""
<|body_1|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_034710 | 1,562 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, npart=10, ndim=3, bounds=None)"
},
{
"docstring": "Return a quasirandomly initialized swarm",
"name": "InitializeSwarm",
"signature": "def InitializeSwarm(self)"
}
] | 2 | null | Implement the Python class `SphereInitializer` described below.
Class description:
Initialize a swarm on a hypersphere
Method signatures and docstrings:
- def __init__(self, npart=10, ndim=3, bounds=None): Constructor
- def InitializeSwarm(self): Return a quasirandomly initialized swarm | Implement the Python class `SphereInitializer` described below.
Class description:
Initialize a swarm on a hypersphere
Method signatures and docstrings:
- def __init__(self, npart=10, ndim=3, bounds=None): Constructor
- def InitializeSwarm(self): Return a quasirandomly initialized swarm
<|skeleton|>
class SphereInit... | 5445b6f90ab49339ca0fdb71e98d44e6827c95a8 | <|skeleton|>
class SphereInitializer:
"""Initialize a swarm on a hypersphere"""
def __init__(self, npart=10, ndim=3, bounds=None):
"""Constructor"""
<|body_0|>
def InitializeSwarm(self):
"""Return a quasirandomly initialized swarm"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SphereInitializer:
"""Initialize a swarm on a hypersphere"""
def __init__(self, npart=10, ndim=3, bounds=None):
"""Constructor"""
self.npart = npart
self.ndim = ndim
self.bounds = bounds
def InitializeSwarm(self):
"""Return a quasirandomly initialized swarm"""... | the_stack_v2_python_sparse | SphereInitializer.py | dayoladejo/SwarmOptimization | train | 0 |
8f7a2eedee630850b9f83fe1124899ef58e70d9d | [
"self.validate_parameters(language_set_id=language_set_id)\n_query_builder = Configuration.get_base_uri()\n_query_builder += '/text/language-sets/{languageSetId}/translations'\n_query_builder = APIHelper.append_url_with_template_parameters(_query_builder, {'languageSetId': language_set_id})\n_query_parameters = {'l... | <|body_start_0|>
self.validate_parameters(language_set_id=language_set_id)
_query_builder = Configuration.get_base_uri()
_query_builder += '/text/language-sets/{languageSetId}/translations'
_query_builder = APIHelper.append_url_with_template_parameters(_query_builder, {'languageSetId': l... | A Controller to access Endpoints in the idfy_rest_client API. | TranslationsController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TranslationsController:
"""A Controller to access Endpoints in the idfy_rest_client API."""
def list_translations(self, language_set_id, language=None, format=None):
"""Does a GET request to /text/language-sets/{languageSetId}/translations. Returns a list of all your translations for... | stack_v2_sparse_classes_36k_train_034711 | 6,361 | permissive | [
{
"docstring": "Does a GET request to /text/language-sets/{languageSetId}/translations. Returns a list of all your translations for the given language set. Args: language_set_id (int): TODO: type description here. Example: language (string, optional): TODO: type description here. Example: format (Format, option... | 3 | null | Implement the Python class `TranslationsController` described below.
Class description:
A Controller to access Endpoints in the idfy_rest_client API.
Method signatures and docstrings:
- def list_translations(self, language_set_id, language=None, format=None): Does a GET request to /text/language-sets/{languageSetId}/... | Implement the Python class `TranslationsController` described below.
Class description:
A Controller to access Endpoints in the idfy_rest_client API.
Method signatures and docstrings:
- def list_translations(self, language_set_id, language=None, format=None): Does a GET request to /text/language-sets/{languageSetId}/... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class TranslationsController:
"""A Controller to access Endpoints in the idfy_rest_client API."""
def list_translations(self, language_set_id, language=None, format=None):
"""Does a GET request to /text/language-sets/{languageSetId}/translations. Returns a list of all your translations for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TranslationsController:
"""A Controller to access Endpoints in the idfy_rest_client API."""
def list_translations(self, language_set_id, language=None, format=None):
"""Does a GET request to /text/language-sets/{languageSetId}/translations. Returns a list of all your translations for the given la... | the_stack_v2_python_sparse | idfy_rest_client/controllers/translations_controller.py | dealflowteam/Idfy | train | 0 |
6718f31ac4f3a60952497035881addfe049e3a4b | [
"self.text = text.split(LINESEP)\nself.screen = screen\nself.drawCursor = drawCursor\nif settings.textSpeed == 'SLOW':\n self.speed = 1\nelif settings.textSpeed == 'MEDIUM':\n self.speed = 2\nelif settings.textSpeed == 'FAST':\n self.speed = 4\nfn = os.path.join(settings.path, 'data', globs.DIALOG)\nroot =... | <|body_start_0|>
self.text = text.split(LINESEP)
self.screen = screen
self.drawCursor = drawCursor
if settings.textSpeed == 'SLOW':
self.speed = 1
elif settings.textSpeed == 'MEDIUM':
self.speed = 2
elif settings.textSpeed == 'FAST':
se... | Class to provide dialogs to be shown by the script engine. | Dialog | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dialog:
"""Class to provide dialogs to be shown by the script engine."""
def __init__(self, text, screen, drawCursor=True):
"""Create the dialog box and load cursors. text - a list of lines of text to go in the dialog. font - the font with which to write the text. screen - the surfac... | stack_v2_sparse_classes_36k_train_034712 | 7,526 | no_license | [
{
"docstring": "Create the dialog box and load cursors. text - a list of lines of text to go in the dialog. font - the font with which to write the text. screen - the surface to draw the dialog onto. soundManager - the sound manager. drawCursor - whether a continuation cursor should be drawn when the text has f... | 4 | stack_v2_sparse_classes_30k_train_017193 | Implement the Python class `Dialog` described below.
Class description:
Class to provide dialogs to be shown by the script engine.
Method signatures and docstrings:
- def __init__(self, text, screen, drawCursor=True): Create the dialog box and load cursors. text - a list of lines of text to go in the dialog. font - t... | Implement the Python class `Dialog` described below.
Class description:
Class to provide dialogs to be shown by the script engine.
Method signatures and docstrings:
- def __init__(self, text, screen, drawCursor=True): Create the dialog box and load cursors. text - a list of lines of text to go in the dialog. font - t... | 35f58b9c931bd2bef7fd2002cadd468523ffbb5d | <|skeleton|>
class Dialog:
"""Class to provide dialogs to be shown by the script engine."""
def __init__(self, text, screen, drawCursor=True):
"""Create the dialog box and load cursors. text - a list of lines of text to go in the dialog. font - the font with which to write the text. screen - the surfac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dialog:
"""Class to provide dialogs to be shown by the script engine."""
def __init__(self, text, screen, drawCursor=True):
"""Create the dialog box and load cursors. text - a list of lines of text to go in the dialog. font - the font with which to write the text. screen - the surface to draw the... | the_stack_v2_python_sparse | dialog.py | wollywatson/DittoEngine | train | 0 |
82fcd049c2303a904e4123d3d02a5c885f1d019e | [
"self.capacity = capacity\nself.cache = {}\nself.rank_queue = []",
"if key not in self.cache:\n return -1\nif key in self.rank_queue:\n self.rank_queue.remove(key)\nself.rank_queue.append(key)\nreturn self.cache[key]",
"if key not in self.cache and len(self.cache) == self.capacity:\n del self.cache[sel... | <|body_start_0|>
self.capacity = capacity
self.cache = {}
self.rank_queue = []
<|end_body_0|>
<|body_start_1|>
if key not in self.cache:
return -1
if key in self.rank_queue:
self.rank_queue.remove(key)
self.rank_queue.append(key)
return 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_034713 | 1,213 | 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 | stack_v2_sparse_classes_30k_train_007468 | 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... | 2711bc08f15266bec4ca135e8e3e629df46713eb | <|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 = {}
self.rank_queue = []
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.cache:
return -1
if key in self.rank_... | the_stack_v2_python_sparse | 0.算法/146_LRU_cache.py | unlimitediw/CheckCode | train | 0 | |
3fa0ad2a6a34d4ff79a9fa8be342d08b705e3f01 | [
"self.smartplug = smartplug\nself.state = None\nself.temperature = None\nself.current_consumption = None\nself.total_consumption = None\nself.available = False\nself._n_tried = 0\nself._last_tried = None",
"if self._last_tried is not None:\n last_try_s = (dt_util.now() - self._last_tried).total_seconds() / 60\... | <|body_start_0|>
self.smartplug = smartplug
self.state = None
self.temperature = None
self.current_consumption = None
self.total_consumption = None
self.available = False
self._n_tried = 0
self._last_tried = None
<|end_body_0|>
<|body_start_1|>
if... | Get the latest data from smart plug. | SmartPlugData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmartPlugData:
"""Get the latest data from smart plug."""
def __init__(self, smartplug):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Get the latest data from the smart plug."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_36k_train_034714 | 4,947 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, smartplug)"
},
{
"docstring": "Get the latest data from the smart plug.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | null | Implement the Python class `SmartPlugData` described below.
Class description:
Get the latest data from smart plug.
Method signatures and docstrings:
- def __init__(self, smartplug): Initialize the data object.
- def update(self): Get the latest data from the smart plug. | Implement the Python class `SmartPlugData` described below.
Class description:
Get the latest data from smart plug.
Method signatures and docstrings:
- def __init__(self, smartplug): Initialize the data object.
- def update(self): Get the latest data from the smart plug.
<|skeleton|>
class SmartPlugData:
"""Get ... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class SmartPlugData:
"""Get the latest data from smart plug."""
def __init__(self, smartplug):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Get the latest data from the smart plug."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SmartPlugData:
"""Get the latest data from smart plug."""
def __init__(self, smartplug):
"""Initialize the data object."""
self.smartplug = smartplug
self.state = None
self.temperature = None
self.current_consumption = None
self.total_consumption = None
... | the_stack_v2_python_sparse | homeassistant/components/dlink/switch.py | BenWoodford/home-assistant | train | 11 |
79f1f9403e408b557a41330ebb7d2d08d8b3f800 | [
"try:\n self.assertEqual(subtract(30, 16), 15)\nexcept Exception as error:\n print(f'Got error in {inspect.stack()[0][3]}, {error}')",
"try:\n self.assertEqual(subtract(-18, -5), -13)\nexcept Exception as error:\n print(error)",
"try:\n self.assertEqual(subtract(0, -6), 7)\nexcept Exception as er... | <|body_start_0|>
try:
self.assertEqual(subtract(30, 16), 15)
except Exception as error:
print(f'Got error in {inspect.stack()[0][3]}, {error}')
<|end_body_0|>
<|body_start_1|>
try:
self.assertEqual(subtract(-18, -5), -13)
except Exception as error:
... | Test subtract function from calculation.py module. | TestSubtractFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSubtractFunction:
"""Test subtract function from calculation.py module."""
def test_subtract_all_args_greater_zero(self):
"""Test subtract function if all arguments are greater than zero."""
<|body_0|>
def test_subtract_all_args_less_zero(self):
"""Test subtr... | stack_v2_sparse_classes_36k_train_034715 | 1,838 | no_license | [
{
"docstring": "Test subtract function if all arguments are greater than zero.",
"name": "test_subtract_all_args_greater_zero",
"signature": "def test_subtract_all_args_greater_zero(self)"
},
{
"docstring": "Test subtract function if all arguments are less than zero.",
"name": "test_subtract... | 3 | stack_v2_sparse_classes_30k_train_012915 | Implement the Python class `TestSubtractFunction` described below.
Class description:
Test subtract function from calculation.py module.
Method signatures and docstrings:
- def test_subtract_all_args_greater_zero(self): Test subtract function if all arguments are greater than zero.
- def test_subtract_all_args_less_z... | Implement the Python class `TestSubtractFunction` described below.
Class description:
Test subtract function from calculation.py module.
Method signatures and docstrings:
- def test_subtract_all_args_greater_zero(self): Test subtract function if all arguments are greater than zero.
- def test_subtract_all_args_less_z... | 3a500c9d55fecf4032b5faf59a1cbecf64592e9a | <|skeleton|>
class TestSubtractFunction:
"""Test subtract function from calculation.py module."""
def test_subtract_all_args_greater_zero(self):
"""Test subtract function if all arguments are greater than zero."""
<|body_0|>
def test_subtract_all_args_less_zero(self):
"""Test subtr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSubtractFunction:
"""Test subtract function from calculation.py module."""
def test_subtract_all_args_greater_zero(self):
"""Test subtract function if all arguments are greater than zero."""
try:
self.assertEqual(subtract(30, 16), 15)
except Exception as error:
... | the_stack_v2_python_sparse | python10/test_calculation.py | maksimok93/Dp-189 | train | 0 |
3a14029ec4b6b63ca761985e8e6950028285728d | [
"if target == 0:\n res.append(tem_res)\n return\nif index >= len(candidates) or target < candidates[index]:\n return\nfor i in range(index, len(candidates)):\n if i > index and candidates[i] == candidates[i - 1]:\n continue\n if target < candidates[i]:\n break\n self.curSum(self, can... | <|body_start_0|>
if target == 0:
res.append(tem_res)
return
if index >= len(candidates) or target < candidates[index]:
return
for i in range(index, len(candidates)):
if i > index and candidates[i] == candidates[i - 1]:
continue
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: ... | stack_v2_sparse_classes_36k_train_034716 | 1,196 | no_license | [
{
"docstring": ":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果",
"name": "curSum",
"signature": "def curSum(self, candidates, index, target, tem_res, res)"
},
{
"docstring": ":type candidates: List[int] :type target: int :rtype: List[List[int]] :组合相加",
... | 2 | stack_v2_sparse_classes_30k_train_021363 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def curSum(self, candidates, index, target, tem_res, res): :param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果
- def combinationSum(self, ca... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def curSum(self, candidates, index, target, tem_res, res): :param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果
- def combinationSum(self, ca... | 45fafcc5dd8f3a9dd26984dc6e82441cc2e8f8d7 | <|skeleton|>
class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
if target == 0:
res.append(tem_res)
return
if index >= len(candidates) or target < candidates[ind... | the_stack_v2_python_sparse | T40.py | zhanggyang/leedcode | train | 0 | |
79ea8c9f796521822e835e9fde4c46269a4d2098 | [
"self.allow_api_based_fetch = allow_api_based_fetch\nself.cluster_destroy_hmac_key = cluster_destroy_hmac_key\nself.cluster_name = cluster_name\nself.enable_cluster_destroy = enable_cluster_destroy\nself.encryption_config = encryption_config\nself.ip_preference = ip_preference\nself.ipmi_config = ipmi_config\nself.... | <|body_start_0|>
self.allow_api_based_fetch = allow_api_based_fetch
self.cluster_destroy_hmac_key = cluster_destroy_hmac_key
self.cluster_name = cluster_name
self.enable_cluster_destroy = enable_cluster_destroy
self.encryption_config = encryption_config
self.ip_preference... | Implementation of the 'CreatePhysicalClusterParameters' model. Specifies the parameters needed for creation of a new Cluster. Attributes: allow_api_based_fetch (bool): Specifies if API based GET should be enabled for cluster destroy params. cluster_destroy_hmac_key (string): Specifies HMAC secret key that will be used ... | CreatePhysicalClusterParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreatePhysicalClusterParameters:
"""Implementation of the 'CreatePhysicalClusterParameters' model. Specifies the parameters needed for creation of a new Cluster. Attributes: allow_api_based_fetch (bool): Specifies if API based GET should be enabled for cluster destroy params. cluster_destroy_hmac... | stack_v2_sparse_classes_36k_train_034717 | 5,957 | permissive | [
{
"docstring": "Constructor for the CreatePhysicalClusterParameters class",
"name": "__init__",
"signature": "def __init__(self, allow_api_based_fetch=None, cluster_destroy_hmac_key=None, cluster_name=None, enable_cluster_destroy=None, encryption_config=None, ip_preference=None, ipmi_config=None, metada... | 2 | stack_v2_sparse_classes_30k_test_001078 | Implement the Python class `CreatePhysicalClusterParameters` described below.
Class description:
Implementation of the 'CreatePhysicalClusterParameters' model. Specifies the parameters needed for creation of a new Cluster. Attributes: allow_api_based_fetch (bool): Specifies if API based GET should be enabled for clust... | Implement the Python class `CreatePhysicalClusterParameters` described below.
Class description:
Implementation of the 'CreatePhysicalClusterParameters' model. Specifies the parameters needed for creation of a new Cluster. Attributes: allow_api_based_fetch (bool): Specifies if API based GET should be enabled for clust... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CreatePhysicalClusterParameters:
"""Implementation of the 'CreatePhysicalClusterParameters' model. Specifies the parameters needed for creation of a new Cluster. Attributes: allow_api_based_fetch (bool): Specifies if API based GET should be enabled for cluster destroy params. cluster_destroy_hmac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreatePhysicalClusterParameters:
"""Implementation of the 'CreatePhysicalClusterParameters' model. Specifies the parameters needed for creation of a new Cluster. Attributes: allow_api_based_fetch (bool): Specifies if API based GET should be enabled for cluster destroy params. cluster_destroy_hmac_key (string)... | the_stack_v2_python_sparse | cohesity_management_sdk/models/create_physical_cluster_parameters.py | cohesity/management-sdk-python | train | 24 |
221af954ec827e037fdab8c1c32d0d14bcb7daeb | [
"if self == other:\n return self\nelif type(self) == type(other):\n return type(self)(self.vars | other.vars)\nelif isinstance(other, SymbolicSubringRejectingVarsFunctor):\n if not self.vars & other.vars:\n return other",
"if R is not SR:\n raise NotImplementedError('This functor can only be ap... | <|body_start_0|>
if self == other:
return self
elif type(self) == type(other):
return type(self)(self.vars | other.vars)
elif isinstance(other, SymbolicSubringRejectingVarsFunctor):
if not self.vars & other.vars:
return other
<|end_body_0|>
<|... | SymbolicSubringAcceptingVarsFunctor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SymbolicSubringAcceptingVarsFunctor:
def merge(self, other):
"""Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or ``None``. EXAMPLES:: sage: from sage.symbolic.subring import SymbolicSubring sage: F = SymbolicSubring(accepting_variables=... | stack_v2_sparse_classes_36k_train_034718 | 31,870 | no_license | [
{
"docstring": "Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or ``None``. EXAMPLES:: sage: from sage.symbolic.subring import SymbolicSubring sage: F = SymbolicSubring(accepting_variables=('a',)).construction()[0] sage: G = SymbolicSubring(rejecting_variables=... | 2 | stack_v2_sparse_classes_30k_train_012252 | Implement the Python class `SymbolicSubringAcceptingVarsFunctor` described below.
Class description:
Implement the SymbolicSubringAcceptingVarsFunctor class.
Method signatures and docstrings:
- def merge(self, other): Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or... | Implement the Python class `SymbolicSubringAcceptingVarsFunctor` described below.
Class description:
Implement the SymbolicSubringAcceptingVarsFunctor class.
Method signatures and docstrings:
- def merge(self, other): Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class SymbolicSubringAcceptingVarsFunctor:
def merge(self, other):
"""Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or ``None``. EXAMPLES:: sage: from sage.symbolic.subring import SymbolicSubring sage: F = SymbolicSubring(accepting_variables=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SymbolicSubringAcceptingVarsFunctor:
def merge(self, other):
"""Merge this functor with ``other`` if possible. INPUT: - ``other`` -- a functor. OUTPUT: A functor or ``None``. EXAMPLES:: sage: from sage.symbolic.subring import SymbolicSubring sage: F = SymbolicSubring(accepting_variables=('a',)).constr... | the_stack_v2_python_sparse | sage/src/sage/symbolic/subring.py | bopopescu/geosci | train | 0 | |
b1a5bd9393e2be2a7e542bebf2c293c15f089ab9 | [
"CNP = str(CNP)\nif len(CNP) != 13:\n return False\nif CNP[0] != '1' and CNP[0] != '2':\n return False\nyear = int(CNP[1]) * 10 + int(CNP[2])\nif year > 99:\n return False\nmouth = int(CNP[3]) * 10 + int(CNP[4])\nif mouth > 12:\n return False\nday = int(CNP[5]) * 10 + int(CNP[6])\nif day > 31:\n retu... | <|body_start_0|>
CNP = str(CNP)
if len(CNP) != 13:
return False
if CNP[0] != '1' and CNP[0] != '2':
return False
year = int(CNP[1]) * 10 + int(CNP[2])
if year > 99:
return False
mouth = int(CNP[3]) * 10 + int(CNP[4])
if mouth > ... | ClientValidator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClientValidator:
def validateCNP(CNP):
"""Verify if the given ID is a valid one: -the first number must be 1 or 2 -the 2-3 digits must be the year of birth -the 4-5 digits the mouth -the 6-7 digits are the day -the 8-9 digits are the locality -the 10-12 digits are random -the 13 digit is... | stack_v2_sparse_classes_36k_train_034719 | 3,725 | no_license | [
{
"docstring": "Verify if the given ID is a valid one: -the first number must be 1 or 2 -the 2-3 digits must be the year of birth -the 4-5 digits the mouth -the 6-7 digits are the day -the 8-9 digits are the locality -the 10-12 digits are random -the 13 digit is the control one",
"name": "validateCNP",
... | 3 | stack_v2_sparse_classes_30k_train_006668 | Implement the Python class `ClientValidator` described below.
Class description:
Implement the ClientValidator class.
Method signatures and docstrings:
- def validateCNP(CNP): Verify if the given ID is a valid one: -the first number must be 1 or 2 -the 2-3 digits must be the year of birth -the 4-5 digits the mouth -t... | Implement the Python class `ClientValidator` described below.
Class description:
Implement the ClientValidator class.
Method signatures and docstrings:
- def validateCNP(CNP): Verify if the given ID is a valid one: -the first number must be 1 or 2 -the 2-3 digits must be the year of birth -the 4-5 digits the mouth -t... | b3950f4bc0d7a4d2f69d9c9c500e05e6092e8350 | <|skeleton|>
class ClientValidator:
def validateCNP(CNP):
"""Verify if the given ID is a valid one: -the first number must be 1 or 2 -the 2-3 digits must be the year of birth -the 4-5 digits the mouth -the 6-7 digits are the day -the 8-9 digits are the locality -the 10-12 digits are random -the 13 digit is... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClientValidator:
def validateCNP(CNP):
"""Verify if the given ID is a valid one: -the first number must be 1 or 2 -the 2-3 digits must be the year of birth -the 4-5 digits the mouth -the 6-7 digits are the day -the 8-9 digits are the locality -the 10-12 digits are random -the 13 digit is the control o... | the_stack_v2_python_sparse | Validator/ClientValidator.py | paul29m/FPMovieRental | train | 0 | |
edb13a0c4e93c6c72e628c4fde7ebcf111bff9c9 | [
"current_keys = essence.get('metadata', {}).get('annotations', {})\nif frozenset(keys_to_remove) & frozenset(current_keys):\n essence['metadata']['annotations'] = {key: val for key, val in essence.get('metadata', {}).get('annotations', {}).items() if key not in keys_to_remove}",
"if 'annotations' in essence.ge... | <|body_start_0|>
current_keys = essence.get('metadata', {}).get('annotations', {})
if frozenset(keys_to_remove) & frozenset(current_keys):
essence['metadata']['annotations'] = {key: val for key, val in essence.get('metadata', {}).get('annotations', {}).items() if key not in keys_to_remove}
<... | A mixin used internally to remove unwanted annotations and empty stanzas. | StorageStanzaCleaner | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StorageStanzaCleaner:
"""A mixin used internally to remove unwanted annotations and empty stanzas."""
def remove_annotations(essence: bodies.BodyEssence, keys_to_remove: Collection[str]) -> None:
"""Remove annotations (in-place)."""
<|body_0|>
def remove_empty_stanzas(es... | stack_v2_sparse_classes_36k_train_034720 | 13,196 | permissive | [
{
"docstring": "Remove annotations (in-place).",
"name": "remove_annotations",
"signature": "def remove_annotations(essence: bodies.BodyEssence, keys_to_remove: Collection[str]) -> None"
},
{
"docstring": "Remove (in-place) the parent structs/stanzas if they are empty.",
"name": "remove_empt... | 2 | stack_v2_sparse_classes_30k_train_004100 | Implement the Python class `StorageStanzaCleaner` described below.
Class description:
A mixin used internally to remove unwanted annotations and empty stanzas.
Method signatures and docstrings:
- def remove_annotations(essence: bodies.BodyEssence, keys_to_remove: Collection[str]) -> None: Remove annotations (in-place... | Implement the Python class `StorageStanzaCleaner` described below.
Class description:
A mixin used internally to remove unwanted annotations and empty stanzas.
Method signatures and docstrings:
- def remove_annotations(essence: bodies.BodyEssence, keys_to_remove: Collection[str]) -> None: Remove annotations (in-place... | 538df59b88d1aab7b985d703483497f73c6c4783 | <|skeleton|>
class StorageStanzaCleaner:
"""A mixin used internally to remove unwanted annotations and empty stanzas."""
def remove_annotations(essence: bodies.BodyEssence, keys_to_remove: Collection[str]) -> None:
"""Remove annotations (in-place)."""
<|body_0|>
def remove_empty_stanzas(es... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StorageStanzaCleaner:
"""A mixin used internally to remove unwanted annotations and empty stanzas."""
def remove_annotations(essence: bodies.BodyEssence, keys_to_remove: Collection[str]) -> None:
"""Remove annotations (in-place)."""
current_keys = essence.get('metadata', {}).get('annotati... | the_stack_v2_python_sparse | kopf/_cogs/configs/conventions.py | nolar/kopf | train | 1,627 |
1c0cc1bb98f5c0b5c05583975d459874cf8455b5 | [
"super(CombinedLoss, self).__init__()\nassert len(loss_modules) == len(loss_weights)\nself.loss_modules = loss_modules\nself.loss_weights = loss_weights",
"losses = self.loss_modules\nweights = self.loss_weights\nloss = losses[0](pred, target) * weights[0]\nfor i in range(1, len(losses)):\n loss = loss + losse... | <|body_start_0|>
super(CombinedLoss, self).__init__()
assert len(loss_modules) == len(loss_weights)
self.loss_modules = loss_modules
self.loss_weights = loss_weights
<|end_body_0|>
<|body_start_1|>
losses = self.loss_modules
weights = self.loss_weights
loss = los... | Loss module to compute weighted sum of the multiple losses. | CombinedLoss | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CombinedLoss:
"""Loss module to compute weighted sum of the multiple losses."""
def __init__(self, loss_modules, loss_weights):
"""Args: loss_modules (list[Module]): list of loss modules. loss_weights (list[float]): weight per each loss."""
<|body_0|>
def forward(self, p... | stack_v2_sparse_classes_36k_train_034721 | 3,995 | permissive | [
{
"docstring": "Args: loss_modules (list[Module]): list of loss modules. loss_weights (list[float]): weight per each loss.",
"name": "__init__",
"signature": "def __init__(self, loss_modules, loss_weights)"
},
{
"docstring": "Args: pred (Tensor): tensor with shape (N, C, H, W, D). target (Tensor... | 2 | stack_v2_sparse_classes_30k_train_018241 | Implement the Python class `CombinedLoss` described below.
Class description:
Loss module to compute weighted sum of the multiple losses.
Method signatures and docstrings:
- def __init__(self, loss_modules, loss_weights): Args: loss_modules (list[Module]): list of loss modules. loss_weights (list[float]): weight per ... | Implement the Python class `CombinedLoss` described below.
Class description:
Loss module to compute weighted sum of the multiple losses.
Method signatures and docstrings:
- def __init__(self, loss_modules, loss_weights): Args: loss_modules (list[Module]): list of loss modules. loss_weights (list[float]): weight per ... | 871a24eaad388b8da427e0ab3c95f951629e36d6 | <|skeleton|>
class CombinedLoss:
"""Loss module to compute weighted sum of the multiple losses."""
def __init__(self, loss_modules, loss_weights):
"""Args: loss_modules (list[Module]): list of loss modules. loss_weights (list[float]): weight per each loss."""
<|body_0|>
def forward(self, p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CombinedLoss:
"""Loss module to compute weighted sum of the multiple losses."""
def __init__(self, loss_modules, loss_weights):
"""Args: loss_modules (list[Module]): list of loss modules. loss_weights (list[float]): weight per each loss."""
super(CombinedLoss, self).__init__()
ass... | the_stack_v2_python_sparse | kits19_3d_segmentation/solvers/losses.py | rabbittuan/kits19_3d_segmentation | train | 0 |
2ab13633ed9ab7e66881f3a37c375bac3c180d64 | [
"scannable = len(configuration.get('url', []))\nif scannable is 0:\n return False\nscanned = 0\nif configuration.get('hour'):\n if datetime.datetime.utcnow().hour != int(configuration.get('hour')):\n return True\nif configuration.get('minute'):\n if datetime.datetime.utcnow().minute != int(configura... | <|body_start_0|>
scannable = len(configuration.get('url', []))
if scannable is 0:
return False
scanned = 0
if configuration.get('hour'):
if datetime.datetime.utcnow().hour != int(configuration.get('hour')):
return True
if configuration.get(... | Monitor URL's as a source of information This source is designed to provide source data on the URL's configured for a GREASE sourcing cluster. A generic configuration looks like this for a url_source:: { 'name': 'example_source', # <-- A name 'job': 'example_job', # <-- Any job you want to run 'exe_env': 'general', # <... | URLParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class URLParser:
"""Monitor URL's as a source of information This source is designed to provide source data on the URL's configured for a GREASE sourcing cluster. A generic configuration looks like this for a url_source:: { 'name': 'example_source', # <-- A name 'job': 'example_job', # <-- Any job you ... | stack_v2_sparse_classes_36k_train_034722 | 4,446 | permissive | [
{
"docstring": "This will make a GET request to all URL's in the list provided by your configuration Args: configuration (dict): Configuration of Source. See Class Documentation above for more info Returns: bool: If True data will be scheduled for ingestion after deduplication. If False the engine will bail out... | 2 | stack_v2_sparse_classes_30k_train_013486 | Implement the Python class `URLParser` described below.
Class description:
Monitor URL's as a source of information This source is designed to provide source data on the URL's configured for a GREASE sourcing cluster. A generic configuration looks like this for a url_source:: { 'name': 'example_source', # <-- A name '... | Implement the Python class `URLParser` described below.
Class description:
Monitor URL's as a source of information This source is designed to provide source data on the URL's configured for a GREASE sourcing cluster. A generic configuration looks like this for a url_source:: { 'name': 'example_source', # <-- A name '... | 7ebf3df71d5c80a8ed9df44d9b64b735a9d0f899 | <|skeleton|>
class URLParser:
"""Monitor URL's as a source of information This source is designed to provide source data on the URL's configured for a GREASE sourcing cluster. A generic configuration looks like this for a url_source:: { 'name': 'example_source', # <-- A name 'job': 'example_job', # <-- Any job you ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class URLParser:
"""Monitor URL's as a source of information This source is designed to provide source data on the URL's configured for a GREASE sourcing cluster. A generic configuration looks like this for a url_source:: { 'name': 'example_source', # <-- A name 'job': 'example_job', # <-- Any job you want to run '... | the_stack_v2_python_sparse | tgt_grease/enterprise/Sources/UrlParser.py | target/grease | train | 46 |
02d5c01c8b703afcc000002edd93305a52e1a84a | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ThreatIntelligence()",
"from ..entity import Entity\nfrom .article import Article\nfrom .article_indicator import ArticleIndicator\nfrom .host import Host\nfrom .host_component import HostComponent\nfrom .host_cookie import HostCookie\... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ThreatIntelligence()
<|end_body_0|>
<|body_start_1|>
from ..entity import Entity
from .article import Article
from .article_indicator import ArticleIndicator
from .host i... | ThreatIntelligence | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreatIntelligence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ThreatIntelligence:
"""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 obje... | stack_v2_sparse_classes_36k_train_034723 | 7,000 | 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: ThreatIntelligence",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_... | 3 | stack_v2_sparse_classes_30k_train_014076 | Implement the Python class `ThreatIntelligence` described below.
Class description:
Implement the ThreatIntelligence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ThreatIntelligence: Creates a new instance of the appropriate class based on disc... | Implement the Python class `ThreatIntelligence` described below.
Class description:
Implement the ThreatIntelligence class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ThreatIntelligence: Creates a new instance of the appropriate class based on disc... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ThreatIntelligence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ThreatIntelligence:
"""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 obje... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThreatIntelligence:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ThreatIntelligence:
"""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: Th... | the_stack_v2_python_sparse | msgraph/generated/models/security/threat_intelligence.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
937f48ab9de736cb316fc386c140bf686bcfdca5 | [
"torch.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, momentum=momentum)\ninplanes = init_conv_nplanes\nself.downsample = torch.nn.ModuleList([])\ns... | <|body_start_0|>
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 = ConvBNBlock(start_planes, init_conv_nplanes, init_conv_kernel, momentum=momentum)
inplanes = init_con... | This class implements a net structure built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the ResNet. ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. inplanes : int Number of planes we want after the ini... | ResNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResNet:
"""This class implements a net structure built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the ResNet. ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. inplanes : int Numb... | stack_v2_sparse_classes_36k_train_034724 | 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_000291 | Implement the Python class `ResNet` described below.
Class description:
This class implements a net structure built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the ResNet. ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is ... | Implement the Python class `ResNet` described below.
Class description:
This class implements a net structure built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the ResNet. ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is ... | 4c2cf181c6f503bf2a9c09bbe16810e727b052e7 | <|skeleton|>
class ResNet:
"""This class implements a net structure built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the ResNet. ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. inplanes : int Numb... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResNet:
"""This class implements a net structure built with ResNet blocks. It takes a tuple of (coordinates, features) and passes it through the ResNet. ... Attributes ---------- spatial_size : tuple The spatial size of the input layer. Size of the tuple is also the dimension. inplanes : int Number of planes ... | the_stack_v2_python_sparse | next_sparseconvnet/networks/architectures.py | next-exp/NEXT_SPARSECONVNET | train | 0 |
46a1f61a9f61b70e42207af09d6b08ecbf126e00 | [
"super().__init__(param_name, index, default, **options)\nif separator is None:\n separator = ' '\nself._separator = separator",
"if value is None:\n return None\nresult = value\nif isinstance(value, LIST_TYPES):\n result = self._separator.join([str(item) for item in value])\nreturn super()._get_represen... | <|body_start_0|>
super().__init__(param_name, index, default, **options)
if separator is None:
separator = ' '
self._separator = separator
<|end_body_0|>
<|body_start_1|>
if value is None:
return None
result = value
if isinstance(value, LIST_TYPES... | composite positional argument class. this class must be used for composite positional cli arguments. composite positional arguments are those that will be emitted after command name at specified index and without any argument name, and the value could be a list. for example: `command value1` or `command value1 value2 v... | CompositePositionalArgument | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompositePositionalArgument:
"""composite positional argument class. this class must be used for composite positional cli arguments. composite positional arguments are those that will be emitted after command name at specified index and without any argument name, and the value could be a list. fo... | stack_v2_sparse_classes_36k_train_034725 | 27,947 | permissive | [
{
"docstring": "initializes an instance of CompositePositionalArgument. :param str param_name: param name presented in method signature. :param int index: zero based index of this param in cli command inputs. :param list[object] | object default: default value to be emitted to cli if this param is not available... | 2 | null | Implement the Python class `CompositePositionalArgument` described below.
Class description:
composite positional argument class. this class must be used for composite positional cli arguments. composite positional arguments are those that will be emitted after command name at specified index and without any argument ... | Implement the Python class `CompositePositionalArgument` described below.
Class description:
composite positional argument class. this class must be used for composite positional cli arguments. composite positional arguments are those that will be emitted after command name at specified index and without any argument ... | 9d4776498225de4f3d16a4600b5b19212abe8562 | <|skeleton|>
class CompositePositionalArgument:
"""composite positional argument class. this class must be used for composite positional cli arguments. composite positional arguments are those that will be emitted after command name at specified index and without any argument name, and the value could be a list. fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CompositePositionalArgument:
"""composite positional argument class. this class must be used for composite positional cli arguments. composite positional arguments are those that will be emitted after command name at specified index and without any argument name, and the value could be a list. for example: `c... | the_stack_v2_python_sparse | src/pyrin/cli/arguments.py | mononobi/pyrin | train | 20 |
04164599d53bdbebca30700f26d746cfa9a95deb | [
"if len(points) < 2:\n raise Exception('not enough points')\nif len(points) >= 2 and points[0] != points[len(points) - 1]:\n raise Exception('start and end points different')\ntemp_xy = []\nfor point in points:\n if len(point) != 2:\n raise Exception('error for point input: ' + str(point))\n temp... | <|body_start_0|>
if len(points) < 2:
raise Exception('not enough points')
if len(points) >= 2 and points[0] != points[len(points) - 1]:
raise Exception('start and end points different')
temp_xy = []
for point in points:
if len(point) != 2:
... | Boundary object for GDSIO | Boundary | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Boundary:
"""Boundary object for GDSIO"""
def __init__(self, layer, dataType, points):
"""initialize Boundary object Parameters ---------- layer : int Layer id dataType : int Layer purpose points : list xy coordinates for Boundary object"""
<|body_0|>
def export(self, st... | stack_v2_sparse_classes_36k_train_034726 | 18,791 | permissive | [
{
"docstring": "initialize Boundary object Parameters ---------- layer : int Layer id dataType : int Layer purpose points : list xy coordinates for Boundary object",
"name": "__init__",
"signature": "def __init__(self, layer, dataType, points)"
},
{
"docstring": "Export to stream Parameters ----... | 2 | null | Implement the Python class `Boundary` described below.
Class description:
Boundary object for GDSIO
Method signatures and docstrings:
- def __init__(self, layer, dataType, points): initialize Boundary object Parameters ---------- layer : int Layer id dataType : int Layer purpose points : list xy coordinates for Bound... | Implement the Python class `Boundary` described below.
Class description:
Boundary object for GDSIO
Method signatures and docstrings:
- def __init__(self, layer, dataType, points): initialize Boundary object Parameters ---------- layer : int Layer id dataType : int Layer purpose points : list xy coordinates for Bound... | 8f62ec1971480cb27cb592421fd97f590379cff9 | <|skeleton|>
class Boundary:
"""Boundary object for GDSIO"""
def __init__(self, layer, dataType, points):
"""initialize Boundary object Parameters ---------- layer : int Layer id dataType : int Layer purpose points : list xy coordinates for Boundary object"""
<|body_0|>
def export(self, st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Boundary:
"""Boundary object for GDSIO"""
def __init__(self, layer, dataType, points):
"""initialize Boundary object Parameters ---------- layer : int Layer id dataType : int Layer purpose points : list xy coordinates for Boundary object"""
if len(points) < 2:
raise Exception(... | the_stack_v2_python_sparse | GDSIO.py | ucb-art/laygo | train | 24 |
6d5b82fcd467f7544606821183d3b08444962797 | [
"self.expiry_timestamp_msecs = expiry_timestamp_msecs\nself.hold_timestamp_msecs = hold_timestamp_msecs\nself.lock_timestamp_msecs = lock_timestamp_msecs\nself.mode = mode\nself.state = state",
"if dictionary is None:\n return None\nexpiry_timestamp_msecs = dictionary.get('expiryTimestampMsecs')\nhold_timestam... | <|body_start_0|>
self.expiry_timestamp_msecs = expiry_timestamp_msecs
self.hold_timestamp_msecs = hold_timestamp_msecs
self.lock_timestamp_msecs = lock_timestamp_msecs
self.mode = mode
self.state = state
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
... | Implementation of the 'FileLockStatus' model. Specifies the information of lock status for a file. Attributes: expiry_timestamp_msecs (long|int): Specifies a expiry timestamp in milliseconds until the file is locked. hold_timestamp_msecs (long|int): Specifies a override timestamp in milliseconds when an expired file is... | FileLockStatus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileLockStatus:
"""Implementation of the 'FileLockStatus' model. Specifies the information of lock status for a file. Attributes: expiry_timestamp_msecs (long|int): Specifies a expiry timestamp in milliseconds until the file is locked. hold_timestamp_msecs (long|int): Specifies a override timesta... | stack_v2_sparse_classes_36k_train_034727 | 3,226 | permissive | [
{
"docstring": "Constructor for the FileLockStatus class",
"name": "__init__",
"signature": "def __init__(self, expiry_timestamp_msecs=None, hold_timestamp_msecs=None, lock_timestamp_msecs=None, mode=None, state=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: ... | 2 | null | Implement the Python class `FileLockStatus` described below.
Class description:
Implementation of the 'FileLockStatus' model. Specifies the information of lock status for a file. Attributes: expiry_timestamp_msecs (long|int): Specifies a expiry timestamp in milliseconds until the file is locked. hold_timestamp_msecs (... | Implement the Python class `FileLockStatus` described below.
Class description:
Implementation of the 'FileLockStatus' model. Specifies the information of lock status for a file. Attributes: expiry_timestamp_msecs (long|int): Specifies a expiry timestamp in milliseconds until the file is locked. hold_timestamp_msecs (... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class FileLockStatus:
"""Implementation of the 'FileLockStatus' model. Specifies the information of lock status for a file. Attributes: expiry_timestamp_msecs (long|int): Specifies a expiry timestamp in milliseconds until the file is locked. hold_timestamp_msecs (long|int): Specifies a override timesta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileLockStatus:
"""Implementation of the 'FileLockStatus' model. Specifies the information of lock status for a file. Attributes: expiry_timestamp_msecs (long|int): Specifies a expiry timestamp in milliseconds until the file is locked. hold_timestamp_msecs (long|int): Specifies a override timestamp in millise... | the_stack_v2_python_sparse | cohesity_management_sdk/models/file_lock_status.py | cohesity/management-sdk-python | train | 24 |
9d6fd3d12b2418c603df787e8523ba01956be39e | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(email=self.normalize_email(email))\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email, password=password)\nuser.is_admin = True\nuser.save(using=self._db)\nreturn user"
] | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email))
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = self.create_user(... | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the given email, date of birth a... | stack_v2_sparse_classes_36k_train_034728 | 2,325 | 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, password=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
"name": "create_... | 2 | stack_v2_sparse_classes_30k_train_012931 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, email, password): C... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email, password=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, email, password): C... | 521bcdf8e30a9ce093df29cb7f28e8c2f2d4d979 | <|skeleton|>
class MyUserManager:
def create_user(self, email, password=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the given email, date of birth a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyUserManager:
def create_user(self, email, 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.model(email=self.normalize_email(email))
user.... | the_stack_v2_python_sparse | Family_Care/doctor/models.py | dkdinesh982/marvelapp | train | 0 | |
63a92be1d7d4fab2c907c4b75b552e7a33d2d229 | [
"slow = 0\nfor fast in range(len(nums)):\n if nums[fast] != val:\n nums[slow] = nums[fast]\n slow += 1\nreturn slow",
"i = 0\nn = len(nums)\nwhile i < n:\n if nums[i] == val:\n nums[i] = nums[n - 1]\n n -= 1\n else:\n i += 1\nreturn n"
] | <|body_start_0|>
slow = 0
for fast in range(len(nums)):
if nums[fast] != val:
nums[slow] = nums[fast]
slow += 1
return slow
<|end_body_0|>
<|body_start_1|>
i = 0
n = len(nums)
while i < n:
if nums[i] == val:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeElement_1(self, nums: List[int], val: int) -> int:
"""双指针1 时间复杂度：O(n)， 假设数组总共有 n 个元素，i 和 j 至多遍历 2n 步。 空间复杂度：O(1)。 :param nums: :param val: :return:"""
<|body_0|>
def removeElement_2(self, nums: List[int], val: int) -> int:
"""双指针2 时间复杂度：O(n)， i 和 ... | stack_v2_sparse_classes_36k_train_034729 | 2,796 | no_license | [
{
"docstring": "双指针1 时间复杂度：O(n)， 假设数组总共有 n 个元素，i 和 j 至多遍历 2n 步。 空间复杂度：O(1)。 :param nums: :param val: :return:",
"name": "removeElement_1",
"signature": "def removeElement_1(self, nums: List[int], val: int) -> int"
},
{
"docstring": "双指针2 时间复杂度：O(n)， i 和 n 最多遍历 nn 步。在这个方法中，赋值操作的次数等于要删除的元素的数量。因此，如... | 2 | stack_v2_sparse_classes_30k_train_001913 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement_1(self, nums: List[int], val: int) -> int: 双指针1 时间复杂度：O(n)， 假设数组总共有 n 个元素，i 和 j 至多遍历 2n 步。 空间复杂度：O(1)。 :param nums: :param val: :return:
- def removeElement_2(s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement_1(self, nums: List[int], val: int) -> int: 双指针1 时间复杂度：O(n)， 假设数组总共有 n 个元素，i 和 j 至多遍历 2n 步。 空间复杂度：O(1)。 :param nums: :param val: :return:
- def removeElement_2(s... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def removeElement_1(self, nums: List[int], val: int) -> int:
"""双指针1 时间复杂度：O(n)， 假设数组总共有 n 个元素，i 和 j 至多遍历 2n 步。 空间复杂度：O(1)。 :param nums: :param val: :return:"""
<|body_0|>
def removeElement_2(self, nums: List[int], val: int) -> int:
"""双指针2 时间复杂度：O(n)， i 和 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeElement_1(self, nums: List[int], val: int) -> int:
"""双指针1 时间复杂度：O(n)， 假设数组总共有 n 个元素，i 和 j 至多遍历 2n 步。 空间复杂度：O(1)。 :param nums: :param val: :return:"""
slow = 0
for fast in range(len(nums)):
if nums[fast] != val:
nums[slow] = nums[fast]
... | the_stack_v2_python_sparse | 软件开发岗刷题（华为笔试准备）/数组和字符串/removeElement.py | MaoningGuan/LeetCode | train | 3 | |
a2c232accecd9e94f71aee65d69d8f7f01c4a76a | [
"n = len(strs)\nif n < 1:\n return []\nsorted_strs = sorted(strs, key=lambda x: sorted(x))\nret = []\npre = sorted_strs[0]\ntmp = [pre]\nfor i in range(1, n):\n cur = sorted_strs[i]\n if sorted(cur) == sorted(pre):\n tmp.append(cur)\n else:\n ret.append(tmp[:])\n tmp = [cur]\n pr... | <|body_start_0|>
n = len(strs)
if n < 1:
return []
sorted_strs = sorted(strs, key=lambda x: sorted(x))
ret = []
pre = sorted_strs[0]
tmp = [pre]
for i in range(1, n):
cur = sorted_strs[i]
if sorted(cur) == sorted(pre):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def groupAnagrams1(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
<|body_0|>
def groupAnagrams2(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
<|body_1|>
def groupAnagrams3(self, strs):
""":type strs:... | stack_v2_sparse_classes_36k_train_034730 | 1,965 | no_license | [
{
"docstring": ":type strs: List[str] :rtype: List[List[str]]",
"name": "groupAnagrams1",
"signature": "def groupAnagrams1(self, strs)"
},
{
"docstring": ":type strs: List[str] :rtype: List[List[str]]",
"name": "groupAnagrams2",
"signature": "def groupAnagrams2(self, strs)"
},
{
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams1(self, strs): :type strs: List[str] :rtype: List[List[str]]
- def groupAnagrams2(self, strs): :type strs: List[str] :rtype: List[List[str]]
- def groupAnagrams3... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def groupAnagrams1(self, strs): :type strs: List[str] :rtype: List[List[str]]
- def groupAnagrams2(self, strs): :type strs: List[str] :rtype: List[List[str]]
- def groupAnagrams3... | d3e8669f932fc2e22711e8b7590d3365d020e189 | <|skeleton|>
class Solution:
def groupAnagrams1(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
<|body_0|>
def groupAnagrams2(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
<|body_1|>
def groupAnagrams3(self, strs):
""":type strs:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def groupAnagrams1(self, strs):
""":type strs: List[str] :rtype: List[List[str]]"""
n = len(strs)
if n < 1:
return []
sorted_strs = sorted(strs, key=lambda x: sorted(x))
ret = []
pre = sorted_strs[0]
tmp = [pre]
for i in ran... | the_stack_v2_python_sparse | leetcode/49.py | liuweilin17/algorithm | train | 3 | |
c8762f77d4afa989c809e65e2b7faaa3df03d6d8 | [
"uname = self.cleaned_data['username']\nif len(uname) < 6:\n raise forms.ValidationError('用户名太短')\nreturn uname",
"pwd1 = self.cleaned_data['password']\npwd2 = self.cleaned_data['password2']\nif pwd1 != pwd2:\n raise forms.ValidationError('两次密码不一致')\nreturn self.cleaned_data"
] | <|body_start_0|>
uname = self.cleaned_data['username']
if len(uname) < 6:
raise forms.ValidationError('用户名太短')
return uname
<|end_body_0|>
<|body_start_1|>
pwd1 = self.cleaned_data['password']
pwd2 = self.cleaned_data['password2']
if pwd1 != pwd2:
... | MyRegFrom | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyRegFrom:
def clean_username(self):
"""此方法限定username必须大于等于６个字符"""
<|body_0|>
def clean(self):
"""验证两个密码是否一致！不一致抛出ValidationError类型的异常"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
uname = self.cleaned_data['username']
if len(uname) < 6:
... | stack_v2_sparse_classes_36k_train_034731 | 1,209 | no_license | [
{
"docstring": "此方法限定username必须大于等于６个字符",
"name": "clean_username",
"signature": "def clean_username(self)"
},
{
"docstring": "验证两个密码是否一致！不一致抛出ValidationError类型的异常",
"name": "clean",
"signature": "def clean(self)"
}
] | 2 | null | Implement the Python class `MyRegFrom` described below.
Class description:
Implement the MyRegFrom class.
Method signatures and docstrings:
- def clean_username(self): 此方法限定username必须大于等于６个字符
- def clean(self): 验证两个密码是否一致！不一致抛出ValidationError类型的异常 | Implement the Python class `MyRegFrom` described below.
Class description:
Implement the MyRegFrom class.
Method signatures and docstrings:
- def clean_username(self): 此方法限定username必须大于等于６个字符
- def clean(self): 验证两个密码是否一致！不一致抛出ValidationError类型的异常
<|skeleton|>
class MyRegFrom:
def clean_username(self):
... | 319daf56d88e92f69ee467e0ccf83c01367ed137 | <|skeleton|>
class MyRegFrom:
def clean_username(self):
"""此方法限定username必须大于等于６个字符"""
<|body_0|>
def clean(self):
"""验证两个密码是否一致！不一致抛出ValidationError类型的异常"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyRegFrom:
def clean_username(self):
"""此方法限定username必须大于等于６个字符"""
uname = self.cleaned_data['username']
if len(uname) < 6:
raise forms.ValidationError('用户名太短')
return uname
def clean(self):
"""验证两个密码是否一致！不一致抛出ValidationError类型的异常"""
pwd1 = self... | the_stack_v2_python_sparse | django_base/mysite6/user/forms.py | vivid-ZLL/tedu | train | 0 | |
c66b999b7b85c6b60b29e358a5db643988fde3b4 | [
"n = len(init_val)\nself.segfunc = segfunc\nself.ide_ele = ide_ele\nself.num = 1 << (n - 1).bit_length()\nself.tree = [ide_ele] * 2 * self.num\nfor i in range(n):\n self.tree[self.num + i] = init_val[i]\nfor i in range(self.num - 1, 0, -1):\n self.tree[i] = self.segfunc(self.tree[2 * i], self.tree[2 * i + 1])... | <|body_start_0|>
n = len(init_val)
self.segfunc = segfunc
self.ide_ele = ide_ele
self.num = 1 << (n - 1).bit_length()
self.tree = [ide_ele] * 2 * self.num
for i in range(n):
self.tree[self.num + i] = init_val[i]
for i in range(self.num - 1, 0, -1):
... | init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN) | SegTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegTree:
"""init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)"""
def __init__(self, init_val, segfunc, ide_ele):
"""init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
... | stack_v2_sparse_classes_36k_train_034732 | 2,441 | no_license | [
{
"docstring": "init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)",
"name": "__init__",
"signature": "def __init__(self, init_val, segfunc, ide_ele)"
},
{
"docstring": "k番目の値をxに更新 k: index(0-index) x: update value",
"name": "update",
"signatur... | 3 | stack_v2_sparse_classes_30k_train_012215 | Implement the Python class `SegTree` described below.
Class description:
init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)
Method signatures and docstrings:
- def __init__(self, init_val, segfunc, ide_ele): init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_el... | Implement the Python class `SegTree` described below.
Class description:
init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)
Method signatures and docstrings:
- def __init__(self, init_val, segfunc, ide_ele): init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_el... | 2526e72de9eb19d1e1c634dbd577816bfe39bc10 | <|skeleton|>
class SegTree:
"""init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)"""
def __init__(self, init_val, segfunc, ide_ele):
"""init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SegTree:
"""init(init_val, ide_ele): 配列init_valで初期化 O(N) update(k, x): k番目の値をxに更新 O(N) query(l, r): 区間[l, r)をsegfuncしたものを返す O(logN)"""
def __init__(self, init_val, segfunc, ide_ele):
"""init_val: 配列の初期値 segfunc: 区間にしたい操作 ide_ele: 単位元 n: 要素数 num: n以上の最小の2のべき乗 tree: セグメント木(1-index)"""
n = l... | the_stack_v2_python_sparse | ABC/ACLBC/ACLBC_D.py | happa64/AtCoder_Beginner_Contest | train | 0 |
2f835e30641a7176346e906f0c71ccb04e46bc27 | [
"\"\"\"\n self.golden_ratio = 1.618\n self.table_size = 65536\n self.table = [[] for _ in range(self.table_size)]\n self.hash = lambda i: i * math.ceil(self.golden_ratio * self.table_size) % self.table_size\n \"\"\"\nself.dict = {}",
"\"\"\"\n self.remove(key) # use the ... | <|body_start_0|>
"""
self.golden_ratio = 1.618
self.table_size = 65536
self.table = [[] for _ in range(self.table_size)]
self.hash = lambda i: i * math.ceil(self.golden_ratio * self.table_size) % self.table_size
"""
self.dic... | MyHashMap | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def put(self, key: int, value: int) -> None:
"""value will always be non-negative."""
<|body_1|>
def get(self, key: int) -> int:
"""Returns the value to which th... | stack_v2_sparse_classes_36k_train_034733 | 3,048 | permissive | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "value will always be non-negative.",
"name": "put",
"signature": "def put(self, key: int, value: int) -> None"
},
{
"docstring": "Returns the value to w... | 4 | stack_v2_sparse_classes_30k_train_012088 | Implement the Python class `MyHashMap` described below.
Class description:
Implement the MyHashMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def put(self, key: int, value: int) -> None: value will always be non-negative.
- def get(self, key: int) -> int: Ret... | Implement the Python class `MyHashMap` described below.
Class description:
Implement the MyHashMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def put(self, key: int, value: int) -> None: value will always be non-negative.
- def get(self, key: int) -> int: Ret... | 4ea4c1579c28308455be4dfa02bd45ebd88b2d0a | <|skeleton|>
class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def put(self, key: int, value: int) -> None:
"""value will always be non-negative."""
<|body_1|>
def get(self, key: int) -> int:
"""Returns the value to which th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
"""
self.golden_ratio = 1.618
self.table_size = 65536
self.table = [[] for _ in range(self.table_size)]
self.hash = lambda i: i * math.ceil(self.golden_rati... | the_stack_v2_python_sparse | src/integers/myHashMap.py | way2arun/datastructures_algorithms | train | 1 | |
4f11d10128806d930428a90fe29a6656b189cf32 | [
"super().__init__()\ndown_list = []\nif stride == 0:\n down_list.append(nn.AdaptiveAvgPool2d((1, 1)))\nelif stride == 1:\n pass\nelse:\n down_list.append(nn.AvgPool2d(kernel_size=kernel_size, stride=stride, padding=stride))\ndown_list.append(nn.BatchNorm2d(in_planes))\ndown_list.append(nn.ReLU(inplace=True... | <|body_start_0|>
super().__init__()
down_list = []
if stride == 0:
down_list.append(nn.AdaptiveAvgPool2d((1, 1)))
elif stride == 1:
pass
else:
down_list.append(nn.AvgPool2d(kernel_size=kernel_size, stride=stride, padding=stride))
down_l... | DAPPMBranch | [
"LicenseRef-scancode-proprietary-license",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DAPPMBranch:
def __init__(self, kernel_size: int, stride: int, in_planes: int, branch_planes: int, inter_mode: str='bilinear'):
"""A DAPPM branch :param kernel_size: the kernel size for the average pooling when stride=0 this parameter is omitted and AdaptiveAvgPool2d over all the input i... | stack_v2_sparse_classes_36k_train_034734 | 28,514 | permissive | [
{
"docstring": "A DAPPM branch :param kernel_size: the kernel size for the average pooling when stride=0 this parameter is omitted and AdaptiveAvgPool2d over all the input is performed :param stride: stride for the average pooling when stride=0: an AdaptiveAvgPool2d over all the input is performed (output is 1x... | 2 | null | Implement the Python class `DAPPMBranch` described below.
Class description:
Implement the DAPPMBranch class.
Method signatures and docstrings:
- def __init__(self, kernel_size: int, stride: int, in_planes: int, branch_planes: int, inter_mode: str='bilinear'): A DAPPM branch :param kernel_size: the kernel size for th... | Implement the Python class `DAPPMBranch` described below.
Class description:
Implement the DAPPMBranch class.
Method signatures and docstrings:
- def __init__(self, kernel_size: int, stride: int, in_planes: int, branch_planes: int, inter_mode: str='bilinear'): A DAPPM branch :param kernel_size: the kernel size for th... | 7240726cf6425b53a26ed2faec03672f30fee6be | <|skeleton|>
class DAPPMBranch:
def __init__(self, kernel_size: int, stride: int, in_planes: int, branch_planes: int, inter_mode: str='bilinear'):
"""A DAPPM branch :param kernel_size: the kernel size for the average pooling when stride=0 this parameter is omitted and AdaptiveAvgPool2d over all the input i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DAPPMBranch:
def __init__(self, kernel_size: int, stride: int, in_planes: int, branch_planes: int, inter_mode: str='bilinear'):
"""A DAPPM branch :param kernel_size: the kernel size for the average pooling when stride=0 this parameter is omitted and AdaptiveAvgPool2d over all the input is performed :p... | the_stack_v2_python_sparse | src/super_gradients/training/models/segmentation_models/ddrnet.py | Deci-AI/super-gradients | train | 3,237 | |
de2c1fb080b40559cac5fdb6710e8ec24bbf8ef3 | [
"assert sr > 9000, 'Sampling rate too low!'\nself.gbank = Gammatone(sr, num_chan, (130.0, 4500.0))\nself.gammawgt = self.gbank.gammawgt(nfft)\n\ndef _stft(sig):\n return stft(sig, wind, hop, nfft, synth=True, zphase=True)\n\ndef _istft(spec):\n return istft(spec, wind, hop, nfft, zphase=True)\nself.stft = _st... | <|body_start_0|>
assert sr > 9000, 'Sampling rate too low!'
self.gbank = Gammatone(sr, num_chan, (130.0, 4500.0))
self.gammawgt = self.gbank.gammawgt(nfft)
def _stft(sig):
return stft(sig, wind, hop, nfft, synth=True, zphase=True)
def _istft(spec):
retur... | Suppression of Slowly-varying components and the Falling edge. This implementation follows paper by Kim and Stern: Kim, Chanwoo, and Richard M. Stern."Nonlinear enhancement of onset for robust speech recognition." Eleventh Annual Conference of the International Speech Communication Association. 2010. See Also -------- ... | SSFEnhancer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSFEnhancer:
"""Suppression of Slowly-varying components and the Falling edge. This implementation follows paper by Kim and Stern: Kim, Chanwoo, and Richard M. Stern."Nonlinear enhancement of onset for robust speech recognition." Eleventh Annual Conference of the International Speech Communicatio... | stack_v2_sparse_classes_36k_train_034735 | 19,410 | permissive | [
{
"docstring": "Instantiate an SSF enhancer. Parameters ---------- sr: int Sampling rate in Hz. wind: numpy.ndarray Window function. hop: float Hop fraction. nfft: int Number of DFT points. Keyword Parameters ------------------ num_chan: int, 40 Number of channels in the Gammatone filterbank. ptype: int, 2 SSF ... | 2 | stack_v2_sparse_classes_30k_train_015194 | Implement the Python class `SSFEnhancer` described below.
Class description:
Suppression of Slowly-varying components and the Falling edge. This implementation follows paper by Kim and Stern: Kim, Chanwoo, and Richard M. Stern."Nonlinear enhancement of onset for robust speech recognition." Eleventh Annual Conference o... | Implement the Python class `SSFEnhancer` described below.
Class description:
Suppression of Slowly-varying components and the Falling edge. This implementation follows paper by Kim and Stern: Kim, Chanwoo, and Richard M. Stern."Nonlinear enhancement of onset for robust speech recognition." Eleventh Annual Conference o... | 740139490208ca7605e9b520f1a28214fa3903dc | <|skeleton|>
class SSFEnhancer:
"""Suppression of Slowly-varying components and the Falling edge. This implementation follows paper by Kim and Stern: Kim, Chanwoo, and Richard M. Stern."Nonlinear enhancement of onset for robust speech recognition." Eleventh Annual Conference of the International Speech Communicatio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SSFEnhancer:
"""Suppression of Slowly-varying components and the Falling edge. This implementation follows paper by Kim and Stern: Kim, Chanwoo, and Richard M. Stern."Nonlinear enhancement of onset for robust speech recognition." Eleventh Annual Conference of the International Speech Communication Association... | the_stack_v2_python_sparse | audlib/enhance.py | templeblock/pyaudlib | train | 0 |
8a4920c227e43edb898d2f61e38e463f3df43473 | [
"current_method = 1\nnext_method = 1\nfor _ in range(n):\n current_method, next_method = (next_method, current_method + next_method)\nreturn current_method",
"from __builtin__ import xrange\ndp = dict()\ndp[0] = 1\ndp[1] = 1\nfor i in xrange(2, n + 1):\n dp[i] = dp[i - 1] + dp[i - 2]\nreturn dp[n]"
] | <|body_start_0|>
current_method = 1
next_method = 1
for _ in range(n):
current_method, next_method = (next_method, current_method + next_method)
return current_method
<|end_body_0|>
<|body_start_1|>
from __builtin__ import xrange
dp = dict()
dp[0] = 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def rewrite(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
current_method = 1
next_method = 1
for _ in range(n):
... | stack_v2_sparse_classes_36k_train_034736 | 1,206 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs",
"signature": "def climbStairs(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "rewrite",
"signature": "def rewrite(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def rewrite(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def rewrite(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def climbStairs(self, n):
""":type ... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def rewrite(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
current_method = 1
next_method = 1
for _ in range(n):
current_method, next_method = (next_method, current_method + next_method)
return current_method
def rewrite(self, n):
""":ty... | the_stack_v2_python_sparse | co_apple/70_Climbing_Stairs.py | vsdrun/lc_public | train | 6 | |
1c6315bf1ee497701ab03a0319aa9cf1024b13f0 | [
"url = '/mybookings/'\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 302)",
"url = '/mybookings/'\nself.client.login(username=self.adminUN, password='pass')\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 20... | <|body_start_0|>
url = '/mybookings/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
<|end_body_0|>
<|body_start_1|>
url = '/mybookings/'
self.client.login(username=self.adminUN, password='pass')
response = self.cl... | MyBookingsTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyBookingsTestCase:
def test_not_logged_in(self):
"""Test that the mybookings view will load whilst not logged in."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the mybookings view will load whilst logged in as admin."""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k_train_034737 | 26,818 | permissive | [
{
"docstring": "Test that the mybookings view will load whilst not logged in.",
"name": "test_not_logged_in",
"signature": "def test_not_logged_in(self)"
},
{
"docstring": "Test that the mybookings view will load whilst logged in as admin.",
"name": "test_logged_in_admin",
"signature": "... | 3 | null | Implement the Python class `MyBookingsTestCase` described below.
Class description:
Implement the MyBookingsTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the mybookings view will load whilst not logged in.
- def test_logged_in_admin(self): Test that the mybookings view wi... | Implement the Python class `MyBookingsTestCase` described below.
Class description:
Implement the MyBookingsTestCase class.
Method signatures and docstrings:
- def test_not_logged_in(self): Test that the mybookings view will load whilst not logged in.
- def test_logged_in_admin(self): Test that the mybookings view wi... | 37d2942efcbdaad072f7a06ac876a40e0f69f702 | <|skeleton|>
class MyBookingsTestCase:
def test_not_logged_in(self):
"""Test that the mybookings view will load whilst not logged in."""
<|body_0|>
def test_logged_in_admin(self):
"""Test that the mybookings view will load whilst logged in as admin."""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyBookingsTestCase:
def test_not_logged_in(self):
"""Test that the mybookings view will load whilst not logged in."""
url = '/mybookings/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
def test_logged_in_admin(self)... | the_stack_v2_python_sparse | mooring/test_views.py | dbca-wa/moorings | train | 0 | |
8e96b820a3ed175dd08658fff5d00040564a2063 | [
"ACTIONS_ALLOWED = ['publish', 'moderate', 'delete', 'undelete']\nif self.cleaned_data['action'] in ACTIONS_ALLOWED:\n return self.cleaned_data['action']\nraise forms.ValidationError(u'Improper comment action specified: %s' % self.cleaned_data['action'])",
"try:\n FreeComment.objects.get(pk=self.cleaned_dat... | <|body_start_0|>
ACTIONS_ALLOWED = ['publish', 'moderate', 'delete', 'undelete']
if self.cleaned_data['action'] in ACTIONS_ALLOWED:
return self.cleaned_data['action']
raise forms.ValidationError(u'Improper comment action specified: %s' % self.cleaned_data['action'])
<|end_body_0|>
<... | SingleQuickActionForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleQuickActionForm:
def clean_action(self):
"""Validates that the action is allowed by the system."""
<|body_0|>
def clean_comment(self):
"""Validates that the comment exists."""
<|body_1|>
def clean_url(self):
"""Validates that the relative U... | stack_v2_sparse_classes_36k_train_034738 | 1,364 | no_license | [
{
"docstring": "Validates that the action is allowed by the system.",
"name": "clean_action",
"signature": "def clean_action(self)"
},
{
"docstring": "Validates that the comment exists.",
"name": "clean_comment",
"signature": "def clean_comment(self)"
},
{
"docstring": "Validates... | 3 | stack_v2_sparse_classes_30k_val_000002 | Implement the Python class `SingleQuickActionForm` described below.
Class description:
Implement the SingleQuickActionForm class.
Method signatures and docstrings:
- def clean_action(self): Validates that the action is allowed by the system.
- def clean_comment(self): Validates that the comment exists.
- def clean_ur... | Implement the Python class `SingleQuickActionForm` described below.
Class description:
Implement the SingleQuickActionForm class.
Method signatures and docstrings:
- def clean_action(self): Validates that the action is allowed by the system.
- def clean_comment(self): Validates that the comment exists.
- def clean_ur... | 1d307854a452674fbce7bc50faf70d367b85f84e | <|skeleton|>
class SingleQuickActionForm:
def clean_action(self):
"""Validates that the action is allowed by the system."""
<|body_0|>
def clean_comment(self):
"""Validates that the comment exists."""
<|body_1|>
def clean_url(self):
"""Validates that the relative U... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SingleQuickActionForm:
def clean_action(self):
"""Validates that the action is allowed by the system."""
ACTIONS_ALLOWED = ['publish', 'moderate', 'delete', 'undelete']
if self.cleaned_data['action'] in ACTIONS_ALLOWED:
return self.cleaned_data['action']
raise forms... | the_stack_v2_python_sparse | apps/staff/commentmod/forms.py | queensjournal/queensjournal.ca | train | 1 | |
cdd9e9a6d1855c14ab825351587b8e12a2f14e76 | [
"match = wrapperRE.match(branchInfo.GetTypeName())\nif match:\n self.type = match.group(1)\nelse:\n raise ValueError('Not edm::Wrapper')\nname = trailingDotRE.sub('', branchInfo.GetName())\npieces = underscoreRE.split(name)\nif len(pieces) != 4:\n raise ValueError('%s not formatted as expected' % name)\nse... | <|body_start_0|>
match = wrapperRE.match(branchInfo.GetTypeName())
if match:
self.type = match.group(1)
else:
raise ValueError('Not edm::Wrapper')
name = trailingDotRE.sub('', branchInfo.GetName())
pieces = underscoreRE.split(name)
if len(pieces) !... | Branch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Branch:
def __init__(self, branchInfo, regexList=None):
"""Takes the needed information from Root's Branch Info"""
<|body_0|>
def __str__(self):
"""String representation"""
<|body_1|>
def _setForm(branchList):
"""Loop through lists and set widths... | stack_v2_sparse_classes_36k_train_034739 | 9,332 | permissive | [
{
"docstring": "Takes the needed information from Root's Branch Info",
"name": "__init__",
"signature": "def __init__(self, branchInfo, regexList=None)"
},
{
"docstring": "String representation",
"name": "__str__",
"signature": "def __str__(self)"
},
{
"docstring": "Loop through ... | 4 | stack_v2_sparse_classes_30k_train_010494 | Implement the Python class `Branch` described below.
Class description:
Implement the Branch class.
Method signatures and docstrings:
- def __init__(self, branchInfo, regexList=None): Takes the needed information from Root's Branch Info
- def __str__(self): String representation
- def _setForm(branchList): Loop throu... | Implement the Python class `Branch` described below.
Class description:
Implement the Branch class.
Method signatures and docstrings:
- def __init__(self, branchInfo, regexList=None): Takes the needed information from Root's Branch Info
- def __str__(self): String representation
- def _setForm(branchList): Loop throu... | 19c178740257eb48367778593da55dcad08b7a4f | <|skeleton|>
class Branch:
def __init__(self, branchInfo, regexList=None):
"""Takes the needed information from Root's Branch Info"""
<|body_0|>
def __str__(self):
"""String representation"""
<|body_1|>
def _setForm(branchList):
"""Loop through lists and set widths... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Branch:
def __init__(self, branchInfo, regexList=None):
"""Takes the needed information from Root's Branch Info"""
match = wrapperRE.match(branchInfo.GetTypeName())
if match:
self.type = match.group(1)
else:
raise ValueError('Not edm::Wrapper')
n... | the_stack_v2_python_sparse | FWCore/PythonUtilities/scripts/edmDumpEventContent | cms-sw/cmssw | train | 1,006 | |
bd0abd8fbc0bbebdff3449441c30c40894361cae | [
"words.sort(key=len)\nwordset = set()\nres = []\n\ndef dfs(s, wset):\n if not wset:\n return False\n dp = {}\n\n def helper(s):\n if not s:\n return True\n if s in dp:\n return dp[s]\n for i in range(len(s)):\n if s[0:i + 1] in wset:\n ... | <|body_start_0|>
words.sort(key=len)
wordset = set()
res = []
def dfs(s, wset):
if not wset:
return False
dp = {}
def helper(s):
if not s:
return True
if s in dp:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findAllConcatenatedWordsInADict(self, words):
""":type words: List[str] :rtype: List[str]"""
<|body_0|>
def findAllConcatenatedWordsInADictTLE(self, words):
""":type words: List[str] :rtype: List[str]"""
<|body_1|>
def findAllConcatenatedWo... | stack_v2_sparse_classes_36k_train_034740 | 3,879 | no_license | [
{
"docstring": ":type words: List[str] :rtype: List[str]",
"name": "findAllConcatenatedWordsInADict",
"signature": "def findAllConcatenatedWordsInADict(self, words)"
},
{
"docstring": ":type words: List[str] :rtype: List[str]",
"name": "findAllConcatenatedWordsInADictTLE",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_011432 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAllConcatenatedWordsInADict(self, words): :type words: List[str] :rtype: List[str]
- def findAllConcatenatedWordsInADictTLE(self, words): :type words: List[str] :rtype: L... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findAllConcatenatedWordsInADict(self, words): :type words: List[str] :rtype: List[str]
- def findAllConcatenatedWordsInADictTLE(self, words): :type words: List[str] :rtype: L... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def findAllConcatenatedWordsInADict(self, words):
""":type words: List[str] :rtype: List[str]"""
<|body_0|>
def findAllConcatenatedWordsInADictTLE(self, words):
""":type words: List[str] :rtype: List[str]"""
<|body_1|>
def findAllConcatenatedWo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findAllConcatenatedWordsInADict(self, words):
""":type words: List[str] :rtype: List[str]"""
words.sort(key=len)
wordset = set()
res = []
def dfs(s, wset):
if not wset:
return False
dp = {}
def helper(s... | the_stack_v2_python_sparse | C/ConcatenatedWords.py | bssrdf/pyleet | train | 2 | |
991476d0a5bbe16e3718fd2926ccf31de42cd983 | [
"l = self.clone()\nl.from_segment = self.to_segment\nl.from_orient = gfapy.invert(self.to_orient)\nl.to_segment = self.from_segment\nl.to_orient = gfapy.invert(self.from_orient)\nl.overlap = self.overlap.complement()\nreturn l",
"tmp = self.from_segment\nself.from_segment = self.to_segment\nself.to_segment = tmp\... | <|body_start_0|>
l = self.clone()
l.from_segment = self.to_segment
l.from_orient = gfapy.invert(self.to_orient)
l.to_segment = self.from_segment
l.to_orient = gfapy.invert(self.from_orient)
l.overlap = self.overlap.complement()
return l
<|end_body_0|>
<|body_star... | Complement | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Complement:
def complement(self):
"""Creates the equivalent link with from and to inverted. The CIGAR operations (order and type) are inverted as well. Tags are left unchanged. Note: The path references are not copied to the complement link. Note: This method shall be overridden if custo... | stack_v2_sparse_classes_36k_train_034741 | 1,585 | permissive | [
{
"docstring": "Creates the equivalent link with from and to inverted. The CIGAR operations (order and type) are inverted as well. Tags are left unchanged. Note: The path references are not copied to the complement link. Note: This method shall be overridden if custom tags are defined, which have a complementat... | 2 | null | Implement the Python class `Complement` described below.
Class description:
Implement the Complement class.
Method signatures and docstrings:
- def complement(self): Creates the equivalent link with from and to inverted. The CIGAR operations (order and type) are inverted as well. Tags are left unchanged. Note: The pa... | Implement the Python class `Complement` described below.
Class description:
Implement the Complement class.
Method signatures and docstrings:
- def complement(self): Creates the equivalent link with from and to inverted. The CIGAR operations (order and type) are inverted as well. Tags are left unchanged. Note: The pa... | 12b31daac26ab137b6ee4a29b4f14554ba962dcb | <|skeleton|>
class Complement:
def complement(self):
"""Creates the equivalent link with from and to inverted. The CIGAR operations (order and type) are inverted as well. Tags are left unchanged. Note: The path references are not copied to the complement link. Note: This method shall be overridden if custo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Complement:
def complement(self):
"""Creates the equivalent link with from and to inverted. The CIGAR operations (order and type) are inverted as well. Tags are left unchanged. Note: The path references are not copied to the complement link. Note: This method shall be overridden if custom tags are def... | the_stack_v2_python_sparse | gfapy/line/edge/link/complement.py | ggonnella/gfapy | train | 63 | |
3f590307c4e50d1541efba93db3325a8e347bd33 | [
"default_sec_group = [group for group in self.os_conn.nova.security_groups.list() if group.name == 'default'][0]\nself.os_conn.nova.security_group_rules.create(default_sec_group.id, ip_protocol='tcp', from_port=22, to_port=22, cidr='0.0.0.0/0')\nself.os_conn.nova.security_group_rules.create(default_sec_group.id, ip... | <|body_start_0|>
default_sec_group = [group for group in self.os_conn.nova.security_groups.list() if group.name == 'default'][0]
self.os_conn.nova.security_group_rules.create(default_sec_group.id, ip_protocol='tcp', from_port=22, to_port=22, cidr='0.0.0.0/0')
self.os_conn.nova.security_group_rul... | Common functions for ovs tests | OvsBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OvsBase:
"""Common functions for ovs tests"""
def setup_rules_for_default_sec_group(self):
"""Add necessary rules to default security group."""
<|body_0|>
def get_current_cookie(self, compute):
"""Get the value of the cookie parameter for br-int or br-tun bridge.... | stack_v2_sparse_classes_36k_train_034742 | 41,546 | no_license | [
{
"docstring": "Add necessary rules to default security group.",
"name": "setup_rules_for_default_sec_group",
"signature": "def setup_rules_for_default_sec_group(self)"
},
{
"docstring": "Get the value of the cookie parameter for br-int or br-tun bridge. :param compute: Compute node where the se... | 2 | stack_v2_sparse_classes_30k_train_015985 | Implement the Python class `OvsBase` described below.
Class description:
Common functions for ovs tests
Method signatures and docstrings:
- def setup_rules_for_default_sec_group(self): Add necessary rules to default security group.
- def get_current_cookie(self, compute): Get the value of the cookie parameter for br-... | Implement the Python class `OvsBase` described below.
Class description:
Common functions for ovs tests
Method signatures and docstrings:
- def setup_rules_for_default_sec_group(self): Add necessary rules to default security group.
- def get_current_cookie(self, compute): Get the value of the cookie parameter for br-... | 8aced2855b78b5f123195d188c80e27b43888a2e | <|skeleton|>
class OvsBase:
"""Common functions for ovs tests"""
def setup_rules_for_default_sec_group(self):
"""Add necessary rules to default security group."""
<|body_0|>
def get_current_cookie(self, compute):
"""Get the value of the cookie parameter for br-int or br-tun bridge.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OvsBase:
"""Common functions for ovs tests"""
def setup_rules_for_default_sec_group(self):
"""Add necessary rules to default security group."""
default_sec_group = [group for group in self.os_conn.nova.security_groups.list() if group.name == 'default'][0]
self.os_conn.nova.securit... | the_stack_v2_python_sparse | mos_tests/neutron/python_tests/test_ovs_restart.py | Mirantis/mos-integration-tests | train | 16 |
17e8080849587459a5429ba9b74c62ce5eeb8083 | [
"try:\n user = User.objects.get(email=username)\n if user.check_password(password):\n return user\n return None\nexcept User.DoesNotExist:\n return None",
"try:\n user = User.objects.get(pk=user_id)\n if user.is_active:\n return user\n return None\nexcept User.DoesNotExist:\n ... | <|body_start_0|>
try:
user = User.objects.get(email=username)
if user.check_password(password):
return user
return None
except User.DoesNotExist:
return None
<|end_body_0|>
<|body_start_1|>
try:
user = User.objects.get(... | to authenticate a user using their email address & password | EmailAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmailAuth:
"""to authenticate a user using their email address & password"""
def authenticate(self, username=None, password=None):
"""get an instance of a User using the email & verify the password"""
<|body_0|>
def get_user(self, user_id):
"""method used by the ... | stack_v2_sparse_classes_36k_train_034743 | 1,231 | no_license | [
{
"docstring": "get an instance of a User using the email & verify the password",
"name": "authenticate",
"signature": "def authenticate(self, username=None, password=None)"
},
{
"docstring": "method used by the Django authentication to get a user instance",
"name": "get_user",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_010771 | Implement the Python class `EmailAuth` described below.
Class description:
to authenticate a user using their email address & password
Method signatures and docstrings:
- def authenticate(self, username=None, password=None): get an instance of a User using the email & verify the password
- def get_user(self, user_id)... | Implement the Python class `EmailAuth` described below.
Class description:
to authenticate a user using their email address & password
Method signatures and docstrings:
- def authenticate(self, username=None, password=None): get an instance of a User using the email & verify the password
- def get_user(self, user_id)... | a80148cb642cb09dac57cff18483be14fed67dfd | <|skeleton|>
class EmailAuth:
"""to authenticate a user using their email address & password"""
def authenticate(self, username=None, password=None):
"""get an instance of a User using the email & verify the password"""
<|body_0|>
def get_user(self, user_id):
"""method used by the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmailAuth:
"""to authenticate a user using their email address & password"""
def authenticate(self, username=None, password=None):
"""get an instance of a User using the email & verify the password"""
try:
user = User.objects.get(email=username)
if user.check_passw... | the_stack_v2_python_sparse | accounts/backends.py | sarahbarron/Stream-3-Project | train | 1 |
07d2561068ee20c057b10c258d3bfb19d08fb391 | [
"text_length = len(text)\namount_to_pad = self.block_size - text_length % self.block_size\nif amount_to_pad == 0:\n amount_to_pad = self.block_size\npad = chr(amount_to_pad)\nreturn text + pad * amount_to_pad",
"pad = ord(decrypted[-1])\nif pad < 1 or pad > 32:\n pad = 0\nreturn decrypted[:-pad]"
] | <|body_start_0|>
text_length = len(text)
amount_to_pad = self.block_size - text_length % self.block_size
if amount_to_pad == 0:
amount_to_pad = self.block_size
pad = chr(amount_to_pad)
return text + pad * amount_to_pad
<|end_body_0|>
<|body_start_1|>
pad = or... | PKCS7-based encryption and decryption algorithm | PKCS7Encoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PKCS7Encoder:
"""PKCS7-based encryption and decryption algorithm"""
def encode(self, text):
"""@param text: orignial plaintext @return: remedium plaintext"""
<|body_0|>
def decode(self, decrypted):
"""Plaintext after you remove the decrypted @param decrypted: dec... | stack_v2_sparse_classes_36k_train_034744 | 8,425 | permissive | [
{
"docstring": "@param text: orignial plaintext @return: remedium plaintext",
"name": "encode",
"signature": "def encode(self, text)"
},
{
"docstring": "Plaintext after you remove the decrypted @param decrypted: decrypted remedium plaintext @return: plaintext before remedium",
"name": "decod... | 2 | null | Implement the Python class `PKCS7Encoder` described below.
Class description:
PKCS7-based encryption and decryption algorithm
Method signatures and docstrings:
- def encode(self, text): @param text: orignial plaintext @return: remedium plaintext
- def decode(self, decrypted): Plaintext after you remove the decrypted ... | Implement the Python class `PKCS7Encoder` described below.
Class description:
PKCS7-based encryption and decryption algorithm
Method signatures and docstrings:
- def encode(self, text): @param text: orignial plaintext @return: remedium plaintext
- def decode(self, decrypted): Plaintext after you remove the decrypted ... | 6be1af50496340ded9879a6450c8208ac9f97e72 | <|skeleton|>
class PKCS7Encoder:
"""PKCS7-based encryption and decryption algorithm"""
def encode(self, text):
"""@param text: orignial plaintext @return: remedium plaintext"""
<|body_0|>
def decode(self, decrypted):
"""Plaintext after you remove the decrypted @param decrypted: dec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PKCS7Encoder:
"""PKCS7-based encryption and decryption algorithm"""
def encode(self, text):
"""@param text: orignial plaintext @return: remedium plaintext"""
text_length = len(text)
amount_to_pad = self.block_size - text_length % self.block_size
if amount_to_pad == 0:
... | the_stack_v2_python_sparse | server/services/wechat/assembly/WXBizMsgCrypt.py | Soopro/totoro | train | 0 |
a1a56f8347f276262673a8c2a88cb9193f10f38e | [
"super().__init__(optimizer, initial_lambda, lambda_updater, logger, val_split)\nif not isinstance(p, int) or p < 1:\n raise ValueError('p must be a positive integer')\nself.p = p",
"del loss\npenalty = 0\nfor group in self.optimizer.param_groups:\n for param in group['params']:\n penalty += th.linal... | <|body_start_0|>
super().__init__(optimizer, initial_lambda, lambda_updater, logger, val_split)
if not isinstance(p, int) or p < 1:
raise ValueError('p must be a positive integer')
self.p = p
<|end_body_0|>
<|body_start_1|>
del loss
penalty = 0
for group in s... | Applies Lp regularization to a loss function. | LpRegularizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LpRegularizer:
"""Applies Lp regularization to a loss function."""
def __init__(self, optimizer: optim.Optimizer, initial_lambda: float, lambda_updater: Optional[updaters.LambdaUpdater], logger: imit_logger.HierarchicalLogger, p: int, val_split: Optional[float]=None) -> None:
"""Init... | stack_v2_sparse_classes_36k_train_034745 | 11,139 | permissive | [
{
"docstring": "Initialize the regularizer.",
"name": "__init__",
"signature": "def __init__(self, optimizer: optim.Optimizer, initial_lambda: float, lambda_updater: Optional[updaters.LambdaUpdater], logger: imit_logger.HierarchicalLogger, p: int, val_split: Optional[float]=None) -> None"
},
{
"... | 2 | null | Implement the Python class `LpRegularizer` described below.
Class description:
Applies Lp regularization to a loss function.
Method signatures and docstrings:
- def __init__(self, optimizer: optim.Optimizer, initial_lambda: float, lambda_updater: Optional[updaters.LambdaUpdater], logger: imit_logger.HierarchicalLogge... | Implement the Python class `LpRegularizer` described below.
Class description:
Applies Lp regularization to a loss function.
Method signatures and docstrings:
- def __init__(self, optimizer: optim.Optimizer, initial_lambda: float, lambda_updater: Optional[updaters.LambdaUpdater], logger: imit_logger.HierarchicalLogge... | 5b0b531bdf6fdfcaab93ff18f454aa1b54bb4355 | <|skeleton|>
class LpRegularizer:
"""Applies Lp regularization to a loss function."""
def __init__(self, optimizer: optim.Optimizer, initial_lambda: float, lambda_updater: Optional[updaters.LambdaUpdater], logger: imit_logger.HierarchicalLogger, p: int, val_split: Optional[float]=None) -> None:
"""Init... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LpRegularizer:
"""Applies Lp regularization to a loss function."""
def __init__(self, optimizer: optim.Optimizer, initial_lambda: float, lambda_updater: Optional[updaters.LambdaUpdater], logger: imit_logger.HierarchicalLogger, p: int, val_split: Optional[float]=None) -> None:
"""Initialize the re... | the_stack_v2_python_sparse | src/imitation/regularization/regularizers.py | HumanCompatibleAI/imitation | train | 936 |
c75ea08d9c8e611a57b0da3eaa909c47d1db8450 | [
"PointCloud.__init__(self)\nAPTMassSpec.__init__(self)\nself.pos = None\nself.identity = None\nself.rand_mass_label = None\nself._data_size = 0\nself._files = {'Data filename': None, 'RRNG filename': None}",
"if data_fname.rsplit('.')[-1] == 'pos':\n self.pos = aptios.read_pos(data_fname)\nelif data_fname.rspl... | <|body_start_0|>
PointCloud.__init__(self)
APTMassSpec.__init__(self)
self.pos = None
self.identity = None
self.rand_mass_label = None
self._data_size = 0
self._files = {'Data filename': None, 'RRNG filename': None}
<|end_body_0|>
<|body_start_1|>
if data... | A class that represent APT data. It inherits the PointCloud and APTMassSpec. More methods should be added to accomodate data analysis of APT point cloud in future. | APTPosData | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class APTPosData:
"""A class that represent APT data. It inherits the PointCloud and APTMassSpec. More methods should be added to accomodate data analysis of APT point cloud in future."""
def __init__(self):
"""Initialize APTPosData class need APT pos data (format [[x0,y0,z0,Da0],...])"""
... | stack_v2_sparse_classes_36k_train_034746 | 5,559 | permissive | [
{
"docstring": "Initialize APTPosData class need APT pos data (format [[x0,y0,z0,Da0],...])",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Load pos file and associated range file.",
"name": "load_data",
"signature": "def load_data(self, data_fname, rrng_fname)... | 4 | stack_v2_sparse_classes_30k_train_001480 | Implement the Python class `APTPosData` described below.
Class description:
A class that represent APT data. It inherits the PointCloud and APTMassSpec. More methods should be added to accomodate data analysis of APT point cloud in future.
Method signatures and docstrings:
- def __init__(self): Initialize APTPosData ... | Implement the Python class `APTPosData` described below.
Class description:
A class that represent APT data. It inherits the PointCloud and APTMassSpec. More methods should be added to accomodate data analysis of APT point cloud in future.
Method signatures and docstrings:
- def __init__(self): Initialize APTPosData ... | c3334d325c85ec8fc6741001d81865929c83beca | <|skeleton|>
class APTPosData:
"""A class that represent APT data. It inherits the PointCloud and APTMassSpec. More methods should be added to accomodate data analysis of APT point cloud in future."""
def __init__(self):
"""Initialize APTPosData class need APT pos data (format [[x0,y0,z0,Da0],...])"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class APTPosData:
"""A class that represent APT data. It inherits the PointCloud and APTMassSpec. More methods should be added to accomodate data analysis of APT point cloud in future."""
def __init__(self):
"""Initialize APTPosData class need APT pos data (format [[x0,y0,z0,Da0],...])"""
Point... | the_stack_v2_python_sparse | OPTICS-APT-GUI/APTPosData.py | pnnl/apt | train | 2 |
f67c0577c557fb3dd5ddcc6e9dc71d18a92b13fc | [
"def rserialize(root, string):\n \"\"\" a recursive helper function for the serialize() function.\"\"\"\n if root is None:\n string += 'None,'\n else:\n string += str(root.val) + ','\n string = rserialize(root.left, string)\n string = rserialize(root.right, string)\n return s... | <|body_start_0|>
def rserialize(root, string):
""" a recursive helper function for the serialize() function."""
if root is None:
string += 'None,'
else:
string += str(root.val) + ','
string = rserialize(root.left, string)
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_034747 | 2,602 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: Node :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 deserialize(se... | 2 | stack_v2_sparse_classes_30k_train_007542 | 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: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Tre... | 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: Node :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype: Tre... | f831fd9603592ae5bee3679924f962a3ebce381c | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: Node :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: Node :rtype: str"""
def rserialize(root, string):
""" a recursive helper function for the serialize() function."""
if root is None:
string += 'None,'
else:
... | the_stack_v2_python_sparse | topic13_tree/T297_Codec/interview.py | GongFuXiong/leetcode | train | 0 | |
f517f3483cd7241e67b53585992b73179c1c2fb9 | [
"if self.task.children:\n current_task = self.task.children[0]\n print('current_task: ', current_task)\n stop_task = getattr(current_task, 'stop_task', None)\n if callable(stop_task):\n stop_task(current_task)\nself.task.clear_widgets()",
"print('Game_Screen/start_task')\nself.remove_task()\nse... | <|body_start_0|>
if self.task.children:
current_task = self.task.children[0]
print('current_task: ', current_task)
stop_task = getattr(current_task, 'stop_task', None)
if callable(stop_task):
stop_task(current_task)
self.task.clear_widgets(... | The screen that shows the current game widgets. | Game_Screen | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Game_Screen:
"""The screen that shows the current game widgets."""
def remove_task(self):
"""Remove all task widgets from the Layout self.task."""
<|body_0|>
def start_task(self, task_id: int):
"""Add task with id task_id. :param task_id: The identifier of the ta... | stack_v2_sparse_classes_36k_train_034748 | 17,786 | permissive | [
{
"docstring": "Remove all task widgets from the Layout self.task.",
"name": "remove_task",
"signature": "def remove_task(self)"
},
{
"docstring": "Add task with id task_id. :param task_id: The identifier of the task to initialize. :type task_id: int",
"name": "start_task",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_002928 | Implement the Python class `Game_Screen` described below.
Class description:
The screen that shows the current game widgets.
Method signatures and docstrings:
- def remove_task(self): Remove all task widgets from the Layout self.task.
- def start_task(self, task_id: int): Add task with id task_id. :param task_id: The... | Implement the Python class `Game_Screen` described below.
Class description:
The screen that shows the current game widgets.
Method signatures and docstrings:
- def remove_task(self): Remove all task widgets from the Layout self.task.
- def start_task(self, task_id: int): Add task with id task_id. :param task_id: The... | 8df61acf8074c80fc8aae950d779647287bff551 | <|skeleton|>
class Game_Screen:
"""The screen that shows the current game widgets."""
def remove_task(self):
"""Remove all task widgets from the Layout self.task."""
<|body_0|>
def start_task(self, task_id: int):
"""Add task with id task_id. :param task_id: The identifier of the ta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Game_Screen:
"""The screen that shows the current game widgets."""
def remove_task(self):
"""Remove all task widgets from the Layout self.task."""
if self.task.children:
current_task = self.task.children[0]
print('current_task: ', current_task)
stop_tas... | the_stack_v2_python_sparse | scripts/velvethat.py | gdies/Velvethat | train | 0 |
8f67d59da3bc32ceb80cb28e394e6aca85cb7f3c | [
"args = [Ndisc.NDISC6_COMMAND_NAME, Ndisc.COUNT_OPTION, str(count), Ndisc.TIMEOUT_OPTION, str(int(timeout) * 1000)]\nif quiet is True:\n args.append(Ndisc.QUIET_OPTION)\nif firstReply is True:\n args.append(Ndisc.FIRST_REPLY_OPTION)\nargs.append(destination)\nargs.append(device)\nrc = Command.execute(logger, ... | <|body_start_0|>
args = [Ndisc.NDISC6_COMMAND_NAME, Ndisc.COUNT_OPTION, str(count), Ndisc.TIMEOUT_OPTION, str(int(timeout) * 1000)]
if quiet is True:
args.append(Ndisc.QUIET_OPTION)
if firstReply is True:
args.append(Ndisc.FIRST_REPLY_OPTION)
args.append(destinati... | Ndisc | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ndisc:
def sendNdiscRequest(logger, device, destination, count=3, timeout=1, quiet=False, firstReply=False, blocking=True):
"""This function sends IPv6 neighbor discovery to a neighbour host Args: logger device - Name of network device where to send ARP REQUEST packets destination - dest... | stack_v2_sparse_classes_36k_train_034749 | 10,343 | no_license | [
{
"docstring": "This function sends IPv6 neighbor discovery to a neighbour host Args: logger device - Name of network device where to send ARP REQUEST packets destination - destination IP to ping count - send ICMPv6 Neighbor Discovery X times timeout - specify a timeout, in seconds, before ndisc exits quiet - q... | 2 | stack_v2_sparse_classes_30k_train_019678 | Implement the Python class `Ndisc` described below.
Class description:
Implement the Ndisc class.
Method signatures and docstrings:
- def sendNdiscRequest(logger, device, destination, count=3, timeout=1, quiet=False, firstReply=False, blocking=True): This function sends IPv6 neighbor discovery to a neighbour host Arg... | Implement the Python class `Ndisc` described below.
Class description:
Implement the Ndisc class.
Method signatures and docstrings:
- def sendNdiscRequest(logger, device, destination, count=3, timeout=1, quiet=False, firstReply=False, blocking=True): This function sends IPv6 neighbor discovery to a neighbour host Arg... | 81bcc74fe7c0ca036ec483f634d7be0bab19a6d0 | <|skeleton|>
class Ndisc:
def sendNdiscRequest(logger, device, destination, count=3, timeout=1, quiet=False, firstReply=False, blocking=True):
"""This function sends IPv6 neighbor discovery to a neighbour host Args: logger device - Name of network device where to send ARP REQUEST packets destination - dest... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ndisc:
def sendNdiscRequest(logger, device, destination, count=3, timeout=1, quiet=False, firstReply=False, blocking=True):
"""This function sends IPv6 neighbor discovery to a neighbour host Args: logger device - Name of network device where to send ARP REQUEST packets destination - destination IP to ... | the_stack_v2_python_sparse | oscar/a/sys/net/lnx/neighbour.py | afeset/miner2-tools | train | 0 | |
04196ffd985a957a79ac589bcef4b42d2e871035 | [
"self._attr_name = f'{client_name} {sensor_type.name}'\nself.type = sensor_type.key\nself.api = api\nself.entity_description = sensor_type",
"try:\n self.api.update()\nexcept requests.exceptions.ConnectionError:\n return\nif self.api.status is None:\n _LOGGER.debug('Update of %s requested, but no status ... | <|body_start_0|>
self._attr_name = f'{client_name} {sensor_type.name}'
self.type = sensor_type.key
self.api = api
self.entity_description = sensor_type
<|end_body_0|>
<|body_start_1|>
try:
self.api.update()
except requests.exceptions.ConnectionError:
... | Representation of a pyLoad sensor. | PyLoadSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyLoadSensor:
"""Representation of a pyLoad sensor."""
def __init__(self, api: PyLoadAPI, sensor_type: SensorEntityDescription, client_name) -> None:
"""Initialize a new pyLoad sensor."""
<|body_0|>
def update(self) -> None:
"""Update state of sensor."""
... | stack_v2_sparse_classes_36k_train_034750 | 5,310 | permissive | [
{
"docstring": "Initialize a new pyLoad sensor.",
"name": "__init__",
"signature": "def __init__(self, api: PyLoadAPI, sensor_type: SensorEntityDescription, client_name) -> None"
},
{
"docstring": "Update state of sensor.",
"name": "update",
"signature": "def update(self) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_004402 | Implement the Python class `PyLoadSensor` described below.
Class description:
Representation of a pyLoad sensor.
Method signatures and docstrings:
- def __init__(self, api: PyLoadAPI, sensor_type: SensorEntityDescription, client_name) -> None: Initialize a new pyLoad sensor.
- def update(self) -> None: Update state o... | Implement the Python class `PyLoadSensor` described below.
Class description:
Representation of a pyLoad sensor.
Method signatures and docstrings:
- def __init__(self, api: PyLoadAPI, sensor_type: SensorEntityDescription, client_name) -> None: Initialize a new pyLoad sensor.
- def update(self) -> None: Update state o... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class PyLoadSensor:
"""Representation of a pyLoad sensor."""
def __init__(self, api: PyLoadAPI, sensor_type: SensorEntityDescription, client_name) -> None:
"""Initialize a new pyLoad sensor."""
<|body_0|>
def update(self) -> None:
"""Update state of sensor."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PyLoadSensor:
"""Representation of a pyLoad sensor."""
def __init__(self, api: PyLoadAPI, sensor_type: SensorEntityDescription, client_name) -> None:
"""Initialize a new pyLoad sensor."""
self._attr_name = f'{client_name} {sensor_type.name}'
self.type = sensor_type.key
sel... | the_stack_v2_python_sparse | homeassistant/components/pyload/sensor.py | home-assistant/core | train | 35,501 |
284d223fc8b651d190bd014dfcfafc922ef7c9b7 | [
"hs = set()\nq = []\nq.append(root)\nwhile q:\n sz = len(q)\n for i in range(sz):\n cur = q.pop(0)\n if k - cur.val in hs:\n return True\n hs.add(cur.val)\n if cur.left:\n q.append(cur.left)\n if cur.right:\n q.append(cur.right)\nreturn False... | <|body_start_0|>
hs = set()
q = []
q.append(root)
while q:
sz = len(q)
for i in range(sz):
cur = q.pop(0)
if k - cur.val in hs:
return True
hs.add(cur.val)
if cur.left:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool BFS+HashSet"""
<|body_0|>
def findTarget1(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool 先中序遍历，再双指针"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_034751 | 1,886 | no_license | [
{
"docstring": ":type root: TreeNode :type k: int :rtype: bool BFS+HashSet",
"name": "findTarget",
"signature": "def findTarget(self, root, k)"
},
{
"docstring": ":type root: TreeNode :type k: int :rtype: bool 先中序遍历，再双指针",
"name": "findTarget1",
"signature": "def findTarget1(self, root, ... | 2 | stack_v2_sparse_classes_30k_train_020900 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTarget(self, root, k): :type root: TreeNode :type k: int :rtype: bool BFS+HashSet
- def findTarget1(self, root, k): :type root: TreeNode :type k: int :rtype: bool 先中序遍历，再... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTarget(self, root, k): :type root: TreeNode :type k: int :rtype: bool BFS+HashSet
- def findTarget1(self, root, k): :type root: TreeNode :type k: int :rtype: bool 先中序遍历，再... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool BFS+HashSet"""
<|body_0|>
def findTarget1(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool 先中序遍历，再双指针"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findTarget(self, root, k):
""":type root: TreeNode :type k: int :rtype: bool BFS+HashSet"""
hs = set()
q = []
q.append(root)
while q:
sz = len(q)
for i in range(sz):
cur = q.pop(0)
if k - cur.val in h... | the_stack_v2_python_sparse | out/production/leetcode/653.两数之和-iv-输入-bst.py | yangyuxiang1996/leetcode | train | 0 | |
1771ed036f391c7282c3e12ab47daf6d6c1a3573 | [
"belong = request.GET.get('belong', 'all')\norder_status = request.GET.get('order_status', '-1')\nmall_type = request.user_profile.webapp_type\nwoid = request.webapp_owner_id\nexport2data = {}\nif belong == 'audit':\n second_nav_name = export.ORDER_AUDIT\n has_order = util.is_has_order(request, True)\n pag... | <|body_start_0|>
belong = request.GET.get('belong', 'all')
order_status = request.GET.get('order_status', '-1')
mall_type = request.user_profile.webapp_type
woid = request.webapp_owner_id
export2data = {}
if belong == 'audit':
second_nav_name = export.ORDER_AU... | 订单列表资源 | OrderList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderList:
"""订单列表资源"""
def get(request):
"""显示订单列表"""
<|body_0|>
def api_get(request):
"""advanced table中订单列表"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
belong = request.GET.get('belong', 'all')
order_status = request.GET.get('orde... | stack_v2_sparse_classes_36k_train_034752 | 36,586 | no_license | [
{
"docstring": "显示订单列表",
"name": "get",
"signature": "def get(request)"
},
{
"docstring": "advanced table中订单列表",
"name": "api_get",
"signature": "def api_get(request)"
}
] | 2 | null | Implement the Python class `OrderList` described below.
Class description:
订单列表资源
Method signatures and docstrings:
- def get(request): 显示订单列表
- def api_get(request): advanced table中订单列表 | Implement the Python class `OrderList` described below.
Class description:
订单列表资源
Method signatures and docstrings:
- def get(request): 显示订单列表
- def api_get(request): advanced table中订单列表
<|skeleton|>
class OrderList:
"""订单列表资源"""
def get(request):
"""显示订单列表"""
<|body_0|>
def api_get(req... | 8b2f7befe92841bcc35e0e60cac5958ef3f3af54 | <|skeleton|>
class OrderList:
"""订单列表资源"""
def get(request):
"""显示订单列表"""
<|body_0|>
def api_get(request):
"""advanced table中订单列表"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderList:
"""订单列表资源"""
def get(request):
"""显示订单列表"""
belong = request.GET.get('belong', 'all')
order_status = request.GET.get('order_status', '-1')
mall_type = request.user_profile.webapp_type
woid = request.webapp_owner_id
export2data = {}
if bel... | the_stack_v2_python_sparse | weapp/mall/order/order.py | chengdg/weizoom | train | 1 |
eb741835f9be1c52d54f8f1a0abe90e43b480d39 | [
"tf.enable_eager_execution()\nif not isinstance(style_image, np.ndarray) or len(style_image.shape) != 3 or style_image.shape[2] != 3:\n raise TypeError('style_image must be a numpy.ndarray with shape (h, w, 3)')\nif not isinstance(content_image, np.ndarray) or len(content_image.shape) != 3 or content_image.shape... | <|body_start_0|>
tf.enable_eager_execution()
if not isinstance(style_image, np.ndarray) or len(style_image.shape) != 3 or style_image.shape[2] != 3:
raise TypeError('style_image must be a numpy.ndarray with shape (h, w, 3)')
if not isinstance(content_image, np.ndarray) or len(content... | A class including model designed to do style transfer between two images | NST | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NST:
"""A class including model designed to do style transfer between two images"""
def __init__(self, style_image, content_image, alpha=10000.0, beta=1):
"""Initialize the class. @style_image: image for style to mimic @content_image: image we're modifying to match style @alpha: lear... | stack_v2_sparse_classes_36k_train_034753 | 2,225 | no_license | [
{
"docstring": "Initialize the class. @style_image: image for style to mimic @content_image: image we're modifying to match style @alpha: learning rate for content @beta: learning rate for style",
"name": "__init__",
"signature": "def __init__(self, style_image, content_image, alpha=10000.0, beta=1)"
... | 2 | null | Implement the Python class `NST` described below.
Class description:
A class including model designed to do style transfer between two images
Method signatures and docstrings:
- def __init__(self, style_image, content_image, alpha=10000.0, beta=1): Initialize the class. @style_image: image for style to mimic @content... | Implement the Python class `NST` described below.
Class description:
A class including model designed to do style transfer between two images
Method signatures and docstrings:
- def __init__(self, style_image, content_image, alpha=10000.0, beta=1): Initialize the class. @style_image: image for style to mimic @content... | 56356c56297d8391bad8a1607eb226489766bc63 | <|skeleton|>
class NST:
"""A class including model designed to do style transfer between two images"""
def __init__(self, style_image, content_image, alpha=10000.0, beta=1):
"""Initialize the class. @style_image: image for style to mimic @content_image: image we're modifying to match style @alpha: lear... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NST:
"""A class including model designed to do style transfer between two images"""
def __init__(self, style_image, content_image, alpha=10000.0, beta=1):
"""Initialize the class. @style_image: image for style to mimic @content_image: image we're modifying to match style @alpha: learning rate for... | the_stack_v2_python_sparse | supervised_learning/0x0C-neural_style_transfer/0-neural_style.py | sidneyriffic/holbertonschool-machine_learning | train | 1 |
f0576a541c8b0f7223af88b7c2a251597800cec0 | [
"signed_up = self.calc_signup(events)\nconsented, cohort = self.calc_consent(events)\nehr_consented = self.calc_ehr_consent(events)\ngror_received = self.calc_gror_received(events)\nbiobank_samples = self.calc_biobank_samples(events)\nphysical_measurements = self.calc_physical_measurements(events)\nthebasics_module... | <|body_start_0|>
signed_up = self.calc_signup(events)
consented, cohort = self.calc_consent(events)
ehr_consented = self.calc_ehr_consent(events)
gror_received = self.calc_gror_received(events)
biobank_samples = self.calc_biobank_samples(events)
physical_measurements = se... | Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sharing stays "Yes" even if there is a negative EHR consent later. | EnrollmentStatusCalculator_v3_0 | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnrollmentStatusCalculator_v3_0:
"""Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sharing stays "Yes" even if there is a neg... | stack_v2_sparse_classes_36k_train_034754 | 6,672 | permissive | [
{
"docstring": "Use the events list to calculate the participant enrolment status and status timestamps. :param events: List of events to use in calculations",
"name": "calculate_from_events",
"signature": "def calculate_from_events(self, events)"
},
{
"docstring": "Save the status timestamp whe... | 4 | stack_v2_sparse_classes_30k_train_006397 | Implement the Python class `EnrollmentStatusCalculator_v3_0` described below.
Class description:
Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sha... | Implement the Python class `EnrollmentStatusCalculator_v3_0` described below.
Class description:
Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sha... | 461ae46aeda21d54de8a91aa5ef677676d5db541 | <|skeleton|>
class EnrollmentStatusCalculator_v3_0:
"""Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sharing stays "Yes" even if there is a neg... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnrollmentStatusCalculator_v3_0:
"""Calculate participant enrollment status. Changes: * Implement Participant PM&B Eligible status * Never downgrade participant status * (v3.1 Feature) : If participant has "Ever" consented to EHR sharing, participant EHR sharing stays "Yes" even if there is a negative EHR con... | the_stack_v2_python_sparse | rdr_service/resource/calculators/participant_enrollment_status_v30.py | all-of-us/raw-data-repository | train | 46 |
b58edda13912fa3f1944e8c2c3b1fb02f01b7afa | [
"cell_method = CellMethod('difference', coords=[coord_name], intervals='1 grid length')\ndiff_cube.add_cell_method(cell_method)\ndiff_cube.attributes['form_of_difference'] = 'forward_difference'\ndiff_cube.rename('difference_of_' + cube_name)",
"points = cube.coord(coord_name).points\nmean_points = (points[1:] + ... | <|body_start_0|>
cell_method = CellMethod('difference', coords=[coord_name], intervals='1 grid length')
diff_cube.add_cell_method(cell_method)
diff_cube.attributes['form_of_difference'] = 'forward_difference'
diff_cube.rename('difference_of_' + cube_name)
<|end_body_0|>
<|body_start_1|>... | Calculate the difference between adjacent grid squares within a cube. The difference is calculated along the x and y axis individually. | DifferenceBetweenAdjacentGridSquares | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DifferenceBetweenAdjacentGridSquares:
"""Calculate the difference between adjacent grid squares within a cube. The difference is calculated along the x and y axis individually."""
def _update_metadata(diff_cube: Cube, coord_name: str, cube_name: str) -> None:
"""Rename cube, add attr... | stack_v2_sparse_classes_36k_train_034755 | 28,733 | permissive | [
{
"docstring": "Rename cube, add attribute and cell method to describe difference. Args: diff_cube coord_name cube_name",
"name": "_update_metadata",
"signature": "def _update_metadata(diff_cube: Cube, coord_name: str, cube_name: str) -> None"
},
{
"docstring": "Put the difference array into a c... | 4 | null | Implement the Python class `DifferenceBetweenAdjacentGridSquares` described below.
Class description:
Calculate the difference between adjacent grid squares within a cube. The difference is calculated along the x and y axis individually.
Method signatures and docstrings:
- def _update_metadata(diff_cube: Cube, coord_... | Implement the Python class `DifferenceBetweenAdjacentGridSquares` described below.
Class description:
Calculate the difference between adjacent grid squares within a cube. The difference is calculated along the x and y axis individually.
Method signatures and docstrings:
- def _update_metadata(diff_cube: Cube, coord_... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class DifferenceBetweenAdjacentGridSquares:
"""Calculate the difference between adjacent grid squares within a cube. The difference is calculated along the x and y axis individually."""
def _update_metadata(diff_cube: Cube, coord_name: str, cube_name: str) -> None:
"""Rename cube, add attr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DifferenceBetweenAdjacentGridSquares:
"""Calculate the difference between adjacent grid squares within a cube. The difference is calculated along the x and y axis individually."""
def _update_metadata(diff_cube: Cube, coord_name: str, cube_name: str) -> None:
"""Rename cube, add attribute and cel... | the_stack_v2_python_sparse | improver/utilities/spatial.py | metoppv/improver | train | 101 |
3999c607a91b596888959cea48bf199fad229f02 | [
"contents = super().proc_playlist(contents)\nsoup = BeautifulSoup(contents, self.html_parser)\ndata = soup.find('script', id='__NEXT_DATA__')\nreturn data.string",
"log.debug(f'Parsing json for {playlist.rel_path}')\nwith open(playlist.file) as f:\n pl_info = json.load(f)\nif 'props' in pl_info:\n pl_info =... | <|body_start_0|>
contents = super().proc_playlist(contents)
soup = BeautifulSoup(contents, self.html_parser)
data = soup.find('script', id='__NEXT_DATA__')
return data.string
<|end_body_0|>
<|body_start_1|>
log.debug(f'Parsing json for {playlist.rel_path}')
with open(pla... | ParserC24C | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParserC24C:
def proc_playlist(self, contents: str) -> str:
"""Process raw playlist contents downloaded from URL before saving to file. For the C24C/MPR3 implementation, we extract the json data from the html input."""
<|body_0|>
def iter_program_plays(self, playlist: Playlis... | stack_v2_sparse_classes_36k_train_034756 | 6,114 | permissive | [
{
"docstring": "Process raw playlist contents downloaded from URL before saving to file. For the C24C/MPR3 implementation, we extract the json data from the html input.",
"name": "proc_playlist",
"signature": "def proc_playlist(self, contents: str) -> str"
},
{
"docstring": "This is the implemen... | 5 | stack_v2_sparse_classes_30k_val_001137 | Implement the Python class `ParserC24C` described below.
Class description:
Implement the ParserC24C class.
Method signatures and docstrings:
- def proc_playlist(self, contents: str) -> str: Process raw playlist contents downloaded from URL before saving to file. For the C24C/MPR3 implementation, we extract the json ... | Implement the Python class `ParserC24C` described below.
Class description:
Implement the ParserC24C class.
Method signatures and docstrings:
- def proc_playlist(self, contents: str) -> str: Process raw playlist contents downloaded from URL before saving to file. For the C24C/MPR3 implementation, we extract the json ... | 4f6eea197ce966c2118d534f5dce74109fe53244 | <|skeleton|>
class ParserC24C:
def proc_playlist(self, contents: str) -> str:
"""Process raw playlist contents downloaded from URL before saving to file. For the C24C/MPR3 implementation, we extract the json data from the html input."""
<|body_0|>
def iter_program_plays(self, playlist: Playlis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParserC24C:
def proc_playlist(self, contents: str) -> str:
"""Process raw playlist contents downloaded from URL before saving to file. For the C24C/MPR3 implementation, we extract the json data from the html input."""
contents = super().proc_playlist(contents)
soup = BeautifulSoup(cont... | the_stack_v2_python_sparse | cm/parser/c24c.py | crashka/cm | train | 0 | |
bed19f27d6f253501d358fdb00bec88092c7f937 | [
"self.parent = None\nself.value = value\nself.left = left\nself.right = right\nif left:\n self.left.parent = self\nif right:\n self.right.parent = self",
"if not self:\n return None\nlistNodes = [self]\nif self.left:\n listNodes = self.left.inorderList() + listNodes\nif self.right:\n listNodes = li... | <|body_start_0|>
self.parent = None
self.value = value
self.left = left
self.right = right
if left:
self.left.parent = self
if right:
self.right.parent = self
<|end_body_0|>
<|body_start_1|>
if not self:
return None
lis... | Node class for a binary tree. | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
<|body_0|>
def inorderList(self):
"""Return an ordered list of nodes."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.par... | stack_v2_sparse_classes_36k_train_034757 | 1,605 | no_license | [
{
"docstring": "Initialize the node.",
"name": "__init__",
"signature": "def __init__(self, value, left=None, right=None)"
},
{
"docstring": "Return an ordered list of nodes.",
"name": "inorderList",
"signature": "def inorderList(self)"
}
] | 2 | null | Implement the Python class `Node` described below.
Class description:
Node class for a binary tree.
Method signatures and docstrings:
- def __init__(self, value, left=None, right=None): Initialize the node.
- def inorderList(self): Return an ordered list of nodes. | Implement the Python class `Node` described below.
Class description:
Node class for a binary tree.
Method signatures and docstrings:
- def __init__(self, value, left=None, right=None): Initialize the node.
- def inorderList(self): Return an ordered list of nodes.
<|skeleton|>
class Node:
"""Node class for a bin... | 97eae3ee806756f4d646d600f434b1e68164ad34 | <|skeleton|>
class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
<|body_0|>
def inorderList(self):
"""Return an ordered list of nodes."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
"""Node class for a binary tree."""
def __init__(self, value, left=None, right=None):
"""Initialize the node."""
self.parent = None
self.value = value
self.left = left
self.right = right
if left:
self.left.parent = self
if right:
... | the_stack_v2_python_sparse | Python/2019_05_28_Problem_133_Inorder_Successor.py | BaoCaiH/Daily_Coding_Problem | train | 0 |
22683dfc9fcdc10d726fb3818c8b0266c0c75ff7 | [
"Runtime.__blockchain = None\nRuntime.__crypto = {}\nRuntime.__keystore = {}\nRuntime.__prover = None",
"if Runtime.__blockchain is None:\n Runtime.__blockchain = _blockchain_classes[cfg.blockchain_backend]()\n from zkay.transaction.types import AddressValue\n AddressValue.get_balance = Runtime.__blockch... | <|body_start_0|>
Runtime.__blockchain = None
Runtime.__crypto = {}
Runtime.__keystore = {}
Runtime.__prover = None
<|end_body_0|>
<|body_start_1|>
if Runtime.__blockchain is None:
Runtime.__blockchain = _blockchain_classes[cfg.blockchain_backend]()
from z... | Provides global access to singleton runtime API backend instances. See interface.py for more information. The global configuration in config.py determines which backends are made available via the Runtime class. | Runtime | [
"LicenseRef-scancode-unknown-license-reference",
"LGPL-3.0-only",
"MIT",
"LGPL-2.0-or-later",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Runtime:
"""Provides global access to singleton runtime API backend instances. See interface.py for more information. The global configuration in config.py determines which backends are made available via the Runtime class."""
def reset():
"""Reboot the runtime. When a new backend is... | stack_v2_sparse_classes_36k_train_034758 | 3,662 | permissive | [
{
"docstring": "Reboot the runtime. When a new backend is selected in the configuration, it will only be loaded after a runtime reset.",
"name": "reset",
"signature": "def reset()"
},
{
"docstring": "Return singleton object which implements ZkayBlockchainInterface.",
"name": "blockchain",
... | 5 | null | Implement the Python class `Runtime` described below.
Class description:
Provides global access to singleton runtime API backend instances. See interface.py for more information. The global configuration in config.py determines which backends are made available via the Runtime class.
Method signatures and docstrings:... | Implement the Python class `Runtime` described below.
Class description:
Provides global access to singleton runtime API backend instances. See interface.py for more information. The global configuration in config.py determines which backends are made available via the Runtime class.
Method signatures and docstrings:... | 920e883c095f456770c03606021c728b34497f42 | <|skeleton|>
class Runtime:
"""Provides global access to singleton runtime API backend instances. See interface.py for more information. The global configuration in config.py determines which backends are made available via the Runtime class."""
def reset():
"""Reboot the runtime. When a new backend is... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Runtime:
"""Provides global access to singleton runtime API backend instances. See interface.py for more information. The global configuration in config.py determines which backends are made available via the Runtime class."""
def reset():
"""Reboot the runtime. When a new backend is selected in ... | the_stack_v2_python_sparse | zkay/transaction/runtime.py | eth-sri/zkay | train | 75 |
4215c5a4c071d593a57161b0c0d4abb4a615ec80 | [
"left, right, area = (0, len(height) - 1, 0)\nwhile left < right:\n area = max(area, min(height[left], height[right]) * (right - left))\n if height[left] < height[right]:\n left += 1\n else:\n right -= 1\nreturn area",
"left, right, area = (0, len(height) - 1, 0)\nwhile left < right:\n m... | <|body_start_0|>
left, right, area = (0, len(height) - 1, 0)
while left < right:
area = max(area, min(height[left], height[right]) * (right - left))
if height[left] < height[right]:
left += 1
else:
right -= 1
return area
<|end_b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea1(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
left, right, area = (0, len(height) - 1, 0)
... | stack_v2_sparse_classes_36k_train_034759 | 955 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea",
"signature": "def maxArea(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea1",
"signature": "def maxArea1(self, height)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013557 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height): :type height: List[int] :rtype: int
- def maxArea1(self, height): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height): :type height: List[int] :rtype: int
- def maxArea1(self, height): :type height: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxArea(se... | b8ec1350e904665f1375c29a53f443ecf262d723 | <|skeleton|>
class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea1(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
left, right, area = (0, len(height) - 1, 0)
while left < right:
area = max(area, min(height[left], height[right]) * (right - left))
if height[left] < height[right]:
le... | the_stack_v2_python_sparse | leetcode/011盛最多水的容器.py | ShawDa/Coding | train | 0 | |
459495c71c8b774814ea3d6f06304987de24bdb8 | [
"type_mappings = [(Text, 'string'), (bytes, 'data'), (bool, 'boolean'), (int, 'integer'), (dict, 'dict'), (float, 'float')]\nif value is None:\n self.none = 'None'\nelif isinstance(value, rdfvalue.RDFValue):\n self.rdf_value.data = value.SerializeToBytes()\n self.rdf_value.name = value.__class__.__name__\n... | <|body_start_0|>
type_mappings = [(Text, 'string'), (bytes, 'data'), (bool, 'boolean'), (int, 'integer'), (dict, 'dict'), (float, 'float')]
if value is None:
self.none = 'None'
elif isinstance(value, rdfvalue.RDFValue):
self.rdf_value.data = value.SerializeToBytes()
... | Wrapper class for DataBlob protobuf. | DataBlob | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataBlob:
"""Wrapper class for DataBlob protobuf."""
def SetValue(self, value, raise_on_error=True):
"""Receives a value and fills it into a DataBlob. Args: value: value to set raise_on_error: if True, raise if we can't serialize. If False, set the key to an error string. Returns: se... | stack_v2_sparse_classes_36k_train_034760 | 15,855 | permissive | [
{
"docstring": "Receives a value and fills it into a DataBlob. Args: value: value to set raise_on_error: if True, raise if we can't serialize. If False, set the key to an error string. Returns: self Raises: TypeError: if the value can't be serialized and raise_on_error is True",
"name": "SetValue",
"sig... | 2 | null | Implement the Python class `DataBlob` described below.
Class description:
Wrapper class for DataBlob protobuf.
Method signatures and docstrings:
- def SetValue(self, value, raise_on_error=True): Receives a value and fills it into a DataBlob. Args: value: value to set raise_on_error: if True, raise if we can't seriali... | Implement the Python class `DataBlob` described below.
Class description:
Wrapper class for DataBlob protobuf.
Method signatures and docstrings:
- def SetValue(self, value, raise_on_error=True): Receives a value and fills it into a DataBlob. Args: value: value to set raise_on_error: if True, raise if we can't seriali... | 44c0eb8c938302098ef7efae8cfd6b90bcfbb2d6 | <|skeleton|>
class DataBlob:
"""Wrapper class for DataBlob protobuf."""
def SetValue(self, value, raise_on_error=True):
"""Receives a value and fills it into a DataBlob. Args: value: value to set raise_on_error: if True, raise if we can't serialize. If False, set the key to an error string. Returns: se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataBlob:
"""Wrapper class for DataBlob protobuf."""
def SetValue(self, value, raise_on_error=True):
"""Receives a value and fills it into a DataBlob. Args: value: value to set raise_on_error: if True, raise if we can't serialize. If False, set the key to an error string. Returns: self Raises: Ty... | the_stack_v2_python_sparse | grr/core/grr_response_core/lib/rdfvalues/protodict.py | google/grr | train | 4,683 |
752baf5385fe36e92276b92fec051107d7cb65a8 | [
"if root is None:\n return '[]'\nqueue = [root]\nres = []\nwhile len(queue) != 0:\n current = queue[0]\n if isinstance(current, TreeNode):\n res.append(current.val)\n else:\n res.append(current)\n queue.pop(0)\n if current != None:\n queue.append(current.left)\n queue.a... | <|body_start_0|>
if root is None:
return '[]'
queue = [root]
res = []
while len(queue) != 0:
current = queue[0]
if isinstance(current, TreeNode):
res.append(current.val)
else:
res.append(current)
... | Encode and decode a binary tree. | BinTreeCodec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinTreeCodec:
"""Encode and decode a binary tree."""
def serialize(cls, root: 'TreeNode'):
"""Encodes a tree to a single string. Args: root: Root node of the binary tree Returns: A serialized string of the input tree."""
<|body_0|>
def deserialize(cls, data: str):
... | stack_v2_sparse_classes_36k_train_034761 | 7,998 | permissive | [
{
"docstring": "Encodes a tree to a single string. Args: root: Root node of the binary tree Returns: A serialized string of the input tree.",
"name": "serialize",
"signature": "def serialize(cls, root: 'TreeNode')"
},
{
"docstring": "Decodes your encoded data to tree. Args: data: A serialized st... | 2 | stack_v2_sparse_classes_30k_val_000794 | Implement the Python class `BinTreeCodec` described below.
Class description:
Encode and decode a binary tree.
Method signatures and docstrings:
- def serialize(cls, root: 'TreeNode'): Encodes a tree to a single string. Args: root: Root node of the binary tree Returns: A serialized string of the input tree.
- def des... | Implement the Python class `BinTreeCodec` described below.
Class description:
Encode and decode a binary tree.
Method signatures and docstrings:
- def serialize(cls, root: 'TreeNode'): Encodes a tree to a single string. Args: root: Root node of the binary tree Returns: A serialized string of the input tree.
- def des... | 9adbe5fc2bce71f4c09ccf83079c44699c27fce4 | <|skeleton|>
class BinTreeCodec:
"""Encode and decode a binary tree."""
def serialize(cls, root: 'TreeNode'):
"""Encodes a tree to a single string. Args: root: Root node of the binary tree Returns: A serialized string of the input tree."""
<|body_0|>
def deserialize(cls, data: str):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinTreeCodec:
"""Encode and decode a binary tree."""
def serialize(cls, root: 'TreeNode'):
"""Encodes a tree to a single string. Args: root: Root node of the binary tree Returns: A serialized string of the input tree."""
if root is None:
return '[]'
queue = [root]
... | the_stack_v2_python_sparse | data_structures/binary_tree.py | 1lch2/PythonExercise | train | 1 |
2a64914a782066498ca488e831698892cbece572 | [
"super().__init__()\nlogging_levels = {val: val for val in LEVELS.values()}\nlogging_levels.update(LEVELS)\nself._ignore_exceptions = []\nfor exc_name, exc_level in ignore_exceptions:\n try:\n self._ignore_exceptions.append((logging_levels[exc_level], exc_name))\n except KeyError as err:\n raise... | <|body_start_0|>
super().__init__()
logging_levels = {val: val for val in LEVELS.values()}
logging_levels.update(LEVELS)
self._ignore_exceptions = []
for exc_name, exc_level in ignore_exceptions:
try:
self._ignore_exceptions.append((logging_levels[exc_... | Filter out the specified exceptions with specified logging level. | ExceptionFilter | [
"BSD-2-Clause",
"BSD-3-Clause",
"BSD-2-Clause-Views"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExceptionFilter:
"""Filter out the specified exceptions with specified logging level."""
def __init__(self, ignore_exceptions):
"""Configure filtering out of the specified exceptions with specified logging level. Note if there are multiple exceptions that have the same name this will... | stack_v2_sparse_classes_36k_train_034762 | 1,804 | permissive | [
{
"docstring": "Configure filtering out of the specified exceptions with specified logging level. Note if there are multiple exceptions that have the same name this will filter out all exceptions with that name. ignore_exceptions: a tuple of tuples ((exception name, loglevel)) example: ((\"ReadTimeout\", \"WARN... | 2 | stack_v2_sparse_classes_30k_train_020440 | Implement the Python class `ExceptionFilter` described below.
Class description:
Filter out the specified exceptions with specified logging level.
Method signatures and docstrings:
- def __init__(self, ignore_exceptions): Configure filtering out of the specified exceptions with specified logging level. Note if there ... | Implement the Python class `ExceptionFilter` described below.
Class description:
Filter out the specified exceptions with specified logging level.
Method signatures and docstrings:
- def __init__(self, ignore_exceptions): Configure filtering out of the specified exceptions with specified logging level. Note if there ... | 232446d776fdb906d2fb253cf0a409c6813a08d6 | <|skeleton|>
class ExceptionFilter:
"""Filter out the specified exceptions with specified logging level."""
def __init__(self, ignore_exceptions):
"""Configure filtering out of the specified exceptions with specified logging level. Note if there are multiple exceptions that have the same name this will... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExceptionFilter:
"""Filter out the specified exceptions with specified logging level."""
def __init__(self, ignore_exceptions):
"""Configure filtering out of the specified exceptions with specified logging level. Note if there are multiple exceptions that have the same name this will filter out a... | the_stack_v2_python_sparse | h/util/logging_filters.py | hypothesis/h | train | 2,558 |
ece465c4868815509ae5749ddab7226c9444c522 | [
"n = 0\nt = head\nwhile t:\n n += 1\n t = t.next\nmid = n // 2\nphead = head\nfor _ in range(mid):\n phead = phead.next\np = phead\nq = phead.next\nphead.next = None\nwhile q:\n r = q.next\n q.next = p\n p = q\n q = r\nfor _ in range(mid):\n if head.val != p.val:\n return False\n h... | <|body_start_0|>
n = 0
t = head
while t:
n += 1
t = t.next
mid = n // 2
phead = head
for _ in range(mid):
phead = phead.next
p = phead
q = phead.next
phead.next = None
while q:
r = q.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPalindrome(self, head):
"""时间复杂度:O(n) 空间复杂度:O(1) :param head: :return:"""
<|body_0|>
def isPalindrome_3(self, head):
"""利用辅助空间 :type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = 0
t = head
... | stack_v2_sparse_classes_36k_train_034763 | 1,798 | no_license | [
{
"docstring": "时间复杂度:O(n) 空间复杂度:O(1) :param head: :return:",
"name": "isPalindrome",
"signature": "def isPalindrome(self, head)"
},
{
"docstring": "利用辅助空间 :type head: ListNode :rtype: bool",
"name": "isPalindrome_3",
"signature": "def isPalindrome_3(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001139 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head): 时间复杂度:O(n) 空间复杂度:O(1) :param head: :return:
- def isPalindrome_3(self, head): 利用辅助空间 :type head: ListNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPalindrome(self, head): 时间复杂度:O(n) 空间复杂度:O(1) :param head: :return:
- def isPalindrome_3(self, head): 利用辅助空间 :type head: ListNode :rtype: bool
<|skeleton|>
class Solution:... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def isPalindrome(self, head):
"""时间复杂度:O(n) 空间复杂度:O(1) :param head: :return:"""
<|body_0|>
def isPalindrome_3(self, head):
"""利用辅助空间 :type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPalindrome(self, head):
"""时间复杂度:O(n) 空间复杂度:O(1) :param head: :return:"""
n = 0
t = head
while t:
n += 1
t = t.next
mid = n // 2
phead = head
for _ in range(mid):
phead = phead.next
p = phead
... | the_stack_v2_python_sparse | 234_回文链表.py | lovehhf/LeetCode | train | 0 | |
099cb67cd295cd3c425fc8aaac0ce577b8b72c80 | [
"downsample_raito = H // SparseHelper._cur_active.shape[-1]\nactive_ex = SparseHelper._cur_active.repeat_interleave(downsample_raito, 2).repeat_interleave(downsample_raito, 3)\nreturn active_ex if returning_active_map else active_ex.squeeze(1).nonzero(as_tuple=True)",
"x = super(type(self), self).forward(x)\nx *=... | <|body_start_0|>
downsample_raito = H // SparseHelper._cur_active.shape[-1]
active_ex = SparseHelper._cur_active.repeat_interleave(downsample_raito, 2).repeat_interleave(downsample_raito, 3)
return active_ex if returning_active_map else active_ex.squeeze(1).nonzero(as_tuple=True)
<|end_body_0|>
... | The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc. | SparseHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparseHelper:
"""The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc."""
def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor:
"""Get current active map with (B, 1, f, f) shape or index format."""
... | stack_v2_sparse_classes_36k_train_034764 | 5,428 | permissive | [
{
"docstring": "Get current active map with (B, 1, f, f) shape or index format.",
"name": "_get_active_map_or_index",
"signature": "def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor"
},
{
"docstring": "Sparse convolution forward function.",
"name": "sp_con... | 3 | stack_v2_sparse_classes_30k_train_009284 | Implement the Python class `SparseHelper` described below.
Class description:
The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc.
Method signatures and docstrings:
- def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor: Get current... | Implement the Python class `SparseHelper` described below.
Class description:
The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc.
Method signatures and docstrings:
- def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor: Get current... | d2ccc44a2c8e5d49bb26187aff42f2abc90aee28 | <|skeleton|>
class SparseHelper:
"""The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc."""
def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor:
"""Get current active map with (B, 1, f, f) shape or index format."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SparseHelper:
"""The helper to compute sparse operation with pytorch, such as sparse convlolution, sparse batch norm, etc."""
def _get_active_map_or_index(H: int, returning_active_map: bool=True) -> torch.Tensor:
"""Get current active map with (B, 1, f, f) shape or index format."""
downsa... | the_stack_v2_python_sparse | mmpretrain/models/utils/sparse_modules.py | open-mmlab/mmpretrain | train | 652 |
4ceb25d102a01d160b316ff965f95e2cbca8c3f5 | [
"self.rate = self.DEFAULT_RATE\nif 'rate' in queue_info:\n self.rate = queue_info['rate']\nself.task_age_limit = self.DEFAULT_AGE_LIMIT\nself.min_backoff_seconds = self.DEFAULT_MIN_BACKOFF\nself.max_backoff_seconds = self.DEFAULT_MAX_BACKOFF\nself.max_doublings = self.DEFAULT_MAX_DOUBLINGS\nif 'retry_parameters'... | <|body_start_0|>
self.rate = self.DEFAULT_RATE
if 'rate' in queue_info:
self.rate = queue_info['rate']
self.task_age_limit = self.DEFAULT_AGE_LIMIT
self.min_backoff_seconds = self.DEFAULT_MIN_BACKOFF
self.max_backoff_seconds = self.DEFAULT_MAX_BACKOFF
self.max... | PushQueue | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PushQueue:
def __init__(self, queue_info, app):
"""Create a PushQueue object. Args: queue_info: A dictionary containing queue info. app: A string containing the application ID."""
<|body_0|>
def __repr__(self):
"""Generates a string representation of the queue. Retur... | stack_v2_sparse_classes_36k_train_034765 | 29,716 | permissive | [
{
"docstring": "Create a PushQueue object. Args: queue_info: A dictionary containing queue info. app: A string containing the application ID.",
"name": "__init__",
"signature": "def __init__(self, queue_info, app)"
},
{
"docstring": "Generates a string representation of the queue. Returns: A str... | 2 | stack_v2_sparse_classes_30k_train_007606 | Implement the Python class `PushQueue` described below.
Class description:
Implement the PushQueue class.
Method signatures and docstrings:
- def __init__(self, queue_info, app): Create a PushQueue object. Args: queue_info: A dictionary containing queue info. app: A string containing the application ID.
- def __repr_... | Implement the Python class `PushQueue` described below.
Class description:
Implement the PushQueue class.
Method signatures and docstrings:
- def __init__(self, queue_info, app): Create a PushQueue object. Args: queue_info: A dictionary containing queue info. app: A string containing the application ID.
- def __repr_... | c24ddfd987c8eed8ed8864cc839cc0556a8af3c7 | <|skeleton|>
class PushQueue:
def __init__(self, queue_info, app):
"""Create a PushQueue object. Args: queue_info: A dictionary containing queue info. app: A string containing the application ID."""
<|body_0|>
def __repr__(self):
"""Generates a string representation of the queue. Retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PushQueue:
def __init__(self, queue_info, app):
"""Create a PushQueue object. Args: queue_info: A dictionary containing queue info. app: A string containing the application ID."""
self.rate = self.DEFAULT_RATE
if 'rate' in queue_info:
self.rate = queue_info['rate']
... | the_stack_v2_python_sparse | AppTaskQueue/appscale/taskqueue/queue.py | christianbaun/appscale | train | 2 | |
03a8dd03eacea4683ee3b2d017aaf8a5e64eab21 | [
"security = getSecurityManager()\nwant_referer = REQUEST['URL1'] + '/manage_owner'\ngot_referer = '%s://%s%s' % parse.urlparse(REQUEST['HTTP_REFERER'])[:3]\n__traceback_info__ = (want_referer, got_referer)\nif want_referer != got_referer or security.calledByExecutable():\n raise Unauthorized('manage_takeOwnershi... | <|body_start_0|>
security = getSecurityManager()
want_referer = REQUEST['URL1'] + '/manage_owner'
got_referer = '%s://%s%s' % parse.urlparse(REQUEST['HTTP_REFERER'])[:3]
__traceback_info__ = (want_referer, got_referer)
if want_referer != got_referer or security.calledByExecutable... | Owned | [
"ZPL-2.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Owned:
def manage_takeOwnership(self, REQUEST, RESPONSE, recursive=0):
"""Take ownership (responsibility) for an object. If 'recursive' is true, then also take ownership of all sub-objects."""
<|body_0|>
def manage_changeOwnershipType(self, explicit=1, RESPONSE=None, REQUEST... | stack_v2_sparse_classes_36k_train_034766 | 3,508 | permissive | [
{
"docstring": "Take ownership (responsibility) for an object. If 'recursive' is true, then also take ownership of all sub-objects.",
"name": "manage_takeOwnership",
"signature": "def manage_takeOwnership(self, REQUEST, RESPONSE, recursive=0)"
},
{
"docstring": "Change the type (implicit or expl... | 2 | stack_v2_sparse_classes_30k_train_005626 | Implement the Python class `Owned` described below.
Class description:
Implement the Owned class.
Method signatures and docstrings:
- def manage_takeOwnership(self, REQUEST, RESPONSE, recursive=0): Take ownership (responsibility) for an object. If 'recursive' is true, then also take ownership of all sub-objects.
- de... | Implement the Python class `Owned` described below.
Class description:
Implement the Owned class.
Method signatures and docstrings:
- def manage_takeOwnership(self, REQUEST, RESPONSE, recursive=0): Take ownership (responsibility) for an object. If 'recursive' is true, then also take ownership of all sub-objects.
- de... | c31b1c635e85a1766f2666cb0bd117337ae5fa67 | <|skeleton|>
class Owned:
def manage_takeOwnership(self, REQUEST, RESPONSE, recursive=0):
"""Take ownership (responsibility) for an object. If 'recursive' is true, then also take ownership of all sub-objects."""
<|body_0|>
def manage_changeOwnershipType(self, explicit=1, RESPONSE=None, REQUEST... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Owned:
def manage_takeOwnership(self, REQUEST, RESPONSE, recursive=0):
"""Take ownership (responsibility) for an object. If 'recursive' is true, then also take ownership of all sub-objects."""
security = getSecurityManager()
want_referer = REQUEST['URL1'] + '/manage_owner'
got_... | the_stack_v2_python_sparse | src/OFS/owner.py | zopefoundation/Zope | train | 335 | |
08d94b72f5650e0e37321b6c4536d2359d4840f8 | [
"h, v = SpatialSvdModuleSplitter.get_svd_matrices(layer, rank)\nconv_a_stride, conv_b_stride = get_strides_for_split_conv_ops(op=layer.module)\nwith layer.model.graph.as_default():\n last_slash_index = layer.module.name.rfind('/')\n data_format = layer.module.get_attr('data_format').decode('utf-8')\n if da... | <|body_start_0|>
h, v = SpatialSvdModuleSplitter.get_svd_matrices(layer, rank)
conv_a_stride, conv_b_stride = get_strides_for_split_conv_ops(op=layer.module)
with layer.model.graph.as_default():
last_slash_index = layer.module.name.rfind('/')
data_format = layer.module.ge... | Spatial SVD module splitter | SpatialSvdModuleSplitter | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpatialSvdModuleSplitter:
"""Spatial SVD module splitter"""
def split_module(layer: Layer, rank: int) -> (tf.Operation, tf.Operation):
""":param layer: Module to be split :param rank: rank for splitting :return: Two split modules"""
<|body_0|>
def get_svd_matrices(layer:... | stack_v2_sparse_classes_36k_train_034767 | 6,069 | permissive | [
{
"docstring": ":param layer: Module to be split :param rank: rank for splitting :return: Two split modules",
"name": "split_module",
"signature": "def split_module(layer: Layer, rank: int) -> (tf.Operation, tf.Operation)"
},
{
"docstring": ":param layer: Module to be split :param rank: rank for... | 2 | null | Implement the Python class `SpatialSvdModuleSplitter` described below.
Class description:
Spatial SVD module splitter
Method signatures and docstrings:
- def split_module(layer: Layer, rank: int) -> (tf.Operation, tf.Operation): :param layer: Module to be split :param rank: rank for splitting :return: Two split modul... | Implement the Python class `SpatialSvdModuleSplitter` described below.
Class description:
Spatial SVD module splitter
Method signatures and docstrings:
- def split_module(layer: Layer, rank: int) -> (tf.Operation, tf.Operation): :param layer: Module to be split :param rank: rank for splitting :return: Two split modul... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class SpatialSvdModuleSplitter:
"""Spatial SVD module splitter"""
def split_module(layer: Layer, rank: int) -> (tf.Operation, tf.Operation):
""":param layer: Module to be split :param rank: rank for splitting :return: Two split modules"""
<|body_0|>
def get_svd_matrices(layer:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpatialSvdModuleSplitter:
"""Spatial SVD module splitter"""
def split_module(layer: Layer, rank: int) -> (tf.Operation, tf.Operation):
""":param layer: Module to be split :param rank: rank for splitting :return: Two split modules"""
h, v = SpatialSvdModuleSplitter.get_svd_matrices(layer, ... | the_stack_v2_python_sparse | TrainingExtensions/tensorflow/src/python/aimet_tensorflow/svd_spiltter.py | quic/aimet | train | 1,676 |
feca7da6c9d767b56d4471369542a0eab199548c | [
"BackPropagation.__init__(self, neural_network, learning_rate, max_error, max_iterations)\nself.momentum = momentum\nself.previous_weight_values = {}\n':type : dict[synapyse.base.connection.Connection, float]'",
"for connection in neuron.input_connections.values():\n connection_input = connection.origin.output... | <|body_start_0|>
BackPropagation.__init__(self, neural_network, learning_rate, max_error, max_iterations)
self.momentum = momentum
self.previous_weight_values = {}
':type : dict[synapyse.base.connection.Connection, float]'
<|end_body_0|>
<|body_start_1|>
for connection in neuron... | MomentumBackPropagation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MomentumBackPropagation:
def __init__(self, neural_network, learning_rate, momentum, max_error, max_iterations=None):
""":type neural_network: synapyse.base.neural_network.NeuralNetwork :type learning_rate: float :type momentum: float :type max_error: float :type max_iterations: int"""
... | stack_v2_sparse_classes_36k_train_034768 | 1,483 | permissive | [
{
"docstring": ":type neural_network: synapyse.base.neural_network.NeuralNetwork :type learning_rate: float :type momentum: float :type max_error: float :type max_iterations: int",
"name": "__init__",
"signature": "def __init__(self, neural_network, learning_rate, momentum, max_error, max_iterations=Non... | 2 | stack_v2_sparse_classes_30k_train_019361 | Implement the Python class `MomentumBackPropagation` described below.
Class description:
Implement the MomentumBackPropagation class.
Method signatures and docstrings:
- def __init__(self, neural_network, learning_rate, momentum, max_error, max_iterations=None): :type neural_network: synapyse.base.neural_network.Neur... | Implement the Python class `MomentumBackPropagation` described below.
Class description:
Implement the MomentumBackPropagation class.
Method signatures and docstrings:
- def __init__(self, neural_network, learning_rate, momentum, max_error, max_iterations=None): :type neural_network: synapyse.base.neural_network.Neur... | 8c9ff53ede2d83af27ce771ce1b6ea6a32155b02 | <|skeleton|>
class MomentumBackPropagation:
def __init__(self, neural_network, learning_rate, momentum, max_error, max_iterations=None):
""":type neural_network: synapyse.base.neural_network.NeuralNetwork :type learning_rate: float :type momentum: float :type max_error: float :type max_iterations: int"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MomentumBackPropagation:
def __init__(self, neural_network, learning_rate, momentum, max_error, max_iterations=None):
""":type neural_network: synapyse.base.neural_network.NeuralNetwork :type learning_rate: float :type momentum: float :type max_error: float :type max_iterations: int"""
BackPro... | the_stack_v2_python_sparse | synapyse/impl/learning/momentum_back_propagation.py | dougefr/synapyse | train | 4 | |
9fe18658a43d2b99dd84819b1e9aa2b603f41a22 | [
"super(CollaQMultiHeadAttention, self).__init__()\nself.act = nn.ReLU()\nself.n_head = n_head\nself.d_k = d_k\nself.d_v = d_v\nself.w_qs = nn.Linear(d_model_q, n_head * d_k)\nself.w_ks = nn.Linear(d_model_v, n_head * d_k)\nself.w_vs = nn.Linear(d_model_v, n_head * d_v)\nself.fc1 = fc_block(n_head * d_v, n_head * d_... | <|body_start_0|>
super(CollaQMultiHeadAttention, self).__init__()
self.act = nn.ReLU()
self.n_head = n_head
self.d_k = d_k
self.d_v = d_v
self.w_qs = nn.Linear(d_model_q, n_head * d_k)
self.w_ks = nn.Linear(d_model_v, n_head * d_k)
self.w_vs = nn.Linear(d_... | Overview: The head of collaq attention module. Interface: __init__, forward | CollaQMultiHeadAttention | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollaQMultiHeadAttention:
"""Overview: The head of collaq attention module. Interface: __init__, forward"""
def __init__(self, n_head: int, d_model_q: int, d_model_v: int, d_k: int, d_v: int, d_out: int, dropout: float=0.0):
"""Overview: initialize the head of collaq attention module... | stack_v2_sparse_classes_36k_train_034769 | 27,383 | permissive | [
{
"docstring": "Overview: initialize the head of collaq attention module Arguments: - n_head (:obj:`int`): the num of head - d_model_q (:obj:`int`): the size of input q - d_model_v (:obj:`int`): the size of input v - d_k (:obj:`int`): the size of k, used by Scaled Dot Product Attention - d_v (:obj:`int`): the s... | 2 | stack_v2_sparse_classes_30k_train_006851 | Implement the Python class `CollaQMultiHeadAttention` described below.
Class description:
Overview: The head of collaq attention module. Interface: __init__, forward
Method signatures and docstrings:
- def __init__(self, n_head: int, d_model_q: int, d_model_v: int, d_k: int, d_v: int, d_out: int, dropout: float=0.0):... | Implement the Python class `CollaQMultiHeadAttention` described below.
Class description:
Overview: The head of collaq attention module. Interface: __init__, forward
Method signatures and docstrings:
- def __init__(self, n_head: int, d_model_q: int, d_model_v: int, d_k: int, d_v: int, d_out: int, dropout: float=0.0):... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class CollaQMultiHeadAttention:
"""Overview: The head of collaq attention module. Interface: __init__, forward"""
def __init__(self, n_head: int, d_model_q: int, d_model_v: int, d_k: int, d_v: int, d_out: int, dropout: float=0.0):
"""Overview: initialize the head of collaq attention module... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollaQMultiHeadAttention:
"""Overview: The head of collaq attention module. Interface: __init__, forward"""
def __init__(self, n_head: int, d_model_q: int, d_model_v: int, d_k: int, d_v: int, d_out: int, dropout: float=0.0):
"""Overview: initialize the head of collaq attention module Arguments: -... | the_stack_v2_python_sparse | ding/model/template/qmix.py | shengxuesun/DI-engine | train | 1 |
f0191ceb0448c8b6eacede545dd5863c69667797 | [
"ret = []\n\ndef preorder(root):\n if root:\n ret.append(root.val)\n preorder(root.left)\n preorder(root.right)\npreorder(root)\nreturn ' '.join(map(str, ret))",
"nums = collections.deque((int(n) for n in data.split()))\n\ndef build(mmin, mmax):\n if nums and mmin < nums[0] < mmax:\n ... | <|body_start_0|>
ret = []
def preorder(root):
if root:
ret.append(root.val)
preorder(root.left)
preorder(root.right)
preorder(root)
return ' '.join(map(str, ret))
<|end_body_0|>
<|body_start_1|>
nums = collections.dequ... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_034770 | 1,219 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | ef8c9422c481aa3c482933318c785ad28dd7703e | <|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"""
ret = []
def preorder(root):
if root:
ret.append(root.val)
preorder(root.left)
preorder(root.right)
preorder(... | the_stack_v2_python_sparse | python/serialize_and_deserialize_BST.py | pzmrzy/LeetCode | train | 2 | |
453b128fad660bb8f062b0f67c54eef6f3480b65 | [
"self.entity_domain = ENTITY_DOMAIN\nsuper().__init__(config_entry=config_entry, coordinator=coordinator, description=description)\nself._attr_entity_category = EntityCategory.DIAGNOSTIC",
"if self.coordinator.data:\n if self.entity_description.state_value:\n if self.entity_description.key:\n ... | <|body_start_0|>
self.entity_domain = ENTITY_DOMAIN
super().__init__(config_entry=config_entry, coordinator=coordinator, description=description)
self._attr_entity_category = EntityCategory.DIAGNOSTIC
<|end_body_0|>
<|body_start_1|>
if self.coordinator.data:
if self.entity_d... | Representation of an HDHomeRun sensor. | HDHomerunSensor | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HDHomerunSensor:
"""Representation of an HDHomeRun sensor."""
def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunSensorEntityDescription) -> None:
"""Initialise."""
<|body_0|>
def native_value(self) -> StateType | date... | stack_v2_sparse_classes_36k_train_034771 | 13,715 | permissive | [
{
"docstring": "Initialise.",
"name": "__init__",
"signature": "def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunSensorEntityDescription) -> None"
},
{
"docstring": "Get the value of the sensor.",
"name": "native_value",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_001609 | Implement the Python class `HDHomerunSensor` described below.
Class description:
Representation of an HDHomeRun sensor.
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunSensorEntityDescription) -> None: Initialise.
- def native... | Implement the Python class `HDHomerunSensor` described below.
Class description:
Representation of an HDHomeRun sensor.
Method signatures and docstrings:
- def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunSensorEntityDescription) -> None: Initialise.
- def native... | 8548d9999ddd54f13d6a307e013abcb8c897a74e | <|skeleton|>
class HDHomerunSensor:
"""Representation of an HDHomeRun sensor."""
def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunSensorEntityDescription) -> None:
"""Initialise."""
<|body_0|>
def native_value(self) -> StateType | date... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HDHomerunSensor:
"""Representation of an HDHomeRun sensor."""
def __init__(self, config_entry: ConfigEntry, coordinator: DataUpdateCoordinator, description: HDHomerunSensorEntityDescription) -> None:
"""Initialise."""
self.entity_domain = ENTITY_DOMAIN
super().__init__(config_entr... | the_stack_v2_python_sparse | custom_components/hdhomerun/sensor.py | bacco007/HomeAssistantConfig | train | 98 |
a5b597f4d7d110a78276f1430b3837a0e929fe0a | [
"np.random.seed(0)\nself.target_func = f\nself.noise = noise\nself.x_train = np.random.random(size=(train_num, 1)) - 0.5\nself.y_train = f(self.x_train) + np.random.normal(0.0, noise, size=self.x_train.shape)\nself.x_test = np.linspace(-0.7, 0.7, 10000).reshape(-1, 1)\nself.x_plot = np.linspace(-0.7, 0.7, 10000).re... | <|body_start_0|>
np.random.seed(0)
self.target_func = f
self.noise = noise
self.x_train = np.random.random(size=(train_num, 1)) - 0.5
self.y_train = f(self.x_train) + np.random.normal(0.0, noise, size=self.x_train.shape)
self.x_test = np.linspace(-0.7, 0.7, 10000).reshape... | Collision_Problem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Collision_Problem:
def __init__(self, f, train_num=100, noise=0):
"""Init (1)training and testing data (2) form the network"""
<|body_0|>
def model(self, latent_dim: int=1):
"""Keras style layers + optimizers"""
<|body_1|>
def find_collision(self, iter_n... | stack_v2_sparse_classes_36k_train_034772 | 7,756 | no_license | [
{
"docstring": "Init (1)training and testing data (2) form the network",
"name": "__init__",
"signature": "def __init__(self, f, train_num=100, noise=0)"
},
{
"docstring": "Keras style layers + optimizers",
"name": "model",
"signature": "def model(self, latent_dim: int=1)"
},
{
"... | 4 | stack_v2_sparse_classes_30k_val_000918 | Implement the Python class `Collision_Problem` described below.
Class description:
Implement the Collision_Problem class.
Method signatures and docstrings:
- def __init__(self, f, train_num=100, noise=0): Init (1)training and testing data (2) form the network
- def model(self, latent_dim: int=1): Keras style layers +... | Implement the Python class `Collision_Problem` described below.
Class description:
Implement the Collision_Problem class.
Method signatures and docstrings:
- def __init__(self, f, train_num=100, noise=0): Init (1)training and testing data (2) form the network
- def model(self, latent_dim: int=1): Keras style layers +... | 92b44d8b8ce775bd558cc1a10c54158932cadc3d | <|skeleton|>
class Collision_Problem:
def __init__(self, f, train_num=100, noise=0):
"""Init (1)training and testing data (2) form the network"""
<|body_0|>
def model(self, latent_dim: int=1):
"""Keras style layers + optimizers"""
<|body_1|>
def find_collision(self, iter_n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Collision_Problem:
def __init__(self, f, train_num=100, noise=0):
"""Init (1)training and testing data (2) form the network"""
np.random.seed(0)
self.target_func = f
self.noise = noise
self.x_train = np.random.random(size=(train_num, 1)) - 0.5
self.y_train = f(s... | the_stack_v2_python_sparse | latent_problem/collision_problem.py | SchroDeCat/Deep-Kernel-GP | train | 0 | |
bebc859117356a1d4787864d3752dac4a7acd98c | [
"init_a[1].login_form(success_a_data['username'], success_a_data['password'], success_a_data['code'])\nsleep(1)\nassert HomePage(init_a[0]).button_is_exist() is True",
"init_a[1].login_form(datas['username'], datas['password'], datas['code'])\nsleep(1)\nassert init_a[1].login_fail_msg() == datas['check']",
"ini... | <|body_start_0|>
init_a[1].login_form(success_a_data['username'], success_a_data['password'], success_a_data['code'])
sleep(1)
assert HomePage(init_a[0]).button_is_exist() is True
<|end_body_0|>
<|body_start_1|>
init_a[1].login_form(datas['username'], datas['password'], datas['code'])
... | TestALogin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestALogin:
def test_login_a_success(self, init_a):
"""A端登录页面，登录成功操作"""
<|body_0|>
def test_login_a_fail(self, init_a, datas):
"""A端登录，登录失败弹框提示"""
<|body_1|>
def test_login_a_fail_code_None(self, init_a):
"""A端登录，验证码错误提示"""
<|body_2|>
<|... | stack_v2_sparse_classes_36k_train_034773 | 1,648 | no_license | [
{
"docstring": "A端登录页面，登录成功操作",
"name": "test_login_a_success",
"signature": "def test_login_a_success(self, init_a)"
},
{
"docstring": "A端登录，登录失败弹框提示",
"name": "test_login_a_fail",
"signature": "def test_login_a_fail(self, init_a, datas)"
},
{
"docstring": "A端登录，验证码错误提示",
"n... | 3 | stack_v2_sparse_classes_30k_train_009879 | Implement the Python class `TestALogin` described below.
Class description:
Implement the TestALogin class.
Method signatures and docstrings:
- def test_login_a_success(self, init_a): A端登录页面，登录成功操作
- def test_login_a_fail(self, init_a, datas): A端登录，登录失败弹框提示
- def test_login_a_fail_code_None(self, init_a): A端登录，验证码错误提... | Implement the Python class `TestALogin` described below.
Class description:
Implement the TestALogin class.
Method signatures and docstrings:
- def test_login_a_success(self, init_a): A端登录页面，登录成功操作
- def test_login_a_fail(self, init_a, datas): A端登录，登录失败弹框提示
- def test_login_a_fail_code_None(self, init_a): A端登录，验证码错误提... | 69e48844077d389f6afc37e12adc24683cd5cc2c | <|skeleton|>
class TestALogin:
def test_login_a_success(self, init_a):
"""A端登录页面，登录成功操作"""
<|body_0|>
def test_login_a_fail(self, init_a, datas):
"""A端登录，登录失败弹框提示"""
<|body_1|>
def test_login_a_fail_code_None(self, init_a):
"""A端登录，验证码错误提示"""
<|body_2|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestALogin:
def test_login_a_success(self, init_a):
"""A端登录页面，登录成功操作"""
init_a[1].login_form(success_a_data['username'], success_a_data['password'], success_a_data['code'])
sleep(1)
assert HomePage(init_a[0]).button_is_exist() is True
def test_login_a_fail(self, init_a, da... | the_stack_v2_python_sparse | TestCases/TestModuleA/test_a_login.py | Sissixi/web_sissi | train | 0 | |
0a872aa55536b7bc95fa58ed875bff3696ded1a2 | [
"if index == 0:\n return 0\nuglyNum = [1]\nidx2, idx3, idx5 = (0, 0, 0)\nfor i in range(index - 1):\n n2, n3, n5 = (uglyNum[idx2] * 2, uglyNum[idx3] * 3, uglyNum[idx5] * 5)\n Min = min(n2, n3, n5)\n uglyNum.append(Min)\n idx2 += Min == n2\n idx3 += Min == n3\n idx5 += Min == n5\nreturn uglyNum[... | <|body_start_0|>
if index == 0:
return 0
uglyNum = [1]
idx2, idx3, idx5 = (0, 0, 0)
for i in range(index - 1):
n2, n3, n5 = (uglyNum[idx2] * 2, uglyNum[idx3] * 3, uglyNum[idx5] * 5)
Min = min(n2, n3, n5)
uglyNum.append(Min)
idx2... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def GetUglyNumber_Solution(self, index):
"""返回第index个丑数"""
<|body_0|>
def isUgly(self, num):
"""判断num是否是丑数"""
<|body_1|>
def nthSuperUglyNumber(self, index, primes):
"""超级丑数 Args: index: n primes: 列表 当某个数的因子只有primes中的元素时，作为超级丑数，求出第n个超级丑... | stack_v2_sparse_classes_36k_train_034774 | 1,820 | no_license | [
{
"docstring": "返回第index个丑数",
"name": "GetUglyNumber_Solution",
"signature": "def GetUglyNumber_Solution(self, index)"
},
{
"docstring": "判断num是否是丑数",
"name": "isUgly",
"signature": "def isUgly(self, num)"
},
{
"docstring": "超级丑数 Args: index: n primes: 列表 当某个数的因子只有primes中的元素时，作为超... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def GetUglyNumber_Solution(self, index): 返回第index个丑数
- def isUgly(self, num): 判断num是否是丑数
- def nthSuperUglyNumber(self, index, primes): 超级丑数 Args: index: n primes: 列表 当某个数的因子只有pr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def GetUglyNumber_Solution(self, index): 返回第index个丑数
- def isUgly(self, num): 判断num是否是丑数
- def nthSuperUglyNumber(self, index, primes): 超级丑数 Args: index: n primes: 列表 当某个数的因子只有pr... | 154f53d0eeeceb2f07f330ae407d4590840fe5ca | <|skeleton|>
class Solution:
def GetUglyNumber_Solution(self, index):
"""返回第index个丑数"""
<|body_0|>
def isUgly(self, num):
"""判断num是否是丑数"""
<|body_1|>
def nthSuperUglyNumber(self, index, primes):
"""超级丑数 Args: index: n primes: 列表 当某个数的因子只有primes中的元素时，作为超级丑数，求出第n个超级丑... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def GetUglyNumber_Solution(self, index):
"""返回第index个丑数"""
if index == 0:
return 0
uglyNum = [1]
idx2, idx3, idx5 = (0, 0, 0)
for i in range(index - 1):
n2, n3, n5 = (uglyNum[idx2] * 2, uglyNum[idx3] * 3, uglyNum[idx5] * 5)
... | the_stack_v2_python_sparse | 剑指offer/GetUglyNumber.py | EchoLLLiu/OtherCodes | train | 0 | |
1aa0ea9f50226b08f2697189cdf4be989d93d9c6 | [
"self.X = X\nself.K = K\nself.centrX = []\nself.C = []\nself.U = []\nself.Z = []\nself.centrX = self._centralized()\nself.C = self._cov()\nself.U = self._U()\nself.Z = self._Z()",
"print('样本矩阵X:\\n', self.X)\ncentrX = []\nmean = np.array([np.mean(attr) for attr in self.X.T])\nprint('样本集的特征均值:\\n', mean)\ncentrX =... | <|body_start_0|>
self.X = X
self.K = K
self.centrX = []
self.C = []
self.U = []
self.Z = []
self.centrX = self._centralized()
self.C = self._cov()
self.U = self._U()
self.Z = self._Z()
<|end_body_0|>
<|body_start_1|>
print('样本矩阵X:\... | CPCA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CPCA:
def __init__(self, X, K):
""":param X,训练样本矩阵X :param K,X的降维矩阵的阶数，即X要特征降维成k阶"""
<|body_0|>
def _centralized(self):
"""矩阵X的中心化"""
<|body_1|>
def _cov(self):
"""求样本矩阵X的协方差矩阵C"""
<|body_2|>
def _U(self):
"""求X的降维转换矩阵U, shap... | stack_v2_sparse_classes_36k_train_034775 | 4,771 | no_license | [
{
"docstring": ":param X,训练样本矩阵X :param K,X的降维矩阵的阶数，即X要特征降维成k阶",
"name": "__init__",
"signature": "def __init__(self, X, K)"
},
{
"docstring": "矩阵X的中心化",
"name": "_centralized",
"signature": "def _centralized(self)"
},
{
"docstring": "求样本矩阵X的协方差矩阵C",
"name": "_cov",
"sign... | 5 | null | Implement the Python class `CPCA` described below.
Class description:
Implement the CPCA class.
Method signatures and docstrings:
- def __init__(self, X, K): :param X,训练样本矩阵X :param K,X的降维矩阵的阶数，即X要特征降维成k阶
- def _centralized(self): 矩阵X的中心化
- def _cov(self): 求样本矩阵X的协方差矩阵C
- def _U(self): 求X的降维转换矩阵U, shape=(n,k), n是X的特征... | Implement the Python class `CPCA` described below.
Class description:
Implement the CPCA class.
Method signatures and docstrings:
- def __init__(self, X, K): :param X,训练样本矩阵X :param K,X的降维矩阵的阶数，即X要特征降维成k阶
- def _centralized(self): 矩阵X的中心化
- def _cov(self): 求样本矩阵X的协方差矩阵C
- def _U(self): 求X的降维转换矩阵U, shape=(n,k), n是X的特征... | f2a1b2f8b6b292815d92a294d49954616d3624d5 | <|skeleton|>
class CPCA:
def __init__(self, X, K):
""":param X,训练样本矩阵X :param K,X的降维矩阵的阶数，即X要特征降维成k阶"""
<|body_0|>
def _centralized(self):
"""矩阵X的中心化"""
<|body_1|>
def _cov(self):
"""求样本矩阵X的协方差矩阵C"""
<|body_2|>
def _U(self):
"""求X的降维转换矩阵U, shap... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CPCA:
def __init__(self, X, K):
""":param X,训练样本矩阵X :param K,X的降维矩阵的阶数，即X要特征降维成k阶"""
self.X = X
self.K = K
self.centrX = []
self.C = []
self.U = []
self.Z = []
self.centrX = self._centralized()
self.C = self._cov()
self.U = self._... | the_stack_v2_python_sparse | 85+张桂锋+深圳/week03/hw03.py | Yang-chen205/badou-Turing | train | 1 | |
f785fece0d947e0e1faf736b0d503ae87d28fbf1 | [
"super().__init__()\nself.transformer_dim = transformer_dim\nself.transformer = transformer\nself.num_multimask_outputs = num_multimask_outputs\nself.iou_token = paddle.nn.Embedding(1, transformer_dim)\nself.num_mask_tokens = num_multimask_outputs + 1\nself.mask_tokens = paddle.nn.Embedding(self.num_mask_tokens, tr... | <|body_start_0|>
super().__init__()
self.transformer_dim = transformer_dim
self.transformer = transformer
self.num_multimask_outputs = num_multimask_outputs
self.iou_token = paddle.nn.Embedding(1, transformer_dim)
self.num_mask_tokens = num_multimask_outputs + 1
s... | MaskDecoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaskDecoder:
def __init__(self, *, transformer_dim: int, transformer: paddle.nn.Layer, num_multimask_outputs: int=3, activation: Type[paddle.nn.Layer]=paddle.nn.GELU, iou_head_depth: int=3, iou_head_hidden_dim: int=256) -> None:
"""Predicts masks given an image and prompt embeddings, usi... | stack_v2_sparse_classes_36k_train_034776 | 7,772 | permissive | [
{
"docstring": "Predicts masks given an image and prompt embeddings, using a tranformer architecture. Arguments: transformer_dim (int): the channel dimension of the transformer transformer (nn.Module): the transformer used to predict masks num_multimask_outputs (int): the number of masks to predict when disambi... | 3 | null | Implement the Python class `MaskDecoder` described below.
Class description:
Implement the MaskDecoder class.
Method signatures and docstrings:
- def __init__(self, *, transformer_dim: int, transformer: paddle.nn.Layer, num_multimask_outputs: int=3, activation: Type[paddle.nn.Layer]=paddle.nn.GELU, iou_head_depth: in... | Implement the Python class `MaskDecoder` described below.
Class description:
Implement the MaskDecoder class.
Method signatures and docstrings:
- def __init__(self, *, transformer_dim: int, transformer: paddle.nn.Layer, num_multimask_outputs: int=3, activation: Type[paddle.nn.Layer]=paddle.nn.GELU, iou_head_depth: in... | 2c8c35a8949fef74599f5ec557d340a14415f20d | <|skeleton|>
class MaskDecoder:
def __init__(self, *, transformer_dim: int, transformer: paddle.nn.Layer, num_multimask_outputs: int=3, activation: Type[paddle.nn.Layer]=paddle.nn.GELU, iou_head_depth: int=3, iou_head_hidden_dim: int=256) -> None:
"""Predicts masks given an image and prompt embeddings, usi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MaskDecoder:
def __init__(self, *, transformer_dim: int, transformer: paddle.nn.Layer, num_multimask_outputs: int=3, activation: Type[paddle.nn.Layer]=paddle.nn.GELU, iou_head_depth: int=3, iou_head_hidden_dim: int=256) -> None:
"""Predicts masks given an image and prompt embeddings, using a tranforme... | the_stack_v2_python_sparse | contrib/SegmentAnything/segment_anything/modeling/mask_decoder.py | PaddlePaddle/PaddleSeg | train | 8,531 | |
66cdc2a2068e50d249bf6ee937436a358d9b9dd3 | [
"n, s = (1, 0)\nfor v in nums:\n if s + v > x:\n n += 1\n s = 0\n s += v\nreturn n",
"n = len(nums)\nif m == 1:\n return sum(nums)\nif m >= n:\n return max(nums)\nl, r = (max(nums), sum(nums))\nwhile l < r:\n x = l + (r - l) // 2\n if self._numSplits(nums, x) > m:\n l = x + ... | <|body_start_0|>
n, s = (1, 0)
for v in nums:
if s + v > x:
n += 1
s = 0
s += v
return n
<|end_body_0|>
<|body_start_1|>
n = len(nums)
if m == 1:
return sum(nums)
if m >= n:
return max(nums)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _numSplits(self, nums, x):
"""min num of splits needed if any split/subarray has sum <= x."""
<|body_0|>
def splitArray(self, nums: List[int], m: int) -> int:
"""binary search + brute force, O(N*log(sum(nums)))"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_034777 | 2,870 | no_license | [
{
"docstring": "min num of splits needed if any split/subarray has sum <= x.",
"name": "_numSplits",
"signature": "def _numSplits(self, nums, x)"
},
{
"docstring": "binary search + brute force, O(N*log(sum(nums)))",
"name": "splitArray",
"signature": "def splitArray(self, nums: List[int]... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _numSplits(self, nums, x): min num of splits needed if any split/subarray has sum <= x.
- def splitArray(self, nums: List[int], m: int) -> int: binary search + brute force, O... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _numSplits(self, nums, x): min num of splits needed if any split/subarray has sum <= x.
- def splitArray(self, nums: List[int], m: int) -> int: binary search + brute force, O... | 6043134736452a6f4704b62857d0aed2e9571164 | <|skeleton|>
class Solution:
def _numSplits(self, nums, x):
"""min num of splits needed if any split/subarray has sum <= x."""
<|body_0|>
def splitArray(self, nums: List[int], m: int) -> int:
"""binary search + brute force, O(N*log(sum(nums)))"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _numSplits(self, nums, x):
"""min num of splits needed if any split/subarray has sum <= x."""
n, s = (1, 0)
for v in nums:
if s + v > x:
n += 1
s = 0
s += v
return n
def splitArray(self, nums: List[int],... | the_stack_v2_python_sparse | src/0400-0499/0410.split.array.minimax.sum.py | gyang274/leetcode | train | 1 | |
148cb3a6d2caf569427fe09e5974594e7dfdc026 | [
"super().__init__(model_dir, *args, **kwargs)\nfrom modelscope.trainers.nlp.space.trainer.gen_trainer import MultiWOZTrainer\nself.model_dir = model_dir\nself.config = kwargs.pop('config', Config.from_file(os.path.join(self.model_dir, ModelFile.CONFIGURATION)))\nimport torch\nself.config.use_gpu = True if ('device'... | <|body_start_0|>
super().__init__(model_dir, *args, **kwargs)
from modelscope.trainers.nlp.space.trainer.gen_trainer import MultiWOZTrainer
self.model_dir = model_dir
self.config = kwargs.pop('config', Config.from_file(os.path.join(self.model_dir, ModelFile.CONFIGURATION)))
impor... | SpaceForDialogModeling | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpaceForDialogModeling:
def __init__(self, model_dir: str, *args, **kwargs):
"""initialize the test generation model from the `model_dir` path. Args: model_dir (`str`): The model path. text_field (`BPETextField`, *optional*, defaults to `MultiWOZBPETextField`): The text field. config (`C... | stack_v2_sparse_classes_36k_train_034778 | 4,353 | permissive | [
{
"docstring": "initialize the test generation model from the `model_dir` path. Args: model_dir (`str`): The model path. text_field (`BPETextField`, *optional*, defaults to `MultiWOZBPETextField`): The text field. config (`Config`, *optional*, defaults to config in model hub): The config.",
"name": "__init_... | 2 | null | Implement the Python class `SpaceForDialogModeling` described below.
Class description:
Implement the SpaceForDialogModeling class.
Method signatures and docstrings:
- def __init__(self, model_dir: str, *args, **kwargs): initialize the test generation model from the `model_dir` path. Args: model_dir (`str`): The mode... | Implement the Python class `SpaceForDialogModeling` described below.
Class description:
Implement the SpaceForDialogModeling class.
Method signatures and docstrings:
- def __init__(self, model_dir: str, *args, **kwargs): initialize the test generation model from the `model_dir` path. Args: model_dir (`str`): The mode... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class SpaceForDialogModeling:
def __init__(self, model_dir: str, *args, **kwargs):
"""initialize the test generation model from the `model_dir` path. Args: model_dir (`str`): The model path. text_field (`BPETextField`, *optional*, defaults to `MultiWOZBPETextField`): The text field. config (`C... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpaceForDialogModeling:
def __init__(self, model_dir: str, *args, **kwargs):
"""initialize the test generation model from the `model_dir` path. Args: model_dir (`str`): The model path. text_field (`BPETextField`, *optional*, defaults to `MultiWOZBPETextField`): The text field. config (`Config`, *optio... | the_stack_v2_python_sparse | ai/modelscope/modelscope/models/nlp/space/dialog_modeling.py | alldatacenter/alldata | train | 774 | |
2c56abeb2396749edb0ac6a156b985fc6cf2b939 | [
"self.instance = get_object_or_404(Instance, slug=self.kwargs['slug'])\ncanvas = self.instance.images().filter(short_id=self.kwargs['short_id']).first()\nif canvas and Instance.allow_canvas_detail(canvas):\n return canvas\nelse:\n raise Http404",
"context = super(CanvasDetail, self).get_context_data(*args, ... | <|body_start_0|>
self.instance = get_object_or_404(Instance, slug=self.kwargs['slug'])
canvas = self.instance.images().filter(short_id=self.kwargs['short_id']).first()
if canvas and Instance.allow_canvas_detail(canvas):
return canvas
else:
raise Http404
<|end_body... | CanvasDetail | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CanvasDetail:
def get_object(self, queryset=None):
"""Limit canvas detail view to those with :class:`derrida.interventions.models.Intervention` objects associated."""
<|body_0|>
def get_context_data(self, *args, **kwargs):
"""Set extra context for :class:`CanvasDetai... | stack_v2_sparse_classes_36k_train_034779 | 37,410 | permissive | [
{
"docstring": "Limit canvas detail view to those with :class:`derrida.interventions.models.Intervention` objects associated.",
"name": "get_object",
"signature": "def get_object(self, queryset=None)"
},
{
"docstring": "Set extra context for :class:`CanvasDetail` view.",
"name": "get_context... | 2 | stack_v2_sparse_classes_30k_train_014485 | Implement the Python class `CanvasDetail` described below.
Class description:
Implement the CanvasDetail class.
Method signatures and docstrings:
- def get_object(self, queryset=None): Limit canvas detail view to those with :class:`derrida.interventions.models.Intervention` objects associated.
- def get_context_data(... | Implement the Python class `CanvasDetail` described below.
Class description:
Implement the CanvasDetail class.
Method signatures and docstrings:
- def get_object(self, queryset=None): Limit canvas detail view to those with :class:`derrida.interventions.models.Intervention` objects associated.
- def get_context_data(... | 6371bb1266d7751af59aeaa3426ef7ac02a1fe17 | <|skeleton|>
class CanvasDetail:
def get_object(self, queryset=None):
"""Limit canvas detail view to those with :class:`derrida.interventions.models.Intervention` objects associated."""
<|body_0|>
def get_context_data(self, *args, **kwargs):
"""Set extra context for :class:`CanvasDetai... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CanvasDetail:
def get_object(self, queryset=None):
"""Limit canvas detail view to those with :class:`derrida.interventions.models.Intervention` objects associated."""
self.instance = get_object_or_404(Instance, slug=self.kwargs['slug'])
canvas = self.instance.images().filter(short_id=s... | the_stack_v2_python_sparse | derrida/books/views.py | Princeton-CDH/derrida-django | train | 13 | |
8731b3c4215318cce9256581c3ef88a63b190c3d | [
"self.bo.swithwindows(By.LINK_TEXT, '新闻')\ntime.sleep(2)\nself.assertIn('news', self.driver.current_url)",
"self.bo.swithwindows(By.LINK_TEXT, 'hao123')\ntime.sleep(2)\nself.assertIn('hao', self.driver.current_url)",
"self.bo.swithwindows(By.LINK_TEXT, '地图')\ntime.sleep(2)\nself.assertIn('map', self.driver.curr... | <|body_start_0|>
self.bo.swithwindows(By.LINK_TEXT, '新闻')
time.sleep(2)
self.assertIn('news', self.driver.current_url)
<|end_body_0|>
<|body_start_1|>
self.bo.swithwindows(By.LINK_TEXT, 'hao123')
time.sleep(2)
self.assertIn('hao', self.driver.current_url)
<|end_body_1|>
... | 百度搜索测试用例 | TestLink | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLink:
"""百度搜索测试用例"""
def test_news(self):
"""测试点击新闻"""
<|body_0|>
def test_hao123(self):
"""测试点击hao123"""
<|body_1|>
def test_map(self):
"""测试点击map"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.bo.swithwindows(By.... | stack_v2_sparse_classes_36k_train_034780 | 1,265 | no_license | [
{
"docstring": "测试点击新闻",
"name": "test_news",
"signature": "def test_news(self)"
},
{
"docstring": "测试点击hao123",
"name": "test_hao123",
"signature": "def test_hao123(self)"
},
{
"docstring": "测试点击map",
"name": "test_map",
"signature": "def test_map(self)"
}
] | 3 | null | Implement the Python class `TestLink` described below.
Class description:
百度搜索测试用例
Method signatures and docstrings:
- def test_news(self): 测试点击新闻
- def test_hao123(self): 测试点击hao123
- def test_map(self): 测试点击map | Implement the Python class `TestLink` described below.
Class description:
百度搜索测试用例
Method signatures and docstrings:
- def test_news(self): 测试点击新闻
- def test_hao123(self): 测试点击hao123
- def test_map(self): 测试点击map
<|skeleton|>
class TestLink:
"""百度搜索测试用例"""
def test_news(self):
"""测试点击新闻"""
<... | 7b790f675419224bfdbe1542eddc5a638982e68a | <|skeleton|>
class TestLink:
"""百度搜索测试用例"""
def test_news(self):
"""测试点击新闻"""
<|body_0|>
def test_hao123(self):
"""测试点击hao123"""
<|body_1|>
def test_map(self):
"""测试点击map"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestLink:
"""百度搜索测试用例"""
def test_news(self):
"""测试点击新闻"""
self.bo.swithwindows(By.LINK_TEXT, '新闻')
time.sleep(2)
self.assertIn('news', self.driver.current_url)
def test_hao123(self):
"""测试点击hao123"""
self.bo.swithwindows(By.LINK_TEXT, 'hao123')
... | the_stack_v2_python_sparse | P9/day_13_integration/iwebshop_selenium/testcase/baidulink.py | liousAlready/NewDream_learning | train | 0 |
04606f18c9417473b81fcfa715768d9a1a709382 | [
"self.zoneType = zoneType\nself.effects = effects\nself.filter = filter",
"zone, cards = self.findPossibleCards(context)\nfor card in cards:\n event = CardsEvent([card], zone, context)\n coroutine = PerformEffects(self.effects, event.context)\n try:\n response = (yield coroutine.next())\n w... | <|body_start_0|>
self.zoneType = zoneType
self.effects = effects
self.filter = filter
<|end_body_0|>
<|body_start_1|>
zone, cards = self.findPossibleCards(context)
for card in cards:
event = CardsEvent([card], zone, context)
coroutine = PerformEffects(sel... | Represents an effect that applies for each matching card | PerMatch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PerMatch:
"""Represents an effect that applies for each matching card"""
def __init__(self, zoneType, effects, filter=None):
"""Initialize the Effect with the condition to evaluate and effect to perform"""
<|body_0|>
def perform(self, context):
"""Perform the Gam... | stack_v2_sparse_classes_36k_train_034781 | 1,261 | no_license | [
{
"docstring": "Initialize the Effect with the condition to evaluate and effect to perform",
"name": "__init__",
"signature": "def __init__(self, zoneType, effects, filter=None)"
},
{
"docstring": "Perform the Game Effect",
"name": "perform",
"signature": "def perform(self, context)"
}... | 3 | null | Implement the Python class `PerMatch` described below.
Class description:
Represents an effect that applies for each matching card
Method signatures and docstrings:
- def __init__(self, zoneType, effects, filter=None): Initialize the Effect with the condition to evaluate and effect to perform
- def perform(self, cont... | Implement the Python class `PerMatch` described below.
Class description:
Represents an effect that applies for each matching card
Method signatures and docstrings:
- def __init__(self, zoneType, effects, filter=None): Initialize the Effect with the condition to evaluate and effect to perform
- def perform(self, cont... | 0b5a7573a3cf33430fe61e4ff8a8a7a0ae20b258 | <|skeleton|>
class PerMatch:
"""Represents an effect that applies for each matching card"""
def __init__(self, zoneType, effects, filter=None):
"""Initialize the Effect with the condition to evaluate and effect to perform"""
<|body_0|>
def perform(self, context):
"""Perform the Gam... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PerMatch:
"""Represents an effect that applies for each matching card"""
def __init__(self, zoneType, effects, filter=None):
"""Initialize the Effect with the condition to evaluate and effect to perform"""
self.zoneType = zoneType
self.effects = effects
self.filter = filte... | the_stack_v2_python_sparse | src/Game/Effects/per_match.py | dfwarden/DeckBuilding | train | 0 |
761d059bc51ee29c9b235411e3002479972c7202 | [
"adm = ProjectAdministration()\nproposal = Grading.from_dict(api.payload)\nif proposal is not None:\n 'Wir verwenden Grading_id und Grade des Proposals für die Erzeugung eines Grading-Objektes.'\n grad = adm.create_grading(proposal.get_grade(), proposal.get_participation_id())\n return (grad, 200)\nelse:\n... | <|body_start_0|>
adm = ProjectAdministration()
proposal = Grading.from_dict(api.payload)
if proposal is not None:
'Wir verwenden Grading_id und Grade des Proposals für die Erzeugung eines Grading-Objektes.'
grad = adm.create_grading(proposal.get_grade(), proposal.get_part... | GradingOperations | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GradingOperations:
def post(self):
"""Anlegen eines neuen Grading-Objekts"""
<|body_0|>
def put(self):
"""Update eines bestimmten Grading-Objekts."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
adm = ProjectAdministration()
proposal = Gradi... | stack_v2_sparse_classes_36k_train_034782 | 44,493 | no_license | [
{
"docstring": "Anlegen eines neuen Grading-Objekts",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Update eines bestimmten Grading-Objekts.",
"name": "put",
"signature": "def put(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014549 | Implement the Python class `GradingOperations` described below.
Class description:
Implement the GradingOperations class.
Method signatures and docstrings:
- def post(self): Anlegen eines neuen Grading-Objekts
- def put(self): Update eines bestimmten Grading-Objekts. | Implement the Python class `GradingOperations` described below.
Class description:
Implement the GradingOperations class.
Method signatures and docstrings:
- def post(self): Anlegen eines neuen Grading-Objekts
- def put(self): Update eines bestimmten Grading-Objekts.
<|skeleton|>
class GradingOperations:
def po... | 4b2826225525ae855e15e1174f5cf90466097021 | <|skeleton|>
class GradingOperations:
def post(self):
"""Anlegen eines neuen Grading-Objekts"""
<|body_0|>
def put(self):
"""Update eines bestimmten Grading-Objekts."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GradingOperations:
def post(self):
"""Anlegen eines neuen Grading-Objekts"""
adm = ProjectAdministration()
proposal = Grading.from_dict(api.payload)
if proposal is not None:
'Wir verwenden Grading_id und Grade des Proposals für die Erzeugung eines Grading-Objektes.'... | the_stack_v2_python_sparse | src/main.py | KieserChristian/SW_Praktikum_Gruppe1 | train | 0 | |
db71aa7681101c0f116efccac5c7f4eae056c81a | [
"self.camera = picamera.PiCamera()\nself.camera.resolution = (x, y)\nreturn",
"if filename is None:\n return\ntime.sleep(2)\nself.camera.capture(filename)"
] | <|body_start_0|>
self.camera = picamera.PiCamera()
self.camera.resolution = (x, y)
return
<|end_body_0|>
<|body_start_1|>
if filename is None:
return
time.sleep(2)
self.camera.capture(filename)
<|end_body_1|>
| Class for dealing with the camera on a Raspberry Pi | RaspiCamera | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RaspiCamera:
"""Class for dealing with the camera on a Raspberry Pi"""
def __init__(self, x=1920, y=1280):
"""Constructor to make camera instance"""
<|body_0|>
def simple_picture(self, filename=None):
"""Take an immediate picture and save to filename"""
<... | stack_v2_sparse_classes_36k_train_034783 | 1,574 | no_license | [
{
"docstring": "Constructor to make camera instance",
"name": "__init__",
"signature": "def __init__(self, x=1920, y=1280)"
},
{
"docstring": "Take an immediate picture and save to filename",
"name": "simple_picture",
"signature": "def simple_picture(self, filename=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016956 | Implement the Python class `RaspiCamera` described below.
Class description:
Class for dealing with the camera on a Raspberry Pi
Method signatures and docstrings:
- def __init__(self, x=1920, y=1280): Constructor to make camera instance
- def simple_picture(self, filename=None): Take an immediate picture and save to ... | Implement the Python class `RaspiCamera` described below.
Class description:
Class for dealing with the camera on a Raspberry Pi
Method signatures and docstrings:
- def __init__(self, x=1920, y=1280): Constructor to make camera instance
- def simple_picture(self, filename=None): Take an immediate picture and save to ... | 7d4a27126f7f2a93f7216b9ea4eed15789599bf3 | <|skeleton|>
class RaspiCamera:
"""Class for dealing with the camera on a Raspberry Pi"""
def __init__(self, x=1920, y=1280):
"""Constructor to make camera instance"""
<|body_0|>
def simple_picture(self, filename=None):
"""Take an immediate picture and save to filename"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RaspiCamera:
"""Class for dealing with the camera on a Raspberry Pi"""
def __init__(self, x=1920, y=1280):
"""Constructor to make camera instance"""
self.camera = picamera.PiCamera()
self.camera.resolution = (x, y)
return
def simple_picture(self, filename=None):
... | the_stack_v2_python_sparse | python3/cherrypy/raspberry_pi_class/RaspiCamera.py | ptracton/experimental | train | 4 |
31f99576fc8c04ccfb1dcadc31b9077bc65457e5 | [
"if not self.slug:\n self.slug = self.get_slug()\nsuper().clean()",
"absolute_url = ''\nif self.slug:\n absolute_url = reverse(f'{self.get_meta().app_label}:detail_slug', args=[str(self.slug)])\nelse:\n absolute_url = reverse(f'{self.get_meta().app_label}:detail', args=[str(self.pk)])\nlogging.debug(f'De... | <|body_start_0|>
if not self.slug:
self.slug = self.get_slug()
super().clean()
<|end_body_0|>
<|body_start_1|>
absolute_url = ''
if self.slug:
absolute_url = reverse(f'{self.get_meta().app_label}:detail_slug', args=[str(self.slug)])
else:
abso... | A model that shows up in ModularHistory's search results; e.g., a quote or occurrence. Ideally, this class would be a mixin, but due to Django's model magic, it must be defined as an abstract model class. | SearchableModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchableModel:
"""A model that shows up in ModularHistory's search results; e.g., a quote or occurrence. Ideally, this class would be a mixin, but due to Django's model magic, it must be defined as an abstract model class."""
def clean(self):
"""Prepare the model instance to be sav... | stack_v2_sparse_classes_36k_train_034784 | 2,832 | no_license | [
{
"docstring": "Prepare the model instance to be saved.",
"name": "clean",
"signature": "def clean(self)"
},
{
"docstring": "Return the URL for the model instance detail page.",
"name": "get_absolute_url",
"signature": "def get_absolute_url(self)"
}
] | 2 | null | Implement the Python class `SearchableModel` described below.
Class description:
A model that shows up in ModularHistory's search results; e.g., a quote or occurrence. Ideally, this class would be a mixin, but due to Django's model magic, it must be defined as an abstract model class.
Method signatures and docstrings... | Implement the Python class `SearchableModel` described below.
Class description:
A model that shows up in ModularHistory's search results; e.g., a quote or occurrence. Ideally, this class would be a mixin, but due to Django's model magic, it must be defined as an abstract model class.
Method signatures and docstrings... | edea4e5b0c382c604db2c3fbb58dc73e57de8431 | <|skeleton|>
class SearchableModel:
"""A model that shows up in ModularHistory's search results; e.g., a quote or occurrence. Ideally, this class would be a mixin, but due to Django's model magic, it must be defined as an abstract model class."""
def clean(self):
"""Prepare the model instance to be sav... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SearchableModel:
"""A model that shows up in ModularHistory's search results; e.g., a quote or occurrence. Ideally, this class would be a mixin, but due to Django's model magic, it must be defined as an abstract model class."""
def clean(self):
"""Prepare the model instance to be saved."""
... | the_stack_v2_python_sparse | apps/search/models/searchable_model.py | RealGuy69/modularhistory | train | 0 |
764c1158423a22f47c9965a292fc5a74204a4512 | [
"if type:\n self.design_type = type\nif status:\n self.region_status = status\nif metadata:\n self.metadata = metadata\nif rangerAgentVersion:\n self.ranger_agent_version = rangerAgentVersion\nif clli:\n self.clli = clli\nif regionname:\n self.name = regionname\nif osversion:\n self.open_stack_... | <|body_start_0|>
if type:
self.design_type = type
if status:
self.region_status = status
if metadata:
self.metadata = metadata
if rangerAgentVersion:
self.ranger_agent_version = rangerAgentVersion
if clli:
self.clli = cl... | class method. | UrlParms | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UrlParms:
"""class method."""
def __init__(self, type=None, status=None, metadata=None, rangerAgentVersion=None, clli=None, regionname=None, osversion=None, location_type=None, state=None, country=None, city=None, street=None, zip=None, vlcp_name=None):
"""init method. :param type: :... | stack_v2_sparse_classes_36k_train_034785 | 3,213 | no_license | [
{
"docstring": "init method. :param type: :param status: :param metadata: :param rangerAgentVersion: :param clli: :param regionname: :param osversion: :param location_type: :param state: :param country: :param city: :param street: :param zip: :param vlcp_name:",
"name": "__init__",
"signature": "def __i... | 4 | stack_v2_sparse_classes_30k_train_000691 | Implement the Python class `UrlParms` described below.
Class description:
class method.
Method signatures and docstrings:
- def __init__(self, type=None, status=None, metadata=None, rangerAgentVersion=None, clli=None, regionname=None, osversion=None, location_type=None, state=None, country=None, city=None, street=Non... | Implement the Python class `UrlParms` described below.
Class description:
class method.
Method signatures and docstrings:
- def __init__(self, type=None, status=None, metadata=None, rangerAgentVersion=None, clli=None, regionname=None, osversion=None, location_type=None, state=None, country=None, city=None, street=Non... | 3ea2dcb191d8e41498fe062a79349c9d055224c6 | <|skeleton|>
class UrlParms:
"""class method."""
def __init__(self, type=None, status=None, metadata=None, rangerAgentVersion=None, clli=None, regionname=None, osversion=None, location_type=None, state=None, country=None, city=None, street=None, zip=None, vlcp_name=None):
"""init method. :param type: :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UrlParms:
"""class method."""
def __init__(self, type=None, status=None, metadata=None, rangerAgentVersion=None, clli=None, regionname=None, osversion=None, location_type=None, state=None, country=None, city=None, street=None, zip=None, vlcp_name=None):
"""init method. :param type: :param status:... | the_stack_v2_python_sparse | orm/services/region_manager/rms/model/url_parm.py | jq1581/ranger | train | 0 |
1c0620022b2b7864d4bff3526252bc6e5325886d | [
"if not nums or len(nums) <= 0:\n return\nres = 0\nfor i in nums:\n res = res ^ i\nindex = self.findFirstBit(res)\nres1 = 0\nres2 = 0\nfor j in nums:\n if j >> index & 1 == 1:\n res1 = res1 ^ j\n else:\n res2 = res2 ^ j\nreturn [res1, res2]",
"indexBit = 0\nwhile num & 1 == 0 and indexBi... | <|body_start_0|>
if not nums or len(nums) <= 0:
return
res = 0
for i in nums:
res = res ^ i
index = self.findFirstBit(res)
res1 = 0
res2 = 0
for j in nums:
if j >> index & 1 == 1:
res1 = res1 ^ j
else... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def findNumsAppearOnce(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findFirstBit(self, num):
"""找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums or len... | stack_v2_sparse_classes_36k_train_034786 | 3,672 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findNumsAppearOnce",
"signature": "def findNumsAppearOnce(self, nums)"
},
{
"docstring": "找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return:",
"name": "findFirstBit",
"signature": "def findFirstBit(self, num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006943 | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def findNumsAppearOnce(self, nums): :type nums: List[int] :rtype: List[int]
- def findFirstBit(self, num): 找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return: | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def findNumsAppearOnce(self, nums): :type nums: List[int] :rtype: List[int]
- def findFirstBit(self, num): 找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return:
<|skeleton|>
class So... | 1db60502acb208f22d2149a4824e1219d8938225 | <|skeleton|>
class Solution1:
def findNumsAppearOnce(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findFirstBit(self, num):
"""找到异或结果从右往左(低位到高位)第一个为1的位置 :param num: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution1:
def findNumsAppearOnce(self, nums):
""":type nums: List[int] :rtype: List[int]"""
if not nums or len(nums) <= 0:
return
res = 0
for i in nums:
res = res ^ i
index = self.findFirstBit(res)
res1 = 0
res2 = 0
for j... | the_stack_v2_python_sparse | code_with_name/test55_prob56_数组中只出现一次的两个数字.py | Binjer/jianzhi_offer | train | 2 | |
9ec14e2dd9e672e0fbd7e2475c9dff346d968361 | [
"self.db.occupants = []\nself.db.max_spots = 6\nself.desc = 'A place for people to privately chat. Dropping it in a room will make it part of the room.'\nself.locks.add(self.PLACE_LOCKS)\nself.at_init()",
"occupants = self.db.occupants or []\nif character in occupants:\n occupants.remove(character)\n self.d... | <|body_start_0|>
self.db.occupants = []
self.db.max_spots = 6
self.desc = 'A place for people to privately chat. Dropping it in a room will make it part of the room.'
self.locks.add(self.PLACE_LOCKS)
self.at_init()
<|end_body_0|>
<|body_start_1|>
occupants = self.db.occu... | Class for placed objects that allow the 'tabletalk' command. | Place | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Place:
"""Class for placed objects that allow the 'tabletalk' command."""
def at_object_creation(self):
"""Run at Place creation."""
<|body_0|>
def leave(self, character):
"""Character leaving the table."""
<|body_1|>
def join(self, character):
... | stack_v2_sparse_classes_36k_train_034787 | 3,619 | permissive | [
{
"docstring": "Run at Place creation.",
"name": "at_object_creation",
"signature": "def at_object_creation(self)"
},
{
"docstring": "Character leaving the table.",
"name": "leave",
"signature": "def leave(self, character)"
},
{
"docstring": "Character joins the table",
"name... | 5 | null | Implement the Python class `Place` described below.
Class description:
Class for placed objects that allow the 'tabletalk' command.
Method signatures and docstrings:
- def at_object_creation(self): Run at Place creation.
- def leave(self, character): Character leaving the table.
- def join(self, character): Character... | Implement the Python class `Place` described below.
Class description:
Class for placed objects that allow the 'tabletalk' command.
Method signatures and docstrings:
- def at_object_creation(self): Run at Place creation.
- def leave(self, character): Character leaving the table.
- def join(self, character): Character... | e1a2006ee728f76ee0f1a7056d99d2fdfa8e4706 | <|skeleton|>
class Place:
"""Class for placed objects that allow the 'tabletalk' command."""
def at_object_creation(self):
"""Run at Place creation."""
<|body_0|>
def leave(self, character):
"""Character leaving the table."""
<|body_1|>
def join(self, character):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Place:
"""Class for placed objects that allow the 'tabletalk' command."""
def at_object_creation(self):
"""Run at Place creation."""
self.db.occupants = []
self.db.max_spots = 6
self.desc = 'A place for people to privately chat. Dropping it in a room will make it part of t... | the_stack_v2_python_sparse | typeclasses/places/places.py | Reilena/arxcode | train | 5 |
aa048432e488aab88a7c267226a94c313e54dc3c | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('aoconno8_dmak1112', 'aoconno8_dmak1112')\nurl = 'https://data.boston.gov/api/3/action/datastore_search?resource_id=bd8dd4bb-867e-4ca2-b6c7-6c3bd9e6c290&limit=176'\nresponse = urllib.request.urlopen(url).... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('aoconno8_dmak1112', 'aoconno8_dmak1112')
url = 'https://data.boston.gov/api/3/action/datastore_search?resource_id=bd8dd4bb-867e-4ca2-b6c7-6c3bd9e6c290&lim... | yearlyEmissions | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class yearlyEmissions:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythi... | stack_v2_sparse_classes_36k_train_034788 | 3,717 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_val_000042 | Implement the Python class `yearlyEmissions` described below.
Class description:
Implement the yearlyEmissions class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=Non... | Implement the Python class `yearlyEmissions` described below.
Class description:
Implement the yearlyEmissions class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=Non... | b5ccaad97f6e35f9580e645ca764f36eb3406f43 | <|skeleton|>
class yearlyEmissions:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class yearlyEmissions:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('aoconno8_dmak1112', 'aoconno8_dmak1... | the_stack_v2_python_sparse | aoconno8_dmak1112/yearlyEmissions.py | dwang1995/course-2018-spr-proj | train | 1 | |
2cb8c3efc4625767b31f0375d8665c388903cd70 | [
"domain_context = request.session.get('domain_context')\nfilters = rest_utils.parse_filters_kwargs(request, self.client_keywords)[0]\nif not filters:\n filters = None\nresult = api.keystone.user_list(request, project=request.GET.get('project_id'), domain=request.GET.get('domain_id', domain_context), group=reques... | <|body_start_0|>
domain_context = request.session.get('domain_context')
filters = rest_utils.parse_filters_kwargs(request, self.client_keywords)[0]
if not filters:
filters = None
result = api.keystone.user_list(request, project=request.GET.get('project_id'), domain=request.GE... | API for keystone users. | Users | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Users:
"""API for keystone users."""
def get(self, request):
"""Get a list of users. By default, a listing of all users for the current domain are returned. You may specify GET parameters for project_id, domain_id and group_id to change that listing's context. The listing result is a... | stack_v2_sparse_classes_36k_train_034789 | 22,644 | permissive | [
{
"docstring": "Get a list of users. By default, a listing of all users for the current domain are returned. You may specify GET parameters for project_id, domain_id and group_id to change that listing's context. The listing result is an object with property \"items\".",
"name": "get",
"signature": "def... | 3 | null | Implement the Python class `Users` described below.
Class description:
API for keystone users.
Method signatures and docstrings:
- def get(self, request): Get a list of users. By default, a listing of all users for the current domain are returned. You may specify GET parameters for project_id, domain_id and group_id ... | Implement the Python class `Users` described below.
Class description:
API for keystone users.
Method signatures and docstrings:
- def get(self, request): Get a list of users. By default, a listing of all users for the current domain are returned. You may specify GET parameters for project_id, domain_id and group_id ... | 7896fd8c77a6766a1156a520946efaf792b76ca5 | <|skeleton|>
class Users:
"""API for keystone users."""
def get(self, request):
"""Get a list of users. By default, a listing of all users for the current domain are returned. You may specify GET parameters for project_id, domain_id and group_id to change that listing's context. The listing result is a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Users:
"""API for keystone users."""
def get(self, request):
"""Get a list of users. By default, a listing of all users for the current domain are returned. You may specify GET parameters for project_id, domain_id and group_id to change that listing's context. The listing result is an object with... | the_stack_v2_python_sparse | openstack_dashboard/api/rest/keystone.py | openstack/horizon | train | 1,060 |
e4a5f8fa097cc3d95c38414b8c178f727fa62aa9 | [
"data_ID = request.args.get('id')\nif data_ID != None:\n app.logger.info(data_ID)\n case_data = testCase.query.filter_by(id=data_ID).all()\n data = [i.as_dict() for i in case_data]\n return {'error': 0, 'msg': {'data': data}}\nelse:\n case_data = testCase.query.all()\n print(type(case_data))\n ... | <|body_start_0|>
data_ID = request.args.get('id')
if data_ID != None:
app.logger.info(data_ID)
case_data = testCase.query.filter_by(id=data_ID).all()
data = [i.as_dict() for i in case_data]
return {'error': 0, 'msg': {'data': data}}
else:
... | TestCaseService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCaseService:
def get(self):
"""查询接口，查询用例数据信息"""
<|body_0|>
def post(self):
"""增加接口，增加用例数据"""
<|body_1|>
def put(self):
"""修改接口信息 :return:"""
<|body_2|>
def delete(self):
"""删除操作 :return:"""
<|body_3|>
<|end_skele... | stack_v2_sparse_classes_36k_train_034790 | 3,113 | no_license | [
{
"docstring": "查询接口，查询用例数据信息",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "增加接口，增加用例数据",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "修改接口信息 :return:",
"name": "put",
"signature": "def put(self)"
},
{
"docstring": "删除操作 :ret... | 4 | stack_v2_sparse_classes_30k_train_002903 | Implement the Python class `TestCaseService` described below.
Class description:
Implement the TestCaseService class.
Method signatures and docstrings:
- def get(self): 查询接口，查询用例数据信息
- def post(self): 增加接口，增加用例数据
- def put(self): 修改接口信息 :return:
- def delete(self): 删除操作 :return: | Implement the Python class `TestCaseService` described below.
Class description:
Implement the TestCaseService class.
Method signatures and docstrings:
- def get(self): 查询接口，查询用例数据信息
- def post(self): 增加接口，增加用例数据
- def put(self): 修改接口信息 :return:
- def delete(self): 删除操作 :return:
<|skeleton|>
class TestCaseService:
... | 8891c10e094b13d07cf4830855c37cebd07bd3d4 | <|skeleton|>
class TestCaseService:
def get(self):
"""查询接口，查询用例数据信息"""
<|body_0|>
def post(self):
"""增加接口，增加用例数据"""
<|body_1|>
def put(self):
"""修改接口信息 :return:"""
<|body_2|>
def delete(self):
"""删除操作 :return:"""
<|body_3|>
<|end_skele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCaseService:
def get(self):
"""查询接口，查询用例数据信息"""
data_ID = request.args.get('id')
if data_ID != None:
app.logger.info(data_ID)
case_data = testCase.query.filter_by(id=data_ID).all()
data = [i.as_dict() for i in case_data]
return {'erro... | the_stack_v2_python_sparse | Backend_Service/apis/api_testcases.py | BlueZUJIUPUP/HogwartsSDE18 | train | 1 | |
3f4d9f0cf8360445bad19e3d8cfb97f550be2594 | [
"self._base_profile = base_profile\nself._shape = shape\nself.center_plev = center_plev\nself.width = width\nself.fixed_T = fixed_T\nself.center_T = None\nif intensity > 1:\n intensity /= 100\nself.intensity = float(intensity)",
"plev = atmosphere['plev']\nT = atmosphere['T'][-1]\nif self.center_T == None:\n ... | <|body_start_0|>
self._base_profile = base_profile
self._shape = shape
self.center_plev = center_plev
self.width = width
self.fixed_T = fixed_T
self.center_T = None
if intensity > 1:
intensity /= 100
self.intensity = float(intensity)
<|end_body... | Wrapper to add a perturbation to a Relative Humidity profile. | PerturbProfile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PerturbProfile:
"""Wrapper to add a perturbation to a Relative Humidity profile."""
def __init__(self, base_profile=VerticallyUniform(), shape='square', center_plev=50000.0, width=5000.0, intensity=0.1, fixed_T=False):
"""Parameters: base_profile (konrad.relative_humidity model): ini... | stack_v2_sparse_classes_36k_train_034791 | 13,283 | permissive | [
{
"docstring": "Parameters: base_profile (konrad.relative_humidity model): initial profile on which we will add the perturbation. shape (str): name of the shape of the perturbation. Implemented : \"square\", \"gaussian\". For a Dirac use a square with width 0. center_plev (float): Pressure of the center of the ... | 2 | stack_v2_sparse_classes_30k_train_010901 | Implement the Python class `PerturbProfile` described below.
Class description:
Wrapper to add a perturbation to a Relative Humidity profile.
Method signatures and docstrings:
- def __init__(self, base_profile=VerticallyUniform(), shape='square', center_plev=50000.0, width=5000.0, intensity=0.1, fixed_T=False): Param... | Implement the Python class `PerturbProfile` described below.
Class description:
Wrapper to add a perturbation to a Relative Humidity profile.
Method signatures and docstrings:
- def __init__(self, base_profile=VerticallyUniform(), shape='square', center_plev=50000.0, width=5000.0, intensity=0.1, fixed_T=False): Param... | 2d9b5a78a1aab5d4dd2ccca99ddbce388de02738 | <|skeleton|>
class PerturbProfile:
"""Wrapper to add a perturbation to a Relative Humidity profile."""
def __init__(self, base_profile=VerticallyUniform(), shape='square', center_plev=50000.0, width=5000.0, intensity=0.1, fixed_T=False):
"""Parameters: base_profile (konrad.relative_humidity model): ini... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PerturbProfile:
"""Wrapper to add a perturbation to a Relative Humidity profile."""
def __init__(self, base_profile=VerticallyUniform(), shape='square', center_plev=50000.0, width=5000.0, intensity=0.1, fixed_T=False):
"""Parameters: base_profile (konrad.relative_humidity model): initial profile ... | the_stack_v2_python_sparse | konrad/humidity/relative_humidity.py | atmtools/konrad | train | 17 |
ba9e6a60a395a9118514acefe21a1a677c0c9edd | [
"Message.__init__(self)\nself.transaction_id = transaction_id\nself.ack = ack\nself.passport = ''\nself.friendly_name = ''",
"message = Message.__str__(self)\ncommand = 'MSG %u %s %u\\r\\n' % (self.transaction_id, self.ack, len(message))\nreturn command + message",
"message = Message.__repr__(self)\nlength = le... | <|body_start_0|>
Message.__init__(self)
self.transaction_id = transaction_id
self.ack = ack
self.passport = ''
self.friendly_name = ''
<|end_body_0|>
<|body_start_1|>
message = Message.__str__(self)
command = 'MSG %u %s %u\r\n' % (self.transaction_id, self.ack, l... | Build MSG commands destined to be sent. | OutgoingMessage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OutgoingMessage:
"""Build MSG commands destined to be sent."""
def __init__(self, transaction_id, ack):
"""Initializer @param transaction_id: the transaction ID @type transaction_id: integer @param ack: Acknowledgment type @type ack: L{message.MessageAcknowledgement}"""
<|bod... | stack_v2_sparse_classes_36k_train_034792 | 6,280 | no_license | [
{
"docstring": "Initializer @param transaction_id: the transaction ID @type transaction_id: integer @param ack: Acknowledgment type @type ack: L{message.MessageAcknowledgement}",
"name": "__init__",
"signature": "def __init__(self, transaction_id, ack)"
},
{
"docstring": "Represents the message ... | 3 | stack_v2_sparse_classes_30k_test_000371 | Implement the Python class `OutgoingMessage` described below.
Class description:
Build MSG commands destined to be sent.
Method signatures and docstrings:
- def __init__(self, transaction_id, ack): Initializer @param transaction_id: the transaction ID @type transaction_id: integer @param ack: Acknowledgment type @typ... | Implement the Python class `OutgoingMessage` described below.
Class description:
Build MSG commands destined to be sent.
Method signatures and docstrings:
- def __init__(self, transaction_id, ack): Initializer @param transaction_id: the transaction ID @type transaction_id: integer @param ack: Acknowledgment type @typ... | 16043edb5070b0755ed79b0aa02cba399d3d839d | <|skeleton|>
class OutgoingMessage:
"""Build MSG commands destined to be sent."""
def __init__(self, transaction_id, ack):
"""Initializer @param transaction_id: the transaction ID @type transaction_id: integer @param ack: Acknowledgment type @type ack: L{message.MessageAcknowledgement}"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OutgoingMessage:
"""Build MSG commands destined to be sent."""
def __init__(self, transaction_id, ack):
"""Initializer @param transaction_id: the transaction ID @type transaction_id: integer @param ack: Acknowledgment type @type ack: L{message.MessageAcknowledgement}"""
Message.__init__(s... | the_stack_v2_python_sparse | pymsn.rewrite/pymsn.rewrite/pymsn/msnp/message.py | Zacchy/nickcheng-python | train | 0 |
104aee12b4f796981cab80555fcb49d5772aa1c3 | [
"dump_node = ListNode(0)\ncur_node = dump_node\nwhile l1 or l2:\n while l1 and (l2 == None or l1.val <= l2.val):\n cur_node.next = ListNode(l1.val)\n cur_node = cur_node.next\n l1 = l1.next\n while l2 and (l1 == None or l2.val < l1.val):\n cur_node.next = ListNode(l2.val)\n ... | <|body_start_0|>
dump_node = ListNode(0)
cur_node = dump_node
while l1 or l2:
while l1 and (l2 == None or l1.val <= l2.val):
cur_node.next = ListNode(l1.val)
cur_node = cur_node.next
l1 = l1.next
while l2 and (l1 == None or ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dump_nod... | stack_v2_sparse_classes_36k_train_034793 | 1,499 | no_license | [
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists",
"signature": "def mergeTwoLists(self, l1, l2)"
},
{
"docstring": ":type lists: List[ListNode] :rtype: ListNode",
"name": "mergeKLists",
"signature": "def mergeKLists(self, lists)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016268 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeKLists(self, lists): :type lists: List[ListNode] :rtype: ListNode
<|skeleton|>... | 22f208400cd7e13fcf2ebf189e61ccad7e22b098 | <|skeleton|>
class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeKLists(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
dump_node = ListNode(0)
cur_node = dump_node
while l1 or l2:
while l1 and (l2 == None or l1.val <= l2.val):
cur_node.next = ListNode(l1.val)
... | the_stack_v2_python_sparse | previously_completed/1-30/23-Merge_k_Sorted_Lists.py | learnerjiahao/leetcode-solve | train | 0 | |
f7c0618e8b1af213f6594ad1a6496f5de699e589 | [
"self.ascending_height_points = np.array([5.0, 10.0, 20.0])\nself.ascending_cube = _set_up_height_cube(self.ascending_height_points)\nself.descending_height_points = np.array([20.0, 10.0, 5.0])\nself.descending_cube = _set_up_height_cube(self.descending_height_points, ascending=False)\nself.plugin_positive = Integr... | <|body_start_0|>
self.ascending_height_points = np.array([5.0, 10.0, 20.0])
self.ascending_cube = _set_up_height_cube(self.ascending_height_points)
self.descending_height_points = np.array([20.0, 10.0, 5.0])
self.descending_cube = _set_up_height_cube(self.descending_height_points, ascend... | Test the ensure_monotonic_increase_in_chosen_direction method. | Test_ensure_monotonic_increase_in_chosen_direction | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_ensure_monotonic_increase_in_chosen_direction:
"""Test the ensure_monotonic_increase_in_chosen_direction method."""
def setUp(self):
"""Set up the cube."""
<|body_0|>
def test_ascending_coordinate_positive(self):
"""Test that for a monotonically ascending co... | stack_v2_sparse_classes_36k_train_034794 | 25,011 | permissive | [
{
"docstring": "Set up the cube.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test that for a monotonically ascending coordinate, where the chosen direction is positive, the resulting coordinate still increases monotonically in the positive direction.",
"name": "test_... | 5 | stack_v2_sparse_classes_30k_train_007167 | Implement the Python class `Test_ensure_monotonic_increase_in_chosen_direction` described below.
Class description:
Test the ensure_monotonic_increase_in_chosen_direction method.
Method signatures and docstrings:
- def setUp(self): Set up the cube.
- def test_ascending_coordinate_positive(self): Test that for a monot... | Implement the Python class `Test_ensure_monotonic_increase_in_chosen_direction` described below.
Class description:
Test the ensure_monotonic_increase_in_chosen_direction method.
Method signatures and docstrings:
- def setUp(self): Set up the cube.
- def test_ascending_coordinate_positive(self): Test that for a monot... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_ensure_monotonic_increase_in_chosen_direction:
"""Test the ensure_monotonic_increase_in_chosen_direction method."""
def setUp(self):
"""Set up the cube."""
<|body_0|>
def test_ascending_coordinate_positive(self):
"""Test that for a monotonically ascending co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_ensure_monotonic_increase_in_chosen_direction:
"""Test the ensure_monotonic_increase_in_chosen_direction method."""
def setUp(self):
"""Set up the cube."""
self.ascending_height_points = np.array([5.0, 10.0, 20.0])
self.ascending_cube = _set_up_height_cube(self.ascending_heig... | the_stack_v2_python_sparse | improver_tests/utilities/test_mathematical_operations.py | metoppv/improver | train | 101 |
3f45929b6069a8d1ae963fbdeb073ad852b4d719 | [
"if not s or s[0] == '0':\n return 0\ndp1, dp2 = (0, 1)\nfor i in range(len(s)):\n current = 0\n if s[i] != '0':\n current = dp2\n if i > 0 and 10 <= int(s[i - 1:i + 1]) <= 26:\n current += dp1\n dp1, dp2 = (dp2, current)\nreturn dp2",
"def dp(index):\n if index in records:\n ... | <|body_start_0|>
if not s or s[0] == '0':
return 0
dp1, dp2 = (0, 1)
for i in range(len(s)):
current = 0
if s[i] != '0':
current = dp2
if i > 0 and 10 <= int(s[i - 1:i + 1]) <= 26:
current += dp1
dp1, dp2... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numDecodings(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def numDecodings(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not s or s[0] == '0':
return 0
dp1, dp2 = (0... | stack_v2_sparse_classes_36k_train_034795 | 2,067 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "numDecodings",
"signature": "def numDecodings(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "numDecodings",
"signature": "def numDecodings(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005569 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numDecodings(self, s): :type s: str :rtype: int
- def numDecodings(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numDecodings(self, s): :type s: str :rtype: int
- def numDecodings(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def numDecodings(self, s):
""... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def numDecodings(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def numDecodings(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numDecodings(self, s):
""":type s: str :rtype: int"""
if not s or s[0] == '0':
return 0
dp1, dp2 = (0, 1)
for i in range(len(s)):
current = 0
if s[i] != '0':
current = dp2
if i > 0 and 10 <= int(s[i -... | the_stack_v2_python_sparse | src/lt_91.py | oxhead/CodingYourWay | train | 0 | |
687c2a9ce6d6e85c7ec828cfd17ddaee1e8c5e94 | [
"data = parser.parse_args()\nproject_type = data.get('type')\nif project_type == 'annotation':\n return project_dao.all(project_type=TASK_ANNOTATION)\nelif project_type == 'fusion':\n return project_dao.all(project_type=TASK_FUSION)\nreturn project_dao.all()",
"req_dict = api.payload\nname = req_dict.get('n... | <|body_start_0|>
data = parser.parse_args()
project_type = data.get('type')
if project_type == 'annotation':
return project_dao.all(project_type=TASK_ANNOTATION)
elif project_type == 'fusion':
return project_dao.all(project_type=TASK_FUSION)
return project... | Shows a list of all projects, and lets you to add new projects. | ProjectList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectList:
"""Shows a list of all projects, and lets you to add new projects."""
def get(self):
"""List all projects"""
<|body_0|>
def post(self):
"""Create new project"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = parser.parse_args()... | stack_v2_sparse_classes_36k_train_034796 | 5,767 | permissive | [
{
"docstring": "List all projects",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Create new project",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000668 | Implement the Python class `ProjectList` described below.
Class description:
Shows a list of all projects, and lets you to add new projects.
Method signatures and docstrings:
- def get(self): List all projects
- def post(self): Create new project | Implement the Python class `ProjectList` described below.
Class description:
Shows a list of all projects, and lets you to add new projects.
Method signatures and docstrings:
- def get(self): List all projects
- def post(self): Create new project
<|skeleton|>
class ProjectList:
"""Shows a list of all projects, a... | 953c2916c38906b0941c015136f80b2e64dd94f3 | <|skeleton|>
class ProjectList:
"""Shows a list of all projects, and lets you to add new projects."""
def get(self):
"""List all projects"""
<|body_0|>
def post(self):
"""Create new project"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectList:
"""Shows a list of all projects, and lets you to add new projects."""
def get(self):
"""List all projects"""
data = parser.parse_args()
project_type = data.get('type')
if project_type == 'annotation':
return project_dao.all(project_type=TASK_ANNOTA... | the_stack_v2_python_sparse | kgeditor/api_1_0/project.py | LaiXinyi823/KGEditor | train | 0 |
6bcd9bd3098be2fb41bd5e9bef808c21e2e9f64a | [
"assert uid == SUPERUSER_ID, 'User to force discount value should be the administrator'\nproduct_ids = self.search(cr, uid, [], discount_id, context=context)\n_logger.debug('Dicount id force default : %d', discount_id)\nself.write(cr, uid, product_ids, {'discount_id': discount_id}, context=context)",
"assert uid ... | <|body_start_0|>
assert uid == SUPERUSER_ID, 'User to force discount value should be the administrator'
product_ids = self.search(cr, uid, [], discount_id, context=context)
_logger.debug('Dicount id force default : %d', discount_id)
self.write(cr, uid, product_ids, {'discount_id': discou... | ProductTemplate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductTemplate:
def force_default_discount(self, cr, uid, ids=[], discount_id=0, context=None):
"""Quick solution to avoid encoding the same discount manually for each product User should be admin"""
<|body_0|>
def force_default_taxes(self, cr, uid, ids=[], taxes_ids=[1], c... | stack_v2_sparse_classes_36k_train_034797 | 12,134 | no_license | [
{
"docstring": "Quick solution to avoid encoding the same discount manually for each product User should be admin",
"name": "force_default_discount",
"signature": "def force_default_discount(self, cr, uid, ids=[], discount_id=0, context=None)"
},
{
"docstring": "Quick solution to avoid encoding ... | 2 | stack_v2_sparse_classes_30k_train_002409 | Implement the Python class `ProductTemplate` described below.
Class description:
Implement the ProductTemplate class.
Method signatures and docstrings:
- def force_default_discount(self, cr, uid, ids=[], discount_id=0, context=None): Quick solution to avoid encoding the same discount manually for each product User sh... | Implement the Python class `ProductTemplate` described below.
Class description:
Implement the ProductTemplate class.
Method signatures and docstrings:
- def force_default_discount(self, cr, uid, ids=[], discount_id=0, context=None): Quick solution to avoid encoding the same discount manually for each product User sh... | 3681cbad05d5748198318fc1774be77b5f6b420e | <|skeleton|>
class ProductTemplate:
def force_default_discount(self, cr, uid, ids=[], discount_id=0, context=None):
"""Quick solution to avoid encoding the same discount manually for each product User should be admin"""
<|body_0|>
def force_default_taxes(self, cr, uid, ids=[], taxes_ids=[1], c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductTemplate:
def force_default_discount(self, cr, uid, ids=[], discount_id=0, context=None):
"""Quick solution to avoid encoding the same discount manually for each product User should be admin"""
assert uid == SUPERUSER_ID, 'User to force discount value should be the administrator'
... | the_stack_v2_python_sparse | account_grouped_invoice/grouped_invoice.py | dbertha/odoo-addons | train | 1 | |
348ad1bfbf42d03f884ebacec344b8dfa1293a8d | [
"N = len(arr)\nif x < arr[0]:\n return arr[:k]\nelif x > arr[-1]:\n return arr[N - k:]\nelse:\n index = bisect.bisect_left(arr, x)\n low = max(0, index - k - 1)\n high = min(N - 1, index + k - 1)\n while high - low > k - 1:\n if low < 0 or x - arr[low] <= arr[high] - x:\n high -=... | <|body_start_0|>
N = len(arr)
if x < arr[0]:
return arr[:k]
elif x > arr[-1]:
return arr[N - k:]
else:
index = bisect.bisect_left(arr, x)
low = max(0, index - k - 1)
high = min(N - 1, index + k - 1)
while high - low ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findClosestElements(self, arr, k, x):
""":type arr: List[int] :type k: int :type x: int :rtype: List[int]"""
<|body_0|>
def findClosestElements_sort(self, arr, k, x):
""":type arr: List[int] :type k: int :type x: int :rtype: List[int]"""
<|body_... | stack_v2_sparse_classes_36k_train_034798 | 1,244 | no_license | [
{
"docstring": ":type arr: List[int] :type k: int :type x: int :rtype: List[int]",
"name": "findClosestElements",
"signature": "def findClosestElements(self, arr, k, x)"
},
{
"docstring": ":type arr: List[int] :type k: int :type x: int :rtype: List[int]",
"name": "findClosestElements_sort",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findClosestElements(self, arr, k, x): :type arr: List[int] :type k: int :type x: int :rtype: List[int]
- def findClosestElements_sort(self, arr, k, x): :type arr: List[int] :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findClosestElements(self, arr, k, x): :type arr: List[int] :type k: int :type x: int :rtype: List[int]
- def findClosestElements_sort(self, arr, k, x): :type arr: List[int] :... | 1a3c1f4d6e9d3444039f087763b93241f4ba7892 | <|skeleton|>
class Solution:
def findClosestElements(self, arr, k, x):
""":type arr: List[int] :type k: int :type x: int :rtype: List[int]"""
<|body_0|>
def findClosestElements_sort(self, arr, k, x):
""":type arr: List[int] :type k: int :type x: int :rtype: List[int]"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findClosestElements(self, arr, k, x):
""":type arr: List[int] :type k: int :type x: int :rtype: List[int]"""
N = len(arr)
if x < arr[0]:
return arr[:k]
elif x > arr[-1]:
return arr[N - k:]
else:
index = bisect.bisect_lef... | the_stack_v2_python_sparse | Algorithm/658_Find_K_Closest_Elements.py | Gi1ia/TechNoteBook | train | 7 | |
1e3dba93ae471f32ec8b1a9eac7aaeb154273b37 | [
"self.data_train = tfds.load('ted_hrlr_translate/pt_to_en', split='train', as_supervised=True)\nself.data_valid = tfds.load('ted_hrlr_translate/pt_to_en', split='validation', as_supervised=True)\nself.tokenizer_pt, self.tokenizer_en = self.tokenize_dataset(self.data_train)",
"STE = tfds.deprecated.text.SubwordTex... | <|body_start_0|>
self.data_train = tfds.load('ted_hrlr_translate/pt_to_en', split='train', as_supervised=True)
self.data_valid = tfds.load('ted_hrlr_translate/pt_to_en', split='validation', as_supervised=True)
self.tokenizer_pt, self.tokenizer_en = self.tokenize_dataset(self.data_train)
<|end_bo... | loads and preps a dataset for machine translation | Dataset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""loads and preps a dataset for machine translation"""
def __init__(self):
"""creates the instance attributes: data_train, which contains the ted_hrlr_translate/pt_to en tf.data.Dataset train split, loaded as_supervided data_valid, which contains the ted_hrlr_translate/pt t... | stack_v2_sparse_classes_36k_train_034799 | 3,158 | no_license | [
{
"docstring": "creates the instance attributes: data_train, which contains the ted_hrlr_translate/pt_to en tf.data.Dataset train split, loaded as_supervided data_valid, which contains the ted_hrlr_translate/pt to_en tf.data.Dataset validate split, loaded as_supervided tokenizer_pt is the Portuguese tokenizer c... | 3 | null | Implement the Python class `Dataset` described below.
Class description:
loads and preps a dataset for machine translation
Method signatures and docstrings:
- def __init__(self): creates the instance attributes: data_train, which contains the ted_hrlr_translate/pt_to en tf.data.Dataset train split, loaded as_supervid... | Implement the Python class `Dataset` described below.
Class description:
loads and preps a dataset for machine translation
Method signatures and docstrings:
- def __init__(self): creates the instance attributes: data_train, which contains the ted_hrlr_translate/pt_to en tf.data.Dataset train split, loaded as_supervid... | 5114f884241b3406940b00450d8c71f55d5d6a70 | <|skeleton|>
class Dataset:
"""loads and preps a dataset for machine translation"""
def __init__(self):
"""creates the instance attributes: data_train, which contains the ted_hrlr_translate/pt_to en tf.data.Dataset train split, loaded as_supervided data_valid, which contains the ted_hrlr_translate/pt t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataset:
"""loads and preps a dataset for machine translation"""
def __init__(self):
"""creates the instance attributes: data_train, which contains the ted_hrlr_translate/pt_to en tf.data.Dataset train split, loaded as_supervided data_valid, which contains the ted_hrlr_translate/pt to_en tf.data.... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/1-dataset.py | icculp/holbertonschool-machine_learning | train | 0 |
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