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337bb0cb814fbcaa2b38156ace0b0437b8059f7f | [
"super().__init__()\nself.num_classes = num_classes\nself.num_features = self.embed_dim = embed_dim\nself.num_tokens = 2 if distilled else 1\nnorm_layer = norm_layer or partial(nn.LayerNorm, eps=1e-06)\nact_layer = act_layer or GELU\nself.patch_embed = embed_layer(img_size=img_size, patch_size=patch_size, in_chans=... | <|body_start_0|>
super().__init__()
self.num_classes = num_classes
self.num_features = self.embed_dim = embed_dim
self.num_tokens = 2 if distilled else 1
norm_layer = norm_layer or partial(nn.LayerNorm, eps=1e-06)
act_layer = act_layer or GELU
self.patch_embed = e... | Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: number of input channels :type in_chans: int :param num_classes: number of class for cla... | VisionTransformer | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VisionTransformer:
"""Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: number of input channels :type in_chans: in... | stack_v2_sparse_classes_10k_train_005900 | 9,222 | permissive | [
{
"docstring": "Construct the VisionTransformer class.",
"name": "__init__",
"signature": "def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classes=1000, embed_dim=768, depth=12, num_heads=12, mlp_ratio=4.0, qkv_bias=True, qk_scale=None, representation_size=None, distilled=False, drop_rat... | 2 | stack_v2_sparse_classes_30k_train_001497 | Implement the Python class `VisionTransformer` described below.
Class description:
Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: numb... | Implement the Python class `VisionTransformer` described below.
Class description:
Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: numb... | 12e37a1991eb6771a2999fe0a46ddda920c47948 | <|skeleton|>
class VisionTransformer:
"""Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: number of input channels :type in_chans: in... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VisionTransformer:
"""Vision Transformer:`An Image is Worth 16x16 Words: Transformers for Image Recognition atScale. :param img_size: input image size :type img_size: int, tuple :param patch_size: patch_size :type patch_size: int, tuple :param in_chans: number of input channels :type in_chans: int :param num_... | the_stack_v2_python_sparse | vega/networks/pytorch/transformer/vit.py | huawei-noah/vega | train | 850 |
0bb1de370d90ab6d6850b0a97fc631b8662c076a | [
"if not root:\n return str([])\nans = [root.val]\nqueue = [root]\nwhile queue:\n node = queue.pop(0)\n if node.left:\n queue.append(node.left)\n ans.append(node.left.val)\n else:\n ans.append(None)\n if node.right:\n queue.append(node.right)\n ans.append(node.right.... | <|body_start_0|>
if not root:
return str([])
ans = [root.val]
queue = [root]
while queue:
node = queue.pop(0)
if node.left:
queue.append(node.left)
ans.append(node.left.val)
else:
ans.append(N... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_005901 | 1,762 | 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:... | 54d777e11b91c5debe49c1aef723234c66a5d2cc | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return str([])
ans = [root.val]
queue = [root]
while queue:
node = queue.pop(0)
if node.left:
que... | the_stack_v2_python_sparse | leetcode_solution/tree/#297.Serialize_and_Deserialize_Binary_Tree.py | HsiangHung/Code-Challenges | train | 0 | |
4e795d4488a814ebc494485f02c8f499cea11005 | [
"user_id = get_jwt_identity()\nif user_id is None:\n query = Blog.select().where(Blog.published)\nelse:\n query = Blog.select()\nreturn paginate(query, pagination)",
"blog = Blog(**args)\nblog.date = datetime.utcnow()\nuser_id = get_jwt_identity()\ntry:\n user = User.get()\nexcept User.DoesNotExist:\n ... | <|body_start_0|>
user_id = get_jwt_identity()
if user_id is None:
query = Blog.select().where(Blog.published)
else:
query = Blog.select()
return paginate(query, pagination)
<|end_body_0|>
<|body_start_1|>
blog = Blog(**args)
blog.date = datetime.u... | BlogListAPI | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlogListAPI:
def get(self, pagination):
"""List blog posts"""
<|body_0|>
def post(self, pagination, args):
"""Create blog post"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user_id = get_jwt_identity()
if user_id is None:
query... | stack_v2_sparse_classes_10k_train_005902 | 4,891 | permissive | [
{
"docstring": "List blog posts",
"name": "get",
"signature": "def get(self, pagination)"
},
{
"docstring": "Create blog post",
"name": "post",
"signature": "def post(self, pagination, args)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004699 | Implement the Python class `BlogListAPI` described below.
Class description:
Implement the BlogListAPI class.
Method signatures and docstrings:
- def get(self, pagination): List blog posts
- def post(self, pagination, args): Create blog post | Implement the Python class `BlogListAPI` described below.
Class description:
Implement the BlogListAPI class.
Method signatures and docstrings:
- def get(self, pagination): List blog posts
- def post(self, pagination, args): Create blog post
<|skeleton|>
class BlogListAPI:
def get(self, pagination):
"""... | dffc3b1e16c24dd49e516e36aaa731a8dd299e66 | <|skeleton|>
class BlogListAPI:
def get(self, pagination):
"""List blog posts"""
<|body_0|>
def post(self, pagination, args):
"""Create blog post"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BlogListAPI:
def get(self, pagination):
"""List blog posts"""
user_id = get_jwt_identity()
if user_id is None:
query = Blog.select().where(Blog.published)
else:
query = Blog.select()
return paginate(query, pagination)
def post(self, paginati... | the_stack_v2_python_sparse | tilda/api/blog.py | tilda-center/backend | train | 0 | |
3e67135375e8e9ffc5c02e10c0562c42049e6251 | [
"user = request.user\naddress = Address.objects.get_default_address(user)\nreturn render(request, 'user_center_site.html', {'page': 'address', 'address': address})",
"receiver = request.POST.get('receiver')\naddr = request.POST.get('addr')\nzip_code = request.POST.get('zip_code')\nphone = request.POST.get('phone'... | <|body_start_0|>
user = request.user
address = Address.objects.get_default_address(user)
return render(request, 'user_center_site.html', {'page': 'address', 'address': address})
<|end_body_0|>
<|body_start_1|>
receiver = request.POST.get('receiver')
addr = request.POST.get('addr... | 用户中心-地址页 | AddressView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddressView:
"""用户中心-地址页"""
def get(self, request):
"""显示"""
<|body_0|>
def post(self, request):
"""地址的添加"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = request.user
address = Address.objects.get_default_address(user)
ret... | stack_v2_sparse_classes_10k_train_005903 | 11,775 | no_license | [
{
"docstring": "显示",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "地址的添加",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | null | Implement the Python class `AddressView` described below.
Class description:
用户中心-地址页
Method signatures and docstrings:
- def get(self, request): 显示
- def post(self, request): 地址的添加 | Implement the Python class `AddressView` described below.
Class description:
用户中心-地址页
Method signatures and docstrings:
- def get(self, request): 显示
- def post(self, request): 地址的添加
<|skeleton|>
class AddressView:
"""用户中心-地址页"""
def get(self, request):
"""显示"""
<|body_0|>
def post(self,... | 91293b05eb28697f5dec7f99a0f608904f6a0b1f | <|skeleton|>
class AddressView:
"""用户中心-地址页"""
def get(self, request):
"""显示"""
<|body_0|>
def post(self, request):
"""地址的添加"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddressView:
"""用户中心-地址页"""
def get(self, request):
"""显示"""
user = request.user
address = Address.objects.get_default_address(user)
return render(request, 'user_center_site.html', {'page': 'address', 'address': address})
def post(self, request):
"""地址的添加"""
... | the_stack_v2_python_sparse | dailyfresh/apps/user/views.py | IronmanJay/Python_Project | train | 15 |
f1120224241851c19baa225fddf63173832d53ab | [
"try:\n serializer = PatientHistoryFilesSerializers(PatientHistoryFiles.objects.all(), many=True)\n return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)\nexcept Exception as e:\n info_message = 'Internal Server Error'\n logger.error(info_message, e)\n return JsonRespons... | <|body_start_0|>
try:
serializer = PatientHistoryFilesSerializers(PatientHistoryFiles.objects.all(), many=True)
return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)
except Exception as e:
info_message = 'Internal Server Error'
... | PatientHistoryFilesView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PatientHistoryFilesView:
def get(self, request):
"""Get all patients"""
<|body_0|>
def post(self, request):
"""Save patient data"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
serializer = PatientHistoryFilesSerializers(PatientHist... | stack_v2_sparse_classes_10k_train_005904 | 12,219 | no_license | [
{
"docstring": "Get all patients",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Save patient data",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002896 | Implement the Python class `PatientHistoryFilesView` described below.
Class description:
Implement the PatientHistoryFilesView class.
Method signatures and docstrings:
- def get(self, request): Get all patients
- def post(self, request): Save patient data | Implement the Python class `PatientHistoryFilesView` described below.
Class description:
Implement the PatientHistoryFilesView class.
Method signatures and docstrings:
- def get(self, request): Get all patients
- def post(self, request): Save patient data
<|skeleton|>
class PatientHistoryFilesView:
def get(self... | b63849983a592fd6a1f654191020fd86aa0787ae | <|skeleton|>
class PatientHistoryFilesView:
def get(self, request):
"""Get all patients"""
<|body_0|>
def post(self, request):
"""Save patient data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PatientHistoryFilesView:
def get(self, request):
"""Get all patients"""
try:
serializer = PatientHistoryFilesSerializers(PatientHistoryFiles.objects.all(), many=True)
return JsonResponse({'message': 'listed all', 'data': serializer.data}, status=200)
except Exce... | the_stack_v2_python_sparse | patient/views.py | RupeshKurlekar/biocare | train | 1 | |
0504d39c19d4a0d19ef084e4f71ae35eb99d31bc | [
"super(RelationalPointerNet, self).__init__()\nself.hidden_size = hidden_size\ninitializer = nn.initializer.TruncatedNormal(std=init_range)\nself.q = _build_linear(hidden_size, hidden_size, new_name(name, 'query_fc'), initializer)\nself.k = _build_linear(hidden_size, hidden_size, new_name(name, 'key_fc'), initializ... | <|body_start_0|>
super(RelationalPointerNet, self).__init__()
self.hidden_size = hidden_size
initializer = nn.initializer.TruncatedNormal(std=init_range)
self.q = _build_linear(hidden_size, hidden_size, new_name(name, 'query_fc'), initializer)
self.k = _build_linear(hidden_size, ... | Pointer Netword with Relations | RelationalPointerNet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelationalPointerNet:
"""Pointer Netword with Relations"""
def __init__(self, hidden_size, num_relations, init_range=0.02, name=None):
"""init of class Args: cfg (TYPE): NULL"""
<|body_0|>
def forward(self, queries, keys, relations, attn_bias=None):
"""relational... | stack_v2_sparse_classes_10k_train_005905 | 15,933 | permissive | [
{
"docstring": "init of class Args: cfg (TYPE): NULL",
"name": "__init__",
"signature": "def __init__(self, hidden_size, num_relations, init_range=0.02, name=None)"
},
{
"docstring": "relational attention forward. seq_len in `shape` means num queries/keys/values of attention Args: queries (TYPE)... | 2 | null | Implement the Python class `RelationalPointerNet` described below.
Class description:
Pointer Netword with Relations
Method signatures and docstrings:
- def __init__(self, hidden_size, num_relations, init_range=0.02, name=None): init of class Args: cfg (TYPE): NULL
- def forward(self, queries, keys, relations, attn_b... | Implement the Python class `RelationalPointerNet` described below.
Class description:
Pointer Netword with Relations
Method signatures and docstrings:
- def __init__(self, hidden_size, num_relations, init_range=0.02, name=None): init of class Args: cfg (TYPE): NULL
- def forward(self, queries, keys, relations, attn_b... | b8ec015fa9e16c0a879c619ee1f2aab8a393c7bd | <|skeleton|>
class RelationalPointerNet:
"""Pointer Netword with Relations"""
def __init__(self, hidden_size, num_relations, init_range=0.02, name=None):
"""init of class Args: cfg (TYPE): NULL"""
<|body_0|>
def forward(self, queries, keys, relations, attn_bias=None):
"""relational... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RelationalPointerNet:
"""Pointer Netword with Relations"""
def __init__(self, hidden_size, num_relations, init_range=0.02, name=None):
"""init of class Args: cfg (TYPE): NULL"""
super(RelationalPointerNet, self).__init__()
self.hidden_size = hidden_size
initializer = nn.in... | the_stack_v2_python_sparse | NLP/Text2SQL-BASELINE/text2sql/models/relational_transformer.py | sserdoubleh/Research | train | 10 |
81566d03b343c74dfea384fb5bcdd5eb05be66be | [
"index = 'test_index'\nsketch_id = 1\nanalyzer = SessionizerSketchPlugin(index, sketch_id)\nanalyzer.datastore.client = mock.Mock()\ndatastore = analyzer.datastore\n_create_mock_event(datastore, 0, 3, time_diffs=[3000, 400000000])\nmessage = analyzer.run()\nself.assertEqual(message, 'Sessionizing completed, number ... | <|body_start_0|>
index = 'test_index'
sketch_id = 1
analyzer = SessionizerSketchPlugin(index, sketch_id)
analyzer.datastore.client = mock.Mock()
datastore = analyzer.datastore
_create_mock_event(datastore, 0, 3, time_diffs=[3000, 400000000])
message = analyzer.run... | Tests the functionality of the sessionizing sketch analyzer, focusing on edge cases. | TestSessionizerPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSessionizerPlugin:
"""Tests the functionality of the sessionizing sketch analyzer, focusing on edge cases."""
def test_multiple_sessions(self):
"""Test multiple events, two of which are in the same session and one in a different session."""
<|body_0|>
def test_zero_t... | stack_v2_sparse_classes_10k_train_005906 | 4,019 | permissive | [
{
"docstring": "Test multiple events, two of which are in the same session and one in a different session.",
"name": "test_multiple_sessions",
"signature": "def test_multiple_sessions(self)"
},
{
"docstring": "Test events with no time difference between them are allocated correctly.",
"name"... | 4 | stack_v2_sparse_classes_30k_train_003903 | Implement the Python class `TestSessionizerPlugin` described below.
Class description:
Tests the functionality of the sessionizing sketch analyzer, focusing on edge cases.
Method signatures and docstrings:
- def test_multiple_sessions(self): Test multiple events, two of which are in the same session and one in a diff... | Implement the Python class `TestSessionizerPlugin` described below.
Class description:
Tests the functionality of the sessionizing sketch analyzer, focusing on edge cases.
Method signatures and docstrings:
- def test_multiple_sessions(self): Test multiple events, two of which are in the same session and one in a diff... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class TestSessionizerPlugin:
"""Tests the functionality of the sessionizing sketch analyzer, focusing on edge cases."""
def test_multiple_sessions(self):
"""Test multiple events, two of which are in the same session and one in a different session."""
<|body_0|>
def test_zero_t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestSessionizerPlugin:
"""Tests the functionality of the sessionizing sketch analyzer, focusing on edge cases."""
def test_multiple_sessions(self):
"""Test multiple events, two of which are in the same session and one in a different session."""
index = 'test_index'
sketch_id = 1
... | the_stack_v2_python_sparse | timesketch/lib/analyzers/sessionizer_test.py | google/timesketch | train | 2,263 |
3316157bbfd1532827ce99a1bce30a30dfb37d54 | [
"if not re.search('^[a-zA-Z0-9._]+$', v):\n raise ValueError('must be alphanumeric')\nreturn v",
"if not values.get('password_old'):\n raise ValueError('old password is required')\nreturn v",
"if not values.get('password_new_1') or v != values['password_new_1']:\n raise ValueError('passwords do not mat... | <|body_start_0|>
if not re.search('^[a-zA-Z0-9._]+$', v):
raise ValueError('must be alphanumeric')
return v
<|end_body_0|>
<|body_start_1|>
if not values.get('password_old'):
raise ValueError('old password is required')
return v
<|end_body_1|>
<|body_start_2|>
... | User update schema. | UpdateUserIn | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateUserIn:
"""User update schema."""
def username_valid(cls, v: Any) -> Any:
"""Username validator. Args: v (Any): Username value. Raises: ValueError: Username invalid. Returns: Any: Username valid."""
<|body_0|>
def passwords_match_1(cls, v: Any, values: Any, **kwarg... | stack_v2_sparse_classes_10k_train_005907 | 4,438 | no_license | [
{
"docstring": "Username validator. Args: v (Any): Username value. Raises: ValueError: Username invalid. Returns: Any: Username valid.",
"name": "username_valid",
"signature": "def username_valid(cls, v: Any) -> Any"
},
{
"docstring": "Check if filled password_new_1 and password_old. Args: v (An... | 3 | stack_v2_sparse_classes_30k_train_001462 | Implement the Python class `UpdateUserIn` described below.
Class description:
User update schema.
Method signatures and docstrings:
- def username_valid(cls, v: Any) -> Any: Username validator. Args: v (Any): Username value. Raises: ValueError: Username invalid. Returns: Any: Username valid.
- def passwords_match_1(c... | Implement the Python class `UpdateUserIn` described below.
Class description:
User update schema.
Method signatures and docstrings:
- def username_valid(cls, v: Any) -> Any: Username validator. Args: v (Any): Username value. Raises: ValueError: Username invalid. Returns: Any: Username valid.
- def passwords_match_1(c... | 8082d3ce9c999c79228a36aa160b4171140440cb | <|skeleton|>
class UpdateUserIn:
"""User update schema."""
def username_valid(cls, v: Any) -> Any:
"""Username validator. Args: v (Any): Username value. Raises: ValueError: Username invalid. Returns: Any: Username valid."""
<|body_0|>
def passwords_match_1(cls, v: Any, values: Any, **kwarg... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UpdateUserIn:
"""User update schema."""
def username_valid(cls, v: Any) -> Any:
"""Username validator. Args: v (Any): Username value. Raises: ValueError: Username invalid. Returns: Any: Username valid."""
if not re.search('^[a-zA-Z0-9._]+$', v):
raise ValueError('must be alpha... | the_stack_v2_python_sparse | app/users/schemas.py | douglaspands/api-server-py | train | 2 |
d15d3c0d50820b63dd4b4dee44cd473f17f6cdce | [
"super(ProjectQueueManager, self).__init__()\nself.zk_client = zk_client\nself.project_id = project_id\nproject_dsn_node = '/appscale/projects/{}/postgres_dsn'.format(project_id)\nglobal_dsn_node = '/appscale/tasks/postgres_dsn'\nif self.zk_client.exists(project_dsn_node):\n pg_dsn = self.zk_client.get(project_d... | <|body_start_0|>
super(ProjectQueueManager, self).__init__()
self.zk_client = zk_client
self.project_id = project_id
project_dsn_node = '/appscale/projects/{}/postgres_dsn'.format(project_id)
global_dsn_node = '/appscale/tasks/postgres_dsn'
if self.zk_client.exists(projec... | Keeps track of queue configuration details for a single project. | ProjectQueueManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectQueueManager:
"""Keeps track of queue configuration details for a single project."""
def __init__(self, zk_client, project_id):
"""Creates a new ProjectQueueManager. Args: zk_client: A KazooClient. project_id: A string specifying a project ID."""
<|body_0|>
def up... | stack_v2_sparse_classes_10k_train_005908 | 7,391 | permissive | [
{
"docstring": "Creates a new ProjectQueueManager. Args: zk_client: A KazooClient. project_id: A string specifying a project ID.",
"name": "__init__",
"signature": "def __init__(self, zk_client, project_id)"
},
{
"docstring": "Caches new configuration details and cleans up old state. Args: queue... | 6 | null | Implement the Python class `ProjectQueueManager` described below.
Class description:
Keeps track of queue configuration details for a single project.
Method signatures and docstrings:
- def __init__(self, zk_client, project_id): Creates a new ProjectQueueManager. Args: zk_client: A KazooClient. project_id: A string s... | Implement the Python class `ProjectQueueManager` described below.
Class description:
Keeps track of queue configuration details for a single project.
Method signatures and docstrings:
- def __init__(self, zk_client, project_id): Creates a new ProjectQueueManager. Args: zk_client: A KazooClient. project_id: A string s... | be17e5f658d7b42b5aa7eeb7a5ddd4962f3ea82f | <|skeleton|>
class ProjectQueueManager:
"""Keeps track of queue configuration details for a single project."""
def __init__(self, zk_client, project_id):
"""Creates a new ProjectQueueManager. Args: zk_client: A KazooClient. project_id: A string specifying a project ID."""
<|body_0|>
def up... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProjectQueueManager:
"""Keeps track of queue configuration details for a single project."""
def __init__(self, zk_client, project_id):
"""Creates a new ProjectQueueManager. Args: zk_client: A KazooClient. project_id: A string specifying a project ID."""
super(ProjectQueueManager, self).__... | the_stack_v2_python_sparse | AppTaskQueue/appscale/taskqueue/queue_manager.py | obino/appscale | train | 1 |
5d1d15bc365c7fbe007055020eac9e62c690077f | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | DataBusServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataBusServicer:
def Publish(self, request, context):
"""Declares the intention to write data to a topic, must be called once before any Write."""
<|body_0|>
def Subscribe(self, request, context):
"""Declares the intention to read data from a topic, must be called on... | stack_v2_sparse_classes_10k_train_005909 | 6,014 | no_license | [
{
"docstring": "Declares the intention to write data to a topic, must be called once before any Write.",
"name": "Publish",
"signature": "def Publish(self, request, context)"
},
{
"docstring": "Declares the intention to read data from a topic, must be called once before any Read.",
"name": "... | 6 | stack_v2_sparse_classes_30k_train_000622 | Implement the Python class `DataBusServicer` described below.
Class description:
Implement the DataBusServicer class.
Method signatures and docstrings:
- def Publish(self, request, context): Declares the intention to write data to a topic, must be called once before any Write.
- def Subscribe(self, request, context):... | Implement the Python class `DataBusServicer` described below.
Class description:
Implement the DataBusServicer class.
Method signatures and docstrings:
- def Publish(self, request, context): Declares the intention to write data to a topic, must be called once before any Write.
- def Subscribe(self, request, context):... | 090b9bd6af1fdf012afc4b7cc19c3c80e4651dba | <|skeleton|>
class DataBusServicer:
def Publish(self, request, context):
"""Declares the intention to write data to a topic, must be called once before any Write."""
<|body_0|>
def Subscribe(self, request, context):
"""Declares the intention to read data from a topic, must be called on... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DataBusServicer:
def Publish(self, request, context):
"""Declares the intention to write data to a topic, must be called once before any Write."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method no... | the_stack_v2_python_sparse | NativeAPI/Native-API/Tools/DataConversion/python/metamoto/services/data_bus_pb2_grpc.py | Huzefa-Kagalwala/OpenCAV-Metamoto | train | 0 | |
5a467c98604adea269491366bc99eb4cdf316c88 | [
"for extension_id, extension in sorted(settings_dict.items()):\n try:\n install_time = int(extension.get(u'install_time', u'0'), 10)\n except ValueError as exception:\n logging.warning(u'Extension ID {0:s} is missing timestamp: {1:s}'.format(extension_id, exception))\n continue\n manif... | <|body_start_0|>
for extension_id, extension in sorted(settings_dict.items()):
try:
install_time = int(extension.get(u'install_time', u'0'), 10)
except ValueError as exception:
logging.warning(u'Extension ID {0:s} is missing timestamp: {1:s}'.format(extens... | Parses Chrome Preferences files. | ChromePreferencesParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChromePreferencesParser:
"""Parses Chrome Preferences files."""
def _ExtractExtensionInstallEvents(self, settings_dict, parser_mediator):
"""Extract extension installation events. Args: settings_dict: A dictionary of settings data from Preferences file. parser_mediator: A parser medi... | stack_v2_sparse_classes_10k_train_005910 | 4,285 | permissive | [
{
"docstring": "Extract extension installation events. Args: settings_dict: A dictionary of settings data from Preferences file. parser_mediator: A parser mediator object (instance of ParserMediator).",
"name": "_ExtractExtensionInstallEvents",
"signature": "def _ExtractExtensionInstallEvents(self, sett... | 2 | stack_v2_sparse_classes_30k_train_002801 | Implement the Python class `ChromePreferencesParser` described below.
Class description:
Parses Chrome Preferences files.
Method signatures and docstrings:
- def _ExtractExtensionInstallEvents(self, settings_dict, parser_mediator): Extract extension installation events. Args: settings_dict: A dictionary of settings d... | Implement the Python class `ChromePreferencesParser` described below.
Class description:
Parses Chrome Preferences files.
Method signatures and docstrings:
- def _ExtractExtensionInstallEvents(self, settings_dict, parser_mediator): Extract extension installation events. Args: settings_dict: A dictionary of settings d... | 0ee446ebf03d17c515f76a666bd3795e91a2dd17 | <|skeleton|>
class ChromePreferencesParser:
"""Parses Chrome Preferences files."""
def _ExtractExtensionInstallEvents(self, settings_dict, parser_mediator):
"""Extract extension installation events. Args: settings_dict: A dictionary of settings data from Preferences file. parser_mediator: A parser medi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ChromePreferencesParser:
"""Parses Chrome Preferences files."""
def _ExtractExtensionInstallEvents(self, settings_dict, parser_mediator):
"""Extract extension installation events. Args: settings_dict: A dictionary of settings data from Preferences file. parser_mediator: A parser mediator object (... | the_stack_v2_python_sparse | plaso/parsers/chrome_preferences.py | aarontp/plaso | train | 1 |
059f6039c91304e330752a684b56e9cd88eeaebf | [
"super().__init__(kernel_size, erosion_iters=0)\nself.prob_threshold = prob_threshold\nself.__erosion_iters = erosion_iters",
"filter_mask = prob_filter(mask=mask, prob_threshold=self.prob_threshold)\ntrimap = super(TrimapGenerator, self).__call__(original_image, filter_mask)\nnew_trimap = prob_as_unknown_area(tr... | <|body_start_0|>
super().__init__(kernel_size, erosion_iters=0)
self.prob_threshold = prob_threshold
self.__erosion_iters = erosion_iters
<|end_body_0|>
<|body_start_1|>
filter_mask = prob_filter(mask=mask, prob_threshold=self.prob_threshold)
trimap = super(TrimapGenerator, self... | TrimapGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrimapGenerator:
def __init__(self, prob_threshold: int=231, kernel_size: int=30, erosion_iters: int=5):
"""Initialize a TrimapGenerator instance Args: prob_threshold: Probability threshold at which the prob_filter and prob_as_unknown_area operations will be applied kernel_size: The size... | stack_v2_sparse_classes_10k_train_005911 | 1,955 | permissive | [
{
"docstring": "Initialize a TrimapGenerator instance Args: prob_threshold: Probability threshold at which the prob_filter and prob_as_unknown_area operations will be applied kernel_size: The size of the offset from the object mask in pixels when an unknown area is detected in the trimap erosion_iters: The numb... | 2 | stack_v2_sparse_classes_30k_train_005518 | Implement the Python class `TrimapGenerator` described below.
Class description:
Implement the TrimapGenerator class.
Method signatures and docstrings:
- def __init__(self, prob_threshold: int=231, kernel_size: int=30, erosion_iters: int=5): Initialize a TrimapGenerator instance Args: prob_threshold: Probability thre... | Implement the Python class `TrimapGenerator` described below.
Class description:
Implement the TrimapGenerator class.
Method signatures and docstrings:
- def __init__(self, prob_threshold: int=231, kernel_size: int=30, erosion_iters: int=5): Initialize a TrimapGenerator instance Args: prob_threshold: Probability thre... | 2935e4655d2c0260195e22ac08af6c43b5969fdd | <|skeleton|>
class TrimapGenerator:
def __init__(self, prob_threshold: int=231, kernel_size: int=30, erosion_iters: int=5):
"""Initialize a TrimapGenerator instance Args: prob_threshold: Probability threshold at which the prob_filter and prob_as_unknown_area operations will be applied kernel_size: The size... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TrimapGenerator:
def __init__(self, prob_threshold: int=231, kernel_size: int=30, erosion_iters: int=5):
"""Initialize a TrimapGenerator instance Args: prob_threshold: Probability threshold at which the prob_filter and prob_as_unknown_area operations will be applied kernel_size: The size of the offset... | the_stack_v2_python_sparse | carvekit/trimap/generator.py | OPHoperHPO/image-background-remove-tool | train | 1,029 | |
e25fab7c14a8ec487c117e48e4a7c55e5b285c36 | [
"inSpec = super(FastFourierTransform, cls).getInputSpecification()\ninSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringListType, strictMode=True))\nreturn inSpec",
"super().__init__()\nself.dynamic = True\nself.targets = None\nself.indices = None",
"super()._handleInput(paramIn... | <|body_start_0|>
inSpec = super(FastFourierTransform, cls).getInputSpecification()
inSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringListType, strictMode=True))
return inSpec
<|end_body_0|>
<|body_start_1|>
super().__init__()
self.dynamic = Tru... | Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target | FastFourierTransform | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastFourierTransform:
"""Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target"""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the ... | stack_v2_sparse_classes_10k_train_005912 | 6,142 | permissive | [
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for which we are retrieving the specification @ Out, inputSpecification, InputData.ParameterInput, class to use for specifying input of cls.",
"name": "getInputSpecification",
"signatur... | 6 | null | Implement the Python class `FastFourierTransform` described below.
Class description:
Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target
Method signatures and docstrings:
- def getInputSpecification(cls): Method to get a reference to a class tha... | Implement the Python class `FastFourierTransform` described below.
Class description:
Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target
Method signatures and docstrings:
- def getInputSpecification(cls): Method to get a reference to a class tha... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class FastFourierTransform:
"""Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target"""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FastFourierTransform:
"""Constructs fast-fourier transform data for a history Outputs are "frequency" for each index and "amplitude" for each target"""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for whi... | the_stack_v2_python_sparse | ravenframework/Models/PostProcessors/FastFourierTransform.py | idaholab/raven | train | 201 |
bfda53fbb253e99a8aa1086af9e69c1c83720e8e | [
"def traverse_longest(row, col, prev_num):\n if not (0 <= row < m and 0 <= col < n):\n return 0\n current_num = matrix[row][col]\n if current_num <= prev_num:\n return 0\n up = traverse_longest(row - 1, col, current_num)\n down = traverse_longest(row + 1, col, current_num)\n left = t... | <|body_start_0|>
def traverse_longest(row, col, prev_num):
if not (0 <= row < m and 0 <= col < n):
return 0
current_num = matrix[row][col]
if current_num <= prev_num:
return 0
up = traverse_longest(row - 1, col, current_num)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestIncreasingPath(self, matrix: list[list[int]]) -> int:
"""DFS"""
<|body_0|>
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""memoization"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def traverse_longest(row,... | stack_v2_sparse_classes_10k_train_005913 | 1,958 | no_license | [
{
"docstring": "DFS",
"name": "longestIncreasingPath",
"signature": "def longestIncreasingPath(self, matrix: list[list[int]]) -> int"
},
{
"docstring": "memoization",
"name": "longestIncreasingPath",
"signature": "def longestIncreasingPath(self, matrix: List[List[int]]) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestIncreasingPath(self, matrix: list[list[int]]) -> int: DFS
- def longestIncreasingPath(self, matrix: List[List[int]]) -> int: memoization | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestIncreasingPath(self, matrix: list[list[int]]) -> int: DFS
- def longestIncreasingPath(self, matrix: List[List[int]]) -> int: memoization
<|skeleton|>
class Solution:
... | e50dc0642f087f37ab3234390be3d8a0ed48fe62 | <|skeleton|>
class Solution:
def longestIncreasingPath(self, matrix: list[list[int]]) -> int:
"""DFS"""
<|body_0|>
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""memoization"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestIncreasingPath(self, matrix: list[list[int]]) -> int:
"""DFS"""
def traverse_longest(row, col, prev_num):
if not (0 <= row < m and 0 <= col < n):
return 0
current_num = matrix[row][col]
if current_num <= prev_num:
... | the_stack_v2_python_sparse | Leetcode/329. Longest Increasing Path in a Matrix.py | brlala/Educative-Grokking-Coding-Exercise | train | 3 | |
a5428b1a799611dac61e81dbc7ee2f8a16a80f57 | [
"if str2bool(value):\n return queryset.filter(allocated__gte=F('quantity'))\nelse:\n return queryset.filter(allocated__lt=F('quantity'))",
"flt = Q(quantity__lte=F('total_available_stock') + F('allocated'))\nif str2bool(value):\n return queryset.filter(flt)\nelse:\n return queryset.exclude(flt)"
] | <|body_start_0|>
if str2bool(value):
return queryset.filter(allocated__gte=F('quantity'))
else:
return queryset.filter(allocated__lt=F('quantity'))
<|end_body_0|>
<|body_start_1|>
flt = Q(quantity__lte=F('total_available_stock') + F('allocated'))
if str2bool(valu... | Custom filterset for the BuildLine API endpoint. | BuildLineFilter | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BuildLineFilter:
"""Custom filterset for the BuildLine API endpoint."""
def filter_allocated(self, queryset, name, value):
"""Filter by whether each BuildLine is fully allocated"""
<|body_0|>
def filter_available(self, queryset, name, value):
"""Filter by whether... | stack_v2_sparse_classes_10k_train_005914 | 20,912 | permissive | [
{
"docstring": "Filter by whether each BuildLine is fully allocated",
"name": "filter_allocated",
"signature": "def filter_allocated(self, queryset, name, value)"
},
{
"docstring": "Filter by whether there is sufficient stock available for each BuildLine: To determine this, we need to know: - Th... | 2 | null | Implement the Python class `BuildLineFilter` described below.
Class description:
Custom filterset for the BuildLine API endpoint.
Method signatures and docstrings:
- def filter_allocated(self, queryset, name, value): Filter by whether each BuildLine is fully allocated
- def filter_available(self, queryset, name, valu... | Implement the Python class `BuildLineFilter` described below.
Class description:
Custom filterset for the BuildLine API endpoint.
Method signatures and docstrings:
- def filter_allocated(self, queryset, name, value): Filter by whether each BuildLine is fully allocated
- def filter_available(self, queryset, name, valu... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class BuildLineFilter:
"""Custom filterset for the BuildLine API endpoint."""
def filter_allocated(self, queryset, name, value):
"""Filter by whether each BuildLine is fully allocated"""
<|body_0|>
def filter_available(self, queryset, name, value):
"""Filter by whether... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BuildLineFilter:
"""Custom filterset for the BuildLine API endpoint."""
def filter_allocated(self, queryset, name, value):
"""Filter by whether each BuildLine is fully allocated"""
if str2bool(value):
return queryset.filter(allocated__gte=F('quantity'))
else:
... | the_stack_v2_python_sparse | InvenTree/build/api.py | inventree/InvenTree | train | 3,077 |
062cb0a03e9e0d28a433e76ce216ab3434960fbf | [
"if n == 1:\n return x\nif n == 0:\n return 1\nflag = 1 if n > 0 else -1\nn = abs(n)\nresult = x\ni = 1\nwhile 2 * i <= n:\n result *= result\n i *= 2\nif i < n:\n result = result * self.myPow(x, n - i)\nreturn result if flag == 1 else 1 / result",
"if x == 0:\n return 0\nif n == 0:\n return ... | <|body_start_0|>
if n == 1:
return x
if n == 0:
return 1
flag = 1 if n > 0 else -1
n = abs(n)
result = x
i = 1
while 2 * i <= n:
result *= result
i *= 2
if i < n:
result = result * self.myPow(x, n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def myPow(self, x, n):
""":type x: float :type n: int :rtype: float"""
<|body_0|>
def myPow1(self, x, n):
""":type x: float :type n: int :rtype: float"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 1:
return x
... | stack_v2_sparse_classes_10k_train_005915 | 1,123 | no_license | [
{
"docstring": ":type x: float :type n: int :rtype: float",
"name": "myPow",
"signature": "def myPow(self, x, n)"
},
{
"docstring": ":type x: float :type n: int :rtype: float",
"name": "myPow1",
"signature": "def myPow1(self, x, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006814 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myPow(self, x, n): :type x: float :type n: int :rtype: float
- def myPow1(self, x, n): :type x: float :type n: int :rtype: float | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myPow(self, x, n): :type x: float :type n: int :rtype: float
- def myPow1(self, x, n): :type x: float :type n: int :rtype: float
<|skeleton|>
class Solution:
def myPow(... | 707829268535a80cfe0ffa1dc0623520c3fcbecf | <|skeleton|>
class Solution:
def myPow(self, x, n):
""":type x: float :type n: int :rtype: float"""
<|body_0|>
def myPow1(self, x, n):
""":type x: float :type n: int :rtype: float"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def myPow(self, x, n):
""":type x: float :type n: int :rtype: float"""
if n == 1:
return x
if n == 0:
return 1
flag = 1 if n > 0 else -1
n = abs(n)
result = x
i = 1
while 2 * i <= n:
result *= result
... | the_stack_v2_python_sparse | leetcode/1-50/_50_my_pow.py | blackwings001/algorithm | train | 0 | |
3bfa569bd9e828d08fb8a64bb2baf36d19cdd4c2 | [
"def isPalindrome(s):\n return s == s[::-1]\nmemo = {}\n\ndef helper(s):\n if not s:\n return [[]]\n if s in memo:\n return memo[s]\n res = []\n for i in range(len(s)):\n if isPalindrome(s[:i + 1]):\n cur = [s[:i + 1]]\n pars = helper(s[i + 1:])\n ... | <|body_start_0|>
def isPalindrome(s):
return s == s[::-1]
memo = {}
def helper(s):
if not s:
return [[]]
if s in memo:
return memo[s]
res = []
for i in range(len(s)):
if isPalindrome(s[:i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def partitionDP(self, s):
""":type s: str :rtype: List[List[str]]"""
<|body_0|>
def partition(self, s):
""":type s: str :rtype: List[List[str]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def isPalindrome(s):
return s == s[... | stack_v2_sparse_classes_10k_train_005916 | 2,078 | no_license | [
{
"docstring": ":type s: str :rtype: List[List[str]]",
"name": "partitionDP",
"signature": "def partitionDP(self, s)"
},
{
"docstring": ":type s: str :rtype: List[List[str]]",
"name": "partition",
"signature": "def partition(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def partitionDP(self, s): :type s: str :rtype: List[List[str]]
- def partition(self, s): :type s: str :rtype: List[List[str]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def partitionDP(self, s): :type s: str :rtype: List[List[str]]
- def partition(self, s): :type s: str :rtype: List[List[str]]
<|skeleton|>
class Solution:
def partitionDP(s... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def partitionDP(self, s):
""":type s: str :rtype: List[List[str]]"""
<|body_0|>
def partition(self, s):
""":type s: str :rtype: List[List[str]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def partitionDP(self, s):
""":type s: str :rtype: List[List[str]]"""
def isPalindrome(s):
return s == s[::-1]
memo = {}
def helper(s):
if not s:
return [[]]
if s in memo:
return memo[s]
r... | the_stack_v2_python_sparse | P/PalindromePartitioning.py | bssrdf/pyleet | train | 2 | |
f5c5a18915ab0e0258610c43e7a7109d16e7bf9a | [
"Parametre.__init__(self, 'boire', 'drink')\nself.tronquer = True\nself.schema = '<nom_familier>'\nself.aide_courte = 'demande à un familier de boire'\nself.aide_longue = \"Cette commande demande au familier dont le nom est précisé en paramètre de boire dans la salle où vous vous trouvez. Les familiers peuvent boir... | <|body_start_0|>
Parametre.__init__(self, 'boire', 'drink')
self.tronquer = True
self.schema = '<nom_familier>'
self.aide_courte = 'demande à un familier de boire'
self.aide_longue = "Cette commande demande au familier dont le nom est précisé en paramètre de boire dans la salle o... | Commande 'familier boire'. | PrmBoire | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmBoire:
"""Commande 'familier boire'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Parametre.__... | stack_v2_sparse_classes_10k_train_005917 | 3,357 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | null | Implement the Python class `PrmBoire` described below.
Class description:
Commande 'familier boire'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmBoire` described below.
Class description:
Commande 'familier boire'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmBoire:
"""Commande 'familier b... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmBoire:
"""Commande 'familier boire'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrmBoire:
"""Commande 'familier boire'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'boire', 'drink')
self.tronquer = True
self.schema = '<nom_familier>'
self.aide_courte = 'demande à un familier de boire'
self.aide_longu... | the_stack_v2_python_sparse | src/secondaires/familier/commandes/familier/boire.py | vincent-lg/tsunami | train | 5 |
c0568e744e921152adc81bb20b5c56296d1e42d8 | [
"if root is None:\n return True\nreturn self.isSameTree(root.left, root.right)",
"if left is None and right is None:\n return True\nif left is not None and right is None or (left is None and right is not None):\n return False\nif left.val != right.val:\n return False\nelse:\n return self.isSameTree... | <|body_start_0|>
if root is None:
return True
return self.isSameTree(root.left, root.right)
<|end_body_0|>
<|body_start_1|>
if left is None and right is None:
return True
if left is not None and right is None or (left is None and right is not None):
r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isSameTree(self, left, right):
"""rType: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is None:
return True
return self.... | stack_v2_sparse_classes_10k_train_005918 | 978 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isSymmetric",
"signature": "def isSymmetric(self, root)"
},
{
"docstring": "rType: bool",
"name": "isSameTree",
"signature": "def isSameTree(self, left, right)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isSymmetric(self, root): :type root: TreeNode :rtype: bool
- def isSameTree(self, left, right): rType: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isSymmetric(self, root): :type root: TreeNode :rtype: bool
- def isSameTree(self, left, right): rType: bool
<|skeleton|>
class Solution:
def isSymmetric(self, root):
... | 0821af55eca60084b503b5f751301048c55e4381 | <|skeleton|>
class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isSameTree(self, left, right):
"""rType: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isSymmetric(self, root):
""":type root: TreeNode :rtype: bool"""
if root is None:
return True
return self.isSameTree(root.left, root.right)
def isSameTree(self, left, right):
"""rType: bool"""
if left is None and right is None:
... | the_stack_v2_python_sparse | Easy/LC101SymmetricTree_S2.py | shuowenwei/LeetCodePython | train | 2 | |
85e7427e530ede4a43da2a2ee54dd9a962d3faef | [
"if await self.check_user_guild(guild_id, user.id):\n return\nasync with aiosqlite.connect(self.resolved_db_path) as db:\n if not await self.check_global_user(user.id):\n await db.execute('INSERT INTO Users (id, name) VALUES (?, ?)', (user.id, user.name))\n await db.execute('INSERT INTO Users_Guilds... | <|body_start_0|>
if await self.check_user_guild(guild_id, user.id):
return
async with aiosqlite.connect(self.resolved_db_path) as db:
if not await self.check_global_user(user.id):
await db.execute('INSERT INTO Users (id, name) VALUES (?, ?)', (user.id, user.name))... | UserRepository | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRepository:
async def add_user(self, user: discord.Member, guild_id: int) -> None:
"""Adds a User to the global users table and/or to the guild specific user tables Args: user (discord.Member) guild_id (int)"""
<|body_0|>
async def check_global_user(self, user_id: int) -... | stack_v2_sparse_classes_10k_train_005919 | 1,912 | permissive | [
{
"docstring": "Adds a User to the global users table and/or to the guild specific user tables Args: user (discord.Member) guild_id (int)",
"name": "add_user",
"signature": "async def add_user(self, user: discord.Member, guild_id: int) -> None"
},
{
"docstring": "Checks if the user is in the glo... | 3 | stack_v2_sparse_classes_30k_train_004388 | Implement the Python class `UserRepository` described below.
Class description:
Implement the UserRepository class.
Method signatures and docstrings:
- async def add_user(self, user: discord.Member, guild_id: int) -> None: Adds a User to the global users table and/or to the guild specific user tables Args: user (disc... | Implement the Python class `UserRepository` described below.
Class description:
Implement the UserRepository class.
Method signatures and docstrings:
- async def add_user(self, user: discord.Member, guild_id: int) -> None: Adds a User to the global users table and/or to the guild specific user tables Args: user (disc... | 2f8b45f06abb510029f3461ab5e39535a5eb3385 | <|skeleton|>
class UserRepository:
async def add_user(self, user: discord.Member, guild_id: int) -> None:
"""Adds a User to the global users table and/or to the guild specific user tables Args: user (discord.Member) guild_id (int)"""
<|body_0|>
async def check_global_user(self, user_id: int) -... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserRepository:
async def add_user(self, user: discord.Member, guild_id: int) -> None:
"""Adds a User to the global users table and/or to the guild specific user tables Args: user (discord.Member) guild_id (int)"""
if await self.check_user_guild(guild_id, user.id):
return
a... | the_stack_v2_python_sparse | bot/data/user_repository.py | new-zelind/ClemBot | train | 1 | |
e9b8e24fe6ad82416d65ccf6a39742bf7257fbeb | [
"if base == tgt:\n a = tmp[:]\n lst.append(a)\n return\nfor i in xrange(depth, len(ref)):\n if base + ref[i] <= tgt:\n tmp.append(ref[i])\n self.CS(base + ref[i], tgt, lst, ref, tmp, i)\n tmp.pop()",
"candidates.sort()\nres, tmp = ([], [])\nself.CS(0, target, res, candidates, tmp,... | <|body_start_0|>
if base == tgt:
a = tmp[:]
lst.append(a)
return
for i in xrange(depth, len(ref)):
if base + ref[i] <= tgt:
tmp.append(ref[i])
self.CS(base + ref[i], tgt, lst, ref, tmp, i)
tmp.pop()
<|end_bod... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def CS(self, base, tgt, lst, ref, tmp, depth):
"""base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int... | stack_v2_sparse_classes_10k_train_005920 | 3,337 | no_license | [
{
"docstring": "base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数",
"name": "CS",
"signature": "def CS(self, base, tgt, lst, ref, tmp, depth)"
},
{
"docstring": ":type candidates: List[int] :type target: int :rtype: List[List[in... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def CS(self, base, tgt, lst, ref, tmp, depth): base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数
- def combina... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def CS(self, base, tgt, lst, ref, tmp, depth): base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数
- def combina... | 507ed2efeff7818ca9cf53a8ee7fb80d3c530d67 | <|skeleton|>
class Solution:
def CS(self, base, tgt, lst, ref, tmp, depth):
"""base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def CS(self, base, tgt, lst, ref, tmp, depth):
"""base: value already calculated tgt: target number lst: result List ref: candidates List tmp: one answer depth: 到了第几个数"""
if base == tgt:
a = tmp[:]
lst.append(a)
return
for i in xrange(depth... | the_stack_v2_python_sparse | Leetcode/Backtracking/#39-Combination Sum/main.py | qizongjun/Algorithms-1 | train | 0 | |
dab0dea68b9be9f10c1eab6194d1621fde193094 | [
"if not args_lateral:\n args_lateral = {'K_P': 1.0, 'K_D': 0.0, 'K_I': 0.0}\nif not args_longitudinal:\n args_longitudinal = {'K_P': 1.0, 'K_D': 0.0, 'K_I': 0.0}\nself._lon_controller = PIDLongitudinalController(**args_longitudinal)\nself._lat_controller = PIDLateralController(**args_lateral)",
"throttle = ... | <|body_start_0|>
if not args_lateral:
args_lateral = {'K_P': 1.0, 'K_D': 0.0, 'K_I': 0.0}
if not args_longitudinal:
args_longitudinal = {'K_P': 1.0, 'K_D': 0.0, 'K_I': 0.0}
self._lon_controller = PIDLongitudinalController(**args_longitudinal)
self._lat_controller ... | VehiclePIDController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VehiclePIDController:
def __init__(self, args_lateral=None, args_longitudinal=None):
""":param args_lateral: dictionary of arguments to set the lateral PID controller using the following semantics: K_P -- Proportional term K_D -- Differential term K_I -- Integral term :param args_longitu... | stack_v2_sparse_classes_10k_train_005921 | 6,840 | no_license | [
{
"docstring": ":param args_lateral: dictionary of arguments to set the lateral PID controller using the following semantics: K_P -- Proportional term K_D -- Differential term K_I -- Integral term :param args_longitudinal: dictionary of arguments to set the longitudinal PID controller using the following semant... | 2 | stack_v2_sparse_classes_30k_train_005987 | Implement the Python class `VehiclePIDController` described below.
Class description:
Implement the VehiclePIDController class.
Method signatures and docstrings:
- def __init__(self, args_lateral=None, args_longitudinal=None): :param args_lateral: dictionary of arguments to set the lateral PID controller using the fo... | Implement the Python class `VehiclePIDController` described below.
Class description:
Implement the VehiclePIDController class.
Method signatures and docstrings:
- def __init__(self, args_lateral=None, args_longitudinal=None): :param args_lateral: dictionary of arguments to set the lateral PID controller using the fo... | 0f5cd710a6fff1c19795662f8032cb9e22575bd7 | <|skeleton|>
class VehiclePIDController:
def __init__(self, args_lateral=None, args_longitudinal=None):
""":param args_lateral: dictionary of arguments to set the lateral PID controller using the following semantics: K_P -- Proportional term K_D -- Differential term K_I -- Integral term :param args_longitu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VehiclePIDController:
def __init__(self, args_lateral=None, args_longitudinal=None):
""":param args_lateral: dictionary of arguments to set the lateral PID controller using the following semantics: K_P -- Proportional term K_D -- Differential term K_I -- Integral term :param args_longitudinal: diction... | the_stack_v2_python_sparse | planning/trajectory_planner/trajectory_planner/controller.py | feiyuxiaoThu/IITS | train | 0 | |
3de7e65d8aff5eeabe000b15a93114d834d21ec2 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | The CAS (content-addressable storage) is used to store the inputs to and outputs from the execution service. Each piece of content is addressed by the digest of its binary data. Most of the binary data stored in the CAS is opaque to the execution engine, and is only used as a communication medium. In order to build an ... | ContentAddressableStorageServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContentAddressableStorageServicer:
"""The CAS (content-addressable storage) is used to store the inputs to and outputs from the execution service. Each piece of content is addressed by the digest of its binary data. Most of the binary data stored in the CAS is opaque to the execution engine, and ... | stack_v2_sparse_classes_10k_train_005922 | 24,490 | no_license | [
{
"docstring": "Determine if blobs are present in the CAS. Clients can use this API before uploading blobs to determine which ones are already present in the CAS and do not need to be uploaded again. There are no method-specific errors.",
"name": "FindMissingBlobs",
"signature": "def FindMissingBlobs(se... | 3 | stack_v2_sparse_classes_30k_train_003378 | Implement the Python class `ContentAddressableStorageServicer` described below.
Class description:
The CAS (content-addressable storage) is used to store the inputs to and outputs from the execution service. Each piece of content is addressed by the digest of its binary data. Most of the binary data stored in the CAS ... | Implement the Python class `ContentAddressableStorageServicer` described below.
Class description:
The CAS (content-addressable storage) is used to store the inputs to and outputs from the execution service. Each piece of content is addressed by the digest of its binary data. Most of the binary data stored in the CAS ... | d7424d21aa0dc121acc4d64b427ba365a3581a20 | <|skeleton|>
class ContentAddressableStorageServicer:
"""The CAS (content-addressable storage) is used to store the inputs to and outputs from the execution service. Each piece of content is addressed by the digest of its binary data. Most of the binary data stored in the CAS is opaque to the execution engine, and ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ContentAddressableStorageServicer:
"""The CAS (content-addressable storage) is used to store the inputs to and outputs from the execution service. Each piece of content is addressed by the digest of its binary data. Most of the binary data stored in the CAS is opaque to the execution engine, and is only used ... | the_stack_v2_python_sparse | google/devtools/remoteexecution/v1test/remote_execution_pb2_grpc.py | msachtler/bazel-event-protocol-parser | train | 1 |
a707f7bc33a7190670796ae04b2a01a3c4be5472 | [
"cur_sum = 0\nways = 0\nif len(nums) == 0:\n return ways\nways = self.dfs(nums, cur_sum, S)\nreturn ways",
"ways = 0\nnums_length = len(nums)\nif nums_length == 0:\n if cur_sum == S:\n return 1\n return 0\nmultiple = [1, -1]\nfor value in multiple:\n new_num = nums[nums_length - 1]\n new_num... | <|body_start_0|>
cur_sum = 0
ways = 0
if len(nums) == 0:
return ways
ways = self.dfs(nums, cur_sum, S)
return ways
<|end_body_0|>
<|body_start_1|>
ways = 0
nums_length = len(nums)
if nums_length == 0:
if cur_sum == S:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findTargetSumWays(self, nums, S):
"""find the target sum by nums, and get the total ways to get that :param nums: :type: list[int] :param S: :type: int :return: :rtype: int"""
<|body_0|>
def dfs(self, nums, cur_sum, S):
"""depth first search the target ... | stack_v2_sparse_classes_10k_train_005923 | 2,744 | no_license | [
{
"docstring": "find the target sum by nums, and get the total ways to get that :param nums: :type: list[int] :param S: :type: int :return: :rtype: int",
"name": "findTargetSumWays",
"signature": "def findTargetSumWays(self, nums, S)"
},
{
"docstring": "depth first search the target num :param n... | 2 | stack_v2_sparse_classes_30k_train_002586 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTargetSumWays(self, nums, S): find the target sum by nums, and get the total ways to get that :param nums: :type: list[int] :param S: :type: int :return: :rtype: int
- de... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findTargetSumWays(self, nums, S): find the target sum by nums, and get the total ways to get that :param nums: :type: list[int] :param S: :type: int :return: :rtype: int
- de... | 37710292b2cfc6060098363c8d5f8881a4c22b26 | <|skeleton|>
class Solution:
def findTargetSumWays(self, nums, S):
"""find the target sum by nums, and get the total ways to get that :param nums: :type: list[int] :param S: :type: int :return: :rtype: int"""
<|body_0|>
def dfs(self, nums, cur_sum, S):
"""depth first search the target ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findTargetSumWays(self, nums, S):
"""find the target sum by nums, and get the total ways to get that :param nums: :type: list[int] :param S: :type: int :return: :rtype: int"""
cur_sum = 0
ways = 0
if len(nums) == 0:
return ways
ways = self.dfs(... | the_stack_v2_python_sparse | python/pyleetcode/queue_and_stack/targetSum.py | yudongnan23/algorithmRoad | train | 0 | |
9591dbcf659188b0ac6a3d826ec5202e6382be19 | [
"super().__init__()\nself.nr_points = 5500\nself.acq_rate = 'FAcq'\nself.timeout_bpms = 10\nself.ch_kick = 5\nself.cv_kick = 5\nself.rf_kick = 5\nself.delay_corrs = 0.05\nself.delay_rf = 0.2\nself.exc_duration = 5\nself.exc_rf = 4\nfreqs = self.find_primes(16, start=120)\nself.ch_freqs = freqs[1::2][:6]\nself.cv_fr... | <|body_start_0|>
super().__init__()
self.nr_points = 5500
self.acq_rate = 'FAcq'
self.timeout_bpms = 10
self.ch_kick = 5
self.cv_kick = 5
self.rf_kick = 5
self.delay_corrs = 0.05
self.delay_rf = 0.2
self.exc_duration = 5
self.exc_rf... | . | ACORMParams | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ACORMParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
<|body_1|>
def find_primes(n_primes, start=3):
"""."""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
super().__init__()
self.nr_po... | stack_v2_sparse_classes_10k_train_005924 | 38,752 | permissive | [
{
"docstring": ".",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ".",
"name": "__str__",
"signature": "def __str__(self)"
},
{
"docstring": ".",
"name": "find_primes",
"signature": "def find_primes(n_primes, start=3)"
}
] | 3 | stack_v2_sparse_classes_30k_train_001883 | Implement the Python class `ACORMParams` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self): .
- def __str__(self): .
- def find_primes(n_primes, start=3): . | Implement the Python class `ACORMParams` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self): .
- def __str__(self): .
- def find_primes(n_primes, start=3): .
<|skeleton|>
class ACORMParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __st... | 39644161d98964a3a3d80d63269201f0a1712e82 | <|skeleton|>
class ACORMParams:
"""."""
def __init__(self):
"""."""
<|body_0|>
def __str__(self):
"""."""
<|body_1|>
def find_primes(n_primes, start=3):
"""."""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ACORMParams:
"""."""
def __init__(self):
"""."""
super().__init__()
self.nr_points = 5500
self.acq_rate = 'FAcq'
self.timeout_bpms = 10
self.ch_kick = 5
self.cv_kick = 5
self.rf_kick = 5
self.delay_corrs = 0.05
self.delay_rf ... | the_stack_v2_python_sparse | apsuite/commisslib/meas_ac_orm.py | lnls-fac/apsuite | train | 1 |
0258983c9b059ccec072195ce6e1f212887933f0 | [
"if context is None:\n context = {}\nsuper(building_fill_insurance, self).view_init(cr, uid, fields_list, context=context)\nif len(context.get('active_ids', [])) > 1:\n raise osv.except_osv(_('Error!'), _('You cannot perform this operation on more than one building.'))\nif context.get('active_id', False):\n ... | <|body_start_0|>
if context is None:
context = {}
super(building_fill_insurance, self).view_init(cr, uid, fields_list, context=context)
if len(context.get('active_ids', [])) > 1:
raise osv.except_osv(_('Error!'), _('You cannot perform this operation on more than one build... | building_fill_insurance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class building_fill_insurance:
def view_init(self, cr, uid, fields_list, context=None):
"""Creates view dynamically and adding fields at runtime. @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param context: A standard dictionary @... | stack_v2_sparse_classes_10k_train_005925 | 4,027 | no_license | [
{
"docstring": "Creates view dynamically and adding fields at runtime. @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param context: A standard dictionary @return: New arch of view with new columns.",
"name": "view_init",
"signature": "def v... | 2 | null | Implement the Python class `building_fill_insurance` described below.
Class description:
Implement the building_fill_insurance class.
Method signatures and docstrings:
- def view_init(self, cr, uid, fields_list, context=None): Creates view dynamically and adding fields at runtime. @param self: The object pointer. @pa... | Implement the Python class `building_fill_insurance` described below.
Class description:
Implement the building_fill_insurance class.
Method signatures and docstrings:
- def view_init(self, cr, uid, fields_list, context=None): Creates view dynamically and adding fields at runtime. @param self: The object pointer. @pa... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class building_fill_insurance:
def view_init(self, cr, uid, fields_list, context=None):
"""Creates view dynamically and adding fields at runtime. @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param context: A standard dictionary @... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class building_fill_insurance:
def view_init(self, cr, uid, fields_list, context=None):
"""Creates view dynamically and adding fields at runtime. @param self: The object pointer. @param cr: A database cursor @param uid: ID of the user currently logged in @param context: A standard dictionary @return: New ar... | the_stack_v2_python_sparse | v_7/GDS/shamil_v3/building_management_6.1/wizard/building_fill_insurance.py | musabahmed/baba | train | 0 | |
2d9b0e4ac0596a74cd5b7d4f4f3be33a071d72ad | [
"fieldsets = super().get_fieldsets(request, obj)\nfieldsets += ((_('Extra info'), {'fields': ['created', 'modified']}),)\nreturn fieldsets",
"readonly_fields = super().get_readonly_fields(request, obj)\nreadonly_fields = readonly_fields + ('created', 'modified')\nif not self.create_only_fields or not obj:\n re... | <|body_start_0|>
fieldsets = super().get_fieldsets(request, obj)
fieldsets += ((_('Extra info'), {'fields': ['created', 'modified']}),)
return fieldsets
<|end_body_0|>
<|body_start_1|>
readonly_fields = super().get_readonly_fields(request, obj)
readonly_fields = readonly_fields ... | Base admin representation. | BaseAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseAdmin:
"""Base admin representation."""
def get_fieldsets(self, request, obj=None):
"""Add created and modified to fieldsets."""
<|body_0|>
def get_readonly_fields(self, request, obj=None):
"""Add created and modified to readonly_fields. Also if create_only_f... | stack_v2_sparse_classes_10k_train_005926 | 1,885 | no_license | [
{
"docstring": "Add created and modified to fieldsets.",
"name": "get_fieldsets",
"signature": "def get_fieldsets(self, request, obj=None)"
},
{
"docstring": "Add created and modified to readonly_fields. Also if create_only_fields were specified add them to readonly_fields, if user is working on... | 2 | stack_v2_sparse_classes_30k_train_005545 | Implement the Python class `BaseAdmin` described below.
Class description:
Base admin representation.
Method signatures and docstrings:
- def get_fieldsets(self, request, obj=None): Add created and modified to fieldsets.
- def get_readonly_fields(self, request, obj=None): Add created and modified to readonly_fields. ... | Implement the Python class `BaseAdmin` described below.
Class description:
Base admin representation.
Method signatures and docstrings:
- def get_fieldsets(self, request, obj=None): Add created and modified to fieldsets.
- def get_readonly_fields(self, request, obj=None): Add created and modified to readonly_fields. ... | 0879ade24685b628624dce06698f8a0afd042000 | <|skeleton|>
class BaseAdmin:
"""Base admin representation."""
def get_fieldsets(self, request, obj=None):
"""Add created and modified to fieldsets."""
<|body_0|>
def get_readonly_fields(self, request, obj=None):
"""Add created and modified to readonly_fields. Also if create_only_f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseAdmin:
"""Base admin representation."""
def get_fieldsets(self, request, obj=None):
"""Add created and modified to fieldsets."""
fieldsets = super().get_fieldsets(request, obj)
fieldsets += ((_('Extra info'), {'fields': ['created', 'modified']}),)
return fieldsets
... | the_stack_v2_python_sparse | project_template/apps/core/admin.py | rhanmar/oi_projects_summer_2021 | train | 0 |
c09dd5c06160b9e5c00ea28e0610d0f0268def4d | [
"if level is None:\n self.logLevel = logging.INFO\nelse:\n pass",
"logger = logging.getLogger(_name)\nlogger.setLevel(self.logLevel)\nhandler = logging.FileHandler('output_files/log_examp.log')\nhandler.setLevel(self.logLevel)\nformatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(messag... | <|body_start_0|>
if level is None:
self.logLevel = logging.INFO
else:
pass
<|end_body_0|>
<|body_start_1|>
logger = logging.getLogger(_name)
logger.setLevel(self.logLevel)
handler = logging.FileHandler('output_files/log_examp.log')
handler.setLeve... | DOCSTRING. | CfgLogger | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CfgLogger:
"""DOCSTRING."""
def __init__(self, level=None):
"""DOCSTRING."""
<|body_0|>
def create_logger(self, _name):
"""DOCSTRING."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if level is None:
self.logLevel = logging.INFO
... | stack_v2_sparse_classes_10k_train_005927 | 836 | no_license | [
{
"docstring": "DOCSTRING.",
"name": "__init__",
"signature": "def __init__(self, level=None)"
},
{
"docstring": "DOCSTRING.",
"name": "create_logger",
"signature": "def create_logger(self, _name)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001805 | Implement the Python class `CfgLogger` described below.
Class description:
DOCSTRING.
Method signatures and docstrings:
- def __init__(self, level=None): DOCSTRING.
- def create_logger(self, _name): DOCSTRING. | Implement the Python class `CfgLogger` described below.
Class description:
DOCSTRING.
Method signatures and docstrings:
- def __init__(self, level=None): DOCSTRING.
- def create_logger(self, _name): DOCSTRING.
<|skeleton|>
class CfgLogger:
"""DOCSTRING."""
def __init__(self, level=None):
"""DOCSTRIN... | 4c4b8fb381c8d98980e119f7f73f393034393468 | <|skeleton|>
class CfgLogger:
"""DOCSTRING."""
def __init__(self, level=None):
"""DOCSTRING."""
<|body_0|>
def create_logger(self, _name):
"""DOCSTRING."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CfgLogger:
"""DOCSTRING."""
def __init__(self, level=None):
"""DOCSTRING."""
if level is None:
self.logLevel = logging.INFO
else:
pass
def create_logger(self, _name):
"""DOCSTRING."""
logger = logging.getLogger(_name)
logger.set... | the_stack_v2_python_sparse | Python_Scripts/config/log.py | jommysmoth/ECE_Music | train | 0 |
e997c1f2b04618bc041ea64344df7098fce80640 | [
"self.name = name\nself.args = []\nfor arg in args:\n self.args.append(arg)",
"s = self.name\nfor arg in self.args:\n s += ' '\n s += str(arg)\nreturn s",
"s = self.name.encode()\nfor arg in self.args:\n s += ESCAPE_CHARACTER + arg.encode()\ns += b'\\n'\ntry:\n verbose('Internal: Sending [', s.de... | <|body_start_0|>
self.name = name
self.args = []
for arg in args:
self.args.append(arg)
<|end_body_0|>
<|body_start_1|>
s = self.name
for arg in self.args:
s += ' '
s += str(arg)
return s
<|end_body_1|>
<|body_start_2|>
s = se... | Message | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message:
def __init__(self, name, *args):
"""Instantiates a new Message. :param name: The name of the command. :param args: The parameters of the command."""
<|body_0|>
def __str__(self) -> str:
"""Converts this object to a String object. :return: This object as a St... | stack_v2_sparse_classes_10k_train_005928 | 1,167 | permissive | [
{
"docstring": "Instantiates a new Message. :param name: The name of the command. :param args: The parameters of the command.",
"name": "__init__",
"signature": "def __init__(self, name, *args)"
},
{
"docstring": "Converts this object to a String object. :return: This object as a String.",
"... | 3 | stack_v2_sparse_classes_30k_train_006279 | Implement the Python class `Message` described below.
Class description:
Implement the Message class.
Method signatures and docstrings:
- def __init__(self, name, *args): Instantiates a new Message. :param name: The name of the command. :param args: The parameters of the command.
- def __str__(self) -> str: Converts ... | Implement the Python class `Message` described below.
Class description:
Implement the Message class.
Method signatures and docstrings:
- def __init__(self, name, *args): Instantiates a new Message. :param name: The name of the command. :param args: The parameters of the command.
- def __str__(self) -> str: Converts ... | 57660ec8ed3b431779524bd40540acf1cb212f6f | <|skeleton|>
class Message:
def __init__(self, name, *args):
"""Instantiates a new Message. :param name: The name of the command. :param args: The parameters of the command."""
<|body_0|>
def __str__(self) -> str:
"""Converts this object to a String object. :return: This object as a St... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Message:
def __init__(self, name, *args):
"""Instantiates a new Message. :param name: The name of the command. :param args: The parameters of the command."""
self.name = name
self.args = []
for arg in args:
self.args.append(arg)
def __str__(self) -> str:
... | the_stack_v2_python_sparse | server/src/network/message.py | CLOVIS-AI/ccg2lambda-qa-assistant | train | 2 | |
740462d93d94264c1f8d97f55cc55c93d0172a6d | [
"self.config = config.setup()\nself.log = logging.getLogger(__name__)\nserver = self.config.get('IMAP', 'server')\nport = int(self.config.get('IMAP', 'port', 143))\nself.user = self.config.get('IMAP', 'user')\npassword = self.config.get('IMAP', 'password')\nself.mailbox_group = self.config.get('IMAP', 'mailbox_grou... | <|body_start_0|>
self.config = config.setup()
self.log = logging.getLogger(__name__)
server = self.config.get('IMAP', 'server')
port = int(self.config.get('IMAP', 'port', 143))
self.user = self.config.get('IMAP', 'user')
password = self.config.get('IMAP', 'password')
... | Provide CRUD methods to Cyrus IMAP mailboxes | SpokeMbx | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpokeMbx:
"""Provide CRUD methods to Cyrus IMAP mailboxes"""
def __init__(self):
"""Get config, setup logging and cyrus connection."""
<|body_0|>
def _validate_mailbox_name(self, mailbox_name):
"""Ensure input is a valid email address format."""
<|body_1|... | stack_v2_sparse_classes_10k_train_005929 | 3,866 | permissive | [
{
"docstring": "Get config, setup logging and cyrus connection.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Ensure input is a valid email address format.",
"name": "_validate_mailbox_name",
"signature": "def _validate_mailbox_name(self, mailbox_name)"
},
... | 5 | stack_v2_sparse_classes_30k_train_003134 | Implement the Python class `SpokeMbx` described below.
Class description:
Provide CRUD methods to Cyrus IMAP mailboxes
Method signatures and docstrings:
- def __init__(self): Get config, setup logging and cyrus connection.
- def _validate_mailbox_name(self, mailbox_name): Ensure input is a valid email address format.... | Implement the Python class `SpokeMbx` described below.
Class description:
Provide CRUD methods to Cyrus IMAP mailboxes
Method signatures and docstrings:
- def __init__(self): Get config, setup logging and cyrus connection.
- def _validate_mailbox_name(self, mailbox_name): Ensure input is a valid email address format.... | 077d45750643a38b1062a9199800de9c9de900ae | <|skeleton|>
class SpokeMbx:
"""Provide CRUD methods to Cyrus IMAP mailboxes"""
def __init__(self):
"""Get config, setup logging and cyrus connection."""
<|body_0|>
def _validate_mailbox_name(self, mailbox_name):
"""Ensure input is a valid email address format."""
<|body_1|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SpokeMbx:
"""Provide CRUD methods to Cyrus IMAP mailboxes"""
def __init__(self):
"""Get config, setup logging and cyrus connection."""
self.config = config.setup()
self.log = logging.getLogger(__name__)
server = self.config.get('IMAP', 'server')
port = int(self.con... | the_stack_v2_python_sparse | spoke/lib/mbx.py | KrisSaxton/spoke | train | 0 |
0dbd7c11be62197540c652848ca26a367fbb1505 | [
"cls.dirname = os.path.abspath(os.path.join(os.path.dirname(__file__), 'temp'))\nos.makedirs(os.path.join(cls.dirname, 'pdep'))\ntest_family = 'R_Recombination'\ncls.rmg = RMG()\nfrom rmgpy.rmg.input import set_global_rmg, pressure_dependence\nset_global_rmg(cls.rmg)\npressure_dependence(method='modified strong col... | <|body_start_0|>
cls.dirname = os.path.abspath(os.path.join(os.path.dirname(__file__), 'temp'))
os.makedirs(os.path.join(cls.dirname, 'pdep'))
test_family = 'R_Recombination'
cls.rmg = RMG()
from rmgpy.rmg.input import set_global_rmg, pressure_dependence
set_global_rmg(cl... | Contains unit tests for CoreEdgeReactionModel.enlarge. | TestEnlarge | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestEnlarge:
"""Contains unit tests for CoreEdgeReactionModel.enlarge."""
def setUpClass(cls):
"""A method that is run ONCE before all unit tests in this class."""
<|body_0|>
def test_enlarge_1_add_nonreactive_species(self):
"""Test that we can add a nonreactive ... | stack_v2_sparse_classes_10k_train_005930 | 34,780 | permissive | [
{
"docstring": "A method that is run ONCE before all unit tests in this class.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Test that we can add a nonreactive species to CERM",
"name": "test_enlarge_1_add_nonreactive_species",
"signature": "def test_enlar... | 6 | stack_v2_sparse_classes_30k_train_000553 | Implement the Python class `TestEnlarge` described below.
Class description:
Contains unit tests for CoreEdgeReactionModel.enlarge.
Method signatures and docstrings:
- def setUpClass(cls): A method that is run ONCE before all unit tests in this class.
- def test_enlarge_1_add_nonreactive_species(self): Test that we c... | Implement the Python class `TestEnlarge` described below.
Class description:
Contains unit tests for CoreEdgeReactionModel.enlarge.
Method signatures and docstrings:
- def setUpClass(cls): A method that is run ONCE before all unit tests in this class.
- def test_enlarge_1_add_nonreactive_species(self): Test that we c... | 349a4af759cf8877197772cd7eaca1e51d46eff5 | <|skeleton|>
class TestEnlarge:
"""Contains unit tests for CoreEdgeReactionModel.enlarge."""
def setUpClass(cls):
"""A method that is run ONCE before all unit tests in this class."""
<|body_0|>
def test_enlarge_1_add_nonreactive_species(self):
"""Test that we can add a nonreactive ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestEnlarge:
"""Contains unit tests for CoreEdgeReactionModel.enlarge."""
def setUpClass(cls):
"""A method that is run ONCE before all unit tests in this class."""
cls.dirname = os.path.abspath(os.path.join(os.path.dirname(__file__), 'temp'))
os.makedirs(os.path.join(cls.dirname, ... | the_stack_v2_python_sparse | rmgpy/rmg/modelTest.py | CanePan-cc/CanePanWorkshop | train | 2 |
af00d63970ed50f846ba6bb2be62bc662bc00015 | [
"queue = deque()\nqueue.append(root)\nwhile queue:\n size = len(queue)\n self.value = queue[0].val\n for _ in range(size):\n node = queue.popleft()\n if node.left:\n queue.append(node.left)\n if node.right:\n queue.append(node.right)\nreturn self.value",
"queue ... | <|body_start_0|>
queue = deque()
queue.append(root)
while queue:
size = len(queue)
self.value = queue[0].val
for _ in range(size):
node = queue.popleft()
if node.left:
queue.append(node.left)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findBottomLeftValue(self, root: TreeNode) -> int:
"""BFS"""
<|body_0|>
def findBottomLeftValue_1(self, root: TreeNode) -> int:
"""改进版BFS"""
<|body_1|>
def findBottomLeftValue_2(self, root: TreeNode) -> int:
"""DFS"""
<|body_... | stack_v2_sparse_classes_10k_train_005931 | 1,622 | no_license | [
{
"docstring": "BFS",
"name": "findBottomLeftValue",
"signature": "def findBottomLeftValue(self, root: TreeNode) -> int"
},
{
"docstring": "改进版BFS",
"name": "findBottomLeftValue_1",
"signature": "def findBottomLeftValue_1(self, root: TreeNode) -> int"
},
{
"docstring": "DFS",
... | 3 | stack_v2_sparse_classes_30k_val_000312 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findBottomLeftValue(self, root: TreeNode) -> int: BFS
- def findBottomLeftValue_1(self, root: TreeNode) -> int: 改进版BFS
- def findBottomLeftValue_2(self, root: TreeNode) -> in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findBottomLeftValue(self, root: TreeNode) -> int: BFS
- def findBottomLeftValue_1(self, root: TreeNode) -> int: 改进版BFS
- def findBottomLeftValue_2(self, root: TreeNode) -> in... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def findBottomLeftValue(self, root: TreeNode) -> int:
"""BFS"""
<|body_0|>
def findBottomLeftValue_1(self, root: TreeNode) -> int:
"""改进版BFS"""
<|body_1|>
def findBottomLeftValue_2(self, root: TreeNode) -> int:
"""DFS"""
<|body_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def findBottomLeftValue(self, root: TreeNode) -> int:
"""BFS"""
queue = deque()
queue.append(root)
while queue:
size = len(queue)
self.value = queue[0].val
for _ in range(size):
node = queue.popleft()
... | the_stack_v2_python_sparse | algorithm/leetcode/bfs/13-找树左下角的值.py | lxconfig/UbuntuCode_bak | train | 0 | |
3f57ee985d79ce69b0e510aff3a59a90e31c59d9 | [
"super(CNN_Text, self).__init__()\nself.args = args\nembed_num = args.embed_num\nembed_dim = args.embed_dim\nclass_num = args.class_num\nchannel_num = args.kernel_num\nkernel_size = args.kernel_sizes\nself.embedding = nn.Embedding(embed_num, embed_dim)\nself.conv = nn.ModuleList([nn.Conv2d(1, channel_num, (K, embed... | <|body_start_0|>
super(CNN_Text, self).__init__()
self.args = args
embed_num = args.embed_num
embed_dim = args.embed_dim
class_num = args.class_num
channel_num = args.kernel_num
kernel_size = args.kernel_sizes
self.embedding = nn.Embedding(embed_num, embed... | CNN_Text | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CNN_Text:
def __init__(self, args):
"""Your code here. Define a text CNN structure. Note that args.kernel_sizes is a list, so you may need to use nn.ModuleList."""
<|body_0|>
def forward(self, x):
"""Your code here. Give the forward pass of the model. With multiple k... | stack_v2_sparse_classes_10k_train_005932 | 1,450 | no_license | [
{
"docstring": "Your code here. Define a text CNN structure. Note that args.kernel_sizes is a list, so you may need to use nn.ModuleList.",
"name": "__init__",
"signature": "def __init__(self, args)"
},
{
"docstring": "Your code here. Give the forward pass of the model. With multiple kernel size... | 2 | stack_v2_sparse_classes_30k_train_000952 | Implement the Python class `CNN_Text` described below.
Class description:
Implement the CNN_Text class.
Method signatures and docstrings:
- def __init__(self, args): Your code here. Define a text CNN structure. Note that args.kernel_sizes is a list, so you may need to use nn.ModuleList.
- def forward(self, x): Your c... | Implement the Python class `CNN_Text` described below.
Class description:
Implement the CNN_Text class.
Method signatures and docstrings:
- def __init__(self, args): Your code here. Define a text CNN structure. Note that args.kernel_sizes is a list, so you may need to use nn.ModuleList.
- def forward(self, x): Your c... | f1af0599ac8c3c8be4852472838dca775a22aa53 | <|skeleton|>
class CNN_Text:
def __init__(self, args):
"""Your code here. Define a text CNN structure. Note that args.kernel_sizes is a list, so you may need to use nn.ModuleList."""
<|body_0|>
def forward(self, x):
"""Your code here. Give the forward pass of the model. With multiple k... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CNN_Text:
def __init__(self, args):
"""Your code here. Define a text CNN structure. Note that args.kernel_sizes is a list, so you may need to use nn.ModuleList."""
super(CNN_Text, self).__init__()
self.args = args
embed_num = args.embed_num
embed_dim = args.embed_dim
... | the_stack_v2_python_sparse | homework5/HuaiyuanYing/model.py | Lukeming-tsinghua/pytorch-NLP-guidance | train | 12 | |
01aad50b5e7ac76aa13671e1e6209ad65cdcae1f | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn WindowsFirewallNetworkProfile()",
"from .state_management_setting import StateManagementSetting\nfrom .state_management_setting import StateManagementSetting\nfields: Dict[str, Callable[[Any], None]] = {'authorizedApplicationRulesFromG... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return WindowsFirewallNetworkProfile()
<|end_body_0|>
<|body_start_1|>
from .state_management_setting import StateManagementSetting
from .state_management_setting import StateManagementSetting
... | Windows Firewall Profile Policies. | WindowsFirewallNetworkProfile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WindowsFirewallNetworkProfile:
"""Windows Firewall Profile Policies."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WindowsFirewallNetworkProfile:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pa... | stack_v2_sparse_classes_10k_train_005933 | 9,152 | 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: WindowsFirewallNetworkProfile",
"name": "create_from_discriminator_value",
"signature": "def create_from_dis... | 3 | null | Implement the Python class `WindowsFirewallNetworkProfile` described below.
Class description:
Windows Firewall Profile Policies.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WindowsFirewallNetworkProfile: Creates a new instance of the appropriate cl... | Implement the Python class `WindowsFirewallNetworkProfile` described below.
Class description:
Windows Firewall Profile Policies.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WindowsFirewallNetworkProfile: Creates a new instance of the appropriate cl... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class WindowsFirewallNetworkProfile:
"""Windows Firewall Profile Policies."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WindowsFirewallNetworkProfile:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The pa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WindowsFirewallNetworkProfile:
"""Windows Firewall Profile Policies."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WindowsFirewallNetworkProfile:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to u... | the_stack_v2_python_sparse | msgraph/generated/models/windows_firewall_network_profile.py | microsoftgraph/msgraph-sdk-python | train | 135 |
93965f7990b3f3f128d051b99b6e550b136ab733 | [
"if not (is_scalar(prior) or isinstance(prior, Beta) or is_any_numeric_map(prior) or is_any_beta_map(prior)):\n raise ValueError('wrong type for prior')\nif not (is_scalar(likelihood) or isinstance(likelihood, Beta) or is_any_numeric_map(likelihood) or is_any_beta_map(likelihood)):\n raise ValueError('wrong t... | <|body_start_0|>
if not (is_scalar(prior) or isinstance(prior, Beta) or is_any_numeric_map(prior) or is_any_beta_map(prior)):
raise ValueError('wrong type for prior')
if not (is_scalar(likelihood) or isinstance(likelihood, Beta) or is_any_numeric_map(likelihood) or is_any_beta_map(likelihood... | Class for testing one or more binary hypotheses using Bayes Rule. | BinaryBayesRule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryBayesRule:
"""Class for testing one or more binary hypotheses using Bayes Rule."""
def __init__(self, prior: Union[float, Beta, AnyFloatMap, AnyBetaMap], likelihood: Union[float, Beta, AnyFloatMap, AnyBetaMap]):
"""Create a new Bayes Rule object from: - the prior P(A) - the lik... | stack_v2_sparse_classes_10k_train_005934 | 2,366 | permissive | [
{
"docstring": "Create a new Bayes Rule object from: - the prior P(A) - the likelihood P(B|A) - the evidence P(B) :param prior: Single figure or Beta-distributed probability representing the hypothesis. :param likelihood: Series with values of Dirichlet likelihoods.",
"name": "__init__",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_val_000129 | Implement the Python class `BinaryBayesRule` described below.
Class description:
Class for testing one or more binary hypotheses using Bayes Rule.
Method signatures and docstrings:
- def __init__(self, prior: Union[float, Beta, AnyFloatMap, AnyBetaMap], likelihood: Union[float, Beta, AnyFloatMap, AnyBetaMap]): Create... | Implement the Python class `BinaryBayesRule` described below.
Class description:
Class for testing one or more binary hypotheses using Bayes Rule.
Method signatures and docstrings:
- def __init__(self, prior: Union[float, Beta, AnyFloatMap, AnyBetaMap], likelihood: Union[float, Beta, AnyFloatMap, AnyBetaMap]): Create... | ff3f5434d3da0d46b127b02cf733699e5a43c904 | <|skeleton|>
class BinaryBayesRule:
"""Class for testing one or more binary hypotheses using Bayes Rule."""
def __init__(self, prior: Union[float, Beta, AnyFloatMap, AnyBetaMap], likelihood: Union[float, Beta, AnyFloatMap, AnyBetaMap]):
"""Create a new Bayes Rule object from: - the prior P(A) - the lik... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BinaryBayesRule:
"""Class for testing one or more binary hypotheses using Bayes Rule."""
def __init__(self, prior: Union[float, Beta, AnyFloatMap, AnyBetaMap], likelihood: Union[float, Beta, AnyFloatMap, AnyBetaMap]):
"""Create a new Bayes Rule object from: - the prior P(A) - the likelihood P(B|A... | the_stack_v2_python_sparse | probability/calculations/bayes_rule/binary_bayes_rule.py | vahndi/probability | train | 3 |
8a28e6f1a47ccd01a5138b32bf227f706803b5e4 | [
"decorator_name = ''.join(('@', OpenCL.__name__.lower()))\nself.decorator_name = decorator_name\nself.args = args\nself.kwargs = kwargs\nself.scope = CONTEXT.in_pycompss()\nself.core_element = None\nself.core_element_configured = False\nif self.scope:\n check_arguments(MANDATORY_ARGUMENTS, DEPRECATED_ARGUMENTS, ... | <|body_start_0|>
decorator_name = ''.join(('@', OpenCL.__name__.lower()))
self.decorator_name = decorator_name
self.args = args
self.kwargs = kwargs
self.scope = CONTEXT.in_pycompss()
self.core_element = None
self.core_element_configured = False
if self.sc... | OpenCL decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on opencl task creation. | OpenCL | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpenCL:
"""OpenCL decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on opencl task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorator. self = its... | stack_v2_sparse_classes_10k_train_005935 | 5,902 | permissive | [
{
"docstring": "Store arguments passed to the decorator. self = itself. args = not used. kwargs = dictionary with the given constraints. :param args: Arguments. :param kwargs: Keyword arguments.",
"name": "__init__",
"signature": "def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None"
},... | 3 | stack_v2_sparse_classes_30k_val_000142 | Implement the Python class `OpenCL` described below.
Class description:
OpenCL decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on opencl task creation.
Method signatures and docstrings:
- def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> ... | Implement the Python class `OpenCL` described below.
Class description:
OpenCL decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on opencl task creation.
Method signatures and docstrings:
- def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> ... | 5f7a31436d0e6f5acbeb66fa36ab8aad18dc4092 | <|skeleton|>
class OpenCL:
"""OpenCL decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on opencl task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorator. self = its... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OpenCL:
"""OpenCL decorator class. This decorator also preserves the argspec, but includes the __init__ and __call__ methods, useful on opencl task creation."""
def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
"""Store arguments passed to the decorator. self = itself. args = n... | the_stack_v2_python_sparse | compss/programming_model/bindings/python/src/pycompss/api/opencl.py | bsc-wdc/compss | train | 39 |
b0590c699b913ada5ada8d0325d30990cf8e32d8 | [
"cliente = get_cliente_id(id_cliente)\nif not cliente:\n api.abort(404)\nelse:\n return cliente",
"data = request.json\ncliente = update_cliente(id_cliente, data)\nif not cliente:\n api.abort(404)\nelse:\n return cliente",
"cliente = delete_cliente(id_cliente)\nif not cliente:\n api.abort(404)\ne... | <|body_start_0|>
cliente = get_cliente_id(id_cliente)
if not cliente:
api.abort(404)
else:
return cliente
<|end_body_0|>
<|body_start_1|>
data = request.json
cliente = update_cliente(id_cliente, data)
if not cliente:
api.abort(404)
... | Cliente | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cliente:
def get(self, id_cliente):
"""get a cliente given its identifier"""
<|body_0|>
def put(self, id_cliente):
"""update a cliente given its identifier"""
<|body_1|>
def delete(self, id_cliente):
"""delete a cliente given its identifier"""
... | stack_v2_sparse_classes_10k_train_005936 | 1,821 | no_license | [
{
"docstring": "get a cliente given its identifier",
"name": "get",
"signature": "def get(self, id_cliente)"
},
{
"docstring": "update a cliente given its identifier",
"name": "put",
"signature": "def put(self, id_cliente)"
},
{
"docstring": "delete a cliente given its identifier... | 3 | stack_v2_sparse_classes_30k_train_003774 | Implement the Python class `Cliente` described below.
Class description:
Implement the Cliente class.
Method signatures and docstrings:
- def get(self, id_cliente): get a cliente given its identifier
- def put(self, id_cliente): update a cliente given its identifier
- def delete(self, id_cliente): delete a cliente gi... | Implement the Python class `Cliente` described below.
Class description:
Implement the Cliente class.
Method signatures and docstrings:
- def get(self, id_cliente): get a cliente given its identifier
- def put(self, id_cliente): update a cliente given its identifier
- def delete(self, id_cliente): delete a cliente gi... | e3e6d716102280e73932e5eba65b2ff27eec45e0 | <|skeleton|>
class Cliente:
def get(self, id_cliente):
"""get a cliente given its identifier"""
<|body_0|>
def put(self, id_cliente):
"""update a cliente given its identifier"""
<|body_1|>
def delete(self, id_cliente):
"""delete a cliente given its identifier"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Cliente:
def get(self, id_cliente):
"""get a cliente given its identifier"""
cliente = get_cliente_id(id_cliente)
if not cliente:
api.abort(404)
else:
return cliente
def put(self, id_cliente):
"""update a cliente given its identifier"""
... | the_stack_v2_python_sparse | app/main/controller/cliente_controller.py | Team-3-TCS/api-my-store | train | 1 | |
5118e334b175e78c1f828bc487961e8d46eba801 | [
"LOGGER.debug(f'Copying {self.archive_path} to {self.duplicate_path}')\nshutil.copyfile(self.archive_path, self.duplicate_path)\nLOGGER.debug(f'Copied {self.archive_path} to {self.duplicate_path}')\nwith DataExplorer(self.duplicate_path, allow_edits=True) as data:\n for step in self.preprocessing_steps:\n ... | <|body_start_0|>
LOGGER.debug(f'Copying {self.archive_path} to {self.duplicate_path}')
shutil.copyfile(self.archive_path, self.duplicate_path)
LOGGER.debug(f'Copied {self.archive_path} to {self.duplicate_path}')
with DataExplorer(self.duplicate_path, allow_edits=True) as data:
... | Coordinate multiple steps of processing. | ProcessCoordinator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessCoordinator:
"""Coordinate multiple steps of processing."""
def run_preprocess(self, debug: bool=False) -> None:
"""Run the pre-processing steps."""
<|body_0|>
def run_process(self, debug: bool=False) -> None:
"""Run the processing steps."""
<|body... | stack_v2_sparse_classes_10k_train_005937 | 12,852 | permissive | [
{
"docstring": "Run the pre-processing steps.",
"name": "run_preprocess",
"signature": "def run_preprocess(self, debug: bool=False) -> None"
},
{
"docstring": "Run the processing steps.",
"name": "run_process",
"signature": "def run_process(self, debug: bool=False) -> None"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_005583 | Implement the Python class `ProcessCoordinator` described below.
Class description:
Coordinate multiple steps of processing.
Method signatures and docstrings:
- def run_preprocess(self, debug: bool=False) -> None: Run the pre-processing steps.
- def run_process(self, debug: bool=False) -> None: Run the processing ste... | Implement the Python class `ProcessCoordinator` described below.
Class description:
Coordinate multiple steps of processing.
Method signatures and docstrings:
- def run_preprocess(self, debug: bool=False) -> None: Run the pre-processing steps.
- def run_process(self, debug: bool=False) -> None: Run the processing ste... | 1c2b5b861849ccf76b5ea6aaf0fcbf429aa6bfcf | <|skeleton|>
class ProcessCoordinator:
"""Coordinate multiple steps of processing."""
def run_preprocess(self, debug: bool=False) -> None:
"""Run the pre-processing steps."""
<|body_0|>
def run_process(self, debug: bool=False) -> None:
"""Run the processing steps."""
<|body... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ProcessCoordinator:
"""Coordinate multiple steps of processing."""
def run_preprocess(self, debug: bool=False) -> None:
"""Run the pre-processing steps."""
LOGGER.debug(f'Copying {self.archive_path} to {self.duplicate_path}')
shutil.copyfile(self.archive_path, self.duplicate_path)... | the_stack_v2_python_sparse | shabanipy/utils/data_processing.py | jnt299/shabanipy | train | 1 |
c8ec9d0f6b13b349ed565761a9edee521b00c1b8 | [
"answer = ''\nfor s in strs:\n answer += str(len(s)) + ':' + s\nreturn answer",
"strs = []\nwhile s:\n i = s.find(':')\n length = int(s[:i])\n s = s[i + 1:]\n strs.append(s[:length])\n s = s[length:]\nreturn strs"
] | <|body_start_0|>
answer = ''
for s in strs:
answer += str(len(s)) + ':' + s
return answer
<|end_body_0|>
<|body_start_1|>
strs = []
while s:
i = s.find(':')
length = int(s[:i])
s = s[i + 1:]
strs.append(s[:length])
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k_train_005938 | 2,430 | no_license | [
{
"docstring": "Encodes a list of strings to a single string. :type strs: List[str] :rtype: str",
"name": "encode",
"signature": "def encode(self, strs)"
},
{
"docstring": "Decodes a single string to a list of strings. :type s: str :rtype: List[str]",
"name": "decode",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_003758 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | eb6b11f97a022b66716cb3890cc56c58f62e8aa4 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
answer = ''
for s in strs:
answer += str(len(s)) + ':' + s
return answer
def decode(self, s):
"""Decodes a single string to a list of st... | the_stack_v2_python_sparse | problemSets/top75/271.py | Th3Lourde/l33tcode | train | 0 | |
39c40f6306e92855a045c0841c63d574ffe680c0 | [
"binning = '1,1' if hdu is None else self.get_meta_value(self.get_headarr(hdu), 'binning')\ndetector_dict = dict(binning=binning, det=1, dataext=1, specaxis=0, specflip=False, spatflip=False, platescale=0.22, darkcurr=0.0, saturation=65535.0, nonlinear=0.76, mincounts=-10000000000.0, numamplifiers=1, gain=np.atleas... | <|body_start_0|>
binning = '1,1' if hdu is None else self.get_meta_value(self.get_headarr(hdu), 'binning')
detector_dict = dict(binning=binning, det=1, dataext=1, specaxis=0, specflip=False, spatflip=False, platescale=0.22, darkcurr=0.0, saturation=65535.0, nonlinear=0.76, mincounts=-10000000000.0, numa... | Child to handle WHT/ISISr red specific code | WHTISISRedSpectrograph | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WHTISISRedSpectrograph:
"""Child to handle WHT/ISISr red specific code"""
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy.io.fits.HDUList`_, optional): The open fits file with th... | stack_v2_sparse_classes_10k_train_005939 | 16,230 | permissive | [
{
"docstring": "Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy.io.fits.HDUList`_, optional): The open fits file with the raw image of interest. If not provided, frame-dependent parameters are set to a default. Returns: :class:`~pypeit.images.detector_... | 4 | stack_v2_sparse_classes_30k_train_002782 | Implement the Python class `WHTISISRedSpectrograph` described below.
Class description:
Child to handle WHT/ISISr red specific code
Method signatures and docstrings:
- def get_detector_par(self, det, hdu=None): Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy... | Implement the Python class `WHTISISRedSpectrograph` described below.
Class description:
Child to handle WHT/ISISr red specific code
Method signatures and docstrings:
- def get_detector_par(self, det, hdu=None): Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy... | 0d2e2196afc6904050b1af4d572f5c643bb07e38 | <|skeleton|>
class WHTISISRedSpectrograph:
"""Child to handle WHT/ISISr red specific code"""
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy.io.fits.HDUList`_, optional): The open fits file with th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WHTISISRedSpectrograph:
"""Child to handle WHT/ISISr red specific code"""
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy.io.fits.HDUList`_, optional): The open fits file with the raw image o... | the_stack_v2_python_sparse | pypeit/spectrographs/wht_isis.py | pypeit/PypeIt | train | 136 |
ea22d79ee64901bf2d21eddd8dc8681b74016a02 | [
"if uuidutils.is_uuid_like(segment_uuid):\n LOG.debug('Fetching failover segment by uuid %s', segment_uuid)\n segment = objects.FailoverSegment.get_by_uuid(context, segment_uuid)\nelse:\n LOG.debug('Failed to fetch failover segment by uuid %s', segment_uuid)\n raise exception.FailoverSegmentNotFound(id=... | <|body_start_0|>
if uuidutils.is_uuid_like(segment_uuid):
LOG.debug('Fetching failover segment by uuid %s', segment_uuid)
segment = objects.FailoverSegment.get_by_uuid(context, segment_uuid)
else:
LOG.debug('Failed to fetch failover segment by uuid %s', segment_uuid)
... | FailoverSegmentAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FailoverSegmentAPI:
def get_segment(self, context, segment_uuid):
"""Get a single failover segment with the given segment_uuid."""
<|body_0|>
def get_all(self, context, filters=None, sort_keys=None, sort_dirs=None, limit=None, marker=None):
"""Get all failover segmen... | stack_v2_sparse_classes_10k_train_005940 | 17,673 | permissive | [
{
"docstring": "Get a single failover segment with the given segment_uuid.",
"name": "get_segment",
"signature": "def get_segment(self, context, segment_uuid)"
},
{
"docstring": "Get all failover segments filtered by one of the given parameters. If there is no filter it will retrieve all segment... | 5 | stack_v2_sparse_classes_30k_train_001992 | Implement the Python class `FailoverSegmentAPI` described below.
Class description:
Implement the FailoverSegmentAPI class.
Method signatures and docstrings:
- def get_segment(self, context, segment_uuid): Get a single failover segment with the given segment_uuid.
- def get_all(self, context, filters=None, sort_keys=... | Implement the Python class `FailoverSegmentAPI` described below.
Class description:
Implement the FailoverSegmentAPI class.
Method signatures and docstrings:
- def get_segment(self, context, segment_uuid): Get a single failover segment with the given segment_uuid.
- def get_all(self, context, filters=None, sort_keys=... | bad1f2fe6e5b4cc1f04c8723d9aba8c4cfffb164 | <|skeleton|>
class FailoverSegmentAPI:
def get_segment(self, context, segment_uuid):
"""Get a single failover segment with the given segment_uuid."""
<|body_0|>
def get_all(self, context, filters=None, sort_keys=None, sort_dirs=None, limit=None, marker=None):
"""Get all failover segmen... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FailoverSegmentAPI:
def get_segment(self, context, segment_uuid):
"""Get a single failover segment with the given segment_uuid."""
if uuidutils.is_uuid_like(segment_uuid):
LOG.debug('Fetching failover segment by uuid %s', segment_uuid)
segment = objects.FailoverSegment.... | the_stack_v2_python_sparse | masakari/ha/api.py | openstack/masakari | train | 74 | |
d2cc412e30fb8ab6432776ebfa83e70e630a5bec | [
"super().__init__(cv)\nself._nextrocket = 0\nself._time = 0\nself._cv = cv\nself._pos = pos",
"super().update(dt)\nself._time = self._time + dt\nif self._time > self._nextrocket:\n r = RocketRocket(self._cv, self._pos, 1000, ['red', 'blue', 'yellow', 'chartreuse2'], [500, 500], 3, 3)\n entities.append(r)\n ... | <|body_start_0|>
super().__init__(cv)
self._nextrocket = 0
self._time = 0
self._cv = cv
self._pos = pos
<|end_body_0|>
<|body_start_1|>
super().update(dt)
self._time = self._time + dt
if self._time > self._nextrocket:
r = RocketRocket(self._cv... | RocketRocketLauncher | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RocketRocketLauncher:
def __init__(self, cv, pos):
"""Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow} -- the canvas upon which this wonderful display pos {int} -- the position of the new rocket from the old roc... | stack_v2_sparse_classes_10k_train_005941 | 16,427 | permissive | [
{
"docstring": "Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow} -- the canvas upon which this wonderful display pos {int} -- the position of the new rocket from the old rocket",
"name": "__init__",
"signature": "def __init__(s... | 2 | stack_v2_sparse_classes_30k_train_003961 | Implement the Python class `RocketRocketLauncher` described below.
Class description:
Implement the RocketRocketLauncher class.
Method signatures and docstrings:
- def __init__(self, cv, pos): Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow}... | Implement the Python class `RocketRocketLauncher` described below.
Class description:
Implement the RocketRocketLauncher class.
Method signatures and docstrings:
- def __init__(self, cv, pos): Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow}... | c6b6d80e9d59f5d115ca8b8fc020fcd6cb030af8 | <|skeleton|>
class RocketRocketLauncher:
def __init__(self, cv, pos):
"""Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow} -- the canvas upon which this wonderful display pos {int} -- the position of the new rocket from the old roc... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RocketRocketLauncher:
def __init__(self, cv, pos):
"""Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow} -- the canvas upon which this wonderful display pos {int} -- the position of the new rocket from the old rocket"""
... | the_stack_v2_python_sparse | scripts/sheet9/9.2.py | LennartElbe/PythOnline | train | 0 | |
9c65e59fb9e599af4d73de79e758e4c0032588e0 | [
"petition = self._petition(confirmation)\nmobile = petition.owner.relation_dict.get('mobile')\nif not mobile:\n raise ValueError('Missing mobile number')\nconfirmation.data['mobile'] = mobile\ndc_update(confirmation, expires=iso_now_offset(datetime.timedelta(minutes=5)))\nself.build_token(confirmation, petition)... | <|body_start_0|>
petition = self._petition(confirmation)
mobile = petition.owner.relation_dict.get('mobile')
if not mobile:
raise ValueError('Missing mobile number')
confirmation.data['mobile'] = mobile
dc_update(confirmation, expires=iso_now_offset(datetime.timedelta... | SMS confirmation handler for petitions | PetitionSMSHandler | [
"Apache-2.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PetitionSMSHandler:
"""SMS confirmation handler for petitions"""
def _create(self, confirmation):
"""Send an SMS with the confirmation id"""
<|body_0|>
def _confirm(self, confirmation, petition=None):
"""Confirms the mobile number on the petition If the mobile nu... | stack_v2_sparse_classes_10k_train_005942 | 11,319 | permissive | [
{
"docstring": "Send an SMS with the confirmation id",
"name": "_create",
"signature": "def _create(self, confirmation)"
},
{
"docstring": "Confirms the mobile number on the petition If the mobile number on the owner relation matches the mobile number of this confirmation the mobile_trusted flag... | 2 | stack_v2_sparse_classes_30k_train_004613 | Implement the Python class `PetitionSMSHandler` described below.
Class description:
SMS confirmation handler for petitions
Method signatures and docstrings:
- def _create(self, confirmation): Send an SMS with the confirmation id
- def _confirm(self, confirmation, petition=None): Confirms the mobile number on the peti... | Implement the Python class `PetitionSMSHandler` described below.
Class description:
SMS confirmation handler for petitions
Method signatures and docstrings:
- def _create(self, confirmation): Send an SMS with the confirmation id
- def _confirm(self, confirmation, petition=None): Confirms the mobile number on the peti... | 680aadb1d9dd02e031b1902a4f9ef19440959465 | <|skeleton|>
class PetitionSMSHandler:
"""SMS confirmation handler for petitions"""
def _create(self, confirmation):
"""Send an SMS with the confirmation id"""
<|body_0|>
def _confirm(self, confirmation, petition=None):
"""Confirms the mobile number on the petition If the mobile nu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PetitionSMSHandler:
"""SMS confirmation handler for petitions"""
def _create(self, confirmation):
"""Send an SMS with the confirmation id"""
petition = self._petition(confirmation)
mobile = petition.owner.relation_dict.get('mobile')
if not mobile:
raise ValueEr... | the_stack_v2_python_sparse | src/iris/service/content/petition/confirmation.py | iris-dni/iris-service | train | 3 |
e9ed6f8f1b581c28c38fd86f5cb450d64c318a10 | [
"payload = {'data': data, 'timestamp': int(time.time() * 1000)}\njwt_token = jwt.encode(payload, 'testingplatformhs256', algorithm='HS256')\nreturn bytes.decode(jwt_token)",
"try:\n return jwt.decode(jwt_token, verify=False)\nexcept DecodeError:\n return None"
] | <|body_start_0|>
payload = {'data': data, 'timestamp': int(time.time() * 1000)}
jwt_token = jwt.encode(payload, 'testingplatformhs256', algorithm='HS256')
return bytes.decode(jwt_token)
<|end_body_0|>
<|body_start_1|>
try:
return jwt.decode(jwt_token, verify=False)
e... | Security | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Security:
def encode(data):
"""生成 jwt token"""
<|body_0|>
def decode(jwt_token):
"""解析 jwt token"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
payload = {'data': data, 'timestamp': int(time.time() * 1000)}
jwt_token = jwt.encode(payload, '... | stack_v2_sparse_classes_10k_train_005943 | 1,417 | permissive | [
{
"docstring": "生成 jwt token",
"name": "encode",
"signature": "def encode(data)"
},
{
"docstring": "解析 jwt token",
"name": "decode",
"signature": "def decode(jwt_token)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003089 | Implement the Python class `Security` described below.
Class description:
Implement the Security class.
Method signatures and docstrings:
- def encode(data): 生成 jwt token
- def decode(jwt_token): 解析 jwt token | Implement the Python class `Security` described below.
Class description:
Implement the Security class.
Method signatures and docstrings:
- def encode(data): 生成 jwt token
- def decode(jwt_token): 解析 jwt token
<|skeleton|>
class Security:
def encode(data):
"""生成 jwt token"""
<|body_0|>
def d... | d7008343c25ec7f47acb670ae5c9b9b5f0593d63 | <|skeleton|>
class Security:
def encode(data):
"""生成 jwt token"""
<|body_0|>
def decode(jwt_token):
"""解析 jwt token"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Security:
def encode(data):
"""生成 jwt token"""
payload = {'data': data, 'timestamp': int(time.time() * 1000)}
jwt_token = jwt.encode(payload, 'testingplatformhs256', algorithm='HS256')
return bytes.decode(jwt_token)
def decode(jwt_token):
"""解析 jwt token"""
... | the_stack_v2_python_sparse | backend/util/jwt_token.py | felixu1992/testing-platform | train | 0 | |
15f39eab02c2098df36033b90b43c0ea373a7cd1 | [
"n = len(prices)\ndp = [[0, -prices[0]]] + [[0, 0] for _ in range(n - 1)]\nfor i in range(1, n):\n dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i] - fee)\n dp[i][1] = max(dp[i - 1][1], dp[i - 1][0] - prices[i])\nreturn dp[-1][0]",
"if not prices:\n return 0\nn = len(prices)\ndp0 = 0\ndp1 = -prices[... | <|body_start_0|>
n = len(prices)
dp = [[0, -prices[0]]] + [[0, 0] for _ in range(n - 1)]
for i in range(1, n):
dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i] - fee)
dp[i][1] = max(dp[i - 1][1], dp[i - 1][0] - prices[i])
return dp[-1][0]
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices, fee):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices, fee):
""":type prices: List[int] :type fee: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(prices)
... | stack_v2_sparse_classes_10k_train_005944 | 1,003 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices, fee)"
},
{
"docstring": ":type prices: List[int] :type fee: int :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices, fee)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003627 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices, fee): :type prices: List[int] :rtype: int
- def maxProfit(self, prices, fee): :type prices: List[int] :type fee: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices, fee): :type prices: List[int] :rtype: int
- def maxProfit(self, prices, fee): :type prices: List[int] :type fee: int :rtype: int
<|skeleton|>
class S... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def maxProfit(self, prices, fee):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, prices, fee):
""":type prices: List[int] :type fee: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices, fee):
""":type prices: List[int] :rtype: int"""
n = len(prices)
dp = [[0, -prices[0]]] + [[0, 0] for _ in range(n - 1)]
for i in range(1, n):
dp[i][0] = max(dp[i - 1][0], dp[i - 1][1] + prices[i] - fee)
dp[i][1] = ma... | the_stack_v2_python_sparse | 0714_Best_Time_to_Buy_and_Sell_Stock_with_Transaction_Fee.py | bingli8802/leetcode | train | 0 | |
f5428f29ec127bbb92eccb4e5c65ea1e4deba769 | [
"Attachment = self.env['ir.attachment']\ninputs = Attachment.browse()\nif path.path not in conn:\n return\nnot_consumed = []\nfor _r, fs in batched(conn[path.path], self._BATCH_SIZE):\n attachment_data = []\n for f in fs:\n if not fnmatch.fnmatch(f['name'], path.glob):\n not_consumed.appe... | <|body_start_0|>
Attachment = self.env['ir.attachment']
inputs = Attachment.browse()
if path.path not in conn:
return
not_consumed = []
for _r, fs in batched(conn[path.path], self._BATCH_SIZE):
attachment_data = []
for f in fs:
... | EDI XML-RPC connection An EDI XML-RPC connection is initiated by external code via the Odoo XML-RPC interface. | EdiConnectionXMLRPC | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdiConnectionXMLRPC:
"""EDI XML-RPC connection An EDI XML-RPC connection is initiated by external code via the Odoo XML-RPC interface."""
def receive_inputs(self, conn, path, _transfer):
"""Receive input attachments"""
<|body_0|>
def send_outputs(self, conn, path, transf... | stack_v2_sparse_classes_10k_train_005945 | 2,798 | no_license | [
{
"docstring": "Receive input attachments",
"name": "receive_inputs",
"signature": "def receive_inputs(self, conn, path, _transfer)"
},
{
"docstring": "Send output attachments",
"name": "send_outputs",
"signature": "def send_outputs(self, conn, path, transfer)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005686 | Implement the Python class `EdiConnectionXMLRPC` described below.
Class description:
EDI XML-RPC connection An EDI XML-RPC connection is initiated by external code via the Odoo XML-RPC interface.
Method signatures and docstrings:
- def receive_inputs(self, conn, path, _transfer): Receive input attachments
- def send_... | Implement the Python class `EdiConnectionXMLRPC` described below.
Class description:
EDI XML-RPC connection An EDI XML-RPC connection is initiated by external code via the Odoo XML-RPC interface.
Method signatures and docstrings:
- def receive_inputs(self, conn, path, _transfer): Receive input attachments
- def send_... | d6d55fbf8abecb0b8201384921833868ae849920 | <|skeleton|>
class EdiConnectionXMLRPC:
"""EDI XML-RPC connection An EDI XML-RPC connection is initiated by external code via the Odoo XML-RPC interface."""
def receive_inputs(self, conn, path, _transfer):
"""Receive input attachments"""
<|body_0|>
def send_outputs(self, conn, path, transf... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EdiConnectionXMLRPC:
"""EDI XML-RPC connection An EDI XML-RPC connection is initiated by external code via the Odoo XML-RPC interface."""
def receive_inputs(self, conn, path, _transfer):
"""Receive input attachments"""
Attachment = self.env['ir.attachment']
inputs = Attachment.bro... | the_stack_v2_python_sparse | addons/edi/models/edi_connection_xmlrpc.py | unipartdigital/odoo-edi | train | 9 |
e96945fababa77d483574550ab01855da9d66d98 | [
"permission = AdministerOrganizationPermission(orgname)\nif permission.can():\n organization = model.organization.get_organization(orgname)\n query = model.organization_skus.get_org_subscriptions(organization.id)\n if query:\n subscriptions = list(query.dicts())\n for subscription in subscrip... | <|body_start_0|>
permission = AdministerOrganizationPermission(orgname)
if permission.can():
organization = model.organization.get_organization(orgname)
query = model.organization_skus.get_org_subscriptions(organization.id)
if query:
subscriptions = li... | Resource for managing an organization's RH SKU | OrganizationRhSku | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationRhSku:
"""Resource for managing an organization's RH SKU"""
def get(self, orgname):
"""Get sku assigned to org"""
<|body_0|>
def post(self, orgname):
"""Assigns a sku to an org"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
permissi... | stack_v2_sparse_classes_10k_train_005946 | 33,890 | permissive | [
{
"docstring": "Get sku assigned to org",
"name": "get",
"signature": "def get(self, orgname)"
},
{
"docstring": "Assigns a sku to an org",
"name": "post",
"signature": "def post(self, orgname)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002049 | Implement the Python class `OrganizationRhSku` described below.
Class description:
Resource for managing an organization's RH SKU
Method signatures and docstrings:
- def get(self, orgname): Get sku assigned to org
- def post(self, orgname): Assigns a sku to an org | Implement the Python class `OrganizationRhSku` described below.
Class description:
Resource for managing an organization's RH SKU
Method signatures and docstrings:
- def get(self, orgname): Get sku assigned to org
- def post(self, orgname): Assigns a sku to an org
<|skeleton|>
class OrganizationRhSku:
"""Resourc... | e400a0c22c5f89dd35d571654b13d262b1f6e3b3 | <|skeleton|>
class OrganizationRhSku:
"""Resource for managing an organization's RH SKU"""
def get(self, orgname):
"""Get sku assigned to org"""
<|body_0|>
def post(self, orgname):
"""Assigns a sku to an org"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class OrganizationRhSku:
"""Resource for managing an organization's RH SKU"""
def get(self, orgname):
"""Get sku assigned to org"""
permission = AdministerOrganizationPermission(orgname)
if permission.can():
organization = model.organization.get_organization(orgname)
... | the_stack_v2_python_sparse | endpoints/api/billing.py | quay/quay | train | 2,363 |
34c44257a98ee3941af3424f64baee7f5150444f | [
"if not nums:\n return True\nn = len(nums)\ncount0 = nums.count(nums[0])\nif n % 3 != 0 and count0 == 2 and (self.isHu(nums[2:]) == True):\n return True\nif count0 == 3 and self.isHu(nums[3:]) == True:\n return True\nif nums[0] + 1 in nums and nums[0] + 2 in nums:\n last_nums = nums.copy()\n last_num... | <|body_start_0|>
if not nums:
return True
n = len(nums)
count0 = nums.count(nums[0])
if n % 3 != 0 and count0 == 2 and (self.isHu(nums[2:]) == True):
return True
if count0 == 3 and self.isHu(nums[3:]) == True:
return True
if nums[0] + 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isHu(self, nums):
"""判断是否能胡牌"""
<|body_0|>
def add_card_main(self, array):
"""建立每个元素与数目的字典映射"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return True
n = len(nums)
count0 = nums.count(nums[0]... | stack_v2_sparse_classes_10k_train_005947 | 2,884 | no_license | [
{
"docstring": "判断是否能胡牌",
"name": "isHu",
"signature": "def isHu(self, nums)"
},
{
"docstring": "建立每个元素与数目的字典映射",
"name": "add_card_main",
"signature": "def add_card_main(self, array)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000367 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isHu(self, nums): 判断是否能胡牌
- def add_card_main(self, array): 建立每个元素与数目的字典映射 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isHu(self, nums): 判断是否能胡牌
- def add_card_main(self, array): 建立每个元素与数目的字典映射
<|skeleton|>
class Solution:
def isHu(self, nums):
"""判断是否能胡牌"""
<|body_0|>
... | 4e4f739402b95691f6c91411da26d7d3bfe042b6 | <|skeleton|>
class Solution:
def isHu(self, nums):
"""判断是否能胡牌"""
<|body_0|>
def add_card_main(self, array):
"""建立每个元素与数目的字典映射"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isHu(self, nums):
"""判断是否能胡牌"""
if not nums:
return True
n = len(nums)
count0 = nums.count(nums[0])
if n % 3 != 0 and count0 == 2 and (self.isHu(nums[2:]) == True):
return True
if count0 == 3 and self.isHu(nums[3:]) == True:... | the_stack_v2_python_sparse | Interview/practice/tt_03.雀魂启动.py | hugechuanqi/Algorithms-and-Data-Structures | train | 3 | |
4becf18393dc157d266e77c022864c96567ad973 | [
"super(CenterLineAtYAxis, self).__init__(dim)\nself.output_size = output_size\nself.output_spacing = output_spacing",
"if self.dim == 2:\n return self.get_2d(**kwargs)\nelif self.dim == 3:\n return self.get_3d(**kwargs)",
"input_image = kwargs.get('image')\nline = kwargs.get('line')\noutput_size = kwargs.... | <|body_start_0|>
super(CenterLineAtYAxis, self).__init__(dim)
self.output_size = output_size
self.output_spacing = output_spacing
<|end_body_0|>
<|body_start_1|>
if self.dim == 2:
return self.get_2d(**kwargs)
elif self.dim == 3:
return self.get_3d(**kwarg... | A composite transformation that centers a given line at the y axis. Used in the bone generators. | CenterLineAtYAxis | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CenterLineAtYAxis:
"""A composite transformation that centers a given line at the y axis. Used in the bone generators."""
def __init__(self, dim, output_size, output_spacing):
"""Initializer. :param dim: The dimension. :param output_size: The output image size in pixels. :param outpu... | stack_v2_sparse_classes_10k_train_005948 | 7,141 | no_license | [
{
"docstring": "Initializer. :param dim: The dimension. :param output_size: The output image size in pixels. :param output_spacing: The output image spacing in mm.",
"name": "__init__",
"signature": "def __init__(self, dim, output_size, output_spacing)"
},
{
"docstring": "Returns the sitk transf... | 4 | stack_v2_sparse_classes_30k_train_004406 | Implement the Python class `CenterLineAtYAxis` described below.
Class description:
A composite transformation that centers a given line at the y axis. Used in the bone generators.
Method signatures and docstrings:
- def __init__(self, dim, output_size, output_spacing): Initializer. :param dim: The dimension. :param o... | Implement the Python class `CenterLineAtYAxis` described below.
Class description:
A composite transformation that centers a given line at the y axis. Used in the bone generators.
Method signatures and docstrings:
- def __init__(self, dim, output_size, output_spacing): Initializer. :param dim: The dimension. :param o... | ef6cee91264ba1fe6b40d9823a07647b95bcc2c4 | <|skeleton|>
class CenterLineAtYAxis:
"""A composite transformation that centers a given line at the y axis. Used in the bone generators."""
def __init__(self, dim, output_size, output_spacing):
"""Initializer. :param dim: The dimension. :param output_size: The output image size in pixels. :param outpu... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CenterLineAtYAxis:
"""A composite transformation that centers a given line at the y axis. Used in the bone generators."""
def __init__(self, dim, output_size, output_spacing):
"""Initializer. :param dim: The dimension. :param output_size: The output image size in pixels. :param output_spacing: Th... | the_stack_v2_python_sparse | transformations/spatial/center_line_at_y_axis.py | XiaoweiXu/MedicalDataAugmentationTool | train | 1 |
c5a7613b0bb497ee9afaf672fd1ded36f1afebfb | [
"if isinstance(value, bytes):\n value = value.decode('utf-8')\nreturn value",
"if isinstance(value, bytes):\n value = value.decode('utf-8')\nresult = repr(value)\nif six.PY2 and result.startswith('u'):\n result = result[1:].decode('unicode-escape')\nreturn result"
] | <|body_start_0|>
if isinstance(value, bytes):
value = value.decode('utf-8')
return value
<|end_body_0|>
<|body_start_1|>
if isinstance(value, bytes):
value = value.decode('utf-8')
result = repr(value)
if six.PY2 and result.startswith('u'):
res... | Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2 | StringSerialization | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringSerialization:
"""Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2"""
def serialize_to_signature(cls, value):
"""Serialize a string to JSON-compatible string. Args: value (byt... | stack_v2_sparse_classes_10k_train_005949 | 30,104 | permissive | [
{
"docstring": "Serialize a string to JSON-compatible string. Args: value (bytes or unicode): The string to serialize. If a byte string, it's expected to contain UTF-8 data. Returns: unicode: The resulting string.",
"name": "serialize_to_signature",
"signature": "def serialize_to_signature(cls, value)"
... | 2 | stack_v2_sparse_classes_30k_train_006507 | Implement the Python class `StringSerialization` described below.
Class description:
Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2
Method signatures and docstrings:
- def serialize_to_signature(cls, value): Seria... | Implement the Python class `StringSerialization` described below.
Class description:
Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2
Method signatures and docstrings:
- def serialize_to_signature(cls, value): Seria... | 756eedeacc41f77111a557fc13dee559cb94f433 | <|skeleton|>
class StringSerialization:
"""Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2"""
def serialize_to_signature(cls, value):
"""Serialize a string to JSON-compatible string. Args: value (byt... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StringSerialization:
"""Base class for serialization for strings. This will encode to a string, and ensure the results are consistent across Python 2 and 3. Version Added: 2.2"""
def serialize_to_signature(cls, value):
"""Serialize a string to JSON-compatible string. Args: value (bytes or unicode... | the_stack_v2_python_sparse | django_evolution/serialization.py | beanbaginc/django-evolution | train | 22 |
0f19f99ae1f59521485aa0c56c44f5cbb97d71f1 | [
"start = 0\nend = len(nums) - 1\nwhile start <= end:\n mid = (start + end) / 2\n if nums[mid - 1] != nums[mid] != nums[mid + 1]:\n return nums[mid]\n elif nums[mid - 1] == nums[mid]:\n end = mid - 1\n else:\n start = mid + 1",
"if len(nums) < 3:\n return nums[0]\nstart = 0\nend... | <|body_start_0|>
start = 0
end = len(nums) - 1
while start <= end:
mid = (start + end) / 2
if nums[mid - 1] != nums[mid] != nums[mid + 1]:
return nums[mid]
elif nums[mid - 1] == nums[mid]:
end = mid - 1
else:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _singleNonDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def singleNonDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
start = 0
end = len(nu... | stack_v2_sparse_classes_10k_train_005950 | 2,085 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "_singleNonDuplicate",
"signature": "def _singleNonDuplicate(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "singleNonDuplicate",
"signature": "def singleNonDuplicate(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _singleNonDuplicate(self, nums): :type nums: List[int] :rtype: int
- def singleNonDuplicate(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _singleNonDuplicate(self, nums): :type nums: List[int] :rtype: int
- def singleNonDuplicate(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _singleNonDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def singleNonDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def _singleNonDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
start = 0
end = len(nums) - 1
while start <= end:
mid = (start + end) / 2
if nums[mid - 1] != nums[mid] != nums[mid + 1]:
return nums[mid]
... | the_stack_v2_python_sparse | 540.single-element-in-a-sorted-array.py | windard/leeeeee | train | 0 | |
d40cea7d00ccf04245c49739e51ff52e3aad4cf3 | [
"super(TempBase, self).__init__(*args, **kwargs)\nforbidden = []\nfor i in self.FORBIDDEN_COLUMN_LIST:\n forbidden.append(self.__tablename__ + '.' + i)\nself.FORBIDDEN_COLUMN_LIST = forbidden\nshow = []\nfor k in self.SHOW_COLUMN_LIST:\n show.append(self.__tablename__ + '.' + k)\nself.SHOW_COLUMN_LIST = show"... | <|body_start_0|>
super(TempBase, self).__init__(*args, **kwargs)
forbidden = []
for i in self.FORBIDDEN_COLUMN_LIST:
forbidden.append(self.__tablename__ + '.' + i)
self.FORBIDDEN_COLUMN_LIST = forbidden
show = []
for k in self.SHOW_COLUMN_LIST:
sho... | 基类 | TempBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempBase:
"""基类"""
def __init__(self, *args, **kwargs):
"""初始化"""
<|body_0|>
def to_dict(self):
"""序列化"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(TempBase, self).__init__(*args, **kwargs)
forbidden = []
for i in self.F... | stack_v2_sparse_classes_10k_train_005951 | 22,283 | no_license | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "序列化",
"name": "to_dict",
"signature": "def to_dict(self)"
}
] | 2 | null | Implement the Python class `TempBase` described below.
Class description:
基类
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): 初始化
- def to_dict(self): 序列化 | Implement the Python class `TempBase` described below.
Class description:
基类
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): 初始化
- def to_dict(self): 序列化
<|skeleton|>
class TempBase:
"""基类"""
def __init__(self, *args, **kwargs):
"""初始化"""
<|body_0|>
def to_dict(... | c50def8cde58fd4663032b860eb058302cbac6da | <|skeleton|>
class TempBase:
"""基类"""
def __init__(self, *args, **kwargs):
"""初始化"""
<|body_0|>
def to_dict(self):
"""序列化"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TempBase:
"""基类"""
def __init__(self, *args, **kwargs):
"""初始化"""
super(TempBase, self).__init__(*args, **kwargs)
forbidden = []
for i in self.FORBIDDEN_COLUMN_LIST:
forbidden.append(self.__tablename__ + '.' + i)
self.FORBIDDEN_COLUMN_LIST = forbidden
... | the_stack_v2_python_sparse | src/workers/preprocess/models/models.py | fan1018wen/Alpha | train | 0 |
274d4086461a02d0f7413b391359524619e32c4c | [
"if not root:\n return []\nstack = []\nres = []\ncur = root\nstack.append(cur)\nwhile stack:\n cur = stack.pop()\n res.append(cur.val)\n if cur.right:\n stack.append(cur.right)\n if cur.left:\n stack.append(cur.left)\nreturn res",
"if root is None:\n return []\nres = []\n\ndef trav... | <|body_start_0|>
if not root:
return []
stack = []
res = []
cur = root
stack.append(cur)
while stack:
cur = stack.pop()
res.append(cur.val)
if cur.right:
stack.append(cur.right)
if cur.left:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存"""
<|body_0|>
def preorderTraversal1(self, root):
""":type root: TreeNode :rtype: List[int] 算法：递归"""
... | stack_v2_sparse_classes_10k_train_005952 | 1,705 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[int] 算法：递归",
"name": "preorderTra... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存
- def preorderTraversal1(self, ro... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存
- def preorderTraversal1(self, ro... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存"""
<|body_0|>
def preorderTraversal1(self, root):
""":type root: TreeNode :rtype: List[int] 算法：递归"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存"""
if not root:
return []
stack = []
res = []
cur = root
stack.append(cur)
while sta... | the_stack_v2_python_sparse | out/production/leetcode/144.二叉树的前序遍历.py | yangyuxiang1996/leetcode | train | 0 | |
76f68093fbb8927100b7ad2af0d984fc4c166a9e | [
"if self.codeable_concept:\n return 'Performer {0.reference_txt} {0.codeable_concept}'.format(self)\nreturn 'Performer {0.reference_txt}'.format(self)",
"if self.codeable_concept:\n return {'actor': self.reference_txt, 'role': self.codeable_concept.as_fhir()}\nreturn self.reference_txt",
"instance = cls()... | <|body_start_0|>
if self.codeable_concept:
return 'Performer {0.reference_txt} {0.codeable_concept}'.format(self)
return 'Performer {0.reference_txt}'.format(self)
<|end_body_0|>
<|body_start_1|>
if self.codeable_concept:
return {'actor': self.reference_txt, 'role': self... | ORM for FHIR Performer - performers table | Performer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Performer:
"""ORM for FHIR Performer - performers table"""
def __str__(self):
"""Print friendly format for logging, etc."""
<|body_0|>
def as_fhir(self):
"""Return self in JSON FHIR formatted string FHIR is not currently consistant in performer inclusion. For exa... | stack_v2_sparse_classes_10k_train_005953 | 4,146 | permissive | [
{
"docstring": "Print friendly format for logging, etc.",
"name": "__str__",
"signature": "def __str__(self)"
},
{
"docstring": "Return self in JSON FHIR formatted string FHIR is not currently consistant in performer inclusion. For example, Observation.performer is simply a list of Reference res... | 4 | stack_v2_sparse_classes_30k_train_002410 | Implement the Python class `Performer` described below.
Class description:
ORM for FHIR Performer - performers table
Method signatures and docstrings:
- def __str__(self): Print friendly format for logging, etc.
- def as_fhir(self): Return self in JSON FHIR formatted string FHIR is not currently consistant in perform... | Implement the Python class `Performer` described below.
Class description:
ORM for FHIR Performer - performers table
Method signatures and docstrings:
- def __str__(self): Print friendly format for logging, etc.
- def as_fhir(self): Return self in JSON FHIR formatted string FHIR is not currently consistant in perform... | 622e90f54692c6fc9c84468f489ab6f297af0feb | <|skeleton|>
class Performer:
"""ORM for FHIR Performer - performers table"""
def __str__(self):
"""Print friendly format for logging, etc."""
<|body_0|>
def as_fhir(self):
"""Return self in JSON FHIR formatted string FHIR is not currently consistant in performer inclusion. For exa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Performer:
"""ORM for FHIR Performer - performers table"""
def __str__(self):
"""Print friendly format for logging, etc."""
if self.codeable_concept:
return 'Performer {0.reference_txt} {0.codeable_concept}'.format(self)
return 'Performer {0.reference_txt}'.format(self... | the_stack_v2_python_sparse | portal/models/performer.py | pep8speaks/true_nth_usa_portal | train | 1 |
0163054dd5e092f954f7f7bbfde502a0d55d41df | [
"def recur(i, j):\n if j == 0 or i == j:\n return 1\n else:\n return recur(i - 1, j - 1) + recur(i - 1, j)\nres = []\nfor i in range(numRows):\n tmp = []\n for j in range(i + 1):\n if j == 0 or i == j:\n tmp.append(1)\n else:\n tmp.append(recur(i - 1, j ... | <|body_start_0|>
def recur(i, j):
if j == 0 or i == j:
return 1
else:
return recur(i - 1, j - 1) + recur(i - 1, j)
res = []
for i in range(numRows):
tmp = []
for j in range(i + 1):
if j == 0 or i == j... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generate_1(self, numRows: int) -> List[List[int]]:
"""递归 时间复杂度：O(numRows^3) 空间复杂度：O(numRows^2) :param numRows: :return:"""
<|body_0|>
def generate_2(self, numRows: int) -> List[List[int]]:
"""动态规划 时间复杂度：O(numRows^2) 空间复杂度：O(numRows^2) :param numRows: :r... | stack_v2_sparse_classes_10k_train_005954 | 1,669 | no_license | [
{
"docstring": "递归 时间复杂度：O(numRows^3) 空间复杂度：O(numRows^2) :param numRows: :return:",
"name": "generate_1",
"signature": "def generate_1(self, numRows: int) -> List[List[int]]"
},
{
"docstring": "动态规划 时间复杂度：O(numRows^2) 空间复杂度：O(numRows^2) :param numRows: :return:",
"name": "generate_2",
"s... | 2 | stack_v2_sparse_classes_30k_train_004121 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate_1(self, numRows: int) -> List[List[int]]: 递归 时间复杂度：O(numRows^3) 空间复杂度：O(numRows^2) :param numRows: :return:
- def generate_2(self, numRows: int) -> List[List[int]]: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate_1(self, numRows: int) -> List[List[int]]: 递归 时间复杂度：O(numRows^3) 空间复杂度：O(numRows^2) :param numRows: :return:
- def generate_2(self, numRows: int) -> List[List[int]]: ... | 62419b49000e79962bcdc99cd98afd2fb82ea345 | <|skeleton|>
class Solution:
def generate_1(self, numRows: int) -> List[List[int]]:
"""递归 时间复杂度：O(numRows^3) 空间复杂度：O(numRows^2) :param numRows: :return:"""
<|body_0|>
def generate_2(self, numRows: int) -> List[List[int]]:
"""动态规划 时间复杂度：O(numRows^2) 空间复杂度：O(numRows^2) :param numRows: :r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def generate_1(self, numRows: int) -> List[List[int]]:
"""递归 时间复杂度：O(numRows^3) 空间复杂度：O(numRows^2) :param numRows: :return:"""
def recur(i, j):
if j == 0 or i == j:
return 1
else:
return recur(i - 1, j - 1) + recur(i - 1, j)
... | the_stack_v2_python_sparse | 软件开发岗刷题（华为笔试准备）/递归/generate.py | MaoningGuan/LeetCode | train | 3 | |
76cd6aabee6122feb7811b641799bc8b292e3529 | [
"nums.sort()\nresults = []\nfor i in range(len(nums) - 3):\n if i == 0 or nums[i] != nums[i - 1]:\n threeResult = self.threeSum(nums[i + 1:], target - nums[i])\n for item in threeResult:\n results.append([nums[i]] + item)\nreturn results",
"res = []\nnums.sort()\nfor i in range(len(num... | <|body_start_0|>
nums.sort()
results = []
for i in range(len(nums) - 3):
if i == 0 or nums[i] != nums[i - 1]:
threeResult = self.threeSum(nums[i + 1:], target - nums[i])
for item in threeResult:
results.append([nums[i]] + item)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]] https://leetcode.com/problems/4sum/discuss/8545/Python-140ms-beats-100-and-works-for-N-sum-(Ngreater2)"""
<|body_0|>
def threeSum(self, nums, target):
"""第15... | stack_v2_sparse_classes_10k_train_005955 | 3,097 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: List[List[int]] https://leetcode.com/problems/4sum/discuss/8545/Python-140ms-beats-100-and-works-for-N-sum-(Ngreater2)",
"name": "fourSum",
"signature": "def fourSum(self, nums, target)"
},
{
"docstring": "第15题 :type nums: List[int]... | 2 | stack_v2_sparse_classes_30k_train_000592 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]] https://leetcode.com/problems/4sum/discuss/8545/Python-140ms-beats-100-and-works-... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fourSum(self, nums, target): :type nums: List[int] :type target: int :rtype: List[List[int]] https://leetcode.com/problems/4sum/discuss/8545/Python-140ms-beats-100-and-works-... | 0b3bc77cbfe0e45e62c3c8f244e9e3d2421e6121 | <|skeleton|>
class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]] https://leetcode.com/problems/4sum/discuss/8545/Python-140ms-beats-100-and-works-for-N-sum-(Ngreater2)"""
<|body_0|>
def threeSum(self, nums, target):
"""第15... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def fourSum(self, nums, target):
""":type nums: List[int] :type target: int :rtype: List[List[int]] https://leetcode.com/problems/4sum/discuss/8545/Python-140ms-beats-100-and-works-for-N-sum-(Ngreater2)"""
nums.sort()
results = []
for i in range(len(nums) - 3):
... | the_stack_v2_python_sparse | 18.py | lailianqi/LeetCodeByPython | train | 0 | |
189ee5e58d0b3a6d7b98ef016260f6f1f35350f8 | [
"random.seed(1)\nself.grid_lat = np.random.rand(1000) * 5 * random.choice([-1, 1]) + -59.1868\nself.grid_long = np.random.rand(1000) * 5 * random.choice([-1, 1]) + 57.1794\nself.grid_dates = np.random.rand(1000) * 5 * random.choice([-1, 1]) + 5.1083 * 10 ** 3\nself.grid_z_values = np.random.rand(1000) * 5 * random.... | <|body_start_0|>
random.seed(1)
self.grid_lat = np.random.rand(1000) * 5 * random.choice([-1, 1]) + -59.1868
self.grid_long = np.random.rand(1000) * 5 * random.choice([-1, 1]) + 57.1794
self.grid_dates = np.random.rand(1000) * 5 * random.choice([-1, 1]) + 5.1083 * 10 ** 3
self.gr... | Test cases for find_besthist function | FindBestHistTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FindBestHistTestCase:
"""Test cases for find_besthist function"""
def setUp(self):
"""Set up for the tests. Creates 1000 historical random data points that are the float data points +/- 5. This could fail randomly if, by pure chance, none of the generated data is in the ellipse, so u... | stack_v2_sparse_classes_10k_train_005956 | 5,447 | no_license | [
{
"docstring": "Set up for the tests. Creates 1000 historical random data points that are the float data points +/- 5. This could fail randomly if, by pure chance, none of the generated data is in the ellipse, so use pseudo random numbers just in case :return: nothing",
"name": "setUp",
"signature": "de... | 5 | stack_v2_sparse_classes_30k_train_004576 | Implement the Python class `FindBestHistTestCase` described below.
Class description:
Test cases for find_besthist function
Method signatures and docstrings:
- def setUp(self): Set up for the tests. Creates 1000 historical random data points that are the float data points +/- 5. This could fail randomly if, by pure c... | Implement the Python class `FindBestHistTestCase` described below.
Class description:
Test cases for find_besthist function
Method signatures and docstrings:
- def setUp(self): Set up for the tests. Creates 1000 historical random data points that are the float data points +/- 5. This could fail randomly if, by pure c... | 3944e9783d58422d2d10bbc95f9706e168550034 | <|skeleton|>
class FindBestHistTestCase:
"""Test cases for find_besthist function"""
def setUp(self):
"""Set up for the tests. Creates 1000 historical random data points that are the float data points +/- 5. This could fail randomly if, by pure chance, none of the generated data is in the ellipse, so u... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FindBestHistTestCase:
"""Test cases for find_besthist function"""
def setUp(self):
"""Set up for the tests. Creates 1000 historical random data points that are the float data points +/- 5. This could fail randomly if, by pure chance, none of the generated data is in the ellipse, so use pseudo ran... | the_stack_v2_python_sparse | ow_calibration/find_besthist/find_besthist_test.py | gmaze/argodmqc_owc | train | 0 |
0101cb4e170a8d168a24134fee231c0d44274d44 | [
"session = db_apis.get_session()\nwith session.begin():\n db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])\namphorae = {amp.id: amp for amp in db_lb.amphorae}\nupdated_ports = {}\nhandle_delta = HandleNetworkDelta()\nfor amp_id, delta in deltas.items():\n ret = handle_de... | <|body_start_0|>
session = db_apis.get_session()
with session.begin():
db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])
amphorae = {amp.id: amp for amp in db_lb.amphorae}
updated_ports = {}
handle_delta = HandleNetworkDelta()
... | Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta | HandleNetworkDeltas | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HandleNetworkDeltas:
"""Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta"""
def execute(self, deltas, loadbalancer):
"""Handle network plugging based off deltas."""
<|body_0|>
def revert(self, result, deltas, *args, **kw... | stack_v2_sparse_classes_10k_train_005957 | 44,034 | permissive | [
{
"docstring": "Handle network plugging based off deltas.",
"name": "execute",
"signature": "def execute(self, deltas, loadbalancer)"
},
{
"docstring": "Handle a network plug or unplug failures.",
"name": "revert",
"signature": "def revert(self, result, deltas, *args, **kwargs)"
}
] | 2 | null | Implement the Python class `HandleNetworkDeltas` described below.
Class description:
Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta
Method signatures and docstrings:
- def execute(self, deltas, loadbalancer): Handle network plugging based off deltas.
- def revert(s... | Implement the Python class `HandleNetworkDeltas` described below.
Class description:
Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta
Method signatures and docstrings:
- def execute(self, deltas, loadbalancer): Handle network plugging based off deltas.
- def revert(s... | 0426285a41464a5015494584f109eed35a0d44db | <|skeleton|>
class HandleNetworkDeltas:
"""Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta"""
def execute(self, deltas, loadbalancer):
"""Handle network plugging based off deltas."""
<|body_0|>
def revert(self, result, deltas, *args, **kw... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class HandleNetworkDeltas:
"""Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta"""
def execute(self, deltas, loadbalancer):
"""Handle network plugging based off deltas."""
session = db_apis.get_session()
with session.begin():
... | the_stack_v2_python_sparse | octavia/controller/worker/v2/tasks/network_tasks.py | openstack/octavia | train | 147 |
c97bdc9758500115d00dd12e74d8b9f2a1772596 | [
"self.groups: set[LcnAddr] = set()\nself.groups_known = asyncio.Event()\nsuper().__init__(addr_conn, num_tries, timeout_msec)",
"if isinstance(inp, inputs.ModStatusGroups):\n if not inp.dynamic:\n self.groups.update(inp.groups)\n self.groups_known.set()\n await self.cancel()",
"if not fa... | <|body_start_0|>
self.groups: set[LcnAddr] = set()
self.groups_known = asyncio.Event()
super().__init__(addr_conn, num_tries, timeout_msec)
<|end_body_0|>
<|body_start_1|>
if isinstance(inp, inputs.ModStatusGroups):
if not inp.dynamic:
self.groups.update(inp.... | Request handler to request static group membership of a module. | GroupMembershipStaticRequestHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupMembershipStaticRequestHandler:
"""Request handler to request static group membership of a module."""
def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500):
"""Initialize class instance."""
<|body_0|>
async def async_process_input... | stack_v2_sparse_classes_10k_train_005958 | 24,302 | permissive | [
{
"docstring": "Initialize class instance.",
"name": "__init__",
"signature": "def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500)"
},
{
"docstring": "Process incoming input object. Method to handle incoming commands for this specific request handler.",
... | 4 | stack_v2_sparse_classes_30k_train_004147 | Implement the Python class `GroupMembershipStaticRequestHandler` described below.
Class description:
Request handler to request static group membership of a module.
Method signatures and docstrings:
- def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500): Initialize class instance.... | Implement the Python class `GroupMembershipStaticRequestHandler` described below.
Class description:
Request handler to request static group membership of a module.
Method signatures and docstrings:
- def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500): Initialize class instance.... | 00b45d5dcec8fccd4b13d218ac56194f44959e68 | <|skeleton|>
class GroupMembershipStaticRequestHandler:
"""Request handler to request static group membership of a module."""
def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500):
"""Initialize class instance."""
<|body_0|>
async def async_process_input... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GroupMembershipStaticRequestHandler:
"""Request handler to request static group membership of a module."""
def __init__(self, addr_conn: ModuleConnection, num_tries: int=3, timeout_msec: int=1500):
"""Initialize class instance."""
self.groups: set[LcnAddr] = set()
self.groups_know... | the_stack_v2_python_sparse | pypck/request_handlers.py | alengwenus/pypck | train | 6 |
f42d522c7b847f447ad3707a8fec16c9ff32ea99 | [
"sm = get_storage_manager()\nwith sm.transaction():\n role = sm.get(models.Role, None, filters={'name': role_name})\n already_exists = models.Permission.query.filter_by(role=role, name=permission_name).first()\n if already_exists:\n raise manager_exceptions.ConflictError(f'{role_name} already has pe... | <|body_start_0|>
sm = get_storage_manager()
with sm.transaction():
role = sm.get(models.Role, None, filters={'name': role_name})
already_exists = models.Permission.query.filter_by(role=role, name=permission_name).first()
if already_exists:
raise manage... | PermissionsRoleId | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PermissionsRoleId:
def put(self, role_name, permission_name):
"""Allow role_name the permission permission_name"""
<|body_0|>
def delete(self, role_name, permission_name):
"""Disallow role_name the permission permission_name"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_10k_train_005959 | 3,208 | permissive | [
{
"docstring": "Allow role_name the permission permission_name",
"name": "put",
"signature": "def put(self, role_name, permission_name)"
},
{
"docstring": "Disallow role_name the permission permission_name",
"name": "delete",
"signature": "def delete(self, role_name, permission_name)"
... | 2 | null | Implement the Python class `PermissionsRoleId` described below.
Class description:
Implement the PermissionsRoleId class.
Method signatures and docstrings:
- def put(self, role_name, permission_name): Allow role_name the permission permission_name
- def delete(self, role_name, permission_name): Disallow role_name the... | Implement the Python class `PermissionsRoleId` described below.
Class description:
Implement the PermissionsRoleId class.
Method signatures and docstrings:
- def put(self, role_name, permission_name): Allow role_name the permission permission_name
- def delete(self, role_name, permission_name): Disallow role_name the... | c0de6442e1d7653fad824d75e571802a74eee605 | <|skeleton|>
class PermissionsRoleId:
def put(self, role_name, permission_name):
"""Allow role_name the permission permission_name"""
<|body_0|>
def delete(self, role_name, permission_name):
"""Disallow role_name the permission permission_name"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PermissionsRoleId:
def put(self, role_name, permission_name):
"""Allow role_name the permission permission_name"""
sm = get_storage_manager()
with sm.transaction():
role = sm.get(models.Role, None, filters={'name': role_name})
already_exists = models.Permission.... | the_stack_v2_python_sparse | rest-service/manager_rest/rest/resources_v3_1/permissions.py | cloudify-cosmo/cloudify-manager | train | 146 | |
a00d5ddef611e1319e745dbe5ae4f910280cd417 | [
"super(ClassificationHead, self).__init__()\nself.dense1 = PointNetDenseLayer(512, momentum)\nself.dense2 = PointNetDenseLayer(256, momentum)\nself.dropout = tf.keras.layers.Dropout(dropout_rate)\nself.dense3 = tf.keras.layers.Dense(num_classes, activation='linear')",
"x = self.dense1(inputs, training)\nx = self.... | <|body_start_0|>
super(ClassificationHead, self).__init__()
self.dense1 = PointNetDenseLayer(512, momentum)
self.dense2 = PointNetDenseLayer(256, momentum)
self.dropout = tf.keras.layers.Dropout(dropout_rate)
self.dense3 = tf.keras.layers.Dense(num_classes, activation='linear')
<... | The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes. | ClassificationHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassificationHead:
"""The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes."""
def __init__(self, num_classes: int=40, momen... | stack_v2_sparse_classes_10k_train_005960 | 9,332 | permissive | [
{
"docstring": "Constructor. Args: num_classes: the number of classes to classify. momentum: the momentum used for the batch normalization layer. dropout_rate: the dropout rate for fully connected layer",
"name": "__init__",
"signature": "def __init__(self, num_classes: int=40, momentum: float=0.5, drop... | 2 | stack_v2_sparse_classes_30k_train_001433 | Implement the Python class `ClassificationHead` described below.
Class description:
The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes.
Method signat... | Implement the Python class `ClassificationHead` described below.
Class description:
The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes.
Method signat... | 1b0203eb538f2b6a1013ec7736d0d548416f059a | <|skeleton|>
class ClassificationHead:
"""The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes."""
def __init__(self, num_classes: int=40, momen... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ClassificationHead:
"""The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes."""
def __init__(self, num_classes: int=40, momentum: float=0.... | the_stack_v2_python_sparse | tensorflow_graphics/nn/layer/pointnet.py | tensorflow/graphics | train | 2,920 |
f88335f1626945df598ec5e619c88df3c14f83ef | [
"app = self.request.app\napp.logger.debug(f'Chat command {cmd}')\nif cmd == '/clear':\n await app.objects.execute(Message.delete().where(Message.room == self.room))\n app.logger.debug(f'Removed {count} messages')\n for peer in app.wslist[self.room.id].values():\n peer.send_json({'cmd': 'empty'})\nel... | <|body_start_0|>
app = self.request.app
app.logger.debug(f'Chat command {cmd}')
if cmd == '/clear':
await app.objects.execute(Message.delete().where(Message.room == self.room))
app.logger.debug(f'Removed {count} messages')
for peer in app.wslist[self.room.id].... | Вспомогательный класс для всяких нужных методов для работы с вебсокетами, что бы не засорять хелпер | WebSocketMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebSocketMixin:
"""Вспомогательный класс для всяких нужных методов для работы с вебсокетами, что бы не засорять хелпер"""
async def command_line(self, cmd: str) -> Dict[str, str]:
"""Некоторые управляющие команды"""
<|body_0|>
async def broadcast(self, message: Message) ... | stack_v2_sparse_classes_10k_train_005961 | 4,826 | no_license | [
{
"docstring": "Некоторые управляющие команды",
"name": "command_line",
"signature": "async def command_line(self, cmd: str) -> Dict[str, str]"
},
{
"docstring": "Рассылка сообщениий по всей комнате",
"name": "broadcast",
"signature": "async def broadcast(self, message: Message) -> None"... | 2 | stack_v2_sparse_classes_30k_train_002138 | Implement the Python class `WebSocketMixin` described below.
Class description:
Вспомогательный класс для всяких нужных методов для работы с вебсокетами, что бы не засорять хелпер
Method signatures and docstrings:
- async def command_line(self, cmd: str) -> Dict[str, str]: Некоторые управляющие команды
- async def br... | Implement the Python class `WebSocketMixin` described below.
Class description:
Вспомогательный класс для всяких нужных методов для работы с вебсокетами, что бы не засорять хелпер
Method signatures and docstrings:
- async def command_line(self, cmd: str) -> Dict[str, str]: Некоторые управляющие команды
- async def br... | b7760f05e1d00f28a06b07bcd120c4af0237ce94 | <|skeleton|>
class WebSocketMixin:
"""Вспомогательный класс для всяких нужных методов для работы с вебсокетами, что бы не засорять хелпер"""
async def command_line(self, cmd: str) -> Dict[str, str]:
"""Некоторые управляющие команды"""
<|body_0|>
async def broadcast(self, message: Message) ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WebSocketMixin:
"""Вспомогательный класс для всяких нужных методов для работы с вебсокетами, что бы не засорять хелпер"""
async def command_line(self, cmd: str) -> Dict[str, str]:
"""Некоторые управляющие команды"""
app = self.request.app
app.logger.debug(f'Chat command {cmd}')
... | the_stack_v2_python_sparse | src/chat_take_aiohttp/web/chat_handlers.py | Tsvetov/chat_take_aiohttp | train | 0 |
f258f0dd77fa1a80fae83317c33d2a91b673b9cb | [
"self.dic = collections.defaultdict(set)\nfor s in dictionary:\n key = s\n if len(s) > 2:\n key = s[0] + str(len(s) - 2) + s[-1]\n self.dic[key].add(s)",
"key = word\nif len(key) > 2:\n key = word[0] + str(len(word) - 2) + word[-1]\nreturn len(self.dic[key]) == 0 or (len(self.dic[key]) == 1 and... | <|body_start_0|>
self.dic = collections.defaultdict(set)
for s in dictionary:
key = s
if len(s) > 2:
key = s[0] + str(len(s) - 2) + s[-1]
self.dic[key].add(s)
<|end_body_0|>
<|body_start_1|>
key = word
if len(key) > 2:
key ... | ValidWordAbbr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
"""initialize your data structure here. :type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
"""check if a word is unique. :type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_10k_train_005962 | 864 | no_license | [
{
"docstring": "initialize your data structure here. :type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": "check if a word is unique. :type word: str :rtype: bool",
"name": "isUnique",
"signature": "def isUnique(self, word)"
... | 2 | stack_v2_sparse_classes_30k_train_007341 | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): initialize your data structure here. :type dictionary: List[str]
- def isUnique(self, word): check if a word is unique. :type word: str ... | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): initialize your data structure here. :type dictionary: List[str]
- def isUnique(self, word): check if a word is unique. :type word: str ... | 024c1b5c98a9e85706e110fc2be8dcebf0f460c3 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
"""initialize your data structure here. :type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
"""check if a word is unique. :type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
def __init__(self, dictionary):
"""initialize your data structure here. :type dictionary: List[str]"""
self.dic = collections.defaultdict(set)
for s in dictionary:
key = s
if len(s) > 2:
key = s[0] + str(len(s) - 2) + s[-1]
... | the_stack_v2_python_sparse | 288.UniqueWordAbbreviation.py | yao9208/lc | train | 0 | |
4978fb5a079afb2dd6b06393d85195e21b6e5159 | [
"app_id_list = get_cc_app_id_by_user()\nstart = self.request.query_params.get('start_time', None)\nstop = self.request.query_params.get('stop_time', None)\nif start and stop:\n return TaskRecord.objects.filter(app_id__in=app_id_list).filter(create_time__range=[start, stop]).order_by('-create_time')\nreturn TaskR... | <|body_start_0|>
app_id_list = get_cc_app_id_by_user()
start = self.request.query_params.get('start_time', None)
stop = self.request.query_params.get('stop_time', None)
if start and stop:
return TaskRecord.objects.filter(app_id__in=app_id_list).filter(create_time__range=[star... | 执行记录RDF视图类，用户可根据集群名称，任务创建时间过滤执行记录数据 | TaskRecordViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskRecordViewSet:
"""执行记录RDF视图类，用户可根据集群名称，任务创建时间过滤执行记录数据"""
def get_queryset(self):
"""重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离"""
<|body_0|>
def get_task_sum_group_by_db(self, request, *args, **kwargs):
"""输出各db组件的的执行记录数"""
<|body_1|>
def get_task(se... | stack_v2_sparse_classes_10k_train_005963 | 4,384 | no_license | [
{
"docstring": "重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "输出各db组件的的执行记录数",
"name": "get_task_sum_group_by_db",
"signature": "def get_task_sum_group_by_db(self, request, *args, **kwargs)"
},
{
"docstri... | 4 | stack_v2_sparse_classes_30k_train_004709 | Implement the Python class `TaskRecordViewSet` described below.
Class description:
执行记录RDF视图类，用户可根据集群名称，任务创建时间过滤执行记录数据
Method signatures and docstrings:
- def get_queryset(self): 重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离
- def get_task_sum_group_by_db(self, request, *args, **kwargs): 输出各db组件的的执行记录数
- def get_task(self, ... | Implement the Python class `TaskRecordViewSet` described below.
Class description:
执行记录RDF视图类，用户可根据集群名称，任务创建时间过滤执行记录数据
Method signatures and docstrings:
- def get_queryset(self): 重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离
- def get_task_sum_group_by_db(self, request, *args, **kwargs): 输出各db组件的的执行记录数
- def get_task(self, ... | 97cfac2ba94d67980d837f0b541caae70b68a595 | <|skeleton|>
class TaskRecordViewSet:
"""执行记录RDF视图类，用户可根据集群名称，任务创建时间过滤执行记录数据"""
def get_queryset(self):
"""重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离"""
<|body_0|>
def get_task_sum_group_by_db(self, request, *args, **kwargs):
"""输出各db组件的的执行记录数"""
<|body_1|>
def get_task(se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TaskRecordViewSet:
"""执行记录RDF视图类，用户可根据集群名称，任务创建时间过滤执行记录数据"""
def get_queryset(self):
"""重写get_queryset方法，根据用户的业务权限来输出对应记录，用户隔离"""
app_id_list = get_cc_app_id_by_user()
start = self.request.query_params.get('start_time', None)
stop = self.request.query_params.get('stop_time... | the_stack_v2_python_sparse | apps/globalview/views.py | sdgdsffdsfff/bk-dop | train | 0 |
e12f36c4fdfe164205d9e207fee538cae27ef937 | [
"self.command_output = ''\nself.browsers = []\nself.data = ''\nself.current_path = os.getcwd()",
"ret_data = {'List of Installed Browsers': []}\nself.command_output = os.popen(\"apropos 'web browser'\").read()\nself.browsers = self.command_output.split('\\n')\nself.browsers.pop()\nself.browsers = [i[:i.find('(') ... | <|body_start_0|>
self.command_output = ''
self.browsers = []
self.data = ''
self.current_path = os.getcwd()
<|end_body_0|>
<|body_start_1|>
ret_data = {'List of Installed Browsers': []}
self.command_output = os.popen("apropos 'web browser'").read()
self.browsers ... | ********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED VARIABLES WHICH IS GOING TO BE USED LATE... | get_browsers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class get_browsers:
"""********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED ... | stack_v2_sparse_classes_10k_train_005964 | 2,883 | permissive | [
{
"docstring": "__init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED VARIABLES WHICH IS GOING TO BE USED LATER BY OTHER MEMBER FUNCTION.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "WORK() DOCFILE: THE FUNCTION WORKS IN FOLLOWI... | 2 | stack_v2_sparse_classes_30k_train_003309 | Implement the Python class `get_browsers` described below.
Class description:
********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZ... | Implement the Python class `get_browsers` described below.
Class description:
********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZ... | 256149b6f22828ac668a68e8cac17f86925ccd5c | <|skeleton|>
class get_browsers:
"""********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class get_browsers:
"""********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED VARIABLES WHI... | the_stack_v2_python_sparse | lib/linux/get_browsers.py | chavarera/Cinfo | train | 9 |
7dd716d0ff7099f1188f3fcf9610367c7c3ac02a | [
"self.Wz = np.random.normal(size=(i + h, h))\nself.Wr = np.random.normal(size=(i + h, h))\nself.Wh = np.random.normal(size=(i + h, h))\nself.Wy = np.random.normal(size=(h, o))\nself.bz = np.zeros((1, h))\nself.br = np.zeros((1, h))\nself.bh = np.zeros((1, h))\nself.by = np.zeros((1, o))",
"U = np.hstack((h_prev, ... | <|body_start_0|>
self.Wz = np.random.normal(size=(i + h, h))
self.Wr = np.random.normal(size=(i + h, h))
self.Wh = np.random.normal(size=(i + h, h))
self.Wy = np.random.normal(size=(h, o))
self.bz = np.zeros((1, h))
self.br = np.zeros((1, h))
self.bh = np.zeros((1... | GRU cell class | GRUCell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GRUCell:
"""GRU cell class"""
def __init__(self, i, h, o):
"""Constructor"""
<|body_0|>
def forward(self, h_prev, x_t):
"""Method that performs forward propagation for one time step"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.Wz = np.ra... | stack_v2_sparse_classes_10k_train_005965 | 1,172 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, i, h, o)"
},
{
"docstring": "Method that performs forward propagation for one time step",
"name": "forward",
"signature": "def forward(self, h_prev, x_t)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003725 | Implement the Python class `GRUCell` described below.
Class description:
GRU cell class
Method signatures and docstrings:
- def __init__(self, i, h, o): Constructor
- def forward(self, h_prev, x_t): Method that performs forward propagation for one time step | Implement the Python class `GRUCell` described below.
Class description:
GRU cell class
Method signatures and docstrings:
- def __init__(self, i, h, o): Constructor
- def forward(self, h_prev, x_t): Method that performs forward propagation for one time step
<|skeleton|>
class GRUCell:
"""GRU cell class"""
d... | 131be8fcf61aafb5a4ddc0b3853ba625560eb786 | <|skeleton|>
class GRUCell:
"""GRU cell class"""
def __init__(self, i, h, o):
"""Constructor"""
<|body_0|>
def forward(self, h_prev, x_t):
"""Method that performs forward propagation for one time step"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GRUCell:
"""GRU cell class"""
def __init__(self, i, h, o):
"""Constructor"""
self.Wz = np.random.normal(size=(i + h, h))
self.Wr = np.random.normal(size=(i + h, h))
self.Wh = np.random.normal(size=(i + h, h))
self.Wy = np.random.normal(size=(h, o))
self.bz ... | the_stack_v2_python_sparse | supervised_learning/0x0D-RNNs/2-gru_cell.py | zahraaassaad/holbertonschool-machine_learning | train | 1 |
11880cd44aa1d64196dce6fb7dd065e124fb4ef3 | [
"if i == n:\n result.append(list(map(''.join, board)))\n return\nfor j in range(n):\n if j not in cols and j - i not in left_diags and (n - 1 - j - i not in right_diags):\n cols.add(j)\n left_diags.add(j - i)\n right_diags.add(n - 1 - j - i)\n board[i][j] = 'Q'\n self.fin... | <|body_start_0|>
if i == n:
result.append(list(map(''.join, board)))
return
for j in range(n):
if j not in cols and j - i not in left_diags and (n - 1 - j - i not in right_diags):
cols.add(j)
left_diags.add(j - i)
right_... | Short and optimized version of the above algorithm. | SolutionShort | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SolutionShort:
"""Short and optimized version of the above algorithm."""
def find_places(self, board, n, i, result, cols, left_diags, right_diags):
"""Finds all possible board n x n board combinations with n queens on it. Backtracking recursive algorithm."""
<|body_0|>
d... | stack_v2_sparse_classes_10k_train_005966 | 5,871 | no_license | [
{
"docstring": "Finds all possible board n x n board combinations with n queens on it. Backtracking recursive algorithm.",
"name": "find_places",
"signature": "def find_places(self, board, n, i, result, cols, left_diags, right_diags)"
},
{
"docstring": "Returns a list of boards, where each board... | 2 | stack_v2_sparse_classes_30k_train_007322 | Implement the Python class `SolutionShort` described below.
Class description:
Short and optimized version of the above algorithm.
Method signatures and docstrings:
- def find_places(self, board, n, i, result, cols, left_diags, right_diags): Finds all possible board n x n board combinations with n queens on it. Backt... | Implement the Python class `SolutionShort` described below.
Class description:
Short and optimized version of the above algorithm.
Method signatures and docstrings:
- def find_places(self, board, n, i, result, cols, left_diags, right_diags): Finds all possible board n x n board combinations with n queens on it. Backt... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class SolutionShort:
"""Short and optimized version of the above algorithm."""
def find_places(self, board, n, i, result, cols, left_diags, right_diags):
"""Finds all possible board n x n board combinations with n queens on it. Backtracking recursive algorithm."""
<|body_0|>
d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SolutionShort:
"""Short and optimized version of the above algorithm."""
def find_places(self, board, n, i, result, cols, left_diags, right_diags):
"""Finds all possible board n x n board combinations with n queens on it. Backtracking recursive algorithm."""
if i == n:
result.... | the_stack_v2_python_sparse | Backtracking/n_queens.py | vladn90/Algorithms | train | 0 |
a2c38667236635c3e06674c183b0a89060446ce8 | [
"if n <= 0:\n return False\nn = math.log2(n)\nif n == int(n):\n return True\nreturn False",
"if n <= 0:\n return False\nreturn not n & n - 1"
] | <|body_start_0|>
if n <= 0:
return False
n = math.log2(n)
if n == int(n):
return True
return False
<|end_body_0|>
<|body_start_1|>
if n <= 0:
return False
return not n & n - 1
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPowerOfTwo1(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isPowerOfTwo(self, n):
""":type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n <= 0:
return False
n = math.log2(n)
... | stack_v2_sparse_classes_10k_train_005967 | 560 | no_license | [
{
"docstring": ":type n: int :rtype: bool",
"name": "isPowerOfTwo1",
"signature": "def isPowerOfTwo1(self, n)"
},
{
"docstring": ":type n: int :rtype: bool",
"name": "isPowerOfTwo",
"signature": "def isPowerOfTwo(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfTwo1(self, n): :type n: int :rtype: bool
- def isPowerOfTwo(self, n): :type n: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfTwo1(self, n): :type n: int :rtype: bool
- def isPowerOfTwo(self, n): :type n: int :rtype: bool
<|skeleton|>
class Solution:
def isPowerOfTwo1(self, n):
... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def isPowerOfTwo1(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isPowerOfTwo(self, n):
""":type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isPowerOfTwo1(self, n):
""":type n: int :rtype: bool"""
if n <= 0:
return False
n = math.log2(n)
if n == int(n):
return True
return False
def isPowerOfTwo(self, n):
""":type n: int :rtype: bool"""
if n <= 0:
... | the_stack_v2_python_sparse | python/leetcode/231_Power_of_Two.py | bobcaoge/my-code | train | 0 | |
deebaff45b12c9ca011e660f33feb8bfd5b7bb35 | [
"develop.initialize_options(self)\nself.no_npm = None\nself.with_doc_deps = None\nself.use_npm_cache = None",
"if self.no_deps:\n develop.install_for_development(self)\n return\nself._run_pip(['install', '-e', '.'])\nself._run_pip(['install', '-r', 'dev-requirements.txt'])\nif self.with_doc_deps:\n self.... | <|body_start_0|>
develop.initialize_options(self)
self.no_npm = None
self.with_doc_deps = None
self.use_npm_cache = None
<|end_body_0|>
<|body_start_1|>
if self.no_deps:
develop.install_for_development(self)
return
self._run_pip(['install', '-e', ... | Installs Review Board in developer mode. This will install all standard and development dependencies (using Python wheels and node.js packages from npm) and add the source tree to the Python module search path. That includes updating the versions of pip and setuptools on the system. To speed up subsequent runs, callers... | DevelopCommand | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DevelopCommand:
"""Installs Review Board in developer mode. This will install all standard and development dependencies (using Python wheels and node.js packages from npm) and add the source tree to the Python module search path. That includes updating the versions of pip and setuptools on the sy... | stack_v2_sparse_classes_10k_train_005968 | 14,185 | permissive | [
{
"docstring": "Initialize options for the command.",
"name": "initialize_options",
"signature": "def initialize_options(self)"
},
{
"docstring": "Install the package for development. This takes care of the work of installing all dependencies.",
"name": "install_for_development",
"signat... | 3 | null | Implement the Python class `DevelopCommand` described below.
Class description:
Installs Review Board in developer mode. This will install all standard and development dependencies (using Python wheels and node.js packages from npm) and add the source tree to the Python module search path. That includes updating the v... | Implement the Python class `DevelopCommand` described below.
Class description:
Installs Review Board in developer mode. This will install all standard and development dependencies (using Python wheels and node.js packages from npm) and add the source tree to the Python module search path. That includes updating the v... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class DevelopCommand:
"""Installs Review Board in developer mode. This will install all standard and development dependencies (using Python wheels and node.js packages from npm) and add the source tree to the Python module search path. That includes updating the versions of pip and setuptools on the sy... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DevelopCommand:
"""Installs Review Board in developer mode. This will install all standard and development dependencies (using Python wheels and node.js packages from npm) and add the source tree to the Python module search path. That includes updating the versions of pip and setuptools on the system. To spee... | the_stack_v2_python_sparse | setup.py | reviewboard/reviewboard | train | 1,141 |
2238757765430213ab6e26b875d4e1ef3d185747 | [
"if data is empty:\n return True\nreturn not any(json.loads(data).values())",
"if self.is_empty_i18n_data(data) and self.required:\n self.fail('required')\nreturn super().validate_empty_values(data)"
] | <|body_start_0|>
if data is empty:
return True
return not any(json.loads(data).values())
<|end_body_0|>
<|body_start_1|>
if self.is_empty_i18n_data(data) and self.required:
self.fail('required')
return super().validate_empty_values(data)
<|end_body_1|>
| I18nCharField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class I18nCharField:
def is_empty_i18n_data(data):
"""check for values in each language empty value example: {"en":""}"""
<|body_0|>
def validate_empty_values(self, data):
"""Empty i18n fields have the following format: {"en":""}, we have to decode json and check empty str... | stack_v2_sparse_classes_10k_train_005969 | 759 | no_license | [
{
"docstring": "check for values in each language empty value example: {\"en\":\"\"}",
"name": "is_empty_i18n_data",
"signature": "def is_empty_i18n_data(data)"
},
{
"docstring": "Empty i18n fields have the following format: {\"en\":\"\"}, we have to decode json and check empty strings for langu... | 2 | stack_v2_sparse_classes_30k_train_002265 | Implement the Python class `I18nCharField` described below.
Class description:
Implement the I18nCharField class.
Method signatures and docstrings:
- def is_empty_i18n_data(data): check for values in each language empty value example: {"en":""}
- def validate_empty_values(self, data): Empty i18n fields have the follo... | Implement the Python class `I18nCharField` described below.
Class description:
Implement the I18nCharField class.
Method signatures and docstrings:
- def is_empty_i18n_data(data): check for values in each language empty value example: {"en":""}
- def validate_empty_values(self, data): Empty i18n fields have the follo... | 338fd6396dbdce971bc542718fbb9608bdcfc2a7 | <|skeleton|>
class I18nCharField:
def is_empty_i18n_data(data):
"""check for values in each language empty value example: {"en":""}"""
<|body_0|>
def validate_empty_values(self, data):
"""Empty i18n fields have the following format: {"en":""}, we have to decode json and check empty str... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class I18nCharField:
def is_empty_i18n_data(data):
"""check for values in each language empty value example: {"en":""}"""
if data is empty:
return True
return not any(json.loads(data).values())
def validate_empty_values(self, data):
"""Empty i18n fields have the foll... | the_stack_v2_python_sparse | api/custom_fields.py | sai9912/mypyton | train | 0 | |
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_10k_train_005970 | 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_002846 | 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_10k | 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 | |
7be8667b460c88fb3cc502f3a9583e0b0f872255 | [
"prefixs = collections.defaultdict(list)\nfor word in words:\n prefixs[word[0]].append(iter(word[1:]))\nfor c in S:\n for it in prefixs.pop(c, ()):\n prefixs[next(it, None)].append(it)\nreturn len(prefixs[None])",
"def match(word):\n i, j = (len(S) - 1, len(word) - 1)\n while i >= 0 and j >= 0:... | <|body_start_0|>
prefixs = collections.defaultdict(list)
for word in words:
prefixs[word[0]].append(iter(word[1:]))
for c in S:
for it in prefixs.pop(c, ()):
prefixs[next(it, None)].append(it)
return len(prefixs[None])
<|end_body_0|>
<|body_start_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numMatchingSubseq(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
<|body_0|>
def numMatchingSubseq_TLE(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_005971 | 2,891 | no_license | [
{
"docstring": ":type S: str :type words: List[str] :rtype: int",
"name": "numMatchingSubseq",
"signature": "def numMatchingSubseq(self, S, words)"
},
{
"docstring": ":type S: str :type words: List[str] :rtype: int",
"name": "numMatchingSubseq_TLE",
"signature": "def numMatchingSubseq_TL... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numMatchingSubseq(self, S, words): :type S: str :type words: List[str] :rtype: int
- def numMatchingSubseq_TLE(self, S, words): :type S: str :type words: List[str] :rtype: in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numMatchingSubseq(self, S, words): :type S: str :type words: List[str] :rtype: int
- def numMatchingSubseq_TLE(self, S, words): :type S: str :type words: List[str] :rtype: in... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def numMatchingSubseq(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
<|body_0|>
def numMatchingSubseq_TLE(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def numMatchingSubseq(self, S, words):
""":type S: str :type words: List[str] :rtype: int"""
prefixs = collections.defaultdict(list)
for word in words:
prefixs[word[0]].append(iter(word[1:]))
for c in S:
for it in prefixs.pop(c, ()):
... | the_stack_v2_python_sparse | src/lt_792.py | oxhead/CodingYourWay | train | 0 | |
7bc1783af65e3191d92d49d03a6a53ff5acd504c | [
"super().__init__()\nself.dense_h_h4 = nn.Linear(n_hidden, n_hidden * 4)\nself.activation = nn.GELU()\nself.dense_h4_h = nn.Linear(n_hidden * 4, n_hidden)",
"x = self.dense_h_h4(x)\nx = self.activation(x)\nx = self.dense_h4_h(x)\nreturn x"
] | <|body_start_0|>
super().__init__()
self.dense_h_h4 = nn.Linear(n_hidden, n_hidden * 4)
self.activation = nn.GELU()
self.dense_h4_h = nn.Linear(n_hidden * 4, n_hidden)
<|end_body_0|>
<|body_start_1|>
x = self.dense_h_h4(x)
x = self.activation(x)
x = self.dense_h4... | ## Feedforward Network | FFNLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FFNLayer:
"""## Feedforward Network"""
def __init__(self, n_hidden: int=6144):
""":param n_hidden: is the embedding size"""
<|body_0|>
def forward(self, x: torch.Tensor):
""":param x: has shape `[batch_size, seq_len, n_hidden]`"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k_train_005972 | 13,522 | no_license | [
{
"docstring": ":param n_hidden: is the embedding size",
"name": "__init__",
"signature": "def __init__(self, n_hidden: int=6144)"
},
{
"docstring": ":param x: has shape `[batch_size, seq_len, n_hidden]`",
"name": "forward",
"signature": "def forward(self, x: torch.Tensor)"
}
] | 2 | null | Implement the Python class `FFNLayer` described below.
Class description:
## Feedforward Network
Method signatures and docstrings:
- def __init__(self, n_hidden: int=6144): :param n_hidden: is the embedding size
- def forward(self, x: torch.Tensor): :param x: has shape `[batch_size, seq_len, n_hidden]` | Implement the Python class `FFNLayer` described below.
Class description:
## Feedforward Network
Method signatures and docstrings:
- def __init__(self, n_hidden: int=6144): :param n_hidden: is the embedding size
- def forward(self, x: torch.Tensor): :param x: has shape `[batch_size, seq_len, n_hidden]`
<|skeleton|>
... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class FFNLayer:
"""## Feedforward Network"""
def __init__(self, n_hidden: int=6144):
""":param n_hidden: is the embedding size"""
<|body_0|>
def forward(self, x: torch.Tensor):
""":param x: has shape `[batch_size, seq_len, n_hidden]`"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FFNLayer:
"""## Feedforward Network"""
def __init__(self, n_hidden: int=6144):
""":param n_hidden: is the embedding size"""
super().__init__()
self.dense_h_h4 = nn.Linear(n_hidden, n_hidden * 4)
self.activation = nn.GELU()
self.dense_h4_h = nn.Linear(n_hidden * 4, ... | the_stack_v2_python_sparse | generated/test_labmlai_neox.py | jansel/pytorch-jit-paritybench | train | 35 |
360d109e764ead839b15e772f7f034d271543b6c | [
"serializer = self.get_serializer(data=self.clean_data(request.data))\nserializer.is_valid(raise_exception=True)\nself.perform_create(serializer)\nheaders = self.get_success_headers(serializer.data)\nreturn Response(serializer.data, status=status.HTTP_201_CREATED, headers=headers)",
"partial = kwargs.pop('partial... | <|body_start_0|>
serializer = self.get_serializer(data=self.clean_data(request.data))
serializer.is_valid(raise_exception=True)
self.perform_create(serializer)
headers = self.get_success_headers(serializer.data)
return Response(serializer.data, status=status.HTTP_201_CREATED, hea... | Model mixin class which cleans inputs using the Mozilla bleach tools. | CleanMixin | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CleanMixin:
"""Model mixin class which cleans inputs using the Mozilla bleach tools."""
def create(self, request, *args, **kwargs):
"""Override to clean data before processing it."""
<|body_0|>
def update(self, request, *args, **kwargs):
"""Override to clean data... | stack_v2_sparse_classes_10k_train_005973 | 6,138 | permissive | [
{
"docstring": "Override to clean data before processing it.",
"name": "create",
"signature": "def create(self, request, *args, **kwargs)"
},
{
"docstring": "Override to clean data before processing it.",
"name": "update",
"signature": "def update(self, request, *args, **kwargs)"
},
... | 4 | null | Implement the Python class `CleanMixin` described below.
Class description:
Model mixin class which cleans inputs using the Mozilla bleach tools.
Method signatures and docstrings:
- def create(self, request, *args, **kwargs): Override to clean data before processing it.
- def update(self, request, *args, **kwargs): O... | Implement the Python class `CleanMixin` described below.
Class description:
Model mixin class which cleans inputs using the Mozilla bleach tools.
Method signatures and docstrings:
- def create(self, request, *args, **kwargs): Override to clean data before processing it.
- def update(self, request, *args, **kwargs): O... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class CleanMixin:
"""Model mixin class which cleans inputs using the Mozilla bleach tools."""
def create(self, request, *args, **kwargs):
"""Override to clean data before processing it."""
<|body_0|>
def update(self, request, *args, **kwargs):
"""Override to clean data... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CleanMixin:
"""Model mixin class which cleans inputs using the Mozilla bleach tools."""
def create(self, request, *args, **kwargs):
"""Override to clean data before processing it."""
serializer = self.get_serializer(data=self.clean_data(request.data))
serializer.is_valid(raise_exc... | the_stack_v2_python_sparse | InvenTree/InvenTree/mixins.py | inventree/InvenTree | train | 3,077 |
c5afd837def6a6ec93ab77a5746a49b3d3ffd86d | [
"assert padding in ['SAME', 'VALID', 'REFLECT'], 'Error: unsupported padding'\nself._padding = padding\nwith tf.variable_scope(name):\n if isinstance(stride, int):\n stride = [1, stride, stride, 1]\n else:\n assert len(stride) == 0, 'stride is either an int or a 2-tuple'\n stride = [1, st... | <|body_start_0|>
assert padding in ['SAME', 'VALID', 'REFLECT'], 'Error: unsupported padding'
self._padding = padding
with tf.variable_scope(name):
if isinstance(stride, int):
stride = [1, stride, stride, 1]
else:
assert len(stride) == 0, '... | Convolution layer with support for equalized learning. | LayerConv | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerConv:
"""Convolution layer with support for equalized learning."""
def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. w: int o... | stack_v2_sparse_classes_10k_train_005974 | 13,442 | permissive | [
{
"docstring": "Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. w: int or 2-tuple, width of the convolution kernel. n: 2-tuple of ints, input and output channel depths. padding: string, the padding method. {SAME, VALID, REFLECT}. use_scaling: bool, w... | 2 | stack_v2_sparse_classes_30k_train_005948 | Implement the Python class `LayerConv` described below.
Class description:
Convolution layer with support for equalized learning.
Method signatures and docstrings:
- def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0): Layer constructor. Args: name: string, layer name. stride: in... | Implement the Python class `LayerConv` described below.
Class description:
Convolution layer with support for equalized learning.
Method signatures and docstrings:
- def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0): Layer constructor. Args: name: string, layer name. stride: in... | 091d6ae9e087cf5a6e18b00bce7d8f7ede9d9d08 | <|skeleton|>
class LayerConv:
"""Convolution layer with support for equalized learning."""
def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. w: int o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LayerConv:
"""Convolution layer with support for equalized learning."""
def __init__(self, name, w, n, stride, padding='SAME', use_scaling=False, relu_slope=1.0):
"""Layer constructor. Args: name: string, layer name. stride: int or 2-tuple, stride for the convolution kernel. w: int or 2-tuple, wi... | the_stack_v2_python_sparse | layers.py | MoustafaMeshry/StEP | train | 6 |
c7f289f030458cc4a3f694f93b361fc691f606ff | [
"tofAxis = timeHistogram.axisFromName('tof')\ntofVector = tofAxis.storage()\nenergyAxis = energyHistogram.axisFromName('energy')\nenergyVector = energyAxis.storage()\nself._calcor(pixelDist, tofVector, energyVector)\nreturn",
"from reduction.vectorCompat.EBinCalcor import EBinCalcor\nself._calcor = EBinCalcor(dat... | <|body_start_0|>
tofAxis = timeHistogram.axisFromName('tof')
tofVector = tofAxis.storage()
energyAxis = energyHistogram.axisFromName('energy')
energyVector = energyAxis.storage()
self._calcor(pixelDist, tofVector, energyVector)
return
<|end_body_0|>
<|body_start_1|>
... | energy bin calculator calculate energy bins out of tof bins | EBinCalcor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EBinCalcor:
"""energy bin calculator calculate energy bins out of tof bins"""
def __call__(self, pixelDist, timeHistogram, energyHistogram):
"""ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin boundaries for histogram with energy axis given pixel dist... | stack_v2_sparse_classes_10k_train_005975 | 2,138 | no_license | [
{
"docstring": "ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin boundaries for histogram with energy axis given pixel distance and histogram with tof axis. inputs: pixelDist: distance from sample to pixel (float) timeHistogram (instance of Histogram with axis \"tof\") energyHis... | 2 | null | Implement the Python class `EBinCalcor` described below.
Class description:
energy bin calculator calculate energy bins out of tof bins
Method signatures and docstrings:
- def __call__(self, pixelDist, timeHistogram, energyHistogram): ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin b... | Implement the Python class `EBinCalcor` described below.
Class description:
energy bin calculator calculate energy bins out of tof bins
Method signatures and docstrings:
- def __call__(self, pixelDist, timeHistogram, energyHistogram): ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin b... | 7ba4ce07a5a4645942192b4b81f7afcae505db90 | <|skeleton|>
class EBinCalcor:
"""energy bin calculator calculate energy bins out of tof bins"""
def __call__(self, pixelDist, timeHistogram, energyHistogram):
"""ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin boundaries for histogram with energy axis given pixel dist... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EBinCalcor:
"""energy bin calculator calculate energy bins out of tof bins"""
def __call__(self, pixelDist, timeHistogram, energyHistogram):
"""ebincalcor( pixelDist, tBinBoundsVec, eBinBoundsVec) -> None Calculate energy bin boundaries for histogram with energy axis given pixel distance and hist... | the_stack_v2_python_sparse | histogrammode/reduction/histCompat/EBinCalcor.py | danse-inelastic/DrChops | train | 0 |
59ed44b3400534bd42e93de074e2aed52fbf383a | [
"self.cluster_info = cluster_info\nself.collection_info = collection_info\nself.database_info = database_info\nself.name = name\nself.mtype = mtype\nself.uuid = uuid",
"if dictionary is None:\n return None\ncluster_info = cohesity_management_sdk.models.mongo_db_cluster.MongoDBCluster.from_dictionary(dictionary... | <|body_start_0|>
self.cluster_info = cluster_info
self.collection_info = collection_info
self.database_info = database_info
self.name = name
self.mtype = mtype
self.uuid = uuid
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
... | Implementation of the 'MongoDBProtectionSource' model. Specifies an Object representing MongoDB. Attributes: cluster_info (MongoDBCluster): Information of a mongodb cluster, only valid for an entity of type kCluster. collection_info (MongoDBCollection): Information about a mongodb collection, only valid for an entity o... | MongoDBProtectionSource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MongoDBProtectionSource:
"""Implementation of the 'MongoDBProtectionSource' model. Specifies an Object representing MongoDB. Attributes: cluster_info (MongoDBCluster): Information of a mongodb cluster, only valid for an entity of type kCluster. collection_info (MongoDBCollection): Information abo... | stack_v2_sparse_classes_10k_train_005976 | 3,661 | permissive | [
{
"docstring": "Constructor for the MongoDBProtectionSource class",
"name": "__init__",
"signature": "def __init__(self, cluster_info=None, collection_info=None, database_info=None, name=None, mtype=None, uuid=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: di... | 2 | null | Implement the Python class `MongoDBProtectionSource` described below.
Class description:
Implementation of the 'MongoDBProtectionSource' model. Specifies an Object representing MongoDB. Attributes: cluster_info (MongoDBCluster): Information of a mongodb cluster, only valid for an entity of type kCluster. collection_in... | Implement the Python class `MongoDBProtectionSource` described below.
Class description:
Implementation of the 'MongoDBProtectionSource' model. Specifies an Object representing MongoDB. Attributes: cluster_info (MongoDBCluster): Information of a mongodb cluster, only valid for an entity of type kCluster. collection_in... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class MongoDBProtectionSource:
"""Implementation of the 'MongoDBProtectionSource' model. Specifies an Object representing MongoDB. Attributes: cluster_info (MongoDBCluster): Information of a mongodb cluster, only valid for an entity of type kCluster. collection_info (MongoDBCollection): Information abo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MongoDBProtectionSource:
"""Implementation of the 'MongoDBProtectionSource' model. Specifies an Object representing MongoDB. Attributes: cluster_info (MongoDBCluster): Information of a mongodb cluster, only valid for an entity of type kCluster. collection_info (MongoDBCollection): Information about a mongodb ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/mongo_db_protection_source.py | cohesity/management-sdk-python | train | 24 |
93cc5b0bea185453dfe6b0eb4d22455884e07111 | [
"my_employee = Employee('justin', 'williams', 80000)\nmy_employee.format_name_salary()\nself.assertEqual(my_employee.format_name_salary(), 'Justin Williams 80000')",
"my_employee = Employee('justin', 'williams', 80000)\nmy_employee.give_raise()\nself.assertEqual(my_employee.salary, 85000)",
"my_employee = Emplo... | <|body_start_0|>
my_employee = Employee('justin', 'williams', 80000)
my_employee.format_name_salary()
self.assertEqual(my_employee.format_name_salary(), 'Justin Williams 80000')
<|end_body_0|>
<|body_start_1|>
my_employee = Employee('justin', 'williams', 80000)
my_employee.give_... | Tests for the class Employee | TestEmployee | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestEmployee:
"""Tests for the class Employee"""
def test_format_name_salary(self):
"""Tests if name and salary are formatted corrctly"""
<|body_0|>
def test_give_default_raise(self):
"""Tests if default raise works"""
<|body_1|>
def test_give_custom... | stack_v2_sparse_classes_10k_train_005977 | 1,428 | no_license | [
{
"docstring": "Tests if name and salary are formatted corrctly",
"name": "test_format_name_salary",
"signature": "def test_format_name_salary(self)"
},
{
"docstring": "Tests if default raise works",
"name": "test_give_default_raise",
"signature": "def test_give_default_raise(self)"
},... | 3 | stack_v2_sparse_classes_30k_train_000738 | Implement the Python class `TestEmployee` described below.
Class description:
Tests for the class Employee
Method signatures and docstrings:
- def test_format_name_salary(self): Tests if name and salary are formatted corrctly
- def test_give_default_raise(self): Tests if default raise works
- def test_give_custom_rai... | Implement the Python class `TestEmployee` described below.
Class description:
Tests for the class Employee
Method signatures and docstrings:
- def test_format_name_salary(self): Tests if name and salary are formatted corrctly
- def test_give_default_raise(self): Tests if default raise works
- def test_give_custom_rai... | 77ecd59829324807279bb0abd06f55c322dbf328 | <|skeleton|>
class TestEmployee:
"""Tests for the class Employee"""
def test_format_name_salary(self):
"""Tests if name and salary are formatted corrctly"""
<|body_0|>
def test_give_default_raise(self):
"""Tests if default raise works"""
<|body_1|>
def test_give_custom... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestEmployee:
"""Tests for the class Employee"""
def test_format_name_salary(self):
"""Tests if name and salary are formatted corrctly"""
my_employee = Employee('justin', 'williams', 80000)
my_employee.format_name_salary()
self.assertEqual(my_employee.format_name_salary(),... | the_stack_v2_python_sparse | chp11/test_employee.py | justinm0rgan/python_work | train | 0 |
287e0a912440098489d420c807f79bae48e26798 | [
"lHead, lTail, rHead, rTail = (None, None, None, None)\nwhile head:\n if head.val < x:\n if lHead == None:\n lHead = head\n lTail = head\n else:\n lTail.next = head\n lTail = lTail.next\n elif rHead == None:\n rHead = head\n rTail = head\... | <|body_start_0|>
lHead, lTail, rHead, rTail = (None, None, None, None)
while head:
if head.val < x:
if lHead == None:
lHead = head
lTail = head
else:
lTail.next = head
lTail = lTai... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def partition(self, head, x):
""":type head: ListNode :type x: int :rtype: ListNode"""
<|body_0|>
def partition2(self, head, x):
""":type head: ListNode :type x: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
lHead, l... | stack_v2_sparse_classes_10k_train_005978 | 1,836 | no_license | [
{
"docstring": ":type head: ListNode :type x: int :rtype: ListNode",
"name": "partition",
"signature": "def partition(self, head, x)"
},
{
"docstring": ":type head: ListNode :type x: int :rtype: ListNode",
"name": "partition2",
"signature": "def partition2(self, head, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000562 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def partition(self, head, x): :type head: ListNode :type x: int :rtype: ListNode
- def partition2(self, head, x): :type head: ListNode :type x: int :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def partition(self, head, x): :type head: ListNode :type x: int :rtype: ListNode
- def partition2(self, head, x): :type head: ListNode :type x: int :rtype: ListNode
<|skeleton|>... | ab49373ff3fc306a03a90de02e1801b8cbe520d7 | <|skeleton|>
class Solution:
def partition(self, head, x):
""":type head: ListNode :type x: int :rtype: ListNode"""
<|body_0|>
def partition2(self, head, x):
""":type head: ListNode :type x: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def partition(self, head, x):
""":type head: ListNode :type x: int :rtype: ListNode"""
lHead, lTail, rHead, rTail = (None, None, None, None)
while head:
if head.val < x:
if lHead == None:
lHead = head
lTail =... | the_stack_v2_python_sparse | explore/list/086.py | yiguid/LeetCodePractise | train | 0 | |
956f9e60f465d4f1a98167191b3b818c37ad776d | [
"super().__init__(*args, **kwargs)\nif ext_args == {}:\n self._freq = 1\nelse:\n self._freq = ext_args.freq",
"if engine.rank != 0:\n for k in engine.log_buffer:\n engine.log_buffer[k].clear()\n return\nfor k, v in engine.log_buffer['scalar'].items():\n setattr(engine.monitor, k, v)\nengine.... | <|body_start_0|>
super().__init__(*args, **kwargs)
if ext_args == {}:
self._freq = 1
else:
self._freq = ext_args.freq
<|end_body_0|>
<|body_start_1|>
if engine.rank != 0:
for k in engine.log_buffer:
engine.log_buffer[k].clear()
... | Overview: Hook to show log Interfaces: __init__, __call__ Property: name, priority, position | LogShowHook | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogShowHook:
"""Overview: Hook to show log Interfaces: __init__, __call__ Property: name, priority, position"""
def __init__(self, *args, ext_args: EasyDict=EasyDict(), **kwargs) -> None:
"""Overview: init LogShowHook Arguments: - ext_args (:obj:`EasyDict`): extended_args, use ext_ar... | stack_v2_sparse_classes_10k_train_005979 | 15,244 | permissive | [
{
"docstring": "Overview: init LogShowHook Arguments: - ext_args (:obj:`EasyDict`): extended_args, use ext_args.freq to set freq",
"name": "__init__",
"signature": "def __init__(self, *args, ext_args: EasyDict=EasyDict(), **kwargs) -> None"
},
{
"docstring": "Overview: Show log, update record an... | 2 | null | Implement the Python class `LogShowHook` described below.
Class description:
Overview: Hook to show log Interfaces: __init__, __call__ Property: name, priority, position
Method signatures and docstrings:
- def __init__(self, *args, ext_args: EasyDict=EasyDict(), **kwargs) -> None: Overview: init LogShowHook Arguments... | Implement the Python class `LogShowHook` described below.
Class description:
Overview: Hook to show log Interfaces: __init__, __call__ Property: name, priority, position
Method signatures and docstrings:
- def __init__(self, *args, ext_args: EasyDict=EasyDict(), **kwargs) -> None: Overview: init LogShowHook Arguments... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class LogShowHook:
"""Overview: Hook to show log Interfaces: __init__, __call__ Property: name, priority, position"""
def __init__(self, *args, ext_args: EasyDict=EasyDict(), **kwargs) -> None:
"""Overview: init LogShowHook Arguments: - ext_args (:obj:`EasyDict`): extended_args, use ext_ar... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LogShowHook:
"""Overview: Hook to show log Interfaces: __init__, __call__ Property: name, priority, position"""
def __init__(self, *args, ext_args: EasyDict=EasyDict(), **kwargs) -> None:
"""Overview: init LogShowHook Arguments: - ext_args (:obj:`EasyDict`): extended_args, use ext_args.freq to se... | the_stack_v2_python_sparse | ding/worker/learner/learner_hook.py | shengxuesun/DI-engine | train | 1 |
a393bf71ef60f5cec5577944e7b7debde696ad99 | [
"try:\n params = request._serialize()\n headers = request.headers\n body = self.call('CancelTask', params, headers=headers)\n response = json.loads(body)\n model = models.CancelTaskResponse()\n model._deserialize(response['Response'])\n return model\nexcept Exception as e:\n if isinstance(e,... | <|body_start_0|>
try:
params = request._serialize()
headers = request.headers
body = self.call('CancelTask', params, headers=headers)
response = json.loads(body)
model = models.CancelTaskResponse()
model._deserialize(response['Response'])
... | VmClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VmClient:
def CancelTask(self, request):
"""可使用该接口取消审核任务，成功取消后，该接口返回已取消任务的TaskId。<br> 默认接口请求频率限制：**20次/秒**。 :param request: Request instance for CancelTask. :type request: :class:`tencentcloud.vm.v20201229.models.CancelTaskRequest` :rtype: :class:`tencentcloud.vm.v20201229.models.CancelT... | stack_v2_sparse_classes_10k_train_005980 | 9,114 | permissive | [
{
"docstring": "可使用该接口取消审核任务，成功取消后，该接口返回已取消任务的TaskId。<br> 默认接口请求频率限制：**20次/秒**。 :param request: Request instance for CancelTask. :type request: :class:`tencentcloud.vm.v20201229.models.CancelTaskRequest` :rtype: :class:`tencentcloud.vm.v20201229.models.CancelTaskResponse`",
"name": "CancelTask",
"signat... | 4 | null | Implement the Python class `VmClient` described below.
Class description:
Implement the VmClient class.
Method signatures and docstrings:
- def CancelTask(self, request): 可使用该接口取消审核任务，成功取消后，该接口返回已取消任务的TaskId。<br> 默认接口请求频率限制：**20次/秒**。 :param request: Request instance for CancelTask. :type request: :class:`tencentclou... | Implement the Python class `VmClient` described below.
Class description:
Implement the VmClient class.
Method signatures and docstrings:
- def CancelTask(self, request): 可使用该接口取消审核任务，成功取消后，该接口返回已取消任务的TaskId。<br> 默认接口请求频率限制：**20次/秒**。 :param request: Request instance for CancelTask. :type request: :class:`tencentclou... | 6baf00a5a56ba58b6a1123423e0a1422d17a0201 | <|skeleton|>
class VmClient:
def CancelTask(self, request):
"""可使用该接口取消审核任务，成功取消后，该接口返回已取消任务的TaskId。<br> 默认接口请求频率限制：**20次/秒**。 :param request: Request instance for CancelTask. :type request: :class:`tencentcloud.vm.v20201229.models.CancelTaskRequest` :rtype: :class:`tencentcloud.vm.v20201229.models.CancelT... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VmClient:
def CancelTask(self, request):
"""可使用该接口取消审核任务，成功取消后，该接口返回已取消任务的TaskId。<br> 默认接口请求频率限制：**20次/秒**。 :param request: Request instance for CancelTask. :type request: :class:`tencentcloud.vm.v20201229.models.CancelTaskRequest` :rtype: :class:`tencentcloud.vm.v20201229.models.CancelTaskResponse`""... | the_stack_v2_python_sparse | tencentcloud/vm/v20201229/vm_client.py | TencentCloud/tencentcloud-sdk-python | train | 594 | |
0ec9cdf1b298f5e9f5fb1e95d35e7630cc30a3c1 | [
"super().__init__(input_size=input_size, hidden_size=hidden_size, bias=bias)\nassert 0 <= dropout <= 1, 'Dropout rate must be in the range [0, 1]'\nassert 0 <= recurrent_dropout <= 1, 'Dropout rate must be in the range [0, 1]'\nself._dropout = dropout\nself._recurrent_dropout = recurrent_dropout",
"if hx is None:... | <|body_start_0|>
super().__init__(input_size=input_size, hidden_size=hidden_size, bias=bias)
assert 0 <= dropout <= 1, 'Dropout rate must be in the range [0, 1]'
assert 0 <= recurrent_dropout <= 1, 'Dropout rate must be in the range [0, 1]'
self._dropout = dropout
self._recurrent... | A wrapper around torch.nn.GRUCell that adds dropout to inputs and hidden. This wrapper makes the implementation more in-line with that of tf.keras.layers.GRUCell It doesn't accomplish it entirely, because: 1) the base GRU cell is different (the ordering of when the reset gate is applied is different between torch and t... | DropoutGRUCell | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DropoutGRUCell:
"""A wrapper around torch.nn.GRUCell that adds dropout to inputs and hidden. This wrapper makes the implementation more in-line with that of tf.keras.layers.GRUCell It doesn't accomplish it entirely, because: 1) the base GRU cell is different (the ordering of when the reset gate i... | stack_v2_sparse_classes_10k_train_005981 | 20,187 | permissive | [
{
"docstring": "Args: input_size: Dimensionality of the input to the GRUCell hidden_size: Dimensionality of the hidden dimension of the GRUCell bias (optional): If False, then the layer does not use bias weights b_ih and b_hh. Defaults to True. dropout (optional): Fraction of the units to drop for the linear tr... | 2 | stack_v2_sparse_classes_30k_train_004241 | Implement the Python class `DropoutGRUCell` described below.
Class description:
A wrapper around torch.nn.GRUCell that adds dropout to inputs and hidden. This wrapper makes the implementation more in-line with that of tf.keras.layers.GRUCell It doesn't accomplish it entirely, because: 1) the base GRU cell is different... | Implement the Python class `DropoutGRUCell` described below.
Class description:
A wrapper around torch.nn.GRUCell that adds dropout to inputs and hidden. This wrapper makes the implementation more in-line with that of tf.keras.layers.GRUCell It doesn't accomplish it entirely, because: 1) the base GRU cell is different... | 8fa75e67c0db8f632b135379740051cd10ff31f2 | <|skeleton|>
class DropoutGRUCell:
"""A wrapper around torch.nn.GRUCell that adds dropout to inputs and hidden. This wrapper makes the implementation more in-line with that of tf.keras.layers.GRUCell It doesn't accomplish it entirely, because: 1) the base GRU cell is different (the ordering of when the reset gate i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DropoutGRUCell:
"""A wrapper around torch.nn.GRUCell that adds dropout to inputs and hidden. This wrapper makes the implementation more in-line with that of tf.keras.layers.GRUCell It doesn't accomplish it entirely, because: 1) the base GRU cell is different (the ordering of when the reset gate is applied is ... | the_stack_v2_python_sparse | rlo/src/rlo/model/layers.py | tomjaguarpaw/knossos-ksc | train | 0 |
9dff19832ffc2e73d7da91c593a43dbae11123fd | [
"super(LSTMAttention, self).__init__()\nself.input_size = input_size\nself.hidden_size = hidden_size\nself.batch_first = batch_first\nself.lstm_cell = nn.LSTMCell(input_size, hidden_size)\nif attn_type == 'soft':\n self.attention_layer = SoftDotAttention(hidden_size)\nelif attn_type == 'mlp':\n self.attention... | <|body_start_0|>
super(LSTMAttention, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.batch_first = batch_first
self.lstm_cell = nn.LSTMCell(input_size, hidden_size)
if attn_type == 'soft':
self.attention_layer = SoftDotAttent... | A long short-term memory (LSTM) cell with attention. | LSTMAttention | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTMAttention:
"""A long short-term memory (LSTM) cell with attention."""
def __init__(self, input_size, hidden_size, batch_first=True, attn_type='soft'):
"""Initialize params."""
<|body_0|>
def forward(self, input, hidden, ctx, ctx_mask=None, return_logattn=False):
... | stack_v2_sparse_classes_10k_train_005982 | 8,483 | permissive | [
{
"docstring": "Initialize params.",
"name": "__init__",
"signature": "def __init__(self, input_size, hidden_size, batch_first=True, attn_type='soft')"
},
{
"docstring": "Propagate input through the network.",
"name": "forward",
"signature": "def forward(self, input, hidden, ctx, ctx_mas... | 2 | stack_v2_sparse_classes_30k_train_007308 | Implement the Python class `LSTMAttention` described below.
Class description:
A long short-term memory (LSTM) cell with attention.
Method signatures and docstrings:
- def __init__(self, input_size, hidden_size, batch_first=True, attn_type='soft'): Initialize params.
- def forward(self, input, hidden, ctx, ctx_mask=N... | Implement the Python class `LSTMAttention` described below.
Class description:
A long short-term memory (LSTM) cell with attention.
Method signatures and docstrings:
- def __init__(self, input_size, hidden_size, batch_first=True, attn_type='soft'): Initialize params.
- def forward(self, input, hidden, ctx, ctx_mask=N... | c530c9af647d521262b56b717bcc38b0cfc5f1b8 | <|skeleton|>
class LSTMAttention:
"""A long short-term memory (LSTM) cell with attention."""
def __init__(self, input_size, hidden_size, batch_first=True, attn_type='soft'):
"""Initialize params."""
<|body_0|>
def forward(self, input, hidden, ctx, ctx_mask=None, return_logattn=False):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LSTMAttention:
"""A long short-term memory (LSTM) cell with attention."""
def __init__(self, input_size, hidden_size, batch_first=True, attn_type='soft'):
"""Initialize params."""
super(LSTMAttention, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_... | the_stack_v2_python_sparse | stanza/models/common/seq2seq_modules.py | stanfordnlp/stanza | train | 4,281 |
863ec30c381cea0e13045bab89b662271773de83 | [
"self._text_maze = text_maze\nself._wall_char = wall_char\nself._make_odd_sized_walls = make_odd_sized_walls\nself._covered = np.full(text_maze.shape, False, dtype=np.bool)\nself._maze_size = GridCoordinates(*text_maze.shape)\nself._next_start = GridCoordinates(0, 0)\nself._calculated = False\nself._walls = ()",
... | <|body_start_0|>
self._text_maze = text_maze
self._wall_char = wall_char
self._make_odd_sized_walls = make_odd_sized_walls
self._covered = np.full(text_maze.shape, False, dtype=np.bool)
self._maze_size = GridCoordinates(*text_maze.shape)
self._next_start = GridCoordinates... | Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, but in most cases should result in a significantly smaller number of geoms than if each cell ... | _MazeWallCoveringContext | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _MazeWallCoveringContext:
"""Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, but in most cases should result in a sign... | stack_v2_sparse_classes_10k_train_005983 | 5,466 | permissive | [
{
"docstring": "Initializes this _MazeWallCoveringContext. Args: text_maze: A `labmaze.TextGrid` instance. wall_char: (optional) The character that signifies a wall. make_odd_sized_walls: (optional) A boolean, if `True` all wall sections generated span odd numbers of grid cells. This option exists primarily to ... | 5 | stack_v2_sparse_classes_30k_train_004801 | Implement the Python class `_MazeWallCoveringContext` described below.
Class description:
Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, bu... | Implement the Python class `_MazeWallCoveringContext` described below.
Class description:
Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, bu... | 33d3ea2682409ee82bf9c5129ceaf06ab01cd48e | <|skeleton|>
class _MazeWallCoveringContext:
"""Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, but in most cases should result in a sign... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class _MazeWallCoveringContext:
"""Calculates a covering of text mazes with overlapping rectangular walls. This class uses a greedy algorithm to try and minimize the number of geoms generated to create a given maze. The solution is not guaranteed to be optimal, but in most cases should result in a significantly sma... | the_stack_v2_python_sparse | src/env/dm_control/dm_control/locomotion/arenas/covering.py | nicklashansen/svea-vit | train | 16 |
6a9a6ac588b3fbdf635e50e4e09503872308054c | [
"tokens = self.input.split(' ', 2)\nif not self.bot.callsign in tokens[0].lower():\n return False\ntry:\n command = tokens[1].lower()\nexcept IndexError:\n return False\nif not command:\n return False\ntry:\n argument = tokens[2]\nexcept IndexError:\n argument = ''\ntry:\n f = getattr(self, 'cm... | <|body_start_0|>
tokens = self.input.split(' ', 2)
if not self.bot.callsign in tokens[0].lower():
return False
try:
command = tokens[1].lower()
except IndexError:
return False
if not command:
return False
try:
ar... | Base class to process IRC events containing commands to the bot. Events that get handled is in the formats: `bot_name command [argument]` for channel messages, `command [argument]` for private ones. Read on BaseContext's .send() for how you should send back text. Usage: ------ You shouldn't need to override any of the ... | BaseCommandContext | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseCommandContext:
"""Base class to process IRC events containing commands to the bot. Events that get handled is in the formats: `bot_name command [argument]` for channel messages, `command [argument]` for private ones. Read on BaseContext's .send() for how you should send back text. Usage: ---... | stack_v2_sparse_classes_10k_train_005984 | 8,615 | permissive | [
{
"docstring": "Dispatch a public event to a cmd__public or cmd_ method",
"name": "do_public",
"signature": "def do_public(self)"
},
{
"docstring": "Dispatch a private event to a cmd__private or cmd_ method",
"name": "do_private",
"signature": "def do_private(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006858 | Implement the Python class `BaseCommandContext` described below.
Class description:
Base class to process IRC events containing commands to the bot. Events that get handled is in the formats: `bot_name command [argument]` for channel messages, `command [argument]` for private ones. Read on BaseContext's .send() for ho... | Implement the Python class `BaseCommandContext` described below.
Class description:
Base class to process IRC events containing commands to the bot. Events that get handled is in the formats: `bot_name command [argument]` for channel messages, `command [argument]` for private ones. Read on BaseContext's .send() for ho... | 61d97a7255300ddc0b3067cd2da43e059d48600e | <|skeleton|>
class BaseCommandContext:
"""Base class to process IRC events containing commands to the bot. Events that get handled is in the formats: `bot_name command [argument]` for channel messages, `command [argument]` for private ones. Read on BaseContext's .send() for how you should send back text. Usage: ---... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseCommandContext:
"""Base class to process IRC events containing commands to the bot. Events that get handled is in the formats: `bot_name command [argument]` for channel messages, `command [argument]` for private ones. Read on BaseContext's .send() for how you should send back text. Usage: ------ You shoul... | the_stack_v2_python_sparse | src/modules/basemodule.py | nickraptis/fidibot | train | 0 |
a7b8fd4e6774328310b57477e1679f2c9ad9b88c | [
"indices = [1, 2, 3]\nK = 2\nresult = k_folds(indices, K)\nexpected = [[2, 3], [1], [3], [1, 2]]\nself.assertEqual(result, expected)",
"indices = [1, 2, 3, 4, 5]\nK = 3\nresult = k_folds(indices, K)\nexpected = [[1, 2], [3, 4, 5], [3, 4], [1, 2, 5], [5], [1, 2, 3, 4]]\nself.assertEqual(result, expected)"
] | <|body_start_0|>
indices = [1, 2, 3]
K = 2
result = k_folds(indices, K)
expected = [[2, 3], [1], [3], [1, 2]]
self.assertEqual(result, expected)
<|end_body_0|>
<|body_start_1|>
indices = [1, 2, 3, 4, 5]
K = 3
result = k_folds(indices, K)
expected ... | Test cases that helped validating the solution. | TestSolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSolution:
"""Test cases that helped validating the solution."""
def test_solution_k_2(self):
"""Simple test case K = 2."""
<|body_0|>
def test_solution_k_3(self):
"""Simple test case K = 3."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ind... | stack_v2_sparse_classes_10k_train_005985 | 1,472 | no_license | [
{
"docstring": "Simple test case K = 2.",
"name": "test_solution_k_2",
"signature": "def test_solution_k_2(self)"
},
{
"docstring": "Simple test case K = 3.",
"name": "test_solution_k_3",
"signature": "def test_solution_k_3(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003237 | Implement the Python class `TestSolution` described below.
Class description:
Test cases that helped validating the solution.
Method signatures and docstrings:
- def test_solution_k_2(self): Simple test case K = 2.
- def test_solution_k_3(self): Simple test case K = 3. | Implement the Python class `TestSolution` described below.
Class description:
Test cases that helped validating the solution.
Method signatures and docstrings:
- def test_solution_k_2(self): Simple test case K = 2.
- def test_solution_k_3(self): Simple test case K = 3.
<|skeleton|>
class TestSolution:
"""Test ca... | 712508a79f9620b7b9ab75ef51000efbad387e18 | <|skeleton|>
class TestSolution:
"""Test cases that helped validating the solution."""
def test_solution_k_2(self):
"""Simple test case K = 2."""
<|body_0|>
def test_solution_k_3(self):
"""Simple test case K = 3."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestSolution:
"""Test cases that helped validating the solution."""
def test_solution_k_2(self):
"""Simple test case K = 2."""
indices = [1, 2, 3]
K = 2
result = k_folds(indices, K)
expected = [[2, 3], [1], [3], [1, 2]]
self.assertEqual(result, expected)
... | the_stack_v2_python_sparse | code-questions/kfolds.py | fberanizo/mle-interview | train | 1 |
e3040cef11a8a41dc73c20b319768b85ac1f5024 | [
"for v in variables:\n if v.systematics_funcs == 'suffix':\n v.fillSystematicsSuffix(systematics)\nself.variables_dict = OrderedDict([(v.name, v) for v in variables])",
"ret = OrderedDict()\nfor vname, v in self.variables_dict.items():\n if schema in v.schema:\n ret[vname] = v.getValue(event, ... | <|body_start_0|>
for v in variables:
if v.systematics_funcs == 'suffix':
v.fillSystematicsSuffix(systematics)
self.variables_dict = OrderedDict([(v.name, v) for v in variables])
<|end_body_0|>
<|body_start_1|>
ret = OrderedDict()
for vname, v in self.variable... | Event description with varying systematics Attributes: variables_dict (dict of string->Var): Variables in the event | Desc | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Desc:
"""Event description with varying systematics Attributes: variables_dict (dict of string->Var): Variables in the event"""
def __init__(self, systematics, variables=[]):
"""Creates the event description based on a list of variables Args: systematics (list of string): systematics... | stack_v2_sparse_classes_10k_train_005986 | 34,880 | no_license | [
{
"docstring": "Creates the event description based on a list of variables Args: systematics (list of string): systematics to use for variable lookup variables (list, optional): Variables to use",
"name": "__init__",
"signature": "def __init__(self, systematics, variables=[])"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_train_005485 | Implement the Python class `Desc` described below.
Class description:
Event description with varying systematics Attributes: variables_dict (dict of string->Var): Variables in the event
Method signatures and docstrings:
- def __init__(self, systematics, variables=[]): Creates the event description based on a list of ... | Implement the Python class `Desc` described below.
Class description:
Event description with varying systematics Attributes: variables_dict (dict of string->Var): Variables in the event
Method signatures and docstrings:
- def __init__(self, systematics, variables=[]): Creates the event description based on a list of ... | d33786f405792cafee22658b40d04f59e37f799b | <|skeleton|>
class Desc:
"""Event description with varying systematics Attributes: variables_dict (dict of string->Var): Variables in the event"""
def __init__(self, systematics, variables=[]):
"""Creates the event description based on a list of variables Args: systematics (list of string): systematics... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Desc:
"""Event description with varying systematics Attributes: variables_dict (dict of string->Var): Variables in the event"""
def __init__(self, systematics, variables=[]):
"""Creates the event description based on a list of variables Args: systematics (list of string): systematics to use for v... | the_stack_v2_python_sparse | Plotting/python/joosep/sparsinator.py | jpata/tthbb13 | train | 2 |
20666abb1b47f877da668f4cc41ae5db09b00e04 | [
"a, b = (q, p)\nwhile not (a & 1 or b & 1):\n a >>= 1\n b >>= 1\nif not a & 1:\n return 0\nelif b & 1:\n return 1\nelse:\n return 2",
"g = gcd(p, q)\na, b = (q // g, p // g)\nif not a & 1:\n return 0\nelif b & 1:\n return 1\nelse:\n return 2"
] | <|body_start_0|>
a, b = (q, p)
while not (a & 1 or b & 1):
a >>= 1
b >>= 1
if not a & 1:
return 0
elif b & 1:
return 1
else:
return 2
<|end_body_0|>
<|body_start_1|>
g = gcd(p, q)
a, b = (q // g, p // g)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mirrorReflection(self, p: int, q: int) -> int:
"""Extend the original box to mutiple boxes in order to simulate the reflections as follows (p = 3, q = 2): See pics/mirror_reflection.png. So in the end the ray will meet the point where ap == bq. The easiest match is to set a... | stack_v2_sparse_classes_10k_train_005987 | 1,515 | no_license | [
{
"docstring": "Extend the original box to mutiple boxes in order to simulate the reflections as follows (p = 3, q = 2): See pics/mirror_reflection.png. So in the end the ray will meet the point where ap == bq. The easiest match is to set a = q and b = p to match the above equation. Now consider the following c... | 2 | stack_v2_sparse_classes_30k_train_002892 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mirrorReflection(self, p: int, q: int) -> int: Extend the original box to mutiple boxes in order to simulate the reflections as follows (p = 3, q = 2): See pics/mirror_reflec... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mirrorReflection(self, p: int, q: int) -> int: Extend the original box to mutiple boxes in order to simulate the reflections as follows (p = 3, q = 2): See pics/mirror_reflec... | edb870f83f0c4568cce0cacec04ee70cf6b545bf | <|skeleton|>
class Solution:
def mirrorReflection(self, p: int, q: int) -> int:
"""Extend the original box to mutiple boxes in order to simulate the reflections as follows (p = 3, q = 2): See pics/mirror_reflection.png. So in the end the ray will meet the point where ap == bq. The easiest match is to set a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def mirrorReflection(self, p: int, q: int) -> int:
"""Extend the original box to mutiple boxes in order to simulate the reflections as follows (p = 3, q = 2): See pics/mirror_reflection.png. So in the end the ray will meet the point where ap == bq. The easiest match is to set a = q and b = p... | the_stack_v2_python_sparse | 2020/mirror_reflection.py | eronekogin/leetcode | train | 0 | |
4e839ba3808743ba8c8785079521bbfa02a0e34f | [
"id = request.GET.get('id', None)\nif id is None:\n fields_of_study = FieldOfStudy.objects.all()\n serializer = FieldOfStudySerializer(fields_of_study, many=True)\n return JsonResponse({'fields_of_study': serializer.data}, safe=False)\nelse:\n field_of_study = get_object_or_404(FieldOfStudy, id=id)\n ... | <|body_start_0|>
id = request.GET.get('id', None)
if id is None:
fields_of_study = FieldOfStudy.objects.all()
serializer = FieldOfStudySerializer(fields_of_study, many=True)
return JsonResponse({'fields_of_study': serializer.data}, safe=False)
else:
... | 专业方向view | FieldsOfStudy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FieldsOfStudy:
"""专业方向view"""
def get(self, request):
"""查询专业方向"""
<|body_0|>
def put(self, request):
"""修改专业方向"""
<|body_1|>
def post(self, request):
"""增加专业方向"""
<|body_2|>
def delete(self, request):
"""删除专业方向"""
... | stack_v2_sparse_classes_10k_train_005988 | 15,061 | permissive | [
{
"docstring": "查询专业方向",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "修改专业方向",
"name": "put",
"signature": "def put(self, request)"
},
{
"docstring": "增加专业方向",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "删除专... | 4 | stack_v2_sparse_classes_30k_train_003272 | Implement the Python class `FieldsOfStudy` described below.
Class description:
专业方向view
Method signatures and docstrings:
- def get(self, request): 查询专业方向
- def put(self, request): 修改专业方向
- def post(self, request): 增加专业方向
- def delete(self, request): 删除专业方向 | Implement the Python class `FieldsOfStudy` described below.
Class description:
专业方向view
Method signatures and docstrings:
- def get(self, request): 查询专业方向
- def put(self, request): 修改专业方向
- def post(self, request): 增加专业方向
- def delete(self, request): 删除专业方向
<|skeleton|>
class FieldsOfStudy:
"""专业方向view"""
d... | 7aaa1be773718de1beb3ce0080edca7c4114b7ad | <|skeleton|>
class FieldsOfStudy:
"""专业方向view"""
def get(self, request):
"""查询专业方向"""
<|body_0|>
def put(self, request):
"""修改专业方向"""
<|body_1|>
def post(self, request):
"""增加专业方向"""
<|body_2|>
def delete(self, request):
"""删除专业方向"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FieldsOfStudy:
"""专业方向view"""
def get(self, request):
"""查询专业方向"""
id = request.GET.get('id', None)
if id is None:
fields_of_study = FieldOfStudy.objects.all()
serializer = FieldOfStudySerializer(fields_of_study, many=True)
return JsonResponse({... | the_stack_v2_python_sparse | plan/views.py | MIXISAMA/MIS-backend | train | 0 |
b1097aff807464567e7df884146279f2fe3384e7 | [
"print(self.id_card)\nparam = {'idcard': self.id_card, 'username': 'api' + self.id_card + '_1', 'nationality': '汉族', 'maritalstatus': 0, 'level': 1, 'contact1': '15212365478', 'residenceaddress': '5101090201', 'address': '测试详细地址', 'emergencycontact1name': '测试', 'emergencycontact1address': '测试地址', 'emergencycontact1... | <|body_start_0|>
print(self.id_card)
param = {'idcard': self.id_card, 'username': 'api' + self.id_card + '_1', 'nationality': '汉族', 'maritalstatus': 0, 'level': 1, 'contact1': '15212365478', 'residenceaddress': '5101090201', 'address': '测试详细地址', 'emergencycontact1name': '测试', 'emergencycontact1address':... | TestBusiness1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestBusiness1:
def test_001(self):
"""添加人员-级别为：普通老人"""
<|body_0|>
def test_002(self):
"""政府端：根据身份证号查询UID"""
<|body_1|>
def test_003(self):
"""积分充值"""
<|body_2|>
def test_004(self):
"""服务订单生成"""
<|body_3|>
<|end_skele... | stack_v2_sparse_classes_10k_train_005989 | 3,118 | no_license | [
{
"docstring": "添加人员-级别为：普通老人",
"name": "test_001",
"signature": "def test_001(self)"
},
{
"docstring": "政府端：根据身份证号查询UID",
"name": "test_002",
"signature": "def test_002(self)"
},
{
"docstring": "积分充值",
"name": "test_003",
"signature": "def test_003(self)"
},
{
"d... | 4 | stack_v2_sparse_classes_30k_train_002260 | Implement the Python class `TestBusiness1` described below.
Class description:
Implement the TestBusiness1 class.
Method signatures and docstrings:
- def test_001(self): 添加人员-级别为：普通老人
- def test_002(self): 政府端：根据身份证号查询UID
- def test_003(self): 积分充值
- def test_004(self): 服务订单生成 | Implement the Python class `TestBusiness1` described below.
Class description:
Implement the TestBusiness1 class.
Method signatures and docstrings:
- def test_001(self): 添加人员-级别为：普通老人
- def test_002(self): 政府端：根据身份证号查询UID
- def test_003(self): 积分充值
- def test_004(self): 服务订单生成
<|skeleton|>
class TestBusiness1:
... | 024bb8f0e8be7d19abfb14b405ef79bd85cc6b7b | <|skeleton|>
class TestBusiness1:
def test_001(self):
"""添加人员-级别为：普通老人"""
<|body_0|>
def test_002(self):
"""政府端：根据身份证号查询UID"""
<|body_1|>
def test_003(self):
"""积分充值"""
<|body_2|>
def test_004(self):
"""服务订单生成"""
<|body_3|>
<|end_skele... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestBusiness1:
def test_001(self):
"""添加人员-级别为：普通老人"""
print(self.id_card)
param = {'idcard': self.id_card, 'username': 'api' + self.id_card + '_1', 'nationality': '汉族', 'maritalstatus': 0, 'level': 1, 'contact1': '15212365478', 'residenceaddress': '5101090201', 'address': '测试详细地址', 'e... | the_stack_v2_python_sparse | test_case/test_business/test_business_1_flow.py | cjuan123/auto_api | train | 0 | |
f1b240251721a2af5c350b82e2f8c6b25198787b | [
"try:\n result = single_run(nnid, ver, node)\n return Response(json.dumps(result))\nexcept Exception as e:\n traceback.print_exc()\n return_data = {'status': '404', 'result': str(e)}\n return Response(json.dumps(return_data))",
"try:\n return_data = ''\n return Response(json.dumps(return_data... | <|body_start_0|>
try:
result = single_run(nnid, ver, node)
return Response(json.dumps(result))
except Exception as e:
traceback.print_exc()
return_data = {'status': '404', 'result': str(e)}
return Response(json.dumps(return_data))
<|end_body_0|... | RunManagerSingleRequest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunManagerSingleRequest:
def post(self, request, nnid, ver, node):
"""We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # Class Name : RunManagerSingleRequest # Description: request single node to be executed"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_005990 | 2,307 | permissive | [
{
"docstring": "We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # Class Name : RunManagerSingleRequest # Description: request single node to be executed",
"name": "post",
"signature": "def post(self, request, nnid, ver, node)"
},
{
"docstrin... | 3 | null | Implement the Python class `RunManagerSingleRequest` described below.
Class description:
Implement the RunManagerSingleRequest class.
Method signatures and docstrings:
- def post(self, request, nnid, ver, node): We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # C... | Implement the Python class `RunManagerSingleRequest` described below.
Class description:
Implement the RunManagerSingleRequest class.
Method signatures and docstrings:
- def post(self, request, nnid, ver, node): We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # C... | 6ad2fbc7384e4dbe7e3e63bdb44c8ce0387f4b7f | <|skeleton|>
class RunManagerSingleRequest:
def post(self, request, nnid, ver, node):
"""We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # Class Name : RunManagerSingleRequest # Description: request single node to be executed"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RunManagerSingleRequest:
def post(self, request, nnid, ver, node):
"""We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # Class Name : RunManagerSingleRequest # Description: request single node to be executed"""
try:
result = sin... | the_stack_v2_python_sparse | api/views/runmanager_single_request.py | yurimkoo/tensormsa | train | 1 | |
dc3d247bb1098d297aad529bf34ae5dfd0af6d33 | [
"new_prop = 'user_prop'\nnew_prop_value = rand_name('new_prop_value')\nimage = self.images_behavior.create_image_via_task()\nresponse = self.images_client.update_image(image.id_, add={new_prop: new_prop_value})\nself.assertEqual(response.status_code, 200)\nupdated_image = response.entity\nself.assertIn(new_prop, up... | <|body_start_0|>
new_prop = 'user_prop'
new_prop_value = rand_name('new_prop_value')
image = self.images_behavior.create_image_via_task()
response = self.images_client.update_image(image.id_, add={new_prop: new_prop_value})
self.assertEqual(response.status_code, 200)
upda... | TestUpdateImagePositive | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that ... | stack_v2_sparse_classes_10k_train_005991 | 6,204 | permissive | [
{
"docstring": "@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that the new property's value is correct",
"name": "test_update_image_add_additional_prope... | 4 | null | Implement the Python class `TestUpdateImagePositive` described below.
Class description:
Implement the TestUpdateImagePositive class.
Method signatures and docstrings:
- def test_update_image_add_additional_property(self): @summary: Update image add additional property 1) Create image 2) Update image adding a new pro... | Implement the Python class `TestUpdateImagePositive` described below.
Class description:
Implement the TestUpdateImagePositive class.
Method signatures and docstrings:
- def test_update_image_add_additional_property(self): @summary: Update image add additional property 1) Create image 2) Update image adding a new pro... | 30f0e64672676c3f90b4a582fe90fac6621475b3 | <|skeleton|>
class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that the new proper... | the_stack_v2_python_sparse | cloudroast/images/v2/functional/test_update_image_positive.py | RULCSoft/cloudroast | train | 1 | |
fad880e928937a6e4c537c2bf66e62120d904775 | [
"self.device_name = None\nself.device_type = None\nself.device_name_abbrev = None\nself.compatible = None\nself.device_address = None\nself.vendor = 'al'\nself.device_attributes = None\nself.attrWriteCommBytes = None\nself.attrWriteComm = None\nself.attributeWriteOffsets = None\nself.initComm = None\nself.initCommB... | <|body_start_0|>
self.device_name = None
self.device_type = None
self.device_name_abbrev = None
self.compatible = None
self.device_address = None
self.vendor = 'al'
self.device_attributes = None
self.attrWriteCommBytes = None
self.attrWriteComm = N... | The configuration for the driver being generated. | DriverConfig | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DriverConfig:
"""The configuration for the driver being generated."""
def __init__(self):
"""Initialize driver configuration."""
<|body_0|>
def parse_json(json_filepath):
"""Parse JSON file into driver configuration. Parameters ---------- json_filepath : str file... | stack_v2_sparse_classes_10k_train_005992 | 4,564 | permissive | [
{
"docstring": "Initialize driver configuration.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Parse JSON file into driver configuration. Parameters ---------- json_filepath : str file path to JSON configuration file Returns ------- DriverConfig Returns an instance o... | 2 | stack_v2_sparse_classes_30k_train_000002 | Implement the Python class `DriverConfig` described below.
Class description:
The configuration for the driver being generated.
Method signatures and docstrings:
- def __init__(self): Initialize driver configuration.
- def parse_json(json_filepath): Parse JSON file into driver configuration. Parameters ---------- jso... | Implement the Python class `DriverConfig` described below.
Class description:
The configuration for the driver being generated.
Method signatures and docstrings:
- def __init__(self): Initialize driver configuration.
- def parse_json(json_filepath): Parse JSON file into driver configuration. Parameters ---------- jso... | 090576504c721ea18d1cc09fadfe9873c0e1f96c | <|skeleton|>
class DriverConfig:
"""The configuration for the driver being generated."""
def __init__(self):
"""Initialize driver configuration."""
<|body_0|>
def parse_json(json_filepath):
"""Parse JSON file into driver configuration. Parameters ---------- json_filepath : str file... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DriverConfig:
"""The configuration for the driver being generated."""
def __init__(self):
"""Initialize driver configuration."""
self.device_name = None
self.device_type = None
self.device_name_abbrev = None
self.compatible = None
self.device_address = None... | the_stack_v2_python_sparse | device_drivers/driver_config.py | fpga-open-speech-tools/simulink_codegen | train | 2 |
4422acca830f4a9655593caba658adf316d3a8c7 | [
"image_file = StringIO.StringIO(temp_image.read())\nimage = Image.open(image_file)\nreturn image",
"try:\n for orientation in ExifTags.TAGS.keys():\n if ExifTags.TAGS[orientation] == 'Orientation':\n exif = dict(image._getexif().items())\n if exif[orientation] == 3:\n ... | <|body_start_0|>
image_file = StringIO.StringIO(temp_image.read())
image = Image.open(image_file)
return image
<|end_body_0|>
<|body_start_1|>
try:
for orientation in ExifTags.TAGS.keys():
if ExifTags.TAGS[orientation] == 'Orientation':
ex... | Assisting methods to help with file upload processes. | PhotoUpload | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhotoUpload:
"""Assisting methods to help with file upload processes."""
def open_image(temp_image):
"""Open a this image using StringIO."""
<|body_0|>
def check_image_orientation(image):
"""Digital photo devices attach EXIF data to an image when a photo is taken... | stack_v2_sparse_classes_10k_train_005993 | 3,690 | no_license | [
{
"docstring": "Open a this image using StringIO.",
"name": "open_image",
"signature": "def open_image(temp_image)"
},
{
"docstring": "Digital photo devices attach EXIF data to an image when a photo is taken. In order to display an image appropriately without it getting rotated, we need to check... | 6 | stack_v2_sparse_classes_30k_train_007012 | Implement the Python class `PhotoUpload` described below.
Class description:
Assisting methods to help with file upload processes.
Method signatures and docstrings:
- def open_image(temp_image): Open a this image using StringIO.
- def check_image_orientation(image): Digital photo devices attach EXIF data to an image ... | Implement the Python class `PhotoUpload` described below.
Class description:
Assisting methods to help with file upload processes.
Method signatures and docstrings:
- def open_image(temp_image): Open a this image using StringIO.
- def check_image_orientation(image): Digital photo devices attach EXIF data to an image ... | a780ccdc3350d4b5c7990c65d1af8d71060c62cc | <|skeleton|>
class PhotoUpload:
"""Assisting methods to help with file upload processes."""
def open_image(temp_image):
"""Open a this image using StringIO."""
<|body_0|>
def check_image_orientation(image):
"""Digital photo devices attach EXIF data to an image when a photo is taken... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PhotoUpload:
"""Assisting methods to help with file upload processes."""
def open_image(temp_image):
"""Open a this image using StringIO."""
image_file = StringIO.StringIO(temp_image.read())
image = Image.open(image_file)
return image
def check_image_orientation(image... | the_stack_v2_python_sparse | common/service/photo_upload.py | wcirillo/ten | train | 0 |
a0cbe4ae7b5fbbff15dfa0293319b376abaac5f1 | [
"N = prior.size\nself.lims = (-1, 1)\nself.pdf_ref, self.bins = np.histogram(prior, bins=N, range=self.lims)",
"if np.min(x) < self.lims[0]:\n tqdm.write('XHAT MIN WAS LOWER THAN X MIN: %g' % np.min(x))\nif np.max(x) > self.lims[1]:\n tqdm.write('XHAT MAX WAS HIGHER THAN X MAX: %g' % np.max(x))\nreturn np.h... | <|body_start_0|>
N = prior.size
self.lims = (-1, 1)
self.pdf_ref, self.bins = np.histogram(prior, bins=N, range=self.lims)
<|end_body_0|>
<|body_start_1|>
if np.min(x) < self.lims[0]:
tqdm.write('XHAT MIN WAS LOWER THAN X MIN: %g' % np.min(x))
if np.max(x) > self.lim... | Picklable object for computing pdfs. Uses histogram to estimate pdf. Attributes ---------- N : int Size of signal. lims : array_like or tuple Upper and lower bounds for range of histogram. pdf_ref : array_like pdf estimate of prior. Used to compare to pdf(xhat). bins : array_like bin locations used for construction of ... | pdf_default | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class pdf_default:
"""Picklable object for computing pdfs. Uses histogram to estimate pdf. Attributes ---------- N : int Size of signal. lims : array_like or tuple Upper and lower bounds for range of histogram. pdf_ref : array_like pdf estimate of prior. Used to compare to pdf(xhat). bins : array_like ... | stack_v2_sparse_classes_10k_train_005994 | 9,248 | no_license | [
{
"docstring": "Note that prior should be normalized between lims=(-1, 1).",
"name": "__init__",
"signature": "def __init__(self, prior)"
},
{
"docstring": "Estimate the pdf of x. Parameters ---------- x : array_like Signal to get pdf estimate of. Returns ------- array_like Histogram of x. Notes... | 2 | stack_v2_sparse_classes_30k_train_001959 | Implement the Python class `pdf_default` described below.
Class description:
Picklable object for computing pdfs. Uses histogram to estimate pdf. Attributes ---------- N : int Size of signal. lims : array_like or tuple Upper and lower bounds for range of histogram. pdf_ref : array_like pdf estimate of prior. Used to c... | Implement the Python class `pdf_default` described below.
Class description:
Picklable object for computing pdfs. Uses histogram to estimate pdf. Attributes ---------- N : int Size of signal. lims : array_like or tuple Upper and lower bounds for range of histogram. pdf_ref : array_like pdf estimate of prior. Used to c... | 08cb43dcf53fd6fddd3304e3514a608842310a34 | <|skeleton|>
class pdf_default:
"""Picklable object for computing pdfs. Uses histogram to estimate pdf. Attributes ---------- N : int Size of signal. lims : array_like or tuple Upper and lower bounds for range of histogram. pdf_ref : array_like pdf estimate of prior. Used to compare to pdf(xhat). bins : array_like ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class pdf_default:
"""Picklable object for computing pdfs. Uses histogram to estimate pdf. Attributes ---------- N : int Size of signal. lims : array_like or tuple Upper and lower bounds for range of histogram. pdf_ref : array_like pdf estimate of prior. Used to compare to pdf(xhat). bins : array_like bin locations... | the_stack_v2_python_sparse | mr_utils/cs/ordinator.py | zongjg/mr_utils | train | 0 |
f5ed6dd93b755b0389868391f22c184c9a552a79 | [
"val_s = Stack()\ncur_node = headnode\nwhile cur_node:\n val_s.push(cur_node.val)\n cur_node = cur_node.next\nwhile not val_s.empty():\n print(val_s.pop())",
"curnode = headnode\nif curnode:\n self.solve2(curnode.next)\n print(curnode.val)"
] | <|body_start_0|>
val_s = Stack()
cur_node = headnode
while cur_node:
val_s.push(cur_node.val)
cur_node = cur_node.next
while not val_s.empty():
print(val_s.pop())
<|end_body_0|>
<|body_start_1|>
curnode = headnode
if curnode:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def solve(self, headnode):
"""思路：用一个栈保存所有节点，之后一个一个 pop"""
<|body_0|>
def solve2(self, headnode):
"""能用栈就可以使用递归。这一点需要能联想到"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
val_s = Stack()
cur_node = headnode
while cur_node:
... | stack_v2_sparse_classes_10k_train_005995 | 1,362 | permissive | [
{
"docstring": "思路：用一个栈保存所有节点，之后一个一个 pop",
"name": "solve",
"signature": "def solve(self, headnode)"
},
{
"docstring": "能用栈就可以使用递归。这一点需要能联想到",
"name": "solve2",
"signature": "def solve2(self, headnode)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002946 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solve(self, headnode): 思路：用一个栈保存所有节点，之后一个一个 pop
- def solve2(self, headnode): 能用栈就可以使用递归。这一点需要能联想到 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def solve(self, headnode): 思路：用一个栈保存所有节点，之后一个一个 pop
- def solve2(self, headnode): 能用栈就可以使用递归。这一点需要能联想到
<|skeleton|>
class Solution:
def solve(self, headnode):
"""思路... | 3469a79c34b6c08ae52797c3974b49fbfa8cca51 | <|skeleton|>
class Solution:
def solve(self, headnode):
"""思路：用一个栈保存所有节点，之后一个一个 pop"""
<|body_0|>
def solve2(self, headnode):
"""能用栈就可以使用递归。这一点需要能联想到"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def solve(self, headnode):
"""思路：用一个栈保存所有节点，之后一个一个 pop"""
val_s = Stack()
cur_node = headnode
while cur_node:
val_s.push(cur_node.val)
cur_node = cur_node.next
while not val_s.empty():
print(val_s.pop())
def solve2(self... | the_stack_v2_python_sparse | 剑指offer/05_PrintListInReversedOrder(从尾到头打印链表).py | Mark24Code/python_data_structures_and_algorithms | train | 1 | |
00d29ece7956092f851a618109135ab23461c543 | [
"if not self.named_regexp:\n self.log.warning('Regular expression not provided for plugin. Run with `--help-all` flag for more information.')\n return None\nmatch = re.match(self.named_regexp, filename)\nif not match or not match.groups():\n self.log.warning(\"Regular expression '{}' did not match anything... | <|body_start_0|>
if not self.named_regexp:
self.log.warning('Regular expression not provided for plugin. Run with `--help-all` flag for more information.')
return None
match = re.match(self.named_regexp, filename)
if not match or not match.groups():
self.log.w... | Submission filename collector plugin for the :class:`~nbgrader.apps.zipcollectapp.ZipCollectApp`. Collect plugin subclasses MUST inherit from this class. | FileNameCollectorPlugin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileNameCollectorPlugin:
"""Submission filename collector plugin for the :class:`~nbgrader.apps.zipcollectapp.ZipCollectApp`. Collect plugin subclasses MUST inherit from this class."""
def _match(self, filename: str) -> Optional[dict]:
"""Match the named group regular expression to t... | stack_v2_sparse_classes_10k_train_005996 | 7,151 | permissive | [
{
"docstring": "Match the named group regular expression to the beginning of the filename and return the match groupdict or None if no match.",
"name": "_match",
"signature": "def _match(self, filename: str) -> Optional[dict]"
},
{
"docstring": "This is the main function called by the :class:`~n... | 2 | stack_v2_sparse_classes_30k_train_000295 | Implement the Python class `FileNameCollectorPlugin` described below.
Class description:
Submission filename collector plugin for the :class:`~nbgrader.apps.zipcollectapp.ZipCollectApp`. Collect plugin subclasses MUST inherit from this class.
Method signatures and docstrings:
- def _match(self, filename: str) -> Opti... | Implement the Python class `FileNameCollectorPlugin` described below.
Class description:
Submission filename collector plugin for the :class:`~nbgrader.apps.zipcollectapp.ZipCollectApp`. Collect plugin subclasses MUST inherit from this class.
Method signatures and docstrings:
- def _match(self, filename: str) -> Opti... | 6db380039dab377157620516ae49eafcf7537fc8 | <|skeleton|>
class FileNameCollectorPlugin:
"""Submission filename collector plugin for the :class:`~nbgrader.apps.zipcollectapp.ZipCollectApp`. Collect plugin subclasses MUST inherit from this class."""
def _match(self, filename: str) -> Optional[dict]:
"""Match the named group regular expression to t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FileNameCollectorPlugin:
"""Submission filename collector plugin for the :class:`~nbgrader.apps.zipcollectapp.ZipCollectApp`. Collect plugin subclasses MUST inherit from this class."""
def _match(self, filename: str) -> Optional[dict]:
"""Match the named group regular expression to the beginning ... | the_stack_v2_python_sparse | nbgrader/plugins/zipcollect.py | jupyter/nbgrader | train | 1,274 |
3d41406e71ebc01b4e5e9a129fc5d76fc4176518 | [
"self.k = k\nheapq.heapify(nums)\nself.heap = nums\nwhile len(self.heap) > k:\n heapq.heappop(self.heap)",
"if len(self.heap) < self.k:\n heapq.heappush(self.heap, val)\nelse:\n heapq.heappushpop(self.heap, val)\nreturn self.heap[0]"
] | <|body_start_0|>
self.k = k
heapq.heapify(nums)
self.heap = nums
while len(self.heap) > k:
heapq.heappop(self.heap)
<|end_body_0|>
<|body_start_1|>
if len(self.heap) < self.k:
heapq.heappush(self.heap, val)
else:
heapq.heappushpop(self... | KthLargest2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest2:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
heapq.heapify(nums)
self.heap ... | stack_v2_sparse_classes_10k_train_005997 | 2,963 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005521 | Implement the Python class `KthLargest2` described below.
Class description:
Implement the KthLargest2 class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest2` described below.
Class description:
Implement the KthLargest2 class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest2:
def __init__(self, k,... | 3e50f6a936b98ad75c47d7c1719e69163c648235 | <|skeleton|>
class KthLargest2:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class KthLargest2:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
heapq.heapify(nums)
self.heap = nums
while len(self.heap) > k:
heapq.heappop(self.heap)
def add(self, val):
""":type val: int :rtype: int"""
if... | the_stack_v2_python_sparse | LeetcodeNew/Heap/LC_703_Kth_Largest_Element_in_a_Stream.py | Taoge123/OptimizedLeetcode | train | 9 | |
e4872b61312de0115e7f6ed0ff00135a457dd4cc | [
"self.dynamic_network_pool_config = dynamic_network_pool_config\nself.groupnet = groupnet\nself.smb_credentials = smb_credentials\nself.static_network_pool_config = static_network_pool_config",
"if dictionary is None:\n return None\ndynamic_network_pool_config = cohesity_management_sdk.models.isilon_env_params... | <|body_start_0|>
self.dynamic_network_pool_config = dynamic_network_pool_config
self.groupnet = groupnet
self.smb_credentials = smb_credentials
self.static_network_pool_config = static_network_pool_config
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return ... | Implementation of the 'IsilonEnvParams_ZoneConfig' model. TODO: type description here. Attributes: dynamic_network_pool_config (IsilonEnvParams_ZoneConfig_NetworkPoolConfig): Dynamic network pool configuration for the access zone. Dynamic pool is used for stateless protocols, e.g. NFSv3. groupnet (string): Name of the ... | IsilonEnvParams_ZoneConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsilonEnvParams_ZoneConfig:
"""Implementation of the 'IsilonEnvParams_ZoneConfig' model. TODO: type description here. Attributes: dynamic_network_pool_config (IsilonEnvParams_ZoneConfig_NetworkPoolConfig): Dynamic network pool configuration for the access zone. Dynamic pool is used for stateless ... | stack_v2_sparse_classes_10k_train_005998 | 3,492 | permissive | [
{
"docstring": "Constructor for the IsilonEnvParams_ZoneConfig class",
"name": "__init__",
"signature": "def __init__(self, dynamic_network_pool_config=None, groupnet=None, smb_credentials=None, static_network_pool_config=None)"
},
{
"docstring": "Creates an instance of this model from a diction... | 2 | null | Implement the Python class `IsilonEnvParams_ZoneConfig` described below.
Class description:
Implementation of the 'IsilonEnvParams_ZoneConfig' model. TODO: type description here. Attributes: dynamic_network_pool_config (IsilonEnvParams_ZoneConfig_NetworkPoolConfig): Dynamic network pool configuration for the access zo... | Implement the Python class `IsilonEnvParams_ZoneConfig` described below.
Class description:
Implementation of the 'IsilonEnvParams_ZoneConfig' model. TODO: type description here. Attributes: dynamic_network_pool_config (IsilonEnvParams_ZoneConfig_NetworkPoolConfig): Dynamic network pool configuration for the access zo... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class IsilonEnvParams_ZoneConfig:
"""Implementation of the 'IsilonEnvParams_ZoneConfig' model. TODO: type description here. Attributes: dynamic_network_pool_config (IsilonEnvParams_ZoneConfig_NetworkPoolConfig): Dynamic network pool configuration for the access zone. Dynamic pool is used for stateless ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IsilonEnvParams_ZoneConfig:
"""Implementation of the 'IsilonEnvParams_ZoneConfig' model. TODO: type description here. Attributes: dynamic_network_pool_config (IsilonEnvParams_ZoneConfig_NetworkPoolConfig): Dynamic network pool configuration for the access zone. Dynamic pool is used for stateless protocols, e.... | the_stack_v2_python_sparse | cohesity_management_sdk/models/isilon_env_params_zone_config.py | cohesity/management-sdk-python | train | 24 |
9fa6f4fcc902ec6f654df3cbcfff050e01c1e997 | [
"client = test_client.TestClient(context.node['baseurl'])\npid = object_info.identifier.value()\nresponse = client.get(context.TOKEN, pid)\nchecksum_from_get = test_utilities.calculate_checksum_on_string(response, object_info.checksum.algorithm)\nassert object_info.checksum.value() == checksum_from_get\nresponse = ... | <|body_start_0|>
client = test_client.TestClient(context.node['baseurl'])
pid = object_info.identifier.value()
response = client.get(context.TOKEN, pid)
checksum_from_get = test_utilities.calculate_checksum_on_string(response, object_info.checksum.algorithm)
assert object_info.ch... | Test050Get | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test050Get:
def validate_object(self, object_info):
"""Get object and verify retrieved information against its ObjectInfo."""
<|body_0|>
def test_010_get_object_by_invalid_pid(self):
"""404 NotFound when attempting to get non-existing object."""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_005999 | 2,629 | permissive | [
{
"docstring": "Get object and verify retrieved information against its ObjectInfo.",
"name": "validate_object",
"signature": "def validate_object(self, object_info)"
},
{
"docstring": "404 NotFound when attempting to get non-existing object.",
"name": "test_010_get_object_by_invalid_pid",
... | 3 | null | Implement the Python class `Test050Get` described below.
Class description:
Implement the Test050Get class.
Method signatures and docstrings:
- def validate_object(self, object_info): Get object and verify retrieved information against its ObjectInfo.
- def test_010_get_object_by_invalid_pid(self): 404 NotFound when ... | Implement the Python class `Test050Get` described below.
Class description:
Implement the Test050Get class.
Method signatures and docstrings:
- def validate_object(self, object_info): Get object and verify retrieved information against its ObjectInfo.
- def test_010_get_object_by_invalid_pid(self): 404 NotFound when ... | d72a9461894d9be7d71178fb7310101b8ef9066a | <|skeleton|>
class Test050Get:
def validate_object(self, object_info):
"""Get object and verify retrieved information against its ObjectInfo."""
<|body_0|>
def test_010_get_object_by_invalid_pid(self):
"""404 NotFound when attempting to get non-existing object."""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test050Get:
def validate_object(self, object_info):
"""Get object and verify retrieved information against its ObjectInfo."""
client = test_client.TestClient(context.node['baseurl'])
pid = object_info.identifier.value()
response = client.get(context.TOKEN, pid)
checksum... | the_stack_v2_python_sparse | test_utilities/src/d1_test/stress_tester/projects/_unit_test_bases_for_stress_tests/tier_1_mn_read_get.py | DataONEorg/d1_python | train | 15 |
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